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Record W3165017804 · doi:10.1097/cej.0000000000000694

Incidence trends in lung and bladder cancers in the Nordic Countries before and after the smoking epidemic

2021· article· en· W3165017804 on OpenAlexaff

Bibliographic record

VenueEuropean Journal of Cancer Prevention · 2021
Typearticle
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsIncidence (geometry)NorwegianLung cancerCancer registryBladder cancerEpidemiologyPopulationCancer

Abstract

fetched live from OpenAlex

Cigarette smoking epidemic, which started before the World War II, completely changed the cancer landscape. Reliable incidence data spanning the stepwise spreading epidemic are rare, but the Nordic cancer registries are unique sources in being able to catch the pre-epidemic situation in the female population where smoking became more prevalent after the War. For Swedish men, smoking prevalence has decease early and cancer rates may herald postsmoking rates. We used data from the NORDCAN database, constructed by the cancer registries of Denmark, Finland, Norway and Sweden, for the analysis of incidence changes in lung and bladder cancers from year 1943 (Denmark), from 1953 (Finland and Norway) and from 1960 (Sweden) until year 2016. The analyses revealed four novel observation relevant to the smoking epidemic. (1) The incidence of lung cancer in Norwegian women in the 1950s, when the smoking prevalence was very low, was 1.8/100 000 (world standard rate), which is at the level of lowest global female rates known to-date; (2) the earliest lung-to-bladder incidence ratio among Norwegian women was 0.64, probably benchmarking the incidence rates prior to the smoking epidemic; (3) bladder cancer incidence for Finnish women diagnosed in the 1950s was 1.2/100 000 which is at the level of the lowest rates currently known and (4) Swedish men with the lowest smoking prevalence in Europe, showed an epochal crossing of lung and bladder cancer incidence rates before year 2015. The data suggest that the approaching of the incidence rates for lung and bladder cancer can be expected in the course of the abating smoking epidemic.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score0.237

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.014
GPT teacher head0.312
Teacher spread0.297 · 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 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

Citations13
Published2021
Admission routes1
Has abstractyes

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