Advances in our understanding of postoperative adjuvant chemotherapy in resectable non-small-cell lung cancer
Bibliographic record
Abstract
PURPOSE OF REVIEW: After publication in 1995 of a meta-analysis of adjuvant chemotherapy in the treatment of NSCLC, a number of randomized trials investigated adjuvant chemotherapy using more active chemotherapeutic regimens and larger numbers of accrued patients per trial. This review will focus on recent clinical trials for adjuvant chemotherapy, and will help to interpret the applicability of these results to daily clinical practice. RECENT FINDINGS: Four large-scale randomized trials that used platinum-based chemotherapy have reported positive results during the last 3 years. These trials included cisplatin-based chemotherapy [the International Adjuvant Lung Cancer (IALT) trial], cisplatin plus vinorelbine [the National Cancer Institute of Canada (NCIC) BR10 trial], and carboplatin plus paclitaxel [the Cancer and Leukemia Group B (CALGB) 9633 trial]. More recently, another adjuvant trial [Adjuvant Navelbine International Trialist Association (ANITA)] was reported, which has added greatly to our understanding of the potential role of adjuvant treatment. Regarding adjuvant UFT (tegafur and uracil) chemotherapy, an individual patient data-based meta-analysis demonstrated its significant effect on survival in selected patients with completely resected non-small-cell lung cancer. SUMMARY: Recent trials indicate a survival benefit of postoperative adjuvant chemotherapy. These findings are anticipated to change the clinical management of patients with completely resectable non-small-cell lung cancer.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".