Commonly Used Clinical Trial Terms in English and Their Chinese Translations; List of Regulatory Guidance for Clinical Trials in China

Friends sometimes ask me about the Chinese translations of the clinical trial terms. Some of the terms are new in Chinese. They did not exist in Chinese until recent years when the drug development and clinical trials had been rapidly expanding in China. It would be useful to list the commonly used terms in clinical trials and provide the corresponding translations. These translations are based on the regulatory documents issued by SFDA (China Food and Drug Administration). Some of the translations are different between the mainland China and the Taiwan.

English	Chinese (中文)
Active Control	阳性对照
Adaptive Design	自适应设计
Absorption, Distribution, Metabolization, and Elimination (ADME)	吸收、分布、代谢、清除
Adverse Event	不良反应
Alpha-spending function	α消耗函数
Alternative Hypothesis	备择假设
Area Under Curve (AUC)	曲线下面积
Audit	稽查
Audit Trail	稽查踪迹
Baseline Value	基线值
Bias	偏倚
Bioavailability	生物利用率
Bioequivalence	生物等效性
Biomarker	生物标志物
Biosimilar	生物类似药
Blind Review	盲态审核
Blinding/Masking	设盲
Candidate Product (Proposed Product)	候选药
Case Report Form	病例报告表
CIOMS	国际医学科学组织委员会
Clinical Trial	临床试验
Maximum Concentration (Cmax)	达峰浓度
Minimum Concentration (Cmin)	谷浓度
Coding Dictionary	术语表
Company Core Data Sheet (CCDS)	公司核心数据表
Common Technical Document (ICH-CTD)	通用技术文件
Common Toxicity Criteria (CTC)	常见毒性反应标准
Comparative Study	比对试验
Confidence Interval	可信区间
Confirmatory Trial	验证性试验
Concomitant Medication	并用药品
Confidentiality	保密性
Conflict of Interest	利益冲突
Contract Research Organization	合同研究组织
Coordinating Investigator	协调研究者
co-primary endpoint	协同的主要疗效指标
Cross-over Design	交叉设计
Data and Safety Monitoring Board (DSMB)	数据与安全监查委员会
Disease－Free Survival ,DFS	无病生存期
Progression-Free Survival ,PFS	无进展生存期
Dose Limited Toxicity, DLT	剂量限制性毒性
Double-Dummy	双模拟
Dropout	脱落
eCTD	电子化通用技术文件
Endpoint Assessment or Adjudication Committee (EAC)	终点判定委员会
Electronic Data Capture (EDC)	电子数据采集
Equivalence	等效性
Ethics Committee	伦理委员会
Exploratory Efficacy Endpoint	辅助疗效指标
Full Analysis Set	全分析集
Generic Product	仿制药
Good Clinical Practice (GCP)	临床试验质量管理规范
Half Life	半衰期
Health-related Quality of Life （HRQoL）	健康相关的生活质量
Highly Variable Drug	高变异性药
Hypothesis Test	假设检验
Immunogenecity	免疫原性
Independent Data Monitoring Committee (IDMC)	独立数据监察委员会
Indication	适应症
Individual Bioequivalence (IBE)	个体生物等效性
Informed Consent Form	知情同意书
Intention To Treat Principl	意向性分析原则
Interim Analysis	期中分析
Inspection	视察
Institutional Review Board	伦理委员会
Interaction	交互作用
Investigator	研究者
Investigator’s Brochure	研究者手册
Investigational Product	试验用药品
Investigational Medicinal Product (IMP)	临床试验用品药
Label	标签
last observation carried forward	结转
Lower Limit of quantitation，LLOQ	定量下限
Maximal Tolerated Dose (MTD)	最大耐受剂量
Mean Residence Time (MRT)	平均滞留时间
Medical History	病史
Missing Data	缺失数据
Monitor	监查员
Multicentre Trial	多中心临床试验
Non-compliance/Violation	不依从/违背方案
No Observed Adverse Effect Level (NOAEL)	未观察到不良反应的剂量
Non-inferiority	非劣（效）性
Open Label	开放
Originator Biologic	原研产品
Overall Survival  （OS）	总生存期
Patient-reported Outcomes (PRO)	患者自评结果
Per Protocol Set	符合方案集
Pivotal Study	关键性临床试验
Placebo	安慰剂
Pharmacodynamics (PD)	药效动力学
Pharmacokinetics (PK)	药代动力学
Pharmacovigilence (PV)	药物警戒
Population Bioequivalence (PBE)	群体生物等效性
Population Pharmacokinetics (PPK)	群体药效动力学
post hoc	事后的
Primary Efficacy Endpoint	主要疗效指标
Primary Efficacy Variable	主要疗效变量
Protocol	试验方案
Protocol Amendment	试验方案修正案
Periodic Safety Update Reports for Marketed Drugs (PSUR)	上市药品定期安全性更新报告
PK/PD Model	药代/药效模型
Relationship（Causality）	关联性
Randomization	随机
Reference Product	参照药
Sample Size	样本量
Secondary Efficacy Endpoint	次要疗效指标
Sequelae	后遗症
Serious Adverse Event	严重不良反应
Single-arm Design	单臂设计
Sponsor	申办者
Standard Operating Procedure	标准操作规程
Statistical Analysis Plan (SAP)	统计分析计划
Steady State	稳态
Superiority	优效性
Surrogate Endpoint and Surrogate Variable	替代指标
Survival analysis	生存分析
Time to Maximum Concentration (Tmax)	达峰时间
Unexpected  Adverse Event	非预期不良事件
Washout period	清洗期

In collecting the Chinese translations for the commonly used clinical trials, I have to review the regulatory guidance issued by SFDA. It is good to have the links below for references. 

• 药品注册管理办法 2007
• 药品注册管理办法（修改草案）2014
• 药品临床研究的若干规定 2000
• 国际多中心药物临床试验指南 2015
• 药物临床试验伦理审查工作指导原则
• 药物临床试验质量管理规范 修订稿 2015
• 药品定期安全性更新报告撰写规范 2013
• 化学药物临床试验报告的结构与内容技术指导原则
• 化学药物和生物制品临床试验的生物统计学技术指导原则
• 化学药物制剂人体生物利用度和生物等效性研究技术指导原则
• 体外诊断试剂临床研究技术指导原则 2014
• 体外诊断试剂临床研究技术指导原则 2007
• 疫苗临床试验技术指导原则 2004
• 医疗器械临床评价技术指导原则 2014
• 体外诊断试剂注册管理办法 (2014-07-30)

医疗器械注册管理办法(2014-07-30)

• 抗肿瘤药物临床试验技术指导原则 2012

抗肿瘤药物上市申请临床数据收集技术指导原则 (2012-05-15)

• 抗肿瘤药物临床试验终点技术指导原则 (2012-05-15)
• 治疗脂代谢紊乱药物临床研究指导原则 (2012-05-15)
• 单纯性和复杂性皮肤及软组织感染抗菌药物临床试验指导原则 (2012-05-15)
• 抗菌药物非劣效临床试验设计技术指导原则 (2012-05-15)
• 癫痫治疗药物临床研究试验技术指导原则 (2012-05-15)
• 治疗糖尿病药物及生物制品临床试验指导原则 (2012-05-15)
• 预防和/或治疗流感药物临床研究指导原则 (2012
• 肝功能损害患者的药代动力学研究技术指导原则 (2012-05-15

肾功能损害患者的药代动力学研究技术指导原则 (2012-05-15)

• 药物代谢产物安全性试验技术指导原则
• 生物类似药研发与评价技术指导原则（试行）

Graphic Presentation: Kaplan-Meier Plot, Q-Q plot, Box Plot, Funnel Plot, Swimmer Plot, Forest Plot, Spaghetti Plot, Bubble Plot

Data visualization is one critical part in statistical analysis. Data visualization is through various plots. Here are some of the plots commonly used in presentation of clinical trial data. These graphs may be generated using commercially software, but they can always be programmed using SAS procedures:

Kaplan-Meier plot is used in analysis of time-to-event variables and can be easily generated using SAS Proc Lifetest.

Q-Q plot is used to compare the data set to a theoretical model (for example, comparing to a normal distribution) and normal Q-Q plot can be easily generated using Proc Univariate.

Box plot or box-and-whisker plot is used to show quartiles and display the variation in samples of a statistical population. The boxplot showes distributions of data is particularly useful for understanding the shape of the distribution and whether there are outliers. SAS has a specific procedure for box-plot – Proc Boxplot. 

Funnel plot is a graph designed to check for the existence of publication bias; funnel plots are commonly used in systematic reviews and meta-analyses. In the absence of publication bias, it assumes that the largest studies will be plotted near the average, and smaller studies will be spread evenly on both sides of the average, creating a roughly funnel-shaped distribution. Deviation from this shape can indicate publication bias.

Funnel plot can be generated using Excel. Rick Wicklin's SAS blog 'The Do Loop' has discussions about generating funnel plot using SAS.

• Funnel plots: An alternative to ranking
• Funnel plots for proportions

Swimmer plot is a good tool to look at an individual subject’s pattern of response. A swimmer plot is a graphical way of showing multiple pieces of a subject’s response 'story' in one glance.   Swimmer plot includes a bar showing the length of treatment duration for each patient, classified by the disease stage at baseline, one for each patient in the study.  Graph also includes indicators for the start and end of each response episode, classified by complete or partial response, and an indicator showing whether the patient is a "Durable responder".

• Sanjay Matange’s blot ‘Graphically Speaking’ had an article discussing how to program the swimmer plot.
• Swimmer Plot: Tell a Graphical Story of Your Time to Response Data Using PROC SGPLOT

Forest Plot is a graphical display designed to illustrate the relative strength of treatment effects in multiple quantitative scientific studies addressing the same question. It was developed for use in medical research as a means of graphically representing a metal-analysis of the results of randomized controlled clinical trials.

Forest plot is also frequently use for graphically displaying the results from subgroup analyses. For example, in a paper “Progression parameters for emphysema: A clinical investigation”, the forest plot was used to show the overall effect and the effect by site.

Forest plot may also be used for combining the meta analysis results and the subgroup analysis. In a paper by Dolor et al “Treatment Strategies for Women With Coronary Artery Disease”, the forest plot was used for showing the treatment effect of meta analysis results by male/female subgroup.

The commercial software Comprehensive Meta Analysis can easily generate the forest plot as part of the Meta Analysis. Forest Plot can also be generated using SAS Proc SGPLOT. There are many papers discussing the programming and the interpretation for the Forest Plot.

• Forest Plot with SAS for subgroup analysis  
• Forest Plot of Hazard Ratios by Patient Subgroup
• SAS codes for creating the forest plot for sub-group analyses

Spaghetti Plot

I had a previous article discussing Spaghetti plot. Spaghetti plot is mainly used in longitudinal data analysis to see the individual profiles in one plot and in pharmacokinetic analysis to see the time-concentration profiles for all individual subjects in one plot.

Spaghetti plot can be generated using SAS PROC SGPLOT:

proc sgplot data=cs NOAUTOLEGEND ;
    series x = timepoint y = concentration
         /group=subject lineattrs = (thickness = 1 pattern=solid color=black) markers;
    xaxis label = 'x axis label'  values=(0, 4, 8, 24, 48, 120, 168);
        yaxis label = 'y axis label' grid values = (0 to 70 by 10);
run;

There are other discussions about generating the Spaghetti plot.

• Create a spaghetti plot with the SGPLOT procedure
• How can I make spaghetti plots?
• Creating Customized Spaghetti Plots
• Longitudinal data: plots of individual profiles and mean 

Bubble plot is a type of plot that displays three dimensions of data. Each entity with its triplet (v₁, v₂, v₃) of associated data is plotted as a disk that expresses two of the v_i values through the disk's xy location and the third through its size. Bubble charts can be considered a variation of the scatter plot, in which the data points are replaced with bubbles. 

Bubble plot is easily to be generated using Microsoft Excel (see a youtube video), but it can also be generated using SAS.

• Generating a Simple Bubble Plot
• Graph Your SAS® Off

Reference:

• Figures in clinical trial reports: current practice & scope for improvement
• How to interpret figures in reports of clinical trials