{"title":"Combined total error in calculated clinical chemistry tests: component analytical error is magnified and decision threshold gray zones widen.","authors":"Alper Gümüş","doi":"10.1093/labmed/lmag068","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Calculated tests propagate component analytical errors, yet laboratories monitor only the measured components, rarely the calculated quantity.</p><p><strong>Methods: </strong>Using analytical performance specifications (APSs) from the European Federation of Clinical Chemistry and Laboratory Medicine Biological Variation Database, we propagated bias and imprecision through 5 calculated tests (low-density lipoprotein cholesterol [LDL-C], anion gap, albumin-corrected calcium, the Homeostatic Model Assessment of Insulin Resistance [HOMA-IR], and the De Ritis ratio), representing difference, linear correction, product, and ratio structures. Difference-based and linear-based tests were assessed across clinical scenarios; the ratio was validated by Monte Carlo simulation.</p><p><strong>Results: </strong>At desirable component APSs, the combined total error was 2.1% to 2.8% for albumin-corrected calcium, 25.9% for the De Ritis ratio, and 34% for the HOMA-IR. At typical values, combined errors for LDL-C and the anion gap were 18.5% and 20.8%, respectively, exceeding their respective allowable total error targets (12.0% and 11.3%). Error was concentration dependent: the anion-gap error decreased to 7.4% at 28 mmol/L but increased to 43.0% at 6 mmol/L; the LDL-C error reached 28.6% at 60 mg/dL. The allowable total error-based estimate closely matched the quadrature-bias estimate but underestimated worst-case error.</p><p><strong>Discussion: </strong>Acceptable component performance does not ensure acceptable performance of calculated tests. Derived quantities require specific APSs, and results near clinical decision limits should be interpreted within concentration-dependent analytical gray zones.</p>","PeriodicalId":94124,"journal":{"name":"Laboratory medicine","volume":"57 5","pages":""},"PeriodicalIF":1.0000,"publicationDate":"2026-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Laboratory medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/labmed/lmag068","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: Calculated tests propagate component analytical errors, yet laboratories monitor only the measured components, rarely the calculated quantity.
Methods: Using analytical performance specifications (APSs) from the European Federation of Clinical Chemistry and Laboratory Medicine Biological Variation Database, we propagated bias and imprecision through 5 calculated tests (low-density lipoprotein cholesterol [LDL-C], anion gap, albumin-corrected calcium, the Homeostatic Model Assessment of Insulin Resistance [HOMA-IR], and the De Ritis ratio), representing difference, linear correction, product, and ratio structures. Difference-based and linear-based tests were assessed across clinical scenarios; the ratio was validated by Monte Carlo simulation.
Results: At desirable component APSs, the combined total error was 2.1% to 2.8% for albumin-corrected calcium, 25.9% for the De Ritis ratio, and 34% for the HOMA-IR. At typical values, combined errors for LDL-C and the anion gap were 18.5% and 20.8%, respectively, exceeding their respective allowable total error targets (12.0% and 11.3%). Error was concentration dependent: the anion-gap error decreased to 7.4% at 28 mmol/L but increased to 43.0% at 6 mmol/L; the LDL-C error reached 28.6% at 60 mg/dL. The allowable total error-based estimate closely matched the quadrature-bias estimate but underestimated worst-case error.
Discussion: Acceptable component performance does not ensure acceptable performance of calculated tests. Derived quantities require specific APSs, and results near clinical decision limits should be interpreted within concentration-dependent analytical gray zones.