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使用严重不良事件评估试验代表性:一项基于临床试验和常规医疗保健数据的汇总和个体水平数据的观察性分析。

Assessing trial representativeness using serious adverse events: an observational analysis using aggregate and individual-level data from clinical trials and routine healthcare data.

机构信息

School for Health and Wellbeing, University of Glasgow, Glasgow, UK.

London School of Hygiene and Tropical Medicine, London, UK.

出版信息

BMC Med. 2022 Oct 28;20(1):410. doi: 10.1186/s12916-022-02594-9.

Abstract

BACKGROUND

The applicability of randomised controlled trials of pharmacological agents to older people with frailty/multimorbidity is often uncertain, due to concerns that trials are not representative. However, assessing trial representativeness is challenging and complex. We explore an approach assessing trial representativeness by comparing rates of trial serious adverse events (SAE) to rates of hospitalisation/death in routine care.

METHODS

This was an observational analysis of individual (125 trials, n=122,069) and aggregate-level drug trial data (483 trials, n=636,267) for 21 index conditions compared to population-based routine healthcare data (routine care). Trials were identified from ClinicalTrials.gov . Routine care comparison from linked primary care and hospital data from Wales, UK (n=2.3M). Our outcome of interest was SAEs (routinely reported in trials). In routine care, SAEs were based on hospitalisations and deaths (which are SAEs by definition). We compared trial SAEs in trials to expected SAEs based on age/sex standardised routine care populations with the same index condition. Using IPD, we assessed the relationship between multimorbidity count and SAEs in both trials and routine care and assessed the impact on the observed/expected SAE ratio additionally accounting for multimorbidity.

RESULTS

For 12/21 index conditions, the pooled observed/expected SAE ratio was <1, indicating fewer SAEs in trial participants than in routine care. A further 6/21 had point estimates <1 but the 95% CI included the null. The median pooled estimate of observed/expected SAE ratio was 0.60 (95% CI 0.55-0.64; COPD) and the interquartile range was 0.44 (0.34-0.55; Parkinson's disease) to 0.87 (0.58-1.29; inflammatory bowel disease). Higher multimorbidity count was associated with SAEs across all index conditions in both routine care and trials. For most trials, the observed/expected SAE ratio moved closer to 1 after additionally accounting for multimorbidity count, but it nonetheless remained below 1 for most.

CONCLUSIONS

Trial participants experience fewer SAEs than expected based on age/sex/condition hospitalisation and death rates in routine care, confirming the predicted lack of representativeness. This difference is only partially explained by differences in multimorbidity. Assessing observed/expected SAE may help assess the applicability of trial findings to older populations in whom multimorbidity and frailty are common.

摘要

背景

由于担心试验不具有代表性,因此,对于有衰弱/多种合并症的老年人,药物随机对照试验的适用性通常不确定。但是,评估试验的代表性具有挑战性和复杂性。我们通过比较试验严重不良事件(SAE)的发生率与常规护理中的住院/死亡发生率来探索一种评估试验代表性的方法。

方法

这是对 21 种指标疾病的个体(125 项试验,n=122069)和药物试验数据的汇总水平(483 项试验,n=636267)进行的观察性分析,将其与基于人群的常规医疗保健数据(常规护理)进行比较。试验从 ClinicalTrials.gov 中确定。常规护理比较来自英国威尔士的链接初级保健和医院数据(n=2300 万)。我们感兴趣的结果是 SAE(试验中常规报告)。在常规护理中,SAE 基于住院和死亡(根据定义,这些是 SAE)。我们将试验中的 SAE 与具有相同指标疾病的年龄/性别标准化常规护理人群中的预期 SAE 进行比较。使用 IPD,我们评估了临床试验和常规护理中合并症计数与 SAE 之间的关系,并在额外考虑合并症的情况下评估了观察到的/预期的 SAE 比值的影响。

结果

对于 21 种指标疾病中的 12 种,汇总的观察到的/预期的 SAE 比值<1,表明试验参与者的 SAE 少于常规护理。另外 6/21 有<1 的点估计值,但 95%CI 包含零。观察到的/预期的 SAE 比值的中位数汇总估计值为 0.60(95%CI 0.55-0.64;COPD),四分位间距为 0.44(0.34-0.55;帕金森氏病)至 0.87(0.58-1.29;炎症性肠病)。在常规护理和试验中,所有指标疾病的合并症计数越高,SAE 发生率越高。对于大多数试验,在额外考虑合并症计数后,观察到的/预期的 SAE 比值更接近 1,但大多数情况下仍低于 1。

结论

与常规护理中基于年龄/性别/疾病的住院和死亡率的预期相比,试验参与者经历的 SAE 较少,这证实了预测的缺乏代表性。这种差异仅部分由合并症的差异解释。评估观察到的/预期的 SAE 可能有助于评估试验结果在合并症和衰弱症常见的老年人群中的适用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/caef/9615407/83cce5bf7691/12916_2022_2594_Fig1_HTML.jpg

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