Brief Report

Sex Differences in Outcomes for Individuals Presenting for Third-Line Antiretroviral Therapy

Catherine Godfrey, MD, FRACP; Michael D. Hughes, PhD; Justin Ritz, MS; Lara Coelho, MD; Robert Gross, MD, MSCE; Robert Salata, MD; Rosie Mngqibisa, MB ChB; Carole L. Wallis, PhD, MSc; Makanga. E. Mumbi, MD; Mitch Matoga, MD; Selvamuthu Poongulali, MBChB; Marije Van Schalkwyk, MD; Evelyn Hogg, BA; Courtney V. Fletcher, PharmD; Beatriz Grinsztejn, MD, PhD; Ann C. Collier, MD


J Acquir Immune Defic Syndr. 2020;84(2):203-207. 

In This Article


Real-time HIV drug resistance results, treatment history, and historical drug resistance (when available) results were used to assign participants to one of 4 treatment cohorts. Participants with no LPV/r resistance and who were susceptible to at least one NRTI were assigned to cohort A. They continued their PI backbone, but NRTIs could be modified. Participants with LPV/r resistance and/or resistance to NRTIs were assigned to cohorts B or C, which prescribed regimens including darunavir/ritonavir and raltegravir, with either etravirine or optimized NRTIs. In cohort D, representing individuals with the most complex resistance profile, the best regimen was constructed using any study-provided or locally available agents. Ritonavir boosting was included in every cohort. This analysis combines cohorts B, C, and D (BCD) as all 3 involved newer ART regimens and numbers were too small in individual cohorts for meaningful analysis. Virological suppression was defined as HIV-1 RNA ≤200 c/mL at week 48, and VF was defined as confirmed HIV-1 RNA≥1000 c/mL at/after week 24. Toxicity and adherence interventions were managed as per the site's standard of care. Sex differences by cohort group (A or BCD) were evaluated using χ 2 tests, in participant characteristics using the Wilcoxon rank-sum test stratified by cohort group, and in outcomes using Cochran–Mantel–Haenszel Tests, logistic regression or proportional hazards models adjusted for cohort group. Differences were further evaluated in models adjusting for cohort group, country, baseline age, weight, and HIV-1 RNA and CD4 count, characteristics considered to have high potential to impact outcomes.