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The atomCAT2 project aims to develop and validate outcome prediction models for anal cancer treated with definitive chemoradiotherapy through distributed learning. These models will be based on data from patients treated with conformal radiotherapy techniques across multiple international centres, without any individual level patient data leaving the institution it originates from, therefore preserving patient data privacy.

The atomCAT2 project will analyse retrospective data from anal cancer patients treated with (chemo)radiotherapy across institutions in the UK and internationally. The study aims to develop and validate outcome prediction models using baseline patient characteristics and simple treatment-related factors. It will use distributing learning methodology, which facilitates multi-centre data analysis without individual patient data leaving the local data repository. This will allow us to examine which factors predict for effect of radiotherapy on the primary cancer, and which factors predict for metastatic spread. Ultimately, this could aid in the design of better trials for anal cancer as well as improve treatment for future patients.

Additional file 1: Appendix 1. Data dictionary

Additional file 2: Appendix 2. Specification of secondary models

Additional file 1: Appendix A. Full search strategies employed in Embase and Medline to identify relevant papers between January 1st 2000 and June 30th 2020. Appendix B. Complete results from the study quality appraisal by both reviewers (ST and RS), including the assessment criteria used. Y: Yes. N: No. NR: Not reported. Appendix C. Complete overview of study characteristics, including the predictors tested in each study. NR: not reported. SCC: Squamous cell carcinoma. RT: radiotherapy. CRT: chemoradiotherapy. MMC: Mitomycin C. Appendix D. Outcome definitions given in each study, stratified into nine categories. The final stratification yielded three disease activity outcome categories and six survival outcome categories. Appendix E. All outcomes reported in each study, along with all factors tested in both univariable and multivariable analysis. Appendix F. Clinical factors identified as prognostic for worse outcomes through univariable and multivariable analysis, stratified by outcome. Where available, factor effects and parameterisation used for analysis are also included. Appendix G. Biomarkers identified as prognostic for worse outcomes through univariable and multivariable analysis, stratified by outcome. Where available, factor effects and parameterisation used for analysis are also included. Appendix H. Imaging factors identified as prognostic for worse outcomes through univariable and multivariable analysis, stratified by outcome. Where available, factor effects are also included.