ArticlePloS one2025
Construction of a nomogram to predict urethral stricture after transurethral resection of the prostate: A retrospective cohort study.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed.
- Can the use of a visual obturator-assisted resectoscope reduce the incidence of urethral strictures after TURP?: a multicenter propensity-matched study.World journal of urology · 2026Article
- Risk factors and the impact of comorbidities in patients developing urethral stricture after transurethral resection of the prostate.World journal of urology · 2026Article
- The relationship between urethral catheterization before TUR-P and postoperative stricture.World journal of urology · 2026Article
- Article
- Suprapubic transvesical adenoma resection of the prostate (STAR-P): step-by-step technique.The Canadian journal of urology · 2026Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTo investigate the risk factors for urethral stricture (US) in patients with benign prostatic hyperplasia (BPH) after transurethral resection of the prostate (TURP) and to construct a nomogram model with predictive features.
methodsClinical data of 400 patients with BPH who underwent TURP between June 2020 and June 2023 at Chengdu University Hospital were retrospectively collected. The data were divided into US group and no US group. Univariate and multivariate logistic regression analyses were performed sequentially to identify independent risk factors associated with US. Based on the results of the multivariate analysis, a nomogram model predicting the risk of US was constructed. We assessed the discriminatory power and calibration of the models using the C index, ROC curves, and calibration plots. In addition, we performed a decision curve analysis to validate the clinical utility of the model.
resultsData from a total of 400 patients were included in this study, and 35 (8.75%) were diagnosed with US. The results of univariate and multivariate analyses indicated that the following five factors age, prostate size, Preoperative indwelling catheter, Preoperative urethral dilation, Postoperative indwelling catheter time were independent influences on the risk of US. Nomogram model of US was constructed using these independent influences. The area under the curve (AUC) of the subject's operating characteristic was 0.916 (95% CI: 0.868-0.959), and after internal validation, the corrected C-index remained at 0.916. This further validates the accuracy and reliability of the predictive model. Calibration plots and decision curve analyses demonstrated the good clinical value of the column-line diagram model.
conclusionsThe nomogram model we constructed can have some guidance in clinical work.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.