Prevalence of bowel dysfunction in colorectal cancer survivors.
Bibliographic record
Abstract
638 Background: There is limited research on the long-term bowel health outcomes of colorectal cancer (CRC) survivors even though colorectal surgery, radiation, and chemotherapy can pose significant morbidity for patients. Our aims were to characterize the prevalence of specific bowel complications in CRC survivors and to compare their outcomes with those of non-CRC survivors and non-cancer controls. Methods: Using population-based data from the 2009 U.S. National Health and Nutrition Examination Survey, we identified 3 different groups of adult patients: CRC survivors, non-CRC survivors, and non-cancer controls. Weighted multivariate logistic regression models were constructed to determine the relationship between survivor status and bowel health outcomes, while controlling for patient and disease characteristics. Main outcomes included leakage of gas, mucus, liquid stool, and solid stool. Stratified analyses were subsequently conducted to assess for effect modification based on gender (men vs. women), age (≤ 60 vs. >60), and ethnicity (white vs. non-white). Results: In total, 10,894 subjects were included: 75 CRC survivors, 910 non-CRC survivors, and 9909 non-cancer controls. Baseline characteristics were similar among all 3 patient groups. In univariate analyses, more CRC survivors reported bowel dysfunction, including leakage of: gas (15 vs. 12 vs. 10%, p=0.01), liquid stool (8 vs. 7 vs. 4%, p<0.001), and solid stool (2 vs. 0 vs. 0%, p<0.001) than non-CRC survivors and non-cancer controls. In multivariate analyses, CRC survivors continued to have significantly higher odds of solid stool incontinence (OR 2.09, 95% CI 1.24-3.53, p<0.05) when compared to the other groups. The association between surviving CRC and presence of bowel dysfunction was not modified by ethnicity, but specific outcomes, such as solid stool leakage, were more prominent in women (p=0.003) and those who were aged >60 years (p=0.002). Conclusions: Bowel problems are significantly more frequent among CRC survivors than non-CRC survivors and non-cancer patients, especially for women and the elderly. Studies to develop interventions that minimize these bowel complications are needed in order to improve the long-term health and quality of life for CRC survivors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".