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Record W4410455900 · doi:10.1016/j.esmoop.2025.104879

307P Relationship between physician-graded symptomatic adverse events and patient-reported quality of life (QOL): An analysis of the phase III PALLAS trial

2025· article· en· W4410455900 on OpenAlexaff
Vesna Bjelic‐Radisic, L. Sölkner, Angela DeMichele, M. Naughton, Julie Lemieux, Nicholas Zdenkowski, Manuel Ruíz Borrego, Jun J. Mao, Eileen H. Shinn, Christian F. Singer, Jane Meisel, Arlene Chan, Hiroji Iwata, T. Mamounas, Sibylle Loibl, Eric Gauthier, Amylou C. Dueck, Dominik Hlauschek, Erica L. Mayer, M.I. Gnant

Bibliographic record

VenueESMO Open · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsQuality of life (healthcare)Adverse effectPhase (matter)MedicineFamily medicineQuality (philosophy)GerontologyInternal medicineNursingPhilosophyChemistry

Abstract

fetched live from OpenAlex

PALLAS is a prospective, randomised, open-label, multi-centre phase III trial comparing the addition of 2 years of palbociclib to adjuvant endocrine therapy (ET) versus ET-alone, in patients (pts) with HR+/HER2- early breast cancer (BC), capturing long term clinical outcomes, physician-graded toxicity by Common Terminology Criteria for Adverse Events (CTCAE) v4.0 and patient-reported QOL . QOL was assessed using EORTC-QLQ-C30. The objective of this analysis is to determine the relationship between clinician-graded symptomatic AEs and patient-reported QOL in the PALLAS study.

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)0.015
metaresearch head score (Gemma)0.019
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.019
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.416
GPT teacher head0.492
Teacher spread0.076 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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