Abstract
Background: Peripheral T-cell lymphomas (PTCLs) comprise a group of non-Hodgkin lymphomas (NHLs) of mature T-cell origin with generally aggressive clinical behavior. Most systemic PTCLs are treated with anthracycline-based combination chemotherapy; however, outcomes remain relatively poor for most subtypes except ALK-positive anaplastic large cell lymphoma (ALCL). We have used landmark analyses based on event-free survival (EFS) to identify clinically useful endpoints in B-cell NHLs, with EFS at 24 (EFS24) months identified to stratify overall survival (OS) in aggressive B-cell NHL. Here we examined the ability of EFS24 to predict subsequent OS in a large, multinational PTCL cohort.
Methods: A cohort of newly diagnosed PTCL patients treated with curative intent combination chemotherapy regimens was assembled from the University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource (MER), Swedish Lymphoma Registry (SWE), and British Columbia Cancer Agency (BCCA). Subtypes included ALK-negative ALCL, angioimmunoblastic T-cell lymphoma (AITL), PTCL, not otherwise specified (NOS), enteropathy-associated T-cell lymphoma (EATL), extranodal NK/T-cell lymphoma, nasal type (ENKTL), and hepatosplenic T-cell lymphoma (HSTCL). Patients were followed based on local institution guidelines, and EFS was defined as time from the date of pathologic diagnosis to progression, re-treatment, or death due to any cause. EFS24 was defined as being alive and event-free 24 months from diagnosis. Subsequent OS was defined as time from achieving EFS24 (24 months from diagnosis) or time from progression in patients failing to achieve EFS24 (progression within 24 months of diagnosis). OS was compared to the age-, sex-, and country-matched general population using United States, Sweden, and British Columbia rate tables via standardized mortality ratios (SMR) and expected survival.
Results: 775 patients diagnosed from 2000-2012 were included in the combined analysis with diagnosis by the WHO classification at the respective institutions (MER=138, SWE=422, BCCA=215). Median age at diagnosis was 64 years (range 18-89) and 63% were male. Patient characteristics are summarized in the table. 736 (95%) received anthracyline-based therapy at diagnosis. At a median follow-up of 77 months (range 1-185), 516 patients (67%) had died. The percentage of patients achieving EFS24 was similar across the 3 cohorts (MER=39%, SWE=35%, BCCA= 36%, combined=36%). Median survival after progression within the first 24 months was only 4.9 months (95% CI: 3.8-5.9), with a 5-year OS of 11% and SMR of 46.4 (95% CI: 41.8-51.3). In contrast, median survival after achieving EFS24 was not reached, with a 5-year OS of 78% (95% CI: 73%-84%). This was inferior to the expected survival of 92% in the age-, sex-, and country matched population (SMR=3.16; 95% CI: 2.48-3.98). In EFS24 subgroup analyses, more favorable outcomes were observed in younger patients (age <=60 years, N=137, 5-year survival of 91% vs. 98% expected) and in patients receiving autologous stem cell transplant in first remission (N=72, 5-year survival of 88% vs. 96% expected). Patients achieving EFS24 who were not transplanted in first remission (N=189) had a 5-year survival of 74% vs. 90% expected.
Conclusions: Assessment of EFS24 stratifies subsequent outcome in PTCL. Patients with early relapse from PTCL have extremely poor outcomes. However, over one-third of patients with PTCL remain in remission two years from diagnosis after initial chemotherapy and have encouraging OS rates, although survival remains significantly worse than the matched general population. Subset analysis suggests that younger patients and patients who receive autologous stem-cell transplant in first CR have 5-year survival rates that approach 90%, though still below the expected survival of the background population. The marked differences in OS after failing or achieving EFS24 in PTCL patients suggest that this endpoint may be useful for patient counseling, as a clinical trial endpoint, and as an endpoint to assess novel biomarkers for risk stratification.
Table Table. Figure 1. Figure 1. Figure 2. Figure 2.
Disclosures
Maurer: Celgene: Research Funding; Kite Pharma: Research Funding. Jerkeman:Mundipharma: Research Funding; Amgen: Research Funding; Janssen: Research Funding; Gilead: Research Funding; Celgene: Research Funding. Connors:Seattle Genetics: Research Funding; Millennium Takeda: Research Funding; NanoString Technologies: Research Funding; F Hoffmann-La Roche: Research Funding; Bristol Myers Squib: Research Funding. Ansell:BMS, Seattle Genetics, Merck, Celldex and Affimed: Research Funding.
Cause of Death in Follicular Lymphoma in the First Decade of the Rituximab Era: A Pooled Analysis of French and US Cohorts
