Evidence mapPaperPMID 35922837Full record

ArticleDiagnostic and prognostic research2022

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

Stelios Theophanous, Per-Ivar Lønne, Ananya Choudhury, Maaike Berbee, Andre Dekker, Kristopher Dennis, Alice Dewdney, Maria Antonietta Gambacorta, Alexandra Gilbert, Marianne Grønlie Guren and 18 more

Open access · goldAbstract read
In one paragraph

Article in Diagnostic and prognostic research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.3field-weighted citation impact, top 20% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

28 authors at 18 institutions in 11 countries.

Stelios TheophanousLeeds Institute of Medical Research at St James's, University of Leeds, Leeds, UK. umsth@leeds.ac.uk.ORCID http://orcid.org/0000-0002-4148-3905
Per-Ivar LønneDepartment of Medical Physics, Oslo University Hospital, Oslo, Norway.
Ananya ChoudhuryMAASTRO (Dept of Radiotherapy), GROW School of Oncology and Developmental Biology, Maastricht University and Maastricht University Medical Centre+, P. Debyelaan 25, 6229, Maastricht, Netherlands.
Maaike BerbeeMAASTRO (Dept of Radiotherapy), GROW School of Oncology and Developmental Biology, Maastricht University and Maastricht University Medical Centre+, P. Debyelaan 25, 6229, Maastricht, Netherlands.
Andre DekkerMAASTRO (Dept of Radiotherapy), GROW School of Oncology and Developmental Biology, Maastricht University and Maastricht University Medical Centre+, P. Debyelaan 25, 6229, Maastricht, Netherlands.
Kristopher DennisThe Ottawa Hospital and the University of Ottawa, Ottawa, Canada.
Alice DewdneyWeston Park Hospital, Sheffield, UK.
Maria Antonietta GambacortaFondazione Policlinico Universitario A. Gemelli IRCCS, Università Cattolica S.Cuore, Rome, Italy.
Alexandra GilbertLeeds Institute of Medical Research at St James's, University of Leeds, Leeds, UK.
Marianne Grønlie GurenDepartment of Oncology, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
Lois HollowayIngham Research Institute and Liverpool Hospital, Liverpool, New South Wales, Australia.
Rashmi JadonAddenbrooke's Hospital, Cambridge, UK.
Rohit KochharThe Christie NHS Foundation Trust, Manchester, UK.
Ahmed Allam MohamedRWTH Aachen University Medical Centre, Aachen, Germany.
Rebecca MuirheadOxford University Hospitals NHS Foundation Trust, Oxford, UK.
Oriol ParésChampalimaud Foundation, Lisbon, Portugal.
Lukasz RaszewskiGreater Poland Cancer Centre, Poznań, Poland.
Rajarshi RoyHull University Teaching Hospitals NHS Trust, Hull, UK.
Andrew ScarsbrookLeeds Institute of Medical Research at St James's, University of Leeds, Leeds, UK.
David Sebag-MontefioreLeeds Institute of Medical Research at St James's, University of Leeds, Leeds, UK.
Emiliano SpeziCardiff University, Cardiff, UK.
Karen-Lise Garm SpindlerAarhus University Hospital, Aarhus, Denmark.
Baukelien van TriestThe Netherlands Cancer Institute-Antoni van Leeuwenhoek (NKI-AVL), Amsterdam, The Netherlands.
Vassilios VassiliouBank of Cyprus Oncology Centre, Nicosia, Cyprus.
Eirik Malinen *Department of Medical Physics, Oslo University Hospital, Oslo, Norway.
Leonard WeeMAASTRO (Dept of Radiotherapy), GROW School of Oncology and Developmental Biology, Maastricht University and Maastricht University Medical Centre+, P. Debyelaan 25, 6229, Maastricht, Netherlands.
Ane L Appelt *Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, UK.
atomCAT consortium
University of Leeds · GBMaastricht University Medical Centre · NLOslo University Hospital · NOThe Netherlands Cancer Institute · NLAarhus University Hospital · DKAddenbrooke's Hospital · GBBank of Cyprus Oncology Center · CYCardiff University · GBChampalimaud Foundation · PTGreater Poland Cancer Center · PLIstituti di Ricovero e Cura a Carattere Scientifico · ITLiverpool Hospital · AUOxford University Hospitals NHS Trust · GBRWTH Aachen University · DEThe Christie NHS Foundation Trust · GBUniversity of Hull · GBUniversity of Ottawa · CAWeston Park Cancer Centre · GB

Funding

Cancer Research UK 28301Cancer Research UK 28832Cancer Research UK C19942/A28832Yorkshire Cancer Research L389AA
6 · The paper itself

Abstract

backgroundAnal 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.

methodsThis 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.

Indexed as

Anal cancerChemoradiotherapyDistributed learningFederated learningFreedom from distant metastasisLocoregional controloutcome modellingOverall survivalSquamous cell carcinoma

Identifiers

PMID35922837
PMCPMC9351222
OpenAlexW4289687832

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.