Prediction of the Risk of Biochemical Relapse After Radical Prostatectomy for Prostate Cancer Using Radomics on Pre-therapeutic MRI

Completed

• Conditions: Prostatic Adenocarcinoma

• Registration Number: NCT04063800
• Lead Sponsor: University Hospital, Brest

Brief Summary

With 50% of post-operative biochemical failure, efficient predictive models are needed to guide post-operative management.

Radiomic features are quantitative features extracted from medical imaging, supposed to be correlated with tumor heterogeneity.

We aim to build and test three predictive models (clinical, radiomic and combined models).

Detailed Description

Not available

Study Timeline

• Study Start: 2018-06-26
• Primary Completion: 2018-08-28
• Study Completion: 2018-08-28
• Status Verified: 2019-08
• Study First Submitted: 2019-08-19
• Study First Submitted QC: 2019-08-20
• Study First Posted: 2019-08-21
• Last Update Submitted: 2019-09-11
• Last Update Posted: 2019-09-12

Recruitment & Eligibility

• Status: COMPLETED
• Sex: Male
• Target Recruitment: 195

Inclusion Criteria

• Age > 18yo
• Patients underwent radical prostatectomy
• High-risk prostate cancers: at least 1 criteria (pt3a/pT3b/pT4, R1, Gleason score > 7)

Exclusion Criteria

• No available pre-operative MRI
• No analyzable pre-operative MRI
• proof of lymph-node involvement (cN1/2 or pN1/2)
• post-operative PSA > 0.04ng/mL

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Prediction of biochemical failure	From the date of surgery until data collection (up to 100 months)	Comparison of AUCs between each predictive model

Secondary Outcome Measures

Name	Time	Method
Prediction of survival without biochemical failure	From the date of surgery until data collection (up to 100 months)	Survival analysis: comparison of Kaplan-Meier curves

Trial Locations

Locations (2)

CHRU de Brest; 🇫🇷 Brest, Bretagne, France

Centre Hospitalier de Cornouaille; 🇫🇷 Quimper, Bretagne, France