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Integrating early palliative care in advanced sarcoma patients for enhanced quality of life: The SARQUALITY study.

2025· article· en· W4410800326 on OpenAlexaffabout
Catherine S. Weadick, Natalie Pulenzas, Harleen Toor, Victor Cellarius, J. Matharu, Abdulazeez Salawu, Geoffrey Alan Watson, Abha A. Gupta, Erica C. Koch Hein, Albiruni Ryan Abdul Razak

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsUniversity of TorontoUniversity Health NetworkMount Sinai HospitalPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicinePalliative careQuality of life (healthcare)SarcomaIntensive care medicineOncologyInternal medicineNursingPathology

Abstract

fetched live from OpenAlex

TPS11587 Background: Patients with advanced cancer may experience physical and psychological symptoms impacting health-related (HRQOL). The World Health Organization defined palliative care as “an approach that improves the quality of life of patients and their families” by identification and management of pain and other symptoms, spiritual and psychosocial assessments and interventions, facilitation of home and community-based supports, and transition to end-of-life care. Early palliative care (EPC) integration with cancer-directed treatment can enhance patient-reported outcomes (PROs). However, patients with sarcoma have been underrepresented in these studies, underscoring the need to evaluate the role and benefits of EPC in this population. This study aims to determine whether EPC alongside standard oncological care (SOC) improves PROs for patients with advanced sarcoma compared to usual care. Methods: This is a single program, dual institution phase 2 open-label clinical trial designed to assess whether EPC improves the HRQoL of patients with advanced sarcoma. Main eligibility criteria at enrolment include systemic treatment naïve patients over the age of 18 years with histologically proven advanced sarcoma, ECOG 0-2, English speaking and life expectancy of over 6 months. Enrolled patients are randomized 1:1 to either SOC alone or with EPC. Patients randomized to EPC will be reviewed by palliative care within 2 weeks of randomization. EPC will include routine in person (or virtual) contact integrated into their oncology visits and access to a 24-hour on-call service. Patients receiving SOC alone will be referred to palliative care upon emergence of uncontrollable symptoms or upon request by the patient. Patients on both arms will receive standard of care follow-up with their oncology teams and complete Edmonton Symptom Assessment System (ESAS) and EORTC QLQ-C30 questionnaires at baseline, weeks 6, 12 and 24. For the primary endpoint, EPC will be considered effective if ESAS score decreases at week 12 compared to baseline using T test, with one-sided significance level set to be 0.05. The secondary endpoints include EORTC QLQ-C30 score change (baseline to weeks 6, 12 and 24), number of extra clinic visits, emergency department attendance and overall survival at 6 and 12 months. Comparison between the two arms, assessing both scores, will be done using Fisher’s exact or Chi-square test. Generalized linear mixed model will be carried out to examine the difference between the arms over time. To ensure this trial is powered to determine a significant statistical difference, we plan to enroll 136 patients with an estimated accrual period up to three years. This study commenced enrolment March 2024 and to date (January 2025) 27 patients have been recruited with 13 (48%) randomized to EPC. An amendment is currently ongoing to include the use of electronic wearables as part of the study evaluation.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.003
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)0.0060.001

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 head0.378
GPT teacher head0.630
Teacher spread0.251 · 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
Published2025
Admission routes2
Has abstractyes

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