Evidence map›Paper›PMID 40240678›Full record

Observational studyInternational wound journal2025

Lymphoedema Development Following a Cancer Diagnosis: An Anonymised Data Linkage Study in Wales, United Kingdom.

Ioan Humphreys, Alan Watkins, Ashley Akbari, Rowena Griffiths, Marie Gabe-Walters, Melanie Thomas, Cheryl Pike, Angela Williams, Tom Dobbs, John Gibson and 2 more

Abstract readObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in International wound journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

12 authors.

Ioan HumphreysSchool of Health and Social Care, Faculty of Medicine, Health and Life Sciences, Swansea University, Swansea, UK.ORCID https://orcid.org/0000-0001-7993-0179
Alan WatkinsSwansea University Medical School, Faculty of Medicine, Health and Life Sciences, Swansea University, Swansea, UK.
Ashley AkbariSwansea University Medical School, Faculty of Medicine, Health and Life Sciences, Swansea University, Swansea, UK.ORCID https://orcid.org/0000-0003-0814-0801
Rowena GriffithsLymphoedema UK Clinical Network, Swansea Bay University Health Board, UK.
Marie Gabe-WaltersLymphoedema UK Clinical Network, Swansea Bay University Health Board, UK.
Melanie ThomasLymphoedema UK Clinical Network, Swansea Bay University Health Board, UK.ORCID https://orcid.org/0000-0001-6631-9629
Cheryl PikeLymphoedema UK Clinical Network, Swansea Bay University Health Board, UK.
Angela WilliamsSwansea University Medical School, Faculty of Medicine, Health and Life Sciences, Swansea University, Swansea, UK.
Tom DobbsSwansea University Medical School, Faculty of Medicine, Health and Life Sciences, Swansea University, Swansea, UK.
John GibsonSwansea University Medical School, Faculty of Medicine, Health and Life Sciences, Swansea University, Swansea, UK.
Iain S WhitakerSwansea University Medical School, Faculty of Medicine, Health and Life Sciences, Swansea University, Swansea, UK.
Hayley A HutchingsSwansea University Medical School, Faculty of Medicine, Health and Life Sciences, Swansea University, Swansea, UK.

Funding

NHS
6 · The paper itself

Abstract

This observational cohort study explored lymphoedema development following a cancer diagnosis and whether demographic factors impacted the time to lymphoedema development. We identified cases through the Secure Anonymised Information Linkage (SAIL) Databank. We used cancer diagnostic codes to identify a cohort of six broad cancer 'types'. We independently used lymphoedema diagnostic codes to identify a cohort who developed lymphoedema. We linked these two cohorts to develop a single cohort of cases and describe the number of cases who went on to develop lymphoedema after a cancer diagnosis, and the time to lymphoedema diagnosis. We used Cox regression models to calculate hazard ratios and produced survival curves to explore whether pre-defined factors (gender, age, deprivation, cancer type) had any impact on time to lymphoedema development. We identified 7538 cases of lymphoedema development after a cancer diagnosis, relating to 7279 people. There was considerable variation in the time to diagnosis, with a mean and standard deviation of 483.3 (701.8) days. Cancer type was the single most important factor in explaining time to lymphoedema diagnosis. Time to lymphoedema was shortest in breast cancer. A large number of breast cancer cases have undergone surgery, and this may account for the earlier development of lymphoedema. Consideration should be made of risk factors for lymphoedema development in order to allow for more targeted treatment plans that could improve health-related quality of life for patients.

Indexed as

LymphedemaNeoplasmsAdultAgedAged, 80 and overCohort StudiesFemaleHumansMaleMiddle AgedWalescancerdiagnosislinked routine datalymphoedemarisk factors

Identifiers

PMID40240678
PMCPMC12003098

What OpenQuestion holds

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LicenceCC BY
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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.