Evidence map›Paper›PMID 23843856›Full record

ArticleJournal of breast cancer2013

Breast cancer risk factors in a defined population: weighted logistic regression approach for rare events.

Najf Zare, Elham Haem, Kamran B Lankarani, Seyyed Taghi Heydari, Esmat Barooti

Open access · goldAbstract read
In one paragraph

Article in Journal of breast cancer, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.5field-weighted citation impact, top 10% 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

10 citing papers in PubMed, 45 citations in OpenAlex.

  1. Review
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  6. Review
  7. Bayesian Generalized Linear Mixed Modeling of Breast Cancer.Iranian journal of public health · 2019
    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

5 authors at 3 institutions in 1 country.

Najf ZareDepartment of Biostatistics, Research Center of Fertility and Infertility, Shiraz University of Medical Sciences School of Medicine, Shiraz, Iran.
Elham Haem
Kamran B Lankarani
Seyyed Taghi Heydari
Esmat Barooti
Shiraz University of Medical Sciences · IRJahrom University of Medical Sciences · IRMinistry of Health and Medical Education · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis study aimed to determine out risk factors for female breast cancer in a low socioeconomic population in Iran.

methodsBetween 2007 and 2009, a total of 25,592 women who were ensured by the Imam Khomeini Relief Foundation participated in this screening program. The characteristics of patients diagnosed with breast cancer (n=111) were compared with those of control cases (n=25,481). In this study, we used relogit analysis (rare event logistic regression) with a weighting method using program Zelig.

resultsOf 25,592 women, 3.9/1,000 had breast cancer, from which 38 were diagnosed during screening and 73 had already been diagnosed. The mean and standard deviation of age in breast cancer patients and in healthy controls were 49.18±8.86 years and 46.65±9.40 years, respectively. The findings based on the multivariate model revealed that the past history of ovarian cancer, hormone therapy, and first relatives with breast cancer were associated with increased risk for breast cancer. However, the use of oral contraceptive pills was found to be associated with reduced risk for breast cancer.

conclusionDue to the rarity of the event in the population, relogit with a weighting method was used to investigate the major risk factors for breast cancer. These factors include oral contraceptive pill use, a history of ovarian cancer of the person under study, first relatives with breast cancer and hormone therapy.

Indexed as

Breast neoplasmsLogistic modelsRisk factorsScreening program

Identifiers

PMID23843856
PMCPMC3706869
OpenAlexW2167626685

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.