Abstract
BackgroundThe current World Health Organization classification recognises 12 major subtypes of renal cell carcinoma (RCC). Although these subtypes differ on molecular and clinical levels, they are generally managed as the same disease, simply because they occur in the same organ. Specifically, there is a paucity of tools to risk-stratify patients with papillary RCC (PRCC). The purpose of this study was to develop and evaluate a tool to risk-stratify patients with clinically non-metastatic PRCC following curative surgery.MethodsWe studied clinicopathological variables and outcomes of 556 patients, who underwent full resection of sporadic, unilateral, non-metastatic (T1–4, N0–1, M0) PRCC at five institutions. Based on multivariable Fine-Gray competing risks regression models, we developed a prognostic scoring system to predict disease recurrence. This was further evaluated in the 150 PRCC patients recruited to the ASSURE trial. We compared the discrimination, calibration and decision-curve clinical net benefit against the Tumour, Node, Metastasis (TNM) stage group, University of California Integrated Staging System (UISS) and the 2018 Leibovich prognostic groups.ResultsWe developed the VENUSS score from significant variables on multivariable analysis, which were the presence of VEnous tumour thrombus, NUclear grade, Size, T and N Stage. We created three risk groups based on the VENUSS score, with a 5-year cumulative incidence of recurrence equalling 2.9% in low-risk, 15.4% in intermediate-risk and 54.5% in high-risk patients. 91.7% of low-risk patients had oligometastatic recurrent disease, compared to 16.7% of intermediate-risk and 40.0% of high-risk patients. Discrimination, calibration and clinical net benefit from VENUSS appeared to be superior to UISS, TNM and Leibovich prognostic groups.ConclusionsWe developed and tested a prognostic model for patients with clinically non-metastatic PRCC, which is based on routine pathological variables. This model may be superior to standard models and could be used for tailoring postoperative surveillance and defining inclusion for prospective adjuvant clinical trials.
Highlights
The current World Health Organization classification recognises 12 major subtypes of renal cell carcinoma (RCC)
RCC subtypes differ on molecular and clinical levels, they are generally managed as the same disease, because they occur in the same organ and due to the fact that there is little data on the efficacy of available treatment options
TNM has been supplemented by several additional independent prognostic factors such as grade and coagulative tumour necrosis [10, 11]; these prognostic models were often established for clear cell RCC only [12, 13] or all RCC subtypes [14, 15], disregarding the considerable proportion of patients with papillary RCC (PRCC)
Summary
The current World Health Organization classification recognises 12 major subtypes of renal cell carcinoma (RCC) These subtypes differ on molecular and clinical levels, they are generally managed as the same disease, because they occur in the same organ. The 2016 World Health Organization classification recognises 12 major subtypes of renal cell carcinoma (RCC) with distinct morphologic, molecular and clinical features [1]. It appears likely that patients at a higher risk for tumour recurrence are most in need of effective adjuvant therapies and should be included in adjuvant trials [8] In this regard, TNM stage has traditionally been used to establish the risk of tumour recurrence for all RCC subtypes, but has limited accuracy when used alone [9]. We develop and evaluate a prognostic model for non-metastatic PRCC following curative surgery
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