Correlation of plasma levels of free insulin-like growth factor 1 and clinical benefit of the IGF-IR inhibitor figitumumab (CP- 751, 871)
Bibliographic record
Abstract
3539 Background: Free IGF-1 (fIGF-1) represents the biologically active fraction of IGF-1, the main circulating ligand of the Insulin-like Growth Factor type I Receptor (IGF-IR). Signaling through the IGF-IR induces tumor survival and resistance to cancer therapy. Figitumumab (F) (CP-751,871) inhibits IGF-1-induced IGF-IR autophosphorylation with an IC50 of 0.42 nmol/L. Methods: Plasma levels of fIGF-1 were measured in a phase 1b/2 multi-center study of Paclitaxel (T) and Carboplatin (C) and F in patients (pts) with treatment-naïve NSCLC. Other serum markers of the IGF-IR pathway, including circulating soluble IGF-IR (sIGF-IR), IGFBP3 and ALS (acid-labile subunit), were also investigated. The Kaplan-Meier method was used to estimate median survival times. Results: A total of 536 blood samples from 159 pts were analyzed. Baseline median and range fIGF-1 were 0.53 and 0.07–1.99 ng/mL. fIGF-1 directly correlated with IGFBP3 and ALS, and inversely with sIGF-IR (Rho=-0.430, p=0.03). Treatment with F resulted in dose-dependent accumulation of fIGF-1 with a sustained >10 fold increase in fIGF-1 plasma levels at the 20 mg/kg dose, suggesting complete systemic blockade of fIGF-1 binding to the IGF-IR. sIGF-IR decreased and IGFBP3 increased in response to F, but increases in IGBP3 were more modest than those of fIGF-1. Baseline plasma levels of fIGF-1 had a 96.6% negative predictive value for PFS status at 6 months (p=0.03). Median PFS were respectively 2.73 and 6.53 months for TC alone and TC with F (20 mg/kg) in the high fIGF-1 group (p=0.001) while no significant treatment effect of F was observed in the low (<0.54 ng/mL) fIGF-1 group. Sixty three percent of pts with high fIGF-1 had tumors of adenocarcinoma histology. Conclusions: IGF-1 is a key element in the biology of NSCLC of adenocarcinoma histology and its determination may contribute to the identification of pts who benefit from figitumumab therapy. [Table: see text]
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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 | 0.001 | 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 | 0.001 |
| 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".