Systemic Therapies in Metastatic Non-Small-Cell Lung Cancer with Emphasis on Targeted Therapies: The Rational Approach
Bibliographic record
Abstract
Historically, first-line treatment of non-small-cell lung cancer (NSCLC) has been based on giving a limited number of cycles of chemotherapy to achieve tumour response or stable disease. Patients are then observed without active therapy until disease progresses, at which point, subsequent lines of therapy are given. In recent years, two new concepts have been introduced to the management of NSCLC: maintenance therapy and therapy with targeted agents. Maintenance therapy-with either a chemotherapeutic or biologic agent-is given immediately after first-line therapy to patients who have achieved tumour response or stable disease. Choice of therapy may include continuation of the agents included in the induction regimen or introduction of different agents (early second-line treatment) with the aim of preventing progression and prolonging progression-free survival. Targeted agents such as bevacizumab and erlotinib target critical molecular signalling pathways and provide several advantages over chemotherapy, including fewer toxicities and the possibility of a longer duration of therapy. This review examines the treatment options in all lines of therapy for metastatic NSCLC, focusing particularly on targeted therapies that have been approved in the United States, Canada, or Europe.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".