Trajectories of cognitive performance over five years in a prospective cohort of patients with breast cancer (NEON-BC)
Bibliographic record
Abstract
PURPOSE: To identify trajectories of cognitive performance up to five years since diagnosis and their predictors, in a cohort of patients with breast cancer (BCa). METHODS: A total of 464 women with BCa admitted to the Portuguese Institute of Oncology, Porto, during 2012, were evaluated with the Montreal Cognitive Assessment (MoCA) before any treatment, and after one, three and five years. Probable cognitive impairment (PCI) at baseline was defined based on normative age- and education-specific reference values. Mclust was used to define MoCA trajectories. Receiver Operating Characteristic curves were used to assess the predictive accuracy for cognitive trajectories. RESULTS: Two trajectories were identified, one with higher scores and increasing overtime, and the other, including 25.9% of the participants, showing a continuous decline. To further characterize each trajectory, participants were also classified as scoring above or below the median baseline MoCA scores. This resulted in four groups: 1) highest baseline scores, stable overtime (0.0% with PCI); 2) lowest baseline scores (29.5% with PCI); 3) mid-range scores at baseline, increasing overtime (10.5% with PCI); 4) mid-range scores at baseline, decreasing overtime (0.0% with PCI). Adding the change in MoCA during the first year to baseline variables significantly increased the accuracy to predict the downward trajectory (area under the curve [AUC] = 0.732 vs. AUC = 0.841, P < 0.001). CONCLUSION: Four groups of patients with BCa with different cognitive performance trends were identified. The assessment of cognitive performance before treatments and after one year allows for the identification of patients more likely to have cognitive decline in the long term.
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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) | 0.000 | 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 | 0.000 |
| 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".