Personalized laboratory medicine in the digital health era: recent developments and future challenges.

Interpretation of laboratory data is a comparative procedure and requires reliable reference data, which are mostly derived from population data but used for individuals in conventional laboratory medicine. Using population data as a "reference" for individuals has generated several problems related to diagnosing, monitoring, and treating single individuals. This issue can be resolved by using data from individuals' repeated samples, as their personal reference, thus needing that laboratory data be personalized. The modern laboratory information system (LIS) can store the results of repeated measurements from millions of individuals. These data can then be analyzed to generate a variety of personalized reference data sets for numerous comparisons. In this manuscript, we redefine the term "personalized laboratory medicine" as the practices based on individual-specific samples and data. These reflect their unique biological characteristics, encompassing omics data, clinical chemistry, endocrinology, hematology, coagulation, and within-person biological variation of all laboratory data. It also includes information about individuals' health behavior, chronotypes, and all statistical algorithms used to make precise decisions. This approach facilitates more accurate diagnosis, monitoring, and treatment of diseases for each individual. Furthermore, we explore recent advancements and future challenges of personalized laboratory medicine in the context of the digital health era.

Improved testing for vitamin B12 deficiency: correcting MMA for eGFR reduces the number of patients classified as vitamin B12 deficient.

Background Methylmalonic acid (MMA) can detect functional vitamin B12 deficiencies as it accumulates early when intracellular deficits arise. However, impaired clearance of MMA from blood due to decreased glomerular filtration rate (eGFR) also results in elevated plasma MMA concentrations. Alternative to clinical trials, a data mining approach was chosen to quantify and compensate for the effect of decreased eGFR on MMA concentration. Methods Comprehensive data on patient's vitamin B12, eGFR and MMA concentrations were collected ( n = 2906). The relationship between vitamin B12, renal function (eGFR) and MMA was modelled using weighted multiple linear regression. The obtained model was used to estimate the influence of decreased eGFR on MMA. Clinical impact was examined by comparing the number of patients labelled vitamin B12 deficient with and without adjustment in MMA. Results Adjusting measured MMA concentrations for eGFR in the group of patients with low-normal vitamin B12 concentrations (90-300 pmol/L) showed that the use of unadjusted MMA concentrations overestimates vitamin B12 deficiency by 40%. Conclusions Through a data mining approach, the influence of eGFR on the relation between MMA and vitamin B12 can be quantified and used to correct the measured MMA concentration for decreased eGFR. Especially in the elderly, eGFR-based correction of MMA may prevent over-diagnosis of vitamin B12 deficiency and corresponding treatment.