Population-Based Analysis of Incidence and Outcome of Transformed Non-Hodgkin's Lymphoma
Bibliographic record
Abstract
PURPOSE: To assess the incidence and predictive factors for development of transformed lymphoma in a population-based series of patients with follicular lymphoma (FL). PATIENTS AND METHODS: The Lymphoid Cancer Database was used to identify patients with FL diagnosed and treated in the province of British Columbia, Canada. Transformed lymphoma was defined as the development of aggressive non-Hodgkin's lymphoma (NHL) in patients with FL. Factors present at the time of initial diagnosis of indolent NHL and at transformation were analyzed for their impact on risk of transformation and subsequent outcome. RESULTS: Between 1986 and 2001, 600 patients with newly diagnosed FL met the inclusion criteria. With a median follow-up of 109 months (range, 10 to 244), 170 (28%) developed transformation, 107 (63%) based on biopsy confirmation. The annual risk of transformation was 3% continuously through 15 years. A multivariate analysis of clinical factors at diagnosis identified advanced stage as the only predictor of future transformation. The median post-transformation survival was 1.7 years. The 5-year survival was superior for patients with limited extent transformation compared with those with advanced cases (66% v 19%, P < .0001). Patients with transformation based on clinical versus histological criteria had an identical median survival of 1.8 years (P = .2). CONCLUSION: The annual risk of transformation of FL is 3% continuing without plateau beyond 15 years. Advanced stage at diagnosis is predictive of future transformation. Clinically diagnosed transformation has an equal impact on outcome as biopsy proven transformation.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".