Evidence map›Paper›PMID 42319727›Full record

ArticleJournal of robotic surgery2026

Predicting extraperitoneal ssRARP difficulty: an MRI-based nomogram.

Jiapeng Liu, Qiansheng Zhang, Fuyang Lin, Gaoyuanzhi Yue, Yingpan Huang, Binghao Zeng, Chao Cai, Di Gu, Yongda Liu

Abstract read
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In one paragraph

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. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  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

9 authors.

Jiapeng Liu *Department of Urology and Guangdong Key Laboratory of Urology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510230, Guangdong, China.
Qiansheng Zhang *Department of Urology and Guangdong Key Laboratory of Urology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510230, Guangdong, China.
Fuyang Lin *Department of Urology and Guangdong Key Laboratory of Urology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510230, Guangdong, China.
Gaoyuanzhi YueDepartment of Urology and Guangdong Key Laboratory of Urology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510230, Guangdong, China.
Yingpan HuangDepartment of Urology and Guangdong Key Laboratory of Urology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510230, Guangdong, China.
Binghao ZengDepartment of Urology and Guangdong Key Laboratory of Urology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510230, Guangdong, China.
Chao CaiDepartment of Urology and Guangdong Key Laboratory of Urology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510230, Guangdong, China.
Di GuDepartment of Urology and Guangdong Key Laboratory of Urology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510230, Guangdong, China. sveong@163.com.
Yongda LiuDepartment of Urology and Guangdong Key Laboratory of Urology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510230, Guangdong, China. 13719007083@163.com.

Funding

Foundation for Innovative Research Groups of the National Natural Science Foundation of China 82370766Guangzhou Municipal Science and Technology Program key projects 202201020511
6 · The paper itself

Abstract

To develop and validate an MRI-clinical nomogram predicting surgical difficulty in extraperitoneal single-site robot-assisted radical prostatectomy (ssRARP). We retrospectively evaluated 252 patients undergoing extraperitoneal ssRARP. High difficulty was defined using cohort-specific ≥ 75th percentiles for console time (≥ 107.75 min) or estimated blood loss (≥ 50 mL). A nomogram was constructed via multivariable logistic regression and assessed using AUC, calibration plots, bootstrap validation, and decision curve analysis (DCA). High difficulty occurred in 124 patients (49.2%). Independent predictors included higher body mass index (OR = 1.122, P = 0.012), neoadjuvant therapy (OR = 1.972, P = 0.019), larger prostate volume (OR = 1.020, P = 0.003), narrower intertuberous distance (OR = 0.971, P = 0.043), and greater symphysis pubis height (OR = 1.071, P = 0.017). The nomogram showed acceptable discrimination (AUC = 0.675; optimism-corrected C-index = 0.650), good calibration, and positive DCA net benefit (13-92% thresholds). This novel nomogram optimizes patient selection and mitigates perioperative risks. However, because the difficulty thresholds were calibrated to our institution's specific cohort, recalibration is required before direct application to other centers.

Indexed as

Magnetic Resonance ImagingNomogramsProstatectomyProstatic NeoplasmsRobotic Surgical ProceduresAgedHumansMaleMiddle AgedOperative TimeProstateRetrospective StudiesNomogramPelvic dimensionsProstate cancerSingle-site robot-assisted radical prostatectomySurgical difficulty

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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.