Temporal Trends in Thyroid Cancer Incidence in California—Letter
Notice bibliographique
Résumé
Horn-Ross and colleagues (1) recently reported on increasing thyroid cancer (TC) incidence in California neighborhoods, which was not explained by immigration in various racial groups. TC incidence is also increasing in Ontario, with significant regional variability (2). National Canadian data have suggested increased TC incidence in regions with the highest prevalence of foreign-born individuals (3). We explored whether the prevalence of immigrants and racial minorities could explain Ontario regional TC incidence, using publicly available data in women.The female, age-adjusted TC incidence rate and number of cases were obtained for each of the 14 Ontario Local Health Integration Network (LHIN) regions from 2007 Cancer Care Ontario data (4). Immigrant and racial data from 2006 were retrieved from a government-sponsored report (5). The relationship between explanatory variables and TC incidence was assessed through separate Poisson regression models, with female TC case count being the response variable and the expected number of cases for each LHIN used as an “offset” term. An overdispersed (or quasi-Poisson) model was used, allowing for the possibility that variation in the case counts is more substantial than predicted by sampling error. To account for non-normally distributed data, risk estimates were described as relative rates for interquartile ranges (IQR, the difference between the 25th and 75th percentiles), and their respective 95% confidence intervals (CI) (based on SEs, with an implicit assumption of spatial independence of intervals). R software (R version 3.0.2, R Foundation for Statistical Computing) was used.The total number of TC cases reported in Ontario women in 2007 was 1,639 (mean incidence 23.5/100,000; ref. 4). The highest TC incidence was in and around Toronto (i.e., Central, Toronto Central, Mississauga Halton, and Central East LHINs), with many of these regions reporting some of the highest prevalence rates for new immigrants or visible minorities. The relative rate for IQR of age-adjusted TC risk was 1.90 (95% CI, 1.73–2.10), according to the regional percentage of immigrants. The relative rate for IQR for TC risk, according to the percentage prevalence of visible minorities, was 1.75 (95% CI, 1.59–1.92).Our preliminary observations on the relationship between Ontario female TC incidence and immigrant/visible minority status need to be confirmed. Differences in study design (including lack of individual-level data on trends over time in our analysis), immigration patterns, and healthcare system funding, may, explain why our findings contrast with that of Horn-Ross and colleagues (1).No potential conflicts of interest were disclosed.A.M. Sawka holds a Chair in Health Services Research from Cancer Care Ontario (funded by the Ontario Ministry of Health and Long-term Care). P.E. Brown is funded by the Natural Sciences and Engineering Research Council of Canada.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».