Evidence map›Paper›PMID 30771221›Full record

ArticleInternational journal of cancer2019

Mortality after breast cancer as a function of time since diagnosis by estrogen receptor status and age at diagnosis.

Harindra Jayasekara, Robert J MacInnis, James A Chamberlain, Gillian S Dite, Nicole M Leoce, James G Dowty, Adrian Bickerstaffe, Aung Ko Win, Roger L Milne, Graham G Giles and 4 more

Abstract read
In one paragraph

Article in International journal of cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Article
  2. Competing risks models with two time scales.Statistical methods in medical research · 2025
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. 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

14 authors.

Harindra JayasekaraCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia.ORCID 0000-0002-2453-0183
Robert J MacInnisCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia.
James A ChamberlainCancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia.
Gillian S DiteCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia.
Nicole M LeoceDepartment of Epidemiology, Mailman School of Public Health, Columbia University, NY, New York.
James G DowtyCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia.
Adrian BickerstaffeCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia.
Aung Ko WinCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia.ORCID 0000-0002-2794-5261
Roger L MilneCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia.
Graham G GilesCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia.
Mary Beth TerryDepartment of Epidemiology, Mailman School of Public Health, Columbia University, NY, New York.
Diana M EcclesCancer Sciences Academic Unit and Southampton Clinical Trials Unit, Faculty of Medicine, University of Southampton and University Hospital Southampton Foundation Trust, Southampton, United Kingdom.
Melissa C SoutheyPrecision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia.
John L HopperCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia.

Funding

Northern California Cooperative Family Registry for Breast CancerU01CA069417 · NCI · NORTHERN CALIFORNIA CANCER CENTER · PI JOHN, ESTHER M. · 1995 to 2010
$22.4M
Core-001U01CA164920 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Irene Andrulis, Sarah Violet Colonna · 2018 to 2026
$17.0M
METROPOLITAN NEW YORK REGISTRY OF BREAST CANCER FAMILIESU01CA069398 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI TERRY, MARY BETH · 1995 to 2010
$10.5M
ONTARIO REGISTRY FOR STUDIES OF FAMILIAL BREAST CANCERU01CA069467 · NCI · CANCER CARE ONTARIO · PI ANDRULIS, IRENE L. · 1995 to 2010
$10.4M
Philadelphia Breast Cancer Family RegistryU01CA069631 · NCI · FOX CHASE CANCER CENTER · PI DALY, MARY BERYL · 1995 to 2010
$7.4M
THE AUSTRALIAN BREAST CANCER FAMILY REGISTRYU01CA069638 · NCI · UNIVERSITY OF MELBOURNE · PI HOPPER, JOHN L · 1995 to 2010
$6.6M
Utah Breast Cancer Family RegistryU01CA069446 · NCI · UNIVERSITY OF UTAH · PI BUYS, SAUNDRA S · 1995 to 2010
$4.6M
National Cancer Institute, US National Institutes of Health CA-06-503NCI NIH HHS U01 CA069398NCI NIH HHS U01 CA069417NCI NIH HHS U01 CA069446NCI NIH HHS U01 CA069467NCI NIH HHS U01 CA069631NCI NIH HHS U01 CA069638NCI NIH HHS U01 CA164920
6 · The paper itself

Abstract

Our aim was to estimate how long-term mortality following breast cancer diagnosis depends on age at diagnosis, tumor estrogen receptor (ER) status, and the time already survived. We used the population-based Australian Breast Cancer Family Study which followed-up 1,196 women enrolled during 1992-1999 when aged <60 years at diagnosis with a first primary invasive breast cancer, over-sampled for younger ages at diagnosis, for whom tumor pathology features and ER status were measured. There were 375 deaths (median follow-up = 15.7; range = 0.8-21.4, years). We estimated the mortality hazard as a function of time since diagnosis using a flexible parametric survival analysis with ER status a time-dependent covariate. For women with ER-negative tumors compared with those with ER-positive tumors, 5-year mortality was initially higher (p < 0.001), similar if they survived to 5 years (p = 0.4), and lower if they survived to 10 years (p = 0.02). The estimated mortality hazard for ER-negative disease peaked at ~3 years post-diagnosis, thereafter declined with time, and at 7 years post-diagnosis became lower than that for ER-positive disease. This pattern was more pronounced for women diagnosed at younger ages. Mortality was also associated with lymph node count (hazard ratio (HR) per 10 nodes = 2.52 [95% CI:2.11-3.01]) and tumor grade (HR per grade = 1.62 [95% CI:1.34-1.96]). The risk of death following a breast cancer diagnosis differs substantially and qualitatively with diagnosis age, ER status and time survived. For women who survive >7 years, those with ER-negative disease will on average live longer, and more so if younger at diagnosis.

Indexed as

AdultAustraliaBreastBreast NeoplasmsCase-Control StudiesFemaleHumansLymph NodesMiddle AgedNeoplasm GradingPrognosisProportional Hazards ModelsReceptors, EstrogenSurvival AnalysisReceptors, Estrogenbreast cancercohort studyestrogen receptormortalitysurvivaltime-dependent effects

Identifiers

PMID30771221
PMCPMC6697632

What OpenQuestion holds

Textmetadata
LicenceTDM
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.