Evidence map›Paper›PMID 32595164›Full record

ArticleBMJ open2020

Monitoring TNM stage of female breast cancer and survival across the South Australian population, with national and international TNM benchmarking: A population-based cohort study.

Ming Li, David Roder, Katina D'Onise, David Walters, Gelareh Farshid, Elizabeth Buckley, Chris Karapetis, Rohit Joshi, Timothy Price, Amanda Townsend and 5 more

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PubMed Full text at PMC Publisher
In one paragraph

Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
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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

15 authors.

Ming LiCancer Research Institute, University of South Australia, Adelaide, South Australia, Australia.
David RoderCancer Research Institute, University of South Australia, Adelaide, South Australia, Australia David.Roder@unisa.edu.au.ORCID 0000-0001-6442-4409
Katina D'OnisePrevention and Population Health, SA Health Department for Health and Wellbeing, Adelaide, South Australia, Australia.
David WaltersDepartment of Surgery, The Queen Elizabeth Hospital, Woodville South, South Australia, Australia.
Gelareh FarshidFaculty of Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia, Australia.
Elizabeth BuckleyCancer Research Institute, University of South Australia, Adelaide, South Australia, Australia.
Chris KarapetisMedical Oncology, Flinders University, Adelaide, South Australia, Australia.
Rohit JoshiFaculty of Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia, Australia.
Timothy PriceFaculty of Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia, Australia.
Amanda TownsendClinical Cancer Research, The Queen Elizabeth Hospital, Woodville South, South Australia, Australia.
Caroline Louise MillerFaculty of Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia, Australia.ORCID 0000-0001-9723-8047
David CurrowChief Executive Officer, Cancer Institute NSW, Eveleigh, New South Wales, Australia.
Kate PowellHealth Policy Centre, South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia.
Dianne Buranyi-TrevartonSA Clinical Cancer Registry, SA Health Department for Health and Wellbeing, Adelaide, South Australia, Australia.
Ian OlverFaculty of Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveUsing linked cancer registry and administrative data to monitor, tumour, node and metastases (TNM) stage and survival from female breast cancer in Australia.

methodAnalysis of 2000-2014 diagnoses with linked population-based data to investigate: (1) sociodemographic predictors of advanced stage (stages III and IV), using unadjusted and adjusted logistic regression; and (2) sociodemographic factors and stage as predictors of breast cancer survival using competing risk regression.

designPopulation-based registry cohort. SETTING AND

participants14 759 South Australian women diagnosed in 2000-2014. PRIMARY AND SECONDARY OUTCOME MEASURES: Stage and survival.

resultsAt diagnosis, 46% of women were classified as stage I, 39% as stage II, 12% as stage III and 4% as stage IV. After adjusting for sociodemographic factors, advanced stage was more common: (1) for ages <50 years; and although not statistically significant, for ages 80+ years; and (2) in women from socioeconomically disadvantaged areas. Compared with 2000-2004 diagnoses, stage and sociodemographic adjusted risks (sub-HRs (SHRs)) of breast cancer death were lower in 2005-2009 (SHR 0.75, 95% CI 0.67 to 0.83) and 2010-2015 (SHR 0.57, 95% CI 0.48 to 0.67). Compared with stage I, the SHR was 3.87 (95% CI 3.32 to 4.53) for stage II, 10.87 (95% CI 9.22 to 12.81) for stage III, and 41.97 (95% CI 34.78 to 50.65) for stage IV. Women aged 70+ years at diagnosis and those living in the most socioeconomically disadvantaged areas were at elevated risk of breast cancer death, independent of stage and sociodemographic factors.

conclusionsStage varied by age, diagnostic period and socioeconomic status, and was a stronger predictor of survival than other statistically significant sociodemographic predictors. Achieving earlier diagnosis outside the original BreastScreen target of 50-69 years (as applying <2014) and in residents of socioeconomically disadvantaged areas likely would increase cancer survival at a population level.

Indexed as

AgedAged, 80 and overAustraliaBenchmarkingBreast NeoplasmsFemaleHumansMiddle AgedNeoplasm StagingRegistriesSocial ClassSurvival Analysisbreast tumoursepidemiologypublic health

Identifiers

PMID32595164
PMCPMC7322288

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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.