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Abstract CT158: Unmutated IGHV is not an adverse predictor of outcome to therapy with ibrutinib in patients with chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL)

2017· article· en· W2739919424 on OpenAlexaff
Thomas J. Kipps, Graeme Fraser, Steven Coutré, Jennifer R. Brown, Jacqueline C. Barrientos, Paul M. Barr, John C. Byrd, Susan O’Brien, Marie‐Sarah Dilhuydy, Stephen Devereux, Ulrich Jaeger, Carol Moreno, Paula Cramer, Stephan Stilgenbauer, Asher Chanan‐Khan, Michelle Mahler, Mariya Salman, Mei Cheng, Anil Londhe, Joi Ninomoto, Angela Howes, Danelle F. James, Michael Hallek

Bibliographic record

VenueCancer Research · 2017
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsMcMaster UniversityJuravinski Cancer Centre
Fundersnot available
KeywordsIGHV@IbrutinibMedicineChronic lymphocytic leukemiaInternal medicineBendamustineOncologyChlorambucilVenetoclaxRituximabFludarabineLeukemiaGastroenterologyLymphomaChemotherapyCyclophosphamide

Abstract

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Abstract Background: Patients (pts) with CLL/SLL who use unmutated IGHV (u-CLL) have a less favorable outcome with standard chemotherapy than pts who use mutated IGHV (m-CLL). Ibrutinib (ibr) inhibits B-cell receptor signaling through Bruton’s tyrosine kinase and has robust clinical activity against CLL. This integrated analysis of 3 phase 3 studies examined the impact of IGHV status on ibr- and comparator (comp)-treated pts. Methods: Pooled data from 3 studies of ibr (420 mg/d) in CLL/SLL pts (RESONATE: relapsed/refractory [R/R] pts, ibr vs ≤ 24 weeks ofatumumab; RESONATE-2: treatment-naïve [TN] pts ≥ 65 yrs of age [no del17p], ibr vs ≤ 12 cycles chlorambucil; HELIOS: R/R pts [no del17p], ≤ 6 cycles bendamustine-rituximab with ibr vs placebo) were analyzed by IGHV status. Analyses included Kaplan-Meier method (overall survival [OS]; progression-free survival [PFS]); log-rank test (group comparisons); and Cox multivariate analysis (prognostic factors; Table). Results: For 491 ibr- (366 u-CLL, 125 m-CLL) and 494 comp-treated (351 u-CLL, 143 m-CLL) pts with IGHV data, baseline characteristics were similar for u-CLL vs m-CLL, except for the proportions of pts who were TN (17 vs 31%), had bulky disease (60 vs 37%), or had CLL cells with del11q (32 vs 16%). Median follow up was 21.4 mos for ibr and 20.6 mos for comp. PFS and OS were similar for u-CLL and m-CLL ibr-treated pts; u-CLL had poorer outcomes than m-CLL in comp-treated pts, which remained after adjustment for prognostic factors (Table). Ibr treatment was more effective than comp regardless of IGHV status. Incidence of adverse events (AEs) was similar between groups. For ibr vs comp pts (u-CLL/m-CLL): serious AEs: 49% (50%/47%) vs 36.5% (37%/35%); AEs that led to discontinuation: 12% (11%/15%) vs 13% (13%/14%); death within 30 days of last dose: 5% (6%/3%) vs 5% (6%/2%). Conclusions: U-CLL was an adverse predictor of outcome for comp-treated, but not for ibr-treated pts. Table.Efficacy Outcomes in Ibr- and Comparator-Treated Patients by IGHV Mutation StatusIbrutinib (N=491)Comparator (N =494)u-CLL (n=717)m-CLL (n=268)u-CLL(n=366): m-CLL(n=125)u-CLL(n=351): m-CLL(n=143)Ibr(n=366): Comp(n=351)Ibr (n=125): Comp (n=143)PFS24-month rate HR78%:81%10%:32%78%:10%81%:32%0.93a1.99a0.12b0.21bp = 0.78p < 0.0001p < 0.0001p <0.0001Adjusted HRc1.02a1.94a0.11b0.17bp = 0.93p < 0.0001p < 0.0001p < 0.0001OS24-month rate HR88%:89%78%:87%88%:78%89%:87%0.95a1.96a0.49b0.85b,ep = 0.86p = 0.02p < 0.01p = 0.66Adjusted HRc1.21a2.10a0.49bNAp =0.57p = 0.01p < 0.001Response ratesu-CLLm-CLLu-CLLm-CLLIbrCompIbrCompORR, %d8990475189479051p = 0.96p = 0.36p < 0.0001p < 0.0001CR, %d221546224156p = 0.10p = 0.44p < 0.0001p = 0.01CI, confidence interval; CR, complete response; HR, hazard ratio; ORR, overall response rate; NA, not applicable. aHR < 1 favors unmutated. bHR < 1 favors ibrutinib. cMultivariate Cox model adjusted for age, sex, current Rai stage, baseline ECOG performance status score, del11q, del17p, number of prior therapies, and cytopenias. dp value is from a Cochran-Mantel-Haenszel chi-square test. eInsufficient number of events prevents meaningful analysis, only 13 and 16 events observed in ibr and comp groups, respectively, and 46 (32%) pts in comp arm crossed over to ibr arm; interpret results with caution. Citation Format: Thomas J. Kipps, Graeme Fraser, Steven Coutre, Jennifer R. Brown, Jacqueline C. Barrientos, Paul M. Barr, John C. Byrd, Susan M. O'Brien, Marie-Sarah Dilhuydy, Stephen Devereux, Ulrich Jaeger, Carol Moreno, Paula Cramer, Stephan Stilgenbauer, Asher A. Chanan-Khan, Michelle Mahler, Mariya Salman, Mei Cheng, Anil Londhe, Joi Ninomoto, Angela Howes, Danelle James, Michael Hallek. Unmutated IGHV is not an adverse predictor of outcome to therapy with ibrutinib in patients with chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr CT158. doi:10.1158/1538-7445.AM2017-CT158

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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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.086
GPT teacher head0.390
Teacher spread0.304 · 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.

Study designObservational
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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Citations2
Published2017
Admission routes1
Has abstractyes

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