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结构报告提高预后标志物研究分析透明度。

Structured reporting to improve transparency of analyses in prognostic marker studies.

机构信息

Institute for Medical Biometry and Statistics, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany.

Department of Statistics and Probability, Michigan State University, East Lansing, MI, USA.

出版信息

BMC Med. 2022 May 12;20(1):184. doi: 10.1186/s12916-022-02304-5.

DOI:10.1186/s12916-022-02304-5
PMID:35546237
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9095054/
Abstract

BACKGROUND

Factors contributing to the lack of understanding of research studies include poor reporting practices, such as selective reporting of statistically significant findings or insufficient methodological details. Systematic reviews have shown that prognostic factor studies continue to be poorly reported, even for important aspects, such as the effective sample size. The REMARK reporting guidelines support researchers in reporting key aspects of tumor marker prognostic studies. The REMARK profile was proposed to augment these guidelines to aid in structured reporting with an emphasis on including all aspects of analyses conducted.

METHODS

A systematic search of prognostic factor studies was conducted, and fifteen studies published in 2015 were selected, three from each of five oncology journals. A paper was eligible for selection if it included survival outcomes and multivariable models were used in the statistical analyses. For each study, we summarized the key information in a REMARK profile consisting of details about the patient population with available variables and follow-up data, and a list of all analyses conducted.

RESULTS

Structured profiles allow an easy assessment if reporting of a study only has weaknesses or if it is poor because many relevant details are missing. Studies had incomplete reporting of exclusion of patients, missing information about the number of events, or lacked details about statistical analyses, e.g., subgroup analyses in small populations without any information about the number of events. Profiles exhibit severe weaknesses in the reporting of more than 50% of the studies. The quality of analyses was not assessed, but some profiles exhibit several deficits at a glance.

CONCLUSIONS

A substantial part of prognostic factor studies is poorly reported and analyzed, with severe consequences for related systematic reviews and meta-analyses. We consider inadequate reporting of single studies as one of the most important reasons that the clinical relevance of most markers is still unclear after years of research and dozens of publications. We conclude that structured reporting is an important step to improve the quality of prognostic marker research and discuss its role in the context of selective reporting, meta-analysis, study registration, predefined statistical analysis plans, and improvement of marker research.

摘要

背景

导致对研究结果理解不足的因素包括报告方法不当,例如选择性报告具有统计学意义的发现或提供的方法细节不足。系统评价表明,预后因素研究的报告仍不理想,即使是对于重要方面,如有效样本量。REPORTING 研究结果的规范有助于研究人员报告肿瘤标志物预后研究的关键方面。REPORTING 规范概要旨在补充这些指南,以帮助进行结构化报告,并重点纳入所进行分析的所有方面。

方法

对预后因素研究进行了系统检索,选择了 2015 年发表的 15 项研究,每个肿瘤学期刊各有 3 项研究入选。如果研究包括生存结果且统计分析中使用了多变量模型,则该研究可被选中。对于每项研究,我们根据 REMARK 规范概要总结了关键信息,概要包括患者人群的详细信息,以及可获得的变量和随访数据,以及所有进行的分析列表。

结果

结构化概要可轻松评估研究报告是否仅存在薄弱环节,或者是否由于缺少许多相关细节而较差。研究报告在排除患者、缺少事件数量信息或缺少有关统计分析的详细信息方面存在不完整,例如在没有任何事件数量信息的小人群中进行亚组分析。在超过 50%的研究中,概要报告存在严重缺陷。未评估分析质量,但一些概要一眼就能看出存在多个缺陷。

结论

大量预后因素研究报告和分析不充分,这对相关的系统评价和荟萃分析产生了严重影响。我们认为,个别研究报告不充分是导致经过多年研究和数十篇出版物后大多数标志物的临床相关性仍不明确的最重要原因之一。我们得出的结论是,结构化报告是提高预后标志物研究质量的重要步骤,并讨论了其在选择性报告、荟萃分析、研究注册、预设统计分析计划和标志物研究改进方面的作用。

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