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Record W4401614952 · doi:10.3390/curroncol31080345

Comparison of Weekly Paclitaxel Regimens in Recurrent Platinum-Resistant Ovarian Cancer: A Single Institution Retrospective Study

2024· article· en· W4401614952 on OpenAlexaffvenueabout
L. Morin, Louis-Philippe Grenier, Nicolas Foucault, Éric Lévesque, François Fabi, Eve-Lyne Langlais, Alexandra Sebastianelli, Marianne Lavoie, Marc Lalancette, Marie Plante, Narcisse Singbo, Vincent Castonguay

Bibliographic record

VenueCurrent Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsUniversité LavalCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsMedicinePaclitaxelOvarian cancerRetrospective cohort studyOncologyInternal medicinePlatinumCancerBiology

Abstract

fetched live from OpenAlex

Weekly paclitaxel (WP) is a chemotherapeutic cornerstone in the management of patients with platinum-resistant ovarian carcinoma. Multiple WP dosing regimens have been used clinically and studied individually. However, no formal comparison of these regimens is available to provide objective guidance in clinical decision making. The primary objective of this study was to compare the cumulative dose of paclitaxel delivered using 80 mg/m2/week, administered using either a 3 weeks out of 4 (WP3) or a 4 weeks out of 4 (WP4) regimen. The secondary objective was to evaluate the clinical outcomes associated with both regimens, including efficacy and toxicity parameters. Our retrospective cohort comprised 149 patients harboring platinum-resistant ovarian cancer treated at the CHU de Québec from January 2012 to January 2023. WP3 and WP4 reached a similar cumulative dose (1353.7 vs. 1404.2 mg/m2; p = 0.29). No significant differences in the clinical outcomes were observed. The frequency of dose reduction was significantly higher for WP4 than WP3 (44.7% vs. 4.9%; p < 0.01), mainly due to treatment intolerance from toxicity (34.0% vs. 3.9%; p < 0.01). Our data suggest that a WP3 regimen delivers a similar cumulative dose to WP4, hence offering a better tolerability profile without compromising efficacy.

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)0.003
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 score0.059
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.144
GPT teacher head0.457
Teacher spread0.313 · 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

Citations2
Published2024
Admission routes3
Has abstractyes

Explore more

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