Abstract

Introduction The advent of novel therapies over the last decade, including proteasome inhibitors, immunomodulators, and monoclonal antibodies, has drastically improved the outcomes in patients with Multiple Myeloma (MM). It is common in both clinical practice and design of clinical trials to risk stratify patients to determine poor-prognosis based on known high-risk cytogenetics and baseline health status. Despite efforts to unify and refine the definition of high-risk disease, significant heterogeneity exists within risk strata and the majority of MM patients do not harbor high-risk cytogenetics. Many patients with ostensibly standard-risk disease progress rapidly, exhibiting a clinical presentation that aligns more closely with high-risk disease biology. We retrospectively evaluated outcomes within an institutional database to determine whether variation in prognosis among patients with standard risk MM may be predicted by clinical and biochemical features that are measurable at the point of care. Methods This retrospective cohort study included patients diagnosed with MM at the Cleveland Clinic in Cleveland, OH between 1/1/2008 - 12/31/2015 who had relapsed or died prior to initiation of the study. Patients with conventional high-risk cytogenetic features including: del(17p), t(4;14), t(14,20) or t(14;16) by fluorescence in situ hybridization (FISH) were excluded. Multiple variables at diagnosis were included in the analysis: race, gender, age, serum calcium (Ca), B-2-microglobulin, albumin, kidney function, hemoglobin, involved: uninvolved serum free light chain ratio, lactate dehydrogenase (LDH), serum monoclonal (M) protein, International Staging System (ISS) stage, Eastern Cooperative Oncology Group (ECOG) score, and the presence of extramedullary disease. Hypercalcemia (HCa) was defined using 3 groups - Group 1: Ca <10.0, Group 2: 10.1 - 12.5, and Group 3: > 12.5 mg/dL. Time to event analysis was conducted using the Kaplan Meier method. The impact of clinical and biochemical features at presentation on PFS and OS was quantified using a Cox Proportional Hazard on a univariate and multivariate basis in order to determine risk factors for early relapse among this cohort of patients with standard-risk cytogenetics. Results A total of 264 NDMM patients were screened for high-risk cytogenetics and the 18 patients excluded. An additional 99 patients were excluded from our analysis due unavailable FISH data at diagnosis. Twenty-one patients did not have serum calcium levels available at the time of diagnosis and were excluded, resulting in a study population of 126. Among these patients, the median age was 61.5 years old, 77.6% (n=97) of patients were Caucasian, and 47.6% (n=60) were male. The median time to follow up was 5.2 (2.9-7.0) years. A total of 13.6% had extramedullary disease (n=17) and 25.4% had a frontline autologous stem cell transplant (ASCT) (n=32). Stratification was conducted utilizing ISS stage: 34.4% Stage 1 (n=42), 31.1% (n-38) Stage II, and 34.4% (n=42) and ECOG score: 34.4% (n=42) Score 1, 38% (n=38) Score 2, and 42% (n=34.4) Score 3. The three hypercalcemia groups were similar with regard to demographics, ECOG, and laboratory data; however, ISS stage (23%, 47%, and 73%, p=0.002) and serum creatinine (median 0.96, 1.4, and 2.3 mg/dL, p=0.001) were positively correlated with calcium level at time of diagnosis. There was a statistically significant difference in 2-year PFS among the HCa groups (54.4%, 36.1%, and 9.1%, p = 0.002 and p <0.001, respectively) (Figure 1). There was also a statistically significant difference in OS among the HCa groups (Median OS years/5-year OS: 6.1/65.3%, 4.5/46.9%, 2.4/9.1%, p=0.032 and p <0.001, respectively) as well (Figure 2). Differences in PFS and OS remained significant after adjusting for age, race, ISS stage, extramedullary disease, ECOG. and frontline ASCT. Conclusion Our results showed that serum calcium level predicted disease progression and survival in a large cohort of patients without high-risk cytogenetic features. Variation in outcomes among MM patients who do not harbor high risk cytogenetics has not been fully explained. These results may help to inform clinical decision making, refine current risk stratification models, and identify a subpopulation with the strata of standard risk for correlative studies to evaluate disease genomics and biology. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

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