Cost-effectiveness of chemotherapy for nonsmall-cell lung cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
After decades of research into its prevention and treatment, lung cancer remains the leading cause of cancer death in North America and Europe. Approximately 75% of all new lung cancer diagnoses are of the nonsmall-cell subtype, and less than 25% of these patients are potentially operable upon first detection. First-generation cisplatin-based chemotherapy regimens for patients with metastatic disease achieved a median survival of 175 days, with 15 to 20% of patients alive at 1 year.In recent years, vinorelbine, gemcitabine, paclitaxel, and docetaxel have emerged as promising agents in the treatment of advanced nonsmall-cell lung cancer. Evidence from randomized trials demonstrates that when these agents are combined with cisplatin, the objective tumor response is 25 to 40%, with a median overall survival approaching 300 days. In addition, recent studies have shown that single-agent docetaxel improves survival and quality of life in patients with platinum-refractory nonsmall-cell lung cancer. Since these modest but important improvements in the management of nonsmall-cell lung cancer are achieved at a significant cost, cost has emerged as a major consideration in health policy decision-making. This article reviews the pharmacoeconomic literature to provide guidance on the cost-effective use of chemotherapy in the treatment of advanced nonsmall-cell lung cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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) | 0.000 | 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 it