BackgroundSerum iron, an essential component of hemoglobin (Hb) synthesis in vivo, is a crucial parameter for evaluating the body's iron storage and metabolism capacity. Iron deficiency leads to reduced Hb synthesis in red blood cells and smaller red blood cell volume, ultimately resulting in iron‐deficiency anemia. Although serum iron cannot independently evaluate iron storage or metabolism ability, it can reflect iron concentration in vivo and serve as a good predictor of iron‐deficiency anemia. Therefore, exploring the influence of different serum iron levels on anemia and diagnosing and treating iron deficiency in the early stages is of great significance for patients with lung cancer.AimThis study aims to explore the related factors of cancer‐related anemia (CRA) in lung cancer and construct a nomogram prediction model to evaluate the risk of CRA in patients with different serum iron levels.MethodsA single‐center retrospective cohort study was conducted, including 1610 patients with lung cancer, of whom 1040 had CRA. The relationship between CRA and its influencing factors was analyzed using multiple linear regression models. Lung cancer patients were divided into two groups according to their serum iron levels: decreased serum iron and normal serum iron. Each group was randomly divided into a training cohort and a validation cohort at a ratio of 7:3. The influencing factors were screened by univariate and multivariate logistic regression analyses, and nomogram models were constructed. The area under the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to evaluate the models.ResultsCRA in lung cancer is mainly related to surgery, chemotherapy, Karnofsky Performance Status (KPS) score, serum iron, C‐reactive protein (CRP), albumin, and total cholesterol (p < 0.05). CRA in lung cancer patients with decreased serum iron is primarily associated with albumin, age, and cancer staging, while CRA in lung cancer patients with normal serum iron is mainly related to CRP, albumin, total cholesterol, and cancer staging. The area under the ROC curve of the training cohort and validation cohort for the prediction model of lung cancer patients with decreased serum iron was 0.758 and 0.760, respectively. Similarly, the area under the ROC curve of the training cohort and validation cohort for the prediction model of lung cancer patients with normal serum iron was 0.715 and 0.730, respectively. The calibration curves of both prediction models were around the ideal 45° line, suggesting good discrimination and calibration. DCA showed that the nomograms had good clinical utility.ConclusionBoth models have good reliability and validity and have significant clinical value. They can help doctors better assess the risk of developing CRA in lung cancer patients. CRP is a risk factor for CRA in lung cancer patients with normal serum iron but not in patients with decreased serum iron. Therefore, whether CRP and the inflammatory state represented by CRP will further aggravate the decrease in serum iron levels, thus contributing to anemia, warrants further study.