Evidence map›Paper›PMID 26807440›Full record

ArticleNPJ breast cancer

Analyzing historical trends in breast cancer biomarker expression: a feasibility study (1947-2009).

Nancy Krieger, Laurel A Habel, Pamela D Waterman, Melina Shabani, Lis Ellison-Loschmann, Ninah S Achacoso, Luana Acton, Stuart J Schnitt

Abstract read
In one paragraph

Article in NPJ breast cancer. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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

8 authors.

Nancy KriegerDepartment of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Laurel A HabelKaiser Permanente Division of Research, Oakland, CA, USA.
Pamela D WatermanDepartment of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Melina ShabaniDepartment of Pathology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
Lis Ellison-LoschmannCentre for Public Health Research, Massey University, Wellington, New Zealand.
Ninah S AchacosoKaiser Permanente Division of Research, Oakland, CA, USA.
Luana ActonKaiser Permanente Division of Research, Oakland, CA, USA.
Stuart J SchnittDepartment of Pathology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.

Funding

Long-Term Trends in Breast Cancer Tumor Profiles & DisparitiesR21CA166115 · NCI · HARVARD SCHOOL OF PUBLIC HEALTH · PI KRIEGER, NANCY · 2013 to 2014
$416k
NCI NIH HHS R21 CA166115
6 · The paper itself

Abstract

BACKGROUND/

objectivesDetermining long-term trends in tumor biomarker expression is essential for understanding aspects of tumor biology amenable to change. Limiting the availability of such data, currently used assays for biomarkers are relatively new. For example, assays for the estrogen receptor (ER), which are the oldest, extend back only to the 1970s.

methodsTo extend scant knowledge about the feasibility of obtaining long-term data on tumor biomarkers, we randomly selected 60 breast cancer cases (10 per decade) diagnosed between 1947-2009 among women members of the Kaiser Permanente Northern California health plan to obtain and analyze their formalin-fixed paraffin-embedded (FFPE) tumor specimens. For each tumor specimen, we created duplicate tissue microarrays for analysis.

resultsWe located tumor blocks and pathology reports for 50 of the 60 cases (83%), from which we randomly sampled 5 cases per decade for biomarker analysis (

conclusionsThese results indicate immunostaining for biomarkers commonly used to evaluate breast cancer biology and assign surrogate molecular phenotypes can reliably be employed on archival FFPE specimens up to 60 years old.

Identifiers

PMID26807440
PMCPMC4721558

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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.