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Article Abstract

Background: The RENAL nephrometry score (RNS) is widely used to describe renal mass complexity and inform patient counseling for partial nephrectomy (PN). However, in cases with multiple tumors, it is unknown which features drive perioperative outcomes.

Objective: To employ a novel scoring equation (multiplex score [MS]) derived from RNS to assess outcomes of multiplex PN at our institution.

Design, Setting, And Participants: A total of 62 consecutive multiplex PN (median (range) # tumors = 4(2-11), 65% robotic) were performed by a single surgeon. The MS was defined a priori as a weighted score derived from RNS (# low risk ([LR] lesions) + 2*(# intermediate risk [IR]) + 4*(# high risk [HR]) based on published complication rates.

Outcome Measurements And Statistical Analysis: MS was dichotomized into favorable/unfavorable based on median score. Patient outcomes were maintained prospectively. MS was compared with other potential RNS derived scoring systems.

Results And Limitation: A total of 249 tumors were scored. Median (range) MS was 6(range 2-20, IQR 3-8). Complications occurred in 10 patients (16.1%). Only 1 complication occurred in the favorable MS(<6) group, and MS was associated with perioperative complication (P = 0.02) and blood loss (P < .001). When compared to other potential scoring systems, MS had the best area under the curve (AUC) to predict operative complications (0.75).

Conclusions: The novel MS was associated with complications and blood loss. This tool may facilitate standardized reporting of complexity for multiplex series, with special relevance for hereditary cancer syndromes.

Patient Summary: For patients who have one kidney tumor, there are established scoring systems to help patients and surgeons decide on the surgical plan. However currently, for patients with more than one renal tumor, there is no such scoring system. Here, we present the "Multiplex Score" to aid shared-decision-making in cases with more than one renal tumor.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10845006PMC
http://dx.doi.org/10.1016/j.urolonc.2023.03.007DOI Listing

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