Alfonso Quintás-Cardama1, Sangbum Choi2, Hagop Kantarjian3, Elias Jabbour3, Xuelin Huang2, Jorge Cortes3. 1. Department of Leukemia, M.D. Anderson Cancer Center, Houston, TX. Electronic address: aquintas@mdanderson.org. 2. Department of Biostatistics, M.D. Anderson Cancer Center, Houston, TX. 3. Department of Leukemia, M.D. Anderson Cancer Center, Houston, TX.
Abstract
BACKGROUND: Current recommendations for monitoring patients with chronic myeloid leukemia (CML) provide recommendations for response assessment and treatment only at 3, 6, 12, and 18 months. These recommendations are based on clinical trial outcomes computed from treatment start. Conditional survival estimates take into account the changing hazard rates as time from treatment elapses as a continuum. PATIENTS AND METHODS: We performed conditional survival analyses among patients with CML to improve prognostication at any time point during the course of therapy. We used 2 cohorts of patients with CML in chronic phase: 1 treated in the frontline DASISION (Dasatinib versus Imatinib Study in Treatment - Naïve CML) phase III study (n = 519) and another treated after imatinib treatment had failed in the dasatinib dose-optimization phase III CA180-034 study (n = 670). Conditional survival estimates were calculated. A modified Cox proportional hazards model was used to build a prognostic nomogram. RESULTS: As the time alive or free from events from commencement of treatment increased, conditional survival estimates changed. No differences were observed regarding future outcomes between patients treated with imatinib or dasatinib in the frontline setting for patients with the same breakpoint cluster region-abelson 1 (BCR-ABL1) transcript levels evaluated at the same time point. Age older than 60 years greatly affected future outcomes particularly in the short-term. Conditional survival-based nomograms allowed the prediction of future outcomes at any time point. CONCLUSION: In summary, we designed a calculator to predict future outcomes of patients with CML at any time point during the course of therapy.
BACKGROUND: Current recommendations for monitoring patients with chronic myeloid leukemia (CML) provide recommendations for response assessment and treatment only at 3, 6, 12, and 18 months. These recommendations are based on clinical trial outcomes computed from treatment start. Conditional survival estimates take into account the changing hazard rates as time from treatment elapses as a continuum. PATIENTS AND METHODS: We performed conditional survival analyses among patients with CML to improve prognostication at any time point during the course of therapy. We used 2 cohorts of patients with CML in chronic phase: 1 treated in the frontline DASISION (Dasatinib versus Imatinib Study in Treatment - Naïve CML) phase III study (n = 519) and another treated after imatinib treatment had failed in the dasatinib dose-optimization phase III CA180-034 study (n = 670). Conditional survival estimates were calculated. A modified Cox proportional hazards model was used to build a prognostic nomogram. RESULTS: As the time alive or free from events from commencement of treatment increased, conditional survival estimates changed. No differences were observed regarding future outcomes between patients treated with imatinib or dasatinib in the frontline setting for patients with the same breakpoint cluster region-abelson 1 (BCR-ABL1) transcript levels evaluated at the same time point. Age older than 60 years greatly affected future outcomes particularly in the short-term. Conditional survival-based nomograms allowed the prediction of future outcomes at any time point. CONCLUSION: In summary, we designed a calculator to predict future outcomes of patients with CML at any time point during the course of therapy.
Authors: Timothy P Hughes; Andreas Hochhaus; Susan Branford; Martin C Müller; Jaspal S Kaeda; Letizia Foroni; Brian J Druker; François Guilhot; Richard A Larson; Stephen G O'Brien; Marc S Rudoltz; Manisha Mone; Elisabeth Wehrle; Vijay Modur; John M Goldman; Jerald P Radich Journal: Blood Date: 2010-08-02 Impact factor: 22.113
Authors: Beth A Zamboni; Greg Yothers; Mehee Choi; Clifton D Fuller; James J Dignam; Peter C Raich; Charles R Thomas; Michael J O'Connell; Norman Wolmark; Samuel J Wang Journal: J Clin Oncol Date: 2010-04-20 Impact factor: 44.544
Authors: Brian J Druker; François Guilhot; Stephen G O'Brien; Insa Gathmann; Hagop Kantarjian; Norbert Gattermann; Michael W N Deininger; Richard T Silver; John M Goldman; Richard M Stone; Francisco Cervantes; Andreas Hochhaus; Bayard L Powell; Janice L Gabrilove; Philippe Rousselot; Josy Reiffers; Jan J Cornelissen; Timothy Hughes; Hermine Agis; Thomas Fischer; Gregor Verhoef; John Shepherd; Giuseppe Saglio; Alois Gratwohl; Johan L Nielsen; Jerald P Radich; Bengt Simonsson; Kerry Taylor; Michele Baccarani; Charlene So; Laurie Letvak; Richard A Larson Journal: N Engl J Med Date: 2006-12-07 Impact factor: 91.245
Authors: George J Chang; Chung-Yuan Hu; Cathy Eng; John M Skibber; Miguel A Rodriguez-Bigas Journal: J Clin Oncol Date: 2009-10-05 Impact factor: 44.544
Authors: Michele Baccarani; Jorge Cortes; Fabrizio Pane; Dietger Niederwieser; Giuseppe Saglio; Jane Apperley; Francisco Cervantes; Michael Deininger; Alois Gratwohl; François Guilhot; Andreas Hochhaus; Mary Horowitz; Timothy Hughes; Hagop Kantarjian; Richard Larson; Jerald Radich; Bengt Simonsson; Richard T Silver; John Goldman; Rudiger Hehlmann Journal: J Clin Oncol Date: 2009-11-02 Impact factor: 44.544
Authors: Koji Sasaki; Hagop M Kantarjian; Preetesh Jain; Elias J Jabbour; Farhad Ravandi; Marina Konopleva; Gautam Borthakur; Koichi Takahashi; Naveen Pemmaraju; Naval Daver; Sherry A Pierce; Susan M O'Brien; Jorge E Cortes Journal: Cancer Date: 2015-10-19 Impact factor: 6.860
Authors: Maria Anna Zipeto; Angela C Court; Anil Sadarangani; Nathaniel P Delos Santos; Larisa Balaian; Hye-Jung Chun; Gabriel Pineda; Sheldon R Morris; Cayla N Mason; Ifat Geron; Christian Barrett; Daniel J Goff; Russell Wall; Maurizio Pellecchia; Mark Minden; Kelly A Frazer; Marco A Marra; Leslie A Crews; Qingfei Jiang; Catriona H M Jamieson Journal: Cell Stem Cell Date: 2016-06-09 Impact factor: 24.633