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Background <p>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.</p> Methods <p>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).</p> Results <p>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.</p> Conclusions <p>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.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月9日

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  • Tuba Çakır,
  • Yüksel Terzi

摘要

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.