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Quality of life (QoL) of patients with metastatic castration resistant prostate cancer (mCRPC) treated with cabazitaxel.

2013· article· en· W2600932175 on OpenAlexaffabout
Eric Winquist, Srikala S. Sridhar, Stacey Hubay, Hazem Assi, Scott R. Berry, Karine Alloul, Éric Lévesque, Nathalie Aucoin, Piotr Czaykowski, Fred Saad

Bibliographic record

VenueJournal of Clinical Oncology · 2013
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsCancerCare ManitobaUniversité de MontréalUniversité LavalSanofi (Canada)Sunnybrook Health Science CentreUniversity of TorontoMoncton HospitalLondon Health Sciences CentreGrand River HospitalPrincess Margaret Cancer Centre
Fundersnot available
KeywordsCabazitaxelMedicineProstate cancerQuality of life (healthcare)DocetaxelInternal medicineCancerOncologyAndrogen deprivation therapy

Abstract

fetched live from OpenAlex

e16088 Background: The effects of cabazitaxel on QoL, pain response and preference/utility data have not been well studied in men with CRPC treated post-docetaxel. As part of a single-arm multicenter Sanofi-funded Early Access Program (EAP) for cabazitaxel, QoL data were collected on Canadian patients. Methods: Between May 2011 and February 2012, 61 patients (pts) were enrolled at 9 centers. QoL was assessed at the start of each cycle using the FACT-P and its subscales, and the EQ 5D-3L. EQ 5D-3L health state index (HIS) data were converted into utility values (Canadian tariff, Bansback 2011). Present pain intensity (PPI) and analgesic scores were assessed using the McGill-Melzack questionnaire. Results: QoL data were evaluable in 55 pts. Baseline pt characteristics were: median age 65 years (range, 42-79), 92.7% of pts were ECOG PS 0 or 1, 87% had bone metastases, and 56% (31/55) received at least 6 cycles of cabazitaxel. Statistically significant changes from baseline in mean QoL scores were observed on FACT-P total score at cycle 2, and prostate cancer specific subscale (PCS) at cycles 1 to 4. As a measure of QoL response, increases were observed and maintained for > 2 consecutive cycles in 9% (>16 points) and 25% (≥10) of pts for FACT-P total score. Improvements to the level of Minimal Important Differences (MID) (Cella 2009) maintained for > 2 consecutive cycles were observed in 36% of pts for FACT-P total score (MID=6), 49% for PCS subscale (MID=2), and 26% for PCS-Pain subscale (MID=2), respectively. The percentage of pts reporting "no problem" in the EQ-5D pain/discomfort domain were above baseline levels at every cycle and improved from baseline to end of treatment from 19% to 29% (p < 0.05). Other EQ-5D dimensions (anxiety/depression, mobility, self-care and usual activities) remained stable over the course of treatment. Improvement from baseline in utility value (HIS) was observed at cycle 4 with a utility value of 0.769 (vs 0.713 at baseline). PPI scores improved despite stable analgesic use and were significantly different from baseline at cycles 2, 4 and 9. Conclusions: Data from this EAP suggest improvements in QoL, pain and prostate cancer specific symptoms with second-line cabazitaxel treatment. Clinical trial information: NCT01254279.

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)0.001
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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.163
GPT teacher head0.490
Teacher spread0.327 · 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
Published2013
Admission routes2
Has abstractyes

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