Construction and validation of prognostic nomograms for elderly patients with metastatic non-small cell lung cancer

Nomogram predicting overall survival of stage IIIB non-small-cell lung cancer patients based on the SEER database

PURPOSE

We aimed to evaluate the prognostic value of stage IIIB non-small-cell (NSCLC) lung cancer patients and to construct a nomogram to effectively predict their overall survival (OS).

METHODS

In total, 4323 patients with stage IIIB NSCLC diagnosed between 1975 and 2018 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Multiple prognostic factors were combined to construct a nomogram for predicting OS of patients with stage IIIB NSCLC. The discrimination and calibration of the nomogram were evaluated by C-indexes and calibration curves. The nomogram was evaluated for predictive ability using receiver operating characteristic (ROC) curves, decision curve analysis curve (DCA), and clinical impact curve (CIC).

RESULTS

The nomogram was built on data of 4323 patients with stage IIIB NSCLC and consisted of the following prognostic factors: age, race, sex, primary labeled, pathology, T stage, whether to receive surgery, whether to receive radiotherapy, and whether to receive chemotherapy. The C-index in the training and validation sets for the nomogram was 0.672 (95% CI: 0.661-0.683) and 0.675 (95% CI: 0.656-0.694), respectively. According to scores of the nomogram, patients in the complete set, validation set, and training set were classified into two risk groups, low risk and high risk.

CONCLUSIONS

We developed the first validated nomogram to estimate the OS of patients with stage IIIB NSCLC. The nomogram was based on nine prognostic factors and provided an individualized risk estimate of 3-year and 5-year OS survival in patients with stage IIIB NSCLC.

Development and Validation of Prognostic Nomograms for Lung Squamous Cell Carcinoma With Brain Metastasis in Patients Aged 45 Years or Older: A Population-Based Study

PURPOSE

We aimed to establish nomograms to predict the survival in patients aged ≥45  years with lung squamous cell carcinoma and brain metastasis.

METHODS

We collected patients diagnosed as lung squamous cell carcinoma with brain metastasis aged ≥45 years between 2010 and 2019 from the Surveillance, Epidemiology, and End Results database. Prognostic factors were determined by the univariate and multivariate Cox regression analysis, and then the nomogram was constructed to predict cancer-specific survival and overall survival. Nomograms were evaluated by decision curve analysis, the area under the receiver operating characteristic curve, calibration plot, concordance index, and risk group stratification.

RESULTS

In total, 2437 patients were included, with 1706 and 731 in the cohorts of training and validation, respectively. The age, N stage, T stage, liver metastasis, chemotherapy, bone metastasis, along with radiotherapy were significant in predicting the survival, and adopted for the establishment of nomograms. In the training and validation sets, the concordance index were .713(95%CI:0.699-.728) & .700(95%CI:0.677-.722) in predicting cancer-specific survival and .715(95%CI:0.701-.729) & .712(95%CI:0.690-.735) in predicting overall survival, respectively. Besides, the area under the receiver operating characteristic curve for predicting cancer-specific survival and overall survival in the training set were all >.7 at 1-, 2-, and 3- years. Calibration plots proved the survival predicted by nomograms were consistent with the actual values. decision curve analysis revealed better clinical validity of the nomogram in predicting cancer-specific survival and overall survival at 1-year than TNM staging. Patients were stratified into the high-/low-risk groups according to the optimal cutoff value of 100.21 for cancer-specific survival and 91.98 for overall survival. A web-based probability calculator was constructed finally.

CONCLUSION

Two nomograms were developed for the prognostic prediction of lung squamous cell carcinoma patients with brain metastasis aged ≥45 years, providing guidance for decision-making in clinical practice.

A Population-Based Study on the Prognostic factors and Efficacy of Adjuvant Chemotherapy in the Postoperative Stage for Patients with Stage IIA Non-Small Cell Lung Cancer

Objective

This study aimed to design a nomogram survival prediction by means of the figures retrieved from the Surveillance, Epidemiology, and End Results (SEER) source bank, and to predict the overall survival (OS) of patients with stage IIA non-small cell lung cancer (NSCLC) after surgery.

Methods

Data for 4511 patients who had been diagnosed with postoperative stage IIA NSCLC were collected from the SEER databank, while information on 528 patients was acquired from the Chongqing University Cancer Hospital for the external validation cohort. The independent risk factors that affected the prognosis were identified using a multivariate Cox proportional hazards regression model (also used to conduct a nomogram). A survival analysis between the low- and the high-risk groups was performed using the Kaplan-Meier method. Furthermore, a subgroup analysis was conducted of the two groups using the Kaplan-Meier method to determine whether the patients had received adjuvant chemotherapy.

Results

The following five variables were integrated into the nomogram: sex (female: HR 1.73, 95% CI 0.64-0.83), age (≥60: HR 1.61, 95% CI 1.39-1.87), differentiation grade (grade II: HR 2.19, 95% CI 1.66-2.88; grade III: HR 2.65, 95% CI 2.00-3.51; grade IV: HR 3.17, 95% CI 1.99-5.03), surgery (lobectomy: HR 0.72, 95% CI 0.59-0.86), and lymph node resection (>12: HR 0.82, 95% CI 0.70-0.96). Furthermore, the patients selected were categorized into high- and low-risk groups. The OS rate was significantly lower in the high-risk group than in the low-risk group (P < 0.001). Finally, adjuvant chemotherapy was highly correlated with OS in the high-risk set (P = 0.035); however, adjuvant chemotherapy was not related to OS in the low-risk set.

Conclusion

A nomogram was created as a reliable, convenient scheme that could predict OS, and it was determined that the high-risk feature patients identified by the nomogram gained benefits from adjuvant chemotherapy.