Incidence and Mortality of Nasopharynx Cancer and Its Relationship With Human Development Index in the World in 2012
Bibliographic record
Abstract
BACKGROUND: One of the most common cancers in head and neck is nasopharynx. Knowledge about the incidence and mortality of this disease and its distribution in terms of geographical areas is necessary for further study, better planning and prevention. Therefore, this study aimed to determine the incidence and mortality of nasopharynx cancer and its relationship with human development index (HDI) in the world in 2012. METHODS: This study was an ecological study conducted based on GLOBOCAN project of World Health Organization (WHO) for the countries in world. The correlation between standardized incidence rates (SIRs) and standardized mortality rates (SMRs) of nasopharynx cancer with HDI and its components was assessed with correlation coefficient by using SPSS 15. RESULTS: In 2012, 86,691 nasopharynx cancer cases occurred in the world, so that 60,896 new cases were seen in men and 25,795 new cases in women (sex ratio = 2.36). SIR of the cancer was 1.2 per 100,000 (1.7 in men and 0.7 in women per 100,000) in the world. In 2012, 50,831 nasopharynx death cases occurred in the world, so that 35,756 death cases were seen in men and 15,075 death cases in women (sex ratio = 2.37). SIR of mortality from the cancer was 0.7 per 100,000 (0.7 in women and 1 in men per 100,000) in the world. The results of correlation analysis showed a negative correlation between the SIR and HDI (r = -0.037, P = 0.629), and also the results of correlation analysis showed a negative correlation between the SMR and HDI (r = -0.237, P = 0.002). CONCLUSION: Nasopharyngeal cancer is native to Southeast Asia and the highest incidence and mortality were seen in countries with moderate and low HDI. It is suggested that studies are conducted on determining the causes of the cancer incidence and mortality in the world and the differences between various regions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".