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Updated: Oct 5, 2026

Database-guided Flow-cytometry for Evaluation of Bone Marrow Myeloid Cell Maturation
Published on: November 3, 2018
Dynamic white blood cell kinetics enable early risk stratification of differentiation syndrome in low- and
Jiajuan Ji1, Yuting Zhu1, Dan Luo1
1Department of Hematology, The First Affiliated Hospital of Harbin Medical University, Harbin, China.
Background:
Differentiation syndrome (DS) is a potentially life-threatening complication during induction therapy for acute promyelocytic leukemia (APL). Previous studies have linked white blood cell (WBC) elevation with DS development; however, conventional WBC-based assessment mainly relies on peak values and does not adequately reflect the dynamic pattern or timing of WBC changes. We aimed to develop and internally validate an early warning model for DS based on early WBC kinetics during arsenic trioxide (ATO) induction therapy in patients with low- and intermediate-risk APL.
Methods:
We retrospectively analyzed 224 newly diagnosed patients with low- and intermediate-risk APL who received single-agent ATO induction therapy. Early WBC kinetics and baseline clinical parameters were analyzed using least absolute shrinkage and selection operator regression and multivariate logistic regression to construct a nomogram.
Results:
DS occurred in 90 patients (40.2%), with a median onset time of 8 days (interquartile range, 7-11 days). WBC doubling occurred at a median of 3 days before DS onset, whereas the WBC peak occurred at a median of 2.5 days after DS onset. Rapid WBC proliferation and increased peripheral blood promyelocyte percentage were independent risk factors, whereas prolonged WBC doubling time was associated with reduced DS risk. The nomogram showed good discrimination, with an area under the curve of 0.825 (95% confidence interval, 0.770-0.880); the corrected area under the curve remained 0.817 after bootstrap internal validation.
Conclusion:
Early WBC kinetic characteristics provide time-sensitive indicators for DS risk assessment. This model may assist with early DS risk stratification and monitoring in low- and intermediate-risk APL patients.
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