Biological variation of CA 15-3, CA 125 and HE 4 on lithium heparinate plasma in apparently healthy Caucasian volunteers.

OBJECTIVES: Tumor markers are well-known for being important tools in the support of diagnosis, monitoring of treatment efficacy and follow-up of cancers. CA 125, CA 15-3 and HE 4 have demonstrated potential efficacy in other clinical indications. The main objective was to evaluate the biological variation of these glycoproteins using two different immunoassays in an apparently healthy Caucasian population. METHODS: Nineteen healthy volunteers including 11 women and 8 men were sampled weekly for 5 consecutive weeks. Samples were analyzed in duplicate on Lumipulse® G600II (Fujirebio) and on the Cobas e602 (Roche Diagnostics) analyzers. After assessment of normality, exclusion of outliers and analysis of homogeneity of variance, analytical variation (CVA), within-subject biological variation (CVI) and between-subject biological variation (CVG) were determined using a nested ANOVA. RESULTS: CVA, CVI and CVG were determined on both analyzers and both genders. For CA 125, the CVA ranges from 1.0 to 3.4%, the CVI from 5.7 to 13.8% and the CVG from 32.2 to 42.9%. For CA 15-3, the CVA is between 1.1 and 3.4%, the CVI between 3.9 and 6.5% and the CVG between 43.7 and 196.9%. Lastly, HE 4 has CVA values between 1.4 and 2.4%, CVI between 5.1 and 10.5% and CVG between 7.1 and 12.6%. CONCLUSIONS: Our study provided updated data on the biological variation of CA 125, HE 4 and CA 15-3. These data allow to improve the clinical interpretation and thus the management of the patient.

Biological investigations of transfusion reactions: Contribution of symptom-based decisional algorithms.

OBJECTIVES: While transfusion is a common and safe therapeutic procedure in health care facilities, transfusion reactions can occur, whether acute or delayed, mild or life-threatening. In face of these reactions, the biological analysis laboratory plays a central role in their diagnosis. The objective of this article is to develop decisional algorithms for laboratory tests to be performed according to the clinical symptoms developed by the patient during or after transfusion. METHODS: Based on the information collected by reviewing the literature and the procedures used in our hospital, we then developed biological investigation algorithms according to the symptoms presented by the patient, rather than the presumed reaction. RESULTS AND CONCLUSION: We have developed symptom-based algorithms for acute transfusion reactions management that streamline laboratory testing and simplify the differential diagnosis.

A biological profile for diagnosis and outcome of COVID-19 patients.

Objectives As severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) pandemic is increasing its victims on a global scale with recurring outbreaks, it remains of outmost importance to rapidly identify people requiring an intensive care unit (ICU) hospitalization. The aim of this study was to identify Coronavirus Disease 2019 (COVID-19) biomarkers, to investigate their correlation with disease severity and to evaluate their usefulness for follow-up. Methods Fifty patients diagnosed with SARS-Cov-2 were included in March 2020. Clinical and biological data were collected at admission, during hospitalization and one month after discharge. Patients were divided into two severity groups: non-ICU (28) and ICU and/or death (22) to stratify the risk. Results Blood parameters in COVID-19 patients at admission showed increased C-reactive protein (CRP) (100%), ferritin (92%), lactate dehydrogenase (LDH) (80%), white blood cell (WBC) count (26%) with lymphopenia (52%) and eosinopenia (98%). There were significant differences in levels of CRP, ferritin, D-dimers, fibrinogen, lymphocyte count, neutrophil count and neutrophil-to-lymphocyte ratio (NLR) among the two severity groups. Mapping of biomarker's kinetics distinguished early and late parameters. CRP, ferritin, LDH, lymphopenia and eosinopenia were present upon admission with a peak at the first week. Late biomarkers such as anemia, neutrophilia and elevated liver biomarkers appeared after one week with a peak at three weeks of hospitalization. Conclusions We confirmed that high-values of CRP, NLR, D-dimers, ferritin as well as lymphopenia and eosinopenia were consistently found and are good markers for risk stratification. Kinetics of these biomarkers correlate well with COVID-19 severity. Close monitoring of early and late biomarkers is crucial in the management of critical patients to avoid preventable deaths.