Background: This study investigates the survival outcomes of individuals with HIV receiving different treatment regimens compared to a control group. Utilizing a cohort dataset with demographic and clinical information, this research aims to assess the impact of various factors, including age, education, and
[...] Read more.
Background: This study investigates the survival outcomes of individuals with HIV receiving different treatment regimens compared to a control group. Utilizing a cohort dataset with demographic and clinical information, this research aims to assess the impact of various factors, including age, education, and travel time, on survival while controlling for confounding effects using propensity score adjustment. Methods: A total of 380 patients with HIV were included in this study, categorized into an intervention group receiving a specific treatment regimen and a control group. The primary outcome measured was the time to death or censoring. Survival analysis was performed using the Cox proportional hazards model, adjusted for potential confounders, including treatment (intervention and control), age, education, travel time, and gestational age at enrollment. Propensity scores were also incorporated to adjust for treatment selection bias. Results: The Cox model revealed a significant protective effect of the intervention on survival (hazard ratio (HR) = 0.583,
p = 0.045), indicating that the treatment improved survival outcomes compared to the control group. After adjusting for propensity scores, the relationship between the intervention and survival remained significant (HR = 0.631,
p = 0.106), suggesting the robustness of the treatment’s effect even after accounting for confounding variables. Other covariates, such as age, education, and travel time, did not show significant independent effects on survival, likely due to their correlation with the treatment variable. Conclusions: This study highlights the crucial role of the intervention in enhancing survival among individuals with HIV. The use of propensity score adjustment improves the validity of these findings by mitigating confounding bias in observational data. These results highlight the importance of ART (antiretroviral therapy) in HIV management and demonstrate the utility of statistical methods like propensity scores in clinical research. Further studies with diverse populations and advanced methodologies are recommended to validate these findings across different settings.
Full article
