Systemic Inflammation and Nutritional Status in Patients on Palliative Cancer Care: A Systematic Review of Observational Studies
Bibliographic record
Abstract
Objective: This systematic literature review explores the results of studies that have analyzed the association between inflammation and nutritional status in patients with cancer in palliative care. Methods: The bibliographic research was performed in May 2019, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Group guidelines. The inclusion criteria were papers that (1) had an online abstract available, (2) were original, (3) used a cohort or cross-sectional design, (4) involved patients with advanced cancer in palliative care, and (5) assessed the association between inflammation and nutritional status. The quality assessment was performed using the Newcastle-Ottawa Scale. Results: Nine studies were selected. Weight loss (WL; n = 7) was the most common nutritional marker employed and C-reactive protein (CRP; n = 6) was the most common inflammatory marker. There was considerable variability (39.0%-92.2%) in the proportion of patients who had WL in a 6-month period, while CRP >5 mg/dL was common in 45.3% to 73.9% of patients. Systemic inflammation was related to nutritional status, highlighting the relationship between CRP and WL and lean mass (LM). Patients with CRP >10 mg/L have been found to have a lower LM ( P < .001) and a faster rate of loss of LM at a faster rate during the disease trajectory ( P = .030). Conclusion: Nutritional status is associated with systemic inflammatory response. Inflammatory markers should be considered an additional parameter for the nutritional diagnosis of patients with cancer in palliative care.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".