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PREDICTIVE FACTORS OF STABLE DEEP MOLECULAR RESPONSE IN CHRONIC PHASE CML PATIENTS TREATED WITH DASATINIB OR NILOTINIB AFTER IMATINIB FAILURE
Author(s): ,
Massimiliano Bonifacio
Affiliations:
Department of Medicine, Section of Hematology,University of Verona,Verona,Italy
,
Gianni Binotto
Affiliations:
Department of Medicine, Hematology and Clinical Immunology,Padua School of Medicine,Padua,Italy
,
Mario Tiribelli
Affiliations:
Division of Hematology and BMT, Department of Experimental and Clinical Medical Sciences,Azienda Ospedaliero-Universitaria di Udine,Udine,Italy
,
Luigi Scaffidi
Affiliations:
Department of Medicine, Section of Hematology,University of Verona,Verona,Italy
,
Alessandra Iurlo
Affiliations:
Oncohematology Division,IRCCS Ca’ Granda – Maggiore Policlinico Hospital Foundation, and University of Milan,Milan,Italy
,
Francesca Cibien
Affiliations:
Hematology Unit,Ca' Foncello Hospital,Treviso,Italy
,
Elena Maino
Affiliations:
Hematology Unit,Dell'Angelo Hospital,Mestre-Venice,Italy
,
Anna Guella
Affiliations:
Hematology Unit,Santa Chiara Hospital,Trento,Italy
,
Gianluca Festini
Affiliations:
Division of Clinical Hematology,Azienda Ospedaliero Universitaria di Trieste,Trieste,Italy
,
Claudia Minotto
Affiliations:
Department of Medical Specialities, Oncology and Onco-Haematology Unit,ULSS13 Mirano,Mirano-Venice,Italy
,
Ercole De Biasi
Affiliations:
Hematology Unit,P.Cosma Hospital,Camposampiero-Padua,Italy
,
Luca Frison
Affiliations:
Department of Medicine, Hematology and Clinical Immunology,Padua School of Medicine,Padua,Italy
,
Federico De Marchi
Affiliations:
Division of Hematology and BMT, Department of Experimental and Clinical Medical Sciences,Azienda Ospedaliero-Universitaria di Udine,Udine,Italy
,
Marta Medeot
Affiliations:
Division of Hematology and BMT, Department of Experimental and Clinical Medical Sciences,Azienda Ospedaliero-Universitaria di Udine,Udine,Italy
,
Cristina Bucelli
Affiliations:
Oncohematology Division,IRCCS Ca’ Granda – Maggiore Policlinico Hospital Foundation, and University of Milan,Milan,Italy
,
Elisabetta Calistri
Affiliations:
Hematology Unit,Ca' Foncello Hospital,Treviso,Italy
,
Manuela Stulle
Affiliations:
Division of Clinical Hematology,Azienda Ospedaliero Universitaria di Trieste,Trieste,Italy
,
Filippo Gherlinzoni
Affiliations:
Hematology Unit,Ca' Foncello Hospital,Treviso,Italy
,
Agostino Cortelezzi
Affiliations:
Oncohematology Division,IRCCS Ca’ Granda – Maggiore Policlinico Hospital Foundation, and University of Milan,Milan,Italy
,
Renato Fanin
Affiliations:
Division of Hematology and BMT, Department of Experimental and Clinical Medical Sciences,Azienda Ospedaliero-Universitaria di Udine,Udine,Italy
,
Gianpietro Semenzato
Affiliations:
Department of Medicine, Hematology and Clinical Immunology,Padua School of Medicine,Padua,Italy
,
Mauro Krampera
Affiliations:
Department of Medicine, Section of Hematology,University of Verona,Verona,Italy
,
Giovanni Pizzolo
Affiliations:
Department of Medicine, Section of Hematology,University of Verona,Verona,Italy
Achille Ambrosetti
Affiliations:
Department of Medicine, Section of Hematology,University of Verona,Verona,Italy
(Abstract release date: 05/19/16) EHA Library. Bonifacio M. 06/09/16; 134718; PB1818
Dr. Massimiliano Bonifacio
Dr. Massimiliano Bonifacio
Contributions
Abstract
Abstract: PB1818

Type: Publication Only

Background
Front-line treatment of newly diagnosed Chronic Myeloid Leukemia (CML) patients with 2nd generation tyrosine kinase inhibitors (2G-TKIs) dasatinib (DAS) or nilotinib (NIL) resulted in higher rates of deep molecular response (MR) as compared to imatinib. Very little is known about rates and stability of deep MR when 2G-TKIs are used after imatinib failure.

Aims
To assess the probability and predictors of stable deep MR in ≥2nd line of treatment.

Methods
We restrospectively analyzed 127 chronic phase CML patients treated with imatinib 400 mg daily as first-line therapy and then switched to 2G-TKIs for resistance or intolerance. Patients progressing to advanced phases before switch were excluded. Deep molecular response (MR4) was defined as BCL-ABRIS ratio ≤0.01% or undetectable disease with ≥10,000 ABL copies. Patients with MR4 lasting ≥ 2 years, ongoing at the last contact, and with at least a Q-PCR test every 6 months were defined as stable MR4. Patients with any sample >0.01% BCR-ABLIS after the achievement of MR4 were defined as unstable MR4. Age, sex, Sokal and EUTOS risk score, type of BCR-ABL transcript, duration of imatinib, reason for switch to 2G-TKIs and early molecular response to 2G-TKIs have been examined for the association with stable MR4. Frequencies were compared by Fisher’s exact test. Univariate and multivariate regression analysis were performed using the competing risk model of Fine and Gray.

Results
Median age at diagnosis was 55 years (range 20-88) and median duration of imatinib treatment was 19 months (range 1-115). Patients resistant (n=89; 70%) or intolerant (n=38; 30%) to imatinib were switched to DAS (n=82; 64.5%) or NIL (n=45; 35.5%). Thirty-six patients were resistant or intolerant to their first 2G-TKI and were switched to 3rd-line NIL (n=20), DAS (n=12), bosutinib (n=2), or ponatinib (n=2). At a median follow-up of 52 months after switch to 2G-TKI (range 6-126), best deep MR to 2G-TKI was: no MR4 in 57 patients (45%), unstable MR4 in 28 patients (22%; 24 with 2nd line and 4 with 3rd line treatment), and stable MR4 in 42 patients (33%; 37 with 2nd line and 5 with 3rd line treatment). Five-year cumulative incidence of stable MR4 was 28.7% (95%CI: 18.9-37.3%). Age, sex, risk scores at diagnosis, type of BCR-ABL transcript, duration of imatinib and type of 2G-TKI were similar between patients with or without stable MR4 (Table I). Predictors of stable MR4 were reason for switch to 2G-TKI (intolerance vs resistance HR 0.41, 95%CI: 0.22-0.79; p=0.007) and 3-month BCR-ABL level after 2G-TKI start (≤10%IS vs >10%IS HR 0.08, 95%CI: 0.01-0.59; p=0.01). Three stable MR4 patients attempted discontinuation and are presently in treatment-free remission phase at 2, 22 and 27 months after 2G-TKI stop, respectively.

Conclusion
In this retrospective, real-life experience, long-term use of 2G-TKIs in ≥2nd line of treatment after imatinib failure resulted in more than half of patients achieving the “safe haven” of deep MR, with around 60% of them in stable MR4, a prerequisite for discontinuing treatment.



Session topic: E-poster

Keyword(s): Molecular response, Prediction, Tyrosine kinase inhibitor
Abstract: PB1818

Type: Publication Only

Background
Front-line treatment of newly diagnosed Chronic Myeloid Leukemia (CML) patients with 2nd generation tyrosine kinase inhibitors (2G-TKIs) dasatinib (DAS) or nilotinib (NIL) resulted in higher rates of deep molecular response (MR) as compared to imatinib. Very little is known about rates and stability of deep MR when 2G-TKIs are used after imatinib failure.

Aims
To assess the probability and predictors of stable deep MR in ≥2nd line of treatment.

Methods
We restrospectively analyzed 127 chronic phase CML patients treated with imatinib 400 mg daily as first-line therapy and then switched to 2G-TKIs for resistance or intolerance. Patients progressing to advanced phases before switch were excluded. Deep molecular response (MR4) was defined as BCL-ABRIS ratio ≤0.01% or undetectable disease with ≥10,000 ABL copies. Patients with MR4 lasting ≥ 2 years, ongoing at the last contact, and with at least a Q-PCR test every 6 months were defined as stable MR4. Patients with any sample >0.01% BCR-ABLIS after the achievement of MR4 were defined as unstable MR4. Age, sex, Sokal and EUTOS risk score, type of BCR-ABL transcript, duration of imatinib, reason for switch to 2G-TKIs and early molecular response to 2G-TKIs have been examined for the association with stable MR4. Frequencies were compared by Fisher’s exact test. Univariate and multivariate regression analysis were performed using the competing risk model of Fine and Gray.

Results
Median age at diagnosis was 55 years (range 20-88) and median duration of imatinib treatment was 19 months (range 1-115). Patients resistant (n=89; 70%) or intolerant (n=38; 30%) to imatinib were switched to DAS (n=82; 64.5%) or NIL (n=45; 35.5%). Thirty-six patients were resistant or intolerant to their first 2G-TKI and were switched to 3rd-line NIL (n=20), DAS (n=12), bosutinib (n=2), or ponatinib (n=2). At a median follow-up of 52 months after switch to 2G-TKI (range 6-126), best deep MR to 2G-TKI was: no MR4 in 57 patients (45%), unstable MR4 in 28 patients (22%; 24 with 2nd line and 4 with 3rd line treatment), and stable MR4 in 42 patients (33%; 37 with 2nd line and 5 with 3rd line treatment). Five-year cumulative incidence of stable MR4 was 28.7% (95%CI: 18.9-37.3%). Age, sex, risk scores at diagnosis, type of BCR-ABL transcript, duration of imatinib and type of 2G-TKI were similar between patients with or without stable MR4 (Table I). Predictors of stable MR4 were reason for switch to 2G-TKI (intolerance vs resistance HR 0.41, 95%CI: 0.22-0.79; p=0.007) and 3-month BCR-ABL level after 2G-TKI start (≤10%IS vs >10%IS HR 0.08, 95%CI: 0.01-0.59; p=0.01). Three stable MR4 patients attempted discontinuation and are presently in treatment-free remission phase at 2, 22 and 27 months after 2G-TKI stop, respectively.

Conclusion
In this retrospective, real-life experience, long-term use of 2G-TKIs in ≥2nd line of treatment after imatinib failure resulted in more than half of patients achieving the “safe haven” of deep MR, with around 60% of them in stable MR4, a prerequisite for discontinuing treatment.



Session topic: E-poster

Keyword(s): Molecular response, Prediction, Tyrosine kinase inhibitor

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