Evolution of Depression and Anxiety among Breast Cancer Patients: a prospective analysis using clinical, biological and genetic factors
Bibliographic record
Abstract
Introduction Numerous studies have explored the symptoms and course of depression and anxiety in breast cancer patients and identified various clinical, sociodemographic, and genetic factors associated with their evolution. Nevertheless, these studies have been limited in duration and have focused on specific time points during chemotherapy or post-treatment follow-up. Furthermore, these studies included patients receiving different treatment regimens and used different tools to assess symptoms. Objectives To assess the prospective evolution of depression in breast cancer patients over eight consecutive chemotherapy cycles, taking into account sociodemographic, clinical, biological, and genetic factors. Methods A prospective longitudinal study was conducted on 69 breast cancer patients treated with intravenous chemotherapy at the oncology outpatient unit of the Hôtel-Dieu de France hospital (2017-2019; Ethics: CEHDF1016). The Hospital Anxiety and Depression Scale (HADS) was used to evaluate anxiety and depression in patients. Genotyping was performed for several genes (ABCB1, COMT, DRD2, OPRM1, CLOCK, CRY2, PER2) using the Lightcycler® 2.0 (Roche). Results Univariate repeated measures analysis showed differences in the evolution of depression and anxiety over time. For depression, a polynomial linear contrast for HADS-D scores was noted from cycle 1 to cycle 8, with a significant increase in depression at cycles 7 and 8 compared with cycle 1 (p-value cycle7=0.004 and p-valuecycle8=0.009; Figures 1 & 2). Repeated measures analysis for anxiety showed a decrease in anxiety scores between cycles 1 and 6 of chemotherapy, followed by an increase starting cycle 6 (a polynomial trend for contrasts) (p-value cycle6 versus 1=0.038; Figures 1 & 2). Multivariable analysis showed that higher anxiety and depression scores at baseline were both associated with higher depression and anxiety scores over time. Other clinical and genetic factors, including polymorphisms in the OPRM1, PER2, and COMT genes, were also significantly associated with higher depression and anxiety scores. Image: Image 2: Conclusions Our findings highlight the importance of understanding the trajectories of depression and anxiety over time in women with breast cancer and identifying the triggering factors. Such personalized approaches would improve patient quality of life. Disclosure of Interest None Declared
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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 | 0.001 |
| 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) | 0.001 | 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".