The potential deployment of a pan-tuberculosis drug regimen in India: A modelling analysis.
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ABSTRACT:
SUBMITTER: Arinaminpathy N
PROVIDER: S-EPMC7100958 | biostudies-literature | 2020
REPOSITORIES: biostudies-literature
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The potential deployment of a pan-tuberculosis drug regimen in India: A modelling analysis.
Arinaminpathy Nimalan N Gomez Gabriela B GB Sachdeva Kuldeep S KS Rao Raghuram R Parmar Malik M Nair Sreenivas A SA Rade Kiran K Kumta Sameer S Hermann David D Hanson Christy C Chin Daniel P DP Dewan Puneet P
PloS one 20200327 3
There is increasing interest in future, highly-potent 'pan-TB' regimens against tuberculosis (TB), that may be equally effective in both drug-susceptible and rifampicin-resistant (RR) forms of TB. Taking the example of India, the country with the world's largest burden of TB, we show that adoption of these regimens could be: (i) epidemiologically impactful, and (ii) cost-saving to the national TB programme, even if the regimen itself is more costly than current TB treatment. Mathematical modelli ...[more]
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Project description:BackgroundA pan-tuberculosis regimen that could be initiated without knowledge of drug susceptibility has been proposed as an objective of tuberculosis regimen development. We modelled the health and economic benefits of such a regimen and analysed which of its features contribute most to impact and savings.MethodsWe constructed a mathematical model of tuberculosis treatment parameterised with data from the published literature specific to three countries with a high tuberculosis burden (India, the Philippines, and South Africa). Our model simulated cohorts of newly diagnosed tuberculosis patients, including drug susceptibility testing if performed, regimen assignment, discontinuation, adherence, costs, and resulting outcomes of durable cure (microbiological cure without relapse), need for retreatment, or death. We compared a pan-tuberculosis regimen meeting the WHO 2023 target regimen profile against the standard of care of separate rifampicin-susceptible and rifampicin-resistant regimens. We estimated incremental cures; averted deaths, secondary cases, and costs; and prices below which a pan-tuberculosis regimen would be cost saving. We also assessed scenarios intended to describe which mechanisms of benefit from a pan-tuberculosis regimen (including improved characteristics compared with the current rifampicin-susceptible and rifampicin-resistant regimens and improved regimen assignment and retention in care for patients with rifampicin-resistant tuberculosis) would be most impactful. Results are presented as a range of means across countries with the most extreme 95% uncertainty intervals (UIs) from the three UI ranges.FindingsCompared with the standard of care, a pan-tuberculosis regimen could increase the proportion of patients durably cured after an initial treatment attempt from 69-71% (95% UI 57-80) to 75-76% (68-83), preventing 30-32% of the deaths (20-43) and 17-20% of the transmission (9-29) that occur after initial tuberculosis diagnosis. Considering savings to the health system and patients during and after the initial treatment attempt, the regimen could reduce non-drug costs by 32-42% (22-49) and would be cost saving at prices below US$170-340 (130-510). A rifamycin-containing regimen that otherwise met pan-tuberculosis targets yielded only slightly less impact, indicating that most of the benefits from a pan-tuberculosis regimen resulted from its improvements upon the rifampicin-susceptible standard of care. Eliminating non-adherence and treatment discontinuation, for example via a long-acting injectable regimen, increased health impact and savings.InterpretationIn countries with a high tuberculosis burden, a shorter, highly efficacious, safe, and tolerable regimen to treat all tuberculosis could yield substantial health improvements and savings.FundingBill & Melinda Gates Foundation.
| S-EPMC11413512 | biostudies-literature
Project description:Globally efforts are underway to shorten the existing 6-month tuberculosis (TB) treatment regimen for drug-sensitive patients, which would be equally effective and safe. At present, there is a lack of evidence on the cost implications of a shorter 4-month TB regimen in India. This economic modeling study was conducted in the Indian context with a high TB burden. We used a hybrid economic model comprising of a decision tree and Markov analysis. The study estimated the incremental costs, life years (LYs), and quality-adjusted life years (QALYs) gained by the introduction of a Moxifloxacin-based shorter 4-month treatment regimen for pulmonary TB patients. The outcomes are expressed in incremental cost-effectiveness ratios (ICERs) per QALYs gained. The cost per case to be treated under the 4-month regimen was USD 145.94 whereas for the 6-month regimen it was USD 150.39. A shorter 4-month TB regimen was cost-saving with USD 4.62 per LY and USD 5.29 per QALY. One-way sensitivity analysis revealed that the cost of the drugs for the 4-month regimen, hospitalization cost for adverse drug reactions, and human resources incurred for the 6-month regimen had a higher influence on the ICER. The probability sensitivity analysis highlighted that the joint incremental cost and effectiveness using QALY were less costly and more effective for 67% of the iteration values. The cost-effectiveness acceptability curve highlights that the 4-month regimen was dominant to both patients and the National TB Elimination Programme in India as compared to the 6-month regimen at different cost-effectiveness threshold values.
| S-EPMC9607110 | biostudies-literature
Project description:BackgroundIn May, 2016, WHO endorsed a 9 month regimen for multidrug-resistant tuberculosis that is cheaper and potentially more effective than the conventional, longer (20-24 month) therapy. We aimed to investigate the population-level implications of scaling up this new regimen.MethodsIn this population modelling analysis, we developed a dynamic transmission model to simulate the introduction of this short-course regimen as an instantaneous switch in 2016. We projected the corresponding percentage reduction in the incidence of multidrug-resistant tuberculosis by 2024 compared with continued use of longer therapy. In the primary analysis in a representative southeast Asian setting, we assumed that the short-course regimen would double treatment access (through savings in resources or capacity) and achieve long-term efficacy at levels seen in preliminary cohort studies. We then did extensive sensitivity analyses to explore a range of alternative scenarios.FindingsUnder the optimistic assumptions in the primary analysis, the incidence of multidrug-resistant tuberculosis in 2024 would be 3·3 (95% uncertainty range 2·2-5·6) per 100 000 population with the short-course regimen and 4·3 (2·9-7·6) per 100 000 population with continued use of longer therapy-ie, the short-course regimen could reduce incidence by 23% (10-38). Incidence would be reduced by 14% (4-28) if the new regimen affected only treatment effectiveness and by 11% (3-24) if it affected only treatment availability. Under more pessimistic assumptions, the short-course regimen would have minimal effect and even potential for harm-eg, when 30% of patients are ineligible for the new regimen because of second-line drug resistance, we projected a change in incidence of -2% (-20 to +28). The new regimen's effect was greater in settings with more ongoing transmission of multidrug-resistant tuberculosis, but results were otherwise similar across settings with different levels of tuberculosis incidence and prevalence of multidrug resistance.InterpretationThe short-course regimen has potential to substantially lessen the multidrug-resistant tuberculosis epidemic, but this effect depends on its long-term efficacy, its ability to expand treatment access, and the role of second-line drug resistance.FundingUS National Institutes of Health and Bill & Melinda Gates Foundation.
| S-EPMC5332590 | biostudies-literature
Project description:BackgroundEmergence of drug resistant varieties of tuberculosis is posing a major threat to global tuberculosis eradication programmes. Although several approaches have been explored to counter resistance, there has been limited success due to a lack of understanding of how resistance emerges in bacteria upon drug treatment. A systems level analysis of the proteins involved is essential to gain insights into the routes required for emergence of drug resistance.ResultsWe derive a genome-scale protein-protein interaction network for Mycobacterium tuberculosis H37Rv from the STRING database, with proteins as nodes and interactions as edges. A set of proteins involved in both intrinsic and extrinsic drug resistance mechanisms are identified from literature. We then compute shortest paths from different drug targets to the set of resistance proteins in the protein-protein interactome, to derive a sub-network relevant to study emergence of drug resistance. The shortest paths are then scored and ranked based on a new scheme that considers (a) drug-induced gene upregulation data, from microarray experiments reported in literature, for the individual nodes and (b) edge-hubness, a network parameter which signifies centrality of a given edge in the network. High-scoring paths identified from this analysis indicate most plausible pathways for the emergence of drug resistance. Different targets appear to have different propensities for four drug resistance mechanisms. A new concept of 'co-targets' has been proposed to counter drug resistance, co-targets being defined as protein(s) that need to be simultaneously inhibited along with the intended target(s), to check emergence of resistance to a given drug.ConclusionThe study leads to the identification of possible pathways for drug resistance, providing novel insights into the problem of resistance. Knowledge of important proteins in such pathways enables identification of appropriate 'co-targets', best examples being RecA, Rv0823c, Rv0892 and DnaE1, for drugs targeting the mycolic acid pathway. Insights obtained about the propensity of a drug to trigger resistance will be useful both for more careful identification of drug targets as well as to identify target-co-target pairs, both implementable in early stages of drug discovery itself. This approach is also inherently generic, likely to significantly impact drug discovery.
| S-EPMC2649132 | biostudies-literature
Project description:Tuberculosis (TB) kills more people than any other infectious disease. Challenges for developing better treatments include the complex pathology due to within-host immune dynamics, interpatient variability in disease severity and drug pharmacokinetics-pharmacodynamics (PK-PD), and the growing emergence of resistance. Model-informed drug development using quantitative and translational pharmacology has become increasingly recognized as a method capable of drug prioritization and regimen optimization to efficiently progress compounds through TB drug development phases. In this review, we examine translational models and tools, including plasma PK scaling, site-of-disease lesion PK, host-immune and bacteria interplay, combination PK-PD models of multidrug regimens, resistance formation, and integration of data across nonclinical and clinical phases.We propose a workflow that integrates these tools with computational platforms to identify drug combinations that have the potential to accelerate sterilization, reduce relapse rates, and limit the emergence of resistance.
| S-EPMC7790895 | biostudies-literature
Project description:Background: Adherence to tuberculosis (TB) drugs is one of the key aspects of global TB control, yet there is a lack of epidemiological evidence on the factors influencing adherence to TB drugs. Thus, this study aimed to explore the adherence and factors associated with adherence among TB patients in South Korea. Methods: We conducted a cohort study using a sampled national healthcare database from 2017 to 2018. Our study population included incident TB patients initiating quadruple or triple regimen who were available for follow-up for 180-days. Adherence was evaluated using the proportion of days covered (PDC): 1) adherent group: patients with PDC ≥80%; 2) non-adherent group: patients with PDC <80%. Kaplan-Meier analysis was conducted to calculate the median time-to-discontinuation in the study population. We calculated the adjusted odds ratios (aOR) with 95% confidence intervals (CI) to assess factors associated with adherence to TB drugs using logistic regression. Results: Of 987 patients, 558 (56.5%) were adherent and 429 (43.5%) were non-adherent, with the overall mean PDC of 68.87% (standard deviation, 33.37%). The median time-to-discontinuation was 113 days (interquartile range 96-136) in the study population. Patients initiating quadruple regimen were more likely to adhere in comparison to the triple regimen (aOR 4.14; 95% CI 2.78-6.17), while those aged ≥65 years (aOR 0.53; 95% CI 0.35-0.81), with a history of dementia (aOR 0.53; 95% CI 0.34-0.85), and with history of diabetes mellitus (aOR 0.70; 95% CI 0.52-0.96) were less likely to adhere to the drug. Conclusion: Approximately 45% of TB patients were non-adherent to the drug, which is a major concern for the treatment outcome. We call for intensified attention from the authorities and healthcare providers to reinforce patients' adherence to the prescribed TB drugs.
| S-EPMC8005597 | biostudies-literature
Project description:The rapid spread of multidrug-resistant strains has created a pressing need for new drug regimens to treat tuberculosis (TB), which kills 1.8 million people each year. Identifying new regimens has been challenging due to the slow growth of the pathogen Mycobacterium tuberculosis (MTB), coupled with the large number of possible drug combinations. Here we present a computational model (INDIGO-MTB) that identified synergistic regimens featuring existing and emerging anti-TB drugs after screening in silico more than 1 million potential drug combinations using MTB drug transcriptomic profiles. INDIGO-MTB further predicted the gene Rv1353c as a key transcriptional regulator of multiple drug interactions, and we confirmed experimentally that Rv1353c upregulation reduces the antagonism of the bedaquiline-streptomycin combination. A retrospective analysis of 57 clinical trials of TB regimens using INDIGO-MTB revealed that synergistic combinations were significantly more efficacious than antagonistic combinations (P value = 1 × 10-4) based on the percentage of patients with negative sputum cultures after 8 weeks of treatment. Our study establishes a framework for rapid assessment of TB drug combinations and is also applicable to other bacterial pathogens.IMPORTANCE Multidrug combination therapy is an important strategy for treating tuberculosis, the world's deadliest bacterial infection. Long treatment durations and growing rates of drug resistance have created an urgent need for new approaches to prioritize effective drug regimens. Hence, we developed a computational model called INDIGO-MTB that identifies synergistic drug regimens from an immense set of possible drug combinations using the pathogen response transcriptome elicited by individual drugs. Although the underlying input data for INDIGO-MTB was generated under in vitro broth culture conditions, the predictions from INDIGO-MTB correlated significantly with in vivo drug regimen efficacy from clinical trials. INDIGO-MTB also identified the transcription factor Rv1353c as a regulator of multiple drug interaction outcomes, which could be targeted for rationally enhancing drug synergy.
| S-EPMC6851285 | biostudies-literature
Project description:Pan-genome analysis is a fundamental tool in the study of bacterial genome evolution. Benchmarking the accuracy of pan-genome analysis methods is challenging, because it can be significantly influenced by both the methodology used to compare genomes, as well as differences in the accuracy and representativeness of the genomes analyzed. In this work, we curated a collection of 151 Mycobacterium tuberculosis (Mtb) isolates to evaluate sources of variability in pan-genome analysis. Mtb is characterized by its clonal evolution, absence of horizontal gene transfer, and limited accessory genome, making it an ideal test case for this study. Using a state-of-the-art graph-genome approach, we found that a majority of the structural variation observed in Mtb originates from rearrangement, deletion, and duplication of redundant nucleotide sequences. In contrast, we found that pan-genome analyses that focus on comparison of coding sequences (at the amino acid level) can yield surprisingly variable results, driven by differences in assembly quality and the softwares used. Upon closer inspection, we found that coding sequence annotation discrepancies were a major contributor to inflated Mtb accessory genome estimates. To address this, we developed panqc, a software that detects annotation discrepancies and collapses nucleotide redundancy in pan-genome estimates. We characterized the effect of the panqc adjustment on both pan-genome analysis of Mtb and E. coli genomes, and highlight how different levels of genomic diversity are prone to unique biases. Overall, this study illustrates the need for careful methodological selection and quality control to accurately map the evolutionary dynamics of a bacterial species.
| S-EPMC10996470 | biostudies-literature
Project description:BackgroundLateral flow urine lipoarabinomannan (LAM) tests could offer important new opportunities for the early detection of tuberculosis (TB). The currently licensed LAM test, Alere Determine TB LAM Ag ('LF-LAM'), performs best in the sickest people living with HIV (PLHIV). However, the technology continues to improve, with newer LAM tests, such as Fujifilm SILVAMP TB LAM ('SILVAMP-LAM') showing improved sensitivity, including amongst HIV-negative patients. It is important to anticipate the epidemiological impact that current and future LAM tests may have on TB incidence and mortality.Methods and findingsConcentrating on South Africa, we examined the impact that widening LAM test eligibility would have on TB incidence and mortality. We developed a mathematical model of TB transmission to project the impact of LAM tests, distinguishing 'current' tests (with sensitivity consistent with LF-LAM), from hypothetical 'future' tests (having sensitivity consistent with SILVAMP-LAM). We modelled the impact of both tests, assuming full adoption of the 2019 WHO guidelines for the use of these tests amongst those receiving HIV care. We also simulated the hypothetical deployment of future LAM tests for all people presenting to care with TB symptoms, not restricted to PLHIV. Our model projects that 2,700,000 (95% credible interval [CrI] 2,000,000-3,600,000) and 420,000 (95% CrI 350,000-520,000) cumulative TB incident cases and deaths, respectively, would occur between 2020 and 2035 if the status quo is maintained. Relative to this comparator, current and future LAM tests would respectively avert 54 (95% CrI 33-86) and 90 (95% CrI 55-145) TB deaths amongst inpatients between 2020 and 2035, i.e., reductions of 5% (95% CrI 4%-6%) and 9% (95% CrI 7%-11%) in inpatient TB mortality. This impact in absolute deaths averted doubles if testing is expanded to include outpatients, yet remains <1% of country-level TB deaths. Similar patterns apply to incidence results. However, deploying a future LAM test for all people presenting to care with TB symptoms would avert 470,000 (95% CrI 220,000-870,000) incident TB cases (18% reduction, 95% CrI 9%-29%) and 120,000 (95% CrI 69,000-210,000) deaths (30% reduction, 95% CrI 18%-44%) between 2020 and 2035. Notably, this increase in impact arises largely from diagnosis of TB amongst those with HIV who are not yet in HIV care, and who would thus be ineligible for a LAM test under current guidelines. Qualitatively similar results apply under an alternative comparator assuming expanded use of GeneXpert MTB/RIF ('Xpert') for TB diagnosis. Sensitivity analysis demonstrates qualitatively similar results in a setting like Kenya, which also has a generalised HIV epidemic, but a lower burden of HIV/TB coinfection. Amongst limitations of this analysis, we do not address the cost or cost-effectiveness of future tests. Our model neglects drug resistance and focuses on the country-level epidemic, thus ignoring subnational variations in HIV and TB burden.ConclusionsThese results suggest that LAM tests could have an important effect in averting TB deaths amongst PLHIV with advanced disease. However, achieving population-level impact on the TB epidemic, even in high-HIV-burden settings, will require future LAM tests to have sufficient performance to be deployed more broadly than in HIV care.
| S-EPMC7732057 | biostudies-literature
Project description:BackgroundRoutine services for tuberculosis (TB) are being disrupted by stringent lockdowns against the novel SARS-CoV-2 virus. We sought to estimate the potential long-term epidemiological impact of such disruptions on TB burden in high-burden countries, and how this negative impact could be mitigated.MethodsWe adapted mathematical models of TB transmission in three high-burden countries (India, Kenya and Ukraine) to incorporate lockdown-associated disruptions in the TB care cascade. The anticipated level of disruption reflected consensus from a rapid expert consultation. We modelled the impact of these disruptions on TB incidence and mortality over the next five years, and also considered potential interventions to curtail this impact.FindingsEven temporary disruptions can cause long-term increases in TB incidence and mortality. If lockdown-related disruptions cause a temporary 50% reduction in TB transmission, we estimated that a 3-month suspension of TB services, followed by 10 months to restore to normal, would cause, over the next 5 years, an additional 1⋅19 million TB cases (Crl 1⋅06-1⋅33) and 361,000 TB deaths (CrI 333-394 thousand) in India, 24,700 (16,100-44,700) TB cases and 12,500 deaths (8.8-17.8 thousand) in Kenya, and 4,350 (826-6,540) cases and 1,340 deaths (815-1,980) in Ukraine. The principal driver of these adverse impacts is the accumulation of undetected TB during a lockdown. We demonstrate how long term increases in TB burden could be averted in the short term through supplementary "catch-up" TB case detection and treatment, once restrictions are eased.InterpretationLockdown-related disruptions can cause long-lasting increases in TB burden, but these negative effects can be mitigated with rapid restoration of TB services, and targeted interventions that are implemented as soon as restrictions are lifted.FundingUSAID and Stop TB Partnership.
| S-EPMC7584493 | biostudies-literature