ArticleFrontiers in immunology2024
A comprehensive nomogram for assessing the prognosis of non-small cell lung cancer patients receiving immunotherapy: a prospective cohort study in China.
Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prognostic Impact of Body Mass index in Lung Cancer Patients Receiving Immune Checkpoint Inhibitors: An Updated Systematic Review and Meta-Analysis.Technology in cancer research & treatmentPooled it
- The Prognostic Value of Serum Inflammatory Markers in Nasopharyngeal Carcinoma Patients Treated With Immune Checkpoint Inhibitors: A Multicenter Study.Cancer medicine · 2026Article
- Systemic inflammatory indices as accessible biomarkers for intracranial outcome and prognosis in driver gene-negative NSCLC with brain metastases treated with first-line chemoimmunotherapy.Discover oncology · 2026Article
- A Cytokine-Related Gene Signature for Pan-Cancer Prognostic Stratification and Malignant Phenotype Characterization.International journal of molecular sciences · 2026Article
- Application of deep learning in prognostic prediction of non-small cell lung cancer.Frontiers in cell and developmental biology · 2026Review
- Development and validation of a nomogram for predicting axillary reverse mapping lymph node metastasis in breast cancer patients.Frontiers in oncology · 2026Article
- Establishment of a nomogram based on Lasso Cox regression for albumin combined with systemic immune-inflammation index score to predict prognosis in advanced pancreatic carcinoma.Frontiers in oncology · 2025Article
- Development and validation of a nomogram for predicting immune-related thyroid dysfunction during immunotherapy in non-small cell lung cancer: a prospective cohort study in China.Frontiers in immunology · 2025Article
- Development and validation of a novel nomogram for predicting outcomes in advanced lung cancer patients treated beyond progression with immune checkpoint inhibitors.Frontiers in immunology · 2025Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: In China, lung cancer ranks first in both incidence and mortality among all malignant tumors. Non-small cell lung cancer (NSCLC) constitutes the vast majority of cases, accounting for 80% to 85% of cases. Immune checkpoint inhibitors (ICIs), either as monotherapies or combined with other treatments, have become the standard first-line therapy for NSCLC patients. This study aimed to establish a nomogram model for NSCLC patients receiving immunotherapy incorporating demographic information, clinical characteristics, and laboratory indicators. Methods: From January 1, 2019, to December 31, 2022, a prospective longitudinal cohort study involving 1321 patients with NSCLC undergoing immunotherapy was conducted at Chongqing University Cancer Hospital. Clinical and pathological characteristics, as well as follow-up data, were collected and analyzed. To explore prognostic factors affecting overall survival (OS), a Cox regression model was used to test the significance of various variables. Independent prognostic indicators were identified through multivariate analysis and then used to construct a nomogram prediction model. To validate the accuracy and practicality of this model, the concordance index (C-index), area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA) were used to assess the predictive performance of the nomogram. Result: In the final model, 11 variables from the training cohort were identified as independent risk factors for patients with NSCLC: age, KPS score, BMI, diabetes, targeted therapy, Hb, WBC, LDH, CRP, PLR, and LMR. The C-index for OS in the training cohort was 0.717 (95% CI, 0.689-0.745) and 0.704 (95% CI, 0.660-0.750) in the validation cohort. Calibration curves for survival probability showed good concordance between the nomogram predictions and actual observations. The AUCs for 1-year, 2-year, and 3-year OS in the training cohort were 0.724, 0.764, and 0.79, respectively, and 0.725, 0.736, and 0.818 in the validation cohort. DCA demonstrated that the nomogram model had a greater overall net benefit. Conclusion: A prognostic model for OS in NSCLC patients receiving immunotherapy was established, providing a simple and reliable tool for predicting patient survival (https://icisnsclc.shinyapps.io/DynNomapp/). This model offers valuable guidance for clinicians in making treatment decisions and recommendations.
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