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Record W2332457988 · doi:10.1097/prs.0000000000000267

Interpreting Clinical Differences in BREAST-Q Scores

2014· article· en· W2332457988 on OpenAlexaffabout
Stefan Cano, Anne F. Klassen, Amie Scott, Amy K. Alderman, Andrea L. Pusic

Bibliographic record

VenuePlastic & Reconstructive Surgery · 2014
Typearticle
Languageen
FieldMedicine
TopicBreast Implant and Reconstruction
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicinePsychosocialBreast augmentationMinimal clinically important differenceQuality of life (healthcare)Breast surgeryStandard deviationBreast cancerPhysical therapyStatisticsGynecologySurgeryRandomized controlled trialInternal medicinePsychiatryCancer

Abstract

fetched live from OpenAlex

Sir: The BREAST-Q is a multiscale, multimodule, patient-reported outcome instrument measuring important aspects of health-related quality of life and patient satisfaction in women who undergo breast surgery.1 Its subscales have undergone extensive psychometric evaluation,2 including examinations of clinical change.3 However, to date, no minimal important difference statistics have been published. These statistics are especially important for power calculations in clinical research and therapeutic trials.4 Thus, here we present distribution-based minimal important differences (i.e., values relating to one-half of the baseline standard deviation in subscale scores, and effect sizes of 0.5)5 for the subscales that compose the BREAST-Q Augmentation Module. These minimal important difference statistics were derived from data collected within a longitudinal study of 245 women undergoing cosmetic breast augmentation. The women in this study completed the BREAST-Q before surgery and again 6 weeks and 6 months after surgery (further information is available from the authors). Table 1 shows the statistics related to the clinical change in BREAST-Q scores. Of importance, the last two columns of Table 1 show the mean minimal important differences based on a 0.5 SD and 0.5 effect size for each of the module’s subscales. Taking the most conservative value in each instance, the mean minimal important difference equates to the following (BREAST-Q Augmentation Module): satisfaction with breasts, 8 (range, 7 to 8); psychosocial well-being, 10 (range, 8 to 11); sexual well-being, 10 (range, 9 to 10); and physical well-being, 7 (range, 2 to 11).Table 1: BREAST-Q Subscale Mean Scores (Measurements), Standard Deviations, Effect Sizes, and Minimal Important Difference (n = 213–216)*One of the key clinical benefits of using Rasch Measurement Theory methods to develop the BREAST-Q is that we have a good understanding of the empirical item order across each subscale.2 Thus, the items (representing important clinical issues) that are associated with every possible subscale score (or measurement) are known. This benefit means that we are able to link the items directly to minimal important differences. For example, based on the BREAST-Q Augmentation Module satisfaction with breasts subscale, Figure 1 and Table 2 show three simulated example scenarios that illustrate change scores: the first not exceeding a minimal important difference (from 61 to 67; red line); the second exceeding 1 minimal important difference (from 70 to 79; blue line); and the third exceeding 2 minimal important difference values (from 40 to 61). Specifically, the scores can be translated into key issues as described by the BREAST-Q. Thus, women who move from a score of 61 to 67 go from being satisfied with the “position” and proximity of their breasts when not wearing a bra and “how their bras fit,” to being very satisfied with the “size,” “firmness,” and how “natural” their breasts appear. However, as described, this improvement in score does not exceed the minimal important difference. Women who change from a score of 70 to a 79 move from being very satisfied with “cleavage,” how “natural” their breasts are, and “how they appear in the mirror clothed” to being very satisfied with the proximity, feeling of the breasts, and “how they appear in the mirror unclothed.” This improvement signifies a minimal important difference at the high end of this subscale. Finally, at the lower end of the scale, moving from a 40 to a 61 (over double the minimal important difference) is associated with the difference between being dissatisfied with the “shape” of the breast, how the breast size “matches” the rest of their body, and “how bras fit” to being satisfied with the “position” and proximity of their breasts when not wearing a bra and “how their bras fit.”Table 2: BREAST-Q Augmentation Module Satisfaction with Breasts SubscaleFig. 1: BREAST-Q Augmentation Module satisfaction with breasts subscale. Three examples of change scores signifying less than a minimal important difference (red line), exceeding 1 minimal important difference (blue line), and exceeding 2 minimal important differences (green line).As we have previously proposed, the ability to provide qualitative statements to subscale scores, and now link these to important differences in scores, begins to provide a solid foundation for the clinical interpretation of the BREAST-Q.2 Interpretability is the cornerstone to successful use of patient-reported outcome instruments in individual clinical care, comparative effectiveness research, and regulator efforts.4 DISCLOSURE The BREAST-Q is jointly owned by the Memorial Sloan-Kettering Cancer Center and the University of British Columbia. Stefan J. Cano, Ph.D., Anne F. Klassen, D.Phil., and Andrea L. Pusic, M.D., M.H.S., are co-developers of the BREAST-Q and, as such, receive a share of any license revenues based on the inventor sharing policies of these two institutions. The BREAST-Q is provided free of charge for academic research and use in clinical practice by health care providers with individual patients. The scoring software, Q-Score, is also offered free of charge to all BREAST-Q users. The BREAST-Q is available at www.BREAST-Q.org. Stefan J. Cano, Ph.D. Clinical Neurology Research Group Plymouth University Peninsula School of Medicine and Dentistry Plymouth, United Kingdom Anne F. Klassen, D.Phil. Faculty of Health Sciences McMaster University Hamilton, Ontario, Canada Amie Scott, M.P.H. Plastic and Reconstructive Surgery Memorial Sloan-Kettering Cancer Center New York, N.Y. Amy Alderman, M.D., M.P.H. Swan Center for Plastic Surgery Atlanta, Ga. Andrea L. Pusic, M.D., M.H.S. Plastic and Reconstructive Surgery Memorial Sloan-Kettering Cancer Center New York, N.Y.

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)0.053
metaresearch head score (Gemma)0.238
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.053
Threshold uncertainty score0.278

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0530.238
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0000.002
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.030
GPT teacher head0.278
Teacher spread0.248 · 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 designNot applicable
Domainnot available
GenreMethods

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".

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Citations54
Published2014
Admission routes2
Has abstractyes

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