药物治疗非随机研究的特点:横断面研究。

BMJ medicine Pub Date : 2024-10-30 eCollection Date: 2024-01-01 DOI:10.1136/bmjmed-2024-000932
Sally Yaacoub, Raphael Porcher, Anna Pellat, Hillary Bonnet, Viet-Thi Tran, Philippe Ravaud, Isabelle Boutron
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引用次数: 0

摘要

摘要:目的:研究评估药物治疗有效性或安全性或两者兼而有之的非随机比较研究的特点:研究评估药物治疗有效性或安全性或两者兼而有之的非随机对比研究的特点:数据来源数据来源:Medline(Ovid),2022年6月1日至2022年8月31日期间发表的报告:纳入评估药物治疗有效性或安全性或两者兼具的非随机对比研究报告。对样本进行随机排序筛选,直至找到 200 份符合条件的报告。在报告指南和目标试验仿真框架的启发下,采用试行表格提取了关于一般特征、报告特征和时间点一致性的数据,以及可能存在的相关偏差:在确定的 462 项非随机研究报告中,有 262 项研究被排除在外(32% 没有参照物,25% 没有考虑混杂因素)。为了评估时间点的一致性和可能存在的相关偏差,我们考虑了三个研究时间点:资格审查、治疗分配和随访开始。在纳入的 200 份报告中,70% 的报告存在一种可能的偏差,涉及:24% 的报告纳入了流行用户、32% 的报告纳入了治疗后资格标准、42% 的报告纳入了不确定的时间段、23% 的报告纳入了治疗分类。报告不完整,只有 2% 的研究报告了全部六项关键要素:资格标准(87%)、治疗描述(46%)、治疗偏差(27%)、因果对比(11%)、主要结果(90%)和混杂因素(88%)。大多数研究使用了常规收集的数据(67%),但只有 7% 的研究报告对用于选择人群的代码或算法进行了验证研究。只有 7% 的报告提到在试验登记处登记,3% 的报告有可用的方案:研究结果表明,尽管获取真实世界的证据很有价值,但非随机研究的稳健性和透明度仍有待提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Characteristics of non-randomised studies of drug treatments: cross sectional study.

Abstract:

Objective: To examine the characteristics of comparative non-randomised studies that assess the effectiveness or safety, or both, of drug treatments.

Design: Cross sectional study.

Data sources: Medline (Ovid), for reports published from 1 June 2022 to 31 August 2022.

Eligibility criteria for selecting studies: Reports of comparative non-randomised studies that assessed the effectiveness or safety, or both, of drug treatments were included. A randomly ordered sample was screened until 200 eligible reports were found. Data on general characteristics, reporting characteristics, and time point alignment were extracted, and possible related biases, with a piloted form inspired by reporting guidelines and the target trial emulation framework.

Results: Of 462 reports of non-randomised studies identified, 262 studies were excluded (32% had no comparator and 25% did not account for confounding factors). To assess time point alignment and possible related biases, three study time points were considered: eligibility, treatment assignment, and start of follow-up. Of the 200 included reports, 70% had one possible bias, related to: inclusion of prevalent users in 24%, post-treatment eligibility criteria in 32%, immortal time periods in 42%, and classification of treatment in 23%. Reporting was incomplete, and only 2% reported all six of the key elements considered: eligibility criteria (87%), description of treatment (46%), deviations in treatment (27%), causal contrast (11%), primary outcomes (90%), and confounding factors (88%). Most studies used routinely collected data (67%), but only 7% reported using validation studies of the codes or algorithms applied to select the population. Only 7% of reports mentioned registration on a trial registry and 3% had an available protocol.

Conclusions: The findings of the study suggest that although access to real world evidence could be valuable, the robustness and transparency of non-randomised studies need to be improved.

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