Evidence map›Paper›PMID 20299982›Full record

ReviewEpidemiology (Cambridge, Mass.)2010

Evaluating cancer epidemiologic risk factors using multiple primary malignancies.

Ekatherina Kuligina, Anne Reiner, Evgeny N Imyanitov, Colin B Begg

Abstract readReview
In one paragraph

Review in Epidemiology (Cambridge, Mass.), 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.3field-weighted citation impact, top 12% 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

11 citing papers in PubMed, 18 citations in OpenAlex.

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  9. A strategy for distinguishing optimal cancer subtypes.International journal of cancer · 2011
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 2 countries.

Ekatherina KuliginaN N Petrov Institute of Oncology, Russian Federation, St Petersburg, Russia.
Anne Reiner
Evgeny N Imyanitov
Colin B Begg
Institute of Oncology NN Petrov · RUMemorial Sloan Kettering Cancer Center · US

Funding

Statistical Methods for Identifying Clonal TumorsR01CA124504 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI BEGG, COLIN B · 2009 to 2011
$1.1M
Estimating Cancer Risks of Rare Genetic VariantsR01CA131010 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI BEGG, COLIN B, CAPANU, MARINELA · 2008 to 2010
$944k
Epidemiologic Parameters of Rare Cancer Risk FactorsR01CA098438 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI BEGG, COLIN B · 2003 to 2005
$839k
NCI NIH HHS CA124504NCI NIH HHS CA131010NCI NIH HHS R01 CA098438NCI NIH HHS R01 CA124504NCI NIH HHS R01 CA131010
6 · The paper itself

Abstract

backgroundSeveral authors have proposed the use of patients with double primary malignancies affecting the same or contralateral organ as a genetically enriched resource of cases for epidemiologic case-control studies in cancer. Such an approach is based on the assumption that the factors that increase the risk of a second primary are the same ones which influence the risk of a first primary. The advantages for statistical power are premised on the assumption that relative risks in survivors of a first primary cancer are similar to relative risks in the unaffected population. We explore these assumptions theoretically and empirically using published data from breast cancer studies involving bilateral breast cancer.

methodsWe conducted a literature review to identify case-control studies of variants in 4 genes known to affect breast cancer risk: CHEK2*1100delC; multiple variants in BRCA1 and BRCA2; and FGFR2 rs2981582. Summary odds ratios were obtained for each of 3 study designs: a conventional case-control design, the design comparing bilateral cases with unilateral controls, and the design comparing bilateral cases with population controls.

resultsThe data show strong patterns of steadily increasing prevalence of risk factors from healthy controls to primary cases to bilateral cases, as expected. Relative risks in survivors of unilateral breast cancer are either the same as in the general population, or modestly attenuated.

conclusionsPatients with double primary malignancies are a very important underused resource for cancer epidemiologic investigation. Such patients are especially useful for broad genome-wide discovery studies, and for studies of rare, strong risk factors such as high penetrance genes.

Indexed as

Breast NeoplasmsCase-Control StudiesEpidemiologic StudiesFemaleHumansNeoplasms, Multiple PrimaryOdds RatioRisk Factors

Identifiers

PMID20299982
PMCPMC3142453
OpenAlexW2004951433

What OpenQuestion holds

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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.