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The ability to accurately predict progression-free survival (PFS) and overall survival (OS) would allow for development of personalised treatment strategies. The aim of the study was to train and external test radiomic\/clinical feature derived time-to-event prediction models.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>Consecutive patients with ASCC treated with curative intent at two large tertiary referral centres with baseline FDG PET-CT were included. Radiomic feature extraction was performed using LIFEx software on the pre-treatment PET-CT. Two distinct predictive models for PFS and OS were trained and tuned at each of the centres, with the best performing models externally tested on the other centres\u2019 patient cohort.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>A total of 187 patients were included from centre 1 (mean age 61.6\u2009\u00b1\u200911.5\u00a0years, median follow up 30\u00a0months, PFS events\u2009=\u200957\/187, OS events\u2009=\u200946\/187) and 257 patients were included from centre 2 (mean age 62.6\u2009\u00b1\u200912.3\u00a0years, median follow up 35\u00a0months, PFS events\u2009=\u200970\/257, OS events\u2009=\u200954\/257). The best performing model for PFS and OS was achieved using a Cox regression model based on age and metabolic tumour volume (MTV) with a training c-index of 0.7 and an external testing c-index of 0.7 (standard error\u2009=\u20090.4).<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>A combination of patient age and MTV has been demonstrated using external validation to have the potential to predict OS and PFS in ASCC patients.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Clinical relevance statement<\/jats:title>\n                <jats:p>A Cox regression model using patients\u2019 age and metabolic tumour volume showed good predictive potential for progression-free survival in external testing. The benefits of a previous radiomics model published by our group could not be confirmed on external testing.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Key Points<\/jats:title>\n                <jats:p><jats:italic>\u2022 A predictive model based on patient age and metabolic tumour volume showed potential to predict overall survival and progression-free survival and was validated on an external test cohort.<\/jats:italic><\/jats:p>\n                <jats:p><jats:italic>\u2022 The methodology used to create a predictive model from age and metabolic tumour volume was repeatable using external cohort data.<\/jats:italic><\/jats:p>\n                <jats:p><jats:italic>\u2022 The predictive ability of positron emission tomography-computed tomography\u2013derived radiomic features diminished when the influence of metabolic tumour volume was accounted for.<\/jats:italic><\/jats:p>\n              <\/jats:sec>","DOI":"10.1007\/s00330-023-10340-9","type":"journal-article","created":{"date-parts":[[2023,11,4]],"date-time":"2023-11-04T10:01:32Z","timestamp":1699092092000},"page":"3194-3204","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Training and external validation of pre-treatment FDG PET-CT-based models for outcome prediction in anal squamous cell carcinoma"],"prefix":"10.1007","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2681-9922","authenticated-orcid":false,"given":"Russell","family":"Frood","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joseph","family":"Mercer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peter","family":"Brown","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ane","family":"Appelt","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hitesh","family":"Mistry","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rohit","family":"Kochhar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew","family":"Scarsbrook","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,11,4]]},"reference":[{"key":"10340_CR1","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1111\/codi.12553","volume":"16","author":"JR Wilkinson","year":"2014","unstructured":"Wilkinson JR, Morris EJA, Downing A et al (2014) The rising incidence of anal cancer in England 1990\u20132010: a population-based study. 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They have not taken part in the review or selection process of this article.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"One of the authors (Dr H Mistry) has significant statistical expertise.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Statistics and biometry"}},{"value":"All patients included within the study gave prospective consent at the time of imaging for their anonymised FDG PET-CT imaging data to be used in research and service development projects.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"As this is a retrospective study, which does not involve patient contact or the alteration of treatment, following discussion with the Research and Innovation Department at Leeds Teaching Hospitals NHS Trust (LTHT), it was agreed that this represented a service improvement project and requirement for formal ethics committee approval was waived for LTHT data collection. Data collection at Christie NHS Foundation Trust (CNFT) was approved by the UK Computer Aided Theragnostics (ukCAT) ethics committee.","order":6,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"Some study subjects or cohorts have been previously reported. The dataset (187 patients) from Leeds has been used for a radiomics-based prediction model which has been published previously\u2014Brown PJ, Zhong J, Frood R, et al (2019) Prediction of outcome in anal squamous cell carcinoma using radiomic feature analysis of pre-treatment FDG PET-CT. Eur J Nucl Med Mol Imaging 46: 2790\u20132799. However, this work looks at a range of different prediction models using the same data set representing new original research. In addition, the current study includes external validation with a large independent dataset not previously published.","order":7,"name":"Ethics","group":{"name":"EthicsHeading","label":"Study subjects or cohorts overlap"}},{"value":"\u2022 retrospective\u2022 diagnostic or prognostic study\u2022 multicenter study","order":8,"name":"Ethics","group":{"name":"EthicsHeading","label":"Methodology"}}]}}