Evidence map›Paper›PMID 41866634›Full record

ArticleJournal of robotic surgery2026

Learning curves of 13 surgeons for robot-assisted radical prostatectomy in a single institution: role of early case density.

Keita Nakamori, Yusaku Imura, Takuya Tsujino, Tatsuo Fukushima, Ko Nakamura, Kohei Kimura, Ippei Takakura, Tomota Okabe, Kazuki Nishimura, Ryoichi Maenosono and 3 more

Abstract read
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Article in Journal of robotic surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Keita Nakamori *Department of Urology, Osaka Medical and Pharmaceutical University, Daigaku-Machi 2-7, Takatsuki City, Osaka, 569-8686, Japan. keita.nakamori@ompu.ac.jp.
Yusaku Imura *Department of Urology, Osaka Medical and Pharmaceutical University, Daigaku-Machi 2-7, Takatsuki City, Osaka, 569-8686, Japan.
Takuya TsujinoDepartment of Urology, Osaka Medical and Pharmaceutical University, Daigaku-Machi 2-7, Takatsuki City, Osaka, 569-8686, Japan. takuya.tsujino@ompu.ac.jp.
Tatsuo FukushimaDepartment of Urology, Osaka Medical and Pharmaceutical University, Daigaku-Machi 2-7, Takatsuki City, Osaka, 569-8686, Japan.
Ko NakamuraDepartment of Urology, Osaka Medical and Pharmaceutical University, Daigaku-Machi 2-7, Takatsuki City, Osaka, 569-8686, Japan.
Kohei KimuraDepartment of Urology, Osaka Medical and Pharmaceutical University, Daigaku-Machi 2-7, Takatsuki City, Osaka, 569-8686, Japan.
Ippei TakakuraDepartment of Urology, Osaka Medical and Pharmaceutical University, Daigaku-Machi 2-7, Takatsuki City, Osaka, 569-8686, Japan.
Tomota OkabeDepartment of Urology, Osaka Medical and Pharmaceutical University, Daigaku-Machi 2-7, Takatsuki City, Osaka, 569-8686, Japan.
Kazuki NishimuraDepartment of Urology, Osaka Medical and Pharmaceutical University, Daigaku-Machi 2-7, Takatsuki City, Osaka, 569-8686, Japan.
Ryoichi MaenosonoDepartment of Urology, Osaka Medical and Pharmaceutical University, Daigaku-Machi 2-7, Takatsuki City, Osaka, 569-8686, Japan.
Tomohisa MatsunagaDepartment of Urology, Osaka Medical and Pharmaceutical University, Daigaku-Machi 2-7, Takatsuki City, Osaka, 569-8686, Japan.
Yuki YoshikawaDepartment of Urology, Osaka Medical and Pharmaceutical University, Daigaku-Machi 2-7, Takatsuki City, Osaka, 569-8686, Japan.
Haruhito AzumaDepartment of Urology, Osaka Medical and Pharmaceutical University, Daigaku-Machi 2-7, Takatsuki City, Osaka, 569-8686, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Robot-assisted radical prostatectomy (RARP) is widely used for localized prostate cancer, yet learning trajectories among multiple surgeons within the same institutional program are not well defined. In this single-center study, we described surgeon-specific learning curves for RARP and examined whether early case density was associated with achieving technical proficiency. We retrospectively reviewed 348 non-proctored RARP cases performed by 13 surgeons at a single tertiary center. For learning curve analysis, 279 standard procedures without extended pelvic lymph node dissection or planned nerve-sparing were included. Surgeon-specific logistic regression models used pneumoperitoneum time ≤ 230 min as the binary outcome and cumulative case number as the explanatory variable; proficiency was defined as the case number at which the predicted probability reached 0.8. Early case density was quantified as 5-case and 10-case densities (cases/day) and evaluated using linear regression. Logistic models could be estimated for 10 surgeons, and 7 (70%) reached the proficiency threshold. The case number at which proficiency was achieved ranged from 16 to 38 (median 26). Higher early case density was associated with a lower case number at proficiency; this association was significant for the 10-case density (P = 0.048) and showed a trend for the 5-case density (P = 0.054). In a single-institution RARP program with standardized technique and perioperative pathways, most surgeons achieved the predefined pneumoperitoneum-time–based proficiency threshold after several dozen cases. Higher early case density was linked to a lower case number at proficiency, suggesting that concentrating initial RARP exposure may support more efficient training and case allocation.

Indexed as

Clinical CompetenceLearning CurveProstatectomyProstatic NeoplasmsRobotic Surgical ProceduresSurgeonsAgedHumansMaleMiddle AgedRetrospective StudiesCase densityLearning curve, Surgical trainingOperative effi ciencyRobot-assisted radical prostatectomy

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Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.