Anna Sureda1, Joseph M. Connors2, Anas Younes3, Andrea Gallamini4, Stephen M. Ansell5, Won S. Kim6, Fiona Miall7, Ashish Bajel8, Wanda Knopinska-Posłuszny9, Carol Anne Ogden10, Shingo Kuroda11, Rachael Liu11, William L. Trepicchio11, John Radford12
1Hematology Department and Hematopoietic Stem Cell Transplant Programme, Institut Català d‘Oncologia - Hospital Duran i Reynals, Barcelona, Spain,2British Columbia Cancer Agency Centre for Lymphoid Cancer, Vancouver, BC, Canada,3Memorial Sloan Kettering Cancer Center, New York, NY, USA,4Research, Innovation and Statistics Department, A Lacassagne Cancer Centre, Nice, France,5Mayo Clinic, Rochester, MN, USA,6Samsung Medical Center, Seoul, South Korea,7Department of Haematology, University Hospitals of Leicester NHS Trust, Leicester, UK,8Department of Clinical Haematology and Bone Marrow Transplantation, Royal Melbourne Hospital, Victoria, Australia,9Independent Public Health Care of the Ministry of the Internal Affairs with the Oncology Centre, Olsztyn, Poland,10Seattle Genetics, Inc., Bothell, WA, USA,11Millennium Pharmaceuticals Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited, Cambridge, MA, USA,12University of Manchester and the Christie NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
Background: Serum levels of soluble(s) CD30 and thymus and activation related chemokine (TARC) are established prognostic biomarkers in cHL. sCD30 and TARC levels are also associated with disease burden, suggesting utility as biomarkers for treatment response. This exploratory ad-hoc biomarker analysis evaluated changes in sCD30 and TARC levels over time, and association with end-of-treatment (EOT) response, PET status after cycle 2 (PET2), and EOT PET status, in the phase 3 ECHELON-1 study of frontline brentuximab vedotin + doxorubicin, vinblastine, and dacarbazine (A+AVD) vs doxorubicin, bleomycin, vinblastine, and dacarbazine (ABVD) in pts with advanced cHL.
Methods: 1334 pts were randomized 1:1 to A+AVD or ABVD (up to six 28-day cycles). The primary endpoint was modified progression-free survival per independent review facility (IRF); response per IRF was a secondary endpoint. Serum sCD30 and TARC levels were analyzed at baseline and each cycle using validated assays.
Results: Overall response rate at EOT was 86% vs 83% with A+AVD vs ABVD, including 73% vs 71% CR. After cycle 2, 89% vs 86% of pts were PET2-negative (Deauville score ≤3). At EOT, 85% vs 80% of pts had PET-negative disease (Deauville score ≤2); 86% vs 82% had a Deauville score ≤3. Mean sCD30 and TARC levels decreased from baseline in both arms; the sCD30 decrease was greater with ABVD; TARC decreases were similar in both arms. There were no clear trends in sCD30 (Figure 1A, B) or TARC (C, D) decrease by response in either arm. Mean sCD30 decrease from baseline to EOT was greater in PET2-negative vs PET2-positive pts with A+AVD (mean –20.93 vs 312.40 ng/mL) but smaller with ABVD (mean –262.84 vs –584.88 ng/mL). Similarly, mean sCD30 decrease was greater in EOT PET-negative vs PET-positive pts with A+AVD (mean –15.86 vs 123.34 ng/mL) but smaller with ABVD (mean –300.13 vs –483.44 ng/mL). Mean TARC decrease from baseline to EOT was slightly greater in PET2-negative vs PET2-positive pts with A+AVD (mean –47,747 vs –37,954 pg/mL); there was no difference with ABVD. Mean TARC decrease was slightly greater in EOT PET-negative vs PET-positive pts with A+AVD (mean –47,820 vs –40,754 pg/mL); with ABVD the decrease was slightly smaller (mean –39,082 vs –40,859 pg/mL).
Conclusions: There were no obvious differences or trends in sCD30 or TARC changes from baseline according to response, PET2 status, or EOT PET status. Based on these findings, sCD30 and TARC are not adequate biomarkers for response.