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

Clinical Snapshot

Key Findings

• P Value: P<0.001 for both primary comparisons

• Effect Size: ILR vs. single-threshold: +11.2 percentage points (93.4% vs. 82.2%); ILR vs. binary: +18.3 percentage points (93.4% vs. 75.1%). PE vignette: ILR 91.9% vs. threshold 70.9% vs. binary 64.7%. Heart failure vignette: ILR 94.9% vs. threshold 93.4% vs. binary 85.6%

• Primary Outcome: Rate of correct clinical management decisions across two vignettes (pulmonary embolism and heart failure)

• Nnt Or Sensitivity: NNT (ILR vs. single-threshold) ≈ 9; NNT (ILR vs. binary) ≈ 5–6. These represent the number of clinicians who need to receive ILR-formatted test data to yield one additional correct clinical decision compared to traditional formats

• Confidence Interval: ILR vs. threshold: 95% CI 6.9–15.6 percentage points; ILR vs. binary: 95% CI 13.5–23.1 percentage points

Clinical Application

Implementation requires reform of how laboratory results and diagnostic test characteristics are communicated — including clinical decision support tools, laboratory reporting systems, and medical education curricula. ILR tables are already available in evidence-based medicine resources (e.g., the Rational Clinical Examination series) but are not routinely embedded in clinical workflows. Feasibility is moderate: the concept is not new, but systematic integration into electronic medical records and point-of-care tools requires institutional investment. In Australia, this research is directly relevant to hospital medicine, emergency medicine, and general practice settings where quantitative diagnostic tests (D-dimer, BNP, troponin, PSA) guide management decisions. The RACGP and RACP both emphasise evidence-based diagnostic reasoning in their curricula and CPD frameworks. Australian laboratory reporting systems (e.g., through RCPA standards) currently report binary or single-threshold reference ranges; adoption of ILR-based reporting would require engagement with pathology providers and health informatics teams. The TGA does not directly regulate how test characteristics are communicated to clinicians, but the Australian Commission on Safety and Quality in Health Care (ACSQHC) has a mandate for clinical decision support improvement. PBS implications are indirect — improved diagnostic accuracy could reduce unnecessary imaging (e.g., CTPA for PE) and inappropriate treatment escalation in heart failure, with potential cost savings. This study provides Level 2 evidence (RCT) supporting a change in how diagnostic information is presented in medical education and clinical practice. Internal medicine physicians, residents, and advanced practice providers making diagnostic and management decisions based on quantitative test results, particularly in conditions where test values span a continuous range (e.g., D-dimer, BNP/NT-proBNP, troponin)

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.

References

1. 1.Goryachok, M., Liu, J., Benjamin, T., Fischer, B. G., Lai, A. R., Levy, K. L., Wogu, A. F., Evans, A. T., & Baduashvili, A. (2026). A randomized trial of interval likelihood ratios for clinical decision-making. NEJM Evidence. https://doi.org/10.1056/EVIDoa2500249