Abstract
Background:
The introduction of antiretroviral therapy (ARV) has significantly improved the survival of people living with HIV (PLWH), increasing the proportion of individuals over 50 years old. This aging trend poses challenges, such as the development of age-related comorbidities and a higher prevalence of polypharmacy. The pharmacotherapeutic complexity, assessed using the Medication Regimen Complexity Index (MRCI), is crucial for identifying and optimizing treatment, especially in elderly and polymedicated patients.
Objective:
The main objective was to assess the association between different ARV regimens and the time required to reach a high level of pharmacotherapeutic complexity in PLWH.
Methods:
A single-center observational analytical research study was conducted, including adult PLWH on active ARV from January 2010 to December 2021 with follow-up until December 2023. An analysis of the time to reach MRCI ≥11.25 was performed, followed by a Cox regression model to determine the influence of ARV on high MRCI.
Results:
A total of 789 PLWH were included, median age of 52 years (interquartile range: 45-58). Overall, 195 patients had an MRCI value ≥11.25 with a mean time to reach it of 181.86 months (95% confidence interval [CI]: 176.24 to 187.49). Significant differences were observed in sex, advanced age, AIDS stage, presence of comorbidities, polypharmacy, and ARV-related variables. A multivariate Cox proportional hazards model showed an association between integrase inhibitor (INSTI)-containing regimens (hazard ratio [HR]: 1.83; 95% CI: 1.08 to 3.10) and non-nucleoside reverse transcriptase inhibitor (NNRTI)-based regimens (HR: 0.72; 95% CI: 0.52 to 0.98) with the time to reach high MRCI.
Conclusions and Relevance:
In summary, NNRTI-based regimens were associated with a lower likelihood of developing high MRCI compared to INSTI-based regimens, which was associated with a higher likelihood. These conclusions are based on a profile of PLWH that included advanced age and a high prevalence of comorbidities and polypharmacy. Identifying high MRCI may help us implement pharmacotherapeutic optimization strategies to improve health outcomes.
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