Biochemical, pathologic, toxicity, and quality-of-life outcomes in a five-fraction hypofractionated accelerated radiotherapy treatment using standard linear accelerators and gold seed fiducials.
Bibliographic record
Abstract
186 Background: Biological dose escalation through hypofractionated image-guided radiotherapy (H-IGRT) holds the promise of improved patient outcomes, system capacity but decreased cost. In 2006 we initiated a prospective trial of H-IGRT of patients with low risk localized prostate cancer. In this report, we report the toxicities, quality of life (QOL), biochemical and pathologic outcomes of this cohort with more mature follow-up. Methods: A phase I/II study in which patients with T1-2b, Gleason≤6, and PSA≤10 ng/ml prostate cancer received 35 Gy in 5 fractions, once a week over 29 days. No patients received hormone therapy. Treatment was delivered with intensity modulated radiotherapy (IMRT) on standard linear accelerators, with daily image guidance using gold seed fiducials, and a 4 mm CTV-PTV margin. CTCAE v3.0 and RTOG late morbidity scores were used to assess acute and late toxicities, respectively. QOL was assessed by the Expanded Prostate Cancer Index Composite (EPIC). Biochemical control (BC) was defined by the Phoenix definition, adjusted for benign bounce. Results: As of September 2011, 83 patients have completed treatment with a median follow-up of 42 months (range 12–60 months). Median age was 67y (42 – 82y). 78 patients (92%) were T1a-c; all had Gleason 6 cancers; median PSA was 5.3 (0.8 – 9.9 ng/ml). 82 (99%) had BC; the remaining patient had a negative biopsy and a history of chronic prostatitis. The median PSA on last visit was 0.69 ng/ml (.02 – 2.6 ng/ml). Of 59 patients who have had a biopsy to date, 2 (3%) were positive but both are under BC. The following toxicities were observed: acute grade 3+: 0% GI, 1% GU, 0% fatigue; late grade 3+: 1% GI, 1% GU. Median transformed QOL scores at baseline (0.5 SD) and 36mo follow-up are: urinary – 95% (4.1), 93%; bowel – 96% (4.8), 96%; sexual – 65% (13.7), 51%; and hormonal – 95% (5.3), 95%. Conclusions: This novel technique employing standard linear accelerators to deliver an extreme hypofractionated schedule of radiotherapy is feasible, well tolerated and shows excellent pathologic and biochemical control. A randomized study versus standard fractionation should be performed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".