A household-level score to predict the risk of tuberculosis among contacts of patients with tuberculosis: a derivation and external validation prospective cohort study
Bibliographic record
Abstract
Background The epidemiological impact and cost-effectiveness of social protection and biomedical interventions for tuberculosis-affected households might be improved by risk stratification. We therefore derived and externally validated a household-level risk score to predict tuberculosis among contacts of patients with tuberculosis. Methods In this prospective cohort study, we recruited tuberculosis-affected households from 15 desert shanty towns in Ventanilla and 17 urban communities in Callao, Lima, Peru. Tuberculosis-affected households included index patients with a new diagnosis of tuberculosis and their contacts who reported being in the same house as the index patient for more than 6 h per week in the 2 weeks preceding index patient diagnosis. Tuberculosis-affected households were not included if the index patient had no eligible contacts or lived alone. We followed contacts until 2018 and defined household tuberculosis, the primary outcome, as any contact having any form of tuberculosis within 3 years. We used logistic regression to identify characteristics of index patients, contacts, and households that were predictive of household tuberculosis, and used these to derive and externally validate a household-level score. Findings Between Dec 12, 2007, and Dec 31, 2015, 16 505 contacts from 3 301 households in Ventanilla were included in a derivation cohort. During the 3-year follow-up, tuberculosis occurred in contacts of index patients in 430 (13%, 95% CI 12–14) households. Index patient predictors were pulmonary tuberculosis and sputum smear grade, age, and the maximum number of hours any contact had spent with the index patient while they had any cough. Household predictors were drug use, schooling of the female head of a household, and lower food spending. Contact predictors were if any of the contacts were children, number of lower-weight (body-mass index [BMI] <20·0 kg/m 2 ) adult contacts, number of normal-weight (BMI 20·0–24·9 kg/m 2 ) adult contacts, and number of past or present household members who previously had tuberculosis. In this derivation cohort, the score c statistic was 0·77 and the risk of household tuberculosis in the highest scoring quintile was 31% (95% CI 25–38; 65 of 211) versus 2% (95% CI 0–4; four of 231) in the lowest scoring quintile. We externally validated the risk score in a cohort of 4248 contacts from 924 households in Callao recruited between April 23, 2014, and Dec 31, 2015. During follow-up, tuberculosis occurred in contacts of index patients in 120 (13%, 95% CI 11–15) households. The score c statistic in this cohort was 0·75 and the risk of household tuberculosis in the highest scoring quintile was 28% (95% CI 21–36; 43 of 154) versus 1% (95% CI 0–5; two of 148) in the lowest scoring quintile. The highest-scoring third of households captured around 70% of all tuberculosis among contacts. A simplified risk score including only five variables performed similarly, with only a small reduction in performance. Interpretation This externally validated score will enable comprehensive biosocial, household-level interventions to be targeted to tuberculosis-affected households that are most likely to benefit. Funding Wellcome Trust, Medical Research Council, Department of Health and Social Care, Department for International Development, Joint Global Health Trials consortium, Bill & Melinda Gates Foundation, Innovation for Health and Development.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".