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Record W2767196447 · doi:10.1093/eurpub/ckx195

Premature mortality due to breast cancer among Canadian women: an analysis of a 30-year period from 1980 through 2010

2017· article· en· W2767196447 on OpenAlexaffabout
Truong‐Minh Pham, Khokan C. Sikdar, Bethany Kaposhi, Sasha Lupichuk, Huiming Yang, Lorraine Shack

Bibliographic record

VenueEuropean Journal of Public Health · 2017
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsUniversity of CalgaryAlberta Health Services
Fundersnot available
KeywordsBreast cancerPeriod (music)DemographyMedicineObstetricsCancerInternal medicineSociology

Abstract

fetched live from OpenAlex

Background: Breast cancer is the most commonly diagnosed cancer and the second most common cause of cancer deaths for women. In the present study, we examined the trend of premature mortality due to breast cancer among Canadian women from 1980 through 2010 and proposed a new measure of lifespan shortening. Methods: Mortality data for female breast cancer was obtained from the World Health Organization mortality database. Years of life lost (YLL) was estimated using Canadian life tables. Average lifespan shortened (ALSS) that is calculated and expressed by a ratio of YLL relative to expected lifespan. Results: Over this study period, age-standardized rates of breast cancer mortality adjusted to World Standard Population decreased by 40% from 23.2 to 14.2 per 100 000 women. The adjusted YLL rates fell from 5.3 years per 1000 women to 3.3 years. On average women with breast cancer died 20.8 years prior to expected death in 1980 and 18.3 years early in 2010. A novel measure of lifespan shortening, the ALSS decreased from one-fourth of the lifespan in 1980 to one-fifth in 2010. Conclusions: Our study reports that among Canadian women with breast cancer, a smaller proportion of life was lost on average at the end of the study period. The 'life lost' measures presented in this study would be useful tools to monitor the pattern of premature mortality for chronic conditions. These measures gauge the effectiveness of the health system with respect to early detection and treatment.

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)0.005
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 score0.079
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.113
GPT teacher head0.374
Teacher spread0.262 · 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

Citations16
Published2017
Admission routes2
Has abstractyes

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