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Updated: May 12, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Loss to follow-up as a competing risk in an observational study of HIV-1 incidence
Susan M Graham1, Janet Raboud, R Scott McClelland
1Department of Medicine, University of Washington, Seattle, Washington, United States of America. grahamsm@u.washington.edu
Objective:
Conventional survival estimates may be biased if loss to follow-up (LTF) is associated with the outcome of interest. Our goal was to assess whether the association between sexual risk behavior and HIV-1 acquisition changed after accounting for LTF with competing risks regression.
Methods:
HIV-1-seronegative women who enrolled in a Kenyan sex worker cohort from 1993-2007 were followed prospectively and tested for HIV at monthly clinic visits. Our primary predictor was self-reported sexual risk behavior in the past week, analyzed as a time-dependent covariate. Outcomes included HIV-1 acquisition and LTF. We analyzed the data using Cox proportional hazards regression and competing risks regression, in which LTF was treated as a competing event.
Results:
A total of 1,513 women contributed 4,150 person-years (py), during which 198 (13.1%) acquired HIV-1 infection (incidence, 4.5 per 100 py) and 969 (64.0%) were LTF (incidence, 23.4 per 100 py). After adjusting for potential confounders, women reporting unprotected sex with multiple partners were less likely to be lost to follow-up (adjusted sub-hazard ratio (aSHR) 0.50, 95% confidence interval (CI) 0.32-0.76, relative to no sexual activity). The risk of HIV-1 acquisition after reporting unprotected sex with multiple partners was similar with Cox regression (adjusted hazard ratio (aHR) 2.41, 95% CI 1.36-4.27) and competing risks regression (aSHR 2.47, 95% CI 1.33-4.58).
Conclusions:
Unprotected sex with multiple partners was associated with higher HIV-1 acquisition risk, but lower attrition. This differential attrition did not substantially bias Cox regression estimates when compared to competing risks regression results.
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