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Record W2162324668 · doi:10.5539/cco.v2n2p34

Utilization of Hypofractionated and Conventional Breast Radiotherapy in the State of Utah

2013· article· en· W2162324668 on OpenAlexvenueno aff
Brandi R. Page, Tom Belnap, Randy C. Bowen, David K. Gaffney, William T. Sause

Bibliographic record

VenueCancer and Clinical Oncology · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBreast cancerRadiation therapyLogistic regressionRandomized controlled trialMedical prescriptionOdds ratioInternal medicineCancer

Abstract

fetched live from OpenAlex

Efficacy of hypofractionated (HF) radiotherapy (RT) in breast cancer has recently been established by randomized trials. We report patterns of care in Utah to identify how patient, tumor, and treatment characteristics may influence prescription patterns. Data from 1,588 patients from nine facilities with 18 providers were retrospectively collected. Conventionally fractionated (CF) RT was defined as >19 fractions with fractions < 200cGy; HF was defined as <19 fractions with fractions >200cGy. Partial breast irradiation (PBI) was defined as external beam RT to 3850cGy in 10 fractions. Patients considered eligible for HF were >45 years with breast separation <25 cm and tumor size <2cm with negative nodes and margins. Analysis utilized Wilcoxon Rank Sum Tests and logistic regression. Of all patients, 83.2% received CF, 12% received HF, and 4.7% received PBI. Based on recent published guidelines, 53.5% of patients were eligible for HF. There were no significant differences with respect to laterality, tissue separation, or medical comorbidities. Calculated odds ratios (OR) for increased use of HF included age (OR 1.05, p<0.001) and lower cancer stage (OR 3.75, p=0.002). Use of HF strongly correlated with increased age, number of miles traveled to clinic (47.8 vs. 21), lower grade, less aggressive surgery, and less chemotherapy. HF RT utilization is increasing over time but only in a segment of eligible patients. We report on changes in practice patterns after recent publication of randomized trial data in an effort to bring awareness to underutilization of HF, and intend to track how this changes over time.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.571
Threshold uncertainty score0.144

Codex and Gemma teacher scores by category

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

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 head0.043
GPT teacher head0.397
Teacher spread0.354 · 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 teacher head, 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

Citations4
Published2013
Admission routes1
Has abstractyes

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