J M Zaucha1,2,3, B Malkowski4,5, S Chauvie6, E Subocz7, J Tajer8, W Kulikowski9,10, A Fijolek-Warszewska11, A Biggi12, F Fallanca13, M Kobylecka14, M Dziuk15, D Woszczyk16, J Rybka17, R Kroll-Balcerzak18, F Bergesio6, A Romanowicz19, A Chamier-Cieminska20, P Kurczab21, A Giza22, K Lesniewski-Kmak1,2,3, R Zaucha23, D Swietlik24, T Wróbel17, W Knopinska-Posluszny9,10, J Walewski8, A Gallamini25. 1. Gdynia Oncology Center, Gdynia. 2. Departments of Oncological Propedeutics. 3. Hematology and Transplantology, Medical University of Gdańsk, Gdańsk. 4. Nuclear Medicine Department, Oncology Center, Bydgoszcz. 5. Positron Emission Tomography and Molecular Imagining Department, Collegium Medicum N. Copernicus University, Bydgoszcz, Poland. 6. Medical Physics Department, Santa Croce e Carle Hospital, Cuneo, Italy. 7. Department of Hematology, Military Institute of Medicine, Warszawa. 8. Department of Lymphoproliferative Diseases, Maria Sklodowska-Curie Memorial Institute, Warszawa. 9. Clinical Department of Hematology, Interior Ministry Hospital, Warmia. 10. Mazury Medical University, Olsztyn. 11. Affidea Mazovian PET/CT Center, Warszawa, Poland. 12. Nuclear Medicine Department, Santa Croce e Carle Hospital, Cuneo. 13. Nuclear Medicine Department, San Raffaele Hospital, Milano, Italy. 14. Nuclear Medicine Department, Warsaw Medical University, Warszawa. 15. Nuclear Medicine Department, Military Institute of Medicine, Warszawa. 16. Hematology Unit, Regional Hospital, Opole. 17. Department of Hematology, Blood Neoplasms and Bone Marrow Transplantation, Wroclaw Medical University, Wroclaw. 18. Department of Hematology, University Medical School, Poznan. 19. Department of Hematology, Central Clinical Hospital MSW, Warszawa. 20. Department of Clinical Oncology, Oncology Center, Bydgoszcz. 21. Poradnia Onkologiczna z Oddzialem Chemioterapii Dziennej NZOZ Mrukmed, Rzeszów. 22. Department of Hematology, Jagiellonian University Medical College, Krakow. 23. Department of Clinical Oncology and Radiotherapy. 24. Intrafaculty College of Medical Informatics & Biostatistics, Medical University of Gdansk, Poland. 25. Department of Research, Innovation and Statistics, A. Lacassagne Cancer Center, Nice, France.
Abstract
BACKGROUND: Interim PET after two ABVD cycles (iPET2) predicts treatment outcome in classical Hodgkin's lymphoma. To test whether an earlier assessment of chemosensitivity would improve the prediction accuracy, we launched a prospective, multicenter observational study aimed at assessing the predictive value of iPET after one ABVD (iPET1) and the kinetics of response assessed by sequential PET scanning. PATIENTS AND METHODS: Consecutive patients with newly diagnosed classical Hodgkin's lymphoma underwent interim PET scan after one ABVD course (iPET1). PETs were interpreted according to the Deauville score (DS) as negative (-) (DS 1-3) and positive (+) (DS 4, 5). Patients with iPET1 DS 3-5 underwent iPET2. RESULTS: About 106 early (I-IIA) and 204 advanced (IIB-IV) patients were enrolled between January 2008 and October 2014. iPET1 was (-) in 87/106 (82%) or (+) in 19/106 (18%) of early, and (-) in 133/204 (65%) or (+) in 71/204 (35%) of advanced stage patients, respectively. Twenty-four patients were excluded from response analysis due to treatment escalation. After a median follow-up of 38.2 (3.2-90.2) months, 9/102 (9%) early and 43/184 (23%) advanced patients experienced a progression-free survival event. At 36 months, negative and positive predictive value for iPET1 were 94% and 41% (early) and 84% and 43% (advanced), respectively. The kinetics of PET response was assessed in 198 patients with both iPETs. All 116 patients with iPET1(-) remained iPET2(-) (fast responders), 41/82 with IPET1(+) became iPET2(-) (slow responders), and the remaining 41 stayed iPET2(+) (non-responders); progression-free survival at 36 months for fast, slow and non-responders was 0.88, 0.79 and 0.34, respectively. CONCLUSION: The optimal tool to predict ABVD outcome in HL remains iPET2 because it distinguishes responders, whatever their time to response, from non-responders. However, iPET1 identified fast responders with the best outcome and might guide early treatment de-escalation in both early and advanced-stage HL.
BACKGROUND: Interim PET after two ABVD cycles (iPET2) predicts treatment outcome in classical Hodgkin's lymphoma. To test whether an earlier assessment of chemosensitivity would improve the prediction accuracy, we launched a prospective, multicenter observational study aimed at assessing the predictive value of iPET after one ABVD (iPET1) and the kinetics of response assessed by sequential PET scanning. PATIENTS AND METHODS: Consecutive patients with newly diagnosed classical Hodgkin's lymphoma underwent interim PET scan after one ABVD course (iPET1). PETs were interpreted according to the Deauville score (DS) as negative (-) (DS 1-3) and positive (+) (DS 4, 5). Patients with iPET1 DS 3-5 underwent iPET2. RESULTS: About 106 early (I-IIA) and 204 advanced (IIB-IV) patients were enrolled between January 2008 and October 2014. iPET1 was (-) in 87/106 (82%) or (+) in 19/106 (18%) of early, and (-) in 133/204 (65%) or (+) in 71/204 (35%) of advanced stage patients, respectively. Twenty-four patients were excluded from response analysis due to treatment escalation. After a median follow-up of 38.2 (3.2-90.2) months, 9/102 (9%) early and 43/184 (23%) advanced patients experienced a progression-free survival event. At 36 months, negative and positive predictive value for iPET1 were 94% and 41% (early) and 84% and 43% (advanced), respectively. The kinetics of PET response was assessed in 198 patients with both iPETs. All 116 patients with iPET1(-) remained iPET2(-) (fast responders), 41/82 with IPET1(+) became iPET2(-) (slow responders), and the remaining 41 stayed iPET2(+) (non-responders); progression-free survival at 36 months for fast, slow and non-responders was 0.88, 0.79 and 0.34, respectively. CONCLUSION: The optimal tool to predict ABVD outcome in HL remains iPET2 because it distinguishes responders, whatever their time to response, from non-responders. However, iPET1 identified fast responders with the best outcome and might guide early treatment de-escalation in both early and advanced-stage HL.
Authors: David J Straus; Sin-Ho Jung; Brandelyn Pitcher; Lale Kostakoglu; John C Grecula; Eric D Hsi; Heiko Schöder; Leslie L Popplewell; Julie E Chang; Craig H Moskowitz; Nina Wagner-Johnston; John P Leonard; Jonathan W Friedberg; Brad S Kahl; Bruce D Cheson; Nancy L Bartlett Journal: Blood Date: 2018-07-26 Impact factor: 22.113
Authors: Marius E Mayerhoefer; Markus Raderer; Ulrich Jaeger; Philipp Staber; Barbara Kiesewetter; Daniela Senn; Ferdia A Gallagher; Kevin Brindle; Edit Porpaczy; Michael Weber; Dominik Berzaczy; Ingrid Simonitsch-Klupp; Christian Sillaber; Cathrin Skrabs; Alexander Haug Journal: Eur J Nucl Med Mol Imaging Date: 2018-02-26 Impact factor: 9.236
Authors: Christian Philipp Reinert; Larissa Wanek; Hans Bösmüller; Birgit Federmann; Jan Fritz; Martin Sökler; Marius Horger Journal: Medicine (Baltimore) Date: 2020-02 Impact factor: 1.817