Nomograms for predicting overall and cancer-specific survival in patients with papillary renal cell carcinoma: a population-based study using SEER database

Abstract

Background: To establish and validate nomograms for predicting the overall survival (OS) and cancerspecific survival (CSS) in patients with papillary renal cell carcinoma (pRCC). Methods: Patients diagnosed with pRCC between 2010 and 2014 in the Surveillance, Epidemiology, and End Results (SEER) database were retrospectively included in this study and divided into training and validation groups randomly. Uni-and multivariate Cox regression analyses were used to identify significant variables related to OS and CSS in the training group. Based on results of multivariate Cox regression analysis, nomograms for 3-and 5-year CSS and OS were established, respectively. Additionally, Kaplan-Meier (KM) survival curves were produced to learn the actual effects of different variables. Finally, the nomograms were evaluated both in the training group and the validation group using the area under the receiver operating characteristic (ROC) curve, the concordance index (C-index) and calibration curves. Results: A total of 4,859 eligible patients were enrolled, with 3,403 categorized into the training group and 1,456 into the validation group. Seven factors [age, T stage, N stage, M stage, use of surgery/lymph node removal (LNR) and insurance status] were significantly related to OS and seven factors (age, T stage, N stage, M stage and use of surgery/chemotherapy/LNR) were significantly associated with CSS. These factors were eventually included in the predictive nomograms. The C-indexes for OS in the training and validation groups were 0.764 and 0.723 respectively, and 0.859 and 0.824 for CSS. The 3-and 5-year AUCs for OS were 0.779 and 0.752 in the training cohort, and 0.749 and 0.722 in the validation cohort. Similarly, 3and 5-year AUCs for OS were 0.871 and 0.844 in the training cohort, and 0.853 and 0.822 in the validation group. Finally, the calibration curves suggested that the predictive nomograms had a good consistency between the observed and the predicted survival. Conclusions: It was the first time to develop nomograms to predict the survival outcomes of pRCC patients. The prognostic nomograms were reliable with high accuracy, which might have guiding significance for clinical practice.

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“…Through the incorporation of diverse prognostic factors, nomograms can determine the probability of a clinical event (e.g., OS or DFS) and thus predict the prognosis of a single patient. Nomograms are necessary in the era of individualized oncological therapy, and several nomograms have been published as adjuncts in prognostic determination in different types of cancer, such as CRC ( 45 ), renal cancer ( 46 ), NSCLC ( 47 ), and gastric cancer ( 48 ). Regarding the HNC, the nomograms have also been constructed to estimate the risk of developing major surgical complications in OSCC patients ( 49 ) and predict the recurrence-free probability in patients with parotid cancer ( 50 ).…”

Development and Validation of Nomograms to Predict Long-term Oncological Outcomes in Serous Ovarian Cancer

“…The advantage is that it can provide better individualized prognostic risk assessments in the form of intuitive graphics, which have de nite value in clinical practice and can provide a reference for individualized clinical decision-making. Thus, such predictive nomograms are widely used in clinical oncology [15][16][17]. All of the nomograms presented showed better discriminatory capacity than did classical staging systems.…”

Nomograms-based prediction of overall and cancer-specific survivals for patients with chromophobe renal cell carcinoma

“…13,14 Various nomogram models have been proposed for RCC, but most are for ccRCC or pRCC. [15][16][17][18] For chRCC prognosis prediction, Xie et al analyzed the relation between the clinical and pathological features of Chinese patients and patients' prognosis, and Luzzago et al explored the effect of tumor stage and grade on CSS of ccRCC and non-ccRCC patients. 19,20 However, there are no effective and reliable nomograms available to the prognostic prediction of chRCC patients.…”