التفاصيل البيبلوغرافية
| العنوان: |
Development, multi-institutional external validation, and algorithmic audit of an artificial intelligence-based Side-specific Extra-Prostatic Extension Risk Assessment tool (SEPERA) for patients undergoing radical prostatectomy: a retrospective cohort study |
| المؤلفون: |
Kwong, Jethro J.C.C., Khondker, Adree, Meng, Eric, Taylor, Nicholas, Kuk, Cynthia, Perlis, Nathan, Kulkarni, Girish G.S., Hamilton, Robert James, Fleshner, Neil Eric, Finelli, Antonio, van der Kwast, Theodorus H., Ali, Amna, Jamal, Munir, Papanikolaou, Frank, Short, Thomas, Srigley, John J.R., Colinet, Valentin, Peltier, Alexandre, Diamand, Romain, Lefebvre, Y., Mandoorah, Qusay, Sanchez-Salas, Rafael, Macek, Petr, Cathelineau, Xavier, Eklund, Martin, Johnson, Alistair Edward William, Feifer, Andrew, Zlotta, Alexandre |
| المصدر: |
The Lancet Digital Health, 5 (7 |
| سنة النشر: |
2023 |
| المجموعة: |
DI-fusion : dépôt institutionnel de l'Université libre de Bruxelles (ULB) |
| مصطلحات موضوعية: |
Généralités |
| الوصف: |
Background: Accurate prediction of side-specific extraprostatic extension (ssEPE) is essential for performing nerve-sparing surgery to mitigate treatment-related side-effects such as impotence and incontinence in patients with localised prostate cancer. Artificial intelligence (AI) might provide robust and personalised ssEPE predictions to better inform nerve-sparing strategy during radical prostatectomy. We aimed to develop, externally validate, and perform an algorithmic audit of an AI-based Side-specific Extra-Prostatic Extension Risk Assessment tool (SEPERA). Methods: Each prostatic lobe was treated as an individual case such that each patient contributed two cases to the overall cohort. SEPERA was trained on 1022 cases from a community hospital network (Trillium Health Partners; Mississauga, ON, Canada) between 2010 and 2020. Subsequently, SEPERA was externally validated on 3914 cases across three academic centres: Princess Margaret Cancer Centre (Toronto, ON, Canada) from 2008 to 2020; L'Institut Mutualiste Montsouris (Paris, France) from 2010 to 2020; and Jules Bordet Institute (Brussels, Belgium) from 2015 to 2020. Model performance was characterised by area under the receiver operating characteristic curve (AUROC), area under the precision recall curve (AUPRC), calibration, and net benefit. SEPERA was compared against contemporary nomograms (ie, Sayyid nomogram, Soeterik nomogram [non-MRI and MRI]), as well as a separate logistic regression model using the same variables included in SEPERA. An algorithmic audit was performed to assess model bias and identify common patient characteristics among predictive errors. Findings: Overall, 2468 patients comprising 4936 cases (ie, prostatic lobes) were included in this study. SEPERA was well calibrated and had the best performance across all validation cohorts (pooled AUROC of 0·77 [95% CI 0·75–0·78] and pooled AUPRC of 0·61 [0·58–0·63]). In patients with pathological ssEPE despite benign ipsilateral biopsies, SEPERA correctly predicted ssEPE in 72 (68%) of 106 ... |
| نوع الوثيقة: |
article in journal/newspaper |
| وصف الملف: |
1 full-text file(s): application/pdf |
| اللغة: |
English |
| العلاقة: |
uri/info:doi/10.1016/S2589-7500(23)00067-5; uri/info:pii/S2589750023000675; uri/info:pmid/37211455; uri/info:scp/85163487583; https://dipot.ulb.ac.be/dspace/bitstream/2013/372090/1/doi_355734.pdfTest; http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/372090Test |
| الإتاحة: |
http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/372090Test |
| رقم الانضمام: |
edsbas.D4D6D746 |
| قاعدة البيانات: |
BASE |
