Lumarie Santiago1, Robert J Volk2, Cristina M Checka3, Dalliah Black3, Joanna Lee4, Jessica S Colen3, Catherine Akay3, Abigail Caudle3, Henry Kuerer3, Elsa M Arribas1. 1. Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA. 2. Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA. 3. Department of Breast Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA. 4. Division of Surgical Oncology, UPMC Magee-Womens Hospital, Pittsburgh, Pennsylvania, USA.
Abstract
PURPOSE: To evaluate the acceptability and impact of 3D-printed breast models (3D-BMs) on treatment-related decisional conflict (DC) of breast cancer patients. METHODS: Patients with breast cancer were accrued in a prospective institutional review board-approved trial. All patients underwent contrast-enhanced breast magnetic resonance imaging (MRI). A personalized 3D-BM was derived from MRI. DC was evaluated pre- and post-3D-BM review. 3D-BM acceptability was assessed post-3D-BM review. RESULTS: DC surveys before and after 3D-BM review and 3D-BM acceptability surveys were completed by 25 patients. 3D-BM were generated in two patients with bilateral breast cancer. The mean patient age was 48.8 years (28-72). The tumor stage was Tis (7), 1 (8), 2 (8), and 3 (4). The nodal staging was 0 (19), 1 (7), and 3 (1). Tumors were unifocal (15), multifocal (8), or multicentric (4). Patients underwent mastectomy (13) and segmental mastectomy (14) with (20) or without (7) oncoplastic intervention. Neoadjuvant therapy was given to seven patients. Patients rated the acceptability of the 3D-BM as good/excellent in understanding their condition (24/24), understanding disease size (25/25), 3D-BM detail (22/25), understanding their surgical options (24/25), encouraging to ask questions (23/25), 3D-BM size (24/25), and impartial to surgical options (17/24). There was a significant reduction in the overall DC post-3D-BM review, indicating patients became more assured of their treatment choice (p = 0.002). Reduction post-3D-BM review was also observed in the uncertainty (p = 0.012), feeling informed about options (p = 0.005), clarity about values (p = 0.032), and effective (p = 0.002) Decisional Conflict Scale subscales. CONCLUSIONS: 3D-BMs are an acceptable tool to decrease DC in breast cancer patients.
PURPOSE: To evaluate the acceptability and impact of 3D-printed breast models (3D-BMs) on treatment-related decisional conflict (DC) of breast cancer patients. METHODS: Patients with breast cancer were accrued in a prospective institutional review board-approved trial. All patients underwent contrast-enhanced breast magnetic resonance imaging (MRI). A personalized 3D-BM was derived from MRI. DC was evaluated pre- and post-3D-BM review. 3D-BM acceptability was assessed post-3D-BM review. RESULTS: DC surveys before and after 3D-BM review and 3D-BM acceptability surveys were completed by 25 patients. 3D-BM were generated in two patients with bilateral breast cancer. The mean patient age was 48.8 years (28-72). The tumor stage was Tis (7), 1 (8), 2 (8), and 3 (4). The nodal staging was 0 (19), 1 (7), and 3 (1). Tumors were unifocal (15), multifocal (8), or multicentric (4). Patients underwent mastectomy (13) and segmental mastectomy (14) with (20) or without (7) oncoplastic intervention. Neoadjuvant therapy was given to seven patients. Patients rated the acceptability of the 3D-BM as good/excellent in understanding their condition (24/24), understanding disease size (25/25), 3D-BM detail (22/25), understanding their surgical options (24/25), encouraging to ask questions (23/25), 3D-BM size (24/25), and impartial to surgical options (17/24). There was a significant reduction in the overall DC post-3D-BM review, indicating patients became more assured of their treatment choice (p = 0.002). Reduction post-3D-BM review was also observed in the uncertainty (p = 0.012), feeling informed about options (p = 0.005), clarity about values (p = 0.032), and effective (p = 0.002) Decisional Conflict Scale subscales. CONCLUSIONS: 3D-BMs are an acceptable tool to decrease DC in breast cancer patients.
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