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Record W162781829 · doi:10.1136/bmj.321.7274.1470/a

Survival and reduction in mortality from breast cancer

2000· letter· en· W162781829 on OpenAlexaff
Michael Baum, H. Gilbert Welch, Tim Reynolds, A S Wierzbicki, Anthony Threlfall, Sarah Collins, C B J Woodman, Michel P. Coleman, Diane Stockton, P. Babb, Marcus Richards

Bibliographic record

VenueBMJ · 2000
Typeletter
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsSurgical Specialties (Canada)
Fundersnot available
KeywordsMedicineBreast cancerMammographyCancerBreast cancer screeningFamily medicineGynecologyDemographyInternal medicineSociology

Abstract

fetched live from OpenAlex

# Impact of mammographic screening is not clear {#article-title-2} EDITOR—We should all rejoice that there has been an improvement in survival and reduction in mortality for carcinoma of the breast, but Richards et al in their paper perpetuate the myth that this is related to the breast screening programme.1 The periods for comparison were 1981-5 and 1986-90. The Forrest report on mammographic screening was published in 1986,2 the first screening centres were established in 1988, and the country was not covered by the programme until 1990. Even the greatest zealots for mammographic screening would not expect an impact on mortality until 1997. The fall in mortality could therefore be attributed only to improvements in treatment, and it is relevant to note that the first overview of the trials of adjuvant systemic treatment were published in 1985.3 The only support for the assertion that the reduction in mortality can be attributed to the breast screening programme was a personal communication from S M Moss. Many people are of the opinion that mammographic screening is saving thousands of lives, but opinion alone does not provide sufficient data to support a publication in a prestigious journal such as the BMJ . 1. 1.↵1. Richards MA, 2. Stockton D, 3. Babb P, 4. Coleman MP . How many deaths have been avoided through improvements in cancer survival? BMJ 2000;320:895–898. (1 April.) [OpenUrl][1][Abstract/FREE Full Text][2] 2. 2.↵1. Forrest P . Breast cancer screening: Report to the Health Ministers of England, Wales, Scotland and Northern Ireland. London: HMSO, 1986. 3. 3.↵1. Early Breast Cancer Trialists Collaborative Group . Effects of adjuvant tamoxifen and of cytotoxics on mortality in early breast cancer: an overview of 61 randomised trials amongst 28,896 women. N Engl J Med 1988;319:1681–1692. [OpenUrl][3][PubMed][4][Web of Science][5] # Diagnostic practice in the United States is different {#article-title-5} EDITOR—Richards et al seem to have made inferences about “deaths avoided” using data on five year survival.1 This measure is, however, powerfully affected by diagnostic practice and is not a reliable indicator of mortality.2 In the United States the problem is best exemplified by prostate cancer. Five year survival has increased from about 40% in the 1950s to about 95% currently.3 Although it is tempting to conclude that we Americans have made major medical advances (and left the United Kingdom in the dust), the truth is that this largely reflects our diagnostic practice. As we aggressively seek and find early stage (and often innocuous) tumours, … [1]: {openurl}?query=rft.jtitle%253DBMJ%26rft.stitle%253DBMJ%26rft.issn%253D0007-1447%26rft.aulast%253DRichards%26rft.auinit1%253DM%2BA%26rft.volume%253D320%26rft.issue%253D7239%26rft.spage%253D895%26rft.epage%253D898%26rft.atitle%253DHow%2Bmany%2Bdeaths%2Bhave%2Bbeen%2Bavoided%2Bthrough%2Bimprovements%2Bin%2Bcancer%2Bsurvival%253F%26rft_id%253Dinfo%253Adoi%252F10.1136%252Fbmj.320.7239.895%26rft_id%253Dinfo%253Apmid%252F10741993%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/ijlink?linkType=ABST&journalCode=bmj&resid=320/7239/895&atom=%2Fbmj%2F321%2F7274%2F1470.2.atom [3]: {openurl}?query=rft.jtitle%253DNew%2BEngland%2BJournal%2Bof%2BMedicine%26rft.stitle%253DNEJM%26rft.issn%253D0028-4793%26rft.volume%253D319%26rft.issue%253D26%26rft.spage%253D1681%26rft.epage%253D1692%26rft.atitle%253DEffects%2Bof%2Badjuvant%2Btamoxifen%2Band%2Bof%2Bcytotoxic%2Btherapy%2Bon%2Bmortality%2Bin%2Bearly%2Bbreast%2Bcancer.%2BAn%2Boverview%2Bof%2B61%2Brandomized%2Btrials%2Bamong%2B28%252C896%2Bwomen.%2BEarly%2BBreast%2BCancer%2BTrialists%2527%2BCollaborative%2BGroup%26rft_id%253Dinfo%253Apmid%252F3205265%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [4]: /lookup/external-ref?access_num=3205265&link_type=MED&atom=%2Fbmj%2F321%2F7274%2F1470.2.atom [5]: /lookup/external-ref?access_num=A1988R516200001&link_type=ISI

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)0.006
metaresearch head score (Gemma)0.038
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.038
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0100.004

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 head0.097
GPT teacher head0.379
Teacher spread0.282 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations11
Published2000
Admission routes1
Has abstractyes

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