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Journal of Tuberculosis and Lung Disease  2026, Vol. 7 Issue (5): 615-623    DOI: 10.19983/j.issn.2096-8493.20262040

• Original Articles • Previous Articles     Next Articles

Construction and validation of a risk prediction model for severe myelosuppression in lung cancer patients undergoing chemotherapy

Liu Suling1, Chen Hua2, Ding Wenping1, Wang Fan1()   

  1. 1 State Key Laboratory of Respiratory Disease, Guangzhou Medical University Institute of Tuberculosis/Guangzhou Chest Hospital Affiliated to Guangdong Pharmaceutical University/Pulmonary Nodule Diagnosis and Treatment Center, Guangzhou 510095, China
    2 State Key Laboratory of Respiratory Disease, Guangzhou Medical University Institute of Tuberculosis/Department of Nontuberculous Mycobacterial Diseases, Guangzhou Chest Hospital Affiliated to Guangdong Pharmaceutical University, Guangzhou 510095, China
  • Received:2026-03-06 Online:2026-10-20 Published:2026-10-19
  • Contact: Wang Fan E-mail:414679388@qq.com
  • Supported by:
    General Guiding Project of Guangzhou Health Science and Technology(20241A010036)

Abstract:

Objective: To explore the risk factors associated with severe myelosuppression in lung cancer patients receiving chemotherapy and to develop a risk prediction model for severe myelosuppression in these patients. Methods: A retrospective analysis was performed on the relevant data of 145 lung cancer patients who experienced myelosuppression following chemotherapy during their hospitalization at Guangzhou Chest Hospital from September 2023 to December 2024.The risk factors contributing to severe myelosuppression were systematically analyzed. Results: Among 145 lung cancer patients with myelosuppression following chemotherapy, 48 cases (33.1%) developed severe myelosuppression. Spearman correlation analysis revealed that severe myelosuppression was significantly positively correlated with the history of pulmonary surgery and platinum-containing chemotherapy regimens, and was negatively correlated with body mass index (BMI), chemotherapy cycles, pre-chemotherapy red blood cell count, hemoglobin level, platelet count, serum albumin level, and gamma-glutamyl transferase. Multivariate regression analysis showed that noninitial chemotherapy was a protective factor against severe myelosuppression in patients with lung cancer undergoing chemotherapy (OR=0.069,95%CI:0.019-0.246), while decreased serum albumin level (OR=10.789,95%CI:4.012-29.015) and history of pulmonary surgery (OR=3.193,95%CI:1.173-8.695) were independent risk factors for severe myelosuppression in these patients. A logistic regression model was established and the predictive efficacy of the model was verified via the area under the ROC curve, which was 0.839 (95% confidence interval (CI): (0.775-0.903) of the final model, with the maximum Youden index 0.566, the sensitivity 81.3%, and the specificity 75.3%. Conclusion: This model exhibits excellent predictive performance and can serve as a valuable reference for clinical treatment and nursing interventions to prevent severe myelosuppression.

Key words: Lung neoplasms, Drug therapy, Bone marrow, Serum albumin, Forecasting

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