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. 2017 Nov;102(11):e456-e459.
doi: 10.3324/haematol.2017.168070. Epub 2017 Aug 3.

Circulating microRNA expressions can predict the outcome of lenalidomide plus low-dose dexamethasone treatment in patients with refractory/relapsed multiple myeloma

Seung-Hyun Jung  1   2 , Sung-Eun Lee  3 , Minho Lee  2 , So-Hee Kim  4 , Seon-Hee Yim  4 , Tae Woo Kim  3 , Chang-Ki Min  5   6 , Yeun-Jun Chung  7   4   8
Affiliations

Circulating microRNA expressions can predict the outcome of lenalidomide plus low-dose dexamethasone treatment in patients with refractory/relapsed multiple myeloma

Seung-Hyun Jung et al. Haematologica. 2017 Nov.
No abstract available

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Figures

Figure 1.
Figure 1.
Kaplan-Meier curves for time to progression (TTP) and overall survival (OS) by miRNA expression level. (A) Patients with lower expression (blue) of each miRNA in all six markers showed significantly poorer TTP than those with higher expression (green). (B) Patients with lower expression (blue) of each miRNA in four markers showed significantly poorer OS than those with higher expression (green). (C) As the sum of the lower expression marker increased, prognosis became significantly worse in a dose-dependent manner (upper plot: TTP; lower plot: OS).
Figure 2.
Figure 2.
Receiver Operating Characteristic (ROC) curves for the lenalidomide+low-dose dexamethasone (Len-dex) treatment response prediction (LdTRP) model. ROC curves for the LdTRP model composed of five clinical variables [cytogenetics, International Staging System (ISS) stage, hemoglobin, white blood cell (WBC) count, and calcium] and two miRNAs (miR-26a-5p and miR-193a-5p) (red), and other support vector machines (SVMs) with either clinical variables only (green) or miRNAs only (blue) are shown. The LdTRP model showed much superior stratification power [area under the curve (AUC)=0.933] to other SVMs, especially in terms of specificity.
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References

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