Effect of delayed resection after initial surveillance and tumor growth rate on final surgical pathology in patients with small renal masses (SRMs)

Clinical T1/2 renal cell carcinoma: multiparametric dynamic contrast-enhanced MRI features-based model for the prediction of individual adverse pathology

BACKGROUND

The detection of renal cell carcinoma (RCC) has been rising due to the enhanced utilization of cross-sectional imaging and incidentally discovered lesions with adverse pathology demonstrate potential for metastasis. The purpose of our study was to determine the clinical and multiparametric dynamic contrast-enhanced magnetic resonance imaging (CEMRI) associated independent predictors of adverse pathology for cT1/2 RCC and develop the predictive model.

METHODS

We recruited 105 cT1/2 RCC patients between 2018 and 2022, all of whom underwent preoperative CEMRI and had complete clinicopathological data. Adverse pathology was defined as RCC patients with nuclear grade III-IV; pT3a upstage; type II papillary RCC, collecting duct or renal medullary carcinoma, unclassified RCC; sarcomatoid/rhabdoid features. The qualitative and quantitative CEMRI parameters were independently reviewed by two radiologists. Univariate and multivariate binary logistic regression analyses were utilized to determine the independent predictors of adverse pathology for cT1/2 RCC and construct the predictive model. The receiver operating characteristic (ROC) curve, confusion matrix, calibration plot, and decision curve analysis (DCA) were conducted to compare the diagnostic performance of different predictive models. The individual risk scores and linear predicted probabilities were calculated for risk stratification, and the Kaplan-Meier curve and log-rank tests were used for survival analysis.

RESULTS

Overall, 45 patients were pathologically confirmed as RCC with adverse pathology. Clinical characteristics, including gender, and CEMRI parameters, including RENAL score, tumor margin irregularity, necrosis, and tumor apparent diffusion coefficient (ADC) value were identified as independent predictors of adverse pathology for cT1/2 RCC. The clinical-CEMRI predictive model yielded an area under the curve (AUC) of the ROC curve of 0.907, which outperformed the clinical model or CEMRI signature model alone. Good calibration, better clinical usefulness, excellent risk stratification ability of adverse pathology and prognosis were also achieved for the clinical-CEMRI predictive model.

CONCLUSIONS

The proposed clinical-CEMRI predictive model offers the potential for preoperative prediction of adverse pathology for cT1/2 RCC. With the ability to forecast adverse pathology, the predictive model could significantly benefit patients and clinicians alike by providing enhanced guidance for treatment planning and decision-making.

Impact of COVID-19 pandemic on diagnosis and surgical management of common urological conditions: results from multi-institutional database analysis from the United States

OBJECTIVE

To determine real life impact during the first pandemic year on diagnosis and surgical management of common urological diseases and 90-day postoperative mortality following common urological surgeries.

METHODS

Cross-sectional study from 2016 to 2021. We used TriNetX to obtain the data. Patients with a diagnosis of six common non-oncologic and five oncologic urologic conditions were included. Twenty-four surgical interventions were also analyzed. The total number of diagnosis and surgical procedures were compared yearly from 2016 to 2021 and Chi-square test was used for statistical analysis. Additionally, monthly changes were evaluated during the first pandemic year and a z score period time was reported. The 90-day post-operative mortality rates during the first pandemic year were compared to the preceding year.

RESULTS

Overall, a decrease in diagnosis and surgeries were observed during the first pandemic year, with maximum drop in April 2020. Among non-oncological conditions, the decrease in diagnosis of enlarged prostate (5.3%), nephrolithiasis (9.4%), urinary incontinence (18.7%), and evaluation for male sterilization (14.8%) reached statistical significance (P < 0.05 in all). Prostate cancer was the only cancer whose diagnosis showed statistically significant decrease (6.2%, P < 0.05). The surgical case load for benign conditions showed higher reduction (13.1-25%) than for malignant conditions (5.9-16.3%). There was no change in 90-day post-operative mortality in any of the analyzed surgeries.

CONCLUSIONS

Our study showed that although healthcare delivery decreased in the first pandemic year, causing a decline in the diagnosis and surgical treatment of several diseases, surgical interventions did not increase the risk of death.

Comparison and development of preoperative systemic inflammation markers-based models for the prediction of unfavorable pathology in newly diagnosed clinical T1 renal cell carcinoma

BACKGROUND

We sought to investigate the preoperative risk factors associated with the unfavorable pathology (UP) of clinical T1 (cT1) renal lesions. The aims of this study were to develop and compare several novel models capable of accurately identifying those patients at high risk of harboring occult adverse histopathological characteristics.

METHODS

The clinical parameters and preoperative laboratory test results from 1281 cT1 renal cell carcinomas (RCCs) patients who underwent partial nephrectomy (PN) or radical nephrectomy (RN) were collected. The data was randomly split into training (70%) and testing (30%) datasets. We performed univariable and multivariable logistic regression analyses for significant predictors and, subsequently, constructed predictive models based on those significant risk factors. Receiver operating characteristic (ROC) analysis was used to determine the model with the highest discrimination power with corresponding area under the curve (AUC). Calibration curves were plotted and decision curve analyses (DCAs) were applied to explore clinical net benefit.

RESULTS

UP was identified in 21.1% (n = 270), 21.0% (n = 188) and 21.3% (n = 82) patients in the total population, training cohort and validation cohort, respectively. R.E.N.A.L. (radius, exophytic/endophytic properties, nearness of tumor to collecting system or sinus, anterior/posterior, location relative to the polar lines) nephrometry score, tumor size, neutrophil-to-lymphocyte ratio (NLR) and albumin-to-globulin ratio (AGR) were independent predictors of UP. Among those predictive models, the model that consisted of tumor size, hemoglobin, NLR and AGR performs best according to the highest AUC of 0.70 and the highest net benefit. When tumor histology was added to the biomarker-based model, including tumor size, hemoglobin, NLR and AGR, the AUC improved from 0.60 to 0.63 in the validation cohort.

CONCLUSIONS

In this analytical model study, our findings verified that systemic inflammation response markers showed high potential for identifying UP. Our biomarker-based models well predicted occult aggressive histopathological characteristics among patients with cT1 renal lesions, and the use of models may be greatly beneficial to urologists in tailoring precise management and therapy for patients. Robust validation is warranted prior to adoption into clinical practice.

Risks from Deferring Treatment for Genitourinary Cancers: A Collaborative Review to Aid Triage and Management During the COVID-19 Pandemic

Context

The coronavirus disease 2019 (COVID-19) pandemic is leading to delays in the treatment of many urologic cancers.

Objective

To provide a contemporary picture of the risks from delayed treatment for urologic cancers to assist with triage.

Evidence acquisition

A collaborative review using literature published as of April 2, 2020.

Evidence synthesis

Patients with low-grade non–muscle-invasive bladder cancer are unlikely to suffer from a 3–6-month delay. Patients with muscle-invasive bladder cancer are at risk of disease progression, with radical cystectomy delays beyond 12 wk from diagnosis or completion of neoadjuvant chemotherapy. Prioritization of these patients for surgery or management with radiochemotherapy is encouraged. Active surveillance should be used for low-risk prostate cancer (PCa). Treatment of most patients with intermediate- and high-risk PCa can be deferred 3–6 mo without change in outcomes. The same may be true for cancers with the highest risk of progression. With radiotherapy, neoadjuvant androgen deprivation therapy (ADT) is the standard of care. For surgery, although the added value of neoadjuvant ADT is questionable, it may be considered if a patient is interested in such an approach. Intervention may be safely deferred for T1/T2 renal masses, while locally advanced renal tumors (≥T3) should be treated expeditiously. Patients with metastatic renal cancer may consider vascular endothelial growth factor targeted therapy over immunotherapy. Risks for delay in the treatment of upper tract urothelial cancer depend on grade and stage. For patients with high-grade disease, delays of 12 wk in nephroureterectomy are not associated with adverse survival outcomes. Expert guidance recommends expedient local treatment of testis cancer. In penile cancer, adverse outcomes have been observed with delays of ≥3 mo before inguinal lymphadenectomy. Limitations include a paucity of data and methodologic variations for many cancers.

Conclusions

Patients and clinicians should consider the oncologic risk of delayed cancer intervention versus the risks of COVID-19 to the patient, treating health care professionals, and the health care system.

Patient summary

The coronavirus disease 2019 pandemic has led to delays in the treatment of patients with urologic malignancies. Based on a review of the literature, patients with high-grade urothelial carcinoma, advanced kidney cancer, testicular cancer, and penile cancer should be prioritized for treatment during these challenging times.

Roles for active surveillance in renal cancer

PURPOSE OF REVIEW

With this review, we describe the most recent advances in active surveillance as well as diagnosis and management of small renal masses (SRMs).

RECENT FINDINGS

We discuss diagnosis, differentiation of solid from cystic lesions, risk prediction and treatment of the SRM. A better understanding of the disease facilitates the use of more conservatory treatments, such as active surveillance. Active surveillance has been increasingly accepted not only for SRM, but also for larger tumors and even metastatic patients. Exiting advances in risk prediction will help us define which patients can be safely managed with active surveillance and which require immediate treatment. Meanwhile, the use of renal tumor biopsies is still an important tool for these cases.

SUMMARY

Active surveillance is an option for many patients with renal masses. Noninvasive methods for diagnosis and risk prediction are being developed, but meanwhile, renal tumor biopsy is a useful tool. A better understanding of the disease increases the number of patients who can undergo active surveillance fully certain of the safety of their management.

Change in Nephrometry Scoring in Small Renal Masses (<4 cm) on Active Surveillance: Preliminary Observations From Tayside Active Surveillance Cohort (TASC) Study

RATIONALE AND OBJECTIVES

Prediction of growth, in particular knowing the possibility of aggressive cancer in small renal masses on active surveillance, remains poorly understood. The study was designed to determine whether serial nephrometry score measurements could predict possibility of aggressive malignancy (grade of cancer) in patients with small renal masses opting for active surveillance initially.

MATERIALS AND METHODS

One hundred sixteen patients between January 2000 and December 2016 undergoing partial nephrectomy were recruited. Out of these, 97 were analyzed using different nephrometry scoring systems. Measurement of nephrometry scores (Radius of tumors, Exo/Endophytic; Nearness of tumors to the collecting system or sinus; Anterior/posterior; Location in relation to polar lines, Preoperative Aspects and Dimensions Used for Anatomical, Centrality Index) was performed by two researchers. Among the patients opting for partial nephrectomy, 40 were on active surveillance for at least 12 months (mean 32; 12-60 months) before partial nephrectomy. Computed tomography scan images of these patients were retrieved and analyzed including comparison to histopathology.

RESULTS

Nephrometry scores measured on serial computed tomography scan images showed a significant correlation between change in score and grade of cancer on multivariate analysis (P value .001). Addition of multivariate analysis to nomogram based on change in size alone did not improve predictive value of area under the curve significantly.

CONCLUSIONS

Change in nephrometry scoring measurements correlates with grade of cancer in small renal masses but falls short of significantly predicting presence of malignancy or grade of cancer on nomogram in patients opting for active surveillance for small renal masses. At present, this approach may be inadequate for decision-making.