Analyzing Efficacy Outcomes from the Phase 2 Study of Single-Agent Tazemetostat As Third-Line Therapy in Patients with Relapsed or Refractory Follicular Lymphoma to Identify Predictors of Response
Bibliographic record
Abstract
Background: Tazemetostat, a first-in-class, oral, enhancer of zeste homolog 2 (EZH2) inhibitor was recently approved by the US Food and Drug Administration in patients with relapsed/refractory (R/R) follicular lymphoma (FL) after demonstrating single-agent, antitumor activity in patients with wild-type (WT) or mutant (MT) EZH2. Progression of disease within 24 months (POD24), exposure to multiple lines of prior therapy, and refractoriness to rituximab therapy have been shown to adversely affect the prognosis of patients receiving second- or third-line regimens for R/R FL, including chemoimmunotherapy. We performed a post hoc exploratory analysis to better understand how these factors impact the outcomes in patients receiving tazemetostat. Methods: This open-label, multicenter study (NCT01897571) evaluated tazemetostat 800 mg administered orally twice daily in patients with MT or WT EZH2 R/R FL. The primary endpoint was objective response rate (ORR; complete response + partial response) as assessed by an independent review committee (IRC); secondary efficacy endpoints included duration of response (DOR) by IRC, progression-free survival (PFS) by IRC, and overall survival (OS) by investigator assessment. Predictive modeling using baseline demographic and disease characteristic variables combined from patients with MT or WT EZH2 R/R FL was performed to identify variables predictive of response (ORR, DOR, PFS, and OS). Models were fitted for variables that were categorical and had no missing observations; they also were fitted with/without Groupe d'Etude des Lymphomes Folliculaires (GELF) criteria and with the number of prior lines of therapy (1, 2, or >2, and 1 or 2 vs >2). Due to incomplete data collection, GELF criteria were analyzed with missing observations (n=28) set to "no." Stepwise logistic and Cox regression was used to determine possible predictors; inclusion at a specified step was based on P≤0.40. Final model inclusion was based on P≤0.20. A final model was run using the possible predictors identified from the previous stepwise regressions. Contingency tables and Kaplan-Meier plots were used to examine significant variables (P≤0.05). Results: In the phase 2 study, the efficacy outcomes by IRC in combined WT and MT EZH2 populations (N=99) were: ORR, 51% (n=50); median DOR, 11 months (95% CI: 7, 19); and median PFS, 12 months (95% CI: 8, 15). Median OS was not reached (95% CI: 38.2, not estimable). Predictive modeling using 17 baseline variables identified possible predictors of efficacy outcome. For ORR, the number (1 or 2 vs >2) of prior lines of therapy was identified as possibly predictive (Table). Patients with 1 line of prior therapy had an ORR of 66% (n=27) vs 40% (n=23) in patients with 2 prior lines of therapy. Disease refractory to rituximab and number (1, 2, or >2) of prior lines of therapy (Table) were identified as possible predictors for DOR. Disease refractory to rituximab, GELF criteria, disease refractory to any treatment, and sex (Table) were possibly predictive for PFS. However, the percentage of subjects that met GELF criteria may be underestimated due to retrospective collection of qualifying data points; therefore, the translation of GELF criteria as a predictive factor for PFS should be interpreted with caution. Other baseline demographic and disease characteristics, including patient age (≤65 y, >65 y), double refractory disease, ECOG performance status, myelosuppression, POD24, disease refractory to last therapy, prior stem cell transplant, and time since last therapy, were not found to be predictive of response, as measured by ORR, DOR, PFS, and OS. Conclusions: In this post hoc exploratory analysis of patients with R/R FL (WT and MT EZH2 cohorts combined), variables associated with heavily pretreated patients (ie, refractory to rituximab, treatment-refractory disease, and number of prior treatments) were identified as possible predictors of response. However, in these analyses other high-risk disease characteristics, such as POD24, were not predictive, although the results may be confounded by the small number of patients in some of the groups. In addition to reinforcing the efficacy of tazemetostat in heavily pretreated patients, these data also suggest that ORR is greater in patient populations who receive treatment as an earlier line of therapy. Prospective confirmatory studies are warranted to confirm these post hoc observations. Disclosures Salles: Kite: Consultancy, Honoraria, Other; Gilead: Consultancy, Honoraria, Other: Participation in educational events; Bristol Myers Squibb: Consultancy, Other; F. Hoffman-La Roche Ltd: Consultancy, Honoraria, Other; Takeda: Consultancy, Honoraria, Other; Janssen: Consultancy, Honoraria, Other: Participation in educational events; Amgen: Honoraria, Other: Participation in educational events; Celgene: Consultancy, Honoraria, Other: Participation in educational events; Autolus: Consultancy; Abbvie: Consultancy, Honoraria, Other: Participation in educational events; Genmab: Consultancy; Epizyme: Consultancy; Debiopharm: Consultancy; MorphoSys: Consultancy, Honoraria, Other; Karyopharm: Consultancy; Novartis: Consultancy, Honoraria, Other. Tilly:BMS: Honoraria. McKay:Greater Glasgow and Clyde Health Board: Current Employment; Roche, Gilead, Takeda, Janssen: Other: For lectures etc; TAKEDA: Membership on an entity's Board of Directors or advisory committees, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company), Speakers Bureau; Janssen: Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company), Speakers Bureau; BeiGene: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees. Phillips:Beigene: Consultancy; Karyopharm: Consultancy; AstraZeneca: Consultancy; Incyte: Consultancy, Other: travel expenses; Seattle Genetics: Consultancy; BMS: Consultancy; Bayer: Consultancy, Research Funding; Abbvie: Consultancy, Research Funding; Pharmacyclics: Consultancy; Cardinal Health: Consultancy. Assouline:Pfizer: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Speakers Bureau; BeiGene: Consultancy, Honoraria, Research Funding; F. Hoffmann-La Roche Ltd: Consultancy, Honoraria, Research Funding; Takeda: Research Funding; AbbVie: Consultancy, Honoraria, Speakers Bureau; AstraZeneca: Consultancy, Honoraria, Speakers Bureau. Batlevi:Janssen, Novartis, Epizyme, Xynomics, Bayer, Autolus, Roche/Genentech: Research Funding; Life Sci, GLG, Juno/Celgene, Seattle Genetics, Kite: Consultancy. Campbell:Amgen, Novartis, Roche, Janssen, Celgene (BMS): Research Funding; AstraZeneca, Janssen, Roche, Amgen, CSL Behring, Novartis: Consultancy. Ribrag:BAY1000394 studies on MCL: Patents & Royalties; Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees; Epizyme: Consultancy, Current equity holder in publicly-traded company, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; argenX: Current equity holder in publicly-traded company, Research Funding; Institut Gustave Roussy: Current Employment; Immune Design: Consultancy, Membership on an entity's Board of Directors or advisory committees; F. Hoffmann-La Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel Expenses; arGEN-X-BVBA: Research Funding; Nanostring: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Honoraria, Membership on an entity's Board of Directors or advisory committees; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche/Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees; Incyte: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Eisai: Honoraria; Servier: Consultancy, Honoraria; Pharmamar: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; AZD: Honoraria, Other; MSD: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel Expenses; Infinity: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Damaj:Roche, Takeda, Accord: Honoraria; Roche, Takeda, Iqone, Accord: Consultancy; Abbevie, Pfizer, Takeda, Roche: Other: Travel. Dickinson:Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau; Gilead: Consultancy, Honoraria, Research Funding, Speakers Bureau; Merck Sharp & Dohme: Consultancy; Novartis: Consultancy, Honoraria, Research Funding, Speakers Bureau. Jurczak:BeiGene: Consultancy, Research Funding; Celgene: Research Funding; Epizyme: Consultancy; Gilead Sciences: Research Funding; MorphoSys: Research Funding; Nordic Nanovector: Research Funding; Servier: Research Funding; Maria Sklodowska-Curie National Research Institute of Oncology, Krakow, Poland: Current Employment; Jagiellonian University, Krakow, Poland: Ended employment in the past 24 months; Sandoz-Novartis: Consultancy; European Medicines Agency,: Consultancy; AstraZeneca: Consultancy; Takeda: Research Funding; Roche: Research Funding; Pharmacyclics: Research Funding; Merck: Research Funding; Afimed: Res
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".