A structured training curriculum for robot-assisted radical nephroureterectomy: a Delphi consensus study.

Publication/Presentation Date

12-1-2025

Abstract

OBJECTIVES: To develop an internationally validated, structured robot-assisted radical nephroureterectomy (RARNU) training programme through expert consensus.

MATERIALS AND METHODS: A RARNU-specific questionnaire was developed/adapted from previously published, validated questionnaires for robot-assisted urological procedures. This included five key domains and 11 surgical steps. In all, 30 upper tract urothelial carcinoma experts were invited to participate. A two-stage modified Delphi approach was employed. Consensus was defined as ≥80% agreement. Modifications and additional statements were proposed during the second round following qualitative/quantitative feedback from the initial round.

RESULTS: Response rates for the first and second Delphi rounds were 80% (24/30) and 92% (22/24), respectively. All agreed that adoption of a standardised training curriculum can improve clinical outcomes during the RARNU learning curve. There was ≥92% agreement on all proposed RARNU steps. Five RARNU clinical modules of increasing complexity were defined using individual step difficulty and number of prior RARNU cases required, with ≥96% agreement among respondents. Respondents unanimously agreed that the final assessment should be based on a procedure-specific scale focusing on the hilar dissection, ureteric dissection, and bladder cuff excision steps. No consensus was reached for the annual minimum RARNU volume required for eligibility as a RARNU curriculum host centre.

CONCLUSION: This is the first structured training curriculum for RARNU using international expert consensus. This will help guide surgical educators and trainees toward independent completion of a full RARNU.

Volume

136

Issue

6

First Page

1114

Last Page

1120

ISSN

1464-410X

Disciplines

Business Administration, Management, and Operations | Health and Medical Administration | Management Sciences and Quantitative Methods

PubMedID

40960222

Department(s)

Administration and Leadership

Document Type

Article

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