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Validation of the Breast Evaluation Questionnaire

2007· letter· en· W2052559553 on OpenAlexaffabout
Andrea L. Pusic, Anne F. Klassen, Stefan Cano, Carolyn L. Kerrigan

Bibliographic record

VenuePlastic & Reconstructive Surgery · 2007
Typeletter
Languageen
FieldMedicine
TopicBreast Implant and Reconstruction
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLumpectomyBreast reductionMedicineMastectomyBreast reconstructionBreast surgeryBreast painIntervention (counseling)Breast cancerGeneral surgeryPhysical therapyMammaplastySurgeryInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Sir: We read with interest the article by Cogwell Anderson et al.,1 which describes the validation of the Breast Evaluation Questionnaire. To appropriately measure the effectiveness of breast surgery, well-developed and validated patient questionnaires are clearly required.2 The authors should be congratulated for presenting the psychometric properties of the Breast Evaluation Questionnaire. To understand all aspects of outcome and to accurately measure change brought about by surgical intervention, questionnaires developed uniquely for breast surgery patients are essential.2 To take this a step further, a useful questionnaire not only should be breast surgery–specific but should also focus on a specific type of breast surgery, whether it be breast augmentation, reduction, or reconstruction. While patients in these different treatment groups have a clear common ground, it does not necessarily follow that they share all the same outcomes of interest. In qualitative interviews we conducted recently with 48 patients undergoing these three different types of breast surgery, we found that the groups often had different concerns. For example, physical function was much more relevant to breast reduction patients, whereas perception of symmetry was more important to augmentation patients.3,4 A questionnaire developed and tested only among cosmetic breast augmentation patients cannot be assumed to adequately measure all the unique concerns of, for example, mastectomy or breast trauma patients. Thus, we question the authors’ recommendation that the Breast Evaluation Questionnaire be used for “assessing outcomes among breast augmentation patients, breast reconstruction patients, mastectomy patients, lumpectomy/breast-sparing surgery patients, breast reduction patients, and patients who have sustained trauma or injury to their breasts.” To draw such conclusions, one would ideally develop a questionnaire with input from all these various patient groups. Such input helps to generate questions that are most relevant and important to the targeted patients. In addition, the questions should take into consideration the patients’ perspectives using language that they understand. Unfortunately, the authors do not report on the development of the Breast Evaluation Questionnaire, so we do not know which patients’ concerns are represented in their instrument or if the concerns were derived from surgeons rather than the patients themselves. An alternate but less optimal approach would be to examine how the Breast Evaluation Questionnaire performs in these diverse patient groups. The current study, however, addresses the validity of the Breast Evaluation Questionnaire only among breast augmentation patients; it does not provide support for the validity of the measure among other patient groups. It is important to adopt the optimal approach for measuring patient satisfaction and quality of life in cosmetic and reconstructive breast surgery patients, so that new studies will have a meaningful basis from which to compare surgical results. We need to ensure that the evidence that we use to make these comparisons is of the highest possible quality. This requires use of not only good study design but also good measurement tools (i.e., questionnaires). Patient-reported outcome questionnaires should ideally undergo full development and validation, as outlined by the Scientific Advisory Committee of the Medical Outcomes Trust5 and most recently by the U.S. Food and Drug Administration.6 To adequately demonstrate the benefits of cosmetic and reconstructive breast surgery, future research is needed to rigorously develop and validate new procedure-specific questionnaires.7 Such new measures will provide surgeons with important tools to support research efforts, clinical practice improvement, and advocacy. Andrea L. Pusic, M.D., M.H.S. Memorial Sloan-Kettering Cancer Center New York, N.Y. Anne Klassen, Ph.D. University of British Columbia Vancouver, British Columbia, Canada Stefan J. Cano, Ph.D. Institute of Neurology University College London London, United Kingdom Carolyn L. Kerrigan, M.D. Dartmouth Hitchcock Medical Center Lebanon, N.H.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.519
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.026
GPT teacher head0.261
Teacher spread0.235 · 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 teacher head, not a consensus.

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

Citations17
Published2007
Admission routes2
Has abstractyes

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