Abstract S6-3: Neurocognitive impact in adjuvant chemotherapy for breast cancer linked to fatigue: A Prospective functional MRI study
Bibliographic record
Abstract
Abstract Background: Our previous research showed evidence of compromised cognitive function prior to adjuvant chemotherapy for breast cancer, with fatigue as a contributory factor. Fatigue is a common symptom reported by women treated for breast cancer, yet its association with neurocognitive function has not been systematically examined. In this prospective study, we examined possible alterations in neurocognitive responses, namely, working memory, from pre- to post- adjuvant treatment during functional magnetic resonance imaging (fMRI) and further investigated whether early fatigue might be linked to cognitive alterations over time. Methods: Women treated with either adjuvant chemotherapy (anthracyline-based combination regimen, n=29) or radiotherapy (n = 37) for localized breast cancer (Stages 0-IIIa) and age-matched healthy controls (n = 32) were enrolled. Participants performed a verbal working memory task (VWMT) with varying levels of demand for cognitive control during fMRI scanning and provided self-reports of fatigue (FACT-F) at two time points coincident with pre- and one-month post chemotherapy assessments. Imaging data were analyzed with general linear models using SPM5; comparative statistics were used to determine group differences, and correlational analyses addressed relationships of fatigue and neurocognitive measures. Findings: The chemotherapy group reported significantly greater severity of fatigue (p < .05) and performed less accurately on the VWMT both pre- and one-month post-treatment than the other groups. Greater fatigue was correlated with poorer performance on the VWMT at both time points across groups, with stronger correlation post-treatment (r = −.22, p = .03). A 2 time-point (pre- vs. post-treatment) × 2 group (chemotherapy vs. controls) × 2 demand-level contrasts (high minus low vs. medium minus low) analytic model showed a significant group × time interaction (p < .05), mainly due to lower pre-treatment activation in an area of the prefrontal cortex supporting working memory, the anatomical left inferior frontal gyrus (LiFG), at higher task demand in the chemotherapy group. The radiotherapy group scored between the other two groups with intermediate activation of those contrasts. Of interest, lower pre-treatment activation in the LiFG in the high-low demand contrast predicted severity of fatigue across all participants at the post-treatment assessment (r = −.27, p < .01), linking early compromise in neurocognitive performance with greater fatigue over time. Discussion: Neurocognitive alterations during a working memory task and greater fatigue were evident before any adjuvant chemotherapy for breast cancer. Notably, functional alterations in working memory processes were evident with fMRI before adjuvant chemotherapy and predicted severity of post-treatment fatigue. Importantly, across all participants, greater fatigue over time was correlated with reduced cognitive performance. Taken together, these findings indicate that pre-treatment neurocognitive compromise and fatigue are key contributors to the cognitive impact often attributed solely to chemotherapy. Early therapeutic interventions targeting fatigue may improve cognitive function and reduce the distress of “chemo brain” throughout the course of adjuvant treatment. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr S6-3.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".