Lead Investigator: Yutaka Shimazu, Kyoto University Hospital
Title of Proposal Research: Pretreatment lymphocyte counts and free light chain ratio predict the efficacy of elotuzumab against relapsed refractory multiple myeloma
Vivli Data Request: 8860
Funding Source: None
Potential Conflicts of Interest: None
Summary of the Proposed Research:
Several new drugs has been introduced in the treatment of multiple myeloma (MM) and the prognosis of MM patients improved dramatically. Among the new drugs, we focused on elotuzumab. Elotuzumab have showed a high response rate in relapsed MM patients. However, the durable efficacy was achieved in only one fourth of the patients. Because non-responders might benefit from alternative treatments, it is important to select suitable patients for elotuzumab beforehand. Here, we are trying to identify the characteristics of patients likely to exhibit a durable response to elotuzumab before the treatment (so called “biomarkers”). In the previous study, we have established simple models to predict the response of elotuzumab. In this study, we will attempt to identify the biomarkers of patients for elotuzumab by focusing on the immunological mechanism of elotuzumab. Elotuzumab is not a cytotoxic drug but rather an immunotherapeutic that works with the help of host immune cells. Therefore, it is important to take into account the host’s immune status. We hypothesized that the balance between the tumor burden and the immune status of the host before treatment may determine the efficacy of elotuzumab treatment. We are planning to use univariate analysis and multivariate analysis for progression free surivival to identify the factors which could be related to the response against elotuzumab treatment and establish simple predicting models. If we could identify the predicting models, it would contribute greatly to the MM patients care.
Statistical Analysis Plan:
We set the significance level to 0.05, power to 0.8 and effect size to 0.5 and calculate the sample size as 164. Sensitive analysis will be used to assess the validity of the study results. Best-case and worst-case scenarios will be considered for imputing the missing values. We will analyze the patients who were treated with elotuzumab plus lenalidomide (ERd) in ELOQUENT-2 study. First, to analyze the underlying factors affecting the progression-free survival (PFS), we perform univariate analysis using the following parameters; age, gender, high-risk cytogenic abnormalities, κ/λ ratio, B2MG, lymphocyte counts, and prior regmine numbers. Then, we will perform multivariate analyses against PFS using the factors that showed p<0.1 in univariate analysis. Next, to establish the predictive model for ERd, we will divide the patients into three groups by using two different models. In model 1, the patients were classified into three categories based on their lymphocyte counts (0 points for ≥1400/μL and 1 point for <1400/μL) and κ/λ ratio (0 points for 0.1-10 and 1 point for <0.1 or ≥10). In model 2, the patients were classified into three categories (total score 0, 1 and 2) based on their lymphocyte counts (0 points for ≥1400/μL and 1 point for <1400/μL) and or β2-microglobulin (0 points for <5.5mg/L and 1 point for ≥5.5mg/L). By using two models, we divide the patients into three groups: total scores of 0,1, and 2. We assess the durable efficacy of elotuzumab by using progression free survival (PFS) data. We calculate the PFS of three groups by Kaplan-Meier method with log-rank test. We use PFS as a primary endpoint. As a secondary endpoint, we would like to compare the overall survival (OS) of three groups by Kaplan-Meier method with log-rank test. Requested Studies:
The purpose of the study is to determine whether the addition of Elotuzumab to Lenalidomide/low-dose Dexamethasone will increase the progression free survival.
Data Contributor: Bristol Myers Squibb
Study ID: NCT01239797
Sponsor ID: NCT01239797