Academic Journal

Development and validation of prognostic models for anal cancer outcomes using distributed learning: protocol for the international multi-centre atomCAT2 study

Bibliographic Details
Title: Development and validation of prognostic models for anal cancer outcomes using distributed learning: protocol for the international multi-centre atomCAT2 study
Authors: Stelios Theophanous, Per-Ivar Lønne, Ananya Choudhury, Maaike Berbee, Andre Dekker, Kristopher Dennis, Alice Dewdney, Maria Antonietta Gambacorta, Alexandra Gilbert, Marianne Grønlie Guren, Lois Holloway, Rashmi Jadon, Rohit Kochhar, Ahmed Allam Mohamed, Rebecca Muirhead, Oriol Parés, Lukasz Raszewski, Rajarshi Roy, Andrew Scarsbrook, David Sebag-Montefiore, Emiliano Spezi, Karen-Lise Garm Spindler, Baukelien van Triest, Vassilios Vassiliou, Eirik Malinen, Leonard Wee, Ane L. Appelt, on behalf of the atomCAT consortium
Source: Diagnostic and Prognostic Research, Vol 6, Iss 1, Pp 1-11 (2022)
Publisher Information: BMC, 2022.
Publication Year: 2022
Collection: LCC:Medicine (General)
Subject Terms: Anal cancer, Squamous cell carcinoma, Chemoradiotherapy, Distributed learning, Federated learning, outcome modelling, Medicine (General), R5-920
Description: Abstract Background Anal cancer is a rare cancer with rising incidence. Despite the relatively good outcomes conferred by state-of-the-art chemoradiotherapy, further improving disease control and reducing toxicity has proven challenging. Developing and validating prognostic models using routinely collected data may provide new insights for treatment development and selection. However, due to the rarity of the cancer, it can be difficult to obtain sufficient data, especially from single centres, to develop and validate robust models. Moreover, multi-centre model development is hampered by ethical barriers and data protection regulations that often limit accessibility to patient data. Distributed (or federated) learning allows models to be developed using data from multiple centres without any individual-level patient data leaving the originating centre, therefore preserving patient data privacy. This work builds on the proof-of-concept three-centre atomCAT1 study and describes the protocol for the multi-centre atomCAT2 study, which aims to develop and validate robust prognostic models for three clinically important outcomes in anal cancer following chemoradiotherapy. Methods This is a retrospective multi-centre cohort study, investigating overall survival, locoregional control and freedom from distant metastasis after primary chemoradiotherapy for anal squamous cell carcinoma. Patient data will be extracted and organised at each participating radiotherapy centre (n = 18). Candidate prognostic factors have been identified through literature review and expert opinion. Summary statistics will be calculated and exchanged between centres prior to modelling. The primary analysis will involve developing and validating Cox proportional hazards models across centres for each outcome through distributed learning. Outcomes at specific timepoints of interest and factor effect estimates will be reported, allowing for outcome prediction for future patients. Discussion The atomCAT2 study will analyse one of the largest available cross-institutional cohorts of patients with anal cancer treated with chemoradiotherapy. The analysis aims to provide information on current international clinical practice outcomes and may aid the personalisation and design of future anal cancer clinical trials through contributing to a better understanding of patient risk stratification.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2397-7523
Relation: https://doaj.org/toc/2397-7523
DOI: 10.1186/s41512-022-00128-8
Access URL: https://doaj.org/article/127c2bcc438a47df81818d07dee02177
Accession Number: edsdoj.127c2bcc438a47df81818d07dee02177
Database: Directory of Open Access Journals
Description
ISSN:23977523
DOI:10.1186/s41512-022-00128-8