Addressing the Younger Age at Onset in Breast Cancer Patients in Asia: An Age-Period-Cohort Analysis of Fifty Years of Quality Data from the International Agency for Research on Cancer
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Bibliographic record
Abstract
Introduction. There is an established fact that Asian breast cancer patients are, on average, younger than their European counterparts. This study aimed to utilize the data from the Cancer Incidence in Five Continents I through XIII (published by the International Agency for Research on Cancer) to examine what contributes to the younger age at onset in the Asian population. Material and Methods. Data (number of breast cancer cases and corresponding population figures) for 29 registries in Europe and 9 registries in Asia for the period of 1953-2002 was accessioned and pooled to form two distinct populations, Asia and Europe. The age specific rates were defined and analyzed cross-sectionally (period wise) and longitudinally (cohort wise). The magnitude and the pattern of age specific rates were analyzed using the age-period-cohort analysis. The constrained generalized linear model with a priority assumption of cohort effect as contributing factor to changing rates was used to analyze the data. Result. During the last 50 years, the rate of breast cancer increased for both populations with an estimated annual percent change of 1.03% (with 95% CI of 1.029, 1.031) for Asia and 1.016% (95% CI of 1.015, 1.017) for Europe. There were stronger cohort effects in the magnitude of rates among the Asian population compared to the European population. The cohort effects, expressed as the rate ratio with cohort born in 1970 as reference, ranged from 0.06 (95% CI 0.05, 0.08) to 0.94 (95% CI 0.93, 0.96) for Asians and 0.35 (95% CI 0.33, 0.36) to 1.03 (95% CI 1.02, 1.04) for Europeans. The estimated longitudinal age specific rates (adjusted for cohort and period effects) showed similar patterns between the two populations. Conclusion. It was concluded that a strong cohort effect contributes to the younger age at onset among Asian breast cancer patients.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it