Biologic Cost of Caring for a Cancer Patient: Dysregulation of Pro- and Anti-Inflammatory Signaling Pathways
Bibliographic record
Abstract
PURPOSE: Caring for a family member with cancer is a psychologically demanding experience. However, it remains unclear whether the distress that caregiving provokes also takes a physiologic toll on the body. This study observed familial caregivers of patients with brain cancer for a year after diagnosis and tracked changes in neurohormonal and inflammatory processes. PATIENTS AND METHODS: Eighteen caregivers (age 50.4 +/- 3.5 years) and 19 controls (age 50.2 +/- 2.6 years) were assessed four times during a year (before and after radiotherapy, as well as 6 weeks and 4 months thereafter). Salivary biomarkers of hypothalamus-pituitary-adrenal axis and sympathetic nervous system (SNS) activity were collected, and blood was drawn for assessment of the systemic inflammatory markers C-reactive protein (CRP) and interleukin-6 (IL-6). Blood was also used to monitor in vitro IL-6 production by endotoxin-stimulated leukocytes and expression of mRNA for pro- and anti-inflammatory signaling molecules. RESULTS: Caregivers showed marked changes over time in diurnal output of salivary amylase, a marker of SNS activity, whereas secretions in controls were stable during follow-up. Cortisol output was similar in caregivers and controls. During the year, caregivers showed a profound linear increase in systemic inflammation, as indexed by CRP. At the same time, they displayed a linear decline in mRNA for anti-inflammatory signaling molecules and diminished in vitro glucocorticoid sensitivity. CONCLUSION: These preliminary data show that familial caregivers of patients with cancer experience marked changes in neurohormonal and inflammatory processes in the year after diagnosis. These changes may place them at risk for morbidity and mortality from diseases fostered by excessive inflammation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".