The disproportionate impact of pre-test probability estimation errors: an analysis across different pre-test probability contexts.

IF 2 Q2 MEDICINE, GENERAL & INTERNAL

Diagnosis Pub Date : 2025-09-02 DOI:10.1515/dx-2025-0033

Matheus Bento de Souza, José Nunes de Alencar

{"title":"The disproportionate impact of pre-test probability estimation errors: an analysis across different pre-test probability contexts.","authors":"Matheus Bento de Souza, José Nunes de Alencar","doi":"10.1515/dx-2025-0033","DOIUrl":null,"url":null,"abstract":"Objectives: Diagnostic reasoning in clinical medicine is permeated by uncertainty. This study aims to analyze how errors in the estimation of pre-test probability affect the application of Bayesian inference in diagnostic reasoning.Methods: We examined the propagation of pre-test probability misestimation through Bayes' Theorem, focusing on its interaction with different likelihood ratios and pre-test probabilities. The analysis explored the mathematical consequences of prior misestimation on post-test probability estimation.Results: We demonstrate that misestimation of prior probabilities has a nonlinear impact on posterior probabilities, with errors propagating differently depending on the likelihood ratio of the diagnostic test and the real pre-test probability. Misestimated priors can produce substantial distortions in posterior probabilities, leading to misplaced confidence in diagnostic test results.Conclusions: Accurate estimation of pre-test probability is essential for the validity of Bayesian diagnostic reasoning. Objective and evidence-based approaches to pre-test probability estimation are necessary to minimize diagnostic errors and to enhance the reliability of clinical decision-making.","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":" ","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Diagnosis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/dx-2025-0033","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}

引用次数: 0

Abstract

Objectives: Diagnostic reasoning in clinical medicine is permeated by uncertainty. This study aims to analyze how errors in the estimation of pre-test probability affect the application of Bayesian inference in diagnostic reasoning.

Methods: We examined the propagation of pre-test probability misestimation through Bayes' Theorem, focusing on its interaction with different likelihood ratios and pre-test probabilities. The analysis explored the mathematical consequences of prior misestimation on post-test probability estimation.

Results: We demonstrate that misestimation of prior probabilities has a nonlinear impact on posterior probabilities, with errors propagating differently depending on the likelihood ratio of the diagnostic test and the real pre-test probability. Misestimated priors can produce substantial distortions in posterior probabilities, leading to misplaced confidence in diagnostic test results.

Conclusions: Accurate estimation of pre-test probability is essential for the validity of Bayesian diagnostic reasoning. Objective and evidence-based approaches to pre-test probability estimation are necessary to minimize diagnostic errors and to enhance the reliability of clinical decision-making.

查看原文本刊更多论文

预测试概率估计错误的不成比例的影响：跨不同的预测试概率上下文的分析。

目的：临床医学诊断推理充满不确定性。本研究旨在分析预测概率估计误差如何影响贝叶斯推理在诊断推理中的应用。方法：通过贝叶斯定理检验预检验概率误估计的传播，重点研究其与不同似然比和预检验概率的相互作用。分析探讨了先验错误估计对后验概率估计的数学后果。结果：我们证明了先验概率的错误估计对后验概率有非线性影响，误差的传播取决于诊断测试和真实预测试概率的似然比。错误估计的先验会对后验概率产生实质性的扭曲，导致对诊断测试结果的错误信心。结论：检验前概率的准确估计对贝叶斯诊断推理的有效性至关重要。客观和循证的方法来预测概率估计是必要的，以尽量减少诊断错误，提高临床决策的可靠性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Diagnosis MEDICINE, GENERAL & INTERNAL-

CiteScore

7.20

自引率

5.70%

发文量

期刊介绍： Diagnosis focuses on how diagnosis can be advanced, how it is taught, and how and why it can fail, leading to diagnostic errors. The journal welcomes both fundamental and applied works, improvement initiatives, opinions, and debates to encourage new thinking on improving this critical aspect of healthcare quality.　 Topics: -Factors that promote diagnostic quality and safety -Clinical reasoning -Diagnostic errors in medicine -The factors that contribute to diagnostic error: human factors, cognitive issues, and system-related breakdowns -Improving the value of diagnosis – eliminating waste and unnecessary testing -How culture and removing blame promote awareness of diagnostic errors -Training and education related to clinical reasoning and diagnostic skills -Advances in laboratory testing and imaging that improve diagnostic capability -Local, national and international initiatives to reduce diagnostic error