Rising Incidence of Colorectal Cancer in Young Adults Corresponds With Increasing Surgical Resections in Obese Patients
Bibliographic record
Abstract
OBJECTIVES: Strong evidence links obesity to esophageal cancer (EC), gastric cancer (GC), colorectal cancer (CRC), and pancreatic cancer (PC). However, national-level studies testing the link between obesity and recent temporal trends in the incidence of these cancers are lacking. METHODS: We queried the Surveillance, Epidemiology, and End Results (SEER) to identify the incidence of EC, GC, CRC, and PC. Cancer surgeries stratified by obesity (body mass index ≥30 kg/m) were obtained from the National Inpatient Sample (NIS). We quantified trends in cancer incidence and resections in 2002-2013, across age groups, using the average annual percent change (AAPC). RESULTS: The incidence of CRC and GC increased in the 20-49 year age group (AAPC +1.5% and +0.7%, respectively, P < 0.001) and across all ages for PC. Conversely, the incidence of CRC and GC decreased in patients 50 years or older and all adults for EC. According to the NIS, the number of patients with obesity undergoing CRC resections increased in all ages (highest AAPC was +15.3% in the 18-49 year age group with rectal cancer, P = 0.047). This trend was opposite to a general decrease in nonobese patients undergoing CRC resections. Furthermore, EC, GC, and PC resections only increased in adults 50 years or older with obesity. DISCUSSION: Despite a temporal rise in young-onset CRC, GC, and PC, we only identify a corresponding increase in young adults with obesity undergoing CRC resections. These data support a hypothesis that the early onset of obesity may be shifting the risk of CRC to a younger age.
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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) | 0.000 | 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 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".