背景:家庭健康史(FHx)是识别有遗传性癌症风险的患者的有效工具。遗传性癌症临床实践指南(CPG)包含用于评估FHx并为遗传咨询提出建议的标准。比较用于评估一组通用FHx的不同CPG,可以深入了解CPG的性能,跨准则的协议程度,以及他们如何确定应该考虑癌症遗传咨询的患者。
方法:我们比较了美国医学遗传学和基因组学学院(ACMG)和国家综合癌症网络(NCCN)(2019)FHx的CPG标准,该标准由聊天机器人收集,并通过本体和网络服务进行评估。收集的FHx符合七个组的标准:基因突变,乳房和卵巢,Li-Fraumeni综合征(LFS),结直肠和子宫内膜,相对符合标准,仅限ACMG标准,NCCN测试。CPG标准在12个ACMG子指南和6个NCCN子指南中进行编码和匹配,以进行比较。
结果:数据集包含4915条记录,其中2221符合ACMG或NCCN标准,2694不符合。存在明显的重叠-1179先证者符合ACMG和NCCN标准。最大的相似性是基因突变和乳腺和卵巢标准,结肠直肠和子宫内膜标准之间存在最大的差异。仅报告了156个阳性基因突变,其中2694个先证者不符合标准,90.6%的患者报告其个人或家族癌症病史中至少有一种癌症。
结论:遗传性癌症CPGs可用于基于FHx识别有癌症发展风险的患者。这个比较表明,在聊天机器人的帮助下,本体论,和Web服务,CPG可以更有效地应用于识别有遗传性癌症风险的患者。此外,该比较检查了ACMG和NCCN之间的相似性和差异,并显示了在评估遗传性癌症风险时使用这两种指南的重要性。
BACKGROUND: Family health history (FHx) is an effective tool for identifying patients at risk of hereditary cancer. Hereditary cancer clinical practice
guidelines (CPG) contain criteria used to evaluate FHx and to make recommendations for genetic consultation. Comparing different CPGs used to evaluate a common set of FHx provides insight into how well the CPGs perform, the extent of agreement across
guidelines, and how well they identify patients who should consider a cancer genetic consultation.
METHODS: We compare the American College of Medical Genetics and Genomics (ACMG) and the National Comprehensive Cancer Networks (NCCN) (2019) CPG criteria for FHx collected by a chatbot and evaluated by ontologies and web services in a previous study. Collected FHx met criteria from seven groups: Gene Mutation, Breast and Ovarian, Li-Fraumeni syndrome (LFS), Colorectal and Endometrial, Relative Meets Criteria, ACMG Only Criteria, and NCCN Testing. CPG Criteria were coded and matched across 12 ACMG sub-
guidelines and 6 NCCN sub-
guidelines for comparison purposes.
RESULTS: The dataset contains 4915 records, of which 2221 met either ACMG or NCCN criteria and 2694 did not. There was significant overlap-1179 probands met both ACMG and NCCN criteria. The greatest similarities were for Gene Mutation and Breast and Ovarian criteria and the greatest disparity existed among Colorectal and Endometrial criteria. Only 156 positive gene mutations were reported and of the 2694 probands who did not meet criteria, 90.6% of them reported at least one cancer in their personal or family cancer history.
CONCLUSIONS: Hereditary cancer CPGs are useful for identifying patients at risk of developing cancer based on FHx. This comparison shows that with the aid of chatbots, ontologies, and web services, CPGs can be more efficiently applied to identify patients at risk of hereditary cancer. Additionally this comparison examines similarities and differences between ACMG and NCCN and shows the importance of using both
guidelines when evaluating hereditary cancer risk.