ArticleNPJ digital medicine2025
A multimodal AI model for precision prognosis in clear cell renal cell carcinoma: A multicenter study.
Article in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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Who cites it
2 citing papers in PubMed.
- Article
- A deep learning-based multimodal model with automated body composition analysis predicts prognosis in advanced clear cell renal cell carcinoma.Scientific reports · 2026Article
Corrections and comments
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Authors and funding
33 authors.
Funding
Abstract
Patients with clear cell renal cell carcinoma (ccRCC) face a high risk of recurrence after surgery, but existing clinical tools based on clinicopathological factors or costly molecular profiling often lack precision and clinical feasibility. We developed the multimodal predictive recurrence score (MPRS), a multimodal prognostic model using clinical features, CT images, and histopathological whole-slide images (WSIs) from 1648 patients across six centers and the TCGA database. MPRS outperformed unimodal models and clinical tools (Leibovich and UISS scores, KEYNOTE-564 risk classification), achieving C-index values of 0.886 and 0.838 in the internal and external validation cohorts, respectively. Importantly, MPRS correctly reclassified 83.3% (50/60) of KEYNOTE-564-defined low-risk recurrence patients as high-risk, avoiding inadequate adjuvant therapy, while reclassifying 57.7% (15/26) of KEYNOTE-564-defined intermediate/high-risk non-recurrence patients as low-risk, preventing excessive adjuvant therapy. By leveraging routinely available data, MPRS provides a cost-effective and accurate approach for recurrence risk stratification, optimizing personalized ccRCC management and therapeutic decision-making.
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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.