Evidence map›Paper›PMID 35638089›Full record

ArticleEuropean urology open science2022

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.

Nnenaya Agochukwu-Mmonu, Adharsh Murali, Daniela Wittmann, Brian Denton, Rodney L Dunn, James Montie, James Peabody, David Miller, Karandeep Singh, Michigan Urological Surgery Improvement Collaborative

Open access · goldAbstract read
In one paragraph

Article in European urology open science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
2.1field-weighted citation impact, top 12% 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Observational
  5. Review
  6. Article
  7. Surgical and non-surgical predictors of long term erectile function after robot assisted radical prostatectomy.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2024
    Article
  8. Article
  9. Review
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

10 authors at 4 institutions in 1 country.

Nnenaya Agochukwu-MmonuDepartment of Urology, New York University, New York, NY, USA.
Adharsh MuraliProvidence Health and Services, Rentan, WA, USA.
Daniela WittmannDepartment of Urology, University of Michigan Medical School, Ann Arbor, MI, USA.
Brian DentonDepartment of Urology, University of Michigan Medical School, Ann Arbor, MI, USA.
Rodney L DunnDepartment of Urology, University of Michigan Medical School, Ann Arbor, MI, USA.
James MontieDepartment of Urology, University of Michigan Medical School, Ann Arbor, MI, USA.
James PeabodyDepartment of Urology, Henry Ford Health System, Detroit, MI, USA.
David MillerDepartment of Urology, University of Michigan Medical School, Ann Arbor, MI, USA.
Karandeep SinghDepartment of Urology, University of Michigan Medical School, Ann Arbor, MI, USA.
Michigan Urological Surgery Improvement Collaborative
University of Michigan–Ann Arbor · USHenry Ford Health System · USNew York University · USProvidence Health & Services · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Radical prostatectomy (RP) is the most common definitive treatment for men with intermediate-risk prostate cancer and is frequently complicated by erectile dysfunction. Objective: To develop and validate models to predict 12- and 24-month post-RP sexual function. Design setting and participants: Using Michigan Urological Surgery Improvement Collaborative (MUSIC) registry data from 2016 to 2021, we developed dynamic, multivariate, random-forest models to predict sexual function recovery following RP. Model factors (established a priori) included baseline patient characteristics and repeated assessments of sexual satisfaction, and Expanded Prostate Cancer Index Composite 26 (EPIC-26) overall scores and sexual domain questions. Outcome measurements and statistical analysis: We evaluated three outcomes related to sexual function: (1) the EPIC-26 sexual domain score (range 0-100); (2) the EPIC-26 sexual domain score dichotomized at ≥73 for "good" function; and (3) a dichotomized variable for erection quality at 12 and 24 months after RP. A gradient-boosting decision tree was used for the prediction models, which combines many decision trees into a single model. We evaluated the performance of our model using the root mean squared error (RMSE) and mean absolute error (MAE) for the EPIC-26 score as a continuous variable, and the area under the receiver operating characteristic curve (AUC) for the dichotomized EPIC-26 sexual domain score (SDS) and erection quality. All analyses were conducted using R v3.6.3. Results and limitations: We identified 3983 patients at 12 months and 2494 patients at 24 months who were randomized to the derivation cohort at 12 and 24 months, respectively. Using baseline information only, our model predicted the 12-month EPIC-26 SDS with RMSE of 24 and MAE of 20. The AUC for predicting EPIC-26 SDS ≥73 (a previously published threshold) was 0.82. Our model predicted 24-month EPIC-26 SDS with RMSE of 26 and MAE of 21, and AUC for SDS ≥73 of 0.81. Inclusion of post-RP data improved the AUC to 0.91 and 0.94 at 12 and 24 months, respectively. A web tool has also been developed and is available at https://ml4lhs.shinyapps.io/askmusic_prostate_pro/. Conclusions: Our model provides a valid way to predict sexual function recovery at 12 and 24 months after RP. With this dynamic, multivariate (multiple outcomes) model, accurate predictions can be made for decision-making and during survivorship, which may reduce decision regret. Patient summary: Our prediction model allows patients considering prostate cancer surgery to understand their probability before and after surgery of recovering their erectile function and may reduce decision regret.

Indexed as

Machine learningPatient educationPrediction modelProstate cancerSexual function

Identifiers

PMID35638089
PMCPMC9142747
OpenAlexW4224304870

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.