Prevalence and Persistence of Anxiety and Depression over Five Years since Breast Cancer Diagnosis—The NEON-BC Prospective Study
Bibliographic record
Abstract
Anxiety and depression are frequent among patients with breast cancer (BCa). Evidence of the persistence and recovery from these conditions and their determinants is scarce. We describe the occurrence of clinically significant anxiety and depression symptoms and their associated factors among BCa patients. A total of 506 women admitted in 2012 at the Portuguese Institute of Oncology of Porto were evaluated before treatment and after one, three, and five years (7.9% attrition rate). The five-year prevalence of anxiety and/or depression (Hospital Anxiety and Depression Scale, subscores ≥ 11) was 55.4%. The peak prevalence for anxiety was before treatment (38.0%), and after one year for depression (13.1%). One in five patients with anxiety/depression at baseline had persistent anxiety/depression over time, while only 11% and 22% recovered permanently from anxiety and depression, respectively, during the first year. Higher education, higher income, practicing physical activity, and adequate fruit and vegetable intake were protective factors against anxiety and/or depression. Loss of job and income, anxiolytics and antidepressants, cancer-related neuropathic pain, and mastectomy were associated with higher odds of anxiety and/or depression. These results highlight the importance of monitoring anxiety/depression during the first five years after cancer diagnosis and identify factors associated with these conditions.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".