Development and Internal Validation of a Nomogram Used to Predict Chemotherapy-Induced Neutropenia in Non-Small Cell Lung Cancer Patients: A Retrospective Cohort Study
Authors Zou W, Xu NL
Received 26 January 2021
Accepted for publication 3 March 2021
Published 26 March 2021 Volume 2021:13 Pages 2797—2804
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Antonella D'Anneo
Wei Zou,1 Neng-Luan Xu2
1Shengli Clinical Medical College of Fujian Medical University, Fujian Medical University, Fuzhou, Fujian, People’s Republic of China; 2Department of Pulmonary and Critical Care Medicine, Fujian Provincial Hospital, Fuzhou, Fujian, People’s Republic of China
Correspondence: Neng-Luan Xu
Department of Pulmonary and Critical Care Medicine, Fujian Provincial Hospital, No. 134 Dong Street, Fuzhou, 350001 Fujian, People’s Republic of China
Tel +86 13805088136
Fax +86 0591-87557768
Email [email protected]
Purpose: This study was designed to develop a nomogram for predicting neutropenia caused by chemotherapy in non-small cell lung cancer (NSCLC) patients.
Patients and Methods: Information was collected from 376 patients between November 2017 and November 2020. The endpoint was chemotherapy-induced neutropenia (absolute neutrophil count < 2× 109/L). Logistic regression was performed to appraise the prognostic value of each potential predictor. Risk predictors from the final predictive model were used to generate a nomogram. C-index and calibration curve as well as decision curve analysis (DCA) was applied to evaluate model performance.
Results: The multivariate regression model ultimately included three predictors: previous radiotherapy, the current cycle of chemotherapy and neutrophil counts before current chemotherapy. A nomogram was developed and displayed better discrimination (with C-index of 0.875 in the development group and 0.907 in the validation group). Favorable consistency was shown between predicted probability and observed probability in the calibration curves. DCA illustrated that when the threshold probability was 8%-90%, the predictive model provided a net benefit relative to the intervention-all or the intervention-none strategy, indicating that the nomogram had favorable potential clinical utility.
Conclusion: This nomogram will be an available tool to quantify the risk of neutropenia after chemotherapy in patients who suffer from NSCLC and deserves further external validation.
Keywords: chemotherapy, neutropenia, nomograms, non-small cell lung cancer
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