Clinical and genetic factors associated with self-reported cognitive deficits in women with breast cancer: the “CAGE-Cog” study
Bibliographic record
Abstract
BACKGROUND: Breast cancer patients undergoing chemotherapy treatment are at particular risk of experiencing acute cognitive impairment leading to daily challenges in decision-making and reduced quality of life and functional autonomy. The aim was to assess the relationship between clinical and genetic factors and cognitive function in a sample of patients with breast cancer undergoing chemotherapy. METHODS: A cross-sectional study was carried out between November 2017 and June 2019 on women (N = 112) treated for breast cancer by intravenous chemotherapy at the oncology outpatient unit of Hôtel-Dieu de France Hospital, Beirut. Patients were evaluated with the 37-item Functional Assessment of Cancer Therapy-Cognitive Function (FACT-Cog). Other validated scales were also used to assess depression, anxiety, sleep disorders, pain, and fatigue. DNA was obtained by a buccal swab (FTA®technology) for genotyping of different genes (ABCB1, COMT, DRD2, OPRM1, CLOCK, CRY2, and PER2) using the Lightcycler®(Roche). RESULTS: The mean age of participants was 56.04 years. Multivariable analysis, taking the four FACT-Cog subscores as the dependent variables, showed that the mean cognitive score decreased with higher depression, anxiety, and insomnia scores. Patients with university education levels had better perceived cognitive abilities than those with primary education. Moreover, carrying the G allele for the OPRM1 polymorphism (c.118A > G;rs197791) was significantly associated with a better cognitive function compared to AA patients (B = 2.05; p = 0.038). CONCLUSIONS: A comprehensive oncological care plan should include a personalized assessment of all factors related to cognitive functioning in cancer patients, particularly anxiety and depression, to achieve an optimal patient outcome.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".