The Importance of Multidisciplinary Team Management of Patients with Non-Small-Cell Lung Cancer
Bibliographic record
Abstract
Historically, a simple approach to the treatment of non-small-cell lung cancer (nsclc) was applicable to nearly all patients. Recently, a more complex treatment algorithm has emerged, driven by both pathologic and molecular phenotype. This increasing complexity underscores the importance of a multidisciplinary team approach to the diagnosis, treatment, and supportive care of patients with nsclc. A team approach to management is important at all points: from diagnosis, through treatment, to end-of-life care. It also needs to be patient-centred and must involve the patient in decision-making concerning treatment. Multidisciplinary case conferencing is becoming an integral part of care. Early integration of palliative care into the team approach appears to contribute significantly to quality of life and potentially extends overall survival for these patients. Supportive approaches, including psychosocial and nutrition support, should be routinely incorporated into the team approach. Challenges to the implementation of multidisciplinary care require institutional commitment and support.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| 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".