Frontiers in Oncology (Mar 2020)

Risk Stratification Using Multivariable Fractional Polynomials in Diffuse Large B-Cell Lymphoma

  • Jin Roh,
  • Jiwon Jung,
  • Jiwon Jung,
  • Yourim Lee,
  • So-Woon Kim,
  • Hyo-Kyung Pak,
  • Hyo-Kyung Pak,
  • Hyo-Kyung Pak,
  • A-Neum Lee,
  • A-Neum Lee,
  • Junho Lee,
  • Junho Lee,
  • Jaehyeong Cho,
  • Hyungwoo Cho,
  • Dok Hyun Yoon,
  • Rae Woong Park,
  • Jooryung Huh,
  • Heung-Bum Oh,
  • Chan-Sik Park,
  • Chan-Sik Park

DOI
https://doi.org/10.3389/fonc.2020.00329
Journal volume & issue
Vol. 10

Abstract

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The risk stratification of diffuse large B-cell lymphoma (DLBCL) is crucial. The International Prognostic Index, the most commonly used and the traditional risk stratification system, is composed of fixed and artificially dichotomized attributes. We aimed to develop a novel prognostic model that allows the incorporation of up-to-date attributes comprehensively without information loss. We analyzed 204 patients with primary DLBCL who were uniformly treated with R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) from 2007 to 2012 at Asan Medical Center. Using the multivariable fractional polynomial (MFP) method and bootstrap resampling, we selected the variables of significance and the best fitted functional form in fractional polynomials. Age, serum β2-microglobulin, serum lactate dehydrogenase, and BCL2 expression were selected as significant variables in predicting overall survival (OS), while age was excluded in predicting 2-years event-free survival. The prognostic score calculated by the MFP model effectively classifies patients into four risk groups with 5-years OS of 89.91% (low risk), 81.21% (low-intermediate risk), 66.40% (high-intermediate risk), and 37.89% (high risk). We suggest a new prognostic model that is simple and flexible. By using the MFP method, we can incorporate various clinicopathologic factors into a risk stratification system without arbitrary dichotomization.

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