L. Larsson, C. Calderwood, E. Marambire, Rishi K. Gupta, D. Banze, A. Mfinanga, Mishelle Mugava, E. Leroy-Terquem, Joseph Jacob, D. Yamada, Francisco Trinchan Fernandez, P. Lungu, Anita Mesic, C. Khosa, Tina Minja, Junior Mutsvangwa, M. Lauseker, K. Held, N. Heinrich, K. Kranzer
2026.3.1Lancet Global Health
tlooto Summary
Although most people remained static over time, the non-infectious state was more dynamic, with most people regressing over time, and the ICE-TB framework was applied to describe movement between states by use of contemporary, granular, longitudinal data.
Abstract
BACKGROUND The conceptualisation of tuberculosis has undergone a paradigm shift from binary states to a spectrum, resulting in the International Consensus for Early TB (ICE-TB) framework. This study aimed to use data from a prospective, observational cohort study and multistate modelling to address the lack of contemporary data to quantify movement between ICE-TB states.
METHODS ERASE-TB was a prospective, observational cohort study evaluating novel diagnostic tests for earlier detection of tuberculosis. Household contacts aged at least 10 years in Zimbabwe, Tanzania, and Mozambique were followed up 6-monthly for 12-24 months with comprehensive tuberculosis investigations at each visit. Those not diagnosed with prevalent tuberculosis, with state classification from at least two timepoints were included. ICE-TB states were defined by use of symptomatology, interferon gamma release assays, chest radiographs, and sputum microbiology. A Markov multistate model based on ICE-TB was applied with one initial state (Mycobacterium tuberculosis non-infection), two intermediate states (M tuberculosis infection and non-infectious disease [asymptomatic-symptomatic]), and one absorbing state (infectious disease [asymptomatic-symptomatic]). Transition probabilities were predicted.
FINDINGS 1789 (84·8%) of 2109 recruited household contacts were included. At enrolment, most (1000 [55·9%]) did not have M tuberculosis infection; 674 (37·7%) had M tuberculosis infection, and 115 (6·5%) had non-infectious disease. 34 people developed infectious disease (23 asymptomatic, 11 symptomatic). In the multistate model, the transition probabilities of progressing from M tuberculosis non-infection to M tuberculosis infection and M tuberculosis infection to non-infectious disease were 13% and 3% by month 12. For those in non-infectious disease, the probabilities of regression and progression by month 12 were 85% and 13%, respectively.
INTERPRETATION This study applied the ICE-TB framework to describe movement between states by use of contemporary, granular, longitudinal data. Although most people remained static over time, the non-infectious state was more dynamic, with most people regressing over time.
FUNDING European and Developing Countries Clinical Trials Partnership.
Citation format
LARSSON, L., et al. Characterising progression and regression patterns across the spectrum of tuberculosis: A multistate modelling approach. Lancet Global Health, 2026, 14 3(3): e347-e355.