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Record W4388660837 · doi:10.3390/cancers15225398

Breast Cancer in the Arabian Gulf Countries

2023· review· en· W4388660837 on OpenAlexaboutno aff
Humaid O. Al‐Shamsi, Nadia Abdelwahed, Amin M. Abyad, Ibrahim Abu-Gheida, Mehdi Afrit, Tasneem Abu ElFuol, Ryad Alasas, Bilal Lababidi, Prasanta K. Dash, Mudhasir Ahmad, Norbert Dreier, Urfan Ul Haq, Thanda Lucy Ann Joshua, Sonia Otsmane, Anwar Al-Nouri, Aydah Al‐Awadhi, Syed Hammad Tirmazy, Faisal Alterkait, Shimaa Elsabae, Nyla Khan, Nehad Kazim Albastaki, Yoginee Sonawane, Mohammed Jouda, Frea Perdawood, Faryal Iqbal, Hassan Jaafar

Bibliographic record

VenueCancers · 2023
Typereview
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsnot available
Fundersnot available
KeywordsBreast cancerCancerMedicineIncidence (geometry)DemographyMalignancyOncologyGynecologyInternal medicine

Abstract

fetched live from OpenAlex

Breast cancer stands as the prevailing malignancy across all six Gulf Cooperation Council (GCC) nations. In this literature review, we highlighted the incidence and trend of breast cancer in the GCC. Most of the studies reported a consistent increase in breast cancer incidence over the past decades, which was particularly attributed to the adoption of a Westernized lifestyle in the region and the implications of emerging risk factors and other environmental and societal factors, the increase in screening uptake, as well as the improvement in data collection and reporting in the GCC. The data on breast cancer risk factors in the GCC were limited. In this geographic region, breast cancer frequently manifests with distinctive characteristics, including an early onset, typically occurring before the age of 50; an advanced stage at presentation; and a higher pathological grade. Additionally, it often exhibits more aggressive features such as human epidermal growth factor receptor 2 (HER2) positivity or the presence of triple-negative (TN) attributes, particularly among younger patients. Despite the growing body of literature on breast cancer in the GCC, data pertaining to survival rates are, regrettably, meager. Reports on breast cancer survival rates emanating from the GCC region are largely confined to Saudi Arabia and the United Arab Emirates (UAE). In the UAE, predictive modeling reveals 2-year and 5-year survival rates of 97% and 89%, respectively, for the same period under scrutiny. These rates, when compared to Western counterparts such as Australia (89.5%) and Canada (88.2%), fall within the expected range. Conversely, Saudi Arabia reports a notably lower 5-year survival rate, standing at 72%. This disparity in survival rates underscores the need for further research directed toward elucidating risk factors and barriers that hinder early detection and screening. Additionally, there is a pressing need for expanded data reporting on survival outcomes within the GCC. In sum, a more comprehensive and nuanced understanding of breast cancer dynamics in this region is imperative to inform effective strategies for prevention, early detection, and improved patient outcomes.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.944
Threshold uncertainty score0.936

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.157
GPT teacher head0.423
Teacher spread0.266 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations18
Published2023
Admission routes1
Has abstractyes

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