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Updated: Oct 1, 2025

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Establishing a prognostic model for metachronous second squamous cell lung cancer in patients with resected squamous
Shen-Shen Fu1, Yu-Zhen Zheng2, Xian-Yu Qin2
1Department of Ultrasonography, Guangzhou First People's Hospital, The Second Affiliated Hospital of South China University of Technology, Guangzhou, China.
Background:
For metachronous second pulmonary squamous cell carcinoma (msPSC) in patients with resected PSC, the method to distinguish tumour clonality has not yet been well established, which makes it difficult to determine accurate staging and predict prognosis.
Methods:
Patients who underwent surgery for first PSC and encountered msPSC were recruited from the Surveillance, Epidemiology, and End Results (SEER) database. We extracted overall survival 1 (OS1) for the first PSC, overall survival 2 (OS2) for msPSC, and interval survival for the time interval between the first and second PSC. The nomogram was calibrated for OS2, and recursive partitioning analysis (RPA) was performed for risk stratification.
Results:
A total of 617 patients were identified. Several independent prognostic factors were identified and integrated into the nomogram for OS2, including gender, age (2nd), nodal status (1st), node metastasis (2nd), and extrapulmonary metastasis (2nd). The calibration curves showed optimal agreement between the predictions and actual observations, and the c-index was 0.678. Surgery was associated with longer survival for msPSC patients. The prognosis of sublobectomy was comparable and inferior to that of lobectomy in the low- and moderate-risk groups, respectively. Radiotherapy was associated with better outcomes in patients who did not undergo surgery.
Conclusions:
The RPA-based clinical nomogram appears to be suitable for the prognostic prediction and risk stratification of OS2 in msPSC. This practical system may help clinicians make decisions and design clinical studies.

