Background

The overall survival(OS) of patients with newly diagnosed multiple myeloma(NDMM) shows wide heterogeneity because of the many influence from patient status, disease biology and therapy options. We therefore developed a comprehensive clinical risk stratification for NDMM patients, integrating patients-related and disease-related risk factors, as well as indicators for immuno-microenvironment in the era of novel agents.

Methods

828 cases were enrolled in our study. Clinical and cytogenetic features were described, and OS was calculated. High-risk aberrations (HRA) was defined as 1q21 amplification, del(17p), and t(4;14)/t(14;16) detected by FISH. Anemia was defined as hemoglobin level<100 g/L; decreased ratio of absolute lymphocyte to monocyte counts (ALC/AMC) was defined as less than 2.95(the cut-off of ALC/AMC was calculated according to the ROC curve as well as AUC value); renal dysfunction refers to serum creatinine ≥2mg/dl; elevated LDH was evaluated as serum LDH>247 U/L; HRA number were calculated by the accumulative occurrence of 1q21 gain, del(17p) and t(4;14)/t(14;16).

Results

In the entire cohort, incidence of 0-3 HRA was 39.6%(249/629), 42.0%(264/629), 17.0%(107/629), and 1.4%(9 /629), respectively. Factors included in the univariate analysis for OS were: age (>65 vs.≤65 years old), hemoglobin level (<100 vs ≥100 g/L), ALC/AMC level (<2.95 vs ≥2.95), LDH elevation (>247 vs.≤247 U/L), renal dysfunction (serum creatinine ≥2 vs.<2 mg/dl), ISS stage (ISS III vs. ISS I/II stage), HRA number (2 vs 1 vs 0). Variables with a p-value<0.05 in univariate analysis were entered into the multivariate Cox proportional hazards model. According to the Cox analysis, age>65 years old (HR=1.58, p=0.003), ALC/AMC<2.95 (HR=1.39 ,p=0.04), elevated LDH>247 U/L (HR=1.53 ,p=0.017), one HRA (vs. 0 HRA, HR=1.59, p=0.004), two HRA (vs. 0 HRA, HR=2.66, p=0.000) and ISS stage III (vs. ISS stage I/II, HR=1.74 ,p=0.011) turned out be independent risk factors(Table1). Therefore, 1 or 2 point was assigned to each factor above according to their HR value, and a risk model was derived(Table2). Comparing with the low-risk category, we observed a worse survival in intermediate-risk (HR=2.47, 95%CI 1.82-3.36, p=0.000) and high-risk category (HR=4.68, 95%CI 3.05-7.19, p=0.000). The median overall survival for the three risk group was 101.6(95%CI, 81.09-122.11), 46.8(95%CI, 39.22-54.38) and 27.7(95%CI, 20.42-34.98)(p value was 3.52*10-9 for int risk vs. low risk; p value was 7.99*10-16 for int risk vs. low risk)(Fig1). Moreover, the risk model remained its predictive power in subgroup-analysis according to R-ISS, exposure to novel agents, and transplantation or not.

Conclusion

We developed a comprehensive clinical risk model for overall survival consisting both patients- and disease biology-related factors. This risk model might be effective in risk stratification and treatment guidance for NDMM patients.

Keywords: Multiple myeloma, Risk stratification, Survival

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Disclosures

No relevant conflicts of interest to declare.

Topics:
multiple myeloma, fiberoptic examinations anoscopy high resolution, creatinine tests, serum, kidney failure, anemia, hemoglobin, hemoglobin measurement, transplantation, univariate analysis, amplification

Author notes

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Asterisk with author names denotes non-ASH members.

© 2019 by The American Society of Hematology
2019
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