A Phase I Study of Tomotherapy in Patients With Primary Benign and Low-grade Brain Tumors
Bibliographic record
Abstract
OBJECTIVES: To evaluate longitudinal quality of life and late neurotoxicity (>12 mo) of tomotherapy in patients with primary benign and low-grade brain tumors. METHODS: Between January 2006 and October 2009, 49 patients with brain tumors were treated with tomotherapy at 2 radiotherapy centers in Canada. The median age of the patients was 51.0 years (range, 21 to 74 y); there were 21 men (42.86%) and 28 women (57.14%). All 49 patients had an initial Karnofsky performance score ≥70. One patient (2.04%) received 45 Gy in 25 fractions, 27 patients (55.10%) received 50.4 Gy in 28 fractions, 15 patients (30.6%) received 54 Gy in 30 fractions, and 5 patients (10.2%) received 60 Gy in 30 fractions. A total of 47 patients were analyzed for late toxicity and outcomes. RESULTS: Changes in the Karnofsky Performance Status of the patients did not reach statistical significance (P>0.05). The majority of the quality of life parameters that reached a statistically significant level (P<0.05) of change at 2 years were changes toward improvement (drowsiness, itchy skin, emotional functioning, fatigue, nausea, and appetite). Statistically significant (P<0.05) interval deterioration in physical, role, and social functioning was observed. Actuarial overall survival at 5 years was 91.6%; disease-free survival at 5 years was 86.6%. CONCLUSIONS: IMRT helical tomotherapy is well tolerated, without statistically significant constitutional and late neurotoxicity up to the 2-year mark.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".