| Title |
Prognostic value of the inverse platelet to lymphocyte ratio (iPLR) in patients with multiple myeloma who were treated up front with a novel agent-containing regimen
|
|---|---|
| Published in |
Annals of Hematology, October 2015
|
| DOI | 10.1007/s00277-015-2521-x |
| Pubmed ID | |
| Authors |
Sung-Hoon Jung, Jin Seok Kim, Won Sik Lee, Suk Joong Oh, Jae-Sook Ahn, Deok-Hwan Yang, Yeo-Kyeoung Kim, Hyeoung-Joon Kim, Je-Jung Lee |
| Abstract |
Recently, reactive thrombosis or platelet to lymphocyte ratio has been reported as a strong predictor of poor prognosis in various types of cancer. However, a study investigating the relationship between platelet counts and thrombopoietic cytokines suggested that low platelet could be important in multiple myeloma (MM), which means platelet count decreased in advanced International Staging System (ISS) stage. Therefore, we developed inverse platelet to lymphocyte ratio (iPLR) and assessed the prognostic value of iPLR in patients with MM. We retrospectively analyzed 283 patients who were treated up front with a novel agent-containing regimen. Patients were classified into three groups based on hazard ratio (HR) according to iPLR: low iPLR (group 1), middle iPLR (group 2), and high iPLR (group 3). Over a median follow-up of 34.8 months, staging by iPLR group had predictive value for progression-free survival (PFS) and overall survival (OS). In addition, staging by iPLR group was a reliable method to predict for survival in patients who presented with renal failure (eGFR < 60 mL/min/1.73 m(2)) and in elderly patients. Multivariate analyses demonstrated that staging by iPLR group was associated with PFS and OS in patients with MM. In conclusion, this study suggested that iPLR is a simple and reliable inflammatory prognostic factor in the era of novel agents. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 15 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 2 | 13% |
| Researcher | 2 | 13% |
| Student > Postgraduate | 2 | 13% |
| Student > Master | 2 | 13% |
| Student > Doctoral Student | 1 | 7% |
| Other | 3 | 20% |
| Unknown | 3 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 11 | 73% |
| Computer Science | 1 | 7% |
| Biochemistry, Genetics and Molecular Biology | 1 | 7% |
| Unknown | 2 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 November 2015.
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#20,295,501
of 22,832,057 outputs
Outputs from Annals of Hematology
#1,705
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Outputs of similar age
#234,162
of 279,238 outputs
Outputs of similar age from Annals of Hematology
#20
of 35 outputs
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