Evidence map›Paper›PMID 41928197›Full record

ArticleBMC women's health2026

Fine and gray competing risk regression model of predictors of loss to follow up among female sex workers receiving antiretroviral therapy in Nigeria: 2016-2022.

Wingston Felix Ng'ambi, Abiye Kalaiwo, Janne Estill, Erol Orel, Chigere Adoration, Kene David Nwosu, Olivia Keiser

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Article in BMC women's health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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7 authors.

Wingston Felix Ng'ambiInstitute of Global Health, University of Geneva, Geneva, Switzerland. wingston.ngambi@gmail.com.
Abiye KalaiwoInstitute of Global Health, University of Geneva, Geneva, Switzerland.
Janne EstillInstitute of Global Health, University of Geneva, Geneva, Switzerland.
Erol OrelInstitute of Global Health, University of Geneva, Geneva, Switzerland.
Chigere AdorationHeartland Alliance LTD/GTE (HALG), Abuja, Nigeria.
Kene David NwosuInstitute of Global Health, University of Geneva, Geneva, Switzerland.
Olivia KeiserInstitute of Global Health, University of Geneva, Geneva, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionGlobally loss to follow up (LTFU) in HIV treatment is a profound challenge in the era of expanded HIV treatment coverage amongst different populations including female sex workers (FSWs). Therefore, we conducted this study to assess the predictors of LTFU among female sex workers on antiretroviral therapy in Nigeria between 1 January 2016 and 31 August 2022.

methodsA retrospective cohort analysis of routine HIV program data evaluating the HIV treatment outcomes of FSWs from Bayelsa, Akwa Ibom, Cross Rivers, Niger and Lagos states in Nigeria. We fitted multivariable competing risk regression analyses for the rate of LTFU using death, stopping ART, and transferring to another clinic as competing events.

resultsA total of 16,727 FSWs were included in this analysis. By 31 August 2022, 15,655 (94%) were alive and under follow-up, 230 (1%) were lost to follow-up (LTFU), 87 (< 1%) had died, 481 (3%) had transferred to other clinics for ART, and 274 (2%) had stopped ART. The median follow-up time was 20 months (IQR: 13–27). Compared with FSWs from other states, those from Niger State had a lower risk of LTFU (adjusted subdistribution hazard ratio [aSHR] 0.56; 95% CI: 0.49–0.64). FSWs aged ≥ 30 years had a higher risk of LTFU than those aged 15–29 years (aSHR 1.24; 95% CI: 1.16–1.33). Migrants had a lower risk of LTFU than non-migrants (aSHR 0.69; 95% CI: 0.64–0.74). Compared with FSWs with no formal education, those with primary, secondary, and tertiary education had lower risks of LTFU, with adjusted SHRs of 0.21 (95% CI: 0.19–0.24), 0.42 (95% CI: 0.38–0.46), and 0.54 (95% CI: 0.48–0.60), respectively. FSWs with hypertension had a higher risk of LTFU (aSHR 1.27; 95% CI: 1.20–1.35), whereas those with normal BMI had a lower risk than underweight FSWs (aSHR 0.70; 95% CI: 0.65–0.74).

conclusionRetention on ART was 94%, with 15,655 of 16,727 FSWs remaining alive and under follow-up by 31 August 2022, although risk of LTFU varied across subgroups. Higher risk of LTFU was observed among FSWs aged ≥ 30 years, students, and those with hypertension, while lower risk was observed among FSWs from Niger State, migrants, unemployed FSWs, and those with normal BMI. Programs in similar settings may consider adapting implementation features of the Nigerian FSW program while strengthening support for subgroups at higher risk of LTFU.

Indexed as

Anti-HIV AgentsAnti-Retroviral AgentsHIV InfectionsLost to Follow-UpSex WorkersAdultFemaleHumansNigeriaRegression AnalysisRetrospective StudiesYoung AdultAnti-HIV AgentsAnti-Retroviral AgentsART outcomesFemale sex workersLoss-to-follow-upNigeriaSub-Saharan Africa

Identifiers

PMID41928197
PMCPMC13169552

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.