Impact of Liver Metastasis on First-Line Immunotherapy in Stage IV Non-Small Cell Lung Cancer
Bibliographic record
Abstract
Background: Immunotherapy has become a key component of systemic therapy in stage IV non-small cell lung cancer (NSCLC). However, there have been conflicting reports of its efficacy in patients with liver metastasis (LM). Methods: Using National Cancer Database (NCDB), patients who have been diagnosed and treated at Commission on Cancer- participating US institutions were screened for analysis. Selection criteria included clinical stage IV NSCLC, available cTNM stage information, overall survival (OS) with at least 1 month, and diagnosis between 2015 and 2017. They were grouped based on status of LM as well as use of immunotherapy. Clinical characteristics were collected and their association with LM/immunotherapy was analyzed. Impact of immunotherapy on OS was examined according to LM status. Propensity score matching (PSM) analysis was also conducted. Results: A total of 83,479 including 18,497 LM-positive and 64,982 LM-negative patients met the study criteria. Presence of LM was associated with a number of clinical variables such as younger age, male sex, and chemotherapy. OS in patients with LM was significantly worse than that in those without LM (median OS, 5.0 vs. 8.8 months; hazard ratio (HR), 1.46; log-rank, P < 0.0001). Significant OS benefit from immunotherapy was observed in both LM-positive (median OS, 4.1 vs. 9.0 months; HR, 0.62; P < 0.0001) and negative groups (median OS, 7.2 vs. 15.6 months; HR, 0.64; P < 0.0001). Conclusion: Immunotherapy benefited similarly to the survival of metastatic NSCLC patients regardless of with or without LM. Further research to validate the result would be warranted.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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 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".