Evidence map›Paper›PMID 38900323›Full record

ReviewAbdominal radiology (New York)2024

Clear cell likelihood score may improve diagnosis and management of renal masses.

Eleonora Salles-Silva, Elissandra Melo Lima, Viviane Brandão Amorim, Miguel Milito, Daniella Braz Parente

Abstract readReview
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In one paragraph

Review in Abdominal radiology (New York), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Eleonora Salles-SilvaFederal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil.ORCID 0000-0002-4903-6042
Elissandra Melo LimaFederal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil.ORCID 0000-0001-7095-529X
Viviane Brandão AmorimGrupo Fleury, Rio de Janeiro, RJ, Brazil.ORCID 0000-0001-9339-1474
Miguel MilitoFederal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil.ORCID 0000-0003-2610-5356
Daniella Braz ParenteFederal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil. daniella.parente@gmail.com.ORCID 0000-0003-0031-5785

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The detection of solid renal masses has increased over time due to incidental findings during imaging studies conducted for unrelated medical conditions. Approximately 20% of lesions measuring less than 4 cm are benign and 80% are malignant. Clear cell renal cell carcinoma (ccRCC) is the most frequent among renal carcinomas, responsible for 65-80% of cases. The increased detection of renal masses facilitates early diagnosis and treatment. However, it also leads to more invasive interventions, which result in higher morbidity and costs. Currently, only histological analysis can offer an accurate diagnosis. Surgical nephron loss significantly elevates morbidity and mortality rates. Active surveillance represents a conservative management approach for patients diagnosed with a solid renal mass that is endorsed by both American Urological Association and the European Society for Medical Oncology. However, active surveillance is used in a minority of patients and varies across institutions. The lack of clinical studies using a standardized approach to incidentally detected small renal masses precludes the widespread use of active surveillance. Hence, there is an urgent need for better patient selection, distinguishing those who require surgery from those suitable for active surveillance. The clear cell likelihood score (ccLS) represents a novel MRI tool for assessing the probability of a renal mass being a ccRCC. In this study, we present a comprehensive review of renal masses and their evaluation using the ccLS to facilitate shared decision between urologists and patients.

Indexed as

Carcinoma, Renal CellKidney NeoplasmsMagnetic Resonance ImagingDiagnosis, DifferentialHumansIncidental FindingsActive surveillanceClear cell likelihood scoreMagnetic resonance imagingRenal carcinomaRenal mass biopsy

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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.