Prognostic and predictive effect of <i>KRAS</i> gene copy number and mutation status in early stage non-small cell lung cancer (NSCLC) patients.
Bibliographic record
Abstract
e21080 Background: The prognostic and predictive role of KRAS mutations and gene copy number aberrations (CNA) in early stage NSCLC is unclear. In this study, we characterize the prognostic effect of KRAS mutation status and concomitant CN gain in early stage NSCLC, and determine the ability to predict survival benefit from adjuvant chemotherapy. We hypothesize that concomitant KRAS mutations and CN gain will be prognostic of worse survival compared to KRAS mutations alone. Methods: Clinical and genomic data from The LACE (Lung Adjuvant Cisplatin Evaluation)-BIO consortium was utilized. CNA were categorized as Gain or Neutral (Neut)/Loss; mutation status was defined as wild type (WT) or mutant (MUT). WT+Neut/Loss (reference), WT+Gain, MUT+Gain and MUT+Neut/Loss groups were compared in all patients and the adenocarcinoma subgroup. Primary endpoint was lung-cancer-specific survival (LCSS); secondary endpoints were DFS and OS. Survival curves were assessed using Kaplan-Meier and log-rank tests. Concomitant KRAS CNA and mutation status was correlated to endpoints using a Cox proportional hazards model stratified by trial and adjusted for treatment, age, gender, histology, WHO performance status, surgery type, tumor and nodal stage. A treatment-by-variable interaction was added to evaluate predictive effect. Results: 946 (399 adenocarcinoma) patients had complete KRAS mutation, CNA and clinical data: 41 (30) MUT+Gain, 145 (99) MUT+Neut/Loss, 125 (16) WT+Gain, 635 (254) WT+Neut/Loss. There was a negative prognostic effect of KRAS MUT+Neut/Loss for LCSS (HR = 1.32 [1.01-1.71]) on univariable analysis, and to a lesser extent after adjusting for covariates (HR = 1.28 [0.97-1.68]). A similar non-significant trend was observed in KRAS MUT+Gain patients for LCSS (HR = 1.34 [0.83-2.17]), DFS (HR = 1.34 [0.86-2.09]) and OS (HR = 1.59 [0.99-2.54]). There was no significant predictive effect in the overall population; however, a potential predictive effect of KRAS for OS was seen in the adenocarcinoma subgroup (interaction p = 0.046). KRAS MUT+Gain was associated with a beneficial effect of chemotherapy on DFS (HR = 0.33 [0.11-0.99], p = 0.048), with a non-significant trend also seen for LCSS (HR = 0.41 [0.13-1.33]) and OS (HR = 0.40 [0.13-1.26]). Conclusions: A small prognostic effect of KRAS mutation was identified for LCSS. A potential predictive effect of concomitant KRAS mutation status and CNA was observed for DFS in adenocarcinoma patients. These results could be driven by the small number of patients and require further validation.
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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 | 0.001 |
| 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".