Abstract
Background The optimal tool for predicting the survival of renal cell carcinoma (RCC) patients with lung metastases remains controversial. Methods We selected patients diagnosed with RCC and lung metastases, from 2010 to 2015, from the Surveillance, Epidemiology, and End Results (SEER) database. After the selection of inclusion criteria and exclusion criterion, the rest of the patients were incorporated into model analysis. Least absolute shrinkage and selection operator (LASSO) regression was used to select the most important features for construction of a nomogram predicting cancer-specific survival. A calibration plot and the concordance index (C-index) were used to estimate nomogram efficacy in a validation cohort. The association between important factors selected by LASSO regression, and prognosis was assessed by the Kaplan-Meier (KM) survival curve. The receiver operating characteristic (ROC) curves were drawn to compare sensitivity and specificity between the nomogram we built and the TNM stage-based model. Results A total of 1,369 patients met the inclusion criteria, but not the exclusion criteria. The LASSO regression model reduced 15 features to seven potential predictors of survival, including tumor grade, the extent of surgery, N and T status, histological profile, and brain and bone metastasis status. Such features had good discrimination in the KM survival curves. The nomogram showed excellent discriminatory power (C-index, 0.71; 95% confidence interval: 0.70 to 0.72) and good calibration in terms of both 1- and 2-year cancer-specific survival. The nomogram showed great discriminatory power (C-index 0.68) and adequate calibration when applied to the validation cohort. The areas under the curve (AUCs) of nomogram were 0.767 and 0.780, respectively, and the AUCs of TNM stage were 0.617 and 0.618 at 1 and 2 years, respectively. Conclusions Our nomogram might play a major role in predicting the cancer-specific survival of RCC patients with lung metastases.
Highlights
Renal cell carcinoma (RCC), a common malignant tumor, accounts for 3.7% of all new tumor cases; renal cell carcinoma (RCC) is more common in male than female patients, and there are 116,000 deaths annually according to the World Health Organization
The median age of both cohorts was 60 years, where RCC is more common in the elder
Nomogram AUC = 0.780 TNM stage AUC = 0.618 (a) metastatic sites including the lung, mediastinum, bone, and liver into consideration, and the results showed that only the lung metastasis was not associated with overall survival [19]
Summary
Renal cell carcinoma (RCC), a common malignant tumor, accounts for 3.7% of all new tumor cases; RCC is more common in male than female patients, and there are 116,000 deaths annually according to the World Health Organization. The optimal tool for predicting the survival of renal cell carcinoma (RCC) patients with lung metastases remains controversial. Least absolute shrinkage and selection operator (LASSO) regression was used to select the most important features for construction of a nomogram predicting cancer-specific survival. The LASSO regression model reduced 15 features to seven potential predictors of survival, including tumor grade, the extent of surgery, N and T status, histological profile, and brain and bone metastasis status. Such features had good discrimination in the KM survival curves. Our nomogram might play a major role in predicting the cancer-specific survival of RCC patients with lung metastases
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