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

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.