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Predicting death and lost to follow-up among adults initiating antiretroviral therapy in resource-limited settings: Derivation and external validation of a risk score in Haiti

Author

Listed:
  • Margaret L McNairy
  • Deanna Jannat-Khah
  • Jean W Pape
  • Adias Marcelin
  • Patrice Joseph
  • Jean Edward Mathon
  • Serena Koenig
  • Martin Wells
  • Daniel W Fitzgerald
  • Arthur Evans

Abstract

Background: Over 18 million adults have initiated life-saving antiretroviral therapy (ART) in resource-poor settings; however, mortality and lost-to-follow-up rates continue to be high among patients in their first year after treatment start. Clinical decision tools are needed to identify patients at high risk for poor outcomes in order to provide individualized risk assessment and intervention. This study aimed to develop and externally validate risk prediction tools that estimate the probability of dying or of being lost to follow-up (LTF) during the year after starting ART. Methods: We used a derivation cohort of 7,031 adults age 15–70 years initiating ART from 2007 to 2013 at 6 clinics in Haiti; 242 (3.5%) had documented death and 1,521 (21.6%) were LTF at 1 year after starting ART. The following routinely collected data were used as predictors in two logistic regression models (one to predict death and another to predict LTF): age, gender, weight, CD4 count, WHO Stage, and diagnosis of tuberculosis (TB). The validation cohort consisted of 1,835 adults initiating ART at a different HIV clinic in Haiti during 2012. We assessed model discrimination by measuring the C-statistic, and measured model calibration by how closely the predicted probabilities approximated actual probabilities of the two outcomes. We derived a nomogram and a point-based risk score from the predictive models. Findings: The model predicting death within the year after starting ART had a C-statistic of 0.75 (95% CI 0.74 to 0.81). There was no evidence for significant overfitting and the predictions were well calibrated. The strongest predictors of 1-year mortality were male gender, low weight, low CD4 count, advanced WHO stage, and the absence of TB. In the validation cohort, the C-statistic was 0.69 (95% CI 0.59 to 0.77). A point-based risk score for death had a C-statistic 0.73 (95% CI 0.69 to 0.76) and categorizes patients as low risk (

Suggested Citation

  • Margaret L McNairy & Deanna Jannat-Khah & Jean W Pape & Adias Marcelin & Patrice Joseph & Jean Edward Mathon & Serena Koenig & Martin Wells & Daniel W Fitzgerald & Arthur Evans, 2018. "Predicting death and lost to follow-up among adults initiating antiretroviral therapy in resource-limited settings: Derivation and external validation of a risk score in Haiti," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-16, August.
  • Handle: RePEc:plo:pone00:0201945
    DOI: 10.1371/journal.pone.0201945
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    References listed on IDEAS

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    1. Horton, Nicholas J. & Kleinman, Ken P., 2007. "Much Ado About Nothing: A Comparison of Missing Data Methods and Software to Fit Incomplete Data Regression Models," The American Statistician, American Statistical Association, vol. 61, pages 79-90, February.
    2. Nancy Puttkammer & Steven Zeliadt & Jean Gabriel Balan & Janet Baseman & Rodney Destiné & Jean Wysler Domerçant & Garilus France & Nathaelf Hyppolite & Valérie Pelletier & Nernst Atwood Raphael & Kenn, 2014. "Development of an Electronic Medical Record Based Alert for Risk of HIV Treatment Failure in a Low-Resource Setting," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-12, November.
    3. Margaret L McNairy & Elaine J Abrams & Miriam Rabkin & Wafaa M El-Sadr, 2017. "Clinical decision tools are needed to identify HIV-positive patients at high risk for poor outcomes after initiation of antiretroviral therapy," PLOS Medicine, Public Library of Science, vol. 14(4), pages 1-6, April.
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