Higher and Increasing Incidence of Cancer between the Age of 20-49 Years in the UAE Population; A Focus Analysis of the UAE National Cancer Registry Data 2015-2017
Bibliographic record
Abstract
There is accumulating evidence that cancer incidence is increasing in younger adults. An earlier report indicating a higher incidence of breast and colorectal cancer in the younger population in the UAE. Open access data from the UAE National Cancer Registry (UAE-NCR) from the Ministry of Health and Prevention (MOHAP) for 2017 were extracted. Estimated data from the International. Agency for Research on Cancer ( IARC ) for Saudi Arabia, Canada, United Kingdom, China, and India for the year 2020 were also extracted and analyzed. When analyzing the 2017 UAE published data with restriction to the age group between 20-49 years of age for both UAE citizens and Non-UAE citizens, The data indicates that, the percentage of cancer incidence in this age group was 45.4% from total number of new malignant cancer cases in 2017, compared with 42.4% in 2015 and 42.7% in 2016. In females the percentage of cancer incidence in this age group was 51.3% from total number of new malignant cancer cases among females in 2017, and 38.3% among males in the same year, compared with 2016 data (49.5% among females and 34.9% among males) and 2015 data (49.9% among females and 34.1% among males), data indicates that, there is a clear trend for an increase in the incidence annual percent change in this age group by 3% (from 42.4% in 2015 to 45.4% in 2017). This increased persisted regardless of sex (males increased incidence by 4.2% from 34.1 % in 2015 to 38.3% in 2017 while in females increased incidence by 1.4% from 49.9% to 51.3%), which more females were diagnosed with cancer at the age of 20-49 than males between 2015 and 2017.When re-analyzing the 2017 data and restriction to the UAE citizens population only with the age group of 20-49, the percentage of cancer incidence remains high at 37.2% (42.4% among females and 28.9% among males). The percentage of cancer incidence in this age group between 20-49 years of age in Saudi Arabia is 39.49% which is comparable to the UAE, yet these incidence rates are extremely high compared with the following countries; Canada 8% (p < 0.005), USA 8.75% (p < 0.005) , United Kingdom 8.33% (p < 0.005), China 16.15% (p < 0.005) and India 26.75% (p < 0.005). The current data indicated an increase in the cancer incidence in the UAE in the age group of 20 – 49 years of age. The incidence is alarming and requires focused research to address potential risk factors. Cancer screening is a vital component in reducing cancer mortality, yet utility and cost-effectiveness has not been evaluated fully in the younger population. UAE-based research to evaluate screening due to the higher incidence may be required to be addressed. A more collaborative regional and global effort is a must to address this global alarming phenomenon.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".