A Randomized Trial of Interval Likelihood Ratios for Clinical Decision-Making.

IF 11.6
NEJM evidence Pub Date : 2026-07-01 Epub Date: 2026-06-23 DOI:10.1056/EVIDoa2500249
Maksym Goryachok, Jintong Liu, Tyler Benjamin, Brett G Fischer, Andrew R Lai, Kathryn L Levy, Adane F Wogu, Arthur T Evans, Amiran Baduashvili
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Abstract

Background: Dichotomized reporting of diagnostic test results may oversimplify test characteristics. Interval likelihood ratios (ILRs), test characteristics across a range of values, offer a nuanced alternative, but their impact on decision-making is uncertain. We assessed whether ILRs improve clinical decisions compared to two traditional formats: single-threshold and binary test characteristics.

Methods: We conducted a multicenter randomized trial of internal medicine residents, attending physicians, and advanced practice providers. Participants were presented with two fictional vignettes (cases involving pulmonary embolism diagnosis and heart failure treatment), each with a clearly correct response centered on a key diagnostic test result. The vignettes were identical except for participants' random assignment to one of three test characteristic presentations: (1) single threshold, (2) binary test characteristics, or (3) ILRs. We compared the correct management decision rates between the ILR and threshold groups and between the ILR and binary groups. Secondary objectives included comparing threshold and binary groups and subgroup analyses by case vignette.

Results: The trial enrolled 611 participants. The correct decision rate was 93.4% in the ILR group compared with 82.2% in the threshold group (difference of 11.2 percentage points; 95% confidence interval [CI], 6.9-15.6, P<0.001) and compared with 75.1% in the binary group (difference of 18.3 percentage points; 95% CI, 13.5-23.1, P<0.001). In the pulmonary embolism case, the correct response rate was 91.9% in the ILR group, 70.9% in the threshold group, and 64.7% in the binary group. In the heart failure case, the correct response rate was 94.9% in the ILR group, 93.4% in the threshold group, and 85.6% in the binary group.

Conclusions: Presenting diagnostic test information using ILRs improved vignette-based clinical decisions. The magnitude of improvement appeared to vary by case vignette.

区间似然比用于临床决策的随机试验。
背景:诊断测试结果的二分法报告可能会过度简化测试特征。区间似然比(ILRs),测试一系列值的特征,提供了一个微妙的选择,但它们对决策的影响是不确定的。我们评估了与两种传统格式(单阈值和二元测试特征)相比,ILRs是否能改善临床决策。方法:我们对内科住院医师、主治医师和高级执业医师进行了一项多中心随机试验。参与者被展示了两个虚构的小插曲(涉及肺栓塞诊断和心力衰竭治疗的病例),每个小插曲都有一个明确正确的反应,集中在一个关键的诊断测试结果上。除了参与者被随机分配到三种测试特征呈现中的一种之外,这些小插曲是相同的:(1)单一阈值,(2)二元测试特征,或(3)ILRs。我们比较了ILR组和阈值组之间以及ILR组和二元组之间的正确管理决策率。次要目的包括比较阈值组和二值组,以及通过病例小片段进行亚组分析。结果:该试验招募了611名参与者。ILR组的正确决策率为93.4%,而阈值组为82.2%(差异为11.2个百分点;95%可信区间[CI], 6.9-15.6, p)。结论:使用ILR提供诊断测试信息改善了基于图像的临床决策。改善的程度似乎因个案而异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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