Association Among Glucocorticoid Receptor Sensitivity, Fatigue, and Inflammation in Patients With Head and Neck Cancer
Bibliographic record
Abstract
OBJECTIVE: Fatigued cancer patients often have high peripheral inflammation; however, the biological mechanisms of this association remain unclear. We examined whether decreased sensitivity of immune cells to the anti-inflammatory effects of glucocorticoids may contribute to inflammation and fatigue in head and neck cancer (HNC) patients during treatment. METHODS: HNC patients without distant metastasis and with curative intent (n = 77) were studied 1 week before intensity-modulated radiotherapy (IMRT) and 1 month after IMRT. At each time point, fatigue was measured by the Multidimensional Fatigue Inventory-20 along with plasma inflammation markers and glucocorticoid receptor (GR) sensitivity as determined by in vitro dexamethasone suppression of lipopolysaccharide-induced interleukin 6. Linear regression models were used. RESULTS: In contrast to our hypothesis, GR sensitivity increased during treatment; however, increased fatigue was associated with a lesser increase in GR sensitivity from baseline to 1 month after IMRT (unstandardized estimate = 4.07, p = .02). This effect was more prominent in human papillomavirus-unrelated HNCs (unstandardized estimate = 8.22, p = .002). Lower increases in GR sensitivity were also associated with increased inflammation at 1 month after IMRT as represented by C-reactive protein, interleukin 6, and tumor necrosis factor α. Addition of inflammation markers to models of GR sensitivity predicting fatigue indicated that these inflammation markers were stronger predictors of fatigue than GR sensitivity. CONCLUSIONS: Lower increases in GR sensitivity during HNC treatment were significantly predictive of increased fatigue and inflammation markers. Inflammation markers in turn predicted fatigue above and beyond levels of GR sensitivity. Our findings indicate that HNC patients with cancer-related fatigue may exhibit a decreased capacity for glucocorticoids to regulate inflammatory processes, as evidenced by a lower increase in GR sensitivity. Larger studies are necessary to verify the findings.
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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 | 0.000 |
| 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) | 0.000 | 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".