Evaluation of VeriStrat, a serum proteomic test, in the randomized, open-label, phase 3 LUX-Lung 8 (LL8) trial of afatinib (A) versus erlotinib (E) for the second-line treatment of advanced squamous cell carcinoma (SCC) of the lung.
Bibliographic record
Abstract
e20510 Background: Treatment (tx) options for patients (pts) with advanced SCC of the lung after progression on platinum-based chemotherapy are limited. In LL8, the irreversible ErbB family blocker, A, significantly improved OS, PFS and disease control rate vs E, a reversible EGFR TKI, in 795 pts with SCC of the lung. VeriStrat is a serum protein test that utilizes MALDI-TOF mass spectrometry to assign a ‘GOOD' (VS-G) or ‘POOR' (VS-P) classification and has demonstrated prognostic and predictive utility for EGFR targeted therapies in NSCLC.1 Here, the predictive ability of VeriStrat was tested in LL8; OS was the primary efficacy variable. Methods: Pre-tx serum samples, blinded to clinical outcome, were classified as VS-G or VS-P based on predefined reference groups. Clinical outcomes were analyzed with respect to VeriStrat status in the overall population (all pts with both clinical and VeriStrat data) and in predefined subgroups. Results: 675 pts were classified (VS-G: 412; VS-P: 263). In the VS-G group, median OS was 11.5 mo for A and 8.9 mo for E (HR [95% CI] 0.79 [0.63–0.98]; p = 0.03); median PFS was 3.3 mo for A and 2.0 mo for E (HR [95% CI] 0.73 [0.59–0.92]; p = 0.005). In the VS-P group, median OS was 4.7 mo for A and 4.8 mo for E (HR [95% CI] 0.90 [0.70–1.16]; p = n.s.); median PFS was 1.9 mo for both A and E (HR [95% CI] 0.96 [0.73–1.27]; p = n.s.). In pts treated with A, both OS (HR [95% CI] 0.40 [0.31–0.51]; p < 0.0001) and PFS (HR [95% CI] 0.56 [0.43–0.72]; p < 0.0001) were longer in the VS-G group vs the VS-P group. Multivariate analysis showed that VeriStrat was an independent predictor of OS and PFS in pts treated with A, regardless of ECOG PS, best response to first-line therapy, age and race. However, there was no interaction between VeriStrat classification and tx group for OS (pint = 0.53) or PFS (pint = 0.12). Conclusions: In LL8, VeriStrat has a strong independent stratification effect in pts with relapsed/refractory SCC of the lung treated with A. In these difficult to treat pts, A conferred significantly better OS and PFS than E in the VS-G group, with a median OS of 11.5 mo. 1. Gregorc V, et al. Lancet Oncol 2014;15:713‒21 Clinical trial information: NCT01523587.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".