ArticleScientific reports2023
A nomogram for predicting severe myelosuppression in small cell lung cancer patients following the first-line chemotherapy.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Machine learning-based prediction and external validation of treatment-related myelosuppression in patients with non-small cell lung cancer receiving PD-1 inhibitors plus platinum-doublet chemotherapy.Journal of thoracic disease · 2026Article
- Haematological toxicity associated with antineoplastic drugs: a pharmacovigilance analysis based on the FDA adverse event reporting system database.Frontiers in immunology · 2026Article
- Application value and safety of trilaciclib in first-line chemotherapy combined with immunotherapy for extensive-stage small cell lung cancer: A real-world study.Oncology letters · 2025Article
- Development of a nomogram for predicting the risk of carcinoma in chronic atrophic gastritis.Discover oncology · 2025Article
- Article
- Development and validation of a prediction model for myelosuppression in lung cancer patients after platinum-based doublet chemotherapy: a multifactorial analysis approach.American journal of cancer research · 2025Article
- Radiomics model based on vertebral calcium-suppressed CT images for predicting chemotherapy-induced myelosuppression in nasopharyngeal carcinoma.Frontiers in oncology · 2025Article
- Pegylated recombinant human granulocyte colony-stimulating factor enhances radiotherapy completion and safety in concurrent chemoradiotherapy for cervical cancer: a retrospective analysis.Frontiers in oncology · 2025Article
- Risk factors and nomogram to predict skip metastasis in papillary thyroid carcinoma.Gland surgery · 2024Article
- Developing and Validating a Risk Model for Severe Bone Marrow Suppression in Esophageal Cancer Treated with Radiotherapy or Chemoradiotherapy: A Retrospective Cohort Study.Technology in cancer research & treatmentArticle
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5 authors.
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Abstract
This study aimed at establishing and validating a nomogram to predict the probability of severe myelosuppression in small cell lung cancer (SCLC) patients following the first-line chemotherapy. A total of 179 SCLC cases were screened as the training group and another 124 patients were used for the validation group. Predictors were determined by the smallest Akaike's information criterion (AIC) in multivariate logistic regression analysis, leading to a new nomogram. The nomogram was validated in both training and validation groups and the predicting value was evaluated by area under the receiver operating characteristics (ROC) curve (AUC), calibration curve, and decision curve analysis (DCA). Age and tumor staging were extracted as predictors to establish a nomogram, which displayed the AUC values as 0.725 and 0.727 in the training and validation groups, respectively. This nomogram exhibited acceptable calibration curves in the two groups and its prediction added more net benefits than the treat-all scheme and treat-none scheme if the range of threshold probability in the DCA was between 15 and 60% in the training and validation groups. Therefore, the nomogram objectively and accurately predict the occurrence of severe myelosuppression in SCLC patients following the first-line chemotherapy.
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