Do We Have Enough Evidence to Implement Particle Therapy as Standard Treatment in Lung Cancer? A Systematic Literature Review
Bibliographic record
Abstract
Abstract Learning Objectives After completing this course, the reader will be able to: Evaluate the published results of particle therapy in the treatment of lung cancer and discuss their implications for the treatment of stage I and stage III NSCLC.Using the available evidence to date, assess the current role of particle therapy in the treatment of lung cancer.Identify relevant outstanding issues and address these issues with an action plan for further research. CME This article is available for continuing medical education credit at CME.TheOncologist.com Background. The societal burden of lung cancer is high because of its high incidence and high lethality. From a theoretical point of view, radiotherapy with beams of protons and heavier charged particles, for example, carbon ions (C-ions), should lead to superior results, compared with photon beams. In this review, we searched for clinical evidence to justify implementation of particle therapy as standard treatment in lung cancer. Methods. A systematic literature review based on an earlier published comprehensive review was performed and updated through November 2009. Results. Eleven fully published studies, all dealing with non-small cell lung cancer (NSCLC), mainly stage I, were identified. No phase III trials were found. For proton therapy, 2- to 5-year local tumor control rates varied in the range of 57%–87%. The 2- and 5-year overall survival (OS) and 2- and 5-year cause-specific survival (CSS) rates were 31%–74% and 23% and 58%–86% and 46%, respectively. Radiation-induced pneumonitis was observed in about 10% of patients. For C-ion therapy, the overall local tumor control rate was 77%, but it was 95% when using a hypofractionated radiation schedule. The 5-year OS and CSS rates were 42% and 60%, respectively. Slightly better results were reported when using hypofractionation, 50% and 76%, respectively. Conclusion. The present results with protons and heavier charged particles are promising. However, the current lack of evidence on the clinical (cost-)effectiveness of particle therapy emphasizes the need to investigate the efficiency of particle therapy in an adequate manner. Until these results are available for lung cancer, charged particle therapy should be considered experimental.
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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 | 0.036 | 0.171 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.009 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".