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Stronger together: Implementing patient-reported symptom tool in routine cancer care in diverse Asia—A multi-national pilot feasibility study (PROMiSE-Pilot).

2024· article· en· W4401514512 on OpenAlexaboutno aff
Piyada Sitthideatphaiboon, Milita Zaheed, Jayson L. Co, Kevin Lee Min Chua, Monica Malik

Bibliographic record

VenueJournal of Clinical Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCancerFamily medicineInternal medicine

Abstract

fetched live from OpenAlex

TPS180 Background: Patients diagnosed with cancer often experience disease or treatment-related symptoms, which can be under-elicited and under-appreciated by clinicians during time-poor consultations. This is particularly challenging in Asia where structural disparities in healthcare access mean oncology services are often under-resourced. Five oncologists from Thailand, India, Singapore, Philippines and Australia formed a working group as part of ASCO Asia-Pacific Leadership Development Program (LDP-AP). Systematic symptom monitoring using patient-reported outcomes measures (PROM) was identified as a potential solution to improve care in diverse Asian settings. PROM has demonstrated improved outcomes in Western settings but its utility in resource limited Asian contexts is less well established. A study was developed to evaluate the feasibility of implementing PROM in routine outpatient care across diverse cultural contexts in Asia. Methods: PROMiSE-Pilot is a prospective, multi-centre, feasibility study of integrating PROM in routine outpatient care across Asia. The Edmonton Symptom Assessment Scale questionnaire (ESAS-r) was selected as the PROM tool. Clinicians in 4 hospitals in Singapore, Manila, Bangkok and Hyderabad will be invited to participate, and their patients will be invited to complete the ESAS-r on paper before each visit. The primary aim is to evaluate if proportion of patients who complete ≥5 of 10 items on ESAS-r is ≥85% (Clopper Pearson). Secondary aims include assessing proportion who complete ≥8 and all 10 items and perceived utility of ESAS-r evaluated through surveys adapted to measure patient and clinician satisfaction. Site-specific patient, clinician, administrative barriers and facilitators will be studied. A pragmatic approach to context-specific implementation was adopted with each site developing its own process map for delivering the pilot and adapting to local patient demographics (e.g. low literacy), cultural contexts and resources. Translated versions of ESAS-r were acquired where necessary. Recruitment commenced in March 2024 following ethics approval at 2 sites. 87 patient encounters have been captured from 5 participating clinicians in Singapore. 5 clinicians have agreed to participate in Bangkok. Target recruitment is 200 encounters per site. Multi-centre data will be presented at the Breakthrough congress. Clinicians from ASCO LDP-AP identified PROM as a low-cost but potentially high-value approach to improving quality of care in resource limited settings in Asia. Understanding the feasibility of such a tool is vital prior to consideration of wider scale adoption by stakeholders. This co-developed multi-national pilot additionally demonstrates the value of collaboration, our strength in diversity and a pragmatic model for investigator-initiated studies in Asia.

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)0.020
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.003
Open science0.0020.004
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0030.001

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 head0.402
GPT teacher head0.558
Teacher spread0.156 · 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 designNon-randomized trial
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
Published2024
Admission routes1
Has abstractyes

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