Clinical Data Acquisition Standards Harmonization
临床数据采集标准协调Implementation Guide for Human Clinical Trials
人类临床试验实施指南
Version 2.0 版本 2.0
Notes to Readers 读者须知
- This is Version 2.0 of the Clinical Data Acquisition Standards Harmonization Implementation Guide for Human Clinical Trials.
这是人类临床试验临床数据采集标准协调实施指南的 2.0 版。 - This document is intended to be paired with the CDASH Model.
本文件旨在与 CDASH 模型配合使用。
Revision History 修订历史
Date 日期 | Version 版本 |
---|---|
2017-09-20 | 2.0 Final 2.0 最终版 |
© 2017 Clinical Data Interchange Standards Consortium. All rights reserved. See also Representations and Warranties, Limitations of Liability, and Disclaimers.
© 2017 临床数据交换标准联盟。保留所有权利。另请参见陈述和保证、责任限制及免责声明。
Contents 内容
- 1 Orientation 方向指导
- 2 How to Use the CDASH Standard
如何使用 CDASH 标准 - 3 General Assumptions for Implementing CDASH
实施 CDASH 的一般假设- 3.1 How CDASH and SDTM Work Together
CDASH 和 SDTM 如何协同工作 - 3.2 Core Designations for Basic Data Collection Fields
基本数据收集字段的核心标识 - 3.3 Additional Information about CDASHIG Core Designations
关于 CDASHIG 核心设计 ations 的附加信息 - 3.4 How to Create New Data Collection Fields When No CDASHIG Field Has Been Defined
如何在未定义 CDASHIG 字段时创建新的数据收集字段 - 3.5 Explanation of Table Headers in the CDASH Model and CDASHIG Metadata Table
CDASH 模型和 CDASHIG 元数据表中表头的解释 - 3.6 Collection of Dates 日期集合
- 3.7 Mapping Relative Times from Collection to Submissions
从收集到提交的相对时间映射 - 3.8 CDISC Controlled Terminology
CDISC 控制术语
- 3.1 How CDASH and SDTM Work Together
- 4 Best Practice Recommendations
最佳实践建议 - 5 Conformance to the CDASH Standard
符合 CDASH 标准 - 6 Other Information 其他信息
- 7 CDASH Special-Purpose Domains
CDASH 特殊用途领域 - 8 General Observation Classes
一般观察班- 8.1 CDASH Interventions Domains
CDASH 干预领域 - 8.2 CDASH Events Domains CDASH 事件域
- 8.3 CDASH Findings Domains CDASH 发现领域
- 8.3.1 General CDASH Assumptions for Findings Domains
一般 CDASH 假设用于发现领域 - 8.3.2 DA - Drug Accountability
药物责任 - 8.3.3 DD - Death Details
死亡详情 - 8.3.4 EG - ECG Test Results
EG - 心电图测试结果 - 8.3.5 IE - Inclusion/Exclusion Criteria Not Met
IE - 包含/排除标准未满足 - 8.3.6 LB - Laboratory Test Results
实验室测试结果 - 8.3.7 MI - Microscopic Findings
MI - 显微镜下发现 - 8.3.8 PC - Pharmacokinetics Sampling
PC - 药代动力学取样 - 8.3.9 PE - Physical Examination
PE - 体检 - 8.3.10 QRS - Questionnaires, Ratings and Scales
QRS - 问卷、评分和量表 - 8.3.11 SC - Subject Characteristics
SC - 主题特征 - 8.3.12 RP - Reproductive System Findings
生殖系统发现 - 8.3.13 SR - Skin Response
SR - 皮肤反应 - 8.3.14 VS - Vital Signs
生命体征 - VS - 8.3.15 FA - Findings About
FA - 发现关于
- 8.3.1 General CDASH Assumptions for Findings Domains
- 8.1 CDASH Interventions Domains
- Appendices 附录
- Appendix A: CDASH Contributors
附录 A:CDASH 贡献者- Appendix A1: CDASH Co-Chairs
附录 A1:CDASH 联合主席 - Appendix A2: CDASH Model and CDASHIG Team Contributors
附录 A2:CDASH 模型和 CDASHIG 团队贡献者
- Appendix A1: CDASH Co-Chairs
- Appendix B: Glossary and Abbreviations
附录 B:术语表和缩略语 - Appendix C: Revision History
附录 C:修订历史- Appendix C1: Changes from CDASH v1.1 to CDASHIG v2.0
附录 C1:从 CDASH v1.1 到 CDASHIG v2.0 的变更
- Appendix C1: Changes from CDASH v1.1 to CDASHIG v2.0
- Appendix D: Representations and Warranties, Limitations of Liability, and Disclaimers
附录 D:陈述和保证、责任限制及免责声明
- Appendix A: CDASH Contributors
1 Orientation 1 定向
This implementation guide has been developed to assist in the following activities associated with the collection and compilation of data in a clinical trial.
本实施指南旨在协助与临床试验中数据收集和汇编相关的以下活动。
"There is arguably no more important document than the instrument that is used to acquire the data from the clinical trial, with the exception of the protocol, which specifies the conduct of that trial. The quality of the data collected relies first and foremost on the quality of that instrument. No matter how much time and effort go into conducting the trial, if the correct data points were not collected, a meaningful analysis may not be possible. It follows, therefore, that the design, development and quality assurance of such an instrument must be given the utmost attention."
可以说,没有比用于获取临床试验数据的工具更重要的文件,除了规定该试验进行方式的方案。收集数据的质量首先依赖于该工具的质量。无论进行试验投入了多少时间和精力,如果没有收集到正确的数据点,就可能无法进行有意义的分析。因此,这种工具的设计、开发和质量保证必须给予极大的关注。
— Good Clinical Data Management Practices, Version 4, October 2005, Society for Clinical Data Management
— 良好的临床数据管理实践,第 4 版,2005 年 10 月,临床数据管理协会
1.1 Purpose 1.1 目的
The Clinical Data Acquisition Standards Harmonization (CDASH) Model, the CDASH Implementation Guide (CDASHIG), and the CDASHIG Metadata Table define basic standards for the collection of clinical trial data and how to implement the standard for specific case report forms. CDASH establishes a standard way to collect data in a similar way across studies and sponsors, so that data collection formats and structures provide clear traceability of submission data into the Study Data Tabulation Model (SDTM), delivering more transparency to regulators and others who conduct data review. The CDASH standard is part of the Clinical Data Interchange Standards Consortium (CDISC) Technical Road Map, which is designed to realize the vision of a set of beginning-to-end harmonized standards for the representation of data from clinical studies throughout the data lifecycle. The CDASH standard directly supports the production of clinical data collection instruments. Through this support, the standard also contributes to:
临床数据采集标准协调(CDASH)模型、CDASH 实施指南(CDASHIG)和 CDASHIG 元数据表定义了临床试验数据收集的基本标准以及如何针对特定病例报告表实施该标准。CDASH 建立了一种在研究和赞助商之间以类似方式收集数据的标准方法,从而使数据收集格式和结构提供清晰的提交数据追溯到研究数据汇总模型(SDTM),为监管机构和其他进行数据审查的人员提供更多透明度。CDASH 标准是临床数据交换标准联盟(CDISC)技术路线图的一部分,旨在实现一套从头到尾协调一致的标准,以表示临床研究数据在整个数据生命周期中的表现。CDASH 标准直接支持临床数据收集工具的生产。通过这种支持,该标准还为以下方面做出贡献:
- Efficient development of research protocols
高效开发研究方案 - Streamlined processes within medical research
医疗研究中的简化流程 - Development of a corporate library of standardized CRFs
标准化 CRF 的企业图书馆开发 - Use of metadata repositories
使用元数据仓库 - Reporting and regulatory submission
报告和监管提交 - Data warehouse population
数据仓库填充 - Data archiving 数据归档
- Post-marketing studies/safety surveillance
上市后研究/安全监测
For more information, click on the following link: http://www.cdisc.org/strategies-and-goals.
有关更多信息,请点击以下链接:http://www.cdisc.org/strategies-and-goals。
There is growing recognition around the globe that industry standards promote data interchange, which is essential to effective partnering and information exchange between and among clinicians and researchers. Clinical care can more easily reap benefits through medical research findings, and more clinicians will be interested in conducting research if the research process can be integrated into their clinical care workflow. CDISC encourages the adoption of its global standards for clinical research, which should continue to be harmonized with healthcare standards, to provide a means for interoperability among healthcare and research systems such that medical research can support informed healthcare decisions and improve patient safety.
全球越来越认识到行业标准促进数据交换,这对临床医生和研究人员之间的有效合作和信息交流至关重要。临床护理可以更容易地从医学研究成果中获益,如果研究过程能够融入他们的临床护理工作流程,更多的临床医生将会对进行研究感兴趣。CDISC 鼓励采用其全球临床研究标准,这些标准应继续与医疗保健标准保持一致,以提供医疗保健和研究系统之间的互操作性,从而使医学研究能够支持知情的医疗决策并提高患者安全。
This document is intended to be used by persons involved in the planning, collection, management, and analysis of clinical trials and clinical data, including Clinical Investigators, Medical Monitors, Clinical Research Associates (Monitors), Clinical Research Study Coordinators, Clinical Data Standards Subject Matter Experts (SMEs), Clinical Data Managers, Clinical Data and Statistical Programmers, Biostatisticians, Drug Safety, Case Report Form (CRF) Designers, and other functions tasked with the responsibility to collect, clean, and ensure the integrity of clinical trial data.
本文件旨在供参与临床试验和临床数据的规划、收集、管理和分析的人员使用,包括临床研究者、医学监测员、临床研究助理(监测员)、临床研究协调员、临床数据标准主题专家(SME)、临床数据经理、临床数据和统计程序员、生物统计学家、药物安全、病例报告表(CRF)设计师以及其他负责收集、清理和确保临床试验数据完整性的职能。
1.2 Organization of this Document
1.2 本文件的组织结构
This document has been organized into the following sections:
本文件已组织为以下几个部分:
- Section 1, Orientation 第一部分,导向
- Section 2, How to Use the CDASH Standard
第 2 节,如何使用 CDASH 标准 - Section 3, General Assumptions for Implementing CDASH
第 3 节,实施 CDASH 的一般假设 - Section 4, Best Practice Recommendations
第 4 节,最佳实践建议 - Section 5, Conformance Rules
第 5 节,符合性规则 - Section 6, Other Information
第六节,其他信息 - Section 7, CDASH Special-Purpose Domains
第 7 节,CDASH 特殊用途领域 - Section 8, General Observation Classes
第 8 节,一般观察类 - Appendices 附录
1.2.1 General Notes 1.2.1 一般说明
- Paper CRFs vs. Electronic CRFs: The term "CRF" used throughout this document refers to both paper and electronic formats, unless otherwise specified.
纸质 CRF 与电子 CRF:本文档中使用的“CRF”一词指纸质和电子格式,除非另有说明。 - Fields vs. Variables: Data collection "fields" refers to terms that are commonly on the CRF. Data collection "variables" refers to what is in a clinical database.
字段与变量:数据收集“字段”是指在 CRF 上常见的术语。数据收集“变量”是指临床数据库中的内容。 - Study Treatment: The phrase "study treatment" has been used instead of investigational/medicinal product, study drug, test article, medical device, etc., in order to include all types of study designs and products.
研究治疗:为了涵盖所有类型的研究设计和产品,使用“研究治疗”这个短语来代替研究性/药物产品、研究药物、测试产品、医疗设备等。 - Mechanisms for Data Collection: Different data collection mechanisms can be used to control how data are collected (e.g., tick boxes, check boxes, radio buttons, drop-down lists, etc.). For the purposes of this document, these terms will be used interchangeably.
数据收集机制:可以使用不同的数据收集机制来控制数据的收集方式(例如,勾选框、复选框、单选按钮、下拉列表等)。在本文件中,这些术语将交替使用。
2 How to Use the CDASH Standard
2 如何使用 CDASH 标准
2.1 The Three Components of the CDASH Standard
2.1 CDASH 标准的三个组成部分
CDASH is composed of the CDASH Model and the CDASH Implementation Guide (CDASHIG), with its associated CDASHIG Metadata Table. A domain is a collection of data points related by a common topic, such as adverse events or demographics. CDASHIG domains are aligned with SDTMIG domains for beginning-to-end traceability.
CDASH 由 CDASH 模型和 CDASH 实施指南(CDASHIG)组成,并附有 CDASHIG 元数据表。领域是与共同主题相关的数据点集合,例如不良事件或人口统计。CDASHIG 领域与 SDTMIG 领域对齐,以实现从头到尾的可追溯性。
CDASH Model CDASH 模型
The CDASH Model v1.0 provides a general framework for creating fields to collect information on CRFs and includes the model metadata, which shows the standard variables in the model. The CDASHIG provides information on the implementation of the CDASH Model and includes the CDASHIG Metadata Table, which details additional specifications for data collection variables within each domain.
CDASH 模型 v1.0 提供了一个通用框架,用于创建字段以收集 CRF 上的信息,并包括模型元数据,显示模型中的标准变量。CDASHIG 提供了关于 CDASH 模型实施的信息,并包括 CDASHIG 元数据表,详细说明了每个领域内数据收集变量的附加规范。
The CDASH Model v1.0 provides root naming conventions for CDASHIG variables that are intended to facilitate mapping to the SDTMIG variables. The variables defined in the CDASH model follow the same "--XXXX" naming convention as the SDTM model. The two dashes are replaced by the domain code when applied to create the CDASHIG variable. For example, --DOSFRQ is the CDASH Model variable name to for Dosing Frequency per Interval in the Interventions Class. When a domain abbreviation is applied (e.g., "CM"), CMDOSFRQ is the CDASHIG variable for the frequency of the concomitant medication use. The CDASH Model includes metadata for variables used in each of the SDTM general observation classes, Timing variables, Identifier variables, variables for Special Purpose domains, and domain-specific variables. See Section 3.5 for specific information on the CDASH Model content.
CDASH 模型 v1.0 提供了 CDASHIG 变量的根命名约定,旨在促进与 SDTMIG 变量的映射。CDASH 模型中定义的变量遵循与 SDTM 模型相同的“--XXXX”命名约定。当应用于创建 CDASHIG 变量时,两个破折号会被领域代码替换。例如,--DOSFRQ 是干预类中每个间隔的给药频率的 CDASH 模型变量名称。当应用领域缩写时(例如,“CM”),CMDOSFRQ 是伴随用药频率的 CDASHIG 变量。CDASH 模型包括用于每个 SDTM 一般观察类、时间变量、标识符变量、特殊目的领域变量和领域特定变量的元数据。有关 CDASH 模型内容的具体信息,请参见第 3.5 节。
CDASHIG
The CDASHIG provides general information on the implementation of CDASH standards. The CDASH standards include the CDASH Model and the CDASHIG, which includes the supporting CDASHIG Metadata Table. The informative content of the CDASHIG and the normative content metadata table comprise the CDASHIG and must be referenced together.
CDASHIG 提供了关于 CDASH 标准实施的一般信息。CDASH 标准包括 CDASH 模型和 CDASHIG,其中包含支持的 CDASHIG 元数据表。CDASHIG 的说明性内容和规范性内容元数据表构成了 CDASHIG,必须一起引用。
CDASHIG Metadata Table CDASHIG 元数据表
The CDASHIG Metadata Table includes only those variables commonly implemented by a significant number of the organizations/companies that provided information/examples (e.g., Medical History, Adverse Events). Implementers can add appropriate variables to their CDASHIG domain using the associated General Observation class within the CDASH Model. The CDASHIG Domain Metadata illustrates the use of Question Text and Prompts employed by many sponsors. Implementers should reference the CDASH Model to see all available options for Question Text and Prompt for parameters and verb tenses that may be substituted.
CDASHIG 元数据表仅包括由提供信息/示例的许多组织/公司普遍实施的变量(例如,病史、不良事件)。实施者可以使用 CDASH 模型中的相关一般观察类将适当的变量添加到他们的 CDASHIG 领域。CDASHIG 领域元数据展示了许多赞助商使用的问题文本和提示。实施者应参考 CDASH 模型,以查看可用于参数和可能替代的动词时态的问题文本和提示的所有可用选项。
2.2 CDASHIG Metadata Table Attributes
2.2 CDASHIG 元数据表属性
The CDASHIG Metadata Table attributes provide building blocks for the development of a case report form and the underlying database or other data collection structure.
CDASHIG 元数据表属性为案例报告表及其基础数据库或其他数据收集结构的开发提供了构建模块。
CRF and Data Management System Design Metadata
CRF 和数据管理系统设计元数据
Certain metadata attributes are essential to CDASH conformance. Combined with the variable naming conventions discussed in Section 5.1 Conformance Rules, these metadata attributes will assist the designer of the CRFs and the underlying database structure to remain in conformance with the standard:
某些元数据属性对于 CDASH 合规性至关重要。结合第 5.1 节合规规则中讨论的变量命名约定,这些元数据属性将帮助 CRF 设计者和基础数据库结构保持与标准的一致性:
- Question Text (full sentence/question forms to prompt for data) OR Prompts (short phrases, often suitable as column headers, to prompt for data)
问题文本(完整句子/问题形式以提示数据)或提示(短语,通常适合作为列标题,以提示数据) - CDISC Controlled Terminology lists and subsets of list values when applicable
CDISC 控制术语列表及其适用的列表值子集 - DRAFT CDASH Definition (to assist in understanding the purpose of each variable)
草案 CDASH 定义(帮助理解每个变量的目的) - CDASHIG and SDTMIG Core designations and implementation notes (which, when used together, can assist a designer in determining the complete set of data to be collected on a form)
CDASHIG 和 SDTMIG 核心设计和实施说明(当一起使用时,可以帮助设计师确定在表单上收集的完整数据集)
SDTMIG Programming Metadata
SDTMIG 编程元数据
Columns in the CDASHIG Metadata Table that will assist in developing programs to generate SDTM domain datasets from CDASHIG compliant data include:
CDASHIG 元数据表中的列将有助于开发程序,从符合 CDASHIG 标准的数据生成 SDTM 领域数据集,包括:
- Domain 域名
- CDASHIG Variable CDASHIG 变量
- Maps to SDTMIG Variable
映射到 SDTMIG 变量 - Mapping Instructions 映射说明
- Implementation Notes 实施说明
Additional Metadata 附加元数据
The CDASHIG Metadata Table includes the column "Case Report Form Completion Instructions" to assist authors in creating this study level documentation for instructing sites how to complete the CRF fields.
CDASHIG 元数据表包括“病例报告表填写说明”列,以帮助作者创建此研究级文档,指导站点如何填写 CRF 字段。
2.3 CRF Development Overview
2.3 CRF 开发概述
The key steps to developing CRFs using CDASH are as follows:
使用 CDASH 开发 CRF 的关键步骤如下:
- Each organization may maintain a corporate library of standardized CRFs. Determine the requirements for data domains from these (if applicable) or the protocol data collection requirements for the study.
每个组织可以维护一个标准化 CRF 的企业库。根据这些(如适用)确定数据领域的要求或研究的协议数据收集要求。 - Review the domains published in CDASHIG to determine which of the data collection domains and fields are already specified in the published domains.
审查 CDASHIG 中发布的领域,以确定哪些数据收集领域和字段已在发布的领域中指定。 - As much as possible, the standard domains should be used to collect data in a manner that will be effective for data collection. Develop the data collection tools using these published, standard domains first.
尽可能使用标准领域以有效的方式收集数据。首先使用这些已发布的标准领域开发数据收集工具。 -
Using the root variables and other CDASH metadata in the CDASH Model, add any additional variables that are needed to meet the requirements of data collection. Follow CDISC Variable-Naming Fragments (see the CDASHIG Glossary and Abbreviations) conventions, and CDASH root variable naming conventions where they exist (e.g., --DAT for dates, --TIM for times, --YN for prompts as described in the CDASH Model).
使用 CDASH 模型中的根变量和其他 CDASH 元数据,添加满足数据收集要求所需的任何附加变量。遵循 CDISC 变量命名片段(参见 CDASHIG 术语表和缩略语)约定,以及存在的 CDASH 根变量命名约定(例如,--DAT 用于日期,--TIM 用于时间,--YN 用于 CDASH 模型中描述的提示)。Example: Replace "--" with the two-character domain code that matches the other variables in the same domain. For example, to add the --LOC variable to a Medical History CRF, the domain code is "MH", so the variable would become "MHLOC" in that domain.
示例:将“--”替换为与同一领域中其他变量匹配的两字符域代码。例如,要将--LOC 变量添加到医疗历史 CRF 中,域代码为“MH”,因此该变量在该领域中将变为“MHLOC”。 -
The Question Text and Prompt columns in the CDASH Model provide different variations in the recommended text for asking the question on a CRF. For each question, the sponsor may elect to either use the Question Text or the Prompt on the CRF. Some text is presented using brackets [ ], parentheses ( ), and/or incorporating forward slashes. These different formats are used to indicate how the Question Text or Prompt may be modified by the sponsor.
CDASH 模型中的问题文本和提示列提供了在 CRF 上询问问题的推荐文本的不同变体。对于每个问题,赞助商可以选择在 CRF 上使用问题文本或提示。一些文本使用方括号[ ]、圆括号( )和/或包含斜杠。这些不同的格式用于指示赞助商如何修改问题文本或提示。-
The text inside the brackets provides an option on the tense of the question, or text that can be replaced with protocol specific verbiage.
括号内的文本提供了问题时态的选项,或可以用特定协议的术语替换的文本。 -
The text inside the parentheses provides options (e.g., singular/plural) or text that may be eliminated.
括号内的文本提供选项(例如,单数/复数)或可能被省略的文本。 -
Text separated with a forward slash provides optional words which the sponsor may choose.
文本中用斜杠分隔的内容提供了赞助商可以选择的可选词。Example: The CDASH variable, --PERF, from the CDASH Model has the following Question Text and Prompt.
示例:CDASH 模型中的 CDASH 变量--PERF 具有以下问题文本和提示。Question Text: 问题文本:
[Were any/Was the] [--TEST/ topic] [measurement(s)/test(s)/examination(s)/specimen(s)/sample(s)] [performed/collected]?
[是否进行了] [--测试/主题] [测量/测试/检查/样本] [?]Prompt: 提示:
[--TEST/Topic] [Measurement(s)/Test(s)/Examination(s)/Specimen(s)/Sample(s)] [Performed/Collected]?
[--测试/主题] [测量/测试/检查/标本/样本] [执行/收集]?The sponsor wants to add a question to a CRF that asks whether a lab specimen was collected using a yes, no response.
赞助商希望在 CRF 中添加一个问题,询问实验室样本是否已收集,回答为“是”或“否”。a) The sponsor selects the CDASH variable --PERF and adds the appropriate domain code. LBPERF
赞助商选择 CDASH 变量--PERF 并添加适当的领域代码。LBPERFb) Use either the Prompt or the full Question Text on the CRF.
b) 在 CRF 上使用提示或完整问题文本。Question Text: Was the laboratory specimen collected?
实验室样本是否已收集?- In the first set of brackets, the text option "Was the" is selected as the study required only one lab test to be performed. [Were any/Was the]
在第一个括号中,文本选项“Was the”被选中,因为研究只需要进行一次实验室测试。[Were any/Was the] - In the second set of brackets, the text used is "laboratory" which is the topic of interest. [--TEST/Topic (laboratory)]
在第二组括号中,使用的文本是“实验室”,这是感兴趣的主题。[--TEST/Topic (实验室)] - In the third set of brackets, the text option "specimen" without the optional "s" is selected. [measurement(s)/test(s)/examination(s)/specimen(s)/sample(s)]
在第三组括号中,选择了不带可选“s”的文本选项“specimen”。[measurement(s)/test(s)/examination(s)/specimen(s)/sample(s)] - In the fourth set of brackets, the text option "collected" is selected. [performed/collected]
在第四组括号中,选择了文本选项“收集”。 [执行/收集]
Prompt: Laboratory Specimen Collected
实验室样本已收集- In the first set of brackets, the text used is the topic of interest (i.e., laboratory). [--TEST/Topic (Laboratory)]
在第一个括号中,使用的文本是感兴趣的主题(即,实验室)。[--测试/主题(实验室)] - In the second set of brackets, the text option "specimen" without the optional "s" is selected. [Measurement(s)/Test(s)/Examination(s)/Specimen(s)/Sample(s)]
在第二组括号中,选择了没有可选“s”的文本选项“specimen”。[测量/测试/检查/标本/样本] - In the third set of brackets, the text option "collected" is selected. [Performed/Collected]
在第三组括号中,选择了文本选项“收集”。[执行/收集]
- In the first set of brackets, the text option "Was the" is selected as the study required only one lab test to be performed. [Were any/Was the]
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- Create custom domains based on one of the General Observation Classes in the CDASH Model.
根据 CDASH 模型中的一般观察类别创建自定义域。
The CDASHIG Metadata Table attributes provide building blocks for the development of a case report form and the underlying database or other data collection structure.
CDASHIG 元数据表属性为案例报告表及其基础数据库或其他数据收集结构的开发提供了构建模块。
3 General Assumptions for Implementing CDASH
实施 CDASH 的三个一般假设
3.1 How CDASH and SDTM Work Together
3.1 CDASH 和 SDTM 如何协同工作
- The Study Data Tabulation Model (SDTM) and the SDTM Implementation Guide (SDTMIG) provide a standard for the submission of data. CDASH is earlier in the data flow and defines a basic set of data collection fields that are expected to be present on the majority of CRFs. SDTM and CDASH are clearly related. The use of CDASH data collection fields and variables is intended to facilitate mapping to the SDTM structure. When the data are identical between the two standards, the SDTMIG variable names are presented in the CDASHIG Metadata Table and should be used to collect the data. In cases where the data are not identical or do not exist in the SDTMIG, CDASH has created standardized data collection variable names.
研究数据制表模型(SDTM)和 SDTM 实施指南(SDTMIG)为数据提交提供了标准。CDASH 位于数据流的早期阶段,定义了一组基本的数据收集字段,这些字段预计在大多数 CRF 中会出现。SDTM 和 CDASH 显然是相关的。使用 CDASH 数据收集字段和变量旨在促进与 SDTM 结构的映射。当两个标准之间的数据相同时,SDTMIG 变量名称会在 CDASHIG 元数据表中列出,并应用于数据收集。在数据不相同或在 SDTMIG 中不存在的情况下,CDASH 创建了标准化的数据收集变量名称。 - The CDASHIG v2.0 content is based on the SDTMIG Version 3.2.
CDASHIG v2.0 内容基于 SDTMIG 版本 3.2。 - All SDTMIG "Required" variables have been addressed either directly through data collection or by determining what needs to be collected to derive the SDTMIG variable. In some cases, SDTMIG variable values can be obtained from data sources other than the CRF or are populated during the preparation of the submission datasets (e.g., --SEQ values).
所有 SDTMIG“必需”变量已通过数据收集直接处理,或通过确定需要收集什么以推导 SDTMIG 变量。在某些情况下,SDTMIG 变量值可以从 CRF 以外的数据源获得,或在准备提交数据集时填充(例如,--SEQ 值)。 - CDASHIG Domains contain variables that may be used in the creation of the RELREC submission dataset. For example: CDASHIG variable CMAENO: "What [is/was] the identifier for the adverse event(s) related to this (concomitant) [medication/therapy]?" may be used to identify a relationship between records in the CM dataset and records in the AE dataset.
CDASHIG 领域包含可能用于创建 RELREC 提交数据集的变量。例如:CDASHIG 变量 CMAENO:“与此(伴随)[药物/治疗]相关的不良事件的标识符是什么[是/曾是]?”可用于识别 CM 数据集中的记录与 AE 数据集中的记录之间的关系。 - The CDASH standard also includes some data collection fields that are not included in the SDTMIG (e.g., "Were any adverse events experienced?" or "Were any (concomitant) [medication(s)/therapy(ies)] taken?"). These data collection fields are intended to assist in the cleaning of data and in confirming that no data are unintentionally missing. To facilitate the use of these types of fields, variable names are provided (e.g., AEYN, CMYN) in the CDASHIG Metadata Table to denote that they are data collection variables, but the SDTMIG Variable Name column is listed as N/A, and the Mapping Instruction column indicates that these CDASHIG variables are not included in the SDTM datasets.
CDASH 标准还包括一些在 SDTMIG 中未包含的数据收集字段(例如,“是否经历了任何不良事件?”或“是否服用了任何(伴随)[药物/治疗]?”)。这些数据收集字段旨在帮助清理数据,并确认没有数据被无意遗漏。为了方便使用这些类型的字段,CDASHIG 元数据表中提供了变量名称(例如,AEYN,CMYN)以表示它们是数据收集变量,但 SDTMIG 变量名称列标记为 N/A,映射说明列则指示这些 CDASHIG 变量未包含在 SDTM 数据集中。 - The CDASHIG Findings domain (e.g., Drug Accountability (DA), ECG Test Results (EG) and Vital Signs (VS)) tables are presented in a structure that is similar to the SDTMIG, which is to list the variable names and some examples of the tests. Implementers are expected to include protocol-specific tests in a CRF presentation layout, using the appropriate values from the relevant CDISC Controlled Terminology codelists. For example, VSTEST values are used to name the test on the CRF, and the corresponding test code is determined from the VSTESTCD codelist. Implementers may use synonyms when the xxTEST values are long or not commonly recognized (e.g., ALT in place of Alanine Aminotransferase). Implementers should use the CDASHIG recommendations to identify the types of data to collect while referring to the SDTMIG and CDISC Controlled Terminology for additional metadata, (e.g., labels, data type, controlled terminology).
CDASHIG 发现领域(例如,药物责任(DA)、心电图测试结果(EG)和生命体征(VS))表格的结构与 SDTMIG 相似,列出了变量名称和一些测试示例。实施者应在 CRF 展示布局中包含特定于方案的测试,使用相关 CDISC 受控术语代码表中的适当值。例如,VSTEST 值用于在 CRF 上命名测试,相应的测试代码由 VSTESTCD 代码表确定。当 xxTEST 值较长或不常被认可时,实施者可以使用同义词(例如,用 ALT 代替丙氨酸氨基转移酶)。实施者应使用 CDASHIG 建议来识别要收集的数据类型,同时参考 SDTMIG 和 CDISC 受控术语以获取附加元数据(例如,标签、数据类型、受控术语)。 - The CDASH standard has intentionally not reproduced other sections of the SDTM standard and implementers are asked to refer to the SDTM Model and SDTMIG on the CDISC website for additional information (http://www.cdisc.org/sdtm).
CDASH 标准故意没有重现 SDTM 标准的其他部分,实施者被要求参考 CDISC 网站上的 SDTM 模型和 SDTMIG 以获取更多信息(http://www.cdisc.org/sdtm)。 - The CDASHIG data collection fields included in the CDASHIG Metadata Table are the most commonly used and should be easily identified by most implementers. Additional data collection fields may be necessary to capture therapeutic area (TA) specific data points as well as other data specified in the clinical study protocol or for local regulatory requirements. Reference the CDASH Model and CDISC Therapeutic Area User Guides for additional information.
CDASHIG 元数据表中包含的 CDASHIG 数据收集字段是最常用的,应该能被大多数实施者轻松识别。可能需要额外的数据收集字段来捕获特定于治疗领域(TA)的数据点,以及临床研究方案中规定的其他数据或当地监管要求。有关更多信息,请参考 CDASH 模型和 CDISC 治疗领域用户指南。 - Use the CDASH recommendations to develop company standards, taking into consideration the stage of clinical development and the individual therapeutic area requirements. To gain the greatest benefit from using the CDASH standard, CRFs should not be developed on a trial-by-trial basis within the implementer organization, but rather be brought into a study from a library of approved CRFs based on the CDASH Model and Implementation Guide, whenever practicable.
使用 CDASH 建议制定公司标准,考虑临床开发阶段和各个治疗领域的要求。为了最大限度地利用 CDASH 标准,CRF 不应在实施组织内逐个试验开发,而应尽可能从基于 CDASH 模型和实施指南的已批准 CRF 库中引入到研究中。 - The CDASHIG is divided into sections of similar types of data and the CDASHIG Metadata Table is arranged in alphabetical order (by domain abbreviation) within their respective general observation class. CRF layout was not within the original scope of the CDASH project; however, to assist with standardization of CRF layout, data collection fields are presented within the CDASHIG Metadata Table in a logical order, and annotated example CRFs have been provided (if available). In addition, implementers are referred to Best Practice for Creating Data Collection Instruments (Best Practice Recommendations), for a discussion on best practices for ordering fields on a case report form.
CDASHIG 被分为相似类型数据的部分,CDASHIG 元数据表按字母顺序(按领域缩写)排列在各自的一般观察类别内。CRF 布局不在 CDASH 项目的原始范围内;然而,为了帮助标准化 CRF 布局,数据收集字段在 CDASHIG 元数据表中以逻辑顺序呈现,并提供了注释示例 CRF(如果可用)。此外,实施者被建议参考《创建数据收集工具的最佳实践》(最佳实践建议),以讨论案例报告表字段排序的最佳实践。
3.2 Core Designations for Basic Data Collection Fields
3.2 基本数据收集字段的核心标识
In order to facilitate classification of the different types of data collection fields, the following categories were used:
为了方便对不同类型的数据收集领域进行分类,使用了以下类别:
- Highly Recommended (HR): A data collection field that should always be on the CRF (e.g., the data are needed to meet a regulatory requirement or are required to create a meaningful dataset).
强烈推荐(HR):一个数据收集领域,应该始终出现在 CRF 上(例如,这些数据是满足监管要求所需,或是创建有意义的数据集所必需的)。 - Recommended/Conditional (R/C): A data collection field that should be on a CRF based on certain conditions (e.g., complete date of birth is preferred, but may not be allowed in some regions; AE time should be captured only if there is another data point with which to compare it). For any recommended/conditional fields, the "condition" is described in the "Implementation Notes" portion of the CDASHIG Metadata Table.
推荐/条件 (R/C):根据某些条件应在 CRF 上包含的数据收集字段(例如,完整的出生日期是首选,但在某些地区可能不被允许;不良事件时间仅在有其他数据点可供比较时捕获)。对于任何推荐/条件字段,“条件”在 CDASHIG 元数据表的“实施说明”部分中描述。 - Optional (O): A data collection field that is available for use.
可选 (O):可供使用的数据收集字段。
3.3 Additional Information about CDASHIG Core Designations
3.3 关于 CDASHIG 核心标识的附加信息
The CDASH team initially considered utilizing the SDTMIG Core Designations of Required, Expected, and Permissible to capitalize on prior understanding of these descriptive designations as well as to enable a consistent categorization across CDASH and SDTM standards. Yet, when the CDASHIG Metadata Table was constructed, it quickly became apparent that CDASHIG core designations would often differ from SDTMIG core designations due to the inherent differences between the manner in which data are collected (to ensure the most accurate data) and the structure in which data are reported and submitted. For example, a variable categorized as Required in the SDTMIG may not be required in the CDASHIG if it can be derived in the SDTM datasets (rather than be a field captured explicitly on a CRF). Also, the SDTMIG core designation of "Required" imposes a rule that the variable cannot be null. CDASHIG Core designations are not intended to impose any rules that require a field to be populated with data. They are only intended to designate which fields should be present on the CRF.
CDASH 团队最初考虑利用 SDTMIG 核心标识的“必需”、“预期”和“允许”来利用对这些描述性标识的先前理解,并实现 CDASH 和 SDTM 标准之间的一致分类。然而,当 CDASHIG 元数据表构建时,很快就显现出 CDASHIG 核心标识往往会与 SDTMIG 核心标识不同,这主要是由于数据收集方式(以确保数据的准确性)和数据报告及提交结构之间的固有差异。例如,在 SDTMIG 中被分类为“必需”的变量,如果可以在 SDTM 数据集中推导出来(而不是在 CRF 上明确捕获的字段),那么在 CDASHIG 中可能并不是必需的。此外,SDTMIG 核心标识“必需”规定该变量不能为 null。CDASHIG 核心标识并不打算强加任何要求字段必须填充数据的规则。它们仅旨在指定 CRF 上应存在哪些字段。
3.4 How to Create New Data Collection Fields When No CDASHIG Field Has Been Defined
3.4 如何在未定义 CDASHIG 字段时创建新的数据收集字段
Adding new collection fields is often constrained by business rules, as well as by clinical data standards SMEs, clinical data management processes, and EDC systems. The naming conventions and other variable creation recommendations in CDASHIG are designed to allow collection of data regardless of subsequent inclusion in SDTM, as well as to consistently facilitate transforming the collected data into submission datasets.
添加新的收集字段通常受到业务规则的限制,以及临床数据标准的主题专家、临床数据管理流程和电子数据采集系统的影响。CDASHIG 中的命名约定和其他变量创建建议旨在允许数据的收集,无论其是否随后包含在 SDTM 中,并且始终有助于将收集的数据转换为提交数据集。
Prior to adding any new fields to current domain models, the CDASH Model should be reviewed to see if there is a root field that will work for the data collection need.
在向当前领域模型添加任何新字段之前,应审查 CDASH 模型,以查看是否有适合数据收集需求的根字段。
New data collection fields (not already defined in a CDASH Model) will fall under one of following categories.
新的数据收集字段(在 CDASH 模型中尚未定义)将属于以下类别之一。
- Fields used for data cleaning purposes only and not submitted in SDTM datasets (e.g., --YN). The field --YN with Question Text "Were there any [interventions/events/findings]?" can be added to a domain for this purpose. Replace the two dashes (--) with the two-character domain code, and create the Question Text or Prompt using generic Question Text or Prompt from the CDASH Model as a base. Always create custom data cleaning/operational variables using consistent naming conventions.
仅用于数据清理目的的字段,不会提交到 SDTM 数据集中(例如,--YN)。字段--YN 的提问文本为“是否有任何[干预/事件/发现]?”可以为此目的添加到一个领域中。将两个破折号(--)替换为两个字符的领域代码,并使用 CDASH 模型中的通用提问文本或提示作为基础创建提问文本或提示。始终使用一致的命名约定创建自定义数据清理/操作变量。 - Fields with a direct mapping to an SDTMIG variable. If a value can be collected exactly as it will be reported in the SDTM dataset (i.e., same value, same datatype, same meaning, same Controlled Terminology), the SDTMIG variable name should be used as part of the data collection variable name in the operational database to streamline the mapping process. Any collection variable whose meaning is the same as an SDTMIG variable should be a copy of the SDTMIG variable, and the meaning should not be modified for data collection.
与 SDTMIG 变量直接映射的字段。如果一个值可以完全按照将在 SDTM 数据集中报告的方式收集(即,相同的值、相同的数据类型、相同的含义、相同的受控术语),则应将 SDTMIG 变量名称作为操作数据库中数据收集变量名称的一部分,以简化映射过程。任何其含义与 SDTMIG 变量相同的收集变量都应是 SDTMIG 变量的副本,并且在数据收集时不应修改其含义。 - Fields without a direct one-to-one mapping to SDTM datasets. If a study requires a field that is not identical to an SDTMIG field, for example the collected data type is different from the data type in the corresponding SDTMIG variable, or the SDTMIG variable is derived from collected data, the operational database should use a variable with a different name from the SDTMIG variable into which it will be mapped.
与 SDTM 数据集没有直接一对一映射的字段。如果研究需要一个与 SDTMIG 字段不完全相同的字段,例如收集的数据类型与相应的 SDTMIG 变量中的数据类型不同,或者 SDTMIG 变量是从收集的数据中派生的,则操作数据库应使用一个与将要映射的 SDTMIG 变量不同名称的变量。
- Example 1: A study collects Findings data in a denormalized format and then maps the data to the normalized SDTM structure. The --TESTCD values can be used as the CDASHIG variable names, and the corresponding --TEST value can be used as the prompt on the CRF (See Section 8.3 General CDASH Assumptions for Findings Domains for more information).
示例 1:一项研究以非规范化格式收集结果数据,然后将数据映射到规范化的 SDTM 结构。--TESTCD 值可以用作 CDASHIG 变量名称,相应的 --TEST 值可以用作 CRF 上的提示(有关结果领域的一般 CDASH 假设的更多信息,请参见第 8.3 节)。 - Example 2: Dates and times are collected in a local format, familiar to the CRF users, and then reported in the SDTM-specified ISO 8601 format. In the operational database, the CDASH variables --DAT and --TIM (if collected) map into the single SDTM variable (--DTC).
示例 2:日期和时间以本地格式收集,方便 CRF 用户使用,然后以 SDTM 指定的 ISO 8601 格式报告。在操作数据库中,CDASH 变量 --DAT 和 --TIM(如果收集)映射到单个 SDTM 变量 (--DTC)。 - Example 3: If the mapping to SDTM is similar, but not direct, "C" can be included before the root variable name to indicate a "collected" version of the variable to which that data will map.
示例 3:如果映射到 SDTM 是相似的,但不是直接的,可以在根变量名称前加上 "C",以表示该数据将映射到的变量的 "收集" 版本。For example, if an injection is to be administered to a subject's LEFT THIGH, RIGHT THIGH, LEFT ARM, or RIGHT ARM, the sponsor may create the variable EXCLOC. The SDTM mapping would split these into EXLOC and EXLAT. That would avoid having to split the collection of the data into two fields on the CRF.
例如,如果要对受试者的左大腿、右大腿、左臂或右臂进行注射,赞助商可以创建变量 EXCLOC。SDTM 映射将这些分为 EXLOC 和 EXLAT。这样可以避免在 CRF 上将数据收集拆分为两个字段。
- Example 1: A study collects Findings data in a denormalized format and then maps the data to the normalized SDTM structure. The --TESTCD values can be used as the CDASHIG variable names, and the corresponding --TEST value can be used as the prompt on the CRF (See Section 8.3 General CDASH Assumptions for Findings Domains for more information).
3.5 Explanation of Table Headers in the CDASH Model and CDASHIG Metadata Table
3.5 CDASH 模型和 CDASHIG 元数据表中表头的解释
3.5.1 CDASH Model 3.5.1 CDASH 模型
This section provides an explanation of the columns used in the CDASH Model.
本节提供了 CDASH 模型中使用的列的解释。
- Observation Class: This column contains the SDTM Class for the domain.
观察类别:此列包含该领域的 SDTM 类别。 - Domain: This column contains the two-letter domain code.
域:此列包含两个字母的域代码。 - CDASH Variable: This column provides the CDASH root variable names (e.g., --ONGO, --DAT).
CDASH 变量:此列提供 CDASH 根变量名称(例如,--ONGO,--DAT)。 - CDASH Variable Label: This column contains a suggested root variable label that that may be used for the CDASHIG variable.
CDASH 变量标签:此列包含可用于 CDASHIG 变量的建议根变量标签。 - Draft CDASH Definition: This column provides a draft definition of the root variable. This text may or may not mirror any text in the SDTM. Currently, there is a new CDASH/SDTM team creating variable definitions. Once these definitions are finalized, the CDASH definitions will be updated to harmonize with them.
草案 CDASH 定义:此列提供根变量的草案定义。该文本可能与 SDTM 中的任何文本相符,也可能不相符。目前,有一个新的 CDASH/SDTM 团队正在创建变量定义。一旦这些定义最终确定,CDASH 定义将会更新以与之协调。 - Question Text: This column in the CDASH Model contains the recommended question text for the data collection field. Question Text is a complete sentence. Some text is presented inside brackets [ ] or parentheses (). The text inside the brackets should be replaced with protocol-specified verbiage. The text inside the parentheses is optional. Text separated with a forward slash indicates optional wording from which the sponsor may choose.
问题文本:CDASH 模型中的这一列包含数据收集字段的推荐问题文本。问题文本是一个完整的句子。一些文本以方括号 [ ] 或圆括号 () 的形式呈现。方括号内的文本应替换为协议指定的措辞。圆括号内的文本是可选的。用斜杠分隔的文本表示赞助方可以选择的可选措辞。 - Prompt: This column in the CDASH Model contains the recommended prompt text for the data collection field. The Prompt is a short version of the question. Some text is presented inside brackets [ ] or parentheses (). The text inside the brackets should be replaced with protocol-specified verbiage. The text inside the parentheses is optional. Text separated with a forward slash indicates optional wording from which the sponsor may choose.
提示:CDASH 模型中的此列包含数据收集字段的推荐提示文本。提示是问题的简短版本。一些文本以方括号 [ ] 或圆括号 () 的形式呈现。方括号内的文本应替换为协议指定的措辞。圆括号内的文本是可选的。用斜杠分隔的文本表示赞助商可以选择的可选措辞。 - Data Type: This column contains the simple data type of the CDASH variable (e.g., Char, Num, Date, or Time).
数据类型:此列包含 CDASH 变量的简单数据类型(例如,字符、数字、日期或时间)。 - SDTM Target: This column provides the suggested mapping to the SDTM root variable. When no direct mapping to an SDTM root variable is available, the column contains "N/A". When the column contains "SUPP--.QNAM", it means that the value represented in the CDASH variable shall be mapped to an SDTM Supplemental Qualifier. NOTE: CDASH variables noted as not having a direct map to SDTM variables (i.e., non standard variables) may have SDTM variable equivalents in future versions.
SDTM 目标:此列提供建议的映射到 SDTM 根变量。当没有直接映射到 SDTM 根变量时,该列包含“N/A”。当该列包含“SUPP--.QNAM”时,意味着 CDASH 变量中表示的值应映射到 SDTM 补充限定符。注意:标记为没有直接映射到 SDTM 变量的 CDASH 变量(即非标准变量)在未来版本中可能会有 SDTM 变量的对应项。 - Mapping Instructions: This column contains information on the suggested mapping of the root variable to the SDTM variable.
映射说明:此列包含有关根变量与 SDTM 变量建议映射的信息。 - Controlled Terminology Codelist Name: This column contains the Controlled Terminology (CT) codelist name {e.g., (LOC)} that is associated with the field. Certain variables (e.g., dates) use ISO formats as CT, however in CDASH these variables are generally not collected using the ISO CT. These variables are converted to the ISO format when the SDTM-based submission datasets are created.
受控术语代码列表名称:此列包含与该字段相关的受控术语(CT)代码列表名称 {例如,(LOC)}。某些变量(例如,日期)使用 ISO 格式作为 CT,但在 CDASH 中,这些变量通常不使用 ISO CT 进行收集。当创建基于 SDTM 的提交数据集时,这些变量会转换为 ISO 格式。 - Implementation Notes: This column contains further information, such as rationale and implementation instructions, on how to implement the CRF data collection fields and how to map CDASH variables to SDTM variables.
实施说明:本栏包含有关如何实施 CRF 数据收集字段以及如何将 CDASH 变量映射到 SDTM 变量的进一步信息,例如理由和实施说明。
Note: When multiple options are contained in a single cell, the options are separated by a semicolon.
注意:当一个单元格中包含多个选项时,选项之间用分号分隔。
3.5.2 CDASHIG Metadata Table
3.5.2 CDASHIG 元数据表
This section provides an explanation of the columns used in the CDASHIG Metadata Table.
本节提供了 CDASHIG 元数据表中使用的列的解释。
- Observation Class: This column contains the SDTM Class for the domain.
观察类别:此列包含该领域的 SDTM 类别。 - Domain: This column contains the two-letter domain code.
域:此列包含两个字母的域代码。 - Data Collection Scenario: This column in the CDASHIG Metadata Table identifies the different data collection options in CDASH for the same domain and is best used for filtering the table. The information in this column provides the context for the CDASHIG Core Designations, e.g., denoting which fields should be present on the CRF. When only one data collection scenario is provided for the domain, the column contains "N/A".
数据收集场景:CDASHIG 元数据表中的这一列标识了同一领域中 CDASH 的不同数据收集选项,最适合用于过滤表格。该列中的信息为 CDASHIG 核心指定提供了背景,例如,指明哪些字段应出现在 CRF 上。当该领域仅提供一个数据收集场景时,该列包含“N/A”。 - Implementation Options: When this column contains "Horizontal-Generic", a sampling of the CDASHIG metadata is provided as a template for the metadata of the CRF in a denormalized structure. When this column contains "Horizontal-Example", it represents a specific execution of CRF metadata in a denormalized structure.
实施选项:当此列包含“水平-通用”时,提供 CDASHIG 元数据的采样作为 CRF 元数据的模板,采用非规范化结构。当此列包含“水平-示例”时,它表示 CRF 元数据在非规范化结构中的特定执行。 - Order Number: This column provides a suggested order of CDASHIG variables to be displayed on a CRF.
订单编号:此列提供建议的 CDASHIG 变量顺序,以便在 CRF 上显示。 - CDASHIG Variable: This column provides the CDASHIG variable names (e.g., CMONGO, AEDAT).
CDASHIG 变量:此列提供 CDASHIG 变量名称(例如,CMONGO,AEDAT)。 - CDASHIG Variable Label: This column provides the CDASHIG variable label.
CDASHIG 变量标签:此列提供 CDASHIG 变量标签。 - Draft CDASHIG Definition: This column provides a draft definition of the CDASHIG variable. This text may or may not mirror any text in the SDTMIG. Currently, there is a new CDASH/SDTM team creating variable definitions. Once these definitions are finalized, the CDASH definitions will be updated to harmonize with them.
草案 CDASHIG 定义:此列提供 CDASHIG 变量的草案定义。该文本可能与 SDTMIG 中的任何文本相符,也可能不相符。目前,有一个新的 CDASH/SDTM 团队正在创建变量定义。一旦这些定义最终确定,CDASH 定义将会更新以与之协调。 - Question Text: This column in the CDASHIG Metadata Table provides the suggested text for the specific Domain. Implementers should refer to the CDASH Model to create alternative question text that may be used that meets the CDASH conformance rules. Question Text is a complete sentence. Some text is presented inside brackets [ ] or parentheses (). The text inside the brackets should be replaced with protocol-specified verbiage. The text inside the parentheses is optional. Text separated with a forward slash indicates optional wording from which the sponsor may choose.
该 CDASHIG 元数据表中的这一列提供了特定领域的建议文本。实施者应参考 CDASH 模型创建符合 CDASH 一致性规则的替代问题文本。问题文本是一个完整的句子。一些文本以方括号 [ ] 或圆括号 ( ) 的形式呈现。方括号内的文本应替换为协议指定的措辞。圆括号内的文本是可选的。用斜杠分隔的文本表示赞助方可以选择的可选措辞。 - Prompt: This column in the CDASHIG Metadata Table provides the suggested text for the specific Domain. Implementers should refer to the CDASH Model to create alternative prompt text that may be used that meets the CDASH conformance rules The Prompt is a short version of the question. Some text is presented inside brackets [ ] or parentheses (). The text inside the brackets should be replaced with protocol-specified verbiage.
该 CDASHIG 元数据表中的这一列提供了特定领域的建议文本。实施者应参考 CDASH 模型创建符合 CDASH 一致性规则的替代提示文本。提示是问题的简短版本。一些文本以方括号 [ ] 或圆括号 () 的形式呈现。方括号内的文本应替换为协议指定的用语。 - Data Type: This column contains the simple data type of the CDASH variable (e.g., Char, Num, Date, or Time).
数据类型:此列包含 CDASH 变量的简单数据类型(例如,字符、数字、日期或时间)。 - CDASHIG Core: This column contains the CDASHIG core designations for basic data collection fields (i.e., Highly Recommended (HR), Recommended/Conditional (R/C), Optional (O)). See Section 3.3 for definitions of CDASH core designations.
CDASHIG 核心:此列包含基本数据收集字段的 CDASHIG 核心标识(即,高度推荐(HR)、推荐/有条件(R/C)、可选(O))。有关 CDASH 核心标识的定义,请参见第 3.3 节。 - Case Report Form Completion Instructions: This column contains recommended example instructions for the clinical site on how to enter collected information on the CRF.
病例报告表填写说明:本栏目包含临床现场关于如何在病例报告表上输入收集信息的推荐示例说明。 - SDTMIG Target: This column provides the suggested mapping to the SDTMIG variable name. It may help facilitate the creation of the SDTMIG variables needed for submission. When no direct mapping to an SDTMIG variable is available the column contains "N/A". When the column contains "SUPP--.QNAM", it means that that the value represented in the CDASH field shall be mapped to an SDTM Supplemental Qualifier. NOTE: CDASHIG variables noted as not having a direct map to SDTMIG variables (i.e., non standard variables) may have SDTM variable equivalents in future versions.
SDTMIG 目标:此列提供了建议的 SDTMIG 变量名称映射。它可能有助于创建提交所需的 SDTMIG 变量。当没有直接映射到 SDTMIG 变量时,该列包含 "N/A"。当该列包含 "SUPP--.QNAM" 时,意味着 CDASH 字段中表示的值应映射到 SDTM 补充限定符。注意:CDASHIG 变量被标记为没有直接映射到 SDTMIG 变量(即非标准变量),在未来版本中可能会有 SDTM 变量的对应项。 - Mapping Instructions: This column contains information on the suggested mapping of the CDASHIG variable to the SDTMIG variable. Mapping instructions in the CDASHIG Metadata Table provide more complete guidance than those present in the CDASH Model. When domain level metadata are not available, consult the Model for SDTM Mapping Instructions.
映射说明:此列包含有关将 CDASHIG 变量映射到 SDTMIG 变量的建议信息。CDASHIG 元数据表中的映射说明提供的指导比 CDASH 模型中的更为全面。当域级元数据不可用时,请参考 SDTM 映射说明模型。 - SDTMIG Core: This column contains the SDTMIG core designations (i.e., Required (Req), Expected (Exp), and Permissible (Perm)). The CDASHIG core designations differ from SDTMIG core designations. A Required variable in the SDTMIG may not be Highly Recommended in the CDASHIG.
SDTMIG 核心:此列包含 SDTMIG 核心标识(即,必需(Req)、预期(Exp)和允许(Perm))。CDASHIG 核心标识与 SDTMIG 核心标识不同。SDTMIG 中的必需变量在 CDASHIG 中可能不是高度推荐的。 - Controlled Terminology Codelist Name: This column contains the Controlled Terminology (CT) codelist name {e.g., (LOC)} that is associated with the field. The SDTMIG indicates that certain variables (e.g., dates) use ISO formats as CT, however in CDASH these variables are generally not collected using the ISO CT. These variables are converted to the ISO format when the SDTM-based submission datasets are created.
受控术语代码列表名称:此列包含与该字段相关的受控术语(CT)代码列表名称{例如,(LOC)}。SDTMIG 指出某些变量(例如,日期)使用 ISO 格式作为 CT,但在 CDASH 中,这些变量通常不是使用 ISO CT 收集的。当创建基于 SDTM 的提交数据集时,这些变量会转换为 ISO 格式。 - Subset Controlled Terminology/CDASH Codelist Name: This column contains the CDISC Controlled Terminology or CDASH Subset Codelist name that may be used for that specific variable (e.g., EXDOSFRM).
子集控制术语/CDASH 代码列表名称:此列包含可用于特定变量的 CDISC 控制术语或 CDASH 子集代码列表名称(例如,EXDOSFRM)。 - Implementation Notes: This column contains further information, such as rationale and implementation instructions, on how to implement the CRF data collection fields and how to map CDASHIG variables to SDTMIG variables.
实施说明:本栏包含有关如何实施 CRF 数据收集字段的进一步信息,例如理由和实施说明,以及如何将 CDASHIG 变量映射到 SDTMIG 变量。
Note: When multiple options are contained in a single cell, the options are separated by a semicolon.
注意:当一个单元格中包含多个选项时,选项之间用分号分隔。
3.6 Collection of Dates 3.6 日期的收集
Collection of Dates: Collect dates in such a way to allow the sites to record only the precision they know. The system should also store only the collected precision. Any incomplete dates must remain incomplete with no imputation and no "zero-filling" of missing components.
日期收集:以允许站点仅记录他们所知道的精度的方式收集日期。系统还应仅存储收集到的精度。任何不完整的日期必须保持不完整,不得进行插补,也不得对缺失的组件进行“零填充”。
Data collection and database processes should allow for the possibility of partial dates and times, since a partial date may be the most precise information that can be collected for some data. An example of when it may be necessary or appropriate to collect partial dates is found in the DM domain. In some countries, collection of a complete date of birth is restricted under privacy rules, so only a year, or year and month of birth might be collected. Other examples of commonly collected partial dates are found in CM and MH, where the subject may not remember the complete date of when they started to take a medication or when a significant medical history condition began.
数据收集和数据库处理应允许部分日期和时间的可能性,因为对于某些数据,部分日期可能是可以收集到的最精确的信息。在 DM 领域中,有时收集部分日期是必要或合适的例子。在某些国家,出于隐私规则,完整的出生日期的收集受到限制,因此可能只收集出生的年份或年份和月份。其他常见的部分日期收集例子出现在 CM 和 MH 中,受访者可能不记得他们开始服用药物的完整日期或某个重要医疗历史状况开始的完整日期。
If a full date is collected, the CDASH variable --DAT or all three date components (--DATYY, --DATMO, and --DATDD) should be included on the collection tool. If a partial date can be collected in a single field, the CDASH --DAT should be used. If a partial date must be collected as separate database fields to collect year, month and day, refer to the CDASH Model for examples of standard naming fragments (--YY, --MO, --DD, --TIM). The capabilities of individual software systems (e.g., EDC) will determine which variable names are needed. CDASH uses separate data collection fields for dates and times. If times are collected, it is expected that they will be used with the appropriate collected date to derive the related SDTM date variable in ISO8601 format.
如果收集了完整的日期,则应在收集工具中包含 CDASH 变量--DAT 或所有三个日期组件(--DATYY、--DATMO 和--DATDD)。如果可以在单个字段中收集部分日期,则应使用 CDASH --DAT。如果必须将部分日期作为单独的数据库字段收集以获取年、月和日,请参考 CDASH 模型以获取标准命名片段的示例(--YY、--MO、--DD、--TIM)。各个软件系统(例如,EDC)的功能将决定需要哪些变量名称。CDASH 为日期和时间使用单独的数据收集字段。如果收集了时间,预计将与适当收集的日期一起使用,以推导出相关的 SDTM 日期变量,格式为 ISO8601。
Conversion of Dates for Submission: See section SDTMIG v3.2 Sections 4.1.4.1 and 4.1.4.2 for detailed information about converting dates and times from the collection format to the submission format using ISO 8601. A specific example of mapping birth date is shown here.
提交日期的转换:有关使用 ISO 8601 将日期和时间从收集格式转换为提交格式的详细信息,请参见 SDTMIG v3.2 第 4.1.4.1 节和第 4.1.4.2 节。这里展示了一个出生日期映射的具体示例。
The SDTM date format allows this partial date to be submitted so the reviewer can see what was collected.
SDTM 日期格式允许提交部分日期,以便审阅者可以查看所收集的信息。
Imputation of Dates: If the missing parts of the date are imputed for analysis purposes, the imputed dates will be generated in the analysis data (ADaM) but not in the SDTM submission data sets.
日期的推算:如果为了分析目的对缺失的日期部分进行推算,推算出的日期将会在分析数据(ADaM)中生成,但不会出现在 SDTM 提交数据集中。
3.7 Mapping Relative Times from Collection to Submissions
3.7 从收集到提交的相对时间映射
Relative Timing variables are sets of variables that provide information about how the timing of the record relates to either the study reference period or another fixed point in time. The CDASH Relative Timing variables are collected for those observations where a date is either not collected or is not available. The CDASH set of variables serve as an indicator (or flag) that the observation's "start" was "prior" to the study reference period or prior to another fixed point in time OR that the observation's "end" was "after" or "ongoing" as of the study reference period or another fixed point in time. The CDASH variables of --PRIOR and --ONGO serve this purpose. How these CDASH "flags" are translated to SDTM (according to controlled terminology) depends on whether the comparison is against the protocol-defined study reference period or against another fixed point in time that may serve as the "reference" for the timing of the record. To emphasize, the collection of these CDASH relative timing variables are always dependent on the actual date either being prospectively "not collected" or not available. Much more information can be found under the "General Assumptions" for both Interventions and Events domains.
相对时间变量是一组变量,提供有关记录的时间如何与研究参考期或另一个固定时间点相关的信息。CDASH 相对时间变量用于那些未收集日期或日期不可用的观察。CDASH 变量集作为指示(或标志),表明观察的“开始”是在研究参考期之前或在另一个固定时间点之前,或者观察的“结束”是在研究参考期之后或在研究参考期时仍在进行。CDASH 变量--PRIOR 和--ONGO 用于此目的。这些 CDASH“标志”如何转换为 SDTM(根据受控术语)取决于比较是针对协议定义的研究参考期,还是针对可能作为记录时间“参考”的另一个固定时间点。需要强调的是,这些 CDASH 相对时间变量的收集始终依赖于实际日期是否前瞻性地“未收集”或不可用。 在干预和事件领域的“一般假设”下可以找到更多信息。
For all SDTM submissions, there is a defined period during which the subject is considered to be "on study". According to the SDTMIG v3.2, the start and end dates of the "on study" period are submitted in the variables RFSTDTC and RFENDTC. The defined period may be protocol-specific or set by company policy, SOPs, or other documented procedures. The "on study" period might be defined as being from the date/time of Informed Consent through the date/time of subject's completion of the study, or it might be from the date/time of first dose to the date/time of last dose. Regardless of how the "on study" period is defined, the dates (and optionally times) of the start and end of that period must be collected.
对于所有 SDTM 提交,有一个定义的时间段,在此期间受试者被视为“在研究中”。根据 SDTMIG v3.2,“在研究中”期间的开始和结束日期在变量 RFSTDTC 和 RFENDTC 中提交。该定义的时间段可能是特定于方案的,或由公司政策、标准操作程序(SOP)或其他文档化程序设定。“在研究中”期间可能被定义为从知情同意的日期/时间到受试者完成研究的日期/时间,或者可能是从第一次给药的日期/时间到最后一次给药的日期/时间。无论“在研究中”期间如何定义,该期间的开始和结束日期(可选时间)必须被收集。
If there is a need to collect information about whether an observation of interest occurred prior to a reference point or milestone other than the beginning of the study, or was ongoing or continuing at some reference point or milestone in the study other than the end of the defined "on study" period, the date/time of that reference point or milestone should also be collected. If this date/time has been collected, reasonable comparisons can be made to that date/time with "prior", "coincident", "continuing", or "ongoing" questions.
如果需要收集有关某个感兴趣的观察是否在研究开始之前的参考点或里程碑发生,或者在研究中某个参考点或里程碑时是否正在进行或持续,应该收集该参考点或里程碑的日期/时间。如果已收集该日期/时间,可以对该日期/时间与“之前”、“同时”、“持续”或“进行中”的问题进行合理比较。
The following steps should be taken to ensure observations of interest that occur over time can be related to the study period or to fixed point in time or a milestone in a meaningful way. Chart 1 below provides a representation of an intervention as it relates to the study reference period, and Charts 2 and 3 provide a representation of comparisons as it relates to other fixed points in time or a milestone.
以下步骤应采取,以确保随时间发生的感兴趣观察可以以有意义的方式与研究期间、固定时间点或里程碑相关联。下面的图表 1 提供了干预与研究参考期间的关系表示,图表 2 和图表 3 提供了与其他固定时间点或里程碑的比较表示。
Study Reference Period (Chart 1)
研究参考期(图表 1)
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Define the "on study" period.(B-C). Once the overall "on study" period has been defined (B-C), collect the dates (/times) of the start of the study reference period (e.g., date of informed consent, date of first dose) and end of the study reference period (e.g., date of last contact, date of last dose), as part of the clinical data with their respective domains (e.g., DS, EX). These dates will map into the RFSTDTC (B) (start of Study Reference Period) and RFENDTC (C) (end of Study Reference Period) variables in the SDTMIG DM dataset.
定义“研究期间”(B-C)。一旦整体“研究期间”被定义(B-C),收集研究参考期开始的日期(时间)(例如,知情同意日期、首次给药日期)和研究参考期结束的日期(时间)(例如,最后联系日期、最后给药日期),作为临床数据的一部分及其各自的领域(例如,DS,EX)。这些日期将映射到 SDTMIG DM 数据集中 RFSTDTC(B)(研究参考期开始)和 RFENDTC(C)(研究参考期结束)变量。 - Collected comparisons ((D, E) using CDASHIG variables (e.g., "prior", "ongoing") of when something started or ended in relation to the "on study" reference period (i.e., RFSTDTC-RFENDTC: (B-C). These CDASH variables are used to populate the SDTMIG variables--STRF and --ENRF variables when the SDTM-based datasets are created. (Note: these relative timing variables are only populated in the SDTM -based datasets when a date is not collected.).
收集的比较((D,E)使用 CDASHIG 变量(例如,“之前”,“进行中”)来表示某事在“研究期间”参考期(即 RFSTDTC-RFENDTC:(B-C))的开始或结束时间。这些 CDASH 变量用于在创建基于 SDTM 的数据集时填充 SDTMIG 变量--STRF 和--ENRF 变量。(注意:这些相对时间变量仅在未收集日期时填充到基于 SDTM 的数据集中。)
Fix point in Time/Milestone (Charts 2, 3)
时间/里程碑的固定点(图表 2, 3)
- Define the fix point in time or milestone (B or C).The fix point in time or milestone can be a date or a description. This will map into either the SDTMIG variables (–STTPT or --ENTPT) when the SDTM-based datasets are created .
定义时间固定点或里程碑(B 或 C)。时间固定点或里程碑可以是一个日期或描述。这将在创建基于 SDTM 的数据集时映射到 SDTMIG 变量(–STTPT 或--ENTPT)。 - Collected comparisons (D or E) using CDASHIG variables (e.g., "prior", "ongoing") of when something started or ended in relation to the fixed point in time or milestone (B or C). These CDASH variables are used to populate the SDTMIG variables--STRTPT or --ENRTPT when the SDTM-based datasets are created.(Note: these relative timing variables are only populated in the SDTM -based datasets when a date is not collected).
收集的比较(D 或 E)使用 CDASHIG 变量(例如,“之前”,“进行中”)来表示某事何时开始或结束,相对于固定时间点或里程碑(B 或 C)。这些 CDASH 变量用于填充 SDTMIG 变量--STRTPT 或--ENRTPT,当创建基于 SDTM 的数据集时。(注意:这些相对时间变量仅在未收集日期时填充到基于 SDTM 的数据集中)。
For information about mapping what is collected in "prior", "ongoing", and "continuing" fields into the appropriate SDTMIG variables, see the SDTMIG V3.2 Section 4.1.4.7.
有关将“先前”、“进行中”和“持续”字段中收集的内容映射到适当的 SDTMIG 变量的信息,请参见 SDTMIG V3.2 第 4.1.4.7 节。
3.8 CDISC Controlled Terminology
3.8 CDISC 控制术语
Submission data standards are required by some global regulators, and controlled terminology (CT) is part of the requirement. Using CT from the start during data collection builds in traceability and transparency, and reduces the problems associated with trying to convert legacy codelists and variables to the submission standards. CT can be used in the following ways during data collection:
提交数据标准是一些全球监管机构所要求的,受控术语(CT)是其中的一部分。在数据收集的初始阶段使用 CT 可以建立可追溯性和透明度,并减少将遗留代码列表和变量转换为提交标准时所遇到的问题。在数据收集过程中,CT 可以以以下方式使用:
- To collect data using a standardized list of values (e.g., Mild, Moderate, Severe)
使用标准化的数值列表(例如:轻度、中度、重度)收集数据 - To ask a specific question on the CRF (e.g., Temperature)
在 CRF 上提出具体问题(例如,温度) - To create a variable name in the database (e.g., TEMP for the collection of vital sign data when a unique variable name must be created for each vital sign result.)
在数据库中创建一个变量名(例如,TEMP,用于收集生命体征数据时,当每个生命体征结果必须创建一个唯一的变量名时)。
Terminology applicable to CDASH data collection fields is either in production or under development by the CDISC Terminology Team. Production terminology is published by the National Cancer Institute's Enterprise Vocabulary Services (NCI EVS) and can be accessed via the following link: http://www.cancer.gov/cancertopics/terminologyresources/CDISC. The examples in this document use CDISC controlled terminology where possible, but some values that seem to be controlled terminology may still be under development at the time of publication, or even especially plausible "best guess" placeholder values. Do not rely on any source other than the CDISC value set in the NCI Thesaurus for controlled terminology.
适用于 CDASH 数据收集字段的术语要么在生产中,要么由 CDISC 术语团队开发中。生产术语由国家癌症研究所的企业词汇服务(NCI EVS)发布,可以通过以下链接访问:http://www.cancer.gov/cancertopics/terminologyresources/CDISC。本文档中的示例尽可能使用 CDISC 控制术语,但一些看似控制术语的值在发布时可能仍在开发中,或者甚至是特别合理的“最佳猜测”占位符值。请不要依赖于 NCI 词库中 CDISC 值集以外的任何来源作为控制术语。
In some cases it is more appropriate to use a subset of a published SDTM terminology list, rather than the entire list. To begin with an established subset of the SDTM terminology, go to https://www.cancer.gov/research/resources/terminology/cdisc and reference the CDASH terminology. These CDASH codelists have been subsetted from the complete SDTM terminology lists and are available to implementers as a way to quickly set up codelists for data collection. However, most implementers will also need to review the SDTM terminology to determine which other values are needed for their particular implementation. The CDASH terminology subset names are provided in the CDASHIG Metadata Table for easy reference.
在某些情况下,使用已发布的 SDTM 术语列表的子集比使用整个列表更为合适。要开始使用已建立的 SDTM 术语子集,请访问 https://www.cancer.gov/research/resources/terminology/cdisc 并参考 CDASH 术语。这些 CDASH 代码列表是从完整的 SDTM 术语列表中提取的,供实施者快速设置数据收集的代码列表。然而,大多数实施者还需要审查 SDTM 术语,以确定其特定实施所需的其他值。CDASH 术语子集名称在 CDASHIG 元数据表中提供,便于参考。
Some codelists, such as Laboratory Test Codes (LBTESTCD), are extensible. This means that values that are not already represented in that list (either as a CDISC Submission Value, a synonym or an NCI preferred term) may be added as needed. Other codelists, such as AE Action Taken with Study Treatment, are non-extensible and must be used without adding any terms to the list. If gaps are indentified, sponsors should submit requests to add values to controlled terminology by using the New Term Request form found at http://ncitermform.nci.nih.gov/ncitermform/?version=cdisc.
某些代码列表,例如实验室测试代码(LBTESTCD),是可扩展的。这意味着可以根据需要添加在该列表中尚未表示的值(无论是作为 CDISC 提交值、同义词还是 NCI 首选术语)。其他代码列表,例如与研究治疗相关的 AE 采取的行动,是不可扩展的,必须在不向列表中添加任何术语的情况下使用。如果发现缺口,赞助商应通过使用位于 http://ncitermform.nci.nih.gov/ncitermform/?version=cdisc 的新术语请求表单提交请求,以将值添加到受控术语中。
In cases where a CDASH/CDASHIG variable has associated controlled terminology, the codelist is referenced in Controlled Terminology column in the CDASH Model and CDASHIG Metadata Table in this format: (codelist name).
在 CDASH/CDASHIG 变量有相关控制术语的情况下,代码列表在 CDASH 模型和 CDASHIG 元数据表的控制术语列中以以下格式引用:(代码列表名称)。
4 Best Practice Recommendations
四个最佳实践建议
CDASH Best Practices describe operational recommendations to support data collection, suggested CRF development workflow, and methods for creating data collections instruments. The first section, Best Practices for Creating Data Collection Instruments, is part of conformance to the CDASH Standard.
CDASH 最佳实践描述了支持数据收集的操作建议、建议的 CRF 开发工作流程以及创建数据收集工具的方法。第一部分,创建数据收集工具的最佳实践,是符合 CDASH 标准的一部分。
4.1 Best Practices for Creating Data Collection Instruments
4.1 创建数据收集工具的最佳实践
Num 数字 | Best Practice Recommendation 最佳实践建议 | Rationale 理由 |
1 |
When a binary response is expected, "Yes/No" responses are preferred over "Check all that apply", because a missing response could lead to a misinterpretation of critical data. For example, if AEs are determined to be serious based only upon checking the applicable serious criteria (e.g., Hospitalization, Congenital Anomaly, etc) failure to check a criterion would potentially delay identification of an SAE. If an assessment has composite responses (e.g., presence or absence of two or more symptoms), "Yes/No" questions for each component response (e.g., symptom) are preferred to "Check all that apply" questions. One exception to this recommendation might be assessments where the majority of options would be answered "No". An example would be the collection of ECG abnormality data where approximately 45 abnormalities may be listed, but only a few will apply. Another exception is when a validated instrument contains checkboxes. In this case, they should remain checkboxes in the CRF or eCRF. Another exception to this recommendation is when there are controlled terminologies governing the values being collected. For example, if collecting RACE using the "check all that apply" option, the RACE values defined by Controlled Terminology should be collected as individual check boxes, and not as a Yes/No response. In cases where the sponsor chooses to use "check all that apply" additional quality checks should be considered (e.g., SDV) to ensure the data collected in the CRF are correct and complete. |
"Yes/No" questions provide a definite answer. The absence of a response is ambiguous as it can mean "No", "None", or that the response is missing. In situations where there is no other dependent or related field by which to gauge the completeness of the field in question, a "Yes/No" response ensures that the data are complete. For example, when an AE End Date is blank, a "Yes" response to the question "Is the AE ongoing?" ensures that the data are complete. When the end date is provided it is not necessary to answer the question "No". |
2 |
The database should contain an indication that a planned exam/assessment was not performed. The mechanism for this may be different from system to system or from paper to EDC. For example, the data collection instrument/CRF could contain a field that allows the site to record an indication that a Vital Sign assessment was not performed (e.g., VSPERF = "N" or TEMP_VSSTAT = "NOT DONE") A "'Yes/No' – assessment completed" question is preferred over the "Check if not done" box, unless the "Check if not done" field can be compared to a completed data field using a validation check to confirm that one or the other has data. |
This will provide a definitive indicator that a data field has missing data and has not been overlooked. This will prevent unnecessary data queries to clarify whether an assessment has been performed. The use of the "Yes/No" format helps to eliminate ambiguity about whether an assessment has been completed. In situations where there is no other dependent or related field to gauge the completeness of the field in question, a "Yes/No" response format should be used to eliminate ambiguity. When another related field is present the "Yes/No" response is optional. For example, when a value for temperature is missing, a simple "Not Done" box may be checked. It is not necessary to respond "Done" when a temperature value is present. |
3 |
Data cleaning prompts should be used to confirm that blank CRFs are intentionally blank. Usually this will be a "Yes/No" question (e.g., AEYN) but it may be a "check if blank" if a validation check can be used to confirm that either the "check if blank" box is checked, or that there are data recorded in the CRF. |
This will provide a definitive indicator that a CRF is blank on purpose and has not been overlooked. This will prevent unnecessary data queries. |
4 | The same data (i.e., the same information at the same time) should not be collected more than once. 相同的数据(即相同时间的相同信息)不应被收集超过一次。 |
Collecting the same data more than once:
|
5 |
A "Check if ongoing" question is recommended to confirm ongoing against an end date. This is a special use case of "Yes/No" where the data entry field may be presented as a single possible response of "Yes" in conjunction with an End Date variable. If the box is checked, the operational variable may contain "Yes". If the box is not checked and the End Date is populated, the value of the variable may be set to "No". For some EDC systems, it may be better to display the possible responses to the "check if ongoing" question as radio buttons. Conditional logic can then be used to solicit the collection of the end date only if the answer to the "Ongoing" question is "N" (No). | For the use case of "Check if ongoing", for the data to be considered "clean", one of the two responses must be present and the other response must be blank. So, the presence of the end date provides confirmation that the event is not ongoing. 对于“检查是否正在进行”的用例,数据要被视为“干净”,必须存在两个响应中的一个,另一个响应必须为空。因此,结束日期的存在确认事件不是正在进行的。 |
6 |
CRFs should use a consistent order of responses (e.g., "Yes/No") from question to question, for questions with response boxes or other standardized lists of values. Exceptions to this would be cases where a validated instrument (e.g., a standardized assessment questionnaire) is used. | A consistent order of response boxes promotes ease of use of the CRF to help reduce data entry errors and to avoid introducing bias or leading the investigator to a desired response. 一致的响应框顺序促进了 CRF 的易用性,有助于减少数据输入错误,并避免引入偏见或引导调查者得到期望的回答。 |
7 | CRF questions and completion instructions should be unambiguous, and should not "lead" the site to answer the question in a particular way. CRF 问题和填写说明应明确无误,不应“引导”现场以特定方式回答问题。 | Data should be collected in a way that does not introduce bias or errors into the study data. Questions should be clear and unambiguous. This includes making sure that the options for answering the question are complete such as providing options for "other" and "none" when applicable. 数据应以不引入偏见或错误的方式收集。问题应清晰明确。这包括确保回答问题的选项是完整的,例如在适用时提供“其他”和“无”的选项。 |
8 |
Collection of dates should use an unambiguous format, such as DD-MON-YYYY, where each part of the date is a unique format: "DD" is the day as a 2-digit numeric value; "MON" is the month as a 3-character letter abbreviation in English, or similar character abbreviation or representation in the local language; and "YYYY" is the year as a 4-digit numeric value. For electronic data capture (EDC), the user may be able to select a date from a calendar, and this would also meet the recommendation for an unambiguous date. If the recommended approach is not adaptable to the local language, a similarly unambiguous format should be used. The method for capturing date values should allow the collection of partial dates, and should use a consistent method or convention for collecting the known date parts to facilitate standard mapping to SDTM. Reference the CDASH Model for standard date variable names. |
Using this data collection format (i.e., DD-MON-YYYY) will provide unambiguous dates. For example, the date "06/08/02" is ambiguous because it can be interpreted as "June 8, 2002" or "August 6, 2002". If subject-completed CRF pages are translated into a local language, the CDASH recommended date format for collection may make translation of the documents easier. Dates are collected in this format, but reformatted and submitted in ISO 8601 format. See the SDTMIG and CDASHIG Section 3.6 for more information about the ISO 8601 format. |
9 |
To eliminate ambiguity, times should be collected with the use of a 24-hour clock, using the HH:MM:SS format for recording times. Use only as many of the HH:MM:SS elements as are needed for a particular field. Sites should be cautioned not to "zero-fill" the time components if they are not known (for example 21:00:00 means "exactly 9 PM", but if the site did not know how many seconds after 9 PM, they should not record the seconds). Subject-completed times may be recorded using a 12-hour clock and an A.M. or P.M. designation. The time would then be transformed to a 24-hour clock in the database. | When times are collected using a 24-hour clock, this eliminates ambiguity and eliminates the need to convert the values from 12-hour to 24-hour clock time when they are converted to ISO 8601 date/time for the SDTM-based datasets. 当时间使用 24 小时制收集时,这消除了歧义,并消除了在将值转换为 ISO 8601 日期/时间以用于基于 SDTM 的数据集时需要将 12 小时制转换为 24 小时制的必要性。 |
10 |
Manually calculated fields should not typically be recorded within the CRF when the raw data on which the calculation is based are recorded in the CRF. An exception is when a treatment and/or study conduct decision should be made based on those calculations. In those cases it may be useful for the calculated field to be recorded within the CRF. It may also be useful to provide the site a step-by-step worksheet to calculate this data. |
Data items that can be calculated from other data captured within the CRF are more accurately reported if they are calculated programmatically using validated algorithms. The noted exception may be in cases where it's important to show how the investigator determined a protocol-defined endpoint from collected raw data. |
11 |
Questions with free text responses should be limited to cases of specific safety or therapeutic need in reporting or analysis, such as Adverse Events, Concomitant Medications, or Medical History, generally in cases where the data will be subsequently coded. Questions should be specific and clear rather than open-ended. Instead of free text comment fields, a thorough review of the CRF by the protocol development team should be performed to maximize the use of pre-defined lists of responses. Refer to the Comments Domain for additional recommendations. |
The collection and processing of free text requires significant resources for data entry: It requires CDM resources to review the text for safety information and for inconsistencies with other recorded data and is of limited use when analyzing and reporting clinical data. Another risk is that sites may enter data into free text fields that should be recorded elsewhere. |
12 | Subject-specific data should be collected and recorded by the site and should not be pre-populated in the CRF/eCRF. 特定主题的数据应由现场收集和记录,不应预先填充在 CRF/eCRF 中。 | The CRF is a tool to collect subject-level data. However, pre-population of some identifying (e.g., investigator name, site identification, protocol number) or timing (e.g., Visit Name) information prevents errors and reduces data entry time.
CRF 是一个收集受试者级别数据的工具。然而,预填充一些识别信息(例如,研究者姓名、地点识别、方案编号)或时间信息(例如,访视名称)可以防止错误并减少数据录入时间。 Fields on the CRF or in the database that are known to be the same for all subjects may be pre-populated (e.g., measurements for which there is only one possible unit, such as Respiratory Rate or Blood Pressure). The units can be displayed on the CRF and populated in the database |
13 | The anatomical location of a measurement, position of subject, or method of measurement should be collected only if the protocol specifies the allowable options, or if the parameter is relevant to the consistency or meaning of the resulting data. 测量的解剖位置、受试者的位置或测量方法应仅在协议指定允许的选项时收集,或者当该参数与结果数据的一致性或意义相关时收集。 |
When a parameter, such as location, position, or method, is specified in a protocol and is part of the analysis, the CRF may include the common options for these parameters to ensure the site can report what actually happened and protocol deviations can be identified. If the parameter is pre-populated on the CRF and other options are not available, then the site should be directed to not record data that was not collected per protocol specifications. Taking measurements in multiple anatomical locations may impact the value of the measurement and/or the ability to analyze the data in a meaningful way (e.g., when data obtained from different locations may bias or skew the analysis). In this case, collecting the location may be necessary to ensure consistent readings. For example, temperature obtained from the ear, mouth, or skin may yield different results. If there is no such rationale for collecting location, position, method, or any other value, it would be considered unnecessary data. Reference Section 4.3, Organizational Best Practices to Support Data Collection, Num 1. |
14 | Sites should record verbatim terms for non-solicited adverse events, concomitant medications, or medical history reported terms. Sites should not be asked to select a preferred term from a coding dictionary as a mechanism for recording data. 站点应逐字记录非自愿不良事件、伴随用药或医疗历史报告的术语。站点不应被要求从编码字典中选择首选术语作为记录数据的机制。 |
When the site records information about spontaneously reported adverse events or medical history, it is best to ask the sites to record responses verbatim, so that no information is omitted. Sites are not expected to be coding experts and are probably not familiar with the coding dictionaries used in clinical research. Having the sites record adverse events from a standardized list is the same as having them code these events. Having multiple sites "coding" data will result in inconsistencies in the coding across sites. See Section 6, Other Information, for more information about collecting data for coding purposes. |
15 |
CRF questions should be as self-explanatory as possible, thereby reducing the need for separate instructions. If required, short instructions may be placed on the CRF page, especially if the Prompt is not specific enough. More detailed instructions may be presented in a CRF completion guideline. All instructions should be concise. Instructions should be standardized as much as possible. |
Putting short instructions and prompts on the CRF increases the probability that they will be read and followed, and can reduce the number of queries and the overall data cleaning costs. Having standard instructions supports all sites using the same conventions for completing the fields. Providing short instructions and prompts on the CRF and moving long instructions to a separate instruction booklet, facing page, or checklist will decrease the number of CRF pages, with the following benefits:
|
16 | An SDTMIG variable name should only be used as a data collection/operational variable name if the collected value will directly populate the SDTMIG variable with no transformation (other than changing case). Otherwise, create a "collected" version of the variable and write a standard mapping to the SDTMIG variable. SDTMIG 变量名称仅应在收集的值将直接填充 SDTMIG 变量且没有任何转换(除了大小写变化)时用作数据收集/操作变量名称。否则,请创建该变量的“收集”版本,并编写标准映射到 SDTMIG 变量。 | This will provide clearer traceability from data collection to submission, and will facilitate a more automated process of transforming collected data to the standardized data tabulations for submission. 这将提供从数据收集到提交的更清晰的可追溯性,并将促进将收集的数据转化为提交的标准化数据表的更自动化的过程。 |
4.2 CRF Design Best Practices
4.2 CRF 设计最佳实践
The recommendations are general principles that may be implemented during CRF form design and/or database set up in different ways, depending on the systems used.
这些建议是一般原则,可以根据使用的系统以不同方式在 CRF 表单设计和/或数据库设置中实施。
Providing the clinical site with a consistent and clinically logical order of these fields will reduce data entry time and result in more reliable data. Therefore, the CRF should be quick and easy for site personnel to complete.
为临床现场提供一致且符合临床逻辑的字段顺序将减少数据录入时间,并提高数据的可靠性。因此,CRF 应该便于现场人员快速、轻松地完成。
Clinical Operations staff should review the CRF for compatibility with common site workflow and site procedures.
临床运营人员应审查 CRF,以确保其与常见现场工作流程和现场程序的兼容性。
Num 数字 | Best Practice Recommendation 最佳实践建议 |
1 | Headings – Place fields that routinely appear on multiple forms at the top of the form. For example, if the collection date and time are both asked, they should appear first and second, respectively, on each form where they are used. 标题 – 在表单顶部放置在多个表单中常规出现的字段。例如,如果同时询问收集日期和时间,它们应分别在每个使用它们的表单中排在第一和第二位。 |
2 | Clinical flow – Fields should be placed on the form in the order that they are expected to be collected during the clinical assessment. It is acceptable to include fields from different domains on the same form if consistent with the clinical flow. 临床流程 - 字段应按照在临床评估中预期收集的顺序放置在表单上。如果与临床流程一致,可以在同一表单上包含来自不同领域的字段。 |
3 | Group related fields for a single clinical encounter together, although multiple time points or visits may appear together on one form. For example, if heart rate and temperature are taken every hour for four hours on Study Day 1, the form can collect the data for Hour 1 (e.g., heart rate result and unit, temperature result and unit), followed by the data for Hour 2, Hour 3, and Hour 4. In this scenario, there would be labels indicating each time point within Study Day 1. 将与单次临床接触相关的字段组合在一起,尽管多个时间点或访问可能在一个表单上一起出现。例如,如果在研究第 1 天每小时测量心率和体温四次,则表单可以收集第 1 小时的数据(例如,心率结果和单位,体温结果和单位),然后是第 2 小时、第 3 小时和第 4 小时的数据。在这种情况下,将有标签指示研究第 1 天的每个时间点。 |
4 |
Group related fields together. Test results and their associated units should always appear next to each other. For example, the results of the "TEMP" should be followed by its allowable units of "F" and "C". In some cases, the result might have only one applicable unit. For example, the only applicable unit for "PULSE" is "beats/min". The unit should be displayed on the CRF and databased. |
5 |
Data fields that are dependent on other data fields should be placed in the CRF in such a way that this dependence is obvious. For example, if there is a question in a paper CRF where "Other, specify" is an option, the text box used to collect what is being specified should be placed in proximity to the "Other" question to indicate that it is a sub-part of the "Other" question. An example of this in an EDC system that requires a specific response in order to render one or more additional, related questions. |
6 | Lists of values that have a logical order should be provided on the CRF in that logical order. For example, the values of "Low", "Medium", and "High" are logically placed in this order. Do not list "Medium" first, "Low" second, and "High" third. 在 CRF 上应按照逻辑顺序提供有逻辑顺序的值列表。例如,“低”、“中”和“高”的值应按此顺序排列。不要将“中”放在第一,“低”放在第二,“高”放在第三。 |
4.3 Organizational Best Practices to Support Data Collection
4.3 支持数据收集的组织最佳实践
Num 数字 | Best Practice Recommendation 最佳实践建议 | Rationale 理由 |
1 |
Collect necessary data only. CRFs should focus on collecting only the data that support protocol objectives and endpoints. The protocol should clearly state which data will be collected in the study |
Usually, only data that will be used for efficacy analysis and to assess safety of the investigational product should be collected on the CRF, due to the cost and time associated with collecting and fully processing the data. However some fields on a CRF may be present to support the eDC functionality and/or review and cleaning of data through automated edit checks. The protocol (and SAP when it is prepared in conjunction with the protocol) should be reviewed to ensure that the parameters needed for analysis are collected and can be easily analyzed. The statistician is responsible for confirming that the CRF collects all of the data necessary to support the analysis. |
2 |
CRF development should be a controlled, documented process that incorporates (as applicable):
CRF development should be controlled by SOPs covering these topics, as well as site training. | A controlled process for developing CRFs will help ensure that CRFs comply with company standards and processes. 一个受控的 CRF 开发过程将有助于确保 CRF 符合公司的标准和流程。 |
3 |
The CRF design process should include adequate review and approval steps, and each reviewer should be informed on the scope of the review they are expected to provide. The team that designs the data collection instruments for a study should be involved in the development of the protocol and should have appropriate expertise represented on the CRF design team, including the following: Medical and Scientific Experts should provide sufficient information to ensure Clinical Data Standards, Standards Subject Matter Experts, and Clinical Data Management (CDM) staff understand the background, context, and medical relevance of the efficacy and/or safety data. Clinical Data Management, Standards Subject Matter Experts, and CRF Designers should review the protocol to ensure that proposed data can be collected, and should ensure that appropriate standards are used to develop the CRF. Statisticians should review the CRF against their planned analyses to make sure all required data will be collected in an appropriate form for those analyses. Clinical Operations Staff should review the CRF to make sure the questions are unambiguous and that requested data can be collected. Programmers should review the CRF to ensure that the manner in which the data are collected on the CRF are consistent with relevant metadata standards. Regulatory Experts should review the CRF for compliance with all applicable regulations. Data Entry Staff should review the CRF to ensure that the data are collected in a form that can be entered accurately. Pharmacovigilance personnel should review to ensure appropriate data capture and process to support expedited reporting. Ideally, the CRF should be developed in conjunction with the protocol (and the SAP if it is available). All research-related data on the CRF should be addressed in the protocol to specify how and when it will be collected. |
Reviewers from different functions increase the probability that the CRF will be easier to complete and support the assessment of safety and efficacy as defined in the protocol and SAP. The CRF design team should ensure that the data can be collected in a manner that is consistent with the implementer's processes and easy for the site to complete. |
4 | Translations of CRFs into other languages should be done under a controlled process by experts who understand both the study questions and the language and culture for which the CRF is being translated. The translation should be a parallel process following the same set of steps with separate reviews and approvals by the appropriate experts. Translations may require author approval and a separate validation of the translated instrument. CRF 的翻译应由了解研究问题以及翻译所针对语言和文化的专家在受控过程中进行。翻译应是一个平行过程,遵循相同的步骤,并由相关专家进行单独的审查和批准。翻译可能需要作者的批准以及对翻译工具的单独验证。 |
CRFs that are translated into other languages should follow the same development process as the original CRF to ensure the integrity of the data collected. Consideration of translation should be part of the CRF development process. Avoid the use of slang or other wording that would complicate or compromise translation into other languages. Cultural and language issues should be addressed appropriately during the process of translating CRFs to ensure the CRF questions have consistent meaning across languages. |
5 |
Data that are collected on CRFs should usually be databased. For some fields, such as "Were there any Adverse Events", the response—in this case "Yes/No"—may need to be databased, but will not be included in the submission data. Some fields, such as Investigator's Signature, can be verified by the data entry staff, but an actual signature may not be databased unless there is an e-signature. |
If certain data are not required in the CRF, but are needed to aid the investigator or monitor, those data should be recorded on a site worksheet (e.g., an entry criteria worksheet or a dose titration worksheet). All such site worksheets should be considered source documents or monitoring tools, and should be maintained at the site with the study files. |
6 | Establish and use standardized case report forms. 建立并使用标准化病例报告表。 |
Using data collection standards across compounds and TAs saves time and money at every step of drug development. Using standards: 使用标准:
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When a binary response is expected, "Yes/No" responsesare preferred over "Check all that apply", becausea missing response could lead to a misinterpretation of critical data. For example, if AEsare determined to be serious based only upon checking the applicable serious criteria (e.g., Hospitalization, Congenital Anomaly, etc.), failure to check a criterion would delay identification of an SAE.
当期望二元响应时,"是/否"的回答比"检查所有适用项"更为优选,因为缺失的响应可能导致对关键数据的误解。例如,如果仅根据勾选适用的严重标准(例如,住院、先天性畸形等)来判断不良事件的严重性,未勾选某一标准将延迟对严重不良事件的识别。
5 Conformance to the CDASH Standard
5 遵循 CDASH 标准
5.1 Conformance Rules 5.1 合规规则
Conformance means that: 符合性意味着:
- Core designations must be followed: All Highly Recommended and applicable Recommended/Conditional Fields must be present in the CRF or available from the operational database.
核心标识必须遵循:所有高度推荐和适用的推荐/条件字段必须在 CRF 中存在或可从操作数据库中获取。 - CDISC Controlled Terminology must be used: The CDISC Controlled Terminology that is included in the CDASHIG Metadata Table must be used to collect the data in the CRF. All codelists displayed in the CRF must use or directly map to the current published CDISC Controlled Terminology submission values, when it is available. Subsets of published Controlled Terminology, such as those provided in CDASH terminology, can be used.
CDISC 控制术语必须使用:在 CRF 中收集数据时,必须使用包含在 CDASHIG 元数据表中的 CDISC 控制术语。CRF 中显示的所有代码列表必须使用或直接映射到当前发布的 CDISC 控制术语提交值(如果可用)。可以使用发布的控制术语的子集,例如 CDASH 术语中提供的子集。- In Findings domains, values from the relevant CDISC Controlled Terminology lists must also be used to create appropriate Question Text, Prompts and/or variable names (e.g., If the question is about the subject's height, incorporate the value of "Height" from the VSTEST codelist as the Prompt on the CRF, and incorporate "HEIGHT" from VSTESTCD in the variable name).
在发现领域中,必须使用相关的 CDISC 控制术语列表中的值来创建适当的问题文本、提示和/或变量名称(例如,如果问题是关于受试者的身高,则在 CRF 上将“Height”从 VSTEST 代码列表中作为提示,并在变量名称中使用“HEIGHT”来自 VSTESTCD)。
- In Findings domains, values from the relevant CDISC Controlled Terminology lists must also be used to create appropriate Question Text, Prompts and/or variable names (e.g., If the question is about the subject's height, incorporate the value of "Height" from the VSTEST codelist as the Prompt on the CRF, and incorporate "HEIGHT" from VSTESTCD in the variable name).
- Best practices must be followed: The design of the CRF must follow the Best Practices for Creating Data Collection Instruments and CRF Design Best Practices.
必须遵循最佳实践:CRF 的设计必须遵循数据收集工具创建的最佳实践和 CRF 设计最佳实践。 - The wording of the CRF questions should be standardized: CDASH Question Text or Prompt must be used to ask the question.
CRF 问题的措辞应标准化:必须使用 CDASH 问题文本或提示来提问。- In cases where the data collection is done in a denormalized presentation on the CRF, the relevant CDISC controlled terminology should be used in the Question Text or Prompt as much as possible. It is acceptable to use synonym text that will directly map to one CDISC Submission Value, including an NCI Preferred Term, if the CDISC Submission Value is not appropriate for data collection. For example, "ALT" may be better than "Alanine Aminotransferase" as the prompt for this lab test. If there is no CDISC Controlled Terminology available, the Question Text or Prompt must be standardized by the implementing organization and used consistently. One of the basic purposes of CDASH is to reduce unnecessary variability between CRFs and to encourage the consistent use of variables to support semantic interoperability; therefore, Question Text and Prompt must be used verbatim.
在数据收集以非规范化形式在 CRF 上进行的情况下,应尽可能在问题文本或提示中使用相关的 CDISC 控制术语。如果 CDISC 提交值不适合数据收集,可以使用直接映射到一个 CDISC 提交值的同义词文本,包括 NCI 首选术语。例如,对于这个实验室测试,"ALT"可能比"丙氨酸氨基转移酶"更合适作为提示。如果没有可用的 CDISC 控制术语,问题文本或提示必须由实施组织进行标准化并保持一致。CDASH 的基本目的之一是减少 CRF 之间不必要的变异性,并鼓励一致使用变量以支持语义互操作性;因此,问题文本和提示必须逐字使用。 - Similarly, where SDTMIG variables may exist in the operational database and the value conforms to Controlled Terminology, it is permissible to use a familiar synonym on the CRF without affecting conformance. An example may be on the Demographics page where SEX may be displayed as "Male" or "Female", while in the operational database, the controlled terminology values of "M" and "F" would be used.
同样,在操作数据库中可能存在 SDTMIG 变量且其值符合受控术语的情况下,可以在 CRF 上使用熟悉的同义词而不影响符合性。例如,在人口统计页面上,性别可以显示为“男性”或“女性”,而在操作数据库中,则使用受控术语值“M”和“F”。 - In some cases, CDASH Questions Text and Prompt allow for flexibility while still being considered conformant. See section 2.3 CRF Development Overview for further details on the usage of Question Text and Prompt.
在某些情况下,CDASH 问题文本和提示允许灵活性,同时仍被视为符合标准。有关问题文本和提示使用的更多详细信息,请参见第 2.3 节 CRF 开发概述。 - The CDASH Model Question Text may contain options for the tense, but if the option is not provided, the tense of the Question Text may be modified to reflect the needs of the study.
CDASH 模型问题文本可能包含时态选项,但如果未提供选项,问题文本的时态可能会根据研究的需要进行修改。 - For cases where the Question Text or Prompt cannot be used due to culture or language, or a CRF must be translated for language or cultural reasons, the implementer must ensure the translation is semantically consistent with the CDASH Question Text and Prompt in the CDASHIG Metadata Table.
对于因文化或语言原因无法使用问题文本或提示的情况,或者由于语言或文化原因必须翻译 CRF 的情况,实施者必须确保翻译在语义上与 CDASHIG 元数据表中的 CDASH 问题文本和提示保持一致。 - In cases where a more specific question needs to be asked than what is provided by Question Text or Prompt, CDASH recommends the use of a brief CRF Completion Instruction, as long as the instruction clarifies the data required by the study without altering the meaning of variable as defined by the standard. For example "Sex at birth" is not the same question as "Sex" (which is loosely defined as "reported sex").
在需要提出比问题文本或提示更具体的问题的情况下,CDASH 建议使用简短的 CRF 填写说明,只要该说明能够澄清研究所需的数据而不改变标准所定义的变量的含义。例如,“出生时性别”与“性别”并不是同一个问题(后者被宽泛定义为“报告的性别”)。
- In cases where the data collection is done in a denormalized presentation on the CRF, the relevant CDISC controlled terminology should be used in the Question Text or Prompt as much as possible. It is acceptable to use synonym text that will directly map to one CDISC Submission Value, including an NCI Preferred Term, if the CDISC Submission Value is not appropriate for data collection. For example, "ALT" may be better than "Alanine Aminotransferase" as the prompt for this lab test. If there is no CDISC Controlled Terminology available, the Question Text or Prompt must be standardized by the implementing organization and used consistently. One of the basic purposes of CDASH is to reduce unnecessary variability between CRFs and to encourage the consistent use of variables to support semantic interoperability; therefore, Question Text and Prompt must be used verbatim.
- Variable Names: The CDASHIG variable naming conventions should be used in the operational database, using a consistent syntax that includes the root variable name and/or controlled terminology, and any other standardized concepts that are needed to support efficient mapping of the collected value to SDTM datasets. The goals are to have beginning-to-end traceability of the variable name from the data capture system to the SDTM datasets, and to support automating electronic data capture (EDC) setup and downstream processes.
变量名称:应在操作数据库中使用 CDASHIG 变量命名约定,采用一致的语法,包括根变量名称和/或受控术语,以及支持将收集的值有效映射到 SDTM 数据集所需的其他标准化概念。目标是实现从数据捕获系统到 SDTM 数据集的变量名称的端到端可追溯性,并支持自动化电子数据捕获(EDC)设置和下游流程。- It is recognized that particularly in an EDC system, the variable name of a data collection field, as well as the name in the underlying database, may have various "system" components that become part of the item's identifier. EDC systems, prior to exporting data in a defined format, may require the variable name to include such database "references" as the EDC page name, the item "group" name, or perhaps a combination.
在电子数据采集(EDC)系统中,数据收集字段的变量名称以及底层数据库中的名称可能包含各种“系统”组件,这些组件成为项目标识符的一部分。EDC 系统在以定义格式导出数据之前,可能要求变量名称包含这些数据库“引用”,例如 EDC 页面名称、项目“组”名称或它们的组合。 - In cases where the data collection is done in a denormalized way, appropriate CDISC controlled terminology must be used when it is available. For example, when collecting Vital Signs results in a denormalized eCRF, the variable names can be created by using terms from the Vital Signs Test Code codelist. For example, Temperature result can be collected in a variable called TEMP or TEMP_VSORRES, Systolic Blood Pressure result, can be collected in a variable called SYSBP or SYSBP_VSORRES. When a particular system's constraints limit the variable name to 8 characters, a similar, consistent implementation that preserves either the normalized root variable (e.g., ORRES) or the controlled terminology (e.g., --TESTCD value) should be implemented.
在数据收集以非规范化方式进行的情况下,必须在可用时使用适当的 CDISC 控制术语。例如,在非规范化的电子病例报告表(eCRF)中收集生命体征结果时,可以使用生命体征测试代码代码表中的术语来创建变量名称。例如,温度结果可以收集在名为 TEMP 或 TEMP_VSORRES 的变量中,收缩压结果可以收集在名为 SYSBP 或 SYSBP_VSORRES 的变量中。当特定系统的限制将变量名称限制为 8 个字符时,应实施类似且一致的实现,以保留规范化的根变量(例如,ORRES)或控制术语(例如,--TESTCD 值)。 - Whereas all CDASHIG defined variable names are 8 characters or less to accommodate SDTM limits on variable names, QNAMs, and --TESTCDs, the maximum length of a variable name that may be implemented is determined by the data management system used, not by CDASH.
由于所有 CDASHIG 定义的变量名称都限制在 8 个字符以内,以适应 SDTM 对变量名称、QNAM 和--TESTCD 的限制,因此可实施的变量名称的最大长度由所使用的数据管理系统决定,而不是由 CDASH 决定。
- It is recognized that particularly in an EDC system, the variable name of a data collection field, as well as the name in the underlying database, may have various "system" components that become part of the item's identifier. EDC systems, prior to exporting data in a defined format, may require the variable name to include such database "references" as the EDC page name, the item "group" name, or perhaps a combination.
- Data Values and Format: Because an SDTM data programmer should be able to assume that data in an SDTMIG variable is SDTMIG compliant, the data output by the operational database into an SDTMIG variable ideally requires no additional processing. Minimal processing (e.g., changing case) is still conformant. This helps to ensure a quality deliverable, even if the SDTM data programmer is unfamiliar with data capture practices.
数据值和格式:因为 SDTM 数据程序员应该能够假设 SDTMIG 变量中的数据符合 SDTMIG 标准,所以操作数据库输出到 SDTMIG 变量的数据理想情况下不需要额外处理。最小的处理(例如,改变大小写)仍然是符合要求的。这有助于确保交付物的质量,即使 SDTM 数据程序员对数据采集实践不熟悉。 - Questionnaires: In order to maintain the validity of a validated instrument, studies that include validated questionnaires, ratings, or scales must present the questions and reply choices in the manner in which these were validated. (Reference QRS - Questionnaires, Ratings and Scales).
问卷:为了保持经过验证的工具的有效性,包含经过验证的问卷、评分或量表的研究必须以这些工具被验证的方式呈现问题和回复选项。(参考 QRS - 问卷、评分和量表)。- In some cases, this may result in CRFs that do not conform to CDASH Best Practices; however, restructuring these questionnaires should not be done because it could invalidate them.
在某些情况下,这可能导致 CRF 不符合 CDASH 最佳实践;然而,不应重组这些问卷,因为这可能使其失效。 - The use of such questionnaires in their native format should not be considered to affect conformance to CDASH.
使用这些问卷的原始格式不应被视为影响对 CDASH 的符合性。
- In some cases, this may result in CRFs that do not conform to CDASH Best Practices; however, restructuring these questionnaires should not be done because it could invalidate them.
Implementers must determine what additional data fields to add to address study-specific and therapeutic area requirements, and applicable regulatory and business practices. Refer to CDASHIG Section 3.4 (How to Create New Data Collection Fields When No CDASHIG Field Has Been Defined) for more information on how to create data collection fields that have not already been described in this implementation guide.
实施者必须确定需要添加哪些额外的数据字段,以满足特定研究和治疗领域的要求,以及适用的监管和商业实践。有关如何创建在本实施指南中尚未描述的数据收集字段的更多信息,请参阅 CDASHIG 第 3.4 节(如何在未定义 CDASHIG 字段时创建新的数据收集字段)。
6 Other Information 6 其他信息
6.1 Form Level CRF Instructions
6.1 表单级 CRF 指示
完工指令的一般设计考虑事项
Whenever possible, details related to the completion of a single field should be placed with the field itself on the CRF. If this is not possible due to the medium and/or system being used to create the CRFs, then it is permissible to include the field-level instructions at the top of the form, in what is generally considered the form-level instruction area. In some cases, such as when the form-level instructions are very lengthy or include graphics or flowcharts, a separate CRF completion instruction guideline may be required.
每当可能时,与单个字段完成相关的细节应与该字段本身放在 CRF 上。如果由于创建 CRF 所使用的媒介和/或系统无法做到这一点,则可以在表单顶部包含字段级说明,这通常被视为表单级说明区域。在某些情况下,例如当表单级说明非常冗长或包含图形或流程图时,可能需要单独的 CRF 完成说明指南。
General Content Considerations for Completion Instructions
完成说明的一般内容考虑事项
When creating form-level instructions for a CRF, the following points should be considered:
在为 CRF 创建表单级说明时,应考虑以下几点:
- The instructions should include clear references to the time period for which data are to be reported for the study, or to specific time windows that are allowed.
说明应包括对研究中要报告数据的时间段或允许的特定时间窗口的明确参考。 - The instructions should provide references to protocol sections for the specifics of and/or limitations on the data to be reported.
说明应提供对协议部分的参考,以便具体说明要报告的数据的细节和/或限制。 - The instructions should include any special instructions for additional reporting or actions required beyond what is collected on the CRF.
说明应包括任何关于额外报告或在 CRF 上收集的内容之外所需采取的行动的特别说明。 - The instructions should include considerations on how data collected on one CRF might have an impact on data that are reported on a different CRF.
说明应包括对在一个 CRF 上收集的数据如何影响在另一个 CRF 上报告的数据的考虑。 - The instructions should refer to any other forms that are related to the CRF being completed.
说明应提及与正在填写的 CRF 相关的任何其他表格。
6.2 General Recommendations on Screen Failures
6.2 屏幕故障的一般建议
如果赞助方选择,筛选失败数据是指那些未能通过筛选且未随后入组研究的受试者所收集的数据。ICH E3 的第 10.1 节描述了临床研究报告中受试者处置的报告。这一节指出,提供筛选纳入患者的数量以及在筛选过程中排除患者的原因细分可能是“相关的,如果这有助于澄清最终药物使用的适当患者群体。”尽管筛选失败数据可能并不适用于所有研究,但建议根据方案和药物开发计划的需要收集筛选失败数据。及时收集筛选失败数据也可以用于识别导致入组挑战的资格标准。
Using CDASH, the minimum data to be collected should include a subject identifier and reason(s) for screen failure. Typically, there is a reason on the End of Study form indicating "Screen Failure". This information allows overall summarization of all subjects screened/enrolled and when captured, provides easy subject accountability for the Clinical Study Report. Other data may be considered for collection, such as date of informed consent, sex, race, date of birth or age, or other data to further describe the reason for ineligibility (e.g., the lab value that was out of range).
使用 CDASH,收集的最少数据应包括受试者标识符和筛选失败的原因。通常,在研究结束表格上会有一个指示“筛选失败”的原因。这些信息允许对所有筛选/入组的受试者进行总体汇总,并在捕获时为临床研究报告提供便捷的受试者责任追踪。还可以考虑收集其他数据,例如知情同意日期、性别、种族、出生日期或年龄,或其他数据以进一步描述不合格的原因(例如,超出范围的实验室值)。
SDTMIG does not provide a separate domain specifically for screen failure data and does not require that the screen failure data be included in SDTM. Data for screen failure subjects, if submitted, should be included in the appropriate SDTMIG domains. Refer to the SDTMIG for further guidance on submitting Screen Failure data.
SDTMIG 没有提供专门用于筛选失败数据的单独领域,也不要求将筛选失败数据包含在 SDTM 中。如果提交筛选失败受试者的数据,应将其包含在适当的 SDTMIG 领域中。有关提交筛选失败数据的进一步指导,请参阅 SDTMIG。
6.3 Standardized Coding of Collected Data
6.3 收集数据的标准化编码
数据收集以促进编码
Adverse Events, Medical History, and Prior and Concomitant Medications are often coded to standard dictionaries (thesauri). There are many coding dictionaries, but this section will focus on the Medical Dictionary for Regulatory Activities (MedDRA®) and the World Health Organization Drug Dictionary (WHO-DD) as examples, since these are common coding dictionaries.
不良事件、病史以及之前和同时使用的药物通常会被编码到标准词典(同义词库)。有许多编码词典,但本节将重点介绍医疗监管活动词典(MedDRA®)和世界卫生组织药物词典(WHO-DD)作为例子,因为这些是常见的编码词典。
The SDTMIG variable AEDECOD is the dictionary-derived text description of AETERM (the reported term for the adverse event) or AEMODIFY (the modified reported term). When coding with MedDRA®, the AEDECOD is the Preferred Term and is a required variable. Corresponding SDTMIG variables CMDECOD (for medications) and MHDECOD (for medical history items) are permissible SDTMIG variables. These are the equivalent of the preferred term in the dictionary used for coding, and when data are coded these SDTMIG variables should be provided.
SDTMIG 变量 AEDECOD 是从字典派生的 AETERM(不良事件的报告术语)或 AEMODIFY(修改后的报告术语)的文本描述。在使用 MedDRA®编码时,AEDECOD 是优选术语,并且是必需变量。相应的 SDTMIG 变量 CMDECOD(用于药物)和 MHDECOD(用于病史项目)是允许的 SDTMIG 变量。这些变量相当于用于编码的字典中的优选术语,当数据被编码时,这些 SDTMIG 变量应提供。
These --DECOD variables are not necessarily collected on CRFs. They are often determined from other collected variables (e.g., AETERM, CMTRT, and MHTERM). Conventions adopted in the collection of these reported terms can have an impact on the resulting --DECOD variables. If collected on a CRF, --DECOD values would be selected from sponsor-defined or CDISC controlled terminology.
这些 --DECOD 变量不一定在 CRF 上收集。它们通常是从其他收集的变量(例如 AETERM、CMTRT 和 MHTERM)中确定的。收集这些报告术语时采用的惯例可能会影响最终的 --DECOD 变量。如果在 CRF 上收集,--DECOD 值将从赞助商定义或 CDISC 控制的术语中选择。
CRF Designers should consult with medical coders, review relevant documentation, and ensure that all elements needed to facilitate the coding process are collected.
CRF 设计师应与医疗编码员咨询,审查相关文档,并确保收集所有促进编码过程所需的元素。
Coding Adverse Events and Medical History Items
编码不良事件和病史项目
Data managers are encouraged to enter into discussion with coding specialists and medical staff to develop guidance to sites in accordance with applicable coding conventions and other company/project agreements and requirements.
数据管理人员被鼓励与编码专家和医疗人员进行讨论,以根据适用的编码规范和其他公司/项目协议及要求,为各个站点制定指导方针。
Reported terms are often coded without other information for the subject. Therefore, sites should be advised that "nothing can be assumed", and that the reported term should include all information relevant to the event being reported. For example, if "Congestion" is reported as an adverse event for a particular subject, together with several other pulmonary events, the coder cannot assume that the congestion is "Lung congestion", rather than congestion of some other organ (e.g., nose, ear, etc.). The reported term "Congestion" will need to be queried before it can be coded.
报告的术语通常在没有其他信息的情况下进行编码。因此,应该告知各个站点“不能假设任何事情”,并且报告的术语应包括与所报告事件相关的所有信息。例如,如果“充血”被报告为某个特定受试者的不良事件,并且还有其他几个肺部事件,编码者不能假设充血是“肺充血”,而不是其他器官(例如,鼻子、耳朵等)的充血。报告的术语“充血”在编码之前需要进行查询。
Medications 药物
With regard to medications, the CDASH standard offers some guidance on the recording of medication names and on the use of additional Recommended/Conditional data collection fields (e.g., CMROUTE, CMINDC) to facilitate coding. See CDASHIG Section 8.1.1, Assumptions for Interventions Domains.
关于药物,CDASH 标准提供了一些关于记录药物名称的指导,以及使用额外的推荐/条件数据收集字段(例如,CMROUTE,CMINDC)以便于编码。请参见 CDASHIG 第 8.1.1 节,干预领域的假设。
The purpose of coding medications is usually to provide a "Standardized Medication Name" (CMDECOD) and a "Medication Class" (CMCLAS). Most dictionaries facilitate the derivation of the Standardized Medication Name on identification of the medication that was taken and the reason taken.
编码药物的目的是通常提供“标准化药物名称”(CMDECOD)和“药物类别”(CMCLAS)。大多数字典通过识别所服用的药物及其服用原因来帮助推导标准化药物名称。
It would be preferable to collect all active ingredients of a particular medication. In a clinical trial, however, this is impractical. There are numerous CRF design possibilities. When designing a collection tool, it is critical to ensure that the details appropriate to the trial and the sponsor's coding requirements are included. For example, betamethasone dipropionate is used topically; however, if the site records only betamethasone (which can be administered orally, as drops, or inhaled), the topical route of the drug will be lost. In this case, collecting route of administration (CMROUTE) or the indication (CMINDC) would provide the additional information needed to code this medication.
最好收集特定药物的所有活性成分。然而,在临床试验中,这并不实际。CRF 设计有许多可能性。在设计收集工具时,确保包含与试验和赞助商编码要求相关的细节至关重要。例如,倍氯米松二丙酸酯是用于局部的;然而,如果现场仅记录倍氯米松(可以口服、滴眼或吸入),则药物的局部给药途径将会丢失。在这种情况下,收集给药途径(CMROUTE)或适应症(CMINDC)将提供编码该药物所需的额外信息。
In summary, when medications are to be coded, the indication (CMINDC) and route (CMROUTE) or anatomical location (CMLOC) should be collected along with the medication name.
总之,在对药物进行编码时,应收集指示(CMINDC)和途径(CMROUTE)或解剖位置(CMLOC),以及药物名称。
7 CDASH Special-Purpose Domains
7 CDASH 特殊用途领域
The SDTMIG includes three types of special-purpose datasets:
SDTMIG 包括三种特殊用途的数据集:
- Domain datasets (Demographics (DM), Comments (CO), Subject Elements (SE), and Subject Visits (SV) which contain subject-level data.
领域数据集(人口统计(DM)、评论(CO)、主题元素(SE)和主题访问(SV),其中包含主题级数据。 - Trial Design Model (TDM) datasets which contain trial-level data.
试验设计模型(TDM)数据集,其中包含试验级数据。 - Relationship datasets 关系数据集
These datasets are described in SDTMIG Section 2.3. CDASH does not currently contain information on Trial Design Model, or Relationship datasets. CDASH standards are for collection of subject-level data, therefore the collection of Trial Design domains is out of the scope for CDASH. CDASHIG contains information on these Special-Purpose Domains: Demographics (DM), and Comments (CO).
这些数据集在 SDTMIG 第 2.3 节中进行了描述。CDASH 目前不包含试验设计模型或关系数据集的信息。CDASH 标准用于收集受试者级别的数据,因此试验设计领域的收集超出了 CDASH 的范围。CDASHIG 包含有关这些特殊用途领域的信息:人口统计(DM)和评论(CO)。
7.1 General CDASH Assumptions for Special-Purpose Domains
7.1 特殊用途领域的一般 CDASH 假设
- Each study must include the Demographics domain.
每个研究必须包括人口统计学领域。 - CDASH does not currently contain metadata information on SDTM Special-Purpose Domains (Subject Elements (SE) and Subjects Visits (SV)). The SDTM SE and SV domains are commonly derived/created during the SDTM dataset creation process. Each implementer has to determine the best practice within their organization for creating visits and collecting the information on any unplanned visits. See the SDTMIG Section 5 Subject Elements and Subject Visits for more information.
CDASH 目前不包含关于 SDTM 特殊用途域(受试者元素(SE)和受试者访视(SV))的元数据。SDTM SE 和 SV 域通常是在 SDTM 数据集创建过程中派生/创建的。每个实施者必须在其组织内确定创建访视和收集任何未计划访视信息的最佳实践。有关更多信息,请参见 SDTMIG 第 5 节受试者元素和受试者访视。
7.2 CO - Comments 7.2 CO - 评论
Description/Overview for the CDASHIG CO - Comments Domain
CDASHIG CO - 评论领域的描述/概述
The CDASH IG Comments (CO) domain describes free text collected alongside other data on typical case report form (CRF) pages such as Adverse Events, when there is not a specified variable for the free text. The CDASHIG CO domain has no mandatory data elements for inclusion in a separate Comments CRF, and the recommendation is to avoid the creation of a General Comments CRF.
CDASH IG 评论 (CO) 领域描述了在典型的病例报告表 (CRF) 页面上收集的自由文本,这些页面包括不良事件,当没有为自由文本指定变量时。CDASHIG CO 领域没有强制性数据元素需要包含在单独的评论 CRF 中,建议避免创建一般评论 CRF。
Specification for the CDASHIG CO - Comments Domain
CDASHIG CO - 评论领域规范
Comments (CO) 评论 (CO)
Assumptions for the CDASHIG CO - Comments Domain
CDASHIG CO - 评论领域的假设
Solicited Comments versus Unsolicited Comments
征求意见与非征求意见
Solicited comments are defined as those comments entered in free-text data collection fields (such as "Please comment") that are intentionally included on the CRFs. These data collection fields provide the site with a pre-defined space to further explain or clarify an associated record within the CRF. For example, the Vital Signs CRF may include a solicited comment data collection field that enables recording of free text, such as "reason for performing assessment out of window".
征求意见被定义为在自由文本数据收集字段(例如“请评论”)中输入的评论,这些字段是故意包含在 CRF 中的。这些数据收集字段为现场提供了一个预定义的空间,以进一步解释或澄清 CRF 中的相关记录。例如,生命体征 CRF 可能包括一个征求意见的数据收集字段,允许记录自由文本,例如“在窗外进行评估的原因”。
Unsolicited comments are those comments entered outside of pre-defined data collection fields (also referred to as "marginal" comments as they are sometimes written in margins of paper CRFs). These may include marginal CRF comments written by site staff, notes written by the subject on paper diaries, or additional information collected through an eDC system function which collects comments that are not included as data collection fields on the eCRF. Although such comments may be intended to reduce queries, in practice they often lead to clinical data not being entered into the correct data collection field and may cause additional work in the data management process. The collection of unsolicited comments should be discouraged. If they are allowed, they should be reviewed and resolved during the conduct of the study.
未经请求的评论是指在预定义数据收集字段之外输入的评论(也称为“边际”评论,因为它们有时写在纸质 CRF 的边缘)。这些可能包括由现场工作人员撰写的边际 CRF 评论、受试者在纸质日记上写的笔记,或通过 eDC 系统功能收集的额外信息,这些信息并未包含在 eCRF 的数据收集字段中。尽管这些评论可能旨在减少查询,但实际上它们往往导致临床数据未输入到正确的数据收集字段中,并可能在数据管理过程中造成额外的工作。应当不鼓励收集未经请求的评论。如果允许收集,应在研究进行期间进行审查和解决。
Some unsolicited comments may be intended to avoid queries, for example "subject visit was delayed due to his holidays", and may not be regarded as clinical data. When these comments are permitted during data collection, the sponsor should have a process by which the comments are reviewed and processed. This should include a method to query and move relevant data to the appropriate form.
一些未经请求的评论可能旨在避免查询,例如“由于他的假期,主题访问被延迟”,并可能不被视为临床数据。当在数据收集期间允许这些评论时,赞助商应有一个审核和处理评论的流程。这应包括一种查询和将相关数据转移到适当表单的方法。
The Investigative site should be trained to enter clinical data in the appropriate data collection fields rather than making marginal notes on the CRF, and to use appropriate methods and tools to communicate to the monitor information that should not be included in the clinical data.
调查地点应接受培训,以在适当的数据收集字段中输入临床数据,而不是在 CRF 上做边注,并使用适当的方法和工具向监查员传达不应包含在临床数据中的信息。
Free Text versus Value List Fields
自由文本与值列表字段
Clinical data must be entered in appropriate data collection fields; otherwise, there is a potential for data that should be entered on other CRFs to be hidden within the comment. For example, if a general comment of "subject visit was delayed as he had the flu" was captured, this would necessitate that someone review the data and query the site to enter "flu" in an Adverse Event CRF and not leave it as a comment. An additional concern with free text comments is the potential for inappropriate, or sensitive, information to be included within general comments data collection fields. For example, a comment could contain a subject's name or may have unblinding information.
临床数据必须输入到适当的数据收集字段中;否则,可能会导致应在其他 CRF 上输入的数据隐藏在评论中。例如,如果记录了一条一般评论“受试者的访问因他得了流感而延迟”,这将需要有人审核数据并询问现场在不将其作为评论的情况下在不良事件 CRF 中输入“流感”。自由文本评论的另一个问题是可能在一般评论数据收集字段中包含不当或敏感信息。例如,评论可能包含受试者的姓名或可能有揭盲信息。
Free text comments are also inefficient for processing due to their variable and unstructured nature; they offer limited or no value for statistical analysis, as they cannot be tabulated.
自由文本评论由于其可变和非结构化的特性,在处理上也效率低下;它们对统计分析的价值有限或没有价值,因为无法进行表格化。
CRF development teams are encouraged to strive for data collection methods that maximize the use of pre-defined lists of responses rather than relying solely on free text comment fields. The recommendation is that CRF development teams consider what additional questions may be needed within a specific CRF, and what the typical responses would be. They can then create a standardized list of responses for those questions, and make the data collected more useful for analysis.
CRF 开发团队被鼓励努力采用数据收集方法,最大限度地利用预定义的响应列表,而不是仅仅依赖自由文本评论字段。建议 CRF 开发团队考虑在特定 CRF 中可能需要哪些额外问题,以及典型的响应是什么。然后,他们可以为这些问题创建一个标准化的响应列表,使收集的数据对分析更有用。
Considerations Regarding Usage of a General Comments CRF
关于使用一般评论 CRF 的考虑事项
Solicited comments often used to be collected on a General Comments CRF. In recent years though, most organizations have discontinued this practice.
征求的意见通常会在一般意见 CRF 上收集。然而近年来,大多数组织已停止这一做法。
The CDASHIG CO domain has no mandatory data elements and is not intended to encourage the creation of a General Comments CRF. The CDASHIG recommends against the use of a General Comments CRF. This recommendation is not meant to discourage investigators from providing unsolicited comments where they are appropriate, nor to discourage solicited free-text comment data collection fields that may appear within any CRF. Free text comment fields should be used to solicit comments where they are needed. When comments are collected, they should use a variable naming convention that is conformant to CDASH (e.g., COVAL may be used in any CRF because it is part of the SDTMIG specification).
CDASHIG CO 领域没有强制性数据元素,并不旨在鼓励创建一般评论 CRF。CDASHIG 不建议使用一般评论 CRF。此建议并不意味着要阻止研究人员在适当的情况下提供主动评论,也不阻止在任何 CRF 中出现的征求自由文本评论数据收集字段。自由文本评论字段应在需要时用于征求评论。当收集评论时,应使用符合 CDASH 的变量命名约定(例如,COVAL 可以在任何 CRF 中使用,因为它是 SDTMIG 规范的一部分)。
Example CRF for the CDASHIG CO - Comments Domain
示例 CRF 用于 CDASHIG CO - 评论领域
This CRF shows the use of a targeted comment to collect the reason a PK sample was drawn more than 5 minutes late.
此 CRF 显示了使用针对性评论来收集 PK 样本延迟超过 5 分钟的原因。
Example 1 示例 1
Example CRF Completion Instructions
示例 CRF 填写说明
- Record the actual collection times
记录实际收集时间 - If the sample was drawn more than 5 minutes late, provide an explanation in the appropriate comment area.
如果样本延迟超过 5 分钟采集,请在适当的评论区域提供解释。
Were blood sample draws performed? 血样采集是否进行了? PCPERF |
Ο Yes NOT SUBMITTED 哦 是的 未提交
Ο No PCSTAT = NOT DONE
没有 PCSTAT = 未完成 |
Collection Date 收集日期 PCDTC PCDAT | _ _ / _ _ _ / _ _ _ _ |
Pre-Dose (Defaulted) 预剂量(默认) PCTPT | Sponsor Defined 赞助商定义 |
Pre-Dose Time 给药前时间 PCDTC PCTIM |
_ _ : _ _ If late, comment _______________ |
30 Minutes Post Dose (Defaulted) 给药后 30 分钟(默认) PCTPT | Sponsor Defined 赞助商定义 |
30 Minutes Post Dose Time 给药后 30 分钟 PCDTC PCTIM |
_ _ : _ _ If late, comment _______________ |
90 Minutes Post Dose (Defaulted) 90 分钟给药后(默认) PCTPT | Sponsor Defined 赞助商定义 |
90 Minutes Post Dose Time 给药后 90 分钟 PCDTC PCTIM |
_ _ : _ _ If late, comment _______________ |
This CRF is only an example and is not meant to imply that any particular layout or collection plan is preferable over another.
此 CRF 仅为示例,并不意味着任何特定的布局或收集计划优于其他。
CRF 注释以显示映射。SDTMIG 中定义的变量为红色。如果 CDASHIG 变量与 SDTMIG 中定义的变量不同,则 CDASHIG 变量为灰色。收集的数据但未在基于 SDTM 的数据集中提交的,标记为未提交。
Annotated CRFs are best understood in conjunction with their respective metadata. Consult the CDASHIG Metadata Table for mapping details.
注释的条件随机场(CRFs)最好与其相应的元数据一起理解。请查阅 CDASHIG 元数据表以获取映射详细信息。
The example CRFs do not include the Highly Recommended header variables. The population of these values are usually determined by each sponsor's data management system.
示例 CRF 不包括强烈推荐的头部变量。这些值的来源通常由每个赞助商的数据管理系统确定。
Sponsors are responsible for understanding and implementing CDISC Controlled Terminology where applicable.
赞助商有责任理解和实施适用的 CDISC 受控术语。
Example Data for the CDASHIG CO - Comments Domain
CDASHIG CO - 评论领域的示例数据
Examples are not available at this time.
目前没有可用的示例。
7.3 DM - Demographics 7.3 DM - 人口统计
Description/Overview for the CDASHIG DM - Demographics Domain
CDASHIG DM - 人口统计领域的描述/概述
The Demographics (DM) CDASHIG domain includes essential data collection fields that describe each subject in a clinical study. The collection of some demographics data is useful to perform simple analyses based upon population stratification.
人口统计(DM)CDASHIG 领域包括描述临床研究中每个受试者的基本数据收集字段。收集一些人口统计数据对于基于人群分层进行简单分析是有用的。
Privacy concerns surrounding the DM & SC data were taken into account when these domains were created. For example, there are optional CDASHIG variables to collect the components of birthdate (e.g., BRTHDD, BRTHMO, and BRTHYY); therefore, limited elements of birthday may be collected and later mapped to the SDTMIG variable BRTHDTC. This approach provides flexibility in categorizing some variables to facilitate compliance with local privacy issues.
在创建这些领域时,考虑了与 DM 和 SC 数据相关的隐私问题。例如,有可选的 CDASHIG 变量用于收集出生日期的组成部分(例如,BRTHDD、BRTHMO 和 BRTHYY);因此,可以收集有限的生日元素,并随后映射到 SDTMIG 变量 BRTHDTC。此方法在对某些变量进行分类时提供了灵活性,以便符合当地的隐私问题。
Collection of Age versus Date of Birth
年龄与出生日期的集合
It is recognized that sponsors may collect the Age or Date of Birth of the subject. In studies that are multi-regional, sponsors may need to enable the collection of either in order to be compliant to local regulations. But only one or the other should be collected for any given subject. When only AGE is collected, the sponsor is left with a window of uncertainty of, at most, 365 days. Knowing the precise date of birth provides the ability to calculate accurately an age for any date, however a precise (and complete) date of birth may be seen as "personally identifying information" for some privacy oversight boards or governmental regulators.
赞助商可能会收集受试者的年龄或出生日期是被认可的。在多地区的研究中,赞助商可能需要启用其中一种收集方式,以遵守当地法规。但对于任何特定受试者,只应收集其中一种。当仅收集年龄时,赞助商面临的最大不确定性为 365 天。知道确切的出生日期可以准确计算任何日期的年龄,然而,对于某些隐私监督机构或政府监管机构来说,确切(和完整)的出生日期可能被视为“个人识别信息”。
Collect the date of birth to the extent that the local regulatory authorities will allow.
收集出生日期,尽可能在当地监管机构允许的范围内。
- The best method is to collect a complete date of birth, and derive age.
最佳方法是收集完整的出生日期,并推算年龄。 - When there are privacy concerns with collecting the complete date of birth, the recommendation is to collect year of birth at a minimum.
当收集完整出生日期存在隐私问题时,建议至少收集出生年份。 - In cases when neither of the above can be implemented (e.g., cultural or regional considerations) then Age and Age Unit should be collected, and Date of Collection should be collected or derived from the Visit Date.
在无法实施上述任何一种情况时(例如,文化或地区考虑),应收集年龄和年龄单位,并应收集或从访问日期推导出收集日期。 - Only use the AGETXT variable in very rare cases when only an age range or age description can be determined.
仅在非常少见的情况下使用 AGETXT 变量,当只能确定年龄范围或年龄描述时。
Date of Birth should be implemented such that incomplete dates are enterable, as allowed by the data capture system.
出生日期应实施为可输入不完整日期,符合数据采集系统的要求。
See Section 3.6 Collection of Dates for more information.
请参阅第 3.6 节 日期收集以获取更多信息。
Collection of Sex 性收藏
The collection of some demographics data is useful to perform simple analyses based upon population stratification.
收集一些人口统计数据对于基于人口分层进行简单分析是有用的。
Collection of Ethnicity and Race
民族和种族的集合
Within the United States of America, collect Ethnicity before Race, per FDA requirement. A secondary analysis is often made using the phenotypic race of the subject. Collect race if required for the protocol and not prohibited by local laws and regulations.
在美国,根据 FDA 要求,先收集民族信息再收集种族信息。通常会使用受试者的表型种族进行二次分析。如果协议要求并且不违反当地法律法规,则收集种族信息。
In 2016, the U.S. Office of Management and Budget (OMB) issued its revised recommendations for the collection and use of race and ethnicity data by Federal agencies. FDA follows this directive and now recommends "the use of the standardized OMB race and ethnicity categories for data collection in clinical trials for two reasons. The use of the recommended OMB categories will help ensure consistency in demographic subset analyses across studies used to support certain marketing applications to FDA and across data collected by other government agencies".
在 2016 年,美国管理和预算办公室(OMB)发布了对联邦机构收集和使用种族及民族数据的修订建议。FDA 遵循这一指令,现在建议“在临床试验的数据收集中使用标准化的 OMB 种族和民族类别,原因有二。使用推荐的 OMB 类别将有助于确保在支持某些向 FDA 提交的市场申请的研究中,以及其他政府机构收集的数据中,人口子集分析的一致性。”
The Race values listed in the FDA Guidance are:
FDA 指导中列出的种族价值包括:
- American Indian or Alaska Native
美洲印第安人或阿拉斯加原住民 - Asian 亚洲人
- Black or African American*
黑人或非裔美国人* - Native Hawaiian or Other Pacific Islander
本土夏威夷人或其他太平洋岛民 - White 白色
*For studies where data are collected outside the U.S., the recommended categories are the same except for "Black" instead of "Black or African American".
对于在美国以外收集数据的研究,推荐的类别相同,只是将“黑人”替换为“黑人或非洲裔美国人”。
CDASH provides only one variable for Race. When the sponsor captures more than one race, the sponsors will need to create non-standard variables to store the collection of the multiple Races and map appropriately to the SDTMIG DM domain.
CDASH 仅提供一个种族变量。当赞助商捕获多个种族时,赞助商需要创建非标准变量来存储多个种族的集合,并适当地映射到 SDTMIG DM 领域。
Race Other has been included as a free-text field to capture responses. The use of this variable is optional and should be used with caution because, when submitting data to the FDA, the FDA requires that all races be mapped to the five standard races recognized by the FDA, and providing an Other, Specify field might lead to mapping errors or difficulties. RACE is R/C because some sponsors prefer to derive values that are compliant with the codelist RACE (e.g., as derived from values collected in CRACE).
种族“其他”已被纳入为自由文本字段以捕捉响应。使用此变量是可选的,应谨慎使用,因为在向 FDA 提交数据时,FDA 要求所有种族都必须映射到 FDA 认可的五个标准种族,提供“其他,具体说明”字段可能会导致映射错误或困难。种族是 R/C,因为一些赞助商更倾向于导出符合种族代码表的值(例如,从 CRACE 中收集的值导出)。
The category of ethnicity is similar to race but, as defined by the CDC, is an arbitrary classification based on cultural, religious, or linguistic traditions; ethnic traits, background, allegiance, or association. In a fairly heterogeneous country, such as in the U.S., ethnicity data might be useful only to confirm that ethnic groups are not being discriminated against by being unfairly excluded from clinical research. Other regulatory bodies may expect the reporting of ethnicity values (different than the U.S. FDA) which more appropriately reflect the population of their areas (e.g., Japanese for MHLW reporting to Japan). These may be collected using the CETHNIC variable with its corresponding codelist, ETHNICC.
民族类别与种族相似,但根据 CDC 的定义,它是一种基于文化、宗教或语言传统的任意分类;民族特征、背景、忠诚或关联。在一个相当异质的国家,如美国,民族数据可能仅用于确认民族群体没有因被不公平地排除在临床研究之外而受到歧视。其他监管机构可能会期望报告的民族值(与美国 FDA 不同)更适当地反映其地区的人口(例如,日本的 MHLW 报告中的日本人)。这些数据可以使用 CETHNIC 变量及其相应的代码表 ETHNICC 进行收集。
If more detailed information on race or ethnicity are required to further characterize the study subject, it is recommended that the presented choices be "collapsible" up to one of the five designations for race, as well as the two categories for representing ethnicity, as needed for reporting to FDA under its guidance. When these more detailed categorizations are desired, the use of race and ethnicity vocabulary tables located within Health Level Seven's Reference Information Model Structural Vocabulary Tables is recommended, as they are designed to collapse up in this manner. For the collection of this added detail or granularity, as the sponsor may require, CDASH provides the variables CRACE and CETHNIC, respectively.
如果需要更详细的种族或民族信息来进一步描述研究对象,建议所提供的选项可以“折叠”到五个种族类别中的一个,以及根据 FDA 指导报告所需的两个民族类别。当需要这些更详细的分类时,建议使用健康七级(Health Level Seven)参考信息模型结构词汇表中的种族和民族词汇表,因为它们被设计为以这种方式折叠。为了收集这些附加细节或粒度,赞助商可能需要,CDASH 分别提供变量 CRACE 和 CETHNIC。
Source: Collection of Race and Ethnicity Data in Clinical Trials; October 26, 2016.
来源:临床试验中的种族和民族数据收集;2016 年 10 月 26 日。
Collection of Special Optional Fields in Demographics
人口统计学中特殊可选字段的集合
The CDASHIG allows for collection of the Date of Informed Consent using the variable RFICDAT. If a sponsor chooses to collect Informed Consent using this variable, the data should not also be collected using DSSTDAT from the DS Domain. The data from RFICDAT would then be mapped to the SDTMIG variable DSSTDTC and the companion variables (e.g., DSTERM, DSDECOD) must be populated accordingly.
CDASHIG 允许使用变量 RFICDAT 收集知情同意日期。如果赞助商选择使用此变量收集知情同意,则不应同时使用 DS 领域中的 DSSTDAT 收集数据。RFICDAT 中的数据将映射到 SDTMIG 变量 DSSTDTC,并且相应的变量(例如 DSTERM、DSDECOD)必须相应填充。
The CDASH Model also defines a field for Death Date (DTHDAT) as a timing variable. It may be collected on any CRF deemed appropriate by the sponsor. The SDTMIG variables DTHDTC and DTHFL are mapped to the DM domain during the SDTM submission dataset creation process. The CDASH field Death Date may be mapped to other SDTMIG domains, as deemed appropriate by the sponsor (e.g., DS).
CDASH 模型还定义了一个死亡日期(DTHDAT)字段作为时间变量。它可以在赞助商认为合适的任何 CRF 上收集。在 SDTM 提交数据集创建过程中,SDTMIG 变量 DTHDTC 和 DTHFL 被映射到 DM 领域。CDASH 字段死亡日期可以根据赞助商的判断映射到其他 SDTMIG 领域(例如,DS)。
See Best Practice in Section 4.1.2 of the CDASHIG for additional guidance recommending that the same data not be collected more than one time per subject.
请参阅 CDASHIG 第 4.1.2 节中的最佳实践,以获取额外指导,建议同一数据不应对每个受试者收集超过一次。
Specification for the CDASHIG DM - Demographics Domain
CDASHIG DM - 人口统计领域规范
Demographics (DM) 人口统计 (DM)