Effect of molecular profile in non-small cell lung carcinoma on the development of brain metastases.
Bibliographic record
Abstract
e20640 Background: Non-Small Cell Lung Cancer (NSCLC) is a heterogenous disease with 44% of pts developing brain metastases (BMs). Molecular Profiling (MP) enables selection of patients for targeted therapy and provides prognostic information. This study aims to investigate the impact of MP on the incidence, presentation and prognosis of brain metastases in patients with NSCLC. Methods: Patients (> 18 years) with NSCLC who enrolled in the IMPACT/COMPACT trial were evaluated in 2 groups evaluated: (1) NSCLC with BMs, (cross referencing with prospective BM database) (2) NSCLC without BMs. The following variables were investigated: Age at diagnosis, Smoking Status, Extracranial Disease Status, Race, Mutations (EGFR, KRAS, TP53, and ALK with tumor profiling using TruSeq Amplification or Sequenom Test), Gender, Histology, and Stage at Diagnosis. Endpoints: BM Yes/No. Logistic regression was used to assess the impact of variables on the occurrence of BMs. Results: A total of 242 pts with NSCLC were identified, of which 88 pts (36%) had BMs. Median age was 62 years (range 18-89 years). Median follow up was 32.5 months (range 0.82–256.9 months). Of all patients, 33.3% of Asian pts had EGFR mutation compared to 18.7% of Caucasian pts (Chi-squared p=0.068). On univariate analysis, pts diagnosed with BMs were more likely to be younger age (p=0.006), be Caucasian (p=0.022), have adenocarcinoma histology (p=0.022), be diagnosed initially with stage IV disease (versus lower stage; p=0.007), and have EGFR mutation (p=0.018). Conclusions: The molecular profile impacts the incidence and timing of brain metastases in patients with NSCLC. Specifically, our study found the following factors were associated with the development of BMs: Age (younger), Race (Caucasian), Tumor stage (advanced), Histology (adenocarcinoma) and EGFR mutation present. Patients with EGFR positive tumors developed BMs slower after their initial lung cancer diagnosis. Development of BMs: Multivariable analysis Variable OR, (95% CI) p value Age (younger) 1.04, (1.01-1.06) 0.007 Race – Caucasian 2.75, (1.25-6.06) 0.007 Stage IV at diagnosis 2.35, (1.33-4.15) 0.003 Mutation - EGFR 2.57, (1.30-5.10) 0.007
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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 | 0.001 |
| 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) | 0.003 | 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".