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Developing a model to predict unfavourable treatment outcomes in patients with tuberculosis and human immunodeficiency virus co-infection in Delhi, India

Author

Listed:
  • Chandravali Madan
  • Kamal Kishore Chopra
  • Srinath Satyanarayana
  • Diya Surie
  • Vineet Chadha
  • Kuldeep Singh Sachdeva
  • Ashwani Khanna
  • Rajesh Deshmukh
  • Lopamudra Dutta
  • Amit Namdeo
  • Ajay Shukla
  • Karuna Sagili
  • Lakhbir Singh Chauhan

Abstract

Background: Tuberculosis (TB) patients with human immunodeficiency virus (HIV) co-infection have worse TB treatment outcomes compared to patients with TB alone. The distribution of unfavourable treatment outcomes differs by socio-demographic and clinical characteristics, allowing for early identification of patients at risk. Objective: To develop a statistical model that can provide individual probabilities of unfavourable outcomes based on demographic and clinical characteristics of TB-HIV co-infected patients. Methodology: We used data from all TB patients with known HIV-positive test results (aged ≥15 years) registered for first-line anti-TB treatment (ATT) in 2015 under the Revised National TB Control Programme (RNTCP) in Delhi, India. We included variables on demographics and pre-treatment clinical characteristics routinely recorded and reported to RNTCP and the National AIDS Control Organization. Binomial logistic regression was used to develop a statistical model to estimate probabilities of unfavourable TB treatment outcomes (i.e., death, loss to follow-up, treatment failure, transfer out of program, and a switch to drug-resistant regimen). Results: Of 55,260 TB patients registered for ATT in 2015 in Delhi, 928 (2%) had known HIV-positive test results. Of these, 816 (88%) had drug-sensitive TB and were ≥15 years. Among 816 TB-HIV patients included, 157 (19%) had unfavourable TB treatment outcomes. We developed a model for predicting unfavourable outcomes using age, sex, disease classification (pulmonary versus extra-pulmonary), TB treatment category (new or previously treated case), sputum smear grade, known HIV status at TB diagnosis, antiretroviral treatment at TB diagnosis, and CD4 cell count at ATT initiation. The chi-square p-value for model calibration assessed using the Hosmer-Lemeshow test was 0.15. The model discrimination, measured as the area under the receiver operator characteristic (ROC) curve, was 0.78. Conclusion: The model had good internal validity, but should be validated with an independent cohort of TB-HIV co-infected patients to assess its performance before clinical or programmatic use.

Suggested Citation

  • Chandravali Madan & Kamal Kishore Chopra & Srinath Satyanarayana & Diya Surie & Vineet Chadha & Kuldeep Singh Sachdeva & Ashwani Khanna & Rajesh Deshmukh & Lopamudra Dutta & Amit Namdeo & Ajay Shukla , 2018. "Developing a model to predict unfavourable treatment outcomes in patients with tuberculosis and human immunodeficiency virus co-infection in Delhi, India," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-16, October.
  • Handle: RePEc:plo:pone00:0204982
    DOI: 10.1371/journal.pone.0204982
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    References listed on IDEAS

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    1. Srinath Satyanarayana & Sreenivas Achutan Nair & Sarabjit Singh Chadha & Roopa Shivashankar & Geetanjali Sharma & Subhash Yadav & Subrat Mohanty & Vishnuvardhan Kamineni & Nevin Charles Wilson & Antho, 2011. "From Where Are Tuberculosis Patients Accessing Treatment in India? Results from a Cross-Sectional Community Based Survey of 30 Districts," PLOS ONE, Public Library of Science, vol. 6(9), pages 1-8, September.
    2. Ramnath Subbaraman & Ruvandhi R Nathavitharana & Srinath Satyanarayana & Madhukar Pai & Beena E Thomas & Vineet K Chadha & Kiran Rade & Soumya Swaminathan & Kenneth H Mayer, 2016. "The Tuberculosis Cascade of Care in India’s Public Sector: A Systematic Review and Meta-analysis," PLOS Medicine, Public Library of Science, vol. 13(10), pages 1-38, October.
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