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Record W2081649626 · doi:10.1159/000212103

The Epidemiology and Aetiology of Female Breast Cancer

2009· article· en· W2081649626 on OpenAlexaboutno aff
Andreas Stang, Rita K. Schmutzler

Bibliographic record

VenueBreast Care · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsnot available
Fundersnot available
KeywordsBreast cancerMedicineIncidence (geometry)EpidemiologyEtiologyCancerGynecologyOncologyRisk factorRisk factors for breast cancerInternal medicine

Abstract

fetched live from OpenAlex

This issue of BREAST CARE focuses on the epidemiology and aetiology of female breast cancer. Katalinic et al. [1] provide an interesting update of the incidence and mortality patterns of breast cancer in Germany. Based on their analyses, they are able to corroborate the recent association between decrease of hormone therapy (HT) among postmenopausal women and breast cancer incidence, as has been seen in many other countries. After more than 30 years of breast cancer incidence increase, this is good news. Even nowadays, East Germany shows considerably lower incidences of breast cancer than West Germany. Katalinic et al. give some interesting insights into the explanations for these findings. In their narrative review, Kluttig and Schmidt-Pokrzywni-ak [2] give an overview of the established risk factors of breast cancer. Their review summarises results of meta-analyses and literature reviews. It helps to condense the huge amount of available literature on the risk factors of breast cancer. They conclude that preventive action against the risk factors of breast cancer could also have a beneficial effect on other diseases, including type 2 diabetes and cardiovascular diseases. Schreer [3] gives an update on the increasing evidence that dense breast tissue is an independent risk factor for breast cancer. Besides age and mutations in the high-risk genes BRCA1 or BRCA2, dense breast tissue constitutes one of the highest risk factors. Although the association is well established, there is a lack of standardised methods to quantitatively measure breast density as a prerequisite for the offer of intensified surveillance. Also, reliable and prospective clinical data are missing that would provide clear evidence for the effectiveness of intensified surveillance strategies such as shorter mammographic intervals or the added value of ultrasound. The explicit illustration of the current dissatisfactory situation provides a rationale for the initiation of prospective studies. Meindl [4] summarises the current search for new susceptibility genes. Given the fact that no further high-penetrance gene was found by linkage analysis of large cohorts of BRCA1- and BRCA2-negative high-risk families within the last decade, the hypothesis emerged that low-susceptibility genes inherited in a complex genetic trait may be the underlying cause for the remaining unexplained familial risk. This hypothesis was further supported by twin studies. A proof of principle was provided last year by the identification of low-susceptibility alleles in several genome-wide association studies. Now the challenge is to identify the underlying genes, their function, the interaction, and the cumulated risks conferred by these alleles. Besides a complex genetic trait, an alternative explanation would be the existence of many more very rare genes with high penetrance transmitted by a dominant trait, thus allocating a distinct gene to only a few families. Candidate gene approaches have already identified a few of such genes providing the rationale for high throughput sequencing studies for the identification of such novel genes. Another much discussed topic in breast cancer epidemiology is the amount of breast cancer overdiagnosis and spontaneous regression of invasive breast cancer in mammography screening programmes. Recently, Zahl et al. [5] published a provoking analysis of data from Norwegian counties before and after the initiation of mammography screening that triggered much debate. Zahl and his colleagues considered the possibility of spontaneous regression in screen-detected invasive breast cancer. To address this issue, they compared the 6-year cumulative incidence of breast cancer in a cohort of women aged 50–64 years at the start of the programme with that of an age-matched cohort from 4 years earlier. If spontaneous regression did not occur, i.e. if all screen-detected breast cancers were to progress or even remain the same size, the cumulative incidence in the 2 cohorts would therefore be expected to be equal. As expected, invitation to the first screening round was associated with a dramatic rise in invasive breast cancer relative to the age-matched control cohort. As time passed and cancer in the control group had the opportunity to become clinically evident, the difference narrowed. However, even after prevalence screening in the control cohort, the cumulative incidence of invasive breast cancer remained 22% higher in the screened cohort (6-year cumulative incidence: 1,909 vs. 1,564 per 100,000 women, relative risk 1.22, 95% confidence interval 1.16–1.30). Zahl et al. conclude that some invasive breast cancers detected by repeated mammography would not persist to be detectable by a single screening at the end of the 6 years. In other words, the natural course for some screen-detected breast cancers may be to spontaneously regress. Interestingly, a Canadian trial of women aged 40–49 years that had a truly unscreened control group also found an excess incidence of 22% in the screened group [6]. Although the study of Zahl et al. was not based on a randomised trial, it has several strengths. It was a population-based study with high participation rates, and outcomes were assessed by a virtually complete registration via the nationwide cancer registry in Norway. The provoking findings of Zahl et al. reveal that little is known about the spontaneous regression of invasive breast cancer and that further studies are needed to address this question.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.005
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.300
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2009
Admission routes1
Has abstractyes

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