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First validation of the supportive care score (SCC) scale: Alert scale for referral of solid cancer patients to supportive oncology team.

2020· article· en· W3031149933 on OpenAlexaboutno aff
Mathilde Chastenet, Pierre-Antoine Laurain, Typhaine Maupoint, Karine Legeay, Julia Salleron, Florian Baumard, Florian Scotté

Bibliographic record

VenueJournal of Clinical Oncology · 2020
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineQuality of life (healthcare)ReferralCancerAnxietyAmbulatoryInternal medicinePhysical therapyEmergency medicineFamily medicinePsychiatryNursing

Abstract

fetched live from OpenAlex

e14025 Background: Patients’ needs are still underestimated during cancer course. The development of a simple and accessible screening tool to identify supportive care needs is an innovative approach to improve the cancer care pathway. Supportive Scale sCore (SCC) is a new tool developed to trigger alert in main need of supportive care such as social, nutritional, physical, pain or psychological disorders. This study aimed to develop and validate the SCC tool for detecting supportive care needs. Methods: The SCC, the Edmonton Symptom Assessment System (ESAS), a symptom scale and the EQ-5D (for Quality Of Life) was distributed to cancer patients over a week, in an ambulatory hospital of oncology department. The acceptability was assessed by the fill rate. The validity of alerts generated by the SCC scale was assessed by their consistency with ESAS and EQ-5D scores. Results: Hundred patients were included with an average age of 67,2 years. Acceptability was good with a fill rate of over 90%. For a-priori defined risk groups by SCC with alert or not, ESAS symptom score and QOL differed significantly (p < 0,05) between groups. We observed higher ESAS symptom scores in the alert group [nutritional alert: appetite: 4 (Standard Deviation SD 2,4) vs 0 (SD 1,6), p < 0,001; physical alert: fatigue: 4 (SD 1,7) vs 2 (SD 2,2) p < 0,001; psychological alert: depressed: 3,5 (SD 2,7) vs 0 (SD 1,5), p < 0,001; anxiety: 4 (SD 2,9) vs 0 (SD 1,5), p < 0,001; unwell-being: 4,5 (SD 2,7) vs. 0 (SD 1,5), p < 0,001]. Moreover, the QOL was poorer in each domain of EQ-5D in the alert group. [Social alert, self-care: 9,3% vs 0%, p = 0,02; usual activities: 25% vs 5,4%, p = 0,005. Physical alert, usual activities: 21,3% vs 2,6%, p = 0,008; mobility 29,5% vs 2,6%, p = 0,01. Pain alert, pain: 81,8% vs 11,9%, p < 0,001. Psychological alert, psychological: 56,3% vs 11,9%, p < 0,001]. Conclusions: The SCC seems to be a reliable instrument to detect cancer patients’ supportive care needs.

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)0.005
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.130
GPT teacher head0.465
Teacher spread0.336 · 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 designBench or experimental
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
Published2020
Admission routes1
Has abstractyes

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