Data from: Cherry-picking by trialists and meta-analysts can drive conclusions about intervention efficacy

PLEASE NOTE, THESE DATA ARE ALSO REFERRED TO IN SUBSEQUENT PUBLICATIONS. PLEASE SEE http://dx.doi.org/10.1016/j.jclinepi.2017.05.007 FOR MORE INFORMATION.

Objectives
The objective of this study was to determine whether disagreements among multiple data sources affect systematic reviews of randomized clinical trials (RCTs).

Study Design and Setting
Eligible RCTs examined gabapentin for neuropathic pain and quetiapine for bipolar depression, reported in public (e.g., journal articles) and nonpublic sources (clinical study reports [CSRs] and individual participant data [IPD]).

Results
We found 21 gabapentin RCTs (74 reports, 6 IPD) and 7 quetiapine RCTs (50 reports, 1 IPD); most were reported in journal articles (18/21 [86%] and 6/7 [86%], respectively). When available, CSRs contained the most trial design and risk of bias information. CSRs and IPD contained the most results. For the outcome domains “pain intensity” (gabapentin) and “depression” (quetiapine), we found single trials with 68 and 98 different meta-analyzable results, respectively; by purposefully selecting one meta-analyzable result for each RCT, we could change the overall result for pain intensity from effective (standardized mean difference [SMD] = −0.45; 95% confidence interval [CI]: −0.63 to −0.27) to ineffective (SMD = −0.06; 95% CI: −0.24 to 0.12). We could change the effect for depression from a medium effect (SMD = −0.55; 95% CI: −0.85 to −0.25) to a small effect (SMD = −0.26; 95% CI: −0.41 to −0.1).

Conclusions
Disagreements across data sources affect the effect size, statistical significance, and interpretation of trials and meta-analyses.

请注意，本数据集相关数据亦见于后续发表文献。更多信息请访问：http://dx.doi.org/10.1016/j.jclinepi.2017.05.007。

【研究目标】
本研究旨在探究多源数据间的不一致是否会对随机对照试验（Randomized Clinical Trials, RCTs）的系统综述产生影响。

【研究设计与研究背景】
符合纳入标准的随机对照试验（Randomized Clinical Trials, RCTs）针对加巴喷丁治疗神经性疼痛以及喹硫平治疗双相抑郁展开，相关报告的来源分为公开来源（如期刊论文）与非公开来源，包括临床研究报告（Clinical Study Reports, CSRs）与个体参与者数据（Individual Participant Data, IPD）。

【研究结果】
本研究共检索到21项加巴喷丁相关符合纳入标准的RCTs（含74篇研究报告、6份IPD）以及7项喹硫平相关符合纳入标准的RCTs（含50篇研究报告、1份IPD）；其中绝大多数结果发表于期刊论文（占比分别为86%[18/21]与86%[6/7]）。在可获取的前提下，CSRs涵盖了最为全面的试验设计与偏倚风险相关信息，而CSRs与IPD则包含了最完整的试验结果数据。针对“疼痛强度”（加巴喷丁相关试验）与“抑郁症状”（喹硫平相关试验）这两个结局领域，我们分别在对应单试验中发现了68项与98项可用于元分析的结果；通过针对性为每项RCT选取一项可用于元分析的结果，我们可将疼痛强度的总体效应从有效（标准化均数差（Standardized Mean Difference, SMD）= −0.45；95%置信区间（Confidence Interval, CI）：−0.63 至 −0.27）调整为无效（SMD = −0.06；95% CI：−0.24 至 0.12）。同样地，我们可将抑郁症状的总体效应从中等效应（SMD = −0.55；95% CI：−0.85 至 −0.25）调整为小效应（SMD = −0.26；95% CI：−0.41 至 −0.1）。

【研究结论】
不同数据来源间的不一致会对试验与元分析的效应量、统计学显著性以及结果解读产生影响。