Firas G Petros1, Wei Qiao2, Nirmish Singla3, Timothy N Clinton3, Haley Robyak4, Jay D Raman4, Vitaly Margulis3, Surena F Matin5. 1. Department of Urology, The University of Texas MD Anderson Cancer Center, Houston, TX. 2. Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX. 3. Department of Urology, University of Texas Southwestern Medical Center, Dallas, TX. 4. Department of Surgery, Division of Urology, Penn State Health Milton S. Hershey Medical Center, Hershey, PA. 5. Department of Urology, The University of Texas MD Anderson Cancer Center, Houston, TX. Electronic address: surmatin@mdanderson.org.
Abstract
BACKGROUND: Accurate risk stratification prior to radical nephroureterectomy remains a challenge with upper-tract urothelial carcinoma (UTUC). Herein, we generated an optimized preoperative tool predicting high-risk nonorgan-confined (NOC)-UTUC. MATERIALS AND METHODS: Retrospective evaluation of 699 patients undergoing radical nephroureterectomy at 3 academic centers. Multiplex preoperative patient, imaging, endoscopic, and laboratory values were evaluated. Model derivation and validation were based on a split-sample method. Patients were divided randomly into a development (training) cohort (70% of patients) and validation (test) cohort (30% of patients). Univariate and multivariate logistic regression addressed the prediction of NOC disease (pT3/pT4 and/or pN+) based on training cohort. A backward stepdown selection process achieved the most informative nomogram. The ROC analysis identified a cut-off point predicting high-risk disease. The test cohort served as "external" validation to verify the findings based on the training cohort. Bootstrap resampling was conducted for both internal and "external" validation to evaluate the model fitting. RESULTS: Total of 566 patients included for analysis, mean age 69.7 years, 85% Caucasian, 64% male, 62% high grade. NOC-UTUC was found in 184 (32.5%) patients on final pathology. Of 184 patients with NOC-UTUC, an equal number of renal pelvis and ureter only tumors (n = 74; 40.2% for each location) were noted; 36 (19.6%) had tumors in both locations. Multivariate model based on development cohort (n = 396) demonstrated clinical stage (odds ratio [OR] 14.0, P < 0.01), biopsy tumor grade (OR 3.3, P = 0.01), tumor architecture (OR 2.65, P = 0.09), and Hgb (OR 0.8, P = 0.02) level were independently associated with NOC disease. A preoperative nomogram incorporating these 4 variables achieved 82% accuracy, 48% sensitivity, and 95% specificity in predicting NOC-UTUC. The cut-off point for predicting high-risk disease was ≥0.49. CONCLUSIONS: We established and validated an accurate tool for the prediction of locally advanced NOC-UTUC. This preoperative nomogram can be used to more optimally select patients for preoperative systemic chemotherapy, and facilitate clinical trial enrollment.
BACKGROUND: Accurate risk stratification prior to radical nephroureterectomy remains a challenge with upper-tract urothelial carcinoma (UTUC). Herein, we generated an optimized preoperative tool predicting high-risk nonorgan-confined (NOC)-UTUC. MATERIALS AND METHODS: Retrospective evaluation of 699 patients undergoing radical nephroureterectomy at 3 academic centers. Multiplex preoperative patient, imaging, endoscopic, and laboratory values were evaluated. Model derivation and validation were based on a split-sample method. Patients were divided randomly into a development (training) cohort (70% of patients) and validation (test) cohort (30% of patients). Univariate and multivariate logistic regression addressed the prediction of NOC disease (pT3/pT4 and/or pN+) based on training cohort. A backward stepdown selection process achieved the most informative nomogram. The ROC analysis identified a cut-off point predicting high-risk disease. The test cohort served as "external" validation to verify the findings based on the training cohort. Bootstrap resampling was conducted for both internal and "external" validation to evaluate the model fitting. RESULTS: Total of 566 patients included for analysis, mean age 69.7 years, 85% Caucasian, 64% male, 62% high grade. NOC-UTUC was found in 184 (32.5%) patients on final pathology. Of 184 patients with NOC-UTUC, an equal number of renal pelvis and ureter only tumors (n = 74; 40.2% for each location) were noted; 36 (19.6%) had tumors in both locations. Multivariate model based on development cohort (n = 396) demonstrated clinical stage (odds ratio [OR] 14.0, P < 0.01), biopsy tumor grade (OR 3.3, P = 0.01), tumor architecture (OR 2.65, P = 0.09), and Hgb (OR 0.8, P = 0.02) level were independently associated with NOC disease. A preoperative nomogram incorporating these 4 variables achieved 82% accuracy, 48% sensitivity, and 95% specificity in predicting NOC-UTUC. The cut-off point for predicting high-risk disease was ≥0.49. CONCLUSIONS: We established and validated an accurate tool for the prediction of locally advanced NOC-UTUC. This preoperative nomogram can be used to more optimally select patients for preoperative systemic chemotherapy, and facilitate clinical trial enrollment.
Authors: Vitaly Margulis; Maneka Puligandla; Edouard J Trabulsi; Elizabeth R Plimack; Elizabeth R Kessler; Surena F Matin; Guilherme Godoy; Ajjai Alva; Noah M Hahn; Michael A Carducci; Jean Hoffman-Censits Journal: J Urol Date: 2019-11-08 Impact factor: 7.450
Authors: Omar Alhalabi; Matthew T Campbell; Lianchun Xiao; Ana C Adriazola; Nathaniel R Wilson; Arlene O Siefker-Radtke; Paul G Corn; Amado Zurita; Eric Jonasch; Jianjun Gao; Mehrad Adibi; Ashish M Kamat; Neema Navai; Louis L Pisters; Colin Dinney; Surena F Matin; Amishi Y Shah Journal: BJUI Compass Date: 2021-10-11
Authors: Victor M Schuettfort; Benjamin Pradere; Fahad Quhal; Hadi Mostafaei; Ekaterina Laukhtina; Keiichiro Mori; Reza Sari Motlagh; Michael Rink; David D'Andrea; Mohammad Abufaraj; Pierre I Karakiewicz; Shahrokh F Shariat Journal: Turk J Urol Date: 2020-10-09