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      The Tuberculosis Cascade of Care in India’s Public Sector: A Systematic Review and Meta-analysis

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          Abstract

          Background

          India has 23% of the global burden of active tuberculosis (TB) patients and 27% of the world’s “missing” patients, which includes those who may not have received effective TB care and could potentially spread TB to others. The “cascade of care” is a useful model for visualizing deficiencies in case detection and retention in care, in order to prioritize interventions.

          Methods and Findings

          The care cascade constructed in this paper focuses on the Revised National TB Control Programme (RNTCP), which treats about half of India’s TB patients. We define the TB cascade as including the following patient populations: total prevalent active TB patients in India, TB patients who reach and undergo evaluation at RNTCP diagnostic facilities, patients successfully diagnosed with TB, patients who start treatment, patients retained to treatment completion, and patients who achieve 1-y recurrence-free survival. We estimate each step of the cascade for 2013 using data from two World Health Organization (WHO) reports (2014–2015), one WHO dataset (2015), and three RNTCP reports (2014–2016). In addition, we conduct three targeted systematic reviews of the scientific literature to identify 39 unique articles published from 2000–2015 that provide additional data on five indicators that help estimate different steps of the TB cascade. We construct separate care cascades for the overall population of patients with active TB and for patients with specific forms of TB—including new smear-positive, new smear-negative, retreatment smear-positive, and multidrug-resistant (MDR) TB.

          The WHO estimated that there were 2,700,000 (95%CI: 1,800,000–3,800,000) prevalent TB patients in India in 2013. Of these patients, we estimate that 1,938,027 (72%) TB patients were evaluated at RNTCP facilities; 1,629,906 (60%) were successfully diagnosed; 1,417,838 (53%) got registered for treatment; 1,221,764 (45%) completed treatment; and 1,049,237 (95%CI: 1,008,775–1,083,243), or 39%, of 2,700,000 TB patients achieved the optimal outcome of 1-y recurrence-free survival.

          The separate cascades for different forms of TB highlight different patterns of patient attrition. Pretreatment loss to follow-up of diagnosed patients and post-treatment TB recurrence were major points of attrition in the new smear-positive TB cascade. In the new smear-negative and MDR TB cascades, a substantial proportion of patients who were evaluated at RNTCP diagnostic facilities were not successfully diagnosed. Retreatment smear-positive and MDR TB patients had poorer treatment outcomes than the general TB population. Limitations of our analysis include the lack of available data on the cascade of care in the private sector and substantial uncertainty regarding the 1-y period prevalence of TB in India.

          Conclusions

          Increasing case detection is critical to improving outcomes in India’s TB cascade of care, especially for smear-negative and MDR TB patients. For new smear-positive patients, pretreatment loss to follow-up and post-treatment TB recurrence are considerable points of attrition that may contribute to ongoing TB transmission. Future multisite studies providing more accurate information on key steps in the public sector TB cascade and extension of this analysis to private sector patients may help to better target interventions and resources for TB control in India.

          Abstract

          In this systematic review and meta-analysis of public sector health data, Ramnath Subbaraman and colleagues estimate how many tuberculosis patients are "lost" and therefore do not receive effective care at each step of the treatment cascade.

          Author Summary

          Why was this study done?
          • India is the country with the highest burden of tuberculosis (TB) in the world, with one-quarter of the world’s patients with active TB disease.

          • The World Health Organization (WHO) estimates that India has nearly 1 million “missing” TB patients, who have not been reported to the national TB program and who therefore may not have received effective TB care.

          • Government reports and studies from local regions of India suggest that a considerable percentage of TB patients are evaluated at government health facilities but fail to be diagnosed with TB or fail to start TB treatment even if they are correctly diagnosed, but these reports and studies have not been collectively analyzed to provide national estimates of critical points at which patients are being “lost” from the government TB program.

          • The purpose of our study is to estimate how many TB patients in India’s national TB program are not being detected, not enrolling in treatment, not completing treatment, and not surviving without TB recurrence for 1 y after finishing treatment, using a model called the “cascade of care.”

          What did the researchers do and find?
          • To estimate different steps of the TB cascade of care in India in 2013, we collected data from multiple official reports published by the WHO and India’s national TB program.

          • We also conducted three systematic searches of the medical literature to identify 39 studies published between 2000–2015 that describe patient loss to follow-up at different steps of India’s TB cascade; we synthesized some of these findings using an approach called meta-analysis.

          • We estimate that, of about 2,700,000 prevalent TB patients in India in 2013, 1,938,027 (72%) were evaluated at government TB health facilities; 1,629,906 (60%) were successfully diagnosed with TB; 1,417,838 (53%) started TB treatment; 1,221,764 (45%) completed TB treatment; and about 1,049,237 (39%) achieved the optimal outcome of 1-y recurrence-free survival.

          • Patients who had a history of TB in the past (also called retreatment patients) and patients with TB resistant to the two most effective medications (also called multidrug-resistant TB) have considerably worse outcomes compared to other TB patients.

          • The critical points at which patients are being “lost” to the government system varies depending on the type of TB that a patient has.

          What do these findings mean?
          • Our findings suggest that, for some forms of TB—such as smear-negative TB and multidrug-resistant TB—increasing detection and diagnosis of new patients by using new TB diagnostic tests may be the most important intervention for improving patient outcomes.

          • For other types of TB patients—such as new smear-positive patients—reducing loss to follow-up immediately after TB is diagnosed and improving adherence to medications so that TB is less likely to recur might be the best interventions to improve patient outcomes.

          • Since a considerable proportion of patients who complete TB therapy experience recurrence of TB, routine follow-up of all patients for 1 y after completion of TB therapy may be an efficient approach for identifying new TB patients.

          • Our study is limited by the fact that very little information is available regarding treatment outcomes for TB patients receiving care in the private sector and by considerable uncertainty in the number of prevalent TB patients in India.

          • We recommend that well-designed research be conducted at multiple sites in India’s national TB program and in the private sector to improve the accuracy of the TB cascade in the future and to monitor progress on TB control.

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          Most cited references59

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          The number of privately treated tuberculosis cases in India: an estimation from drug sales data

          Summary Background Understanding the amount of tuberculosis managed by the private sector in India is crucial to understanding the true burden of the disease in the country, and thus globally. In the absence of quality surveillance data on privately treated patients, commercial drug sales data offer an empirical foundation for disease burden estimation. Methods We used a large, nationally representative commercial dataset on sales of 189 anti-tuberculosis products available in India to calculate the amount of anti-tuberculosis treatment in the private sector in 2013–14. We corrected estimates using validation studies that audited prescriptions against tuberculosis diagnosis, and estimated uncertainty using Monte Carlo simulation. To address implications for numbers of patients with tuberculosis, we explored varying assumptions for average duration of tuberculosis treatment and accuracy of private diagnosis. Findings There were 17·793 million patient-months (95% credible interval 16·709 million to 19·841 million) of anti-tuberculosis treatment in the private sector in 2014, twice as many as the public sector. If 40–60% of private-sector tuberculosis diagnoses are correct, and if private-sector tuberculosis treatment lasts on average 2–6 months, this implies that 1·19–5·34 million tuberculosis cases were treated in the private sector in 2014 alone. The midpoint of these ranges yields an estimate of 2·2 million cases, two to three times higher than currently assumed. Interpretation India's private sector is treating an enormous number of patients for tuberculosis, appreciably higher than has been previously recognised. Accordingly, there is a re-doubled need to address this burden and to strengthen surveillance. Tuberculosis burden estimates in India and worldwide require revision. Funding Bill & Melinda Gates Foundation.
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            A cascade of care for diabetes in the United States: visualizing the gaps.

            A "cascade-of-care" concept helped to address implementation gaps in HIV care.
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              Predictors of relapse among pulmonary tuberculosis patients treated in a DOTS programme in South India.

              To identify risk factors associated with relapse among cured tuberculosis (TB) patients in a DOTS programme in South India. Sputum samples collected from a cohort of TB patients registered between April 2000 and December 2001 were examined by fluorescence microscopy for acid-fast bacilli and by culture for Mycobacterium tuberculosis at 6, 12 and 18 months after treatment completion. Of the 534 cured patients, 503 (94%) were followed up for 18 months after treatment completion. Of these, 62 (12%) relapsed during the 18-month period; 48 (77%) of the 62 relapses occurred during the first 6 months of follow-up. Patients who took treatment irregularly were twice more likely to have a relapse than adherent patients (20% vs. 9%; adjusted odds ratio [aOR] 2.5; 95% CI 1.4-4.6). Other independent predictors of relapse were initial drug resistance to isoniazid and/or rifampicin (aOR 4.8; 95% CI 2.0-11.6) and smoking (aOR 3.1; 95% CI 1.6-6.0). The relapse rate among non-smoking, treatment adherent patients with drug-sensitive organisms was 4.8%. The relapse rate under the DOTS programme may be reduced by ensuring that patients take their treatment regularly and are counselled effectively about quitting smoking.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS Med
                PLoS Med
                plos
                plosmed
                PLoS Medicine
                Public Library of Science (San Francisco, CA USA )
                1549-1277
                1549-1676
                25 October 2016
                October 2016
                31 October 2016
                : 13
                : 10
                : e1002149
                Affiliations
                [1 ]Division of Infectious Diseases, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
                [2 ]Partners for Urban Knowledge, Action, and Research (PUKAR), Mumbai, India
                [3 ]Division of Infectious Diseases, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, United States of America
                [4 ]Section of Infectious Diseases & Immunity, Imperial College London, London, United Kingdom
                [5 ]Department of Epidemiology, Biostatistics and Occupational Health and McGill International TB Centre, McGill University, Montreal, Canada
                [6 ]Center for Operations Research, International Union Against Tuberculosis and Lung Disease, Paris, France
                [7 ]Department of Social and Behavioral Research, National Institute for Research in Tuberculosis, Chennai, India
                [8 ]Epidemiology and Research Division, National Tuberculosis Institute, Bangalore, India
                [9 ]World Health Organization, Country Office for India (RNTCP-TSN), New Delhi, India
                [10 ]Indian Council of Medical Research, New Delhi, India
                [11 ]The Fenway Institute, Boston, Massachusetts, United States of America
                Harvard School of Public Health, UNITED STATES
                Author notes

                The authors of this manuscript have read the journal's policy and have the following competing interests: MP is a consultant to the Bill & Melinda Gates Foundation and a member of the Editorial Board of PLOS Medicine.

                • Conceptualization: RS SSa RRN KHM MP SSw VKC KR BET.

                • Formal analysis: RS RRN SSa.

                • Methodology: RS RRN SSa MP KHM.

                • Resources: MP KHM RS.

                • Supervision: KHM MP SSw VKC KR.

                • Validation: RS RRN SSa MP KHM.

                • Visualization: RS.

                • Writing – original draft: RS.

                • Writing – review & editing: RRN SSa KHM MP VKC SSw KR BET.

                Author information
                http://orcid.org/0000-0002-2063-943X
                http://orcid.org/0000-0002-3544-5021
                http://orcid.org/0000-0001-7601-0780
                Article
                PMEDICINE-D-16-01101
                10.1371/journal.pmed.1002149
                5079571
                27780217
                164caaad-8ee1-4688-9280-cbcb043cffb0
                © 2016 Subbaraman et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 5 April 2016
                : 9 September 2016
                Page count
                Figures: 11, Tables: 5, Pages: 38
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100000060, National Institute of Allergy and Infectious Diseases;
                Award ID: R25 TW009338
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000060, National Institute of Allergy and Infectious Diseases;
                Award ID: AI007433
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000060, National Institute of Allergy and Infectious Diseases;
                Award ID: 2P30AI060354-11
                Award Recipient :
                Funded by: Imperial College London (GB)
                Award ID: Institutional Strategic Support Fund Global Health Fellowship
                Award Recipient :
                Funded by: Canadian Thoracic Society
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100005850, International Union Against Tuberculosis and Lung Disease;
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100001804, Canada Research Chairs;
                Award Recipient :
                RS was supported by a Fogarty Global Health Equity Scholars Fellowship (NIAID R25 TW009338, http://ghes.berkeley.edu/) and a Harvard University T32 HIV post-doctoral clinical research fellowship (NIAID AI007433, http://cfar.globalhealth.harvard.edu). RRN was supported by a grant from the Harvard Center for AIDS Research (NIAID 2P30AI060354-11, http://cfar.globalhealth.harvard.edu) and an Imperial College Institutional Strategic Support Fund Global Health Fellowship. SSa is supported by a studentship from the Canadian Thoracic Society (July 2015-June 2016, https://cts.lung.ca) and a fellowship from the Center for Operations Research, The Union, Paris, France ( http://www.theunion.org). MP is supported by a Canada Research Chair award and grants from IC-IMPACTS and the Bill & Melinda Gates Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
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                All relevant data are available within the paper and its supporting information files, with references to the original manuscripts and reports from which data were extracted for the systematic reviews.

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