PURPOSE: In the two consecutive German studies III and IIIA on chronic myeloid leukemia, between 1995 and 2004, 781 patients were randomized to receive either allogeneic hematopoietic stem cell transplantation with a related donor or continued drug treatment. Despite comparable transplantation protocols and most centers participating in both studies, the post-transplant survival probabilities for patients transplanted in first chronic phase were significantly higher in study IIIA (144 patients) than in study III (113 patients). Prior to the decision on a combined analysis of both studies, reasons for this discrepancy had to be investigated. METHODS: The Cox proportional hazard cure model was used to identify prognostic factors for post-transplant survival. RESULTS: Donor-recipient matching for human leukocyte antigen, patient age, time between diagnosis and transplantation, and calendar time showed a significant influence on survival and/or the incidence of cure. Added as a further factor, affiliation to study IIIA had no significant impact any longer. CONCLUSIONS: Discrepancies in influential prognostic factors explained the different post-transplant survival probabilities between the studies. The significance of calendar time suggests a lack of consistency of transplantation practice over time. Accordingly, the prerequisite for a common assessment of overall survival in the two randomized transplantation arms was not met. Moreover, our analyses provide an independent validation of established prognostic factors and their cutoffs. The statistical approach in investigating and modeling potential prognostic factors for survival sets an example for the examination of studies with unexpected outcome differences in concurrent treatment arms.
RCT Entities:
PURPOSE: In the two consecutive German studies III and IIIA on chronic myeloid leukemia, between 1995 and 2004, 781 patients were randomized to receive either allogeneic hematopoietic stem cell transplantation with a related donor or continued drug treatment. Despite comparable transplantation protocols and most centers participating in both studies, the post-transplant survival probabilities for patients transplanted in first chronic phase were significantly higher in study IIIA (144 patients) than in study III (113 patients). Prior to the decision on a combined analysis of both studies, reasons for this discrepancy had to be investigated. METHODS: The Cox proportional hazard cure model was used to identify prognostic factors for post-transplant survival. RESULTS:Donor-recipient matching for human leukocyte antigen, patient age, time between diagnosis and transplantation, and calendar time showed a significant influence on survival and/or the incidence of cure. Added as a further factor, affiliation to study IIIA had no significant impact any longer. CONCLUSIONS: Discrepancies in influential prognostic factors explained the different post-transplant survival probabilities between the studies. The significance of calendar time suggests a lack of consistency of transplantation practice over time. Accordingly, the prerequisite for a common assessment of overall survival in the two randomized transplantation arms was not met. Moreover, our analyses provide an independent validation of established prognostic factors and their cutoffs. The statistical approach in investigating and modeling potential prognostic factors for survival sets an example for the examination of studies with unexpected outcome differences in concurrent treatment arms.
Authors: R Hehlmann; A Hochhaus; H J Kolb; J Hasford; A Gratwohl; H Heimpel; W Siegert; J Finke; G Ehninger; E Holler; U Berger; M Pfirrmann; A Muth; A Zander; A A Fauser; A Heyll; C Nerl; D K Hossfeld; H Löffler; H Pralle; W Queisser; A Tobler Journal: Blood Date: 1999-12-01 Impact factor: 22.113
Authors: Susanne Saussele; Michael Lauseker; Alois Gratwohl; Dietrich W Beelen; Donald Bunjes; Rainer Schwerdtfeger; Hans-Jochem Kolb; Anthony D Ho; Christiane Falge; Ernst Holler; Günter Schlimok; Axel R Zander; Renate Arnold; Lothar Kanz; Robert Dengler; Claudia Haferlach; Brigitte Schlegelberger; Markus Pfirrmann; Martin C Müller; Susanne Schnittger; Armin Leitner; Nadine Pletsch; Andreas Hochhaus; Joerg Hasford; Rüdiger Hehlmann Journal: Blood Date: 2009-11-18 Impact factor: 22.113
Authors: A Gratwohl; J Hermans; J M Goldman; W Arcese; E Carreras; A Devergie; F Frassoni; G Gahrton; H J Kolb; D Niederwieser; T Ruutu; J P Vernant; T de Witte; J Apperley Journal: Lancet Date: 1998-10-03 Impact factor: 79.321
Authors: R Hehlmann; H Heimpel; J Hasford; H J Kolb; H Pralle; D K Hossfeld; W Queisser; H Löffler; A Hochhaus; B Heinze Journal: Blood Date: 1994-12-15 Impact factor: 22.113
Authors: Michele Baccarani; Michael W Deininger; Gianantonio Rosti; Andreas Hochhaus; Simona Soverini; Jane F Apperley; Francisco Cervantes; Richard E Clark; Jorge E Cortes; François Guilhot; Henrik Hjorth-Hansen; Timothy P Hughes; Hagop M Kantarjian; Dong-Wook Kim; Richard A Larson; Jeffrey H Lipton; François-Xavier Mahon; Giovanni Martinelli; Jiri Mayer; Martin C Müller; Dietger Niederwieser; Fabrizio Pane; Jerald P Radich; Philippe Rousselot; Giuseppe Saglio; Susanne Saußele; Charles Schiffer; Richard Silver; Bengt Simonsson; Juan-Luis Steegmann; John M Goldman; Rüdiger Hehlmann Journal: Blood Date: 2013-06-26 Impact factor: 22.113
Authors: A Gratwohl; M Pfirrmann; A Zander; N Kröger; D Beelen; J Novotny; C Nerl; C Scheid; K Spiekermann; J Mayer; H G Sayer; C Falge; D Bunjes; H Döhner; A Ganser; I Schmidt-Wolf; R Schwerdtfeger; H Baurmann; R Kuse; N Schmitz; A Wehmeier; J Th Fischer; A D Ho; M Wilhelm; M-E Goebeler; H W Lindemann; M Bormann; B Hertenstein; G Schlimok; G M Baerlocher; C Aul; M Pfreundschuh; M Fabian; P Staib; M Edinger; M Schatz; A Fauser; R Arnold; T Kindler; G Wulf; A Rosselet; A Hellmann; E Schäfer; O Prümmer; M Schenk; J Hasford; H Heimpel; D K Hossfeld; H-J Kolb; G Büsche; C Haferlach; S Schnittger; M C Müller; A Reiter; U Berger; S Saußele; A Hochhaus; R Hehlmann Journal: Leukemia Date: 2015-10-14 Impact factor: 11.528