Urothelial Cancer - Machine Learning and External Validation of the IDENTIFY Risk Calculator for Patients with Haematuria Referred to Secondary Care for Suspected Urinary Tract Cancer

Aug 6, 2026

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The study evaluates a machine-learning approach to externally validate the IDENTIFY risk calculator for patients presenting with haematuria who are referred to secondary care for suspected urinary tract cancer. It focuses on applying a previously developed predictive tool to new patient cohorts, assessing performance consistency beyond the original development setting. The work supports more reliable risk stratification to guide clinical decision-making in urothelial cancer pathways, emphasizing generalizability and practical use for improving referral and evaluation efficiency in suspected urinary tract malignancy.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages9

Reading Time23 min

AccessFree to download

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Available online

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[available at www . science direct . com](available at www . science direct . com) journal homepage: [www . european urology . com/eu focus](www . european urology . com/eu focus) Urothelial Cancer Machine Learning and External Validation of the IDENTIFY Risk Calculator for Patients with Haematuria Referred to Secondary Care for Suspected Urinary Tract Cancer Sinan Khadhouria,b,*, Artsiom Hramykac, Kevin Gallagher b,d,e, Alexander Light b,f, Simona Ippolitib,g, Marie Edison b,h, Cameron Alexander b,i, Meghana Kulkarnib,j, Eleanor Zimmermann b,k, Arjun Nathan b,e, Luca Orecchial, Ravi Banthiam, Pietro Piazza n, David Mako, Nikolaos Pyrgidisp, Prabhat Narayan q, Pablo Abad Lopez r, Faisal Nawaz s, Trung-Thanh Trant,u, Francesco Clapsv, Donnacha Hogan w, Juan Gomez Rivas x, Santiago Alonso x, Ijeoma Chibuzoy, Beatriz Gutierrez Hidalgo z, Jessica Whitburn aa, Jeremy Teoh bb, Gautier Marcq cc,dd, Alexandra Szostek cc, Jasper Bondadee, Petros Sountoulidesff, Tom Kelsey c, Veeru Kasivisvanathan b,gg, IDENTIFY Study Group y a School of Medicine, University of St Andrews, St Andrews, UK; b British Urological Researchers in Surgical Training (BURST), London, UK; c School of Computer Science, University of St Andrews, St Andrews, UK; d Institute of Cancer and Genetics, University of Edinburgh, Edinburgh, UK; e Division of Surgery and Interventional Science, University College London, London, UK; f Department of Surgery and Cancer, Imperial College London, London, UK; gDepartment of Paediatric Surgery, Hull Royal Inﬁrmary, Hull University Teaching Hospitals, Hull, UK; h Department of Urology, Chelsea and Westminster Hospital, London, UK; i Luton and Dunstable University Hospital, Luton, UK; j Department of Urology, St George’s University Hospitals NHS Foundation Trust, London, UK; k Department of Urology, Southmead Hospital, Bristol, UK; lAOU Policlinico Tor Vergata University Hospital of Rome, Rome, Italy; m University Hospital Coventry Warwickshire, Coventry, UK; n IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy; o Royal Wolverhampton Hospitals, Wolverhamp- y PubMed indexed collaborators: Luca Orecchia, Adan Tijerina, Adrian Simoes, Ahmed Ali, Aisling Nican Riogh, Albert Wong, Alex Kiciak, Alexander Ridgway, Alexandra Szostek, Ananda Dhanasekaran, Anderson Cheong, Andrew Atayi, Ashna Ashpak, Beatriz Gutierrez Hidalgo, Bernardo Teixeira, Carlo Maria Scornajenghi, Carolina Marramaque, Charmian Reynoldson, Christopher Ho Chee Kong, Claire Crewe, Daniel Grifﬁths, Daniele Amporore, David Mak, Debashis Sarkar, Desmond Chung Wei Ling, Divya Bheenick, Donnacha Hogan, Dubem Orakwe, Emma Gordon, Enrico Checcucci, Faisal Nawaz, Fernando Ribeiro Gonçalves, Fernando Lozano Palacio, Francesco Prata, Francesco Claps, Francesco Del Giudice, Gaurav Aggarwal, Gautier Marcq, Georgios Hatzichristodoulou, Georgios Karagiannidis, Giacomo Maria Pirola, Giorgio Russo, Hamid Hytham, Hau Chun Khoo, Hesham Abozied, Hiten D Patel, Holly Colvin, Iftikhar Ali, Ijeoma Chibuzo, Ildar Fakhradiyev, Ioannis Sokolakis, Ioannis Tsikopoulos, James Chong, Jasper Bondad, Jayasimha Abbaraju, Jeremy Teoh, Jessica Whitburn, John Hayes, Jose Luis Bauza Quetglas, Jose Antonio Herranz Yague, Juan Gomez Rivas, Juan Colombo Stenstrom, Kathryn Bandeira de Mello, Katie Brodie, Lazaros Tzelves, Lazarou Lazaros, Louise Paramore, Luis Rico, Lydia Lilis, Maha Ullmann, Mahmoud Srour, Matteo Boltri, Mohamed Mustafa, Mohammad Eyad Takahji, Mohammed Almusimie, Mohammud Shakeel Inder, Mostafa Elgamal, Muftah Misurati, MuhammadKabir Ali, Muhannud Binnawara, Nabeela Bhaloo, Natalia Vidal Crespo, Nelson Ernesto Morales Palacios, Nicola Santoni, Nikolaos Pyrgidis, Olivia Hamilton, Pablo Abad Lopez, Pattabiraman Maheshkumar, Petros Sountoulides, Pietro Piazza, Pilar Moreno, Piyush Sarmah, Prabhat Narayan, Ravi Banthia, Richard Matulewicz, Roberto Contieri, Rotimi David, Sabir Mohammad, Sadiq Abu, Santiago Alonso, Simona Ippoliti, Stephan Weber, Suleiman Abuhasanein

FAQs

What is the main purpose of the study described here?

To externally validate the IDENTIFY risk calculator using a machine-learning approach for patients with haematuria referred to secondary care for suspected urinary tract cancer.

What patient group does the IDENTIFY risk calculator target in this work?

Patients with haematuria who are referred to secondary care because of suspected urinary tract cancer.

Why does the study emphasize external validation?

External validation checks whether the predictive tool performs reliably beyond the original development setting, supporting generalizability for clinical use.

Aug 6, 2026

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