Additional economic burden of HIV infection in treating adult patients with Hodgkin lymphoma

Objective: To evaluate, from a pharmacoeconomic perspective, treatment strategies for adult patients with Hodgkin lymphoma (HL) complicated by human immunodeficiency virus (HIV) infection and HL patients without HIV infection. Material and methods. The study sampled 67 adult HL patients including 34 HIV-positive (HIV-HL group) and 33 HIV-negative (nonHIV-HL group) subjects. All patients were treated at the Loginov Moscow Clinical Scientific Center between June 2015 and December 2023. The median surface area and body weight of patients were 1.85 m2 and 70.9 kg, respectively. Cost estimation was performed using decision-tree pharmacoeconomic modeling, medical institution price lists (excluding marginal markup). Government-regulated drug prices (for essential medicines), and 2024 public procurement prices (for other drugs, including targeted therapies and autologous stem cell transplantations) were considered. HIV treatment costs were excluded. Clinical endpoints included remission rates, 5-year overall survival, 5-year event-free survival, and 5-year relapse-free survival. Pharmacoeconomic analyses comprised cost-minimization, cost-effectiveness, and incremental cost-effectiveness analyses. Results were validated via probabilistic sensitivity analysis using Monte Carlo simulation (10,000-patient extrapolation). Results. Treatment in the HIV-HL group was found to be more cost-effective both with the development of complications (1,020,332 vs. 3,935,166.50 rubles) and without complications (440,616 vs. 584,641 rubles), provided that the median cost of treatment is calculated. Weighted average costs favored HIV-HL treatment only with complications (2,416,961.67 vs. 3,578,882.08 rubles); without complications, non-HIV-HL treatment was more cost-effective (575,499.19 vs. 852,010.48 rubles). Monte Carlo simulations revealed model instability, though two of four scenarios (remission in HIV-HL with complications, using median and weighted costs) demonstrated robust outcomes. Conclusion. The decision-tree model effectively evaluated median and weighted treatment costs for HL by HIV status. A combined pricing approach identified key cost drivers, including median-mean disparities, while cost-effectiveness and Monte Carlo analyses confirmed result stability. Both methods highlighted limitations in extrapolating small-cohort data to broader populations.