PB2074 AUTOMATED EARLY DETECTION OF MYELODYSPLASIA WITH BECKMAN-COULTER DXH 800 HEMATOLOGY ANALYZER BY USING TEN RESEARCH PARAMETERS

Background: Moderate anemia affects a substantial fraction of the elderly population and blood smear analysis can help to guide towards a diagnosis of myelodysplasia (MDS). Nevertheless, in medical laboratories, review of blood smear is realized only if there is quantitative or qualitative flag on the complete blood count (CBC). Consequently, the suspicion of MDS could be delayed because of the absence of systematic blood smear triggering. The DxH 800 Hematology Analyzer measures and calculates 126 cytological parameters based on photometry, impedance or light scatter. These parameters regroup 23 standard CBC parameters and 103 unexploited “research parameters”. Aims: The goal of our study was to create an original mathematical model using “research parameters” to determine a suspicion score of MDS which triggers blood smear examination and consequently the process of identification of sub‐clinical patients suffering from MDS. Methods We compared the 126 parameters measured by the Beckman‐Coulter DxH 800 Hematology Analyzer from peripheral blood samples of MDS patients and healthy volunteers. MDS and healthy volunteers cohorts were composed of 101 MDS patients of the Tours university hospital of Tours and 88 aged matched subjects (ClinicalTrials.gov # NCT02789839 and # NCT02809222), respectively. Statistical analyses were performed using R studio version 1.0.153. The normal distribution of values was studied by Shapiro Wilk tests and the homoscedasticity by Levene tests. Means comparisons were performed by Wilcoxon and Student tests. Principal component analysis (PCA) was performed using FactoMine R. The logarithmic logistic regression was done thanks to the glm() function of the stats package. The general linear model was obtained by using logistic regression with weighted parameters and was validated by split sample strategy (10,000 repeats). Samples were divided into two groups (“learning” and “test” groups) randomly mixing MDS patients and healthy volunteers. The “learning” group (n = 130) allowed to build the model and the “test” group (n = 59) was used to validate it. Results: After monoparametric and multiparametric comparisons, 10 parameters were selected to establish the model of interest according to the best contributions at the first axe of PCA, the best correlations at two first axes of PCA and the most significant p values. In order to determine the Suspicion Score of MDS (SS‐MDS), the 10 selected parameters were weighted during split sampling strategy by logistic regression. After repeat of 10,000 split samples, SS‐MDS determined using weighted parameters was validated with average efficiency of 92.3%. For each parameter, the median of weighting coefficients was used in the mathematical model: “SS‐MDS = ΣCi.Pi + intercept” with “Ci: weighting coefficient of parameter i” and “Pi: parameter i value”. On the whole cohort, SSMDS induced “MDS” flag for 11 MDS patients for which conventional CBC algorithms failed to generate flag spreading peripheral blood smear. By fixing the threshold at 1.5, the sensitivity and specificity of SS‐MDS were 100% and 92%, respectively. Moreover, the positive and negative predictive values were 93.5% and 100%, respectively. Summary/Conclusion: The incidence of MDS increases with aging and the early diagnosis enables optimal care of these diseases. The Beckman Coulter DxH 800 Hematology Analyzer is widely used over the world. We propose in this study the clinical use of 10 unexploited “research parameters” to early detect subclinical MDS by selective triggering of blood smear examination. A prospective/multicentric study will allow the optimization of SS‐MDS. image