Definitive radiotherapy for localized follicular lymphoma staged by 18F-FDG PET-CT: a collaborative study by ILROG
Bibliographic record
Abstract
Abstract Radiotherapy (RT) can be curative in patients with localized follicular lymphoma (FL), with historical series showing a 10-year disease-free survival of 40 to 50%. As 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography with computerized tomography (PET-CT) upstages 10 to 60% of patients compared to CT, we sought to evaluate outcomes in patients staged by PET-CT, to determine if more accurate staging leads to better patient selection and results. We conducted a multicenter retrospective study under the direction of the International Lymphoma Radiation Oncology Group (ILROG). Inclusion criteria were: RT alone for untreated stage I to II FL (grade 1-3A) with dose equivalent ≥24 Gy, staged by PET-CT, age ≥18 years, and follow-up ≥3 months. End points were freedom from progression (FFP), local control, and overall survival (OS). A total of 512 patients treated between 2000 and 2017 at 16 centers were eligible for analysis; median age was 58 years (range, 20-90); 410 patients (80.1%) had stage I disease; median RT dose was 30 Gy (24-52); and median follow-up was 52 months (3.2-174.6). Five-year FFP and OS were 68.9% and 96%. For stage I, FFP was 74.1% vs 49.1% for stage II (P < .0001). Eight patients relapsed in-field (1.6%). Four had marginal recurrences (0.8%) resulting in local control rate of 97.6%. On multivariable analysis, stage II (hazard ratio [HR], 2.11; 95% confidence interval [CI], 1.44-3.10) and BCL2 expression (HR, 1.62; 95% CI, 1.07-2.47) were significantly associated with less favorable FFP. Outcome after RT in PET-CT staged patients appears to be better than in earlier series, particularly in stage I disease, suggesting that the curative potential of RT for truly localized FL has been underestimated.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".