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Multiplex polymerase chain reaction‐based prognostic models in diffuse large B‐cell lymphoma patients treated with R‐CHOP
Author(s) -
Green Tina M.,
Jensen Andreas K.,
Holst René,
Falgreen Steffen,
Bøgsted Martin,
Stricker Karin,
Plesner Torben,
MouritsAndersen Torben,
Frederiksen Mikael,
Johnsen Hans E.,
Pedersen Lars M.,
Møller Michael B.
Publication year - 2016
Publication title -
british journal of haematology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.907
H-Index - 186
eISSN - 1365-2141
pISSN - 0007-1048
DOI - 10.1111/bjh.14138
Subject(s) - international prognostic index , diffuse large b cell lymphoma , medicine , oncology , vincristine , chop , rituximab , proportional hazards model , prednisone , lymphoma , cyclophosphamide , chemotherapy
Summary We present a multiplex analysis for genes known to have prognostic value in an attempt to design a clinically useful classification model in patients with diffuse large B‐cell lymphoma (DLBCL). Real‐time polymerase chain reaction was used to measure transcript levels of 28 relevant genes in 194 de novo DLBCL patients treated with R‐CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone). Including International Prognostic Index (IPI) as a variable in a penalized Cox regression, we investigated the association with disease progression for single genes or gene combinations in four models. The best model was validated in data from an online available R‐CHOP treated cohort. With progression‐free survival (PFS) as primary endpoint, the best performing IPI independent model incorporated the LMO2 and HLADQA1 as well as gene interactions for GCSAM x MIB1 , GCSAM x CTGF and FOXP1 x PDE4B . This model assigned 33% of patients ( n = 60) to poor outcome with an estimated 3‐year PFS of 40% vs. 87% for low risk ( n = 61) and intermediate ( n = 60) risk groups ( P < 0·001). However, a simpler, IPI independent model incorporated LMO2 and BCL2 and assigned 33% of the patients with a 3‐year PFS of 35% vs. 82% for low risk group ( P < 0·001). We have documented the impact of a few single genes added to IPI for assignment in new drug trials.