Evidence map›Paper›PMID 38149419›Full record

ArticleBMJ open2023

ARCHERY: a prospective observational study of artificial intelligence-based radiotherapy treatment planning for cervical, head and neck and prostate cancer - study protocol.

Ajay Aggarwal, Laurence Edward Court, Peter Hoskin, Isabella Jacques, Mariana Kroiss, Sarbani Laskar, Yolande Lievens, Indranil Mallick, Rozita Abdul Malik, Elizabeth Miles and 10 more

Registry-linked trialOpen access · goldAbstract readClinical Trial Protocol
PubMed Full text at PMC Publisher
In one paragraph

Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05653063 (ARCHERY - Artificial Intelligence Based Radiotherapy Treatment Planning for Cervical, Head and Neck and Prostate Cancer), which is not on this map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.4field-weighted citation impact, top 7% 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.

NCT05653063 active not recruitingnot on this map

ARCHERY - Artificial Intelligence Based Radiotherapy Treatment Planning for Cervical, Head and Neck and Prostate Cancer

TypeobservationalSponsorUniversity College, LondonRan2023 to 2026Enrolled1,029ConditionsCancer of Prostate, Cancer Head Neck, Cancer CervixArmsA web-based artificial intelligence (AI) auto-planning tool
3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
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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

20 authors at 12 institutions in 7 countries.

Ajay AggarwalInstitute of Clinical Trials and Methodology - MRC CTU at UCL, University College London, London, UK a.aggarwal@ucl.ac.uk.
Laurence Edward CourtMD Anderson Cancer Center, University of Texas, Houston, Texas, USA.
Peter HoskinDepartment of Oncology, The Christie NHS Foundation Trust, Manchester, UK.
Isabella JacquesInstitute of Clinical Trials and Methodology - MRC CTU at UCL, University College London, London, UK.
Mariana KroissNational Radiotherapy Trials Quality Assurance Group, Mount Vernon Hospital, Northwood, UK.
Sarbani LaskarDepartment of Radiation Oncology, Tata Memorial Hospital, Mumbai, Maharashtra, India.
Yolande LievensGhent University Hospital, Gent, Belgium.
Indranil MallickDepartment of Radiation Oncology, Tata Memorial Center, Kolkata, West Bengal, India.
Rozita Abdul MalikUniversity of Malaya, Kuala Lumpur, Wilayah Persekutuan, Malaysia.
Elizabeth MilesNational Radiotherapy Trials Quality Assurance Group, Mount Vernon Hospital, Northwood, UK.
Issa MohamadKing Hussein Cancer Center, Amman, Jordan.
Claire MurphyInstitute of Clinical Trials and Methodology - MRC CTU at UCL, University College London, London, UK.ORCID 0009-0001-1160-0058
Matthew NankivellInstitute of Clinical Trials and Methodology - MRC CTU at UCL, University College London, London, UK.
Jeannette ParkesUniversity of Cape Town, Rondebosch, South Africa.
Mahesh ParmarInstitute of Clinical Trials and Methodology - MRC CTU at UCL, University College London, London, UK.ORCID 0000-0003-0166-1700
Carol RoachInstitute of Clinical Trials and Methodology - MRC CTU at UCL, University College London, London, UK.
Hannah SimondsStellenbosch University, Stellenbosch, Western Cape, South Africa.
Julie TorodeKing's College London, London, UK.
Barbara VanderstraetenGhent University Hospital, Gent, Belgium.
Ruth LangleyInstitute of Clinical Trials and Methodology - MRC CTU at UCL, University College London, London, UK.
MRC Clinical Trials Unit at UCL · GBGhent University Hospital · BEMount Vernon Hospital · GBTata Memorial Hospital · INKing Hussein Cancer Center · JOKing's College London · GBLondon School of Hygiene & Tropical Medicine · GBStellenbosch University · ZAThe Christie NHS Foundation Trust · GBThe University of Texas MD Anderson Cancer Center · USUniversity of Cape Town · ZAUniversity of Malaya · MY

Funding

ARCHERY: Artificial Intelligence based Radiotherapy treatment planning for Cervical and Head and Neck cancerU01CA269143 · NCI · UNIVERSITY COLLEGE LONDON · PI Ajay Aggarwal · 2022 to 2026
$1.6M
Medical Research Council MC_UU_00004/01NCI NIH HHS U01 CA269143
6 · The paper itself

Abstract

introductionFifty per cent of patients with cancer require radiotherapy during their disease course, however, only 10%-40% of patients in low-income and middle-income countries (LMICs) have access to it. A shortfall in specialised workforce has been identified as the most significant barrier to expanding radiotherapy capacity. Artificial intelligence (AI)-based software has been developed to automate both the delineation of anatomical target structures and the definition of the position, size and shape of the radiation beams. Proposed advantages include improved treatment accuracy, as well as a reduction in the time (from weeks to minutes) and human resources needed to deliver radiotherapy.

methodsARCHERY is a non-randomised prospective study to evaluate the quality and economic impact of AI-based automated radiotherapy treatment planning for cervical, head and neck, and prostate cancers, which are endemic in LMICs, and for which radiotherapy is the primary curative treatment modality. The sample size of 990 patients (330 for each cancer type) has been calculated based on an estimated 95% treatment plan acceptability rate. Time and cost savings will be analysed as secondary outcome measures using the time-driven activity-based costing model. The 48-month study will take place in six public sector cancer hospitals in India (n=2), Jordan (n=1), Malaysia (n=1) and South Africa (n=2) to support implementation of the software in LMICs. ETHICS AND DISSEMINATION: The study has received ethical approval from University College London (UCL) and each of the six study sites. If the study objectives are met, the AI-based software will be offered as a not-for-profit web service to public sector state hospitals in LMICs to support expansion of high quality radiotherapy capacity, improving access to and affordability of this key modality of cancer cure and control. Public and policy engagement plans will involve patients as key partners.

Indexed as

Artificial IntelligenceProstatic NeoplasmsHumansMaleObservational Studies as TopicProspective StudiesRadiotherapy Planning, Computer-AssistedSoftwareAdult oncologyONCOLOGYRADIOTHERAPY

Identifiers

PMID38149419
PMCPMC10711912
OpenAlexW4389462571

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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 OpenQuestion graph.