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Record W60325291 · doi:10.24095/hpcdp.33.2.03

Cancer incidence, mortality and survival trends in Canada, 1970–2007

2013· article· en· W60325291 on OpenAlexafffundvenueabout
Linda Kachuri, P De, Larry F. Ellison, R Semenciw

Bibliographic record

VenueChronic diseases and injuries in Canada · 2013
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsPublic Health Agency of CanadaStatistics CanadaCanadian Cancer SocietyPublic Health OntarioUniversity of Toronto
FundersCenters for Disease Control and PreventionPublic Health AgencyPublic Health Agency of CanadaCancer Care Ontario
KeywordsMedicineCancerIncidence (geometry)ProstateOncologyProstate cancerCancer registryKidney cancerColorectal cancerInternal medicineMortality rateBreast cancerMelanomaRelative survivalDemographyGynecologyCancer research

Abstract

fetched live from OpenAlex

INTRODUCTION: Monitoring cancer trends can help evaluate progress in cancer control while reinforcing prevention activities. This analysis examines long-term trends for selected cancers in Canada using data from national databases. METHODS: Annual changes in trends for age-standardized incidence and mortality rates between 1970 and 2007 were examined by sex for 1) all cancers combined, 2) the four most common cancers (prostate, breast, lung, colorectal) and 3) cancers that demonstrate the most recent notable changes in trend. Five-year relative survival for 1992-2007 was also calculated. RESULTS: Incidence rates for all primary cancer cases combined increased 0.9% per year in males and 0.8% per year in females over the study period, with varying degrees of increase for melanoma, thyroid, liver, prostate, kidney, colorectal, lung, breast, and bladder cancers and decrease for larynx, oral, stomach and cervical cancers. Mortality rates were characterized by significant declines for all cancers combined and for most cancers examined except for melanoma and female lung cancer. The largest improvements in cancer survival were for prostate, liver, colorectal and kidney cancers. While the overall trends in mortality rates and survival point to notable successes in cancer control, the increasing trend in incidence rates for some cancers emphasize the need for continued efforts in prevention.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.316
Teacher spread0.287 · 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.

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

Citations74
Published2013
Admission routes4
Has abstractyes

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