Stereotactic Body Radiation Therapy for Patients with Early-stage Prostate Cancer
Bibliographic record
Abstract
AIM: Stereotactic body radiation therapy (SBRT) is emerging as a new treatment option for early-stage prostate cancer, theoretically providing clinical and economic benefits compared to conventionally fractionated external-beam radiation therapy (CF-EBRT). This review aimed to evaluate available published data to determine if the proposed theoretical benefits translate clinically. MATERIALS AND METHODS: A systematic search strategy was employed across three databases using predefined search terms, inclusion and exclusion criteria to identify relevant articles. RESULTS: Sixteen articles were included. Biochemical progression-free survival rates of 77.1-100% were reported in SBRT studies compared to 55-98% in CF-EBRT studies. Incidence of acute grade 1, 2, and 3 genitourinary toxicities were reported in the range of 13.3-71%, 12-25% and 0-3%, respectively, in the SBRT cohort in comparison to 28.7-51.9%, 15.6-41.4%. and 1.1-8.1%, respectively, in the CF-EBRT cohort. Incidence of acute grade 1, 2, and 3 gastrointestinal toxicities were reported in the range of 13-67%, 1-27% and 0-9%, respectively, of the SBRT cohort compared to 16.1- 51.1%, 6.3-20.7% and 0-3%, respectively, of the CF-EBRT cohort. Mean treatment costs estimates associated with SBRT ranged from $22,152 to $24,873 and $33,068 to $35,431 for CF-EBRT. CONCLUSION: Available data support the hypothesis of lower rates of acute toxicity and reduced economic burden associated with SBRT compared to CF-EBRT, however, randomised data with longer follow-up are needed to determine whether SBRT is clinically more effective than CF-EBRT.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".