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Record W2954499677 · doi:10.1158/1538-7445.am2019-4191

Abstract 4191: The worldwide female breast cancer incidence and survival, 2018

2019· article· en· W2954499677 on OpenAlexaboutno aff
Zoubida Zaidi, Hussain Adlane Dib

Bibliographic record

VenueCancer Research · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNutrition, Genetics, and Disease
Canadian institutionsnot available
Fundersnot available
KeywordsBreast cancerCancerMedicineIncidence (geometry)PopulationDemographyCancer registryEpidemiologyInternational agencyEpidemiology of cancerRelative survivalGynecologyInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

Abstract Background: this communication presents the latest international descriptive epidemiological data for invasive breast cancer amongst women, including incidence and survival in the worldwide. Methods: the incidence statistics presented here for cancers worldwide were taken from the International Agency for Research on Cancer IARC: * The Cancer Incidence in five Continents Vol XI.* GLOBOCAN 2018. *The datas of Cancer survival are taken from: * Cancer survival in five continents, a worldwide population-based study or Concord Study Version 1, 2 and 3. These Concord studies included 101 population-based cancer registries in 31 countries for the period 1990-1994 and followed up to 1999 for the Concord Study 1, 279 population-based cancer registries in 67 countries for the period 1995-2009 for the Concord Study 2 and 412 cancer registries in 85 countries for the period 2000-14 for the Concord Study 3 Results: breast cancer is by far the most frequent cancer among women with an estimated. 2 million new cancer cases diagnosed in 2018 (23% of all cancers), and ranks second overall (10.9% of all cancers). It is now the most common cancer both in developed and developing regions.* Incidence rates vary from 19.3 per 100,000 women in Eastern Africa to 89.7 per 100,000 women in Western Europe, and are high (greater than 80 per 100,000) in developed regions of the world (except Japan) and low (less than 40 per 100,000) in most of the developing regions.For women diagnosed during 2010-14, the range of survival estimates is still wide in each continent, apart from North America and Oceania with 5-year net survival approached 90%. **Age-standardised 5-year net survival was 85% or higher in 25 countries, Costa Rica, Martinique, Canada and the USA, Israel, Japan and 16 European countries, Denmark, Finland, Iceland, Norway, Sweden, UK, Austria, Belgium, France, Germany, the Netherlands, and Switzerland and Italy, Malta, Portugal and Spain. **5-year survival was in the range 80-84% in 12 countries, three countries in Central and South America Argentina, Peru, and Puerto Rico, five Asian countries (Singapore, China, Hong Kong and Taiwan and Turkey and four European countries the Czech Republic and Latvia and Slovenia.**Survival was in the range 70-79% in 12 countrie, Cuba and Ecuador, Kuwait and Mongolia and eight countries in Europe, Estonia, Lithuania, Croatia and Bulgaria and Poland. **Breast cancer survival remains lower in Eastern Europe and Africa. Conclusion: the future worldwide breast cancer burden will be strongly influenced by large predicted rises in incidence throughout parts of Asia due to an increasingly westernised lifestyle. Efforts are underway to reduce the global disparities in survival for women with breast cancer using cost-effective interventions. Note: This abstract was not presented at the meeting. Citation Format: Zoubida Zaidi, Hussain Adlane Dib. The worldwide female breast cancer incidence and survival, 2018 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4191.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.579
Threshold uncertainty score0.669

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 head0.038
GPT teacher head0.370
Teacher spread0.332 · 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

Citations46
Published2019
Admission routes1
Has abstractyes

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