RESUMEN
BACKGROUND: India accounts for about one-quarter of people contracting tuberculosis (TB) disease annually and nearly one-third of TB deaths globally. Many Indians do not navigate all care cascade stages to receive TB treatment and achieve recurrence-free survival. Guided by a population/exposure/comparison/outcomes (PECO) framework, we report findings of a systematic review to identify factors contributing to unfavorable outcomes across each care cascade gap for TB disease in India. METHODS AND FINDINGS: We defined care cascade gaps as comprising people with confirmed or presumptive TB who did not: start the TB diagnostic workup (Gap 1), complete the workup (Gap 2), start treatment (Gap 3), achieve treatment success (Gap 4), or achieve TB recurrence-free survival (Gap 5). Three systematic searches of PubMed, Embase, and Web of Science from January 1, 2000 to August 14, 2023 were conducted. We identified articles evaluating factors associated with unfavorable outcomes for each gap (reported as adjusted odds, relative risk, or hazard ratios) and, among people experiencing unfavorable outcomes, reasons for these outcomes (reported as proportions), with specific quality or risk of bias criteria for each gap. Findings were organized into person-, family-, and society-, or health system-related factors, using a social-ecological framework. Factors associated with unfavorable outcomes across multiple cascade stages included: male sex, older age, poverty-related factors, lower symptom severity or duration, undernutrition, alcohol use, smoking, and distrust of (or dissatisfaction with) health services. People previously treated for TB were more likely to seek care and engage in the diagnostic workup (Gaps 1 and 2) but more likely to suffer pretreatment loss to follow-up (Gap 3) and unfavorable treatment outcomes (Gap 4), especially those who were lost to follow-up during their prior treatment. For individual care cascade gaps, multiple studies highlighted lack of TB knowledge and structural barriers (e.g., transportation challenges) as contributing to lack of care-seeking for TB symptoms (Gap 1, 14 studies); lack of access to diagnostics (e.g., X-ray), non-identification of eligible people for testing, and failure of providers to communicate concern for TB as contributing to non-completion of the diagnostic workup (Gap 2, 17 studies); stigma, poor recording of patient contact information by providers, and early death from diagnostic delays as contributing to pretreatment loss to follow-up (Gap 3, 15 studies); and lack of TB knowledge, stigma, depression, and medication adverse effects as contributing to unfavorable treatment outcomes (Gap 4, 86 studies). Medication nonadherence contributed to unfavorable treatment outcomes (Gap 4) and TB recurrence (Gap 5, 14 studies). Limitations include lack of meta-analyses due to the heterogeneity of findings and limited generalizability to some Indian regions, given the country's diverse population. CONCLUSIONS: This systematic review illuminates common patterns of risk that shape outcomes for Indians with TB, while highlighting knowledge gaps-particularly regarding TB care for children or in the private sector-to guide future research. Findings may inform targeting of support services to people with TB who have higher risk of poor outcomes and inform multicomponent interventions to close gaps in the care cascade.
Asunto(s)
Tuberculosis , Humanos , India/epidemiología , Tuberculosis/terapia , Tuberculosis/diagnóstico , Tuberculosis/epidemiología , Accesibilidad a los Servicios de Salud , Resultado del Tratamiento , MasculinoRESUMEN
INTRODUCTION: Digital adherence technologies (DATs), such as phone-based technologies and digital pillboxes, can provide more person-centric approaches to support tuberculosis (TB) treatment. However, there are varying estimates of their performance for measuring medication adherence. METHODS: We conducted a systematic review (PROSPERO-CRD42022313526), which identified relevant published literature and preprints from January 2000 to April 2023 in five databases. Studies reporting quantitative data on the performance of DATs for measuring TB medication adherence against a reference standard, with at least 20 participants, were included. Study characteristics and performance outcomes (eg, sensitivity, specificity and predictive values) were extracted. Sensitivity was the proportion correctly classified as adherent by the DAT, among persons deemed adherent by a reference standard. Specificity was the proportion correctly classified as non-adherent by the DAT, among those deemed non-adherent by a reference standard. RESULTS: Of 5692 studies identified by our systematic search, 13 met inclusion criteria. These studies investigated medication sleeves with phone calls (branded as '99DOTS'; N=4), digital pillboxes N=5), ingestible sensors (N=2), artificial intelligence-based video-observed therapy (N=1) and multifunctional mobile applications (N=1). All but one involved persons with TB disease. For medication sleeves with phone calls, compared with urine testing, reported sensitivity and specificity were 70%-94% and 0%-61%, respectively. For digital pillboxes, compared with pill counts, reported sensitivity and specificity were 25%-99% and 69%-100%, respectively. For ingestible sensors, the sensitivity of dose detection was ≥95% compared with direct observation. Participant selection was the most frequent potential source of bias. CONCLUSION: The limited number of studies available suggests suboptimal and variable performance of DATs for dose monitoring, with significant evidence gaps, notably in real-world programmatic settings. Future research should aim to improve understanding of the relationships of specific technologies, settings and user engagement with DAT performance and should measure and report performance in a more standardised manner.