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Enregistrement W1970884898 · doi:10.1097/prs.0b013e3182362e65

Use of the BREAST-Q in Clinical Outcomes Research

2011· letter· en· W1970884898 sur OpenAlexaffabout
Andrea L. Pusic, Anne F. Klassen, Stefan Cano

Notice bibliographique

RevuePlastic & Reconstructive Surgery · 2011
Typeletter
Langueen
DomaineSocial Sciences
ThématiqueDelphi Technique in Research
Établissements canadiensMcMaster University
Organismes subventionnairesnon disponible
Mots-clésMedicinePsychology

Résumé

récupéré en direct d'OpenAlex

Sir:FigureWe wrote this Letter to the Editor regarding the article by Patel et al.1 For patients undergoing oncoplastic breast surgery, quality of life and satisfaction with breast appearance are key considerations. Dr. Patel et al. should thus be congratulated on their cross-sectional evaluation of these important patient-reported outcomes. We were very pleased to see that the authors selected the BREAST-Q2 as the primary outcome measure for their study. With grant support from the Plastic Surgery Foundation, the BREAST-Q was developed and validated over a 5-year period with the aid of approximately 3000 women. The BREAST-Q is a psychometrically sound and clinically meaningful patient-reported outcome measure with a state-of-the-art scoring system. Based on the article by Patel et al., we would like to raise and clarify two critical issues about the use of the BREAST-Q by the clinical research community. The first issue relates to appropriate use of the BREAST-Q. The BREAST-Q is composed of multiple, independently functioning scales (e.g., Satisfaction with Breasts, Psychosocial Well-Being, Sexual Well-Being). In any given study, it is not necessary to use all the scales. Rather, given that each scale was designed to measure a unidimensional construct, investigators are able to pick and choose which scales they deem to be the most relevant to answering their study's research question(s). Scale selection per se does not constitute an “adaptation” of the BREAST-Q (this was erroneously suggested by Patel et al.). Conversely, any changes made to the content of the BREAST-Q (e.g., changing the wording of individual questionnaire items, or adding new items to any of its validated scales) is not acceptable. The problem with changing previously developed and psychometrically validated scales is that such changes nullify the psychometric properties of the questionnaire. Furthermore, using an adapted measure makes it impossible to compare findings with those of other BREAST-Q studies. Importantly, such adaptations are prohibited under copyright laws. The second issue relates to appropriate scoring of the BREAST-Q. It is crucial that raw responses provided by patients be transformed into BREAST-Q scores using the Q-Score program. This program is provided free of charge on our Web site (www.BREAST-Q.org). Using this program, researchers are able to convert their raw questionnaire data and then compute summary scores for each BREAST-Q scale that range from 0 to 100 (with a higher number indicating higher satisfaction or better quality of life). The transformation is essential, as it is through this process that the ordinal-level data are linearized by means of item calibrations.2 Using Q-Score, researchers may then compare their sample of patients with patients from different studies on the same metrics. As Dr. Patel et al. did not use the Q-Score program to score their study data, it is impossible to interpret their findings or compare their findings with other BREAST-Q–based research. It is exciting to see a growing number of clinical researchers using patient-reported outcome measures such as the BREAST-Q in their studies and working to better understand the impact of plastic surgery from a patient perspective. Our team recommends that users of the BREAST-Q adhere to our published guidelines about the appropriate use and scoring of this measure. Doing so will ensure that the accumulation of BREAST-Q data by the research community can be brought together to inform further clinical interpretation of BREAST-Q data scores. Andrea L. Pusic, M.D., M.H.S. Memorial Sloan-Kettering Cancer Center, New York, N.Y. Anne F. Klassen, D.Phil. McMaster University, Hamilton, Ontario, Canada Stefan J. Cano, Ph.D. Peninsula College of Medicine and Dentistry, Plymouth, United Kingdom DISCLOSURE The BREAST-Q is owned by Memorial Sloan-Kettering Cancer Center and the University of British Columbia. Drs. Pusic, Klassen, and Cano are co-developers of the BREAST-Q and receive a share of licensing revenues based on the inventor-sharing policies of these two institutions.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,100
score de la tête « metaresearch » (Gemma)0,414
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,100
Score d'incertitude au seuil0,529

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,1000,414
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0030,004
Études des sciences et des technologies0,0020,006
Communication savante0,0070,006
Science ouverte0,0030,003
Intégrité de la recherche0,0090,014
Charge utile insuffisante (le modèle a refusé de juger)0,0050,003

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,412
Tête enseignante GPT0,482
Écart entre enseignants0,071 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations51
Publié2011
Routes d'admission2
Résumé présentoui

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