The conditional survival analysis of relapsed DLBCL after autologous transplant: a subgroup analysis of LY.12 and CORAL
Bibliographic record
Abstract
The conditional survival of patients after frontline therapy for diffuse large B-cell lymphoma (DLBCL) approaches that of the general population once patients have survived disease free for 2 years. We sought to determine the conditional survival of patients among patients with relapsed de novo DLBCL successfully undergoing an autologous stem-cell transplant (ASCT) after first relapse. A total of 478 patients with de novo DLBCL, relapsed after 1 treatment from the Collaborative Trial in Relapsed Aggressive Lymphoma (CORAL) and LY.12, were included. Patients were followed prospectively after ASCT for a median of 5.3 and 8.2 years, respectively. Individual patient data were analyzed for event-free survival (EFS) and overall survival. Standardized mortality ratios (SMRs) were estimated using French and Canadian life tables. The EFS estimates declined with each year of follow-up after ASCT and were 50.1% (95% confidence interval [CI]: 43.7% to 56.3%) and 43.4% (95% CI: 36.7% to 49.9%) at 5 years in CORAL and LY.12, respectively. The rate of death stabilized once patients achieved at least 4 years of EFS. Compared with the age- and sex-matched population, the SMR was significantly higher until 5 years after ASCT, when values were no longer statistically significant. Patients undergoing ASCT for relapsed DLBCL continue to have a higher rate of death at least until they have survived event free for 5 years. These observations can help to determine endpoints for future clinical trials in this population and for patient counseling. This trial was registered at www.clinicaltrials.gov as #NCT00078949.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".