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Rohr JK, Ive P, Horsburgh CR, et al. Developing a predictive risk model for first-line antiretroviral therapy failure in South Africa. J Int AIDS Soc. 2016;19(1):20987doi: 10.7448/IAS.19.1.20987.
Rohr, J. K., Ive, P., Horsburgh, C. R., Berhanu, R., Shearer, K., Maskew, M., Long, L., Sanne, I., Bassett, J., Ebrahim, O., & Fox, M. P. (2016). Developing a predictive risk model for first-line antiretroviral therapy failure in South Africa. Journal of the International AIDS Society, 19(1), 20987. https://doi.org/10.7448/IAS.19.1.20987
Rohr, Julia K, et al. "Developing a predictive risk model for first-line antiretroviral therapy failure in South Africa." Journal of the International AIDS Society vol. 19,1 (2016): 20987. doi: https://doi.org/10.7448/IAS.19.1.20987
Rohr JK, Ive P, Horsburgh CR, Berhanu R, Shearer K, Maskew M, Long L, Sanne I, Bassett J, Ebrahim O, Fox MP. Developing a predictive risk model for first-line antiretroviral therapy failure in South Africa. J Int AIDS Soc. 2016 Sep 26;19(1):20987. doi: 10.7448/IAS.19.1.20987. eCollection 2016. PMID: 27677395; PMCID: PMC5039239.
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J Int AIDS Soc. 2016 Sep 26;19(1):20987. doi: 10.7448/IAS.19.1.20987. eCollection 2016.

Developing a predictive risk model for first-line antiretroviral therapy failure in South Africa.

Journal of the International AIDS Society

Julia K Rohr, Prudence Ive, C Robert Horsburgh, Rebecca Berhanu, Kate Shearer, Mhairi Maskew, Lawrence Long, Ian Sanne, Jean Bassett, Osman Ebrahim, Matthew P Fox

Affiliations

  1. Center for Global Health & Development, Boston University, Boston, MA, USA; [email protected].
  2. Clinical HIV Research Unit, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
  3. Center for Global Health & Development, Boston University, Boston, MA, USA.
  4. Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA.
  5. Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
  6. Right to Care, HIV Testing Center, Johannesburg, South Africa.
  7. Witkoppen Health and Welfare Centre, Johannesburg, South Africa.
  8. Department of Medical Microbiology, University of Pretoria, Pretoria, South Africa.

PMID: 27677395 PMCID: PMC5039239 DOI: 10.7448/IAS.19.1.20987

Abstract

INTRODUCTION: A substantial number of patients with HIV in South Africa have failed first-line antiretroviral therapy (ART). Although individual predictors of first-line ART failure have been identified, few studies in resource-limited settings have been large enough for predictive modelling. Understanding the absolute risk of first-line failure is useful for patient monitoring and for effectively targeting limited resources for second-line ART. We developed a predictive model to identify patients at the greatest risk of virologic failure on first-line ART, and to estimate the proportion of patients needing second-line ART over five years on treatment.

METHODS: A cohort of patients aged ≥18 years from nine South African HIV clinics on first-line ART for at least six months were included. Viral load measurements and baseline predictors were obtained from medical records. We used stepwise selection of predictors in accelerated failure-time models to predict virologic failure on first-line ART (two consecutive viral load levels >1000 copies/mL). Multiple imputations were used to assign missing baseline variables. The final model was selected using internal-external cross-validation maximizing model calibration at five years on ART, and model discrimination, measured using Harrell's C-statistic. Model covariates were used to create a predictive score for risk group of ART failure.

RESULTS: A total of 72,181 patients were included in the analysis, with an average of 21.5 months (IQR: 8.8-41.5) of follow-up time on first-line ART. The final predictive model had a Weibull distribution and the final predictors of virologic failure were men of all ages, young women, nevirapine use in first-line regimen, low baseline CD4 count, high mean corpuscular volume, low haemoglobin, history of TB and missed visits during the first six months on ART. About 24.4% of patients in the highest quintile and 9.4% of patients in the lowest quintile of risk were predicted to experience treatment failure over five years on ART.

CONCLUSIONS: Age, sex, CD4 count and having any missed visits during the first six months on ART were the strongest predictors of ART failure. The predictive model identified patients at high risk of failure, and the predicted failure rates over five years closely reflected actual rates of failure.

Keywords: South Africa; antiretroviral therapy; predictive model; prognostic score; public health; resource-limited settings; treatment failure

Conflict of interest statement

The authors declare that they have no competing interests.

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