Evidence map›Paper›PMID 33775495›Full record

ArticleClinical oncology (Royal College of Radiologists (Great Britain))2021

Variations in Demand across England for the Magnetic Resonance-Linac Technology, Simulated Utilising Local-level Demographic and Cancer Data in the Malthus Project.

T Mee, A J Vickers, R Jena, K J Kirkby, A Choudhury, N F Kirkby

Abstract read
In one paragraph

Article in Clinical oncology (Royal College of Radiologists (Great Britain)), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  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

6 authors.

T MeeDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK; The Christie NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK. Electronic address: thomas.mee@manchester.ac.uk.
A J VickersDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK; The Christie NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK.
R JenaUniversity of Cambridge Department of Oncology, Cambridge Biomedical Campus, Addenbrooke's Hospital, Cambridge, UK.
K J KirkbyDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK; The Christie NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK.
A ChoudhuryDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK; The Christie NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK.
N F KirkbyDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK; The Christie NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK.

Funding

Cancer Research UK 28870CRUK C309/A21993
6 · The paper itself

Abstract

aimsCancer incidence varies across England, which affects the local-level demand for treatments. The magnetic resonance-linac (MR-linac) is a new radiotherapy technology that combines imaging and treatment. Here we model the demand and demand variations for the MR-linac across England. MATERIALS AND

methodsInitial clinical indications were provided by the MR-linac consortium and introduced into the Malthus radiotherapy clinical decision trees. The Malthus model contains Clinical Commissioning Group (CCG) population, cancer incidence and stage presentation data (for lung and prostate) and simulated the demand for the MR-linac for all CCGs and Radiotherapy Operational Delivery Networks (RODN) across England.

resultsBased on the initial target clinical indications, the MR-linac could service 16% of England's fraction burden. The simulated fractions/million population demand/annum varies between 3000 and 10 600 fractions/million at the CCG level. Focussing only on the cancer population, the simulated fractions/1000 cancer cases demand/annum ranges from 1028 to 1195 fractions/1000 cases. If a national average for fractions/million demand was then used, at the RODN level, the variation from actual annual demand ranges from an overestimation of 8400 fractions to an underestimation of 5800 fractions. When using the national average fractions/1000 cases, the RODN demand varies from an overestimation of 3200 fractions to an underestimation of 3000 fractions.

conclusionsPlanning cancer services is complex due to regional variations in cancer burden. The variations in simulated demand of the MR-linac highlight the requirement to use local-level data when planning to introduce a new technology.

Indexed as

NeoplasmsParticle AcceleratorsEnglandHumansIncidenceMagnetic Resonance ImagingMagnetic Resonance SpectroscopyMaleRadiotherapy Planning, Computer-AssistedTechnologyDemand modellinghealth services needs and demandhealth services researchMR-linacradiotherapyRadiotherapy Operational Delivery Network

Identifiers

PMID33775495
PMCPMC8217906

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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 OpenQuestion graph.