Evidence map›Paper›PMID 37338747›Full record

ArticleAnnals of surgical oncology2023

Nomogram Predicting Locally Advanced Prostate Cancer in Patients with Clinically Organ-Confined Disease Who Underwent Robot-Assisted Radical Prostatectomy: A Retrospective Multicenter Cohort Study in Japan (The MSUG94 Group).

Makoto Kawase, Takayuki Goto, Shin Ebara, Tomoyuki Tatenuma, Takeshi Sasaki, Takuma Ishihara, Yoshinori Ikehata, Akinori Nakayama, Masahiro Toide, Tatsuaki Yoneda and 10 more

Abstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in Annals of surgical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.8field-weighted citation impact, top 25% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Article
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

20 authors at 12 institutions in 1 country.

Makoto KawaseDepartment of Urology, Gifu University Graduate School of Medicine, Gifu, Japan.
Takayuki GotoDepartment of Urology, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Shin EbaraDepartment of Urology, Hiroshima City Hiroshima Citizens Hospital, Hiroshima, Japan.
Tomoyuki TatenumaDepartment of Urology, Yokohama City University, Yokohama, Japan.
Takeshi SasakiDepartment of Nephro-Urologic Surgery and Andrology, Mie University Graduate School of Medicine, Tsu, Japan.
Takuma IshiharaInnovative and Clinical Research Promotion Center, Gifu University Hospital, Gifu, Japan.
Yoshinori IkehataDepartment of Urology, University of Toyama, Toyama, Japan.
Akinori NakayamaDepartment of Urology, Dokkyo Medical University Saitama Medical Center, Koshigaya, Japan.
Masahiro ToideDepartment of Urology, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital, Tokyo, Japan.
Tatsuaki YonedaDepartment of Urology, Seirei Hamamatsu General Hospital, Hamamatsu, Japan.
Kazushige SakaguchiDepartment of Urology, Toranomon Hospital, Tokyo, Japan.
Jun TeishimaDepartment of Urology, Kobe City Hospital Organization Kobe City Medical Center West Hospital, Kobe, Japan.
Takashi KobayashiDepartment of Urology, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Kazuhide MakiyamaDepartment of Urology, Yokohama City University, Yokohama, Japan.
Takahiro InoueDepartment of Nephro-Urologic Surgery and Andrology, Mie University Graduate School of Medicine, Tsu, Japan.
Hiroshi KitamuraDepartment of Urology, University of Toyama, Toyama, Japan.
Kazutaka SaitoDepartment of Urology, Dokkyo Medical University Saitama Medical Center, Koshigaya, Japan.
Fumitaka KogaDepartment of Urology, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital, Tokyo, Japan.
Shinji UrakamiDepartment of Urology, Toranomon Hospital, Tokyo, Japan.
Takuya KoieDepartment of Urology, Gifu University Graduate School of Medicine, Gifu, Japan. koie.takuya.h2@f.gifu-u.ac.jp.
Gifu University · JPKyoto University · JPMie University · JPSocial Insurance Saitama Chuo Hospital · JPTokyo Metropolitan Komagome Hospital · JPToranomon Hospital · JPUniversity of Toyama · JPYokohama City University · JPGifu University Hospital · JPHiroshima City Asa Citizens Hospital · JPKobe City Medical Center West Hospital · JPSeirei Hamamatsu General Hospital · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeWe created a clinically applicable nomogram to predict locally advanced prostate cancer using preoperative parameters and performed external validation using an external independent validation cohort. PATIENTS AND

methodsFrom a retrospective multicenter cohort study of 3622 Japanese patients with prostate cancer who underwent robot-assisted radical prostatectomy at ten institutions, the patients were divided into two groups (MSUG cohort and validation cohort). Locally advanced prostate cancer was defined as pathological T stage ≥ 3a. A multivariable logistic regression model was used to identify factors strongly associated with locally advanced prostate cancer. Bootstrap area under the curve was calculated to assess the internal validity of the prediction model. A nomogram was created as a practical application of the prediction model, and a web application was released to predict the probability of locally advanced prostate cancer.

resultsA total of 2530 and 427 patients in the MSUG and validation cohorts, respectively, met the criteria for this study. On multivariable analysis, initial prostate-specific antigen, prostate volume, number of cancer-positive and cancer-negative biopsy cores, biopsy grade group, and clinical T stage were independent predictors of locally advanced prostate cancer. The nomogram predicting locally advanced prostate cancer was demonstrated (area under the curve 0.72). Using a nomogram cutoff of 0.26, 464 of 1162 patients (39.9%) could be correctly diagnosed with pT3, and 2311 of 2524 patients (91.6%) could avoid underdiagnosis.

conclusionsWe developed a clinically applicable nomogram with external validation to predict the probability of locally advanced prostate cancer in patients undergoing robot-assisted radical prostatectomy.

Indexed as

Prostatic NeoplasmsRoboticsCohort StudiesHumansJapanMaleNeoplasm GradingNomogramsProstateProstatectomyProstate-Specific AntigenRetrospective StudiesProstate-Specific AntigenLocally advanced prostate cancerNomogramProstate cancerRobot-assisted radical prostatectomy

Identifiers

PMID37338747
OpenAlexW4381308403

What OpenQuestion holds

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Registered trials

None linked

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.