A single institution study evaluating outcomes of PD-L1 high KRAS-mutant advanced non-small cell lung cancer (NSCLC) patients treated with first line immune checkpoint inhibitors
Bibliographic record
Abstract
AIM: This study aimed to evaluate the impact of KRAS status on the efficacy of first-line immune checkpoint inhibitors (ICI) in patients with advanced non-small cell lung cancer (NSCLC). PATIENTS AND METHODS: Patients with advanced incurable or metastatic NSCLC with PD-L1 ≥50% treated with palliative-intent, single-agent PD-1/PD-L1 inhibitors at the Cancer Centre of Southeastern Ontario were included. KRAS mutation status was determined via massively parallel sequencing. Primary study outcome was median overall survival (mOS). RESULTS: Seventy-eight patients (59 non-squamous, 19 squamous) were identified; only non-squamous patients were included in KRAS mutation analyses. Thirty patients (51%) were KRAS-MT (mutant), with G12C (19%), G12V (15%), and G12D (13%) accounting for the most common KRAS mutation subtypes. There was no difference in mOS between KRAS-MT and KRAS-WT (wild-type) patients (12.9 vs. 19.3 months, p = 0.879). There was a non-significant trend towards worse mOS in KRAS G12C patients compared to non-G12C and KRAS-WT patients (11.4 vs. 44.9 vs. 19.3 months, p = 0.772). On multivariable analysis, KRAS-MT status was not associated with mOS (HR 0.901, 95%CI 0.417-1.946, p = 0.791). ECOG≥2 was an independent prognostic factor for worse mOS (HR 2.853, 95%CI 1.237-6.583, p = 0.014). Immune-related adverse events did not differ between KRAS-MT and KRAS-WT groups (48% vs. 52%, p = 1.000). CONCLUSIONS: KRAS mutation status did not have a significant impact on ICI efficacy or safety. However, a non-significant trend towards worse survival was noted in patients treated with ICI whose tumours harboured the KRAS G12C variant. This study provides valuable information for comparative analysis in the future.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 teacher head, 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".