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Comparative Analysis of Breast Cancer (BrCa) Mortality Reduction among Regions of Canada between 1950 – 2004: Impact of Systemic and Diagnostic Guidelines after 1977, with Model Definition of Number of Potentially Avoided Annual Deaths (N-PAAD).

2009· article· en· W1984741870 on OpenAlexaffabout
Joseph Ragaz, Hubert Wong, Hong Qian

Bibliographic record

VenueCancer Research · 2009
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsUniversity of British ColumbiaMcGill University
Fundersnot available
KeywordsDemographyMedicineCancerBreast cancerMortality rateGuidelineInternal medicinePathology

Abstract

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Abstract BACKGROUNDWe reported in the past the BrCa mortality trends in three Provinces of Canada with different Levels of Provincial Diagnostic and Therapy Guideline (ProvDgThGuide) implementation, reflecting access to optimum cancer care (LEVEL I, most uniform: British Columbia (B.C.); LEVEL II, medium: Ontario(ON); LEVEL III, least uniform (Atlantic Provinces AP), and have shown best outcomes in B.C. (Cancer Res 2009 69[S] 2:383).OBJECTIVETo estimate the number of BrCa deaths that potentially could have been avoided during the period 1978 – 2004 if the ProvDgThGuide Level I (i.e. of B.C.) had been implemented in Canada, Ontario and Atlantic Provinces, respectively.METHODSData were obtained from Statistics Canada.i. For each region, we calculated the average annual age-standardized mortality rate / 100,000 (aveASR) for the periods 1950-1977 (R1) and 1978-2004 (R2).ii. Subsequently, calculated was the Relative Change (RC, expressed in %) in mortality rate between the two time periods (RC = (R2-R1)/R1).iii. And for each region, the 1978 – 2004 expected rates (RE) based on RC from B.C. [i.e. calculated as "-13.8%" [(RE = 1- 0138) x R1].iv. These steps permitted estimates of Number of potentially avoided [annual] deaths (N-PAAD), based on the difference in observed mortality during the 1978-2004 period and the mortality that would have occurred if the regions had experienced the same relative change in mortality rate as observed in B.C. (R2-RE x # at risk).RESULTS R1(aveASR 1950-1977)R2(aveASR 1978-2004)RCREN-PAAD(N-AveAnnDeaths)BC30.025.8-13.8%----Ontario30.929.2-5.3%26.6137Atlantic27.528.8+4.7%23.760Canadaexcluding BC30.729.0-5.5%26.5315CONCLUSIONThis study confirms in most but not all regions of Canada a substantial mortality reduction after 1977, suggestive that implementation of optimum levels of Provincial Diagnostic and Therapy Guidelines (optimum access to cancer care) may affect mortality, and that their delay may prevent materialization of survival gains.Once the average annual rates of B.C. was applied to the rates of rest of Canada, the newly developed "Potentially Avoided Annual Deaths" model estimates over 8,000 avoided BrCa deaths in Canada (without B.C.) during the period 1978 – 2004 (26 [years] x 315).The model estimates over 3,500 (26 x 137) and 1500 (26 x 60) avoided deaths, respectively, for Ontario and Atlantic Provinces.These data are relevant to all world regions with differing access to optimum cancer care. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 2063.

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)0.003
metaresearch head score (Gemma)0.006
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.176

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.165
GPT teacher head0.461
Teacher spread0.296 · 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

Citations3
Published2009
Admission routes2
Has abstractyes

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