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Record W3097520009 · doi:10.1182/blood-2020-134645

Geographical Distance from Quaternary Treatment Center Does Not Impact Choice of Upfront Therapy, Clinical Trial Participation and Outcomes in Patients with Newly Diagnosed AML

2020· article· en· W3097520009 on OpenAlexaffabout
Samantha Hershenfeld, Steven M. Chan, Vikas Gupta, Dawn Maze, Caroline McNamara, Mark D. Minden, Tracy Murphy, Andre C. Schuh, Hassan Sibai, Karen Yee, Aaron D. Schimmer

Bibliographic record

VenueBlood · 2020
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineChemotherapy regimenInternal medicineClinical trialChemotherapyPediatrics

Abstract

fetched live from OpenAlex

Upfront therapy for newly diagnosed patients with acute myeloid leukemia (AML) includes intensive induction chemotherapy with curative intent, low dose chemotherapy, best supportive care, and clinical trials. The choice between these therapies is influenced by multiple factors including age, cytogenetic and molecular mutations, and performance status. In our single payer provincial health care system, induction chemotherapy and clinical trials are only offered at a small number of specialized quaternary care centers with geographically large catchment areas. As a result, some patients are required to travel long distances for their appointments, which may constitute a barrier to care, especially among elderly patients. We therefore asked whether distance from the quaternary center influences the choice of care for AML. We reviewed the records of patients ≥18 years of age diagnosed with AML from 2015-2017 and assessed at our quaternary care center in Toronto, Canada. We compared upfront therapy choice and survival between patients living close versus distant from the cancer center (empirically defined as <50 km versus >50km) and stratified by age. A total of 675 patients were assessed by our quaternary center for a new diagnosis of AML during the timeframe studied. Of those patients, 477 (71%) patients lived ≤50km, and 198 (29%) patients lived >50km from the quaternary center. The overall median distance from patient residence to the quaternary center was 33.2km (range: 1-1791km), and the median distance of patients in the >50km group was 93km (range: 50.2-1791km). Age, sex, baseline Eastern Cooperative Oncology Group Performance Status (ECOG), and cytogenetic risk were not significantly different between the two groups. There were no differences in the proportion of patients receiving induction chemotherapy or clinical trial as upfront therapy between patients living close versus distant from the quaternary center, even when stratified for age ≥70 years. There was no difference in overall survival between patients living ≤50km versus >50km from the quaternary center either overall, or when stratified by age. In conclusion, geographic distance from treatment center does not appear to impact choice of upfront therapy, access to clinical trials, or clinical outcomes in this study of newly diagnosed patients with AML treated in a single payer environment. Disclosures Gupta: Bristol MyersSquibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Incyte: Honoraria, Research Funding; Pfizer: Consultancy; Sierra Oncology: Consultancy, Membership on an entity's Board of Directors or advisory committees. Maze:Novartis: Honoraria; Pfizer: Consultancy; Takeda: Research Funding. McNamara:Novartis: Honoraria. Schimmer:Takeda: Honoraria, Research Funding; Novartis: Honoraria; Jazz: Honoraria; Otsuka: Honoraria; Medivir AB: Research Funding; AbbVie Pharmaceuticals: Other: owns stock .

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.223
Threshold uncertainty score0.443

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.048
GPT teacher head0.369
Teacher spread0.320 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2020
Admission routes2
Has abstractyes

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