Evaluating the influence of vaccine archetypes and epidemiological conditions on clinical trial metrics for tuberculosis vaccine candidates

BACKGROUND: Conducting tuberculosis vaccine trials in high-transmission settings offers potential gains in efficiency, yet the impact of repeated exposure in the presence of incomplete protection on measured vaccine efficacy is uncertain. We evaluated the effect of vaccine characteristics and epidemiological context on estimates of vaccine efficacy and requisite sample size for tuberculosis vaccine trials. METHODS: We simulated clinical trials of hypothetical tuberculosis vaccines using a stochastic compartmental model of tuberculosis natural history. We considered vaccines that confer "leaky" (50% per-exposure reduction) versus "all-or-none" protection against infection and/or disease that were evaluated in QuantiFERON Gold Plus (QFT) positive, negative or mixed populations with 2% (medium burden; incidence 400 per 100,000), 5% (high burden; 800 per 100,000) or 50% (very high burden; 4500 per 100,000) annual risk of infection (ARI), including protection against infection alone. We compared estimates of vaccine efficacy and statistical power to detect differences according to sample size for each vaccine archetype and epidemiologic setting. FINDINGS: Simulated trials of vaccines protecting against disease, alone or with protection against infection, gave comparable estimates of efficacy across epidemiological settings, whether all-or-none or leaky. The largest reduction was for a leaky vaccine protecting against both infection and disease in QFT negative participants, whose efficacy fell from 75% at medium ARI to 67% at very high ARI (relative reduction 11%). A vaccine acting only by preventing infection fell further, from 50% to 36% (28%). Trials at very high ARI could nonetheless achieve 90% power with 80-96% fewer participants than at medium ARI. INTERPRETATION: While vaccines conferring leaky protection against infection and disease tested in settings with very high ARI could modestly underestimate efficacy, trials could be adequately powered with a fraction of the sample size in such settings. Further, trials could enroll a mixture of QFT negative and positive individuals, increasing generalizability.

Authors

Institutions

Publication Details

Journal
Vaccine
Published
2026-09-01
DOI
https://doi.org/10.1016/j.vaccine.2026.129097
Primary Topic
Tuberculosis Research and Epidemiology
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evaluating the influence of vaccine archetypes and epidemiological conditions on clinical trial metrics for tuberculosis vaccine candidates

Richard G. White, Frank Cobelens, Jason R. Andrews, Sabine Hermans et al.
Vaccine
Tuberculosis Research and Epidemiology
article

Evaluating the influence of vaccine archetypes and epidemiological conditions on clinical trial metrics for tuberculosis vaccine candidates

Richard G. White, Frank Cobelens, Jason R. Andrews, Sabine Hermans, Alberto L. García-Basteiro, Julio Croda
article en

Abstract

BACKGROUND: Conducting tuberculosis vaccine trials in high-transmission settings offers potential gains in efficiency, yet the impact of repeated exposure in the presence of incomplete protection on measured vaccine efficacy is uncertain. We evaluated the effect of vaccine characteristics and epidemiological context on estimates of vaccine efficacy and requisite sample size for tuberculosis vaccine trials. METHODS: We simulated clinical trials of hypothetical tuberculosis vaccines using a stochastic compartmental model of tuberculosis natural history. We considered vaccines that confer "leaky" (50% per-exposure reduction) versus "all-or-none" protection against infection and/or disease that were evaluated in QuantiFERON Gold Plus (QFT) positive, negative or mixed populations with 2% (medium burden; incidence 400 per 100,000), 5% (high burden; 800 per 100,000) or 50% (very high burden; 4500 per 100,000) annual risk of infection (ARI), including protection against infection alone. We compared estimates of vaccine efficacy and statistical power to detect differences according to sample size for each vaccine archetype and epidemiologic setting. FINDINGS: Simulated trials of vaccines protecting against disease, alone or with protection against infection, gave comparable estimates of efficacy across epidemiological settings, whether all-or-none or leaky. The largest reduction was for a leaky vaccine protecting against both infection and disease in QFT negative participants, whose efficacy fell from 75% at medium ARI to 67% at very high ARI (relative reduction 11%). A vaccine acting only by preventing infection fell further, from 50% to 36% (28%). Trials at very high ARI could nonetheless achieve 90% power with 80-96% fewer participants than at medium ARI. INTERPRETATION: While vaccines conferring leaky protection against infection and disease tested in settings with very high ARI could modestly underestimate efficacy, trials could be adequately powered with a fraction of the sample size in such settings. Further, trials could enroll a mixture of QFT negative and positive individuals, increasing generalizability.

VaccineVol. 91
Universidade Federal de Mato Grosso do Sul (BR), London School of Hygiene & Tropical Medicine (GB), Centro de Investigación Biomédica en Red (ES), Amsterdam Institute for Global Health and Development (NL)
Bill and Melinda Gates Foundation, King Baudouin Foundation United States, World Health Organization, Fundació la Marató de TV3, Wellcome Trust, Open Philanthropy Project, Economic and Social Research Council, National Institute of Allergy and Infectious Diseases, European and Developing Countries Clinical Trials Partnership
Good health and well-being
Openalex Percentile: Top 11%
Tuberculosis Research and Epidemiology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.