A surveillance study of the current status of reirradiation and patterns of practice
Bibliographic record
Abstract
The aim of this study was to survey the current status of reirradiation (Re-RT) and patterns of practice in Japan. An email questionnaire was sent to Kansai Cancer Therapist Group partner institutions, using questions similar to those in the Canadian radiation oncologist (RO) survey (2008). A total of 34 ROs from 28 institutions returned the survey. All 28 institutions experienced Re-RT cases in 2014. However, 26 of the 28 institutions (93%) reported difficulty in obtaining Re-RT case information from their respective databases. Responses from 19 institutions included the number of Re-RT cases; this rose from 183 in the period 2005-2009 (institution median = 4; 2-12.9) to 562 in the period 2010-2014 (institution median = 26; 2-225). Important considerations for indication of Re-RT were age (65%), performance status (83%), life expectancy (70%), absence of distant metastases (67%), and interval since previous treatment (73%). Previous total radiation dose (48%), volume of tissue irradiated (72%), and the biologically equivalent dose (BED; 68.5%) were taken into account during Re-RT planning. These factors were similar to those considered in the Canadian survey; however, the present study did not consider age. In eight site-specific scenarios, barring central nervous system recurrence, more than 90% of ROs agreed to perform Re-RT, which was higher than the percentage observed in the Canadian survey. Re-RT cases have increased in number and aroused interest among ROs in this decade of advanced technology. However, consensus building to establish guidelines for the practice and prospective evaluation of Re-RT is required.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".