Evidence map›Paper›PMID 34661173›Full record

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).

Zine-Eddine Khene, Alessandro Larcher, Jean-Christophe Bernhard, Nicolas Doumerc, Idir Ouzaid, Umberto Capitanio, François-Xavier Nouhaud, Romain Boissier, Nathalie Rioux-Leclercq, Alexandre De La Taille and 6 more

Open access · goldAbstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
2.1field-weighted citation impact, top 12% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors at 11 institutions in 2 countries.

Zine-Eddine KheneDepartment of Urology, University of Rennes, Rennes, France.
Alessandro LarcherUnit of Urology, Division of Experimental Oncology, Urological Research Institute, IRCCS San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.
Jean-Christophe BernhardDepartment of Urology, University of Bordeaux, Bordeaux, France.
Nicolas DoumercDepartment of Urology, University of Toulouse, Toulouse, France.
Idir OuzaidDepartment of Urology, Bichat Claude Bernard Hospital, Paris, France.
Umberto CapitanioUnit of Urology, Division of Experimental Oncology, Urological Research Institute, IRCCS San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.
François-Xavier NouhaudDepartment of Urology, University Hospital of Rouen, Rouen, France.
Romain BoissierDepartment of Urology, Aix-Marseille University, Marseille, France.
Nathalie Rioux-LeclercqDepartment of Pathology, University of Rennes, Rennes, France.
Alexandre De La TailleDepartment of Urology, Mondor Hospital, Créteil, France.
Philippe BarthelemyDepartment of Oncology, University of Strasbourg, Strasbourg, France.
Francesco MontorsiUnit of Urology, Division of Experimental Oncology, Urological Research Institute, IRCCS San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.
Morgan RouprêtDepartment of Urology, La Pitie Salpétrière Hospital, Paris, France.
Pierre BigotDepartment of Urology, University of Angers, Angers, France.
Karim BensalahDepartment of Urology, University of Rennes, Rennes, France.
French Committee of Urologic Oncology
Centre Hospitalier Universitaire de Rennes · FRVita-Salute San Raffaele University · ITAix-Marseille Université · FRCentre Hospitalier Universitaire d'Angers · FRCentre Hospitalier Universitaire de Rouen · FRCentre Hospitalier Universitaire Henri-Mondor · FRSorbonne Université · FRUniversité Claude Bernard Lyon 1 · FRUniversité de Bordeaux · FRUniversité de Strasbourg · FRUniversité Fédérale de Toulouse Midi-Pyrénées · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

External validationKidney cancerNephrectomyPrognosisRisk groupsSurvival

Identifiers

PMID34661173
PMCPMC8502703
OpenAlexW3203691974

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.