Evidence map›Paper›PMID 18253115›Full record

ArticleBritish journal of cancer2008

Population mixing, socioeconomic status and incidence of childhood acute lymphoblastic leukaemia in England and Wales: analysis by census ward.

C A Stiller, M E Kroll, P J Boyle, Z Feng

Abstract read
In one paragraph

Article in British journal of cancer, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 2 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

20 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  20. Biological Entanglement-Like Effect After Communication of Fish Prior to X-Ray Exposure.Dose-response : a publication of International Hormesis Society
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

C A StillerChildhood Cancer Research Group, Department of Paediatrics, University of Oxford, Oxford OX2 6HJUK, UK. charles.stiller@ccrg.ox.ac.uk
M E Kroll
P J Boyle
Z Feng

Funding

Cancer Research UKDepartment of Health
6 · The paper itself

Abstract

In this population-based study of acute lymphoblastic leukaemia (ALL) diagnosed among children aged under 15 years in England and Wales during 1986-1995, we analysed incidence at census ward level in relation to a range of variables from the 1991 census, which could be relevant to theories of infectious aetiology. 'Population-mixing' measures, used as surrogates for quantity and diversity of infections entering the community, were calculated from census data on the origins and destinations of migrants in the year before the census. Incidence at ages 1-4 years tended independently to be higher in rural wards, to increase with the diversity of origin wards from which in-migrants had moved during the year before the census, and to be lower in the most deprived areas as categorised by the Carstairs index. This last association was much weaker when urban/rural status and in-migrants' diversity were allowed for. There was no evidence of association with population mixing or deprivation for ALL diagnosed at ages 0 or 5-14 years. The apparent specificity to the young childhood age group suggests that these associations are particularly marked for precursor B-cell ALL, with the disease more likely to occur when delayed exposure to infection leads to increased immunological stress, as predicted by Greaves. The association with diversity of incomers, especially in rural areas, is also consistent with the higher incidence of leukaemia predicted by Kinlen, where population mixing results in below average herd immunity to an infectious agent.

Indexed as

AdolescentCensusesChildChild, PreschoolEnglandHumansIncidenceInfantInfant, NewbornPrecursor Cell Lymphoblastic Leukemia-LymphomaSocioeconomic FactorsWales

Identifiers

PMID18253115
PMCPMC2266854

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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.