Associations between county-level surgeon density and colorectal cancer (CRC) mortality.
Notice bibliographique
Résumé
511 Background: Strong associations between surgeon procedure volumes and patient outcomes have been observed for many types of cancers. Whether surgeon density in a population has a similar impact on cancer outcomes is unclear. Our aims were to 1) explore the effect of US county-level surgeon density on CRC mortality and on annual changes in death, 2) compare the relative importance of colorectal surgeon (CS) versus general surgeon (GS) density on these CRC outcomes, and 3) identify other county characteristics associated with reduced mortality. Methods: Using county-level data from the Area Resource File, US Census and National Cancer Institute, we developed multivariate regression models to determine the effect of a) CS and b) GS on overall CRC mortality and changes in death between 2002 and 2006, while controlling for CRC incidence, county demographics and other socioeconomic factors. Results: A total of 1,187 US counties were included: mean CRC incidence and death rates were 64.9 and 19.9, respectively; 57% were metropolitan and 43% were rural counties; mean CS and GS densities were 1.23 and 1.94 per 100,000 people, respectively. When compared to counties with no CS and no GS, those with at least of one of these surgeons had a statistically significant decrease in CRC-specific mortality (beta coefficients were -0.035 and -0.051 for CS and GS, respectively; p=0.014). Increasing the county-level density of surgeons improved outcomes, but increasing it beyond 8 CS or 12 GS per 100,000 people did not continue to result in significant reductions in CRC mortality. Similar associations between surgeon density and annual changes in CRC-related death were observed. Counties with a high proportion of Medicare enrollees also showed increased CRC mortality. Conclusions: The presence of CS and GS at the county level is each associated with lower mortality from CRC. However, there appears to be a ceiling effect at which point further increases in their density do not produce continued improvements in CRC outcomes. A balanced strategy of allocating healthcare resources and distributing the surgical workforce evenly across all counties will likely offer the most substantial population-based improvements in CRC mortality. No significant financial relationships to disclose.
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 | 0,003 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| 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; un appel candidat d’une seule tête enseignante, 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 ».