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Predictors of stopping chemotherapy early and short survival in patients with potentially platinum sensitive (PPS) recurrent ovarian cancer (ROC) who have had ≥3 lines of prior chemotherapy: The GCIG symptom benefit study (SBS).

2017· article· en· W2735026933 on OpenAlexaff
Felicia Roncolato, Florence Joly, Rachel O’Connell, Anne Lanceley, Florian Heitz, Luke Buizen, Aikou Okamoto, Eriko Aotani, Vanda Salutari, Paul Donnellan, Amit M. Oza, Elisabeth Åvall‐Lundqvist, Jonathan S. Berek, Felix Hilpert, Amanda Feeney, C. Roemer-Bécuwe, Martin R. Stockler, Madeleine King, Michael Friedländer

Bibliographic record

VenueJournal of Clinical Oncology · 2017
Typearticle
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsMedicineChemotherapyInternal medicineProportional hazards modelCarboplatinOvarian cancerLogistic regressionCancerSurgeryOncologyCisplatin

Abstract

fetched live from OpenAlex

5575 Background: PPS ROC is defined by a platinum free interval > 6 months. Women starting ≥3 lines of chemotherapy for PPS ROC are however a heterogeneous group with variable response to chemotherapy and OS. We sought to identify baseline characteristics (health related quality of life [HRQL] and clinical features) that were associated with stopping chemotherapy early and shorter OS to improve patient selection for palliative chemotherapy. Methods: 378 women with PPS ROC starting ≥3 lines chemotherapy enrolled in GCIG SBS. HRQL was assessed with EORTC QLQ-C30/QLQ-OV28. Associations with stopping chemotherapy early (by 8 weeks) were assessed with logistic regression. Associations with OS were assessed with Cox proportional hazards regression. Variables significant in univariable analysis (p < 0.05) were included as candidates for multivariable analyses using backward elimination to select those independently significant at p < 0.05. Results: Median age was 64 years. The line of chemotherapy was third in 40%, fourth in 29%, and ≥ fifth in 31%. Chemotherapy was stopped early in 45/378 (12%) and their median OS was 3.4 months. Poor physical function (PF) and global health status (GHS) at baseline were significant univariable predictors of stopping chemotherapy early (p < 0.008); PF remained significant in a multivariable model adjusting for clinical factors (haemoglobin [Hb], ascites, abdominal cramps, neutrophil: lymphocyte≥5, platelets, log CA125); p = 0.03. Median OS in the whole group was 16.6 months. PF, role function, GHS and abdominal/GI symptoms were significant univariable predictors of OS (p < 0.001); PF and GHS remained significant predictors of OS in multivariable models including Hb, ascites, neutrophil: lymphocyte≥5, platelets, log CA125, ECOG and BMI (p < 0.007). Conclusions: In women with PPS ROC ≥3 lines chemotherapy, baseline PF and GHS are independent significant predictors of stopping chemotherapy early and short OS. HRQOL is easily measured, prognostic and may improve clinical trial stratification, patient-doctor communication and support clinical decision making. Clinical trial information: 12607000603415.

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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0010.000

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 head0.051
GPT teacher head0.394
Teacher spread0.343 · 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
Published2017
Admission routes1
Has abstractyes

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