EHA Library - The official digital education library of European Hematology Association (EHA)

IS A DEEP RESPONSE THE KEY TO SUCCESSFUL TREATMENT OF MULTIPLE MYELOMA?
Author(s): ,
Johan Liwing
Affiliations:
Department of Medicine,Karolinska Institutet, Stockholm,Stockholm,Sweden
,
Bart M.S. Heeg
Affiliations:
Ingress-health, Rotterdam,Netherlands
,
Sigrid Karstorp
Affiliations:
Department of Medicine,Karolinska Institutet, Stockholm,Stockholm,Sweden
,
Maarten Postma
Affiliations:
Unit of PharmacoEpidemiology & PharmacoEconomics,Institute of Science in Healthy Aging & health caRE (SHARE),Groningen,Netherlands
,
Raija Silvennoinen
Affiliations:
Kuopio University Hospital,Kuopio,Finland
,
Mervi Putkonen
Affiliations:
Turku University Hospital,Turku,Finland
,
Pekka Anttila
Affiliations:
HUS,Helsinkki,Finland
,
Kari Remes
Affiliations:
Turku University Hospital,Turku,Finland
,
Niels Abildgaard
Affiliations:
Department of Hematology, Odense University Hospital, Odense,Denmark
,
Anders Waage
Affiliations:
Department of Hematology,St Olavs Hospital,Trondheim,Norway
Hareth Nahi
Affiliations:
Department of Medicine,Karolinska Institutet, Stockholm,Stockholm,Sweden
(Abstract release date: 05/21/15) EHA Library. Liwing J. 06/12/15; 100540; P291 Disclosure(s): Karolinska Institutet, Stockholm
Department of Medicine Janssen, Stockholm
Global Commercial Strategy Organization
Johan Liwing
Johan Liwing
Contributions
Abstract
Abstract: P291

Type: Poster Presentation

Presentation during EHA20: From 12.06.2015 17:15 to 12.06.2015 18:45

Location: Poster area (Hall C)

Background
Several authors have highlighted the importance of a deep response to chemotherapy in multiple myeloma (MM), especially in first line.

Aims
The objective was to assess which patient/treatment/disease characteristics are prognostic for a deep response. Also, to assess whether the deep response is prognostic for overall survival (OS) independent of treatment, treatment line and patient/disease characteristics.

Methods
A retrospective analysis was performed on 2960 MM-patients from 24 hospitals in Denmark, Finland, Norway and Sweden. The database contained information on patient baseline characteristics such as age, gender, ISS stage, albumin, creatine, and MM type, which were recorded at start of first line therapy. The following outcomes were considered; response, time to next line of treatment (TTNT) and OS. The following categories of response were differentiated: progressive disease (PD), no response (NR), partial response (PR), very good PR (VGPR) and equal or better than near complete response (>=nCR). To identify prognostic factors for response, univariate and multivariate multinomial regression were conducted with response as dependent and patient baseline characteristics and type of treatment as independent variables. To assess whether response is an independent predictor of OS, multivariate cox-proportional hazard models were run for the first four lines of treatment.

Results
Patients in the dataset were on average 67 years old, 48% were male, 28%, 41% and 31% in ISS stages I, II and III, respectively. Multinomial regression showed that type of treatment, age, ISS type and MM type were significant prognostic factors for response in first line. In second line, first line response, type of treatment and age were significant prognostic factors for response in second line. Multivariate cox-regression showed that in first line patients with NR, PR, VGPR and >=nCR had significant lower hazard ratio’s (HRs) 0.61 (0.43-0.85), 0.56 (0.41-0.78), 0.34 (0.22-0.51) and 0.36 (0.24-0.54) respectively compared to PD. Age, Albumin, Calcium and Beta-2-microglobulin levels were also significant prognostic factors for OS with HRs of 1.03 (1.01-1.04), 0.98 (0.96-0.99), 1.41 (1.11-1.79) and 1.02 (1.01-1.03) respectively. The following categorical variables also were significant prognostic factors for first line OS; type of treatment, ISS-stage and MM type. For second line OS multivariate cox-regression showed that patients with PR, VGPR and >=nCR had significant lower HR’s 0.58 (0.46-0.73), 0.42 (0.3-0.58), 0.4 (0.27-0.6) compared to PD respectively. Age also had a significant HR of 1.02 (1.01-1.03). For third line OS multivariate cox-regression showed that patients with NR, PR, VGPR and >=nCR had significant lower HR’s 0.67 (0.5-0.89), 0.37 (0.27-0.51), 0.32 (0.21-0.5), 0.18 (0.1-0.34) compared to PD respectively. Age also had a significant HR of 1.01 (1.00-1.02). For fourth line OS multivariate cox-regression showed that patients with PR, VGPR and >=nCR had significant lower HR’s 0.45 (0.31-0.64), 0.31 (0.19-0.52) and 0.39 (0.21-0.73) compared to PD respectively. Age was also identified as a significant prognostic factor.

Summary
Type of treatment, age, ISS type and MM type were significant prognostic factors for response in first line. For second line response, the significant prognostic factors were response in first line, type of treatment and age. Moreover, multivariate cox-regressions shows that in the first four lines of treatment, response is an independent prognostic factor for OS. Future research should include genetic prognostic factors, which were not collected in our dataset and could therefore not be assessed.

Keyword(s): Multiple myeloma, Survival prediction

Session topic: Multiple myeloma - Clinical 5
Abstract: P291

Type: Poster Presentation

Presentation during EHA20: From 12.06.2015 17:15 to 12.06.2015 18:45

Location: Poster area (Hall C)

Background
Several authors have highlighted the importance of a deep response to chemotherapy in multiple myeloma (MM), especially in first line.

Aims
The objective was to assess which patient/treatment/disease characteristics are prognostic for a deep response. Also, to assess whether the deep response is prognostic for overall survival (OS) independent of treatment, treatment line and patient/disease characteristics.

Methods
A retrospective analysis was performed on 2960 MM-patients from 24 hospitals in Denmark, Finland, Norway and Sweden. The database contained information on patient baseline characteristics such as age, gender, ISS stage, albumin, creatine, and MM type, which were recorded at start of first line therapy. The following outcomes were considered; response, time to next line of treatment (TTNT) and OS. The following categories of response were differentiated: progressive disease (PD), no response (NR), partial response (PR), very good PR (VGPR) and equal or better than near complete response (>=nCR). To identify prognostic factors for response, univariate and multivariate multinomial regression were conducted with response as dependent and patient baseline characteristics and type of treatment as independent variables. To assess whether response is an independent predictor of OS, multivariate cox-proportional hazard models were run for the first four lines of treatment.

Results
Patients in the dataset were on average 67 years old, 48% were male, 28%, 41% and 31% in ISS stages I, II and III, respectively. Multinomial regression showed that type of treatment, age, ISS type and MM type were significant prognostic factors for response in first line. In second line, first line response, type of treatment and age were significant prognostic factors for response in second line. Multivariate cox-regression showed that in first line patients with NR, PR, VGPR and >=nCR had significant lower hazard ratio’s (HRs) 0.61 (0.43-0.85), 0.56 (0.41-0.78), 0.34 (0.22-0.51) and 0.36 (0.24-0.54) respectively compared to PD. Age, Albumin, Calcium and Beta-2-microglobulin levels were also significant prognostic factors for OS with HRs of 1.03 (1.01-1.04), 0.98 (0.96-0.99), 1.41 (1.11-1.79) and 1.02 (1.01-1.03) respectively. The following categorical variables also were significant prognostic factors for first line OS; type of treatment, ISS-stage and MM type. For second line OS multivariate cox-regression showed that patients with PR, VGPR and >=nCR had significant lower HR’s 0.58 (0.46-0.73), 0.42 (0.3-0.58), 0.4 (0.27-0.6) compared to PD respectively. Age also had a significant HR of 1.02 (1.01-1.03). For third line OS multivariate cox-regression showed that patients with NR, PR, VGPR and >=nCR had significant lower HR’s 0.67 (0.5-0.89), 0.37 (0.27-0.51), 0.32 (0.21-0.5), 0.18 (0.1-0.34) compared to PD respectively. Age also had a significant HR of 1.01 (1.00-1.02). For fourth line OS multivariate cox-regression showed that patients with PR, VGPR and >=nCR had significant lower HR’s 0.45 (0.31-0.64), 0.31 (0.19-0.52) and 0.39 (0.21-0.73) compared to PD respectively. Age was also identified as a significant prognostic factor.

Summary
Type of treatment, age, ISS type and MM type were significant prognostic factors for response in first line. For second line response, the significant prognostic factors were response in first line, type of treatment and age. Moreover, multivariate cox-regressions shows that in the first four lines of treatment, response is an independent prognostic factor for OS. Future research should include genetic prognostic factors, which were not collected in our dataset and could therefore not be assessed.

Keyword(s): Multiple myeloma, Survival prediction

Session topic: Multiple myeloma - Clinical 5

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