Clinical research study
Estimating the proportion of patients infected with HIV who will die of comorbid diseases

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Abstract

Purpose

Effective antiretroviral therapies have improved the prognosis for patients infected with the human immunodeficiency virus (HIV). We aimed to estimate the likelihood that HIV-infected patients would die of comorbid disease.

Methods

A probabilistic simulation of antiretroviral-naïve HIV-infected patients in the United States was calibrated with data from an observational cohort (N = 3545) and validated with data from a separate patient cohort (N = 12 574). The simulation explicitly represents the 2 main determinants of treatment failure and subsequent death from HIV-related causes: nonadherence to combination therapy and accumulation of phenotypic resistance to combination therapy. The likelihood of deaths not directly attributable to HIV was estimated from the Collaborations in HIV Outcomes Research-US (CHORUS) cohort.

Results

For patients with newly diagnosed HIV infections, CD4 counts of 500 cells/mm3, and viral loads of 10 000 copies/mL, the median estimated survival was 26.8 years for 30-year-olds, 24.4 years for 40-year-olds and 14.6 years for 50-year-olds. The proportion of deaths not directly attributable to HIV was 36% for 30-year-olds, 53% for 40-year-olds, and 72% for 50-year-olds. For patients with characteristics similar to CHORUS participants, the median estimated survival approached 20.4 years, the mean age at death approached 60.4 years, and 41% died of illnesses not directly attributable to HIV. These estimates of non-HIV mortality were likely conservative.

Conclusion

As HIV-infected patients live longer, our results suggest they will experience increasing mortality from causes not directly attributable to HIV. The projected risk from comorbid disease has clinical and policy implications for future delivery of care to HIV-infected patients.

Section snippets

Methods

We simulated cohorts of 10 000 antiretroviral-naïve patients who were newly diagnosed with chronic HIV infections. For the vast majority of analyses, each hypothetical cohort consisted of identical patients who were initially equivalent with respect to a particular combination of baseline characteristics (age, CD4 count, and viral load). For the particular analysis in which we estimated causes of non-HIV-related deaths, we simulated a hypothetical cohort with characteristics similar to those of

Calibration and validation of simulation

The computer simulation closely replicated Kaplan-Meier curves depicting the duration of combination therapy for antiretroviral-naïve patients in a large cohort of HIV-infected patients, demonstrating that the simulation was well calibrated (Figure 2, A–C). It was also able to approximate the survival curve for this cohort (Figure 2, D).

When 3-year mortality estimates for each of 20 possible combinations of baseline age, CD4 count, and viral load strata were compared with corresponding data

Discussion

HIV is increasingly a disease that people die with rather than a disease that people die from. The results of our simulation suggest that a substantial proportion of deaths among HIV-infected patients in the current treatment era will not be directly attributable to HIV. Indeed, for many of the groups examined, the simulation estimates that a majority of deaths will be from nonattributable causes. If the age, CD4 count, and viral load distributions of antiretroviral-naïve patients entering the

Acknowledgment

The authors thank Andrea Casas for editing, proofreading, and preparing the manuscript.

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    This work was funded by National Institute of Alcohol Abuse and Alcoholism, National Institutes of Health grants #1 K23 AA14483-01 and #UO1 AA13566-01, and National Library of Medicine grant #T15-LM07092-09.

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