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Record W2617460267 · doi:10.1002/ijc.30794

Benefits and harms of breast cancer screening with mammography in women aged 40–49 years: A systematic review

2017· review· en· W2617460267 on OpenAlexaboutno aff
Caroline van den Ende, Anouk Oordt-Speets, Hilde Vroling, Heleen M.E. van Agt

Bibliographic record

VenueInternational Journal of Cancer · 2017
Typereview
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMammographyBreast cancerBreast cancer screeningPopulationCancerGynecologyObstetricsInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

Early detection of breast cancer through screening can lower breast cancer mortality rates and reduce the burden of this disease in the population. In most western countries, mammography screening starting from age 50 is recommended. However, there is debate about whether breast cancer screening should be extended to younger women. This systematic review provides an overview of the evidence from RCTs on the benefits and harms of breast cancer screening with mammography in women aged 40-49 years. The quality of the evidence for each outcome was appraised using the GRADE approach. Four articles reporting on two different trials-the Age trial and the Canadian National Breast Screening Study-I (CNBSS-I)-were included. The results showed no significant effect on breast cancer mortality (Age trial: RR 0.93 (95% CI 0.80-1.09); CNBSS-I: HR 1.10 (95% CI 0.86-1.40)) nor on all-cause mortality (RR 0.98, 95% CI 0.93-1.03) in women aged 40-49 years offered screening. Among regularly attending women, the cumulative risk of experiencing a false-positive recall was 20.5%. Over-diagnosis of invasive breast cancer at 5 years post-cessation of screening for women aged 40-49 years was estimated to be 32% and at 20 years post-cessation of screening to be 48%. Including ductal carcinoma in situ, these numbers were 41% and 55%. Based on the current evidence from randomised trials, extending mammography screening to younger age groups cannot be recommended. However, there were limitations including relatively low sensitivity of screening and screening attendance, insufficient power, and contamination, which may explain the nonsignificant results.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.694
Threshold uncertainty score0.775

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.107
GPT teacher head0.422
Teacher spread0.315 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
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".

Quick stats

Citations87
Published2017
Admission routes1
Has abstractyes

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