Evidence map›Paper›PMID 37814225›Full record

ArticleBMC public health2023

Demographic, health, and prognostic characteristics of Australians with liver cancer: a cohort study of linked data in New South Wales for informing cancer control.

David Roder, David Banham, Jacob George, Shelley Rushton, Tracey O'Brien

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.9field-weighted citation impact, top 20% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. 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

5 authors at 3 institutions in 1 country.

David RoderCancer Institute NSW, NSW Government, Sydney, NSW, Australia.ORCID http://orcid.org/0000-0001-6442-4409
David BanhamCancer Institute NSW, NSW Government, Sydney, NSW, Australia. david.banham@health.nsw.gov.au.ORCID http://orcid.org/0000-0001-6869-7236
Jacob GeorgeStorr Liver Centre, The Westmead Institute of Medical research, Westmead Hospital and University of Sydney, Sydney, NSW, Australia.ORCID http://orcid.org/0000-0002-8421-5476
Shelley RushtonCancer Institute NSW, NSW Government, Sydney, NSW, Australia.
Tracey O'BrienCancer Institute NSW, NSW Government, Sydney, NSW, Australia.ORCID http://orcid.org/0000-0002-5759-6162
Government of New South Wales · AUNew South Wales Department of Health · AUThe University of Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAustralian age-standardized incidence and death rates for liver cancer are lower than world averages, but increasing as in other economically advanced western countries. World Health Organization emphasizes the need to address sociodemographic disparities in cancer risk. A more detailed sociodemographic risk profiling was undertaken for liver cancer in New South Wales (NSW) by diagnostic stage, than possible with NSW Cancer Registry (NSWCR) alone, by incorporating linked data from the Australian Bureau of Statistics (ABS). The purpose was to inform targeting and monitoring of cancer services.

methodsThe ABS manages the Multi-Agency Data Integration Project (MADIP) which includes a wide range of health, educational, welfare, census, and employment data. These data were linked at person level to NSWCR liver cancer registrations for the period post 2016 census to December 2018. De-identified data were analyzed. Sex-specific age-adjusted odds ratios (95%CIs) of liver cancer were derived using logistic regression by age, country of birth, residential remoteness, proficiency in spoken English, household income, employment status, occupation type, educational attainment, sole person household, joblessness, socioeconomic status, disability status, multimorbidity, and other health-related factors, including GP consultations. These data complement the less detailed sociodemographic data available from the NSWCR, with alignment of numerators and population denominators for accurate risk assessment.

resultsResults indicate liver cancer disproportionately affects population members already experiencing excess social and health disadvantage. Examples where 95% confidence intervals of odds ratios of liver cancer were elevated included having poor English-speaking proficiency, limited education, housing authority tenancy, living in sole-person households, having disabilities, multiple medicated conditions, and being carers of people with a disability. Also, odds of liver cancer were higher in more remote regions outside major cities, and in males, with higher odds of more advanced cancer stages (degrees of spread) at diagnosis in more remote regions.

conclusionsLinked data enabled more detailed risk profiling than previously possible. This will support the targeting of cancer services and benchmarking.

Indexed as

Liver NeoplasmsSemantic WebAustraliaCensusesCohort StudiesFemaleHumansLogistic ModelsMaleNew South WalesPrognosisData linkageLiver cancerRisk factors – demographic factors

Identifiers

PMID37814225
PMCPMC10563226
OpenAlexW4387460950

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.