Current Status of Clinical Trials in Head and Neck Cancer 2014
Bibliographic record
Abstract
INTRODUCTION: The last few years have seen significant increase in the number of available clinical trials in head and neck cancer. It has been difficult to stay abreast of these efforts because multiple cooperative groups and institutions are engaged in their recruitment. This review presents the state of the art of available clinical trials organized around major research themes. DATA SOURCES: Published literature, published cooperative group monographs, expert review. REVIEW METHODS: Initial themes in head and neck cancer clinical trial development were first identified along with examples. Opinions from an international panel of multidisciplinary experts were then solicited. RESULTS/DISCUSSION: Current major themes of head and neck clinical trials centered on 5 major themes: (1) recognition of human papillomavirus oropharynx cancer and optimal treatment strategies, (2) defining the role of transoral surgery in head and neck cancer treatment, (3) improving postoperative adjuvant treatment, (4) investigation of rare malignancies, and (5) the importance of biomarker-driven, innovative, and targeted therapy investigation. CONCLUSIONS: A number of exciting clinical trials are currently in development or accrual with the potential for tremendous impact and improvement of the treatment of head and neck cancer. IMPLICATIONS FOR PRACTICE: Awareness by practicing otolaryngologists and trainees of these current themes will be essential for study accrual, success, and improvement in the care of head and neck cancer.
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How this classification was reachedexpand
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".