Carbon-Ion Radiotherapy for Prostate Cancer in Patients with a History of Surgery for Benign Prostatic Hyperplasia
Bibliographic record
Abstract
Background/Objectives: Carbon-ion radiotherapy (CIRT) offers precise dose distribution and enhanced biological effectiveness in localized prostate cancer. However, the safety of CIRT in patients with a history of surgery for benign prostatic hyperplasia (BPH), such as transurethral resection of the prostate (TURP), remains unclear. This study aimed to evaluate the long-term safety and oncological outcomes of CIRT in this population. Methods: A retrospective analysis was conducted in 74 of 3848 patients with prostate cancer and a history of surgery for BPH who underwent CIRT combined with risk-adapted androgen deprivation therapy between 2007 and 2023. Adverse events were assessed using CTCAE v5.0. Biochemical recurrence-free survival was estimated using the Kaplan–Meier method and risk factors for hematuria with multivariate logistic regression and receiver operation characteristic (ROC) analysis. Results: CIRT was generally well-tolerated. Early Grade 2 genitourinary (GU) adverse events occurred in 5.4% of patients, and late-Grade 2 or higher GU events occurred in 8.1%. The cumulative incidence of Grade 2 ≥ GU events remained 10% at 36 months. Compared to holmium laser enucleation of the prostate, a shorter interval between BPH surgery and CIRT initiation and a history of TURP were independently associated with an increased risk of hematuria. Notably, 5-year bRFS was 100% in low- and intermediate-risk groups and 88.6% in the high-risk group. Conclusions: CIRT demonstrates acceptable oncological outcomes and urinary complication rates in patients with prostate cancer and a history of BPH surgery. These findings suggest that CIRT can be a feasible treatment option in this surgically altered population, but careful patient selection, individualized treatment planning, and long-term follow-up are essential. Given the absence of a non-BPH control group, oncological efficacy should be interpreted with caution.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".