Evidence map›Paper›PMID 37667231›Full record

SynthesisBMC cancer2023

Clinical trials in cancer screening, prevention and early diagnosis (SPED): a systematic mapping review.

Emma L O'Dowd, Samuel W D Merriel, Vinton W T Cheng, Sam Khan, Lynne M Howells, Dipesh P Gopal, Elizabeth A Roundhill, Paul M Brennan, Philip A J Crosbie, Richard D Neal and 3 more

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in BMC cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
3.0field-weighted citation impact, top 8% 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

3 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
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

13 authors at 8 institutions in 1 country.

Emma L O'Dowd *Department of Respiratory Medicine, Nottingham University Hospitals NHS Trust, Hucknall Road, Nottingham, NG5 1PB, UK. emma.odowd@nottingham.ac.uk.
Samuel W D Merriel *Centre for Primary Care & Health Services Research, University of Manchester, Oxford Road, Manchester, M13 9PL, UK.
Vinton W T ChengLeeds Institute of Medical Research, University of Leeds, Leeds, UK.
Sam KhanLeicester Cancer Research Centre, University of Leicester, Leicester, LE2 7LX, UK.
Lynne M HowellsLeicester Cancer Research Centre, University of Leicester, Leicester, LE2 7LX, UK.
Dipesh P GopalPrimary Care Unit, Centre for Primary Care, Wolfson Institute of Population Health, Queen Mary University, London, UK.
Elizabeth A RoundhillChildren's Cancer Research Group, Leeds Institute of Medical Research, University of Leeds, Leeds, UK.
Paul M BrennanTranslational Neurosurgery, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.
Philip A J CrosbieDivision of Infection, Immunity & Respiratory Medicine, University of Manchester, Manchester, UK.
Richard D NealExeter Medical School, St Luke's Campus, University of Exeter, 1.12 College House, Magdalen Road, EX1 2LU, Exeter, UK.
Karen BrownLeicester Cancer Research Centre, University of Leicester, Leicester, LE2 7LX, UK.
Emma J CrosbieDepartment of Obstetrics and Gynaecology, St Mary's Hospital, Manchester University NHS Foundation Trust, Oxford Road, Manchester, M13 9WL, UK.
David R BaldwinDepartment of Respiratory Medicine, Nottingham University Hospitals NHS Trust, Hucknall Road, Nottingham, NG5 1PB, UK.
University of Leicester · GBNottingham University Hospitals NHS Trust · GBUniversity of Leeds · GBUniversity of Manchester · GBManchester University NHS Foundation Trust · GBQueen Mary University of London · GBUniversity of Edinburgh · GBUniversity of Exeter · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGlobal annual cancer incidence is forecast to rise to 27.5 M by 2040, a 62% increase from 2018. For most cancers, prevention and early detection are the most effective ways of reducing mortality. This study maps trials in cancer screening, prevention, and early diagnosis (SPED) to identify areas of unmet need and highlight research priorities.

methodsA systematic mapping review was conducted to evaluate all clinical trials focused on cancer SPED, irrespective of tumour type. The National Cancer Research Institute (NCRI) portfolio, EMBASE, PubMed and Medline were searched for relevant papers published between 01/01/2007 and 01/04/2020. References were exported into Covidence software and double-screened. Data were extracted and mapped according to tumour site, geographical location, and intervention type.

resultsOne hundred seventeen thousand seven hundred one abstracts were screened, 5157 full texts reviewed, and 2888 studies included. 1184 (52%) trials focussed on screening, 554 (24%) prevention, 442 (20%) early diagnosis, and 85 (4%) a combination. Colorectal, breast, and cervical cancer comprised 61% of all studies compared with 6.4% in lung and 1.8% in liver cancer. The latter two are responsible for 26.3% of global cancer deaths compared with 19.3% for the former three. Number of studies varied markedly according to geographical location; 88% were based in North America, Europe, or Asia.

conclusionsThis study shows clear disparities in the volume of research conducted across different tumour types and according to geographical location. These findings will help drive future research effort so that resources can be directed towards major challenges in cancer SPED.

Indexed as

Liver NeoplasmsUterine Cervical NeoplasmsAsiaBreastEarly Detection of CancerFemaleHumansCancerEarly detection of cancerPreventionScreeningSystematic mappingTrials

Identifiers

PMID37667231
PMCPMC10476302
OpenAlexW4386416789

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.