Colorectal Cancer and Onset of Anxiety and Depression: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Research suggests that colorectal cancer (CRC) is associated with mental health disorders, primarily anxiety and depression. To synthesize this evidence, we conducted a systematic review and meta-analysis of studies evaluating the onset of anxiety and depression among patients with CRC. We searched EMBASE and Medline from inception to June 2022. We included original, peer-reviewed studies that: used an epidemiologic design; included patients with CRC and a comparator group of individuals without cancer; and evaluated anxiety and depression as outcomes. We used random effects models to obtain pooled measures of associations. Quality assessment was completed using the Newcastle-Ottawa scale. Of 7326 articles identified, 8 were eligible; of which 6 assessed anxiety and depression and 2 assessed depression only. Meta-analyses showed a non-significant association between CRC and anxiety (pooled HR 1.67; 95% CI 0.88 to 3.17) and a significant association between CRC and depression (pooled HR 1.78; 95% CI 1.23 to 2.57). Predictors of anxiety and depression among patients with CRC included clinical characteristics (e.g., comorbidities, cancer stage, cancer site), cancer treatment (e.g., radiotherapy, chemotherapy, colostomy), and sociodemographic characteristics (e.g., age, sex). The impacts of anxiety and depression in patients with CRC included increased mortality and decreased quality of life. Altogether, our systematic review and meta-analysis quantified the risks and impacts of CRC on anxiety and depression, particularly an increased risk of depression after CRC diagnosis. Findings provide support for oncologic care that encompasses mental health supports for patients with CRC.
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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 | 0.012 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.043 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".