Prioritising attributes for tuberculosis preventive treatment regimens: a modelling analysis

Background Recent years have seen important improvements in available preventive treatment regimens for tuberculosis (TB), and research is ongoing to develop these further. To assist with the formulation of target product profiles for future regimens, we examined which regimen properties would be most influential in the epidemiological impact of preventive treatment. Methods Following expert consultation, we identified 5 regimen properties relevant to the incidence-reducing impact of a future preventive treatment regimen: regimen duration, efficacy, ease-of-adherence (treatment completion rates in programmatic conditions), forgiveness to non-completion and the barrier to developing rifampicin resistance during treatment. For each regimen property, we elicited expert input for minimally acceptable and optimal (ideal-but-feasible) performance scenarios for future regimens. Using mathematical modelling, we then examined how each regimen property would influence the TB incidence reduction arising from full uptake of future regimens according to current WHO guidelines, in four countries: South Africa, Kenya, India and Brazil. Results Of all regimen properties, efficacy is the single most important predictor of epidemiological impact, while ease-of-adherence plays an important secondary role. These results are qualitatively consistent across country settings; sensitivity analyses show that these results are also qualitatively robust to a range of model assumptions, including the mechanism of action of future preventive regimens. Conclusions As preventive treatment regimens against TB continue to improve, understanding the key drivers of epidemiological impact can assist in guiding further development. By meeting these key targets, future preventive treatment regimens could play a critical role in global efforts to end TB..

Medienart:

E-Artikel

Erscheinungsjahr:

2022

Erschienen:

2022

Enthalten in:

Zur Gesamtaufnahme - volume:20

Enthalten in:

BMC medicine - 20(2022), 1 vom: 18. Mai

Sprache:

Englisch

Beteiligte Personen:

Vesga, Juan F. [VerfasserIn]
Lienhardt, Christian [VerfasserIn]
Nsengiyumva, Placide [VerfasserIn]
Campbell, Jonathon R. [VerfasserIn]
Oxlade, Olivia [VerfasserIn]
den Boon, Saskia [VerfasserIn]
Falzon, Dennis [VerfasserIn]
Schwartzman, Kevin [VerfasserIn]
Churchyard, Gavin [VerfasserIn]
Arinaminpathy, Nimalan [VerfasserIn]

Links:

Volltext [kostenfrei]

Themen:

Mathematical modelling
Preventive therapy
Tuberculosis

Anmerkungen:

© The Author(s) 2022

doi:

10.1186/s12916-022-02378-1

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

SPR050718371