Red blood cell size differential method for time-series detailed monitoring of anemic disorders with RBC size abnormalities in mean corpuscular volume (MCV) and/or red blood cell distribution width (RDW)

Background: Size heterogeneity in red blood cells (RBCs), as indicated by elevated RBC distribution width (RDW), is increasingly considered a prognostic factor in various diseases. However, the semi-quantitative nature of the RDW value appears limited when evaluating quantitative changes in time-series RBC size distributions over a clinical course. Methods: We developed a time-series anemia monitoring program by displaying progressive differences between six size fractions in an RBC size distribution. To standardize each variation precisely, our program includes an angular transformation that is applied to all measured count ratio data. Results: By representing microcytic and/or macrocytic changes in time series independently, this method appears to improve evaluations of anisocytosis, reflecting the responsiveness of treatments and effects, such as deficiencies in iron or vitamin B12. Time-series displays of RBC size changes also appear to enable verification of latent clinical developments at earlier stages and the characterization of imbalances between RBC supply and RBC loss in anemic pathologies. Conclusions: By displaying linear relationships between RBC size categories on a time scale, our proposed *Corresponding author: Sunao Atogami, Department of Laboratory Medicine, Nagasaki University Graduate School of Biomedical Sciences, 1-7-1, Sakamoto, Nagasaki-shi, Nagasaki 852-8501, Japan; Department of Laboratory Medicine, Sasebo City General Hospital, 9-3, Hirase-cho, Sasebo-shi, Nagasaki 857-8511, Japan E-mail: [email protected]. nagasaki.jp Reviewing editor: Udo Schumacher, University Medical Center Hamburg-Eppendorf, Germany Additional information is available at the end of the article ABOUT THE AUTHORS Sunao Atogami’s interest in a parametric analysis method by flow cytometry-measured histograms in time series came from past research of DNA aneuploidy changes in adult T-cell leukemia cells, over the course of monitoring ATL patients under the direction of Nagasaki University professor Emeritus Shimeru Kamihira. His research currently focuses on applying the same parametric analysis to a monitoring method of anisocytosis or elevated RBC distribution width (RDW), a more common clinical finding which relates to the various pathogeneses of anemic disorders as apparent in time series. Charles de Kerckhove is a Mechanical Engineer keen to build on the Engineering approach and related distant memories of Statistics for a thorough understanding and communication of how to display hematological change in time series. Katsunori Yanagihara, professor at Nagasaki University and Head of the Nagasaki University Hospital Department of Laboratory Medicine, and Shimeru Kamihira are both supervisors of this study. PUBLIC INTEREST STATEMENT Flow cytometry count data, such as complete blood cell counts, have been widely used in clinical laboratories. We usually must use non-parametric statistical analysis to compare such cell count data, but quantitative evaluations employing some type of computed index from count data in time series can at times be necessary for making key clinical decisions. Therefore, we studied the characteristics of both precision and accuracy and the instability of uncertainty in count ratio variables for improved clarity in flow cytometry analysis. Through our proposed control of uncertainty propagation in computed indices from a hematology analyzer’s cell count data, we hope that our clinical evaluation method might contribute to an easy-to-visualize, programmable, and real-time detailed anemia interface. We also hope that our report’s case studies on tracking various types of anemia might indicate such a method’s potential applicability to routine medical care. Received: 01 September 2016 Accepted: 17 October 2016 First Published: 24 October 2016 © 2016 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.