New Cancer Diagnoses Before and During the COVID-19 Pandemic
Notice bibliographique
Résumé
Importance: Disruptions to health care during the COVID-19 pandemic may have led to missed cancer diagnoses. It is critical to evaluate the association between the COVID-19 pandemic and cancer incidence to address public and patient anxiety, inform recovery efforts, and identify strategies to reduce the system's vulnerability to future disruptions. Objective: To examine the association between the COVID-19 pandemic and cancer incidence in Manitoba, Canada. Design, Setting, and Participants: A population-based cross-sectional study design was conducted using data from the Manitoba Cancer Registry and an interrupted time-series analysis. All individuals diagnosed with cancer in Manitoba, Canada, from January 1, 2015, until December 31, 2021, were included. Individuals diagnosed with breast, colon, rectal, or lung cancer were grouped by age as follows: younger than 50 years, 50 to 74 years, and 75 years and older. Exposures: COVID-19 pandemic. Main Outcomes and Measures: Age-standardized cancer incidence rates and the estimated cumulative difference between the number of cases in the absence of COVID-19 and observed (fitted) number of cancer cases. Results: A total of 48 378 individuals were included. The median (IQR) age at diagnosis was 68 (59-77) years and 23 972 participants (49.6%) were female. In April 2020, there was a 23% decrease in overall cancer incidence. Cancer incidence decreased by 46% for breast, 35% for colon, 47% for rectal, 50% for head and neck, 65% for melanoma, and 33% for endocrine cancer diagnoses and increased by 12% for hematological cancer diagnoses and 8% for diagnoses of cancers with an unknown primary site. Lung cancer incidence remained stable until December 2020 when it decreased by 11%. Brain and central nervous system and urinary cancer diagnoses decreased consistently over time from April 2020 to December 2021 by 26% and 12%, respectively. No association was observed with gynecologic (1% increase), other digestive (1% decrease), or pancreatic (7% increase) cancer incidence. As of December 2021, Manitoba had an estimated deficit of 692 (5.3%) cancers. The largest estimated deficits were for breast (273 cases, 14.1% deficit), colon (133 cases, 12.2% deficit), and lung cancers (132 cases, 7.6% deficit). Conclusions and Relevance: In this study, the COVID-19 pandemic was associated with an initial decrease in cancer diagnosis incidence followed by a recovery for most cancer sites. However, the cumulative deficit for some cancers with high fatality needs immediate attention.
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| 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 | 0,000 |
| 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 ».