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Modeling Mortality Risk Among HIV/AIDS Patients on Antiretroviral Therapy Using Survival Methods: Insights from Kaplan-Meier, Cox Proportional Hazards Models, and Log Rank Tests

Author

Listed:
  • Winfred Karimi

    (Department of Mathematics, Meru University of Science Technology, Kenya)

  • Robert Muriungi Gitunga

    (Department of Mathematics, Meru University of Science Technology, Kenya)

  • Frank Gekara Onyambu

    (Department of Medical Laboratory, Meru Universityo f Science Technology,Kenya)

  • Christine Gacheri

    (Department of Mathematics, Meru University of Science Technology, Kenya)

Abstract

Background: Despite significant advancements in antiretroviral therapy (ART), HIV/AIDS continues to be a critical health challenge in Meru County, Kenya, particularly regarding the high mortality rates among people living with HIV (PLHIV). This study aimed to fit a survival model for predicting mortality and evaluate survival differences among adult HIV/AIDS patients under ART at Meru Teaching and Referral Hospital (MTRH). Method: A retrospective cohort design was adopted, using secondary data from MTRH for all HIV-positive adults who received ART between January 1, 2018, and December 31, 2023. The target population comprised patients with complete medical records available for analysis. Collected data included demographic, socioeconomic, and clinical variables, with mortality as the event of interest. Data were de-identified to ensure privacy and analyzed using R statistical software. The quantitative analysis employed the Cox Proportional Hazards regression model to fit a survival model for predicting mortality. The Log-rank test evaluated survival differences among PLHIV across different treatment groups. Results: Results indicated that gender and age were significant predictors of mortality. Specifically, being male was associated with a 72% higher hazard of mortality compared to females (exp(coef) = 1.718), and each additional year of age increased the hazard by 1.5% (coefficient = 1.015). However, smoking status and employment were not significantly associated with mortality. The Log-rank test revealed a significant difference in survival rates between male and female participants (χ2 =4.1, df=1, p=0.04), with females showing better survival outcomes, while no significant differences were found based on age, smoking status, or marital status. Conclusion: The study concluded that gender and age are key determinants of mortality among PLHIV under ART at MTRH, with males facing higher mortality risks. The findings emphasize the need for gender-sensitive healthcare interventions and age-appropriate care strategies to improve survival outcomes. Further research is recommended to explore the specific challenges faced by male PLHIV and to investigate the broader impact of socioeconomic factors on survival outcomes.

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Handle: RePEc:epw:ejmath:v:6:y:2025:i:2:id:14389
DOI: 10.24018/ejmath.2025.6.2.389
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