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Tumor Engraftment in a Xenograft Mouse Model of Human Mantle Cell Lymphoma
Published on: March 30, 2018
Useful prognostic tools based on complete blood cell counts in diffuse large B-cell lymphoma.
Joji Shimono1,2, Shogo Takahashi1, Ryo Takemura1
1Department of Hematology, Asahikawa city hospital, Asahikawa, Japan.
A simple complete blood count (CBC) model using lymphocyte-to-monocyte ratio (LMR), hemoglobin, and platelets can predict diffuse large B-cell lymphoma (DLBCL) patient outcomes. This CBC-based prognostic tool aids in stratifying high-risk patients.
Area of Science:
- Hematology
- Oncology
- Clinical Pathology
Background:
- Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma.
- Current prognostic models include the International Prognostic Index (IPI), Revised-IPI (R-IPI), and National Comprehensive Cancer Network-IPI (NCCN-IPI).
Purpose of the Study:
- To develop a prognostic model for DLBCL utilizing readily available complete blood cell count (CBC) parameters.
- To assess the predictive value of lymphocyte-to-monocyte ratio (LMR), hemoglobin, and platelet counts in DLBCL prognosis.
Main Methods:
- A prognostic model was developed using CBC data (LMR, hemoglobin, platelets) from 214 DLBCL patients treated with R-CHOP therapy.
- Receiver operating characteristic (ROC) curve analysis determined cutoff values for LMR (1.6), hemoglobin (100 g/L), and platelets (150 × 10^9/L).
- Patients were stratified into three groups based on the presence of these factors.
Main Results:
- The 5-year overall survival (OS) rates for the three CBC groups were 78.2%, 60.9%, and 10.1%.
- Multivariate analysis identified the presence of all three factors (CBC Group 3) as a significant prognostic factor for OS (HR, 2.976; P = .01).
- CBC Group 3 enabled further stratification within existing high-risk IPI and R-IPI groups.
Conclusions:
- A combination of three CBC parameters (LMR, hemoglobin, platelets) shows potential as a valuable prognostic tool in DLBCL.
- This simple CBC-based model can aid in identifying and stratifying patients with poor prognoses.
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