<i>TP53</i> mutation and survival in aggressive B cell lymphoma
Bibliographic record
Abstract
TP53 is mutated in 20-25% of aggressive B-cell lymphoma (B-NHL). To date, no studies have addressed the impact of TP53 mutations in prospective clinical trial cohorts. To evaluate the impact of TP53 mutation to current risk models in aggressive B-NHL, we investigated TP53 gene mutations within the RICOVER-60 trial. Of 1,222 elderly patients (aged 61-80 years) enrolled in the study and randomized to six or eight cycles of CHOP-14 with or without Rituximab (NCT00052936), 265 patients were analyzed for TP53 mutations. TP53 mutations were demonstrated in 63 of 265 patients (23.8%). TP53 mutation was associated with higher LDH (65% vs. 37%; p < 0.001), higher international prognostic index-Scores (IPI 4/5 27% vs. 12%; p = 0.025) and B-symptoms (41% vs. 24%; p = 0.011). Patients with TP53 mutation were less likely to obtain a complete remission CR/CRu (CR unconfirmed) 61.9% (mut) vs. 79.7% (wt) (p = 0.007). TP53 mutations were associated with decreased event-free (EFS), progression-free (PFS) and overall survival (OS) (median observation time of 40.2 months): the 3 year EFS, PFS and OS were 42% (vs. 60%; p = 0.012), 42% (vs. 67.5%; p < 0.001) and 50% (vs. 76%; p < 0.001) for the TP53 mutation group. In a Cox proportional hazard analysis adjusting for IPI-factors and treatment arms, TP53 mutation was shown to be an independent predictor of EFS (HR 1.5), PFS (HR 2.0) and OS (HR 2.3; p < 0.001). TP53 mutations are independent predictors of survival in untreated patients with aggressive CD20+ lymphoma. TP53 mutations should be considered for risk models in DLBCL and strategies to improve outcome for patients with mutant TP53 must be developed.
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 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".