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Enregistrement W3033219417 · doi:10.1182/blood.v130.suppl_1.1282.1282

Widening Survival Disparities between AYA with ALL Treated in Pediatric Vs. Adult Centers: A Population-Based Study Using the IMPACT Cohort

2017· article· en· W3033219417 sur OpenAlexaffabout
Sumit Gupta, Jason D. Pole, Cindy Lau, Chenthila Nagamuthu, Rinku Sutradhar, Nancy N. Baxter, Paul C. Nathan

Notice bibliographique

RevueQueensland's institutional digital repository (The University of Queensland) · 2017
Typearticle
Langueen
DomaineMedicine
ThématiqueChildhood Cancer Survivors' Quality of Life
Établissements canadiensSt. Michael's HospitalUniversity of TorontoInstitute for Clinical Evaluative SciencesPediatric Oncology GroupHospital for Sick Children
Organismes subventionnairesnon disponible
Mots-clésMedicineCohortHazard ratioProportional hazards modelPopulationYoung adultPediatricsPediatric cancerCohort studyCancerGerontologyDemographyInternal medicineConfidence intervalEnvironmental health

Résumé

récupéré en direct d'OpenAlex

Abstract Background: Survival outcomes in adolescents and young adults (AYA) with cancer have not improved at the same rates as those in children. Studies in AYA with acute lymphoblastic leukemia (ALL) have shown that pediatric-based treatment protocols result in better survival compared to adult protocols. Consequently, many adult centers have begun to treat AYA ALL with pediatric protocols. Whether this change in practice has diminished survival disparities between pediatric and adult centers has not been established. Methods: The IMPACT Cohort comprises all Ontario, Canada AYA 15-21 years old diagnosed with one of six common cancers (including ALL) between 1992 and 2011. Detailed demographic, disease, treatment, and outcome data were collected through chart abstraction and validated by content experts. Locus of cancer care (pediatric vs. adult center) was determined based on where the majority of chemotherapy was delivered in the first three months after diagnosis. Linkage to population-based health administrative data identified cancer events (relapse, death) that were not detected through chart abstraction. Various predictors of locus of care were examined, including age (continuous variable), gender, time period (1992-1998 vs. 1999-2005 vs. 2006-2011), rural residence, and socioeconomic status using logistic regression. The impact of the above predictors and of locus of care on event-free (EFS) and overall survival (OS) was determined using Cox proportional hazard models. Events included disease progression, relapse, death, and second malignancies. Results: The cohort included 271 patients with ALL, 152 (56%) of whom received therapy at an adult center. In multivariable analysis, older patients [odds ratio (OR) 11.9 per year; 95th confidence interval (CI) 6.1-25.0] and those in the earliest time period (1992-1998 vs. 2006-2011, OR 3.5; 95CI 1.1-10.7) were more likely to be treated in an adult center. The 5-year EFS of patients treated at a pediatric center was 69.8%±4.2% vs. 50.7%±4.0% at adult centers (p=0.0006). 5-year OS was 78.0%±3.9% vs. 58.7%±5.5% (p=0.0006). For the entire cohort, there was no significant improvement in EFS over time. In multivariable analysis, only locus of care was significantly associated with EFS [adult vs. pediatric hazard ratio (HR) 4.0; 95CI 1.4-11.9]; age and time period were not predictive. The disparity in both EFS and OS between pediatric and adult cancer centers widened over time (Table 1). In the earliest time period (1992-1998) there was no significant different in OS between adult vs. pediatric centers (HR 1.8; 95CI 0.8-4.3). The HR increased and became statistically significant in the middle time period (1999-2005; HR 2.4; 95CI 0.9-5.6) and widened further in the most recent time period (2006-2011; HR 4.3; 95CI 1.4-13.8). Conclusions: Despite studies showing improved survival outcomes in AYA with ALL treated on pediatric-based protocols, and the increased use of such protocols at adult centers, outcomes in Ontario did not improve over the 20-year study period. Contrary to expectations, disparities in survival between pediatric and adult centers widened, with the largest disparities seen in the most recent time period. These results suggest that at a population-level, the use of pediatric protocols may not be sufficient to abolish locus of care-based outcome disparities. Future analyses will look at the impact of protocol adherence, delays in therapy, toxicity, and hospital volume on survival. Download : Download high-res image (80KB) Download : Download full-size image Disclosures No relevant conflicts of interest to declare.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,339
Score d'incertitude au seuil0,674

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,003
Études des sciences et des technologies0,0020,001
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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.

Tête enseignante Opus0,027
Tête enseignante GPT0,282
Écart entre enseignants0,255 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2017
Routes d'admission2
Résumé présentoui

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