AI Article Synopsis

  • The study aimed to identify key factors influencing the choice of surgical treatment for patients with localized Renal-Cell Carcinoma (RCC) using clinical and nephrometry data.
  • It involved a retrospective analysis of patients who underwent surgery for localized RCC between 2010 and 2017 and used multivariate predictive modeling to assess risks associated with surgical options.
  • Results indicated that the risks for partial nephrectomy (PN) were linked to remaining functioning kidney tissue volumes for polar and lateral tumors, while tumor size was the main factor for medial tumors, with the predictive model showing high sensitivity (95.2%) and specificity (95.4%).

Article Abstract

Objective: to determine the key factors affecting the surgical treatment selection for patients with localized Renal-Cell Carcinoma (RCC) based on clinical and nephrometry data.

Materials And Methods: A retrospective cohort study to determine the key factors affecting the surgical treatment on a subset of patients with localized RCC (T1-T2) that underwent surgical treatment at primary investigational center from 2010 to 2017. Primary results were validated on the retrospective dataset of patients treated at high-volume referent center. Validation aimed to test applicability of the predictive model designed during primary analysis. To determine the relationship between the risks of radical or partial nephrectomy, the multivariate predictive modeling method was used.

Results: Based on the analysis, for polary and laterally located tumors, the risk of RN was conditioned only by remaining functioning parenchyma volume (RFPV). The average critical value of RFPV for polar lesions was = 58%; for lateral tumors = 67%. For medial location, the risk of RN only depended on the tumor size. Average critical value of the tumor size in the medial location was = 38mm. Based on the ROC curve comparison, there were no statistically significant differences between the predictive models containing 12 and 3 factors (AUC and AUC; P = 0.12); thus, the reduced amount of the factor indicators from 12 to 3 did not worsen the model predictive qualities. Designed during primary analysis hypothesis was successfully validated in a referent center on the cohort of 300 patients. Predictive model is characterized by high sensitivity (95.2%) and specificity (95.4%) in selecting patients for partial nephrectomy.

Conclusions: For the polar and lateral tumor locations, the functioning parenchymal volumes of over 58 and 67% respectively serve as PN indications. However, for the medial lesions, the primary PN indication is a tumor size less than 38 mm.

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Source
http://dx.doi.org/10.1016/j.urolonc.2024.09.019DOI Listing

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