Impact of New Chemotherapeutic and Targeted Agents on Survival in Stage IV Non-Small Cell Lung Cancer
Bibliographic record
Abstract
PURPOSE: Significant advances in the systemic management of metastatic non-small cell lung cancer (NSCLC) have occurred over the past decade, with options now including multiple lines of chemotherapy, epidermal growth factor receptor inhibitors, and antiangiogenic agents. Improvements in overall survival have been demonstrated in randomized controlled trials comparing these newer agents with best supportive care or standard therapy. This study examined uptake of these therapies in general practice and their impact on survival. METHODS: This retrospective cohort study compared demographic, treatment, and survival data among 987 patients diagnosed with stage IV NSCLC at two institutions in 1998, 2003, and 2008. Cohorts were selected based on intervals when doublet chemotherapy, second-line chemotherapy, and targeted agents were incorporated into the standard treatment regimen. RESULTS: The proportion of patients receiving systemic therapy increased over time (20% in 1998, 42% in 2008). Overall survival improved significantly across cohorts (p < .001), with 2-year survival rates of 0.3% in 1998, 4% in 2003, and 15% in 2008. In a multivariate survival analysis, the 2003 and 2008 cohorts were independently associated with longer survival, as was the use of one or more lines of systemic therapy. Elderly patients (aged ≥70 years) were also more likely to receive systemic therapy over time, with longer overall survival (p < .001). CONCLUSION: Over the past decade, there has been an increasing use of systemic therapy in stage IV NSCLC patients, including the elderly. This has been associated with significantly longer overall survival.
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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 | 0.003 |
| 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".