An international survey on liver metastases radiotherapy
Bibliographic record
Abstract
BACKGROUND: An international survey of radiation therapy (RT) of liver metastases was undertaken by the Liver Cancer Workgroup of the Third International Consensus on Metastases Workshop at the 2010 American Society for Radiation Oncology (ASTRO) meeting. MATERIAL AND METHODS: Canadian, European, Australian, New Zealand and American centers participated in this online survey. The survey had four objectives: 1) to describe the practice patterns for RT of liver metastases; 2) to report on the use of low-dose RT for symptomatic liver metastases; 3) to report on the use of technology; and 4) to describe the regional differences in the management of liver metastases. RESULTS: A total of 69 individuals treating liver metastases with radiotherapy responded to the survey. Regional response rates ranged from 39% to 50%. The primary professional affiliation of all respondents was evenly distributed amongst ASTRO, CARO, ESTRO and TROG/RANZCR. A 36% increase in the average annual number of referrals over the past five years is reported. The majority of referrals were for radical RT. The most common technologies used were 4D-CT (61%), SBRT (55%), IGRT (50%), and/or IMRT (28%). A uniform treatment approach was not found. The most commonly employed radical regimens were 45 Gy in 3 fractions, 40-50 Gy in 5 fractions, and 45 Gy in 15 fractions. Palliative regimens included 20 Gy in 5 fractions, 30 Gy in 10 fractions, 8 Gy in 1 fraction, and 10 Gy in 2 fractions. CONCLUSIONS: This survey suggests radiation oncologists will be seeing more referrals for liver RT. The majority of experience in liver metastases RT is with radical SBRT for focal metastases rather than low-dose palliative RT for symptom control. There is significant variation in technology utilization and dose regimens. Prospective studies or registries may allow for comparison of regimens and identification of parameters to optimize patient selection.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".