The Impact of Multiple Primary Rules on Cancer Statistics in Canada, 1992 to 2012.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: Several sets of multiple primary rules have been used in Canada to determine whether a cancer is new and little is known of the impact on cancer statistics. We examine the effect of rules on the magnitude and trend of age-standardized incidence rates (ASIRs) of cancer in Canada between 1992 and 2012. METHODS: Cancer- and sex-specific ASIRs were estimated using Canadian Cancer Registry (CCR) rules and the more conservative International Agency for Research on Cancer (IARC) rules. CCR- and IARC-based ASIRs and trends were compared using rate ratios (CCR:IARC) and joinpoint analysis, respectively. We highlight instances where CCR-based ASIRs exceed the upper 95% confidence limit of corresponding IARC-based ASIRs, as well as instances where the magnitude and/or direction of annual percent change (APC) in ASIRs differ across rules. Additionally, we examine how differences in CCR- and IARC-based estimates vary across regions. RESULTS: Between 1992 and 2012, ASIR ratios (CCR:IARC) for all cancers combined increased from about 1 to 1.061 and 1.067 for males and females, respectively, and reached as high as 1.141 for male melanoma and 1.109 for female breast cancer. Between 2010 and 2012, ASIR ratios were elevated for stage 0-1 colorectal (males, 1.060; females, 1.072) and lung and bronchus cancer (males, 1.052; females, 1.061) and all stages of female breast cancer (stage 0-1, 1.100; stage 2, 1.061; stage 3, 1.059; stage 4, 1.094). Where differences existed, CCR-based trends tended to demonstrate steeper increases (eg, male and female melanoma) or less steep declines (eg, all male cancers, female breast cancer). Ontario was particularly impacted and substantially influenced national estimates. CONCLUSION: Multiple primary rules can substantially affect the magnitude and trend of ASIRs. The impact will continue to grow as the number of people surviving cancer, and thus at risk for subsequent cancers, continues to grow. Because of inconsistencies in the multiple primary rules used over time, we recommend using IARC rules for monitoring trends and making comparisons across jurisdictions, and using CCR rules for quantifying the full burden of cancer.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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