The Best Supportive Care in Stage III Non-Small-Cell Lung Cancer
Bibliographic record
Abstract
Lung cancer is a major cause of cancer deaths worldwide. Non-small-cell lung cancer (NSCLC) represents most lung cancer cases, and approximately one-third of patients present with stage III disease at diagnosis. As multiple treatment plans can be adopted for these patients depending on tumor size and nodal staging, stage III NSCLC management is challenging. Over the past decades, multidisciplinary teams (MDTs) have been implemented in healthcare services to coordinate actions among the different health care professionals involved in cancer care. The aim of this review was to discuss real-world evidence of the impact of MDTs on stage III NSCLC management, survival, and quality of life. Here, we performed a literature review to investigate the role of nutrition and navigational nursing in NSCLC care and the influence of MDTs in the choice of treatment plans, including immunotherapy consolidation, and in the management of chemotherapy and radiotherapy-related adverse events. We also performed a mapping review to identify gaps in the implementation of cancer care MDTs in healthcare services around the world.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".