MétaCan
Menu
Back to cohort

Patient- versus clinician-reported symptoms in the POLARIX study.

2023· article· en· W4379341012 on OpenAlexaff
Carrie A. Thompson, Neha Mehta-Shah, Christopher R. Flowers, Gilles Salles, Hervé Tilly, Neil Chua, Olivier Casasnovas, Fiona Miall, Tae Min Kim, Cheng‐Hong Tsai, Sunita D. Nasta, Seung‐Tae Lee, Veronica Craine, Avrita Campinha‐Bacote, Jamie Hirata, Calvin Lee, Matthew Sugidono, Jonathan W. Friedberg

Bibliographic record

VenueJournal of Clinical Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicCancer Treatment and Pharmacology
Canadian institutionsRoche (Canada)University of Alberta
Fundersnot available
KeywordsMedicineConstipationNauseaAdverse effectVomitingPlaceboCommon Terminology Criteria for Adverse EventsIncidence (geometry)MedDRAQuality of life (healthcare)Internal medicineDiarrheaClinical trialPhysical therapyPharmacovigilanceAlternative medicine

Abstract

fetched live from OpenAlex

12100 Background: The safety profiles of novel agents are mainly based on clinician-reported adverse events (AEs) from clinical trials. Patient-reported outcomes (PROs) may better represent the treatment burden experienced by patients (pts) compared with clinician-reported AEs. Using data from POLARIX, a double-blind, placebo-controlled, randomized Phase 3 international study (NCT03274492), we previously presented PRO and clinician-reported data showing similar rates of neuropathy (Trněný et al. 2022). Here, we evaluate the reporting of other common symptoms using PRO and clinician-reported data in POLARIX. Methods: POLARIX methods were previously described (Tilly et al. 2022); this analysis included all pts with PRO data. PRO and clinician-reported data described the incidence and severity of fatigue, constipation, diarrhea, nausea, and vomiting. Clinician-reported severity grading was based on the NCI Common Terminology Criteria for Adverse Events (NCI-CTCAE) v4.0. PROs were collected using the European Organisation Research and Treatment of Cancer Quality of Life-Core 30 questionnaire (EORTC QLQ-C30), which was administered to pts at clinic visits on Day 1 of Cycles 1 (baseline), 2, 3, and 5, and end of treatment (EOT). PRO severity scores included ‘A little’, ‘Quite a bit’, and ‘Very much’. Results: Overall, 825 pts were evaluable. From baseline to EOT, PROs showed a higher incidence of symptoms compared with clinicians for fatigue (98% vs 27%), constipation (68% vs 29%), diarrhea (56% vs 26%), nausea (58% vs 40%), and vomiting (24% vs 15%). PRO severity scores of ‘Quite a bit’ or ‘Very much’ were reported in 33% of pts for fatigue, 29% for constipation, 17% for diarrhea, 19% for nausea, and 7% for vomiting. Clinicians reported Grade ≥2 symptoms in 11% of pts for fatigue, 11% for constipation, 11% for diarrhea, 14% for nausea, and 6% for vomiting. Conclusions: In POLARIX, pts reported a higher incidence and severity of symptoms compared with clinicians. Although distinct scales were used, the differences in symptom rates reported by pts and clinicians were clinically meaningful. These data may have implications for symptom management, including physician evaluation and communication of symptom expectations for pts. Reporting of symptoms by PROs should be incorporated into clinical trials as an adjunct to standard AE reporting to better characterize the patient experience. Clinical trial information: NCT03274492 . [Table: see text]

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)0.011
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.989
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.294
GPT teacher head0.580
Teacher spread0.286 · 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.

Study designObservational
DomainMethods
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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Clinical OncologySame topicCancer Treatment and PharmacologyFrench-language works237,207