Associations between Plasma Insulin-Like Growth Factor Proteins and C-Peptide and Quality of Life in Patients with Metastatic Colorectal Cancer
Bibliographic record
Abstract
OBJECTIVE: Predictors of quality of life (QOL) in patients with metastatic colorectal cancer are lacking. The insulin-like growth factor (IGF) family of proteins is associated with QOL in noncancer populations. We sought to study whether these proteins are associated with QOL in patients with colorectal cancer. METHOD: We used a cohort of 526 patients with metastatic colorectal cancer treated with combination chemotherapy. Plasma samples of IGF-I, IGF-II, IGF binding protein-3, and C-peptide were collected before initiation of chemotherapy. QOL was measured by the uniscale instrument and the Symptom Distress Scale at baseline and throughout treatment. RESULTS: Baseline plasma levels of IGF-I and IGF-II before initiation of chemotherapy were significantly associated with several important baseline QOL measures in patients with metastatic colorectal cancer. Patients with lower levels of IGF-I reported increased distress with regard to appearance, appetite, cough, and nausea intensity after adjustment for potential confounders. Similarly, decreased levels of IGF-II were predictive of worse quality related to appearance, appetite, fatigue, nausea frequency and intensity, pain frequency, and composite Symptom Distress Scale score. IGF binding protein-3 and C-peptide were not predictive of baseline QOL. Baseline biomarkers were not associated with subsequent changes in QOL during treatment. Higher body mass index was significantly associated with superior baseline QOL in several areas; nonetheless, the association of IGF-I and IGF-II with baseline QOL measures remained significant even after controlling for baseline body mass index. CONCLUSION: Baseline plasma IGF-I and IGF-II are significantly associated with symptom distress. Whether this association is simply reflective of patient nutritional status and/or disease burden or represents an independent biological effect of IGFs on QOL remains uncertain. Nonetheless, these data suggest that molecular biomarkers may be useful predictors of QOL in cancer patients.
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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 | 0.000 | 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".