Ontology highlight
ABSTRACT:
Method: Objective measures and panel assessment were undertaken independently for 3D-SI of women who underwent BCT 1-5 years previously. Univariate analysis was used to test for association between measures and panel score. A forward stepwise multiple linear regression model was fitted to identify 3D measurements that jointly predicted the mean panel score. The fitted model coefficients were used to predict mean panel scores for an independent validation set then compared to the mean observed panel score.
Results: Very good intra-panel reliability was observed for the training and validation sets (w??=?0.87, w??=?0.84). Six 3D-measures were used in the multivariate model. There was a good correlation between the predicted and mean observed panel score in the training (n?=?190) and validation (n?=?100) sets (r?=?0.68, r?=?0.65). The 3D model tended to predict scores towards the median. The model was calibrated which improved the distribution of predicted scores.
Conclusion: A six-variable objective aesthetic outcome model for BCT has been described and validated. This can predict and could replace panel assessment, facilitating the independent and unbiased evaluation of aesthetic outcome to communicate and compare results, benchmark practice, and raise standards.
SUBMITTER: Godden AR
PROVIDER: S-EPMC7717038 | biostudies-literature | 2020 Nov
REPOSITORIES: biostudies-literature
Godden Amy R AR O'Connell Rachel L RL Barry Peter A PA Krupa Katherine C D KCD Wolf Lisa M LM Mohammed Kabir K Kirby Anna M AM Rusby Jennifer E JE
Breast cancer (Tokyo, Japan) 20200619 6
<h4>Background</h4>Two-thirds of patients with early breast cancer undergo breast-conserving treatment (BCT). Aesthetic outcome is important and has long term implications for psychosocial wellbeing. The aesthetic goal of BCT is symmetry for which there is no gold-standard measure. Panel scoring is the most widely adopted assessment but has well-described limitations. This paper describes a model to objectively report aesthetic outcome using measures derived from 3-dimensional surface images (3D ...[more]