Evidenced-Based Prior for Estimating the Treatment Effect of Phase III Randomized Trials in Oncology.

IF 5.3 2区 医学 Q1 ONCOLOGY JCO precision oncology Pub Date : 2024-10-01 Epub Date: 2024-10-02 DOI:10.1200/PO.24.00363
Alexander D Sherry, Pavlos Msaouel, Gabrielle S Kupferman, Timothy A Lin, Joseph Abi Jaoude, Ramez Kouzy, Zachary R McCaw, Ethan B Ludmir, Erik van Zwet
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Abstract

Purpose: The primary results of phase III oncology trials may be challenging to interpret, given that results are generally based on P value thresholds. The probability of whether a treatment is beneficial, although more intuitive, is not usually provided. Here, we developed and released a user-friendly tool that calculates the probability of treatment benefit using trial summary statistics.

Methods: We curated 415 phase III randomized trials enrolling 338,600 patients published between 2004 and 2020. A phase III prior probability distribution for the treatment effect was developed on the basis of a three-component zero-mean mixture distribution of the observed z-scores. Using this prior, we computed the probability of clinically meaningful benefit (hazard ratio [HR] <0.8). The distribution of signal-to-noise ratios and power of phase III oncology trials were compared with that of 23,551 randomized trials from the Cochrane Database.

Results: The signal-to-noise ratios of phase III oncology trials tended to be much larger than randomized trials from the Cochrane Database. Still, the median power of phase III oncology trials was only 49% (IQR, 14%-95%), and the power was <80% in 65% of trials. Using the phase III oncology-specific prior, only 53% of trials claiming superiority (114 of 216) had a ≥90% probability of clinically meaningful benefits. Conversely, the probability that the experimental arm was superior to the control arm (HR <1) exceeded 90% in 17% of trials interpreted as having no benefit (34 of 199).

Conclusion: By enabling computation of contextual probabilities for the treatment effect from summary statistics, our robust, highly practical tool, now posted on a user-friendly webpage, can aid the wider oncology community in the interpretation of phase III trials.

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估算肿瘤学 III 期随机试验治疗效果的循证先例。
目的:III 期肿瘤试验的主要结果通常以 P 值阈值为基础,因此解释这些结果可能具有挑战性。治疗是否获益的概率虽然更直观,但通常不会提供。在此,我们开发并发布了一款用户友好型工具,可使用试验摘要统计计算治疗获益概率:我们整理了 2004 年至 2020 年间发表的 415 项 III 期随机试验,共招募了 338600 名患者。在观察到的 z 分数的三组零均值混合分布的基础上,我们建立了 III 期治疗效果的先验概率分布。利用该先验值,我们计算了有临床意义的获益概率(危险比 [HR] 结果):肿瘤学 III 期试验的信噪比往往比 Cochrane 数据库中的随机试验大得多。尽管如此,III 期肿瘤学试验的中位研究功率仅为 49%(IQR,14%-95%),研究功率为结论值:我们的工具功能强大、实用性强,目前已发布在用户友好型网页上,可帮助广大肿瘤学界解读III期试验。
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CiteScore
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自引率
4.30%
发文量
363
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