Limited‐stage diffuse large B‐cell lymphoma treated with abbreviated systemic therapy and consolidation radiotherapy
Bibliographic record
Abstract
BACKGROUND: For limited-stage diffuse large B-cell lymphoma (DLBCL), treatment decisions are often influenced by toxicity profiles. One strategy that minimizes chemotherapy-induced toxicities is abbreviated chemotherapy plus consolidation involved-field radiotherapy (IFRT). Involved-node radiotherapy (INRT) is a new concept to DLBCL, aimed to reduce radiotherapy-induced toxicities. We retrospectively review the long-term outcomes of limited-stage DLBCL treated with abbreviated systemic therapy and radiotherapy focusing on field size: IFRT versus INRT. METHODS: The British Columbia Cancer Agency Lymphoid Cancer Database was used to identify patients diagnosed with limited-stage DLBCL (stage I/II, without B-symptoms; bulk < 10 cm) from 1981 to 2007. Patients were prescribed 3 cycles of chemotherapy plus IFRT (1981-1996) or INRT≤5 cm (1996-2007), defined as INRT to the prechemotherapy involved nodes with margins ≤ 5 cm. RESULTS: A total of 288 patients were identified: 56% were aged >60 years, 34% had stage II disease, 55% had extranodal disease, 19% had elevated lactate dehydrogenase levels, and 15% received rituximab. The two radiotherapy groups were IFRT (138 patients; 48%) and INRT≤5cm (150 patients; 52%); median follow-up was 117 and 89 months, respectively. Distant relapse was the most common site of failure in both groups. After INRT≤5 cm, marginal recurrence was infrequent (2%). Time to progression (P = .823), progression-free survival (P = .575), and overall survival (P = .417) were not significantly different between the radiotherapy cohorts. Radiotherapy field size was not a significant prognostic factor on multivariate analyses. CONCLUSIONS: This research is the first known body of work to apply the concept of INRT to limited-stage DLBCL. Reducing the field size from IFRT to INRT≤5 cm maintains a low marginal recurrence risk with no impact on overall outcome.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".