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Crew KD, Bhatkhande G, Silverman T, Amenta J, Jones T, McGuinness JE, Mata J, Guzman A, He T, Dimond J, Tsai WY, Kukafka R. Patient and Provider Web-Based Decision Support for Breast Cancer Chemoprevention: A Randomized Controlled Trial. Cancer Prev Res (Phila) 2022; 15:689-700. [PMID: 35679576 PMCID: PMC9532364 DOI: 10.1158/1940-6207.capr-22-0013] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 05/09/2022] [Accepted: 06/06/2022] [Indexed: 11/16/2022]
Abstract
Significant underutilization of breast cancer chemoprevention remains, despite guidelines stating that physicians should recommend chemoprevention with antiestrogen therapy to high-risk women. We randomized women, ages 35 to 75 years, who met high-risk criteria for breast cancer, without a personal history of breast cancer or prior chemoprevention use, to standard educational materials alone or combined with a web-based decision aid. All healthcare providers, including primary care providers and breast specialists, were given access to a web-based decision support tool. The primary endpoint was chemoprevention uptake at 6 months. Secondary outcomes included decision antecedents (perceived breast cancer risk/worry, chemoprevention knowledge, self-efficacy) and decision quality (decision conflict, chemoprevention informed choice) based upon patient surveys administered at baseline, 1 and 6 months after randomization. Among 282 evaluable high-risk women enrolled from November 2016 to March 2020, mean age was 57 years (SD, 9.9) and mean 5-year invasive breast cancer risk was 2.98% (SD, 1.42). There was no significant difference in chemoprevention uptake at 6 months between the intervention and control groups (2.1% vs. 3.5%). Comparing the intervention and control arms at 1 month, there were significant differences among high-risk women in accurate breast cancer risk perceptions (56% vs. 39%, P = 0.017), adequate chemoprevention knowledge (49% vs. 27%, P < 0.001), mean decision conflict (34.0 vs. 47.0, P < 0.001), and informed choice (41% vs. 23%, P = 0.003). These differences were no longer significant at 6 months. Although our decision support tools did not result in a significant increase in chemoprevention uptake, we did observe improvements in decision antecedents and decision quality measures. PREVENTION RELEVANCE In this randomized controlled trial of decision support for 300 high-risk women and 50 healthcare providers, we did not observe a significant increase in chemoprevention uptake, which remained low at under 5%. However, these decision support tools may increase knowledge and informed choice about breast cancer chemoprevention.
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Affiliation(s)
- Katherine D. Crew
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY
- Department of Epidemiology, Mailman School of Public Health, Columbia University Irving Medical Center, New York, NY
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY
| | - Gauri Bhatkhande
- Department of Epidemiology, Mailman School of Public Health, Columbia University Irving Medical Center, New York, NY
| | - Thomas Silverman
- Department of Biomedical Informatics, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY
| | - Jacquelyn Amenta
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY
| | - Tarsha Jones
- Christine E. Lynn College of Nursing, Florida Atlantic University, Boca Raton, FL
| | - Julia E. McGuinness
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY
| | - Jennie Mata
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY
| | - Ashlee Guzman
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY
| | - Ting He
- Department of Biomedical Informatics and Data Sciences, Johns Hopkins University, Baltimore, MD
| | | | - Wei-Yann Tsai
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY
- Department of Biostatistics, Mailman School of Public Health, Columbia University Irving Medical Center, New York, NY
| | - Rita Kukafka
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY
- Department of Biomedical Informatics, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, NY
- Department of Sociomedical Sciences, Mailman School of Public Health, Columbia University Irving Medical Center, New York, NY
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