Patterns of Relapse Following Radiation Therapy of Intermediate-Risk Prostate Cancer in the PROFIT Randomized Trial
Bibliographic record
Abstract
PURPOSE: Conventionally fractionated radiation therapy (CFRT) and hypofractionated RT (HFRT) are established treatments for intermediate-risk (IR) prostate cancer (PCa), with differing dose per fraction. However, their comparative patterns of failure remain unclear. This stuy aims to analyze the distinct relapse patterns of HFRT versus CFRT in terms of local progression-free survival (LPFS), pelvic lymph node metastasis-free survival (pnMFS), extrapelvic lymph node MFS (epnMFS), and bone MFS (bMFS). METHODS AND MATERIALS: Patients with IR PCa included in French and Australian centers in the "PROstate Fractionated Irradiation Trial (PROFIT)" study (NCT00304759), a phase 3, multicenter, randomized controlled trial. Using molecular positron emission tomography imaging, magnetic resonance imaging, and bone scintigraphy, the anatomic sites of relapse were retrospectively identified in biochemically relapsing patients after HFRT or CFRT. LPFS, pnMFS, epnMFS, and bMFS were compared between both treatment arms using Kaplan-Meier analyses. RESULTS AND LIMITATIONS: With a median follow-up of 6.4 years, 274 patients (130 HFRT and 144 CFRT) were included, among whom 35 (24.3%) in the HFRT arm and 28 (19.4%) in the CFRT arm experienced relapse. Median time to relapse varied by site: 4.9 years locally, 3.96 years for pelvic lymph nodes, 2.95 years for extrapelvic lymph nodes, and 3.6 years for bone metastasis. No significant differences were found between HFRT and CFRT arms in LPFS, pnMFS, epnMFS, or bMFS. CONCLUSIONS: Relapse rates after HFRT or CFRT are low, with no discernible variance in anatomical relapse patterns between treatments. Tailored management strategies considering these relapse patterns could optimize care of IR patients, including initial staging and microboosting of dominant lesions.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".