Mortality and years of life lost of colorectal cancer in China, 2005–2020: findings from the national mortality surveillance system
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
BACKGROUND: Colorectal cancer (CRC) is the fourth cause of cancer death in China. We aimed to provide national and subnational estimates and changes of CRC premature mortality burden during 2005-2020. METHODS: Data from multi-source on the basis of the national surveillance mortality system were used to estimate mortality and years of life lost (YLL) of CRC in the Chinese population during 2005-2020. Estimates were generated and compared for 31 provincial-level administrative divisions in China. RESULTS: Estimated CRC deaths increased from 111.41 thousand in 2005 to 178.02 thousand in 2020; age-standardized mortality rate decreased from 10.01 per 100,000 in 2005 to 9.68 per 100,000 in 2020. Substantial reduction in CRC premature mortality burden, as measured by age-standardized YLL rate, was observed with a reduction of 10.20% nationwide. Marked differences were observed in the geographical patterns of provincial units, and they appeared to be obvious in areas with higher economic development. Population aging was the dominant driver which contributed to the increase in CRC deaths, followed by population growth and age-specific mortality change. CONCLUSIONS: Substantial discrepancies were observed in the premature mortality burden of CRC across China. Targeted considerations were needed to promote a healthy lifestyle, expand cost-effective CRC early screening and diagnosis, and improve medical treatment to reduce CRC mortality among high-risk populations and regions with inadequate healthcare resources.
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.
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 | 0.001 | 0.003 |
| 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 | 0.001 |
| 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