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Allogeneic Stem Cell Transplantation Can Overcome the Adverse Prognostic Impact of TP53 Mutation In Chronic Lymphocytic Leukemia (CLL): Results From the GCLLSG CLL3x Trial

2010· article· en· W2588865636 on OpenAlexaff
Thorsten Zenz, Peter Dreger, Sascha Dietrich, Sebastian Böttcher, Matthias Ritgen, Dirk Winkler, Andreas Bühler, Donald Bunjes, Dietrich W. Beelen, Sandra Cohen, Ute Hegenbart, Matthias Zeis, Michael Hallek, Michael Kneba, Norbert Schmitz, Hartmut Döhner, Stephan Stilgenbauer

Bibliographic record

VenueBlood · 2010
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsUniversité de MontréalHôpital Maisonneuve-Rosemont
Fundersnot available
KeywordsFludarabineTransplantationMedicineInternal medicineChronic lymphocytic leukemiaOncologyHematopoietic stem cell transplantationLeukemiaGastroenterologyImmunologyChemotherapyCyclophosphamide

Abstract

fetched live from OpenAlex

Abstract Abstract 2357 There is ample evidence that poor-risk CLL, as defined by fludarabine refractoriness or the presence of deletion 17p-, can be successfully treated by allogeneic stem cell transplantation (alloSCT). It is unknown, however, whether alloSCT can also overcome the treatment resistance associated with TP53 mutations seen under conventional fludarabine combination therapy. Therefore we have assessed the impact of TP53 mutations on the outcome of alloSCT with the patient cohort enrolled on the CLL3X trial of the German CLL Study Group. Patients and Methods: The CLL3X trial included 90 patients with poor-risk CLL who were allografted with unmanipulated blood stem cells from related or unrelated donors after nonmyeloablative conditioning. With a median follow-up of 46 months, 4-year event-free (EFS) and overall survival (OS) was 42% and 65%, respectively (Blood July 1, 2010). PFS and OS of 13 patients with deletion 17p- were similar to that of patients without this abnormality. TP53 mutations were identified by denaturating high-performance liquid chromatography (DHLPC) (exons 4–10). In addition, cases with deletion 17p- where no TP53 mutation was detected were also directly sequenced. Results: The TP53 mutational status could be obtained in 72 of 90 patients who had informative DNA samples from the time of study entry available. Of these, 19 (26%) showed TP53 mutations; 7 (10%) with a concurrent deletion 17p-, and 9 (12%) in the absence of deletion 17p-. 17p- status was not available in three TP53-mutated patients (4%). Three additional patients (4%) had 17p- without TP53 mutation. Four-year EFS and OS was 46% and 56% with TP53 mutation vs 38% and 66% without TP53 mutation (Figure). Within the TP53-mutated group, 4-year EFS and OS was 44% and 56% for patients without deletion 17p- vs 38% and 50% for patients with concurrent deletion 17p-. None of these differences were statistically significant. Among the patients who were event-free 12 months post alloSCT and had results of minimal residual disease (MRD) assessment available, the probability of being MRD-negative at this landmark was 71% with TP53 mutations and 63% without (p = 1.0). Finally, multivariate analysis using Cox regression modeling (adjusting for age, deletion 17p-, remission status at alloSCT, and T cell depletion) did not show a significant impact of TP53 mutations on EFS (Hazard ratio (HR) 0.71; 95%CI 0.31–1.61) and OS (HR 1.13; 95%CI 0.41–3.12). Conclusions: AlloSCT can provide long-term EFS in about 40% of patients with poor-risk CLL with TP53 mutation independent from the presence of concurrent deletion 17p-. Disease control appears to be similar in patients with and without TP53 mutation, suggesting that alloSCT can overcome the treatment resistance associated with this abnormality. Disclosures: Stilgenbauer: Amgen: Research Funding; Bayer: Consultancy, Honoraria, Research Funding; Boehringer-Ingelheim: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Genzyme: Consultancy, Honoraria, Research Funding; GSK: Consultancy, Honoraria, Research Funding; Mundipharma: Consultancy, Honoraria, Research Funding; Roche: Consultancy, Honoraria, Research Funding; Sanofi Aventis: Research Funding.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.556
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.018
GPT teacher head0.286
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

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Citations8
Published2010
Admission routes1
Has abstractyes

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