Puyat Joseph H, Brode Sarah K, Shulha Hennady, Romanowski Kamila, Menzies Dick, Benedetti Andrea, Duchen Raquel, Huang Anjie, Fang Jiming, Macdonald Liane, Marras Ted K, Rea Elizabeth, Kwong Jeffrey C, Campitelli Michael A, Campbell Jonathon R, Schwartzman Kevin, Cook Victoria J, Johnston James C
Centre for Advancing Health Outcomes, Providence Health Care, Vancouver, British Columbia, Canada.
School of Population and Public Health, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.
Clin Infect Dis. 2025 Mar 17;80(3):644-652. doi: 10.1093/cid/ciae561.
Tuberculosis (TB) incidence remains disproportionately high in people who migrate to Canada and other countries with low TB incidence, but systematic TB screening and prevention in migrants are 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.
We developed and validated a proportional baselines landmark supermodel for TB risk prediction using health administrative data from British Columbia and Ontario, 2 distinct provincial healthcare systems in Canada. Demographic (age, sex, refugee status, year of entry, TB incidence in country of origin), TB exposure, and medical (human immunodeficiency virus, kidney disease, diabetes, solid organ transplantation, cancer) covariates were used to derive and test models in British Columbia; 1 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.
The study included 715 423 individuals (including 1407 people with TB disease) in the British Columbia derivation cohort and 958 131 individuals (including 1361 people with TB disease) in the Ontario validation cohort. The 2- and 5-year concordance statistic in the validation cohort was 0.77 (95% confidence interval [CI]: .75 to .78) and 0.77 (95% CI: .76 to .78), respectively. Calibration-in-the-large values were 0.14 (95% CI: .08 to .21) and -0.05 (95% CI: -.12 to .02) in 2- and 5-year prediction windows.
This prediction model, available online at https://tb-migrate.com, may improve TB risk stratification in people who migrate to low-incidence countries and may help inform TB screening policy and guidelines.
在移民到加拿大及其他结核病发病率较低国家的人群中,结核病发病率仍然高得不成比例,但对移民进行系统性结核病筛查和预防对结核病防治项目来说成本往往过高。我们旨在开发并验证一种结核病风险预测模型,为加拿大外国出生的永久居民的结核病筛查决策提供依据。
我们利用来自加拿大两个不同省级医疗系统(不列颠哥伦比亚省和安大略省)的卫生行政数据,开发并验证了一种用于结核病风险预测的比例基线标志性超级模型。人口统计学因素(年龄、性别、难民身份、入境年份、原籍国结核病发病率)、结核病暴露情况以及医学因素(人类免疫缺陷病毒、肾病、糖尿病、实体器官移植、癌症)协变量被用于在不列颠哥伦比亚省推导和测试模型;选择了一个模型在安大略队列中进行外部验证。使用区分度和校准统计数据评估该模型预测安大略队列中2年和5年结核病风险的能力。
研究纳入了不列颠哥伦比亚省推导队列中的715423人(包括1407例结核病患者)和安大略省验证队列中的958131人(包括1361例结核病患者)。验证队列中2年和5年的一致性统计量分别为0.77(95%置信区间[CI]:0.75至0.78)和0.77(CI:0.76至0.78)。在2年和5年预测窗口中,整体校准值分别为0.14(95%CI:0.08至0.21)和-0.05(95%CI:-0.12至0.02)。
这个可在https://tb-migrate.com在线获取的预测模型,可能会改善移民到低发病率国家人群的结核病风险分层,并可能有助于为结核病筛查政策和指南提供依据。