Digital tool for genetic cancer risk assessment in a historically underserved population: a randomized controlled
Emily M Webster1, Muhammad Danyal Ahsan1, Isabelle R Chandler1
1Department of Obstetrics and Gynecology, Weill Cornell Medicine, New York, NY, USA; Genetics and Personalized Cancer Prevention Program, Weill Cornell Medicine, New York, NY, USA.
Background:
Up to 95% of individuals with cancer-predisposing germline pathogenic variants in the U.S. remain unidentified, particularly among historically underserved populations.
Objective:
In this 2-arm randomized controlled trial, we compared the proportion of high-risk patients identified and recommended for hereditary cancer syndrome genetic testing when risk assessment was performed by a digital tool vs usual clinician interview.
Study Design:
New gynecology patients at an urban academic clinic were randomized 1:1 to either a digital risk stratification tool or usual clinician-driven interview for genetic risk assessment. Eligibility for genetic testing was determined by criteria set forth by the National Comprehensive Cancer Network. The primary outcome was the proportion of high-risk patients identified and recommended for hereditary cancer syndrome genetic testing. The secondary outcomes were completion of genetic testing and exploration of patient factors including social determinants of health.
Results:
From January to December 2023, 100 patients enrolled in the study; 51 were randomized to genetic cancer risk assessment via digital tool and 49 via usual clinician interview. Thirty-nine (39%) patients self-identified as Hispanic, 23 (23%) as non-Hispanic White, 20 (20%) as non-Hispanic Black, 11 (11%) as Asian, 2 (2%) as mixed race, and 5 (5%) preferred not to answer. Most patients had Medicaid insurance (68; 68%), and 32 (32%) reported having a household income of less than $40,000. In the intervention arm, 44 (86%) completed the digital tool. Twenty-one (21%) patients were identified by study personnel as high-risk and met criteria for genetic testing (intervention: 8; control: 13). Use of the genetic cancer risk assessment tool was associated with a higher likelihood of high-risk patients being identified and recommended for genetic testing (7 [88%] vs 2 [15%]; P=.002). Among high-risk patients, 4 (50%) in the intervention arm and 2 (15%) in the control arm proceeded with genetic testing for hereditary cancers (P=.146). Within the intervention arm, social determinants of health did not impact use of the digital tool.
Conclusion:
In a historically underserved population, the use of a digital genetic cancer risk stratification tool led to increased identification and counseling high-risk patients identified and recommended for genetic testing. The integration of a digital risk stratification tool may work toward mitigating disparities in utilization of genetic services.
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