Dynamic Features Occurring during Multiple Myeloma Course Can Modify the Outcome Predicted at Diagnosis By R-ISS Stage

Introduction: Multiple Myeloma (MM) is a heterogeneous disease with a very wide range of progression free survival (PFS) and overall survival (OS) duration. At now, Revised- International Staging System (R-ISS), that classifies patients as low- (LR), intermediate- (IR) and high-risk (HR) according to ISS, cytogenetic and lactate dehydrogenase (LDH), is the most powerful tool to stratify patients with different outcome. Nevertheless, there is still too much variability in outcome in each risk group, particularly in the IR risk group, that deserves further dissection. However, this variability, behind initial prognostic factors, may be still dependent on dynamic features that are unpredictable at diagnosis and that could provide information during the course of the disease.

The aim of this study is to evaluate how much dynamic aspects, such as therapy strategy and response to the therapy, could explain the variability in the R-ISS risk groups and how these information during the course of the disease could be helpful to tailor disease management.

Methods: We analyzed 192 patients recorded in our data-base from 2005 to 2015. All patients received new-drugs (immunomodulatory drugs and proteasome inhibitors) as induction therapy. We classified patients according to R-ISS staging system and analyzed their outcome, in terms of PFS and OS, according to Kaplan-Meier method. Moreover, we analyzed the effect of dynamic variables, such as initial therapy, response to therapy and subsequent therapy, on the outcome of each R-ISS subgroup by stepwise Cox regression method.

Results: Median age of the 192 analyzed patients was 67 years (range 37-93); 27% of patients had > 75 years. Forty-three patients (22%) had stage III ISS and 25% had high-risk cytogenetics. Thalidomide-, proteasome inhibitors- and lenalidomide-based induction therapy was used in 16%, 62% and 22%, respectively. Forty-five percent of patients underwent transplant and 40% received maintenance therapy (54% lenalidomide, 38% bortezomib).

According to R-ISS staging system, LR group (63 patients, 33%), IR group (108 patients, 56%) and HR group (21 patients, 11%) had a median PFS and OS of 58.5 and 124.6 months, of 42.5 and 78.5 months and of 20 and 41.3 months, respectively. Analyzing separately the three R-ISS risk-groups according to the abovementioned dynamic variables, we found that, into the LR population, patients who received maintenance therapy had a significantly longer PFS compared to those who did not (87 vs 40 months; HR=0.36, 95%CI=0.15-0.84; p=0.019) whereas initial therapy and response to therapy were not significantly related. In the IR population, patients who did not achieve a CR had a significantly shorter PFS compared to the patients who did (31 vs 63.5 months; HR=2.5, 95%CI=1.4-4.3; p=0.002); moreover, patients receiving maintenance therapy had a significantly longer PFS compared to those who did not (55 vs 34 months; HR=0.55, 95%CI=0.33-0.94; p=0.028). Finally, in the small HR population we found that patients treated with immunomodulatory drugs tend to have a shorter PFS compared to those treated with proteasome inhibitors (20 vs 34.5 months; HR=2.7, 95%CI=1.0-9.2; p=0.106). No dynamic variables were significantly related to OS in the LR and HR groups whereas in the IR population, patients not achieving CR had a significantly shorter OS (67 months vs not reached, HR=2.6, 95%CI=1.2-5.5; p=0.012).

Conclusions: These results suggest that therapeutic strategy and response to therapy, could modify a priori prognostication given by R-ISS. Patients allocated in IR group achieving CR and that received maintenance therapy have a PFS and OS similar to those patients who were classify as LR (63 vs 58 months and NR vs 124 months, respectively). Moreover, in the LR group, maintenance therapy is proved to maximize PFS. In the HR group, R-ISS seems to be almost predictive for the outcome. These patients seem to benefit from proteasome inhibitor based-therapy although none of the available therapies seem to be really effective. These data could be used to plan studies, testing different therapeutic strategies, with the aim to personalize therapeutic approach according to risk-group assigned at diagnosis.