Semiparametric Analysis of Interval-Censored Data Subject to Inaccurate Diagnoses with A Terminal Event

TL;DR

This paper develops a semiparametric Cox model for interval-censored data with inaccurate diagnoses, incorporating sensitivity and specificity, and demonstrates its effectiveness through simulations and AD risk analysis.

Contribution

It introduces a novel framework that accounts for diagnostic inaccuracies in interval-censored survival data using a Cox model with an EM algorithm.

Findings

Amyloid-beta significantly associated with Alzheimer's disease

Tau predicts both Alzheimer's disease and mortality

Method achieves semiparametric efficiency bounds

Abstract

Interval-censoring frequently occurs in studies of chronic diseases where disease status is inferred from intermittently collected biomarkers. Although many methods have been developed to analyze such data, they typically assume perfect disease diagnosis, which often does not hold in practice due to the inherent imperfect clinical diagnosis of cognitive functions or measurement errors of biomarkers such as cerebrospinal fluid. In this work, we introduce a semiparametric modeling framework using the Cox proportional hazards model to address interval-censored data in the presence of inaccurate disease diagnosis. Our model incorporates sensitivity and specificity of the diagnosis to account for uncertainty in whether the interval truly contains the disease onset. Furthermore, the framework accommodates scenarios involving a terminal event and when diagnosis is accurate, such as through postmortem analysis. We propose a nonparametric maximum likelihood estimation method for inference and develop an efficient EM algorithm to ensure computational feasibility. The regression coefficient estimators are shown to be asymptotically normal, achieving semiparametric efficiency bounds. We further validate our approach through extensive simulation studies and an application assessing Alzheimer's disease (AD) risk. We find that amyloid-beta is significantly associated with AD, but Tau is predictive of both AD and mortality.