Evidence map›Paper›PMID 38036328›Full record

ArticleEuropean urology oncology2024

Positive Surgical Margins After Anterior Robot-assisted Radical Prostatectomy: Assessing the Learning Curve in a Multi-institutional Collaboration.

Carlo A Bravi, Paolo Dell'Oglio, Pietro Piazza, Simone Scarcella, Lorenzo Bianchi, Ugo Falagario, Filippo Turri, Iulia Andras, Fabrizio Di Maida, Ruben De Groote and 14 more

Open access · greenAbstract readMulticenter Study
In one paragraph

Article in European urology oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
3.4field-weighted citation impact, top 7% of its field
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

14 citing papers in PubMed, 13 citations in OpenAlex.

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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

24 authors at 16 institutions in 6 countries.

Carlo A BraviDepartment of Urology, The Royal Marsden NHS Foundation Trust, London, UK; Department of Urology, Onze-Lieve-Vrouwziekenhuis Hospital, Aalst, Belgium; ORSI Academy, Ghent, Belgium. Electronic address: carloandrea.bravi@gmail.com.
Paolo Dell'OglioDepartment of Urology, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy; Department of Urology, Antoni van Leeuwenhoek Hospital, The Netherlands Cancer Institute, Amsterdam, The Netherlands; Interventional Molecular Imaging Laboratory, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
Pietro PiazzaDivision of Urology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
Simone ScarcellaDivision of Urology, United Hospital of Ancona, School of Medicine Marche Polytechnic University, Ancona, Marche, Italy; Department of Urology, Azienda Ospedaliera Ospedali Riuniti Marche Nord, Pesaro, Italy.
Lorenzo BianchiDivision of Urology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
Ugo FalagarioUrology and Renal Transplantation Unit, Department of Medical and Surgical Sciences, University of Foggia, Foggia, Italy.
Filippo TurriDepartment of Urology, ASST Santi Paolo e Carlo, University of Milan, Milan, Italy.
Iulia AndrasDepartment of Urology, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania.
Fabrizio Di MaidaDepartment of Urology, Careggi University Hospital, Florence, Italy.
Ruben De GrooteDepartment of Urology, Onze-Lieve-Vrouwziekenhuis Hospital, Aalst, Belgium; ORSI Academy, Ghent, Belgium.
Federico PiramideSchool of Medicine, Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy.
Marcio Covas MoschovasAdventHealth Global Robotics Institute, Celebration, FL, USA.
Nazareno SuardiIRCCS Ospedale Policlinico San Martino, Genova, Italy; Department of Urology, Ospedali Civili of Brescia, Brescia, Italy.
Carlo TerroneIRCCS Ospedale Policlinico San Martino, Genova, Italy.
Giuseppe CarrieriUrology and Renal Transplantation Unit, Department of Medical and Surgical Sciences, University of Foggia, Foggia, Italy.
Vipul PatelAdventHealth Global Robotics Institute, Celebration, FL, USA.
Riccardo AutorinoDepartment of Urology, Rush University, Chicago, IL, USA.
Francesco PorpigliaSchool of Medicine, Division of Urology, Department of Oncology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy.
Andrew VickersDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Alberto BrigantiDivision of Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy.
Francesco MontorsiDivision of Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy.
Alexandre MottrieDepartment of Urology, Onze-Lieve-Vrouwziekenhuis Hospital, Aalst, Belgium; ORSI Academy, Ghent, Belgium.
Alessandro LarcherDivision of Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy.
Junior ERUS/Young Academic Urologist Working Group on Robot-assisted Surgery
IRCCS Ospedale San Raffaele · ITAdventHealth Celebration · USAzienda USL di Bologna · ITOnze Lieve Vrouwziekenhuis Hospital · BEOspedale San Luigi Gonzaga · ITUniversity of Foggia · ITAzienda Ospedaliero-Universitaria Careggi · ITAzienda Socio Sanitaria Territoriale degli Spedali Civili di Brescia · ITIuliu Hațieganu University of Medicine and Pharmacy · ROMemorial Sloan Kettering Cancer Center · USORSI Academy · BEOspedale Policlinico San Martino · ITOspedali Riuniti Marche Nord · ITRush University · USThe Netherlands Cancer Institute · NLUniversity of Milan · IT

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Hongbiao Carl Lekaye · 1985 to 2026
$347.4M
SPORE In Prostate CancerP50CA092629 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI JAMES A EASTHAM · 2001 to 2026
$63.0M
NCI NIH HHS P30 CA008748NCI NIH HHS P50 CA092629
6 · The paper itself

Abstract

backgroundThe learning curve for robot-assisted radical prostatectomy (RARP) remains controversial, with prior studies showing that, in contrast with evidence on open and laparoscopic radical prostatectomy, biochemical recurrence rates of experienced versus inexperienced surgeons did not differ.

objectiveTo characterize the learning curve for positive surgical margins (PSMs) after RARP. DESIGN, SETTING, AND

participantsWe analyzed the data of 13 090 patients with prostate cancer undergoing RARP by one of 74 surgeons from ten institutions in Europe and North America between 2003 and 2022. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Multivariable models were used to assess the association between surgeon experience at the time of each patient's operation and PSMs after surgery, with adjustment for preoperative prostate-specific antigen level, grade, stage, and year of surgery. Surgeon experience was coded as the number of robotic radical prostatectomies done by the surgeon before the index patient's operation. RESULTS AND LIMITATIONS: Overall, 2838 (22%) men had PSMs on final pathology. After adjusting for case mix, we found a significant, nonlinear association between surgical experience and probability of PSMs after surgery, with a lower risk of PSMs for greater surgeon experience (p < 0.0001). The probabilities of PSMs for a patient treated by a surgeon with ten, 250, 500, and 2000 prior robotic procedures were 26%, 21%, 18%, and 14%, respectively (absolute risk difference between ten and 2000 procedures: 11%; 95% confidence interval: 9%, 14%). Similar results were found after stratifying patients according to extracapsular extension at final pathology. Results were also unaltered after excluding surgeons who had moved between institutions.

conclusionsWhile we characterized the learning curve for PSMs after RARP, the relative contribution of surgical learning to the achievement of optimal outcomes remains controversial. Future investigations should focus on what experienced surgeons do to avoid positive margins and should explore the relationship between learning, margin rate, and biochemical recurrence. Understanding what margins affect recurrence and whether these margins are trainable or a result of other factors may shed light on where to focus future efforts in surgical education. PATIENT SUMMARY: In patients receiving robotic radical prostatectomy for prostate cancer, we characterized the learning curve for positive margins. The risk of surgical margins decreased progressively with increasing experience, and plateaued around the 500th procedure. Understanding what margins affect recurrence and whether these margins are trainable or a result of other factors has implications for surgeons and patients, and it may shed light on where to focus future efforts in surgical education.

Indexed as

Learning CurveMargins of ExcisionProstatectomyProstatic NeoplasmsRobotic Surgical ProceduresAgedClinical CompetenceHumansMaleMiddle AgedLearning curvePositive surgical marginsProstate cancerRobot-assisted radical prostatectomyRobotic surgerySurgical education

Identifiers

PMID38036328
PMCPMC12127505
OpenAlexW4389137223

What OpenQuestion holds

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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.