Dataset Information

Survival Analysis and Prediction Model for Pulmonary Sarcomatoid Carcinoma Based on SEER Database.

ABSTRACT:

Objective

This study aimed to investigate the incidence of the pulmonary sarcomatoid carcinoma (PSC), to compare the clinical characteristics and overall survival (OS) of patients with PSC and those with other non-small-cell lung cancer (oNSCLC), so as to analyze the factors affecting the OS of patients with PSC and construct a nomogram prediction model.

Methods

Data of patients with PSC and those with oNSCLC diagnosed between 2004 and 2015 from the Surveillance, Epidemiology, and End Results database were collected. The age-adjusted incidence of PSC was calculated. The characteristics of patients with PSC and those with oNSCLC were compared, then the patients were matched 1:2 for further survival analysis. Patients with PSC were randomly divided into training set and testing set with a ratio of 7:3. The Cox proportional hazards model was used to identify the covariates associated with the OS. Significant covariates were used to construct the nomogram, and the C-index was calculated to measure the discrimination ability. The accuracy of the nomogram was compared with the tumor-node-metastasis (TNM) clinical stage, and the corresponding area under the curve was achieved.

Results

A total of 1049 patients with PSC were enrolled, the incidence of PSC was slowly decreased from 0.120/100,000 in 2004 to 0.092/100,000 in 2015. Before PSM, 793 PSC patients and 191356 oNSCLC patients were identified, the proportion of male, younger patients (<65 years), grade IV, TNM clinical stage IV was higher in the PSC. The patients with PSC had significantly poorer OS compared with those with oNSCLC. After PSM, PSC still had an extremely inferior prognosis. Age, sex, TNM clinical stage, chemotherapy, radiotherapy, and surgery were independent factors for OS. Next, a nomogram was established based on these factors, and the C-indexs were 0.775 and 0.790 for the training and testing set, respectively. Moreover, the nomogram model indicated a more comprehensive and accurate prediction than the TNM clinical stage.

Conclusions

The incidence of PSC was slowly decreased. PSC had a significantly poor prognosis compared with oNSCLC. The nomogram constructed in this study accurately predicted the prognosis of PSC, performed better than the TNM clinical stage.

SUBMITTER: Chen M

PROVIDER: S-EPMC8201495 | biostudies-literature |

REPOSITORIES: biostudies-literature

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