Evidence map›Paper›PMID 34389805›Full record

ArticleBritish journal of cancer2021

Investigating the inequalities in route to diagnosis amongst patients with diffuse large B-cell or follicular lymphoma in England.

Matthew J Smith, Miguel Angel Luque Fernandez, Aurélien Belot, Matteo Quartagno, Audrey Bonaventure, Sara Benitez Majano, Bernard Rachet, Edmund Njeru Njagi

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in British journal of cancer, 2021. 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
–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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

8 authors.

Matthew J SmithInequalities in Cancer Outcomes Network, Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK. matthew.smith1@lshtm.ac.uk.ORCID http://orcid.org/0000-0002-8502-0056
Miguel Angel Luque FernandezInequalities in Cancer Outcomes Network, Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.ORCID http://orcid.org/0000-0001-6683-5164
Aurélien BelotInequalities in Cancer Outcomes Network, Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.ORCID http://orcid.org/0000-0003-1410-5172
Matteo QuartagnoMRC Clinical Trials Unit, Institute of Clinical Trials and Methodology, University College London, London, UK.
Audrey BonaventureCRESS, Université de Paris, INSERM, UMR 1153, Epidemiology of Childhood and Adolescent Cancers Team, Villejuif, France.
Sara Benitez MajanoInequalities in Cancer Outcomes Network, Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
Bernard RachetInequalities in Cancer Outcomes Network, Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
Edmund Njeru NjagiInequalities in Cancer Outcomes Network, Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.

Funding

Cancer Research UK 18525Cancer Research UK 29018Medical Research Council MC_UU_00004/07
6 · The paper itself

Abstract

introductionDiagnostic delay is associated with lower chances of cancer survival. Underlying comorbidities are known to affect the timely diagnosis of cancer. Diffuse large B-cell (DLBCL) and follicular lymphomas (FL) are primarily diagnosed amongst older patients, who are more likely to have comorbidities. Characteristics of clinical commissioning groups (CCG) are also known to impact diagnostic delay. We assess the association between comorbidities and diagnostic delay amongst patients with DLBCL or FL in England during 2005-2013.

methodsMultivariable generalised linear mixed-effect models were used to assess the main association. Empirical Bayes estimates of the random effects were used to explore between-cluster variation. The latent normal joint modelling multiple imputation approach was used to account for partially observed variables.

resultsWe included 30,078 and 15,551 patients diagnosed with DLBCL or FL, respectively. Amongst patients from the same CCG, having multimorbidity was strongly associated with the emergency route to diagnosis (DLBCL: odds ratio 1.56, CI 1.40-1.73; FL: odds ratio 1.80, CI 1.45-2.23). Amongst DLBCL patients, the diagnostic delay was possibly correlated with CCGs that had higher population densities.

conclusionsUnderlying comorbidity is associated with diagnostic delay amongst patients with DLBCL or FL. Results suggest a possible correlation between CCGs with higher population densities and diagnostic delay of aggressive lymphomas.

Indexed as

AdultAgedAged, 80 and overBayes TheoremComorbidityCross-Sectional StudiesDelayed DiagnosisEnglandFemaleHumansLinear ModelsLymphoma, FollicularLymphoma, Large B-Cell, DiffuseMaleMiddle AgedNeoplasm Staging

Identifiers

PMID34389805
PMCPMC8548410

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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.