Abstract 3708: Filling the void of Canadian T-cell lymphoma epidemiology: Data from the canadian institute for health information discharge abstract database
Notice bibliographique
Résumé
Abstract Introduction Epidemiological data for rare malignancies can be difficult to obtain; population-based data sets are often abridged to group disparate rare malignancies into larger more manageable clusters. These problems are acute in Canada, where such epidemiological data are often estimated from “second-hand” US data (e.g. Surveillance, Epidemiology and End-Results (SEER) data). Recently, the Canadian Institute of Health Information (CIHI) has set out to make epidemiological data more readily accessible, permitting University-affiliated researchers to access the anonymized and codified CIHI Discharge Abstract Database (DAD). Methods We undertook to estimate the incidence, demographics, and outcome data relating to the various subtypes of peripheral T-cell lymphomas (PTCLs) in Canada (excluding Quebec and British Columbia, for which data was not collected). The CIHI DAD consists of a two fiscal-year anonymized 10% random sample of all hospital discharge abstracts in Canada. The DAD is indexed by a unique anonymous patient identifiers and includes relative date metrics, by which all dates originally present on the abstract are standardized to a unique but confidential CIHI DAD reference date. From these data we were able to identify all hematolymphoid diagnoses, isolate the PTCLs, separate new from historical diagnoses, and identify patient age range, gender and disposition data. When the disposition data were combined with the relative date metrics, a gross estimate of T-cell lymphoma overall survival (relative to all other hematolymphoid diagnoses) was generated. Population normalization was achieved using inter-censal estimates obtained from Statistics Canada. Results PTCL incidence was estimated at 0.72 cases per 100,000 per annum (comparable to recently published SEER data). We also estimated a prevalence of 21 PTCLs per 100,000 healthcare encounters. Most cases of PTCL originated from males (63%) and the distribution of age ranges was skewed toward older adults (median age by number of cases = 60 years). The most frequent diagnosis was PTCL, NOS (46%). By the Cox-proportional hazards method, there was a statistically significant difference in survival between the T-cell lymphomas and non T-cell hematolymphoid malignancies (regression co-efficient for PTCL vs. non-PTCL diagnosis p = 0.003) in favor of the latter; not surprisingly, age was also predictive of overall survival, regardless of the subtype of malignancy (regression co-efficient p = 0.004). Conclusions To our knowledge, the above is the first attempt to estimate the epidemiology of PTCLs in Canada. In addition, we present a unique approach to obtaining high-quality (albeit geographically incomplete) Canadian epidemiological data via the CIHI DAD database; this dataset may serve as a valuable resource in the context of rare diseases whose epidemiological data may not be widely or publicly available. Citation Format: Etienne R. Mahe, Princess Margaret Cancer Centre Advanced MolecularDiagnostics Laboratory, Trevor Pugh, Tracy Stockley, Suzanne Kamel-Reid. Filling the void of Canadian T-cell lymphoma epidemiology: Data from the canadian institute for health information discharge abstract database. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3708. doi:10.1158/1538-7445.AM2015-3708
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 | 0,005 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 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 ».