ArticlePlastic and reconstructive surgery2019
Introducing BREAST-Q Computerized Adaptive Testing: Short and Individualized Patient-Reported Outcome Assessment following Reconstructive Breast Surgery.
Article in Plastic and reconstructive surgery, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Machine learning in the development and application of patient-reported outcome measures (PROMs) for surgical patients: a systematic review.Journal of patient-reported outcomes · 2026Pooled it
- Patient-Reported Outcome Measures for Post-mastectomy Breast Reconstruction: A Systematic Review of Development and Measurement Properties.Annals of surgical oncology · 2021Pooled it
- Article
- Key considerations to reduce or address respondent burden in patient-reported outcome (PRO) data collection.Nature communications · 2022Review
- BREAST-Q REACT: Clinical Reference Values for the BREAST-Q in Post-mastectomy Breast Reconstruction Patients.Annals of surgical oncology · 2022Article
- Maximizing the Potential of Patient-Reported Assessments by Using the Open-Source Concerto Platform With Computerized Adaptive Testing and Machine Learning.Journal of medical Internet research · 2020Article
- Registering Study Analysis Plans (SAPs) Before Dissecting Your Data-Updating and Standardizing Outcome Modeling.Frontiers in oncology · 2020Article
- Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
backgroundThe BREAST-Q is a widely used patient-reported outcome instrument measuring health-related quality-of-life and patient satisfaction in breast surgery. Shorter assessment potentially increases patients' willingness to complete scales, but simply offering a shortened version leads to unacceptable loss in measurement precision. The authors aimed to develop a computerized adaptive test (CAT) to shorten the BREAST-Q's Satisfaction with Breasts scale while maintaining reliability of measurement.
methodsThe authors created a CAT, which repetitively administered questions from the pool of 16 questions, until prespecified levels of reliability were reached [i.e., standard errors (SE) of 0.32 to 0.55]. In a simulation study, the authors tested the CAT's feasibility for all potential satisfaction scores. In a second study using actual patient data, 5000 breast reconstruction patients who had previously completed the full scale were randomly selected from a large database. Their full-scale satisfaction scores were compared with their CAT-derived scores.
resultsIn both studies, by applying CAT, the Satisfaction with Breasts scale could be reduced to an average of 10 questions when using the minimum level of measurement precision for individual-patient measurement (SE, 0.32), compared with four questions when using the minimum precision level for group-based research (SE, 0.55). Score estimates were highly correlated between the CAT assessment and the full scale (0.91 to 0.98 in the simulation study, and 0.89 to 0.98 in the patient data study).
conclusionsApplying computerized adaptive testing to the BREAST-Q's Satisfaction with Breasts scale facilitates reliable assessment, with 38 to 75 percent fewer questions than the full version. The novel BREAST-Q CAT version may decrease response burden and help overcome barriers to implementation in routine care.
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