Clinical Outcomes and Safety of Ultra-Low-Dose Radiotherapy for Ocular Adnexal Lymphoma: A Systematic Review.
Bibliographic record
Abstract
Background/Objectives: Ultra-low-dose radiotherapy (ULD-RT), an ultra-low-dose regimen delivering 4 Gy in two fractions, has emerged as a promising treatment for indolent ocular adnexal lymphoma (OAL), offering disease control with minimal toxicity. However, the clinical outcomes and safety profile of ULD-RT remain inconsistently reported across studies. Methods: We conducted a systematic review of peer-reviewed studies evaluating ULD-RT in patients with OAL, including prospective, retrospective, and comparative cohorts published between 2000 and 2025. A comprehensive search was performed in PubMed, Embase, and Scopus. Eligible studies reported clinical outcomes (e.g., response rates, local control, progression-free survival) and safety data (acute and late toxicities). Methodological quality was assessed using the Newcastle-Ottawa Scale (NOS). Results: Ten studies comprising 591 patients met the inclusion criteria. The overall response rate to ULD-RT ranged from 88% to 100%, with complete response rates of 50% to 95%. Local control rates ranged from 63% to 100%, and 2-year progression-free survival exceeded 85% in most studies. Importantly, no grade ≥ 3 toxicities were observed following the regimen of 4 Gy in two fractions. Acute toxicities occurred in up to 42% of patients, typically grade 1 dry eye or conjunctivitis. Late toxicities were uncommon (16-33%), with cataracts rarely requiring surgery. All included studies were rated as good quality (NOS score ≥ 7), indicating low risk of bias. Conclusions: ULD-RT is a highly effective and safe treatment modality for OAL, providing excellent local control with a favorable toxicity profile. These findings support the adoption of ULD-RT as a first-line radiotherapy strategy for indolent OAL. Future prospective trials with longer follow-up and standardized toxicity reporting are warranted to confirm and refine its clinical role.
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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 | 0.007 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".