Prognostic Implications of Timing of Immunotherapy in Stage IV Non-Small Cell Lung Cancer
Bibliographic record
Abstract
Background: Currently, the established approach for addressing stage IV non-small cell lung cancer (NSCLC) involves combining chemotherapy with immunotherapy. However, the necessity for molecular analysis prior to commencing immunotherapy often results in a delay in its initiation following the commencement of chemotherapy. Therefore, this study aimed to study the significance of postponing immunotherapy on pertinent patient outcomes. Methods: Using the National Cancer Database (NCBD), patients diagnosed with stage IV NSCLC between 2017 and 2018 were screened. Inclusion criteria comprised those treated with multi-agent chemotherapy as the first-line therapy within 30 days of treatment, surviving beyond 2 months of diagnosis, and absence of neuroendocrine pathology. Patients were grouped among those receiving immunotherapy within 30 days of chemotherapy, immunotherapy within 31 - 60 days of chemotherapy, or chemotherapy alone. Clinical characteristics were collected and their correlation with the timing of immunotherapy was evaluated. The impact of delaying immunotherapy on overall survival (OS) was investigated using Kaplan-Meier analysis. Multivariate Cox regression analysis was employed to identify independent prognostic variables associated with OS. Results: Our cohort comprised 99,008 patients with clinical stage IV NSCLC diagnosed between 2017 and 2018, which were distributed in the three treatment groups described above. Patients receiving immunotherapy within 30 days of chemotherapy showed greater OS in contrast to both those subjected to delayed immunotherapy (hazard ratio (HR) = 0.74, 95% confidence interval (CI): 0.64 - 0.87, P = 0.0003). Subsequent multivariate regression analysis showed that postponing immunotherapy, older age, male sex, white race, non-adenocarcinoma histology, higher clinical N stage, use of radiation treatment, and presence of liver metastasis were all associated with worse OS. Conclusions: Introducing immunotherapy within the first 30 days of chemotherapy initiation significantly increases survival in patients with stage IV NSCLC.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".