Acute hematologic toxicity of radiation therapy - a comprehensive analysis and predictive nomogram
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Updated: Jul 16, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Kazuya Takeda1,2, Rei Umezawa1, Takaya Yamamoto1
1Department of Radiation Oncology, Tohoku University Graduate School of Medicine, 1-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi 980-8574, Japan.
Abstract:
To investigate radiation-induced cytopenia and establish predictive nomograms for hematological toxicity, we reviewed 3786 patients aged 18 or older who received radiation monotherapy between 2010 and 2021 for non-hematologic malignancies. We collected data on patient background, treatment content and hematologic toxicities for 12 weeks after the start of radiotherapy. The patients were randomly divided into training and test groups in 7:3 ratio. In the training group, we conducted ordered logistic regression analysis to identify predictive factors for neutropenia, lymphocytopenia, anemia and thrombocytopenia. Nomograms to predict Grade 2-4 cytopenia were generated and validated in the test group. Grade 3 or higher hematologic toxicities were observed in 9.7, 44.6, 8.3 and 3.1% of patients with neutropenia, lymphocytopenia, anemia and thrombocytopenia, respectively. We identified six factors for neutropenia grade, nine for lymphocytopenia grade and six for anemia grade with statistical significance. In the analysis of thrombocytopenia, the statistical model did not converge because of a small number of events. Nomograms were generated using factors with high predictive power. In evaluating the nomograms, we found high area under the receiver operating characteristic curve values (neutropenia; 0.75-0.85, lymphopenia; 0.89-0.91 and anemia; 0.85-0.86) in predicting Grade 2-4 cytopenia in the test group. We established predictive nomograms for neutropenia, leukocytopenia and anemia and demonstrated high reproducibility when validated in an independent cohort of patients.
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