ReviewCancers2026
Risk Stratification in Renal Cell Carcinoma: A Narrative Review.
Review in Cancers, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Renal cell carcinoma (RCC) accounts for the majority of kidney cancers, with approximately 80,000 new diagnoses and over 14,000 deaths annually in the United States. Risk stratification is essential for prognostication, treatment selection, and clinical trial design across all disease stages. In localized and locally advanced RCC, pathological stage, histology, and grade remain the primary prognostic factors, while the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) criteria serve as the standard risk stratification tool in the metastatic setting. However, current models rely predominantly on clinical and pathologic variables that act as indirect surrogates of tumor biology and do not account for the molecular heterogeneity inherent to RCC. This narrative review synthesizes and compares established and emerging risk stratification and prognostic models across all stages of RCC. Established models such as the IMDC criteria and the stage, size, grade, and necrosis (SSIGN) score demonstrate robust prognostic performance but are limited by their reliance on clinical and pathologic variables alone. Emerging biomarkers-including circulating tumor DNA, methylated DNA, artificial intelligence-based radiomics, and tissue-based molecular signatures-show promise for improving risk discrimination. The molecular heterogeneity of RCC underscores an urgent need for integrated molecular-clinical-pathologic prognostic tools tailored to specific histologic subtypes to enable more precise, individualized care.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.