Predicting risk of tuberculosis disease in people migrating to a low-TB incidence country: development and validation of a multivariable dynamic risk prediction model using health administrative data

Joseph H Puyat; Sarah K Brode; Hennady Shulha; Kamily Romanowski; Dick Menzies; Andrea Benedetti; Raquel Duchen; Anjie Huang; Jiming Fang; Liane Macdonald; Ted K Marras; Elizabeth Rea; Jeffrey C Kwong; Michael A Campitelli; Jonathon R Campbell; Kevin Schwartzman; Victoria J Cook; James C Johnston

doi:10.1093/cid/ciae561

Predicting risk of tuberculosis disease in people migrating to a low-TB incidence country: development and validation of a multivariable dynamic risk prediction model using health administrative data

Clin Infect Dis. 2024 Nov 20:ciae561. doi: 10.1093/cid/ciae561. Online ahead of print.

Authors

Joseph H Puyat^{1

2}, Sarah K Brode^{3

4

5}, Hennady Shulha^{6

7}, Kamily Romanowski^{8

9

10}, Dick Menzies^{9

10

11}, Andrea Benedetti^{9

10

11}, Raquel Duchen⁵, Anjie Huang⁵, Jiming Fang⁵, Liane Macdonald^{12

13}, Ted K Marras^{3

4}, Elizabeth Rea^{13

14}, Jeffrey C Kwong^{3

5

12

13

15}, Michael A Campitelli⁵, Jonathon R Campbell^{9

10

11}, Kevin Schwartzman^{9

10

11}, Victoria J Cook^{8

15}, James C Johnston^{2

8

11

16}

Affiliations

¹ Centre for Advancing Health Outcomes, Providence Health Care, Vancouver, BC, Canada.
² School of Population and Public Health, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada.
³ University Health Network, Toronto, ON, Canada.
⁴ Division of Respirology, Department of Medicine, University of Toronto, ON, Canada.
⁵ ICES, Toronto, ON, Canada.
⁶ Vaccine Evaluation Centre, BC Children's Hospital Research Institute, Vancouver, BC, Canada.
⁷ Department of Pediatrics, University of British Columbia, Vancouver, BC, Canada.
⁸ Provincial TB Services, British Columbia Centre for Disease Control, Vancouver, BC, Canada.
⁹ Respiratory Epidemiology and Clinical Research Unit, Research Institute of the McGill University Health Centre, Montreal, QC, Canada.
¹⁰ Department of Global and Public Health, McGill University, Montreal, QC, Canada.
¹¹ McGill International TB Centre, Montreal, QC, Canada.
¹² Public Health Ontario, Toronto, ON, Canada.
¹³ Dalla Lana School of Public Health, University of Toronto, ON, Canada.
¹⁴ Toronto Public Health, Toronto, ON, Canada.
¹⁵ Department of Family and Community Medicine, University of Toronto, Toronto, ON, Canada.
¹⁶ Division of Respiratory Medicine, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada.

PMID: 39561254
DOI: 10.1093/cid/ciae561

Abstract

Background: Tuberculosis (TB) incidence remains disproportionately high in people migrating to Canada and other low TB incidence countries, but systematic TB screening and prevention in migrants is often cost-prohibitive for TB programs. We aimed to develop and validate a TB risk prediction model to inform TB screening decisions in foreign-born permanent residents of Canada.

Methods: We developed and validated a proportional baselines landmark supermodel for TB risk prediction using health administrative data from British Columbia and Ontario, two distinct provincial healthcare systems in Canada. Demographic (age, sex, refugee status, year of entry, TB incidence in country of origin), TB exposure, and medical (HIV, kidney disease, diabetes, solid organ transplantation, cancer) covariates were used to derive and test models in British Columbia; one model was chosen for external validation in the Ontario cohort. The model's ability to predict 2- and 5-year TB risk in the Ontario cohort was assessed using discrimination and calibration statistics.

Results: The study included 715,423 individuals (including 1,407 people with TB disease) in the British Columbia derivation cohort, and 958,131 individuals (including 1,361 people with TB disease) in the Ontario validation cohort. The 2- and 5-year concordance statistic in the validation cohort was 0.77 (95%CI: 0.75-0.78) and 0.77 (95%CI: 0.76-0.78), respectively. Calibration-in-the-large values were 0.14 (95% CI: 0.08-0.21) and -0.05 (95% CI: -0.12-0.02) in 2- and 5-year prediction windows.

Conclusions: This prediction model, available online at https://tb-migrate.com, may improve TB risk stratification in people migrating to low incidence countries and may help inform TB screening policy and guidelines.

Keywords: epidemiology; prognostic model; public health; survival analysis; tuberculosis disease.

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