Socioeconomic inequality in treatment of acute myeloid leukaemia (AML) in England, 2015-2022: A population-based study.

Koki Shimizu, Mari Kajiwara Saito, Camille Maringe, Yasushi Miyazaki, Bernard Rachet

Abstract read

In one paragraph

Article in British journal of haematology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Koki ShimizuInequalities in Cancer Outcomes Network, Department of Health Services Research and Policy, Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK.ORCID https://orcid.org/0000-0003-3549-9000

Mari Kajiwara SaitoInequalities in Cancer Outcomes Network, Department of Health Services Research and Policy, Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK.

Camille MaringeInequalities in Cancer Outcomes Network, Department of Health Services Research and Policy, Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK.ORCID https://orcid.org/0000-0002-8739-9565

Yasushi MiyazakiDepartment of Haematology, Atomic Bomb Disease Institute, Nagasaki University, Nagasaki, Japan.

Bernard RachetInequalities in Cancer Outcomes Network, Department of Health Services Research and Policy, Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK.

Funding

Cancer Research UK EPNCZS34Nagasaki University

6 · The paper itself

Abstract

The socioeconomic inequality in acute myeloid leukaemia (AML) survival may be driven by differential access to intensive chemotherapy (ICT). We aimed to quantify socioeconomic inequality in the receipt of ICT among patients with AML in England and identify its key drivers. We evaluated 10 495 patients with de novo AML identified in the national cancer registry of England (2015-2022) along with their area-deprivation status, as a measure of socioeconomic inequality, and treatment information based on linkage databases. We related prevalence of the ICT receipt to deprivation with multivariable-adjusted generalised regression and mixed-effects probit regression. Overall, 5190 patients (49%) received ICT. The patients in the most deprived area were 6.1% less likely to receive ICT than those in the least deprived area. The differences in the prevalence measures varied across the 125 administrative clusters of health service units. If all patients had access to ICT similar to the least deprived patients, 247 more patients would receive ICT. Of the deprivation effect, 94% was estimated to be attributable to the variability among administrative clusters. Despite universal healthcare coverage, socioeconomic inequality exists in AML treatment in England. The inequality may be driven by cluster-level variations such as institutional culture and resource capacity.

Indexed as

Healthcare DisparitiesLeukemia, Myeloid, AcuteAdolescentAdultAgedAged, 80 and overEnglandFemaleHumansLow Socioeconomic StatusMaleMiddle AgedRegistriesSocioeconomic Disparities in HealthSocioeconomic FactorsYoung Adultacute myeloid leukaemiaEnglandNHS Trustsocioeconomic inequalities

Identifiers

PMID42452790

DOI10.1111/bjh.70695

PMCPMC13570205

What OpenQuestion holds

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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.