Department of Biomedical Informatics, Harvard Medical School, Boston, MA.
Department of Medicine, Stanford University School of Medicine, Stanford, CA.
Clin Chem. 2021 Mar 1;67(3):500-507. doi: 10.1093/clinchem/hvaa271.
Physicians sometimes consider whether or not to perform diagnostic testing in healthy people, but it is unknown whether nonextreme values of diagnostic tests typically encountered in such populations have any predictive ability, in particular for risk of death. The goal of this study was to quantify the associations among population reference intervals of 152 common biomarkers with all-cause mortality in a representative, nondiseased sample of adults in the United States.
The study used an observational cohort derived from the National Health and Nutrition Examination Survey (NHANES), a representative sample of the United States population consisting of 6 survey waves from 1999 to 2010 with linked mortality data (unweighted N = 30 651) and a median followup of 6.1 years. We deployed an X-wide association study (XWAS) approach to systematically perform association testing of 152 diagnostic tests with all-cause mortality.
After controlling for multiple hypotheses, we found that the values within reference intervals (10-90th percentiles) of 20 common biomarkers used as diagnostic tests or clinical measures were associated with all-cause mortality, including serum albumin, red cell distribution width, serum alkaline phosphatase, and others after adjusting for age (linear and quadratic terms), sex, race, income, chronic illness, and prior-year healthcare utilization. All biomarkers combined, however, explained only an additional 0.8% of the variance of mortality risk. We found modest year-to-year changes, or changes in association from survey wave to survey wave from 1999 to 2010 in the association sizes of biomarkers.
Reference and nonoutlying variation in common biomarkers are consistently associated with mortality risk in the US population, but their additive contribution in explaining mortality risk is minor.
医生有时会考虑是否对健康人群进行诊断性检查，但目前尚不清楚人群中通常遇到的非极端诊断检测值是否具有预测能力，特别是对死亡风险的预测能力。本研究的目的是量化美国代表性非患病成年人人群中 152 种常见生物标志物的参考区间与全因死亡率之间的关联。
该研究使用了来自国家健康和营养检查调查（NHANES）的观察性队列，这是美国人口的代表性样本，由 1999 年至 2010 年的 6 个调查波组成，具有相关的死亡数据（未加权 N=30651），中位随访时间为 6.1 年。我们采用 X 广泛关联研究（XWAS）方法，系统地对 152 种诊断检测与全因死亡率进行关联检验。
在控制了多个假设后，我们发现，20 种常用的诊断检测或临床测量值的参考区间（10-90 百分位数）内的值与全因死亡率相关，包括血清白蛋白、红细胞分布宽度、血清碱性磷酸酶等，在调整年龄（线性和二次项）、性别、种族、收入、慢性疾病和前一年的医疗保健利用情况后。然而，所有生物标志物联合解释的死亡率风险变异仅增加了 0.8%。我们发现，生物标志物的关联大小在每年都有适度的变化，或者从 1999 年到 2010 年，从一个调查波到另一个调查波，关联都有变化。
常见生物标志物的参考值和非异常值变化与美国人群的死亡率风险始终相关，但它们在解释死亡率风险方面的附加贡献较小。
