Cancer anorexia‐cachexia syndrome is characterized by more than one inflammatory pathway
Bibliographic record
Abstract
BACKGROUND: The interdependence of cytokines and appetite-modifying hormones implicated in cancer anorexia-cachexia syndrome (CACS) remains unclear. This study aimed to regroup these cytokines and hormones into distinct inflammatory (or non-inflammatory) pathways and determine whether these pathways can classify patients with CACS phenotypes. METHODS: Clinical characteristics of 133 patients [61.7% male; mean age = 63.4 (SD: 13.1) years] with advanced cancer prior to oncology treatments were documented, including weight loss history. Patients completed the Functional Assessment of Anorexia-Cachexia Therapy (FAACT) questionnaire and Timed Up and Go test and had their sex-standardized skeletal muscle index (z-SMI) and fat mass index (z-FMI) derived using computed tomography scans. Their plasma levels of cytokines and appetite-modifying hormones were also determined. Date of death was recorded. Exploratory factor analysis (EFA) was used to regroup 15 cytokines and hormone into distinct inflammatory pathways (factors). For each patient, regression factor scores (RFS), which tell how strongly the patient associates with each factor, were derived. Two-step cluster analysis on the RFS was used to classify patients into groups. CACS phenotypes were correlated with RFS and compared between groups. Groups' survival was estimated using Kaplan-Meier analysis. RESULTS: ; SD: 56.25), and 62 (46.6%) had cachexia. EFA identified three factors: (F-1) IFN-γ, IL-1β, Il-4, IL-6, IL-10, IL-12, TGFβ1 (positive contribution), and IL-18 (negative); (F-2) IL-8, IL-18, MCP-1, TGFβ1, TNF-α (positive), and ghrelin (negative); and (F-3) TRAIL and leptin (positive), and TGFβ1 and adiponectin (negative). RFS-1 was associated with cachexia (P = 0.002); RFS-2, with higher CRP (P < 0.0001) and decreased physical function (P = 0.01); and RFS-3 with better appetite (P = 0.04), lower CRP (P = 0.002), higher z-SMI (P = 0.04) and z-FMI (P < 0.0001), and less cachexia characteristics (all P < 0.001). Four patient groups were identified with specific RFS clusters aligning with the CACS continuum from no cachexia to pre-cachexia, cachexia, and terminal cachexia. Compared to the other two groups, groups 1 and 2 had higher plasma levels of IL-18 and TRAIL. Group 1 also had lower inflammatory cytokines, adiponectin, and CRP compared to the other three groups. Group 3 had inflammatory cytokine levels similar to group 2, except for TNF-α and leptin which were lower. Group 4 had very high inflammatory cytokines, adiponectin, and CRP compared to the other 3 groups (all P < 0.0001). Groups 3 and 4 had worse cachexia characteristics (P < 0.05) and shorter survival (log rank: P = 0.0009) than the other two groups. CONCLUSIONS: This exploratory study identified three distinct pathways of inflammation, or lack thereof, characterizing different CACS phenotypes.
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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 | 0.001 |
| 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) | 0.001 | 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".