Evidence map›Paper›PMID 30589822›Full record

ArticlePlastic and reconstructive surgery2019

Introducing BREAST-Q Computerized Adaptive Testing: Short and Individualized Patient-Reported Outcome Assessment following Reconstructive Breast Surgery.

Danny A Young-Afat, Christopher Gibbons, Anne F Klassen, Andrew J Vickers, Stefan J Cano, Andrea L Pusic

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Danny A Young-AfatFrom the University Medical Center Utrecht; Brigham and Women's Hospital; Harvard University; McMaster University; Memorial Sloan Kettering Cancer Center; and Modus Outcomes.
Christopher GibbonsFrom the University Medical Center Utrecht; Brigham and Women's Hospital; Harvard University; McMaster University; Memorial Sloan Kettering Cancer Center; and Modus Outcomes.
Anne F KlassenFrom the University Medical Center Utrecht; Brigham and Women's Hospital; Harvard University; McMaster University; Memorial Sloan Kettering Cancer Center; and Modus Outcomes.
Andrew J VickersFrom the University Medical Center Utrecht; Brigham and Women's Hospital; Harvard University; McMaster University; Memorial Sloan Kettering Cancer Center; and Modus Outcomes.
Stefan J CanoFrom the University Medical Center Utrecht; Brigham and Women's Hospital; Harvard University; McMaster University; Memorial Sloan Kettering Cancer Center; and Modus Outcomes.
Andrea L PusicFrom the University Medical Center Utrecht; Brigham and Women's Hospital; Harvard University; McMaster University; Memorial Sloan Kettering Cancer Center; and Modus Outcomes.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
NCI NIH HHS P30 CA008748
6 · The paper itself

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.

Indexed as

MammaplastyPatient Reported Outcome MeasuresPatient SatisfactionAdultAlgorithmsBreast NeoplasmsComputer SimulationFeasibility StudiesFemaleHumansMastectomyProspective StudiesPsychometricsQuality of LifeReproducibility of ResultsSoftware

Identifiers

PMID30589822
PMCPMC6713453

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.