ArticleEuropean urology open science2021
External Validation of the ASSURE Model for Predicting Oncological Outcomes After Resection of High-risk Renal Cell Carcinoma (RESCUE Study: UroCCR 88).
Article in European urology open science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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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
3 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.
- Diagnostic accuracy of deep learning in detection and prognostication of renal cell carcinoma: a systematic review and meta-analysis.Frontiers in medicine · 2024Pooled it
- UroPredict: Machine learning model on real-world data for prediction of kidney cancer recurrence (UroCCR-120).NPJ precision oncology · 2024Article
- Predicting cancer outcomes after resection of high-risk RCC.Nature reviews. Urology · 2022Article
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Authors and funding
16 authors at 11 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A prognostic model based on the population of the ASSURE phase 3 trial has recently been described. The ASSURE model stratifies patients into risk groups to predict survival after surgical resection of intermediate- and high-risk localised kidney cancer. We evaluated this model in an independent cohort of 1372 patients using discrimination, calibration, and decision curve analysis. Regarding disease-free survival, the ASSURE model showed modest discrimination (65%), miscalibration, and poor net benefit compared with the UCLA Integrated Staging System (UISS) and Leibovich 2018 models. Similarly, the ability of the ASSURE model to predict overall survival was poor in terms of discrimination (63%), with overestimation on calibration plots and a modest net benefit for the probability threshold of between 10% and 40%. Overall, our results show that the performance of the ASSURE model was less optimistic than expected, and not associated with a clear improvement in patient selection and clinical usefulness in comparison to with available models. We propose an updated version using the recalibration method, which leads to a (slight) improvement in performance but should be validated in another external population. PATIENT SUMMARY: The recent ASSURE model evaluates survival after surgery for nonmetastatic kidney cancer. We found no clear improvement in patient classification when we compared ASSURE with older models, so use of this model for patients with nonmetastatic kidney cancer still needs to be clarified.
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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.