Contributions
Abstract: PB1964
Type: Publication Only
Background
Estimation of survival for patients with RRMM, requires prognostic tools that define the relative risk of death after first relapse. We recently developed a risk stratification algorithm (RSA) using real-world data from the Czech Registry of Monoclonal Gammopathies (RMG). Our RSA uses patient and disease characteristics at diagnosis and at initiation of second-line treatment (2L), and previous treatment outcomes to stratify patients based on their overall survival (OS) expectations from initiation of 2L treatment (Hajek et al. Blood 2016). The value of such an algorithm depends on its validation, but also on understanding the evidence that explains these differences in survival expectations.
Aims
To describe 2L treatment patterns by RSA group and to report OS, progression-free survival (PFS) and response by treatment received in 2L per RSA risk group.
Methods
Data were collected from the Czech RMG for patients aged ≥18 years who were diagnosed with symptomatic MM between May 2007 and April 2016 and in whom 2L treatment had been initiated. Predictors of OS from the start of 2L were identified using Cox regression analyses. Hazard ratios for each OS predictor were multiplied to obtain an overall score for each patient. Risk groups were defined based on the overall score. To provide optimal patient stratification, cut-offs of the score were estimated using K-adaptive partitioning for survival (KAPS) analysis.
Results
Data from 1418 patients were analysed. KAPS analysis defined four groups based on risk of death: low (LR; score ≤ 4.1; n=403), intermediate-low (ILR; score 4.2–10.3; n=635), intermediate-high (IHR; score 10.4–20.1; n=237) and high (HR; score ≥20.2; n=143) risk. Median OS (months) was 57, 29, 13 and 5 for the LR, ILR, IHR and HR groups, respectively. Following stratification, compared with patients in the lower risk groups, a higher proportion of those in the HR group had LDH levels above 360 U/L and an Eastern Cooperative Oncology Group Performance Status of 3–4 at initiation of 2L. Treatments received at 2L were similar across all risk groups, with bortezomib and lenalidomide being the most common 2L treatments. Patients who received bortezomib at 1L were often given lenalidomide or thalidomide at 2L and those who received thalidomide at 1L were frequently given bortezomib at 2L. This suggests that 2L treatment choice was not defined by the underlying risk of death for each patient, but rather by the type of previous treatment. For patients receiving bortezomib at 2L, median OS (months) from start of 2L was 57, 29, 13 and 6 (Figure 1), and median PFS (months) was 18, 12, 8 and 3 in the LR, ILR, IHR and HR groups, respectively. A very good partial response or better (VGPR+) was reported for 29.3%, 31.0%, 18.7% and 19.6% of patients in the LR, ILR, IHR and HR groups, respectively. For patients receiving lenalidomide at 2L, median OS (months) was 45, 29, 14 and 5, and median PFS (months) was 20, 12, 10 and 3 for patients in the LR, ILR, IHR and HR groups, respectively. A VGPR+ was reported for 33.6%, 22.9%, 26.0% and 7.1% of patients in the LR, ILR, IHR and HR groups, respectively.
Conclusion
The RSA effectively stratifies patients according to OS from initiation of 2L. However, these results must be validated in an external dataset. The outcomes of each risk group are mainly driven by the underlying risk of death at initiation of 2L; treatment with bortezomib or lenalidomide provided similar outcomes independent of risk group. Use of our RSA at 2L would support physician decision making to improve patient specific care.
Session topic: 14. Myeloma and other monoclonal gammopathies - Clinical
Keyword(s): Survival prediction, Multiple Myeloma
Abstract: PB1964
Type: Publication Only
Background
Estimation of survival for patients with RRMM, requires prognostic tools that define the relative risk of death after first relapse. We recently developed a risk stratification algorithm (RSA) using real-world data from the Czech Registry of Monoclonal Gammopathies (RMG). Our RSA uses patient and disease characteristics at diagnosis and at initiation of second-line treatment (2L), and previous treatment outcomes to stratify patients based on their overall survival (OS) expectations from initiation of 2L treatment (Hajek et al. Blood 2016). The value of such an algorithm depends on its validation, but also on understanding the evidence that explains these differences in survival expectations.
Aims
To describe 2L treatment patterns by RSA group and to report OS, progression-free survival (PFS) and response by treatment received in 2L per RSA risk group.
Methods
Data were collected from the Czech RMG for patients aged ≥18 years who were diagnosed with symptomatic MM between May 2007 and April 2016 and in whom 2L treatment had been initiated. Predictors of OS from the start of 2L were identified using Cox regression analyses. Hazard ratios for each OS predictor were multiplied to obtain an overall score for each patient. Risk groups were defined based on the overall score. To provide optimal patient stratification, cut-offs of the score were estimated using K-adaptive partitioning for survival (KAPS) analysis.
Results
Data from 1418 patients were analysed. KAPS analysis defined four groups based on risk of death: low (LR; score ≤ 4.1; n=403), intermediate-low (ILR; score 4.2–10.3; n=635), intermediate-high (IHR; score 10.4–20.1; n=237) and high (HR; score ≥20.2; n=143) risk. Median OS (months) was 57, 29, 13 and 5 for the LR, ILR, IHR and HR groups, respectively. Following stratification, compared with patients in the lower risk groups, a higher proportion of those in the HR group had LDH levels above 360 U/L and an Eastern Cooperative Oncology Group Performance Status of 3–4 at initiation of 2L. Treatments received at 2L were similar across all risk groups, with bortezomib and lenalidomide being the most common 2L treatments. Patients who received bortezomib at 1L were often given lenalidomide or thalidomide at 2L and those who received thalidomide at 1L were frequently given bortezomib at 2L. This suggests that 2L treatment choice was not defined by the underlying risk of death for each patient, but rather by the type of previous treatment. For patients receiving bortezomib at 2L, median OS (months) from start of 2L was 57, 29, 13 and 6 (Figure 1), and median PFS (months) was 18, 12, 8 and 3 in the LR, ILR, IHR and HR groups, respectively. A very good partial response or better (VGPR+) was reported for 29.3%, 31.0%, 18.7% and 19.6% of patients in the LR, ILR, IHR and HR groups, respectively. For patients receiving lenalidomide at 2L, median OS (months) was 45, 29, 14 and 5, and median PFS (months) was 20, 12, 10 and 3 for patients in the LR, ILR, IHR and HR groups, respectively. A VGPR+ was reported for 33.6%, 22.9%, 26.0% and 7.1% of patients in the LR, ILR, IHR and HR groups, respectively.
Conclusion
The RSA effectively stratifies patients according to OS from initiation of 2L. However, these results must be validated in an external dataset. The outcomes of each risk group are mainly driven by the underlying risk of death at initiation of 2L; treatment with bortezomib or lenalidomide provided similar outcomes independent of risk group. Use of our RSA at 2L would support physician decision making to improve patient specific care.
Session topic: 14. Myeloma and other monoclonal gammopathies - Clinical
Keyword(s): Survival prediction, Multiple Myeloma