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Is prostate brachytherapy a dying art? Evidence of increasing utilization in Ontario, Canada.

2020· article· en· W3032708276 on OpenAlexaffabout
Mark T. Corkum, Gerard Morton, Alexander V. Louie, Glenn Bauman, Lucas C. Mendez, David D’Souza, Robert Dinniwell, Vikram Velker, Andrew Warner, George Rodrigues

Bibliographic record

VenueJournal of Clinical Oncology · 2020
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsOttawa Regional Cancer FoundationHealth Sciences CentreWestern UniversitySunnybrook Health Science CentreCancer Care Ontario
Fundersnot available
KeywordsMedicineProstatectomyBrachytherapyProstate cancerUrologyLogistic regressionProstateGynecologyInternal medicineCancerRadiation therapy

Abstract

fetched live from OpenAlex

e17608 Background: A worldwide decline in prostate brachytherapy (BT) utilization has been reported in multiple health care settings/jurisdictions, despite strong evidence for efficacy and safety compared to other alternatives. We sought to evaluate contemporary trends in BT, EBRT and prostatectomy utilization in a publicly funded healthcare system. Methods: Men with localized prostate cancer diagnosed and treated between 2007 and 2017 in Ontario, Canada were identified using administrative data from the Institute for Clinical Evaluative Sciences. Men were coded to have received EBRT, BT (monotherapy or boost) or prostatectomy as initial definitive management. Trends were evaluated using the Cochran-Armitage test. Multivariate logistic regression was used to evaluate patient-, tumour-, and provider-factors on treatment utilization over time. Results: 57,655 men were included in our study. Prostate BT use increased from 7.5% of all treatments in 2007 to 15.4% in 2017 ( p< 0.01), primarily due to increased use of BT boost (1.7% in 2007 to 10.4% in 2017, p < 0.01). Relative to EBRT, BT use increased from 17.9% in 2007 to 28.1% in 2017 ( p< 0.01). On multivariate analysis (MVA), BT boost use increased by 28% per year (OR 1.28, 95% CI 1.26–1.31, p< 0.01) and BT monotherapy use increased by 12% per year (OR 1.12, 95% CI 1.10–1.14, p< 0.01), offset by decreasing prostatectomy use (12% per year, OR 0.88, 95% CI 0.87–0.89, p< 0.01). Comparing BT to EBRT, the strongest predictors of receiving BT were geographic residence (OR 27.6, 95% CI: 20.3–37.6, p< 0.01 between highest/lowest Local Health Integration Networks) and whether the first consulting radiation oncologist performed BT (OR 3.46, 95% CI: 3.15–3.80, p< 0.01). Other significant factors predicting BT use vs. EBRT included lower age, lower PSA, lower Charlson comorbidity score and increasing neighborhood income quintile. Low-intermediate, high-intermediate and high-risk groups were predictive of receiving BT boost, whereas BT monotherapy was predominantly used in low-risk disease. Conclusions: Contrary to trends observed in other jurisdictions, utilization of prostate BT is increasing over time in Ontario. However, substantial variation in BT utilization was found, strongly driven by both geographic region and radiation oncologist BT practice patterns. To our knowledge, this is the first study to report increasing BT utilization in the era of dose-escalated EBRT, with Ontario potentially serving as a model to promote BT utilization elsewhere.

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)0.007
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 score0.054
Threshold uncertainty score0.393

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.008
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.273
GPT teacher head0.470
Teacher spread0.196 · 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

Citations1
Published2020
Admission routes2
Has abstractyes

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