Open Access
March 2020 Integrative survival analysis with uncertain event times in application to a suicide risk study
Wenjie Wang, Robert Aseltine, Kun Chen, Jun Yan
Ann. Appl. Stat. 14(1): 51-73 (March 2020). DOI: 10.1214/19-AOAS1287

Abstract

The concept of integrating data from disparate sources to accelerate scientific discovery has generated tremendous excitement in many fields. The potential benefits from data integration, however, may be compromised by the uncertainty due to incomplete/imperfect record linkage. Motivated by a suicide risk study, we propose an approach for analyzing survival data with uncertain event times arising from data integration. Specifically, in our problem deaths identified from the hospital discharge records together with reported suicidal deaths determined by the Office of Medical Examiner may still not include all the death events of patients, and the missing deaths can be recovered from a complete database of death records. Since the hospital discharge data can only be linked to the death record data by matching basic patient characteristics, a patient with a censored death time from the first dataset could be linked to multiple potential event records in the second dataset. We develop an integrative Cox proportional hazards regression in which the uncertainty in the matched event times is modeled probabilistically. The estimation procedure combines the ideas of profile likelihood and the expectation conditional maximization algorithm (ECM). Simulation studies demonstrate that under realistic settings of imperfect data linkage the proposed method outperforms several competing approaches including multiple imputation. A marginal screening analysis using the proposed integrative Cox model is performed to identify risk factors associated with death following suicide-related hospitalization in Connecticut. The identified diagnostics codes are consistent with existing literature and provide several new insights on suicide risk, prediction and prevention.

Citation

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Wenjie Wang. Robert Aseltine. Kun Chen. Jun Yan. "Integrative survival analysis with uncertain event times in application to a suicide risk study." Ann. Appl. Stat. 14 (1) 51 - 73, March 2020. https://doi.org/10.1214/19-AOAS1287

Information

Received: 1 November 2017; Revised: 1 May 2019; Published: March 2020
First available in Project Euclid: 16 April 2020

zbMATH: 07200161
MathSciNet: MR4085083
Digital Object Identifier: 10.1214/19-AOAS1287

Keywords: Cox model , data linkage , ECM algorithm , integrative learning , suicide prevention

Rights: Copyright © 2020 Institute of Mathematical Statistics

Vol.14 • No. 1 • March 2020
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