Lin Jielu, Marcum Christopher S, Myers Melanie F, Koehly Laura M
Social and Behavioral Research Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland.
Social and Behavioral Research Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland.
Am J Prev Med. 2017 May;52(5):640-644. doi: 10.1016/j.amepre.2016.11.018. Epub 2017 Jan 3.
An accurate family health history is essential for individual risk assessment. This study uses a multiple-informant approach to examine whether family members have consistent perceptions of shared familial risk for four common chronic conditions (heart disease, Type 2 diabetes, high cholesterol, and hypertension) and whether accounting for inconsistency in family health history reports leads to more accurate risk assessment.
In 2012-2013, individual and family health histories were collected from 127 adult informants of 45 families in the Greater Cincinnati Area. Pedigrees were linked within each family to assess inter-informant (in)consistency regarding common biological family member's health history. An adjusted risk assessment based on pooled pedigrees of multiple informants was evaluated to determine whether it could more accurately identify individuals affected by common chronic conditions, using self-reported disease diagnoses as a validation criterion. Analysis was completed in 2015-2016.
Inter-informant consistency in family health history reports was 54% for heart disease, 61% for Type 2 diabetes, 43% for high cholesterol, and 41% for hypertension. Compared with the unadjusted risk assessment, the adjusted risk assessment correctly identified an additional 7%-13% of the individuals who had been diagnosed, with a ≤2% increase in cases that were predicted to be at risk but had not been diagnosed.
Considerable inconsistency exists in individual knowledge of their family health history. Accounting for such inconsistency can, nevertheless, lead to a more accurate genetic risk assessment tool. A multiple-informant approach is potentially powerful when coupled with technology to support clinical decisions.
准确的家族健康史对于个体风险评估至关重要。本研究采用多信息源方法，以考察家庭成员对于四种常见慢性病（心脏病、2型糖尿病、高胆固醇和高血压）的家族共同风险是否具有一致的认知，以及考虑家族健康史报告中的不一致性是否能带来更准确的风险评估。
2012年至2013年，从大辛辛那提地区45个家庭的127名成年信息提供者处收集了个人和家族健康史。在每个家庭内部将家谱联系起来，以评估信息提供者之间关于共同生物学家庭成员健康史的（不）一致性。基于多个信息提供者汇总的家谱进行调整后的风险评估，以自我报告的疾病诊断作为验证标准，来确定其是否能更准确地识别受常见慢性病影响的个体。分析于2015年至2016年完成。
家族健康史报告中，信息提供者之间关于心脏病的一致性为54%，2型糖尿病为61%，高胆固醇为43%，高血压为41%。与未调整的风险评估相比，调整后的风险评估正确识别出另外7%-13%已被诊断的个体，而预测有风险但未被诊断的病例增加了≤2%。
个体对其家族健康史的了解存在相当大的不一致性。然而，考虑到这种不一致性可以产生更准确的遗传风险评估工具。当多信息源方法与支持临床决策的技术相结合时，可能会发挥强大作用。
