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Understanding patient characteristics, treatment patterns, and clinical outcomes for advanced and recurrent endometrial cancer in Alberta, Canada.

2022· article· en· W4281654617 on OpenAlexaffabout
Jacob McGee, Dylan E. O’Sullivan, Devon J. Boyne, Winson Y. Cheung, Odette Allonby, Mara Habash, Darren R. Brenner, Diana Martins

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicEndometrial and Cervical Cancer Treatments
Canadian institutionsGlaxoSmithKline (Canada)University of CalgaryWestern University
Fundersnot available
KeywordsMedicineInternal medicineChemotherapyRegimenCancerIncidence (geometry)CohortRadiation therapyRetrospective cohort studyOncologyEndometrial cancerSurgery

Abstract

fetched live from OpenAlex

e17624 Background: Endometrial cancer (EC) incidence in Canada is steadily increasing and a paucity of real-world data exists. This study aimed to examine treatment (tx) patterns and clinical outcomes for patients (pts) with advanced and recurrent (A/R) EC in Canada. Methods: A retrospective observational cohort study was conducted among pts with primary advanced EC (de novo stage IIIB, IIIC, IV) or recurrent EC (progression from de novo stage I, II, IIIA) between 2010 and 2018 in Alberta, Canada. Health administrative data were used to describe baseline characteristics, time to next tx (TTNT), and overall survival (OS). Using Kaplan-Meier methods, TTNT was defined from tx initiation to initiation of subsequent tx or death from any cause, and OS was examined from tx initiation until death from any cause. Outcomes were stratified by pt type (A/R) and tx. Results: 1,053 pts were included: 620 (58.9%) advanced and 433 (41.1%) recurrent pts. 713 (67.7%) pts received first-line (1L) systemic therapy; this differed by pt type (75.2% of advanced and 57.0% of recurrent pts). Advanced pts who received chemotherapy were more likely to have prior surgery (p < 0.001), radiotherapy (p = 0.01), were younger (p < 0.001), and had fewer comorbidities (p < 0.001) than those without chemotherapy. Platinum-based chemotherapy (PBCT) was the most common 1L regimen (78.6%), differing by pt type (96.1% for advanced and 45.4% for recurrent pts). Hormone therapy in 1L was higher for recurrent compared to advanced pts (27.9% vs 3.2%). Median TTNT and OS from 1L systemic therapy was 19.9 months (95% confidence interval [CI]: 17.5–23.5) and 35.9 months (95% CI: 31.5–53.5), differing by therapy (p < 0.05). Median OS from 1L ranged from 8.5 months (95% CI: 6.2–20.0; platinum monotherapy) to 62.5 months (95% CI: 59.2–NA; hormone therapy). 257 pts received second-line (2L) chemotherapy, with a median TTNT of 7.0 months (95% CI: 6.1–8.2) and median OS of 12.6 months (95% CI: 10.0–14.6). Outcomes differed by tx (p < 0.05), with median OS ranging from 8.0 months (95% CI: 5.9–13.2; non-platinum monotherapy) to 17.1 months (95% CI: 12.7–NA; non-platinum combination). Among pts who received a 1L PBCT, median OS from 2L chemotherapy (N = 187) was 10.4 months (95% CI: 8.9–13.3) and was significantly higher for those rechallenged with PBCT compared to no rechallenge (13.3 months [95% CI: 11.2–20.9] vs 6.4 months [95% CI: 4.6–10.4]). Median OS in third-line (N = 71) and fourth-line (N = 26) chemotherapy was 11.0 months (95% CI: 8.2–13.5) and 12.0 months (95% CI: 7.5–NA), respectively. Outcomes did not differ significantly by pt type (A/R; p≥0.05). Conclusions: Outcomes for pts with A/R EC in Alberta, Canada are poor, particularly following 1L therapy where tx options are limited. Novel therapies with proven efficacy could address this unmet need and improve pt outcomes. Funding: GSK (216962; diana.d.martins@gsk.com).

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)0.002
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 score0.020
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.217
GPT teacher head0.470
Teacher spread0.253 · 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".

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Citations0
Published2022
Admission routes2
Has abstractyes

Explore more

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