Survival analysis of left-truncated and right-censored HIV data: comparison of Cox regression and alternative models

BACKGROUND: This study examined the impact of delayed entry in HIV cohorts by analyzing left-truncated and right-censored (LTRC) survival data from 69 HIV-positive male patients (24 deaths) followed at a tertiary infectious diseases center. The primary objective was to empirically compare commonly used survival models in estimating survival and identifying prognostic factors under LTRC conditions. METHODS: Three LTRC-adapted modeling frameworks were applied with identical covariates: the semiparametric Cox proportional hazards model, accelerated failure time (AFT) models, and parametric proportional hazards models. Median survival time was estimated using Kaplan-Meier methods under both right-censoring-only and LTRC specifications to assess truncation-related differences. Hazard ratios (HRs) and 95% confidence intervals (CIs) were obtained from the LTRC-adjusted Cox model. Model performance was evaluated using information criteria (AIC, BIC, HQIC). RESULTS: Ignoring left truncation substantially inflated median survival estimates (3,885 vs. 2,626 days). In the LTRC-adjusted Cox model, age (HR = 1.049, 95% CI: 1.011-1.089) and log-transformed HIV RNA (HR = 1.214, 95% CI: 1.055-1.400) were significant predictors, whereas CD4 count and comorbidity status were not. Among the evaluated models, the Cox model showed the lowest information criterion values within this dataset. CONCLUSIONS: Appropriate risk-set specification under left truncation is essential for reliable survival estimation in delayed-entry HIV cohorts. Within this empirical dataset, the LTRC-adapted Cox model showed favorable performance relative to AFT and parametric PH alternatives.