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Postmastectomy radiation in women with node positive breast cancer in the Ontario population.

2017· article· en· W2622134420 on OpenAlexaffabout
Steven Latosinsky, Krista Bray Jenkyn, Lihua Li, Salimah Z. Shariff

Bibliographic record

VenueJournal of Clinical Oncology · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsInstitute for Clinical Evaluative SciencesWestern University
Fundersnot available
KeywordsMedicineBreast cancerMastectomyPopulationRadiation therapyCancerCancer registryComorbidityRandomized controlled trialLogistic regressionInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

e12104 Background: Despite two randomized controlled trials first published in 1997 showing improvements in both locoregional control and survival, postmastectomy radiation for node positive breast cancer patients has not been universally accepted; particularly for patients with 1-3 positive nodes. Subsequent favorable meta-analyses have resulted in more recent guidelines supporting postmastectomy radiation. We examined the rate and predictors of postmastectomy radiation receipt in node positive breast cancer patients in Ontario (population 13.2 million). Methods: We used the Ontario Cancer Registry, a population-based, prospectively-collected registry, to identify all node positive female breast cancer patients in the province with a diagnosis date between April 1, 2010 and Sept 30, 2014. Patient records were linked to prospectively maintained health administrative databases. Through these databases, the universal single-payer health care system in Ontario can capture details for each patient for all health care encounters, hospitalizations, procedures (mastectomy), prescription medications, systemic cancer therapy and radiation. Logistic regression modeling using generalized estimating equations was employed to determine the association between patient, tumor and treatment characteristics and receipt of radiation, while accounting for the possible clustering effect by health regions. Results: Of the 6,535 women with node positive breast cancer who had undergone a mastectomy 73.9% received radiation. Of the 4227 women with 1-3 positive nodes, 68.7% received radiation, and of the 2308 women with > 3 positive nodes 83.4% received radiation. Receipt of radiation was positively associated with younger age ( < 70 years), increasing cancer stage and a lower Charlson comorbidity index. Conclusions: In a setting with universal healthcare, the majority of women with node positive breast cancer in Ontario received postmastectomy radiation, including women with 1-3 positive nodes. Older women, those with higher stage and those who had increased co-occurring medical conditions were less likely to receive radiation therapy.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.093
Threshold uncertainty score0.186

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.032
GPT teacher head0.396
Teacher spread0.364 · 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
Published2017
Admission routes2
Has abstractyes

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