Methodological approaches to population based research of screening procedures in the presence of selection bias and exposure measurement error: colonoscopy and colorectal cancer outcomes in Ontario
Notice bibliographique
Résumé
BACKGROUND: The study describes the methodological challenges encountered in an observational study estimating the effectiveness of colonoscopy in reducing colorectal cancer (CRC) incidence and mortality. METHODS: Using Ontario provincial administrative data, we conducted a population-based retrospective cohort study to assess CRC incidence and mortality in a group of average-risk subjects aged 50-74 years who underwent colonoscopy between 1996-2000. We created two study cohorts; unselected and restricted. The unselected cohort consists of subjects aged 50-74 years who were eligible for CRC screening and who had the same primary care physician (PCP) during the period 1996-2000 with at least two years of follow-up. PCPs are general practioners/family physicians who are the main source of health care for Ontarians. The restricted cohort was a nested sample of unselected cohort who were alive and free of CRC as on January 1, 2001 and whose PCPs had at least 10 screen-eligible patients with a colonoscopy referral rate of more than 3%. We compared the outcomes in the two study cohorts; unselected vs. restricted. We then estimated the absolute risk reduction associated with colonoscopy in preventing CRC incidence and mortality in the restricted cohort, using traditional regression analysis, propensity score analysis and instrumental variable analysis. RESULTS: The unselected cohort (N = 1,341,612) showed that colonoscopy was associated with an increase in CRC incidence (1.61% vs. 4.61%) and mortality (0.36% vs. 1.16%), whereas the restricted cohort (N = 1,089,998) showed that colonoscopy was associated with a reduction in CRC incidence (1.36% vs. 0.84%) and mortality (0.23% vs. 0.15%). For CRC incidence, the absolute risk reduction (ARR) associated with colonoscopy use was 0.52% in an unadjusted model, 0.53% in a multivariate logistic regression model, 0.54% in a propensity score-weighted outcome model, 0.56% in propensity score-matched model, and 0.60% using instrumental variable analysis. For CRC mortality, the ARR was 0.08% in the unadjusted model, multivariate logistic regression model and for a propensity score- weighted outcome model, 0.10% using propensity score matched model and 0.17% using the IVA model. CONCLUSIONS: Colonoscopy use reduced the risk of CRC incidence and mortality in the restricted cohort. The study highlights the importance of appropriate selection of study subjects and use of analytic methods for the evaluation of screening methods using observational data.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,062 | 0,112 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».