ASTRO Publishes Evidence-Based Guideline for Thoracic Radiotherapy
Bibliographic record
Abstract
ImageThe American Society for Radiation Oncology has a new guideline for use of external-beam radiation therapy, endobronchial brachytherapy, and concurrent chemotherapy to palliate thoracic symptoms caused by advanced lung cancer. Although many patients whose lung cancer has spread receive radiation therapy to treat symptoms such as cough, shortness of breath, bronchial obstruction, and chest pain, there has been no one specific treatment approach. This variation, a news release notes, prompted the Guidelines Subcommittee of ASTRO's Clinical Affairs and Quality Committee to identify the use of palliative thoracic radiation therapy as a high-priority topic needing an evidence-based guideline. This panel was co-chaired by George Rodrigues, MD, MSc, a radiation oncologist and clinician scientist at London Health Sciences Centre in Ontario, and Benjamin Movsas, MD, chairman of radiation oncology at Henry Ford Health System in Detroit. ASTRO's Board of Directors then put together a multidisciplinary task force that was charged with reviewing and synthesizing the current evidence to develop such a guideline. The task force's main findings are: Various regimens of thoracic external-beam radiation therapy are very effective for palliation of symptoms, with moderately higher-dose regimens associated with a modest improvement in survival for selected patients primarily with good performance status. There is no evidence to recommend the use of endobronchial brachytherapy in the routine initial palliative management of lung cancer. There is no added benefit to patients to use chemotherapy at the same time as radiation therapy in the relief of thoracic symptoms for lung cancer patients. However, optimally integrating sequential chemotherapy and radiation therapy is important in the management of lung cancer symptoms. “It is our hope that this evidence-based guideline will help doctors determine the optimal palliative radiation treatments for lung cancer patients, thereby yielding improved quality of life,” Dr. Movsas said in a statement. The guideline is now available online ahead of print in Practical Radiation Oncology.
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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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.015 | 0.016 |
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".