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Prediction of Renal Mass Aggressiveness Using Clinical and Radiographic Features
abstract
This abstract is available on the publisher's site.
Access this abstract nowOBJECTIVE
To examine the ability of preoperative clinical characteristics to predict histological features of renal masses (RMs).
PATIENTS AND METHODS
Data from consecutive patients with clinical stage I RMs treated surgically between 2010 and 2011 in the Clinical Research Office of Endourology Society (CROES) Renal Mass Registry were collected. Based on surgical histology, tumours were categorised as benign, low- or high-aggressiveness cancer. Multivariate logistic regression was used to estimate the probability of the histological group by clinical and radiographic features in the entire cohort and a subcohort of cT1a tumours. The performance of the models was studied by calibration, Nagelkerke's R(2) , and discrimination (area under the receiver operating characteristic curve).
RESULTS
The study cohort included 2 224 patients with a clinical stage I RM, of which 1 367 (61%) were cT1a. Benign lesions were found in 369 (16.6%), low-aggressiveness tumours in 1 156 (52%) and high-aggressiveness tumours in 699 (31.4%). Male gender, smoking history, increased tumour size, and lower exophytic rate were associated with malignancy and high-aggressiveness features (all P < 0.05). Models developed based on these characteristics had the ability to discriminate benign from malignant (bootstrap corrected c-index of 0.64) and high-aggressiveness tumours from benign and low-aggressiveness tumours (bootstrap corrected c-index of 0.66). Similar results were achieved in the cT1a subgroup. The c-index of tumour diameter as a single predictor of malignancy and high-aggressiveness tumours in the entire cohort was 0.6 and 0.63, respectively.
CONCLUSION
Although older age, male gender, smoking history, increased tumour diameter, and reduced exophytic rate are associated with malignancy and high aggressiveness of clinical stage I RMs, models incorporating these characteristics have modest discriminating power, being only slightly better than the predictive ability of tumour size alone.
Additional Info
Disclosure statements are available on the authors' profiles:
Prediction of Renal Mass Aggressiveness Using Clinical and Radiographic Features: A Global, Multicentre Prospective Study
BJU Int 2016 Jun 01;117(6)914-922, S Golan, S Eggener, S Subotic, E Barret, L Cormio, S Naito, A Tefekli, M Pilar Laguna PesFrom MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.
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This study evaluates a large, retrospective, and multicenter database of clinically localized renal masses. Given the caveats of retrospective data, the authors do an excellent job of characterizing predictors of high-risk or potentially aggressive tumors and find that male gender, older age, smoking history, increasing tumor diameter, and endophytic tumors predict aggressive malignancy. This corroborates the results from a large, systematic review performed by the Agency for Healthcare Quality and Research (AHRQ) and sponsored by the American Urological Association (AUA) in which male gender and tumor size were determined to be the strongest predictors of malignancy.1 There are a number of important limitations that need to be recognized when reading this study. Most importantly, “high aggressiveness” disease is defined as high-grade and/or advanced stage (≥pT3a) tumors. While high-grade tumors certainly appear aggressive and are more likely to be at an advanced stage, survival outcomes in the clinically localized renal mass population are driven by stage with uniformly excellent outcomes among patients with localized low- and high-grade tumors. This may contribute to the relatively low concordance indices for these models (0.64–0.66). Nevertheless, this study provides important data for practitioners as they counsel patients as to the risk of malignancy and aggressive malignancy prior to surgery.
Reference