BACKGROUND: High attrition and irregular testing for human immunodeficiency virus (HIV) in cohort studies for high-risk populations can bias incidence estimates. We compare incidence trends for high-risk women attending a dedicated HIV prevention and treatment clinic, using common methods for assigning when seroconversion occurs and whether seroconversion occurs among those with attrition. METHODS: Between April 2008 and May 2009, women were enrolled into cohort 1 and from January 2013 into cohort 2, then scheduled for follow-up once every 3 months. Incidence trends based on assuming a midpoint in the seroconversion interval were compared with those of assigning a random-point. We also compared estimates based on the random-point with and without multiple imputation (MI) of serostatuses for participants with attrition. RESULTS: By May 2017, 3084 HIV-negative women had been enrolled with 18,364 clinic visits. Before attrition, 27.6% (6990 of 25,354) were missed visits. By August 2017, 65.8% (426 of 647) of those enrolled in cohort 1 and 49.0% (1194 of 2437) in cohort 2 were defined with attrition. Among women with 1 or more follow-up visit, 93 of 605 in cohort 1 and 77 of 1601 in cohort 2 seroconverted. Periods with longer seroconversion intervals appeared to have noticeable differences in incidences when comparing the midpoint and random-point values. The MI for attrition is likely to have overestimated incidence after escalated attrition of participants. Based on random-point without MI for attrition, incidence at end of observation was 3.8/100 person-years in cohort 1 and 1.8/100 in cohort 2. CONCLUSIONS: The random-point approach attenuated variation in incidence observed using midpoint. The high incidence after years of ongoing prevention efforts in this vulnerable population should be investigated to further reduce incidence.
BACKGROUND: High attrition and irregular testing for human immunodeficiency virus (HIV) in cohort studies for high-risk populations can bias incidence estimates. We compare incidence trends for high-risk women attending a dedicated HIV prevention and treatment clinic, using common methods for assigning when seroconversion occurs and whether seroconversion occurs among those with attrition. METHODS: Between April 2008 and May 2009, women were enrolled into cohort 1 and from January 2013 into cohort 2, then scheduled for follow-up once every 3 months. Incidence trends based on assuming a midpoint in the seroconversion interval were compared with those of assigning a random-point. We also compared estimates based on the random-point with and without multiple imputation (MI) of serostatuses for participants with attrition. RESULTS: By May 2017, 3084 HIV-negative women had been enrolled with 18,364 clinic visits. Before attrition, 27.6% (6990 of 25,354) were missed visits. By August 2017, 65.8% (426 of 647) of those enrolled in cohort 1 and 49.0% (1194 of 2437) in cohort 2 were defined with attrition. Among women with 1 or more follow-up visit, 93 of 605 in cohort 1 and 77 of 1601 in cohort 2 seroconverted. Periods with longer seroconversion intervals appeared to have noticeable differences in incidences when comparing the midpoint and random-point values. The MI for attrition is likely to have overestimated incidence after escalated attrition of participants. Based on random-point without MI for attrition, incidence at end of observation was 3.8/100 person-years in cohort 1 and 1.8/100 in cohort 2. CONCLUSIONS: The random-point approach attenuated variation in incidence observed using midpoint. The high incidence after years of ongoing prevention efforts in this vulnerable population should be investigated to further reduce incidence.
Authors: Andrew Abaasa; Jim Todd; Stephen Nash; Yunia Mayanja; Pontiano Kaleebu; Patricia E Fast; Matt Price Journal: BMC Med Res Methodol Date: 2020-02-12 Impact factor: 4.615
Authors: Deogratius Ssemwanga; Nicholas Bbosa; Rebecca N Nsubuga; Alfred Ssekagiri; Anne Kapaata; Maria Nannyonjo; Faridah Nassolo; Alex Karabarinde; Joseph Mugisha; Janet Seeley; Gonzalo Yebra; Andrew Leigh Brown; Pontiano Kaleebu Journal: Viruses Date: 2020-11-10 Impact factor: 5.048
Authors: Nicholas Bbosa; Deogratius Ssemwanga; Rebecca N Nsubuga; Noah Kiwanuka; Bernard S Bagaya; John M Kitayimbwa; Alfred Ssekagiri; Gonzalo Yebra; Pontiano Kaleebu; Andrew Leigh-Brown Journal: Viruses Date: 2021-05-24 Impact factor: 5.048