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Standardized Assessment of Breast Cancer Surgical Scars Integrating the Vancouver Scar Scale, Short-Form McGill Pain Questionnaire, and Patients?? Perspectives

2005· article· en· W1980761012 on OpenAlexafffundabout
Pauline T. Truong, Freddy Abnousi, Celina M. Yong, Allen Hayashi, J. Runkel, T. Phillips, Ivo A. Olivotto

Bibliographic record

VenuePlastic & Reconstructive Surgery · 2005
Typearticle
Languageen
FieldMedicine
TopicPain Management and Opioid Use
Canadian institutionsUniversity of British ColumbiaBC Cancer AgencyIsland Health
FundersMcGill University
KeywordsMedicineIntraclass correlationCronbach's alphaBreast cancerScarsPhysical therapySurgeryCancerInternal medicinePsychometrics

Abstract

fetched live from OpenAlex

BACKGROUND: Currently, there is no standardized, comprehensive method to assess surgical scars after breast cancer surgery. This article evaluates the application of the Vancouver Scar Scale, in conjunction with patients' scar self-rating and scar-related pain, in a cohort of breast cancer patients. METHODS: Data were prospectively collected in 59 women with breast cancer. Scar assessment comprised: 1. objective rating by pairs of independent observers using the Vancouver Scar Scale; 2. patient's ratings of the scar's physical parameters and overall satisfaction; and 3. pain assessment using the Short-Form McGill Pain Questionnaire. A total of 212 scar scores (59 pairs of breast/chest wall and 47 pairs of axillary scar scores) were generated by 13 observers: three physicians, five radiation therapists, and five nurses. Internal consistency was tested using Cronbach's alpha statistics. Interobserver reliability was evaluated with Spearman's rho and intraclass correlation coefficient computations. Convergent validity of the observer and patient ratings was examined with Spearman's correlation statistics. Linear regression analysis was performed to identify significant factors associated with Vancouver Scar Scale scores and patient satisfaction. RESULTS: The Vancouver Scar Scale, patient self-rating scale, and Short-Form McGill Pain Questionnaire had acceptable internal consistency (Cronbach's alpha 0.79, 0.64, and 0.72 respectively). Interobserver reliability using the Vancouver Scar Scale was significant with Spearman's correlation coefficients of 0.53 for pliability, 0.47 for scar height, 0.49 for vascularity, 0.54 for pigmentation, and 0.66 for overall score (all p values < 0.001). Significant agreement between observer and patient ratings of scar pliability (p = 0.01) and color (p = 0.001) was demonstrated. Mild to moderate pain was reported by more than 40 percent of patients. Patient satisfaction was significantly associated with self-rating of scar pliability and pain, but not Vancouver Scar Scale scores. CONCLUSIONS: The Vancouver Scar Scale is a reliable and valid tool to objectively evaluate scars after breast cancer surgery. Evaluation of scar-related pain and patients' scar rating and satisfaction provide additional information relevant to scar assessment. This integrated approach is feasible in a busy clinical setting to advance care and research in scar management for breast cancer patients.

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)0.006
metaresearch head score (Gemma)0.016
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.262
Teacher spread0.253 · 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

Citations69
Published2005
Admission routes3
Has abstractyes

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