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A New Model Under Study to Predict Staging of Upper Tract Urothelial Cancer

By: Lauren Harrison, MS
Posted: Thursday, July 22, 2021

A team of researchers, led by Shahrokh F. Shariat, MD, of the Medical University of Vienna, created a risk stratification model that is intended to help identify patients who may be candidates for endoscopic kidney-sparing surgery for upper tract urothelial carcinoma. This large retrospective analysis identified the predictive value of various disease characteristics for identifying patients with stage T2/N+ or greater disease and was published in European Urology.

This predictive model was based on data from 1,214 patients who had undergone ureterorenoscopy with biopsy and had subsequent radical nephroureterectomy for non-metastatic upper tract urothelial carcinoma. Data including patient age, sex, biopsy grading, urine cytology, invasion on cross-sectional imaging, tumor size, preoperative hydronephrosis, previous radical cystectomy, tumor multifocality, and variant histology were collected and used for logistic regression and predictive mean matching. These analyses were performed to assess the risk of a patient having stage T2/N+ or greater disease.

In the study population, there were 659 patients (54.3%) with stage T1 or lower disease and 555 patients (45.7%) with stage T2/N+ or greater disease. After multivariable logistic regression analysis, a number of factors were associated with stage T2/N+ disease: age (odds ratio [OR] = 1.02, P = .013), high-grade biopsy (OR = 1.81, P < .001), biopsy cT1+ staging (OR = 3.23, P < .001), preoperative hydronephrosis (OR = 1.37, P = .024), tumor size (OR = 1.09, P = .029), invasion on imaging (OR = 5.10, P < .001), and sessile architecture (OR = 2.31, P < .001).

According to the study authors, the proposed model outperformed previously generated models from both the National Comprehensive Cancer Network and the European Association of Urology in terms of performance accuracy (75% accuracy vs. 66% to 71% in other models) and reduction in nephroureterectomy. Using this new model to guide treatment decisions, the investigators predicted that it may be possible to avoid radical nephroureterectomy in 4 of 100 additional patients.

Disclosure: For a full list of author disclosures, visit sciencedirect.com.



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