Pre-diagnostic anthropometry and survival after colorectal cancer diagnosis in Western European populations
Bibliographic record
Abstract
General and abdominal adiposity are associated with a high risk of developing colorectal cancer (CRC), but the role of these exposures on cancer survival has been less studied. The association between pre-diagnostic anthropometric characteristics and CRC-specific and all-cause death was examined among 3,924 men and women diagnosed with CRC between 1992 and 2009 in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Multivariable Cox proportional hazards models were used to calculate hazard ratios (HRs) and corresponding 95% confidence intervals (CIs). Over a mean follow-up period of 49 months, 1,309 deaths occurred of which 1,043 (79.7%) were due to CRC. In multivariable analysis, pre-diagnostic BMI ≥ 30 kg/m(2) was associated with a high risk for CRC-specific (HR = 1.26, 95% CI = 1.04-1.52) and all-cause (HR = 1.32, 95% CI = 1.12-1.56) death relative to BMI <25 kg/m(2). Every 5 kg/m(2) increase in BMI was associated with a high risk for CRC-specific (HR = 1.10, 95% CI = 1.02-1.19) and all-cause death (HR = 1.12, 95% CI = 1.05-1.20); and every 10 cm increase in waist circumference was associated with a high risk for CRC-specific (HR = 1.09, 95% CI = 1.02-1.16) and all-cause death (HR = 1.11, 95% CI = 1.05-1.18). Similar associations were observed for waist-to-hip and waist-to-height ratios. Height was not associated with CRC-specific or all-cause death. Associations tended to be stronger among men than in women. Possible interactions by age at diagnosis, cancer stage, tumour location, and hormone replacement therapy use among postmenopausal women were noted. Pre-diagnostic general and abdominal adiposity are associated with lower survival after CRC diagnosis.
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.
How this classification was reachedexpand
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) | 0.001 | 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 teacher head, 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".