ArticleEuropean urology2020
Development and Internal Validation of a Web-based Tool to Predict Sexual, Urinary, and Bowel Function Longitudinally After Radiation Therapy, Surgery, or Observation.
Article in European urology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
What it found
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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
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Variation across operating sites in urinary and sexual outcomes after radical prostatectomy in localized and locally advanced prostate cancer.World journal of urology · 2022Trial
- Late Functional Outcomes After Robot-Assisted Radical Prostatectomy: Impact of Baseline and Perioperative Risk Factors.Cancers · 2026Article
- Systematic development of a patient-reported ONCOlogical-ROUTinE-Screening (ONCO-ROUTES) procedure at the University Cancer Center Regensburg.Journal of cancer research and clinical oncology · 2024Article
- External validation of predictive models of sexual, urinary, bowel and hormonal function after surgery in prostate cancer subjects.BMC urology · 2024Article
- A comparison of machine learning models for predicting urinary incontinence in men with localized prostate cancer.Frontiers in oncology · 2023Article
- Development and external validation of multivariate prediction models for erectile dysfunction in men with localized prostate cancer.PloS one · 2023Article
- Observational
- Development and Validation of Dynamic Multivariate Prediction Models of Sexual Function Recovery in Patients with Prostate Cancer Undergoing Radical Prostatectomy: Results from the MUSIC Statewide Collaborative.European urology open science · 2022Article
- Pelvic Radiation Disease.Clinics in colon and rectal surgery · 2022Review
- A novel mHealth App (RyPros) for prostate cancer management: an accessibility and acceptability study.Translational andrology and urology · 2021Article
- Risk stratification for the prognosis of patients with chemoresistant urothelial cancer treated with pembrolizumab.Cancer science · 2021Article
- Risk stratification tools in prostate cancer, where do we stand?Translational andrology and urology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors.
Funding
Abstract
backgroundShared decision making to guide treatment of localized prostate cancer requires delivery of the anticipated quality of life (QOL) outcomes of contemporary treatment options (including radical prostatectomy [RP], intensity-modulated radiation therapy [RT], and active surveillance [AS]). Predicting these QOL outcomes based on personalized features is necessary.
objectiveTo create an easy-to-use tool to predict personalized sexual, urinary, bowel, and hormonal function outcomes after RP, RT, and AS. DESIGN, SETTING, AND
participantsA prospective, population-based cohort study was conducted utilizing US cancer registries of 2563 men diagnosed with localized prostate cancer in 2011-2012.
interventionPatient-reported urinary, sexual, and bowel function up to 5 yr after treatment. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Patient-reported urinary, sexual, bowel, and hormonal function through 5 yr after treatment were collected using the 26-item Expanded Prostate Index Composite (EPIC-26) questionnaire. Comprehensive models to predict domain scores were fit, which included age, race, D'Amico classification, body mass index, EPIC-26 baseline function, treatment, and standardized scores measuring comorbidity, general QOL, and psychosocial health. We reduced these models by removing the instrument scores and replacing D'Amico classification with prostate-specific antigen (PSA) and Gleason score. For the final model, we performed bootstrap internal validation to assess model calibration from which an easy-to-use web-based tool was developed. RESULTS AND LIMITATIONS: The prediction models achieved bias-corrected R-squared values of 0.386, 0.232, 0.183, 0.214, and 0.309 for sexual function, urinary incontinence, urinary irritative, bowel, and hormonal domains, respectively. Differences in R-squared values between the comprehensive and parsimonious models were small in magnitude. Calibration was excellent. The web-based tool is available at https://statez.shinyapps.io/PCDSPred/.
conclusionsFunctional outcomes after treatment for localized prostate cancer can be predicted at the time of diagnosis based on age, race, PSA, biopsy grade, baseline function, and a general question regarding overall health. Providers and patients can use this prediction tool to inform shared decision making. PATIENT SUMMARY: In this report, we studied patient-reported sexual, urinary, hormonal, and bowel function through 5 yr after treatment with radical prostatectomy, radiation therapy, or active surveillance for localized prostate cancer. We developed a web-based predictive tool that can be used to predict one's outcomes after treatment based on age, race, prostate-specific antigen, biopsy grade, pretreatment baseline function, and a general question regarding overall health. We hope both patients and providers can use this tool to better understand expected outcomes after treatment, further enhancing shared decision making between providers and patients.
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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.