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针对历史上服务不足人群的遗传性癌症风险评估数字工具:一项随机对照试验

Digital tool for genetic cancer risk assessment in a historically underserved population: a randomized controlled trial.

作者信息

Webster Emily M, Ahsan Muhammad Danyal, Chandler Isabelle R, Primiano Michelle, Mcdougale Auja, Howard Denise, Fishman David, Rosenberg Shoshana M, Chapman-Davis Eloise, Levi Sarah, Grant Benjamin, Bull Leslie E, Christos Paul, Sharaf Ravi N, Frey Melissa K

机构信息

Department of Obstetrics and Gynecology, Weill Cornell Medicine, New York, NY, USA; Genetics and Personalized Cancer Prevention Program, Weill Cornell Medicine, New York, NY, USA.

Department of Obstetrics and Gynecology, Weill Cornell Medicine, New York, NY, USA; Genetics and Personalized Cancer Prevention Program, Weill Cornell Medicine, New York, NY, USA.

出版信息

Am J Obstet Gynecol. 2025 Mar 27. doi: 10.1016/j.ajog.2025.03.026.

Abstract

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.

摘要

背景

在美国,高达95%携带癌症易感种系致病变异的个体仍未被识别,尤其是在历史上服务不足的人群中。

目的

在这项双臂随机对照试验中,我们比较了通过数字工具进行风险评估与临床医生常规访谈时,识别出的高危患者比例以及被推荐进行遗传性癌症综合征基因检测的情况。

研究设计

城市学术诊所的新妇科患者按1:1随机分为数字风险分层工具组或临床医生主导的常规访谈组,以进行遗传风险评估。基因检测的资格由美国国立综合癌症网络制定的标准确定。主要结局是识别出的高危患者比例以及被推荐进行遗传性癌症综合征基因检测的情况。次要结局是基因检测的完成情况以及对患者因素的探索,包括健康的社会决定因素。

结果

2023年1月至12月,100名患者参与了该研究;51名患者被随机分配通过数字工具进行遗传性癌症风险评估,49名患者通过临床医生常规访谈进行评估。39名(39%)患者自我认定为西班牙裔,23名(23%)为非西班牙裔白人,20名(-20%)为非西班牙裔黑人,11名(11%)为亚洲人,2名(2%)为混血儿,5名(5%)不愿回答。大多数患者拥有医疗补助保险(68名;68%),32名(32%)报告家庭收入低于40,000美元。在干预组中,44名(86%)患者完成了数字工具评估。研究人员将21名(21%)患者确定为高危且符合基因检测标准(干预组:8名;对照组:13名)。使用遗传性癌症风险评估工具与识别出高危患者并推荐其进行基因检测的可能性更高相关(7名[88%]对2名[15%];P = 0.002)。在高危患者中,干预组有4名(50%)、对照组有2名(15%)进行了遗传性癌症基因检测(P = 0.146)。在干预组中,健康社会决定因素并未影响数字工具的使用。

结论

在历史上服务不足的人群中,使用数字遗传性癌症风险分层工具可增加对高危患者的识别,并为被识别出且被推荐进行基因检测的患者提供咨询。数字风险分层工具的整合可能有助于减少基因服务利用方面的差异。

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