Comparison of two discrimination indexes in the categorisation of continuous predictors in time-to-event studies

  1. Irantzu Barrio 3
  2. María Xosé Rodríguez-Álvarez 1
  3. Luis Meira-Machado 2
  4. Cristobal Esteban 4
  5. Inmaculada Arostegui 3
  1. 1 Departamento de Estadística e Investigación Operativa and Biomedical Research Centre (CINBIO). Universidade de Vigo
  2. 2 University of Minho,
  3. 3 Departamento de Matemática Aplicada y Estadística e Investigación Operativa. Universidad del País Vasco UPV/EHU
  4. 4 Red de Investigación de Servicios de Salud en Enfermedades Crónicas
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    Red de Investigación de Servicios de Salud en Enfermedades Crónicas

    Madrid, España

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Revista:
Sort: Statistics and Operations Research Transactions

ISSN: 1696-2281

Año de publicación: 2017

Volumen: 41

Número: 1

Páginas: 73-92

Tipo: Artículo

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Otras publicaciones en: Sort: Statistics and Operations Research Transactions

Resumen

The Cox proportional hazards model is the most widely used survival prediction model for analysing time-to-event data. To measure the discrimination ability of a survival model the concordance probability index is widely used. In this work we studied and compared the performance of two different estimators of the concordance probability when a continuous predictor variable is categorised in a Cox proportional hazards regression model. In particular, we compared the c-index and the concordance probability estimator. We evaluated the empirical performance of both estimators through simulations. To categorise the predictor variable we propose a methodology which considers the maximal discrimination attained for the categorical variable. We applied this methodology to a cohort of patients with chronic obstructive pulmonary disease, in particular, we categorised the predictor variable forced expiratory volume in one second in percentage.

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Información de financiación

This study was supported by grants IT620-13 from the Departamento de Educaci?n, Pol?tica Ling??stica y Cultura del Gobierno Vasco, MTM2013-40941-P, MTM2014-55966-P and MTM2016-74931-P from the Ministerio de Econom?a y Competitividad and FEDER and the Agrupamento INBIOMED from DXPCTSUG-FEDER unhamaneira de facer Europa (2012/273). Mar?a Xos? Rodr?guez-?lvarez acknowledges financial support for Severo Ochoa Program SEV-2013-0323 and Basque Government BERC Program 2014-2017. Lu?s Meira-Machado acknowledges financial support for Portuguese Funds through FCT-"Funda??o para a Ci?ncia e a Tecnologia", within Project UID/MAT/00013/2013. The collection of the COPD data used for this study was supported in part by grants PI020510 from the Fondo de Investigaci?n Sanitaria and 200111002, 2005111008, from the Departamento de Salud del Gobierno Vasco and the Research Committee Hospital Galdakao-Usansolo.

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