| Literature DB >> 31500572 |
Emily A Kendall1, Shelly Malhotra2,3, Sarah Cook-Scalise2, Claudia M Denkinger4,5, David W Dowdy6.
Abstract
BACKGROUND: Regimens that could treat both rifampin-resistant (RR) and rifampin-susceptible tuberculosis (TB) while shortening the treatment duration have reached late-stage clinical trials. Decisions about whether and how to implement such regimens will require an understanding of their likely clinical impact and how this impact depends on local epidemiology and implementation strategy.Entities:
Keywords: Clinical outcomes; Drug resistance; Modeling; Novel regimens; Regimen selection; Treatment; Tuberculosis
Mesh:
Substances:
Year: 2019 PMID: 31500572 PMCID: PMC6734288 DOI: 10.1186/s12879-019-4429-x
Source DB: PubMed Journal: BMC Infect Dis ISSN: 1471-2334 Impact factor: 3.090
Fig. 1Model diagram. The full pathway of treatment and beyond is shown here only for RR-TB receiving the novel regimen, but other pathways proceed similarly. Transition probabilities depend on characteristics of the individual patient and on the BPaMZ implementation scenario modeled. Probability of cure depends on the drugs in the regimen prescribed, the initial drug resistance, and the duration of treatment completed. Acquired resistance, by definition, means the patient will not be cured; the probability of acquired resistance is accounted for in the overall probability of failure or relapse for each possible combination of patient and treatment course. Failure or relapse is split into failure (which immediately returns to active TB) and relapse (which becomes active after a short delay). Loss to follow up is modeled as a constant hazard during treatment, with cumulative risk thus depending on the treatment duration. Death, not shown, also may occur from any state, with mortality being increased among patients with HIV and/or TB
Select model parameters
| Parameter | Estimate, South Africa | Range in sensitivity analysis | References and notes |
|---|---|---|---|
| Fraction of TB cases previously treated for TB | 10% | 8–13% | [ |
| Fraction of TB cases with HIV | 60% | 54–66% | [ |
| Baseline prevalence of RR, new cases | 3.4% | 2.5–4.3% | [ |
| Baseline prevalence of RR, cases previously treated for TB | 7.1% | 4.8–9.5% | [ |
| Prevalence of pyrazinamide resistance, if RR | 44% | 33–55% | [ |
| Prevalence of pyrazinamide resistance, if RS | 1.3% | 0.8–2.0% | [ |
| Prevalence of any moxifloxacin resistance, if RR | 9.5% | 4–18% | [ |
| Prevalence of high-level moxifloxacin resistance, if RR | 5.9% | 2–12% | [ |
| Prevalence of any moxifloxacin resistance, if RS | 0.4% | 0–0.9% | [ |
| Mean time from TB onset to TB diagnosis | 9 months | 6–15 | Incidence:prevalence ratio estimates [ |
| Pretreatment loss to follow up | 10% | 5–20% | [ |
| Monthly loss to follow up during treatment | 1% | 0.8–2% | [ |
| Monthly TB mortality, untreated active TB | 2.1% | 2.3–2.8% | [ |
| Present-day Xpert MTB/RIF coverage, new patients | 70% | 60–80% | [ |
| Present-day Xpert MTB/RIF coverage, patients previously treated for TB | 75% | 60–90% | [ |
| Relapse after six months HRZE or four months of BPaMZ (assuming drug susceptibility)a | 6.3% | 2–12% | [ |
| Odds ratio of cure from moxifloxacin-containing regimen, low-level versus high-level moxifloxacin resistance | 1.7 | 1.3–2.2 | [ |
| Risk of acquired RR after HRZE b | 0.005 | 0.002–0.15 | [ |
| Risks of acquired B, Pa, or M after BPaMZ b | 0.002 | 0–0.01 | Assumed |
| Risk of acquired moxifloxacin resistance after conventional multidrug-resistant TB regimen | 0.04 | 0.005–0.08 | [ |
TB = tuberculosis, RS = rifampin susceptible, RR = rifampin resistant, Z = pyrazinamide, M = moxifloxacin. B = bedaquiline, Pa = pretomanid, HRZE = standard first-line regimen of isoniazid, rifampin, pyrazinamide, ethambutol.
a The probability of successful treatment is reduced when resistance is present to one or more drugs in the regimen prescribed, or when duration is changed (shortened due to loss to follow up, or extended to six months for patients with RR-TB receiving BPaMZ), as shown in part b of the Table
b Parameter value shown is the risk if initially susceptible to R and Z (HRZE), or to B, Pa, and M (BPaMZ). Risk of acquired resistance to remaining drugs is increased for M. tuberculosis strains already resistant to one or more of these drugs in the regimen used; see Additional File 1 for details
Selected probabilities of durable cure, by active drugs and duration of treatmenta
| Active drugs in prescribed regimen | 4 months | 6 months | 18 months |
|---|---|---|---|
| HR(ZE) b | 86.0%c | 94.4% | Not applicable |
| R(ZE) b | 58.0%c | 83.3% | Not applicable |
| BPaMZ | 93.7% | 97.6% | Not applicable |
| BPamZ d | 91.6% | 96.8% | Not applicable |
| BPaM | 89.5% | 95.9% | Not applicable |
| BPaZ | 86.5% | 94.6% | Not applicable |
| BPam d | 70.2% | 89.4% | Not applicable |
| Conventional multidrug-resistant TB regimen with full fluoroquinolone activity [ | 20.0%c | 40.2%c | 91.3% |
| Conventional multidrug-resistant TB regimen in presence of fluoroquinolone resistance [ | 20.0%c | 20.0%c | 79.1% |
a Modeled as a function of two-month culture conversion and time on treatment, for the set of drugs in the prescribed regimen to which the patient’s TB strain is susceptible. Details in Additional file 1
b Outcomes of HRZE are affected explicitly by isoniazid and/or rifampin resistance, but because data for the HRZE regimen come from studies that did not test for pyrazinamide or ethambutol resistance, outcomes are weighted averages reflecting the distribution of pyrazinamide and ethambutol resistance within each patient subpopulation
c Durations of 4 months for HRZE, and of 4 or 6 month for conventional MDR regimens, are shown for comparison but are not prescribed and are used within the model only if patients are lost to follow up at these time points
d “m” represents a moxifloxacin-containing regimen used to treat a TB strain that has low-level moxifloxacin resistance
Fig. 2Simulated impact of BPaMZ regimen on status of South African TB cohort and RR sub-cohort over time. Scenarios modeled are: (a) standard of care baseline (including conventional DR-TB regimens for those found to have RR-TB, and HRZE for all others; top row), (b) introduction of the novel regimen for patients known to have RR-TB (middle row), and (c) introduction of the novel regimen for all patients (with duration dependent on the DST result if rifampin DST is performed; bottom row). The percentages along the right edge of each panel show the fraction of the cohort in each state 30 months after onset of TB (with fractions < 2% not labeled)
Fig. 3Impact of BPaMZ regimen use and barrier to resistance on potentially infectious person-time. Total time with drug-resistant TB (left column) includes the time prior to the first treatment within the model, while the right column shows time with active drug-resistant TB after an individual has begun treatment at least once within the model – that is, time and potential transmission that better treatment might have prevented. For comparison, in the Current Care scenario, total time with TB (with or without drug resistance) was 8900 person-months overall and 1400 person-months after a treatment attempt, per 100 TB cases. Acquired resistance risk parameters increase risks of moxifloxacin, bedaquiline, and pretomanid resistance during BPaMZ, and also of isoniazid resistance during HRZE
Fig. 4BPaMZ treatment outcomes in different scenarios of local RR prevalence and rifampin DST (Xpert) coverage. “High Xpert” coverage reaches 70% of new and 75% of previously-treated patients, and “Low Xpert” coverage reaches 10% of new and 37.5% of retreatment patients. “Low RIF-R” prevalence is RR in 3.4% of new and 7.1% of previously-treated TB (3.8% overall), and “High RIF-R” prevalence increases the odds of RR-TB three-fold, to RR prevalence of 9.6% of new and 18.7% of retreatment patients (10.5% overall). The lower left panel thus represents the base model of present-day South Africa. Error bars show the standard deviation over repeated simulations of each scenario with cohorts of 100,000 patients in each setting