Open AccessEstimation of Relative and Absolute Risks in a Competing-Risks Setting Using a Nested Case-Control Study Design: Example From the ProMort Study
Author(s) -
Renata Zelić,
Daniela Zugna,
Matteo Bottai,
Ove Andrén,
Jonna Fridfeldt,
Jessica Carlsson,
Sabina Davidsson,
Valentina Fiano,
Michelangelo Fiorentino,
Francesca Giunchi,
Chiara Grasso,
Luca Lianas,
Cecilia Mascia,
Luca Molinaro,
Gianluigi Zanetti,
Lorenzo Richiardi,
Andreas Pettersson,
Olof Akre
Publication year - 2019
Publication title -
american journal of epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.33
H-Index - 256
eISSN - 1476-6256
pISSN - 0002-9262
DOI - 10.1093/aje/kwz026
Subject(s) - nested case control study , hazard ratio , medicine , prostate cancer , statistics , absolute risk reduction , cohort study , proportional hazards model , relative risk , cancer , cohort , econometrics , oncology , mathematics , confidence interval
In this paper, we describe the Prognostic Factors for Mortality in Prostate Cancer (ProMort) study and use it to demonstrate how the weighted likelihood method can be used in nested case-control studies to estimate both relative and absolute risks in the competing-risks setting. ProMort is a case-control study nested within the National Prostate Cancer Register (NPCR) of Sweden, comprising 1,710 men diagnosed with low- or intermediate-risk prostate cancer between 1998 and 2011 who died from prostate cancer (cases) and 1,710 matched controls. Cause-specific hazard ratios and cumulative incidence functions (CIFs) for prostate cancer death were estimated in ProMort using weighted flexible parametric models and compared with the corresponding estimates from the NPCR cohort. We further drew 1,500 random nested case-control subsamples of the NPCR cohort and quantified the bias in the hazard ratio and CIF estimates. Finally, we compared the ProMort estimates with those obtained by augmenting competing-risks cases and by augmenting both competing-risks cases and controls. The hazard ratios for prostate cancer death estimated in ProMort were comparable to those in the NPCR. The hazard ratios for dying from other causes were biased, which introduced bias in the CIFs estimated in the competing-risks setting. When augmenting both competing-risks cases and controls, the bias was reduced.