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Enregistrement W2908534685 · doi:10.1182/blood-2018-99-111532

Older Adults with Acute Myeloid Leukemia in Rural Areas Are Less Likely to Receive Azacitidine with Worsened Overall Survival

2018· article· en· W2908534685 sur OpenAlexaffabout
Ryan J. Stubbins, Lauren Lee, Yasser Abou Mourad, Michael J. Barnett, Raewyn Broady, Donna L. Forrest, Alina S. Gerrie, Donna E. Hogge, Stephen H. Nantel, Sujaatha Narayanan, Thomas J. Nevill, Maryse Power, Kevin Song, Heather J. Sutherland, Cynthia L. Toze, Jennifer White, David Sanford

Notice bibliographique

RevueBlood · 2018
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensLeukemia & Lymphoma Society of CanadaUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésMedicineAzacitidinePopulationCancer registryMyelodysplastic syndromesCohortPediatricsInternal medicineCancerBone marrow

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction Acute myeloid leukemia (AML) in older adults is a challenging clinical problem with a poor prognosis. Hypomethylating agents, such as azacitidine, improve survival in this population. (Oran B, Haematologica 2012) These treatments can be challenging to deliver, particularly in patients far from tertiary care centres. We examined whether residence outside of a major metropolitan area impacted referral patterns, treatments, and outcomes in a population-based cohort of AML patients over age 60 in British Columbia (BC), Canada. Methods Patients with ICD-10 diagnoses of AML were identified from the population based BC Cancer registry and BC Cancer pharmacy database. Diagnoses between 2010 and 2016 were included. Exclusion criteria included diagnosis age less than 60 years, any treatment outside BC, or APL. The diagnosis of AML was verified by chart review. Azacitidine was available at our institution in 2010, and is used primarily for patients with bone marrow blast counts below 30%. Patients were defined as having a hematologist/oncologist assessment if a provider with these credentials was listed in notes or pathology reports. Patients were defined as having received a treatment if it was dispensed at least once, with a date after AML diagnosis. Patients were defined as urban if they had a mailing address in a center of >/= 100,000 people, per the Statistics Canada definition, and rural if they had a mailing address elsewhere. Urban residences included greater Vancouver, Victoria and Kelowna, which comprise 71.5% of the population. (Statistics Canada, 2016 census) Between group differences were assessed by 2-tailed t-test or chi-square tests. Overall survival (OS) was assessed by Kaplan-Meier, with a log-rank test, and Cox regression. A p < 0.05 was significant. Results A total of 879 patients over age 60 with AML, excluding APL, were identified. Of these, 525 (60%) resided in urban areas vs 354 (40%) residing in rural areas. These groups were similar for median age at diagnosis (urban 75.9 years, rural 74.3 years, p = 0.067), adverse cytogenetic profile (urban 56%, rural 44%, p = 0.356), NPM1 positivity (urban 69%, rural 31%, p = 0.101) and FLT3 positivity (urban 76%, rural 24%, p = 0.052). Rural residents were less likely to have a documented hematologist/oncologist assessment (urban 84%, rural 65%, p < 0.001). Few patients overall received induction chemotherapy (151, 17%), with no difference between rural and urban residency (p = 0.524). Similarly, few patients underwent hematopoietic stem cell transplantation (38, 4%), with no difference with place of residence (p = 1.000). Median OS for patients treated with induction chemotherapy was 11.0 months (95% CI 9.0 - 13.1 mo). Median OS for patients treated with subcutaneous (SC) azacitidine was 7.1 months (95% CI 4.8 - 9.5 mo) vs 4.7 months (95% CI 3.3 - 6.1 mo) with SC cytarabine. With best supportive care, the median OS was 1.7 months (95% CI 1.5 - 1.9 mo). Median follow-up was 43.7 months (95% CI 39.2 - 48.2 mo), with 706 (97%) of patients deceased at last follow-up. Amongst the 728 patients who did not receive induction chemotherapy, 82 (11%) received SC cytarabine and 127 (17%) received SC azacitidine. Place of residence did not impact whether patients received SC cytarabine (urban 10%, rural 13%, p = 0.285). Rural residents were, however, less likely to receive SC azacitidine (urban 21%, rural 12%, p = 0.002). In patients not undergoing induction, rural residents had a worse OS by Kaplan-Meier analysis (p = 0.021), with a hazard ratio of 1.2 (95% CI 1.026 - 1.387, p = 0.022) on univariate Cox regression. Conclusions Older adults with a diagnosis of AML who reside in rural areas of BC are less likely to have a documented hematologist/oncologist assessment, and are less likely to receive SC azacitidine. This group also has a worsened OS, though the effect size is modest. There was no difference in rates of treatment with potentially curative regimens, although this approach applied to a minority of patients. We hypothesize that this difference may be partially due to the travel burdens placed on rural patients who receive SC azacitidine, which must be administered in a healthcare facility, unlike SC cytarabine. Less access to supportive care in rural areas is also likely a contributing factor. Policymakers should direct additional resources for rural oncologic healthcare delivery, and the importance of low burden drug formulations is AML should be emphasized. 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)0,000
score de la tête « metaresearch » (Gemma)0,001
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 enseignants0,104
Score d'incertitude au seuil0,207

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,000
Communication savante0,0010,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0050,000

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 Opus0,012
Tête enseignante GPT0,257
Écart entre enseignants0,245 · 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
Publié2018
Routes d'admission2
Résumé présentoui

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