Prognostic nomogram for cancer-specific survival in adenosquamous carcinoma of lung patients treated with chemotherapy: A SEER-based retrospective cohort study
Year: 2026
Type: article
Study design: Observational Study
Abstract: This study aims to establish a prognostic nomogram among adenosquamous carcinoma of lung (ASC) patients who received chemotherapy. A total of 704 ASC patients who received chemotherapy were extracted from the Surveillance, Epidemiology, and End Results database. Patients were randomly divided into a training (n = 493) and a validation (n = 211) cohort. Cancer-specific survival (CSS) was the primary endpoint of this study. First, independent prognostic predictors of CSS identified from univariate and multivariate Cox regression analyses were used to construct a prognostic nomogram for predicting 1-, 3-, and 5-year CSS in those patients. Then, calibration curves and receiver operating characteristic curves were used to evaluate the nomogram's prediction accuracy, while decision curve analysis was used to evaluate the nomogram's clinical utility. Finally, a mortality risk stratification system was constructed for this subpopulation. Eight clinical parameters were identified as independent prognostic factors for ASC patients who received chemotherapy, including age, household income, T stage, N stage, bone metastasis, brain metastasis, surgery, and the primary site of the tumor. The calibration curves, receiver operating characteristic, and decision curve analysis showed that the nomogram had excellent discrimination and clinical value. Moreover, the mortality risk stratification system could effectively divide all patients into 3 risk subgroups and achieve targeted patient management. Based on the Surveillance, Epidemiology, and End Results database, a novel prognostic nomogram for predicting 1-, 3-, and 5-year CSS in patients with ASC that underwent chemotherapy has been constructed and validated. The nomogram showed relatively good performance, which could be used in clinical practice to assist clinicians in individualized treatment strategies.
Source: Medicine
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $1,950
OpenAlex ID: W7128766873
