Author:
Lu Yaxiao,Yu Jingwei,Gong Wenchen,Su Liping,Sun Xiuhua,Bai Ou,Zhou Hui,Guan Xue,Zhang Tingting,Li Lanfang,Qiu Lihua,Qian Zhengzi,Zhou Shiyong,Meng Bin,Ren Xiubao,Wang Xianhuo,Zhang Huilai
Abstract
PurposeAlthough the role of tumor-infiltrating T cells in follicular lymphoma (FL) has been reported previously, the prognostic value of peripheral blood T lymphocyte subsets has not been systematically assessed. Thus, we aim to incorporate T-cell subsets with clinical features to develop a predictive model of clinical outcome.MethodsWe retrospectively screened a total of 1,008 patients, including 252 newly diagnosed de novo FL patients with available peripheral blood T lymphocyte subsets who were randomized to different sets (177 in the training set and 75 in the internal validation set). A nomogram and a novel immune-clinical prognostic index (ICPI) were established according to multivariate Cox regression analysis for progression-free survival (PFS). The concordance index (C-index), Akaike’s information criterion (AIC), and likelihood ratio chi-square were employed to compare the ICPI’s discriminatory capability and homogeneity to that of FLIPI, FLIPI2, and PRIMA-PI. Additional external validation was performed using a dataset (n = 157) from other four centers.ResultsIn the training set, multivariate analysis identified five independent prognostic factors (Stage III/IV disease, elevated lactate dehydrogenase (LDH), Hb <120g/L, CD4+ <30.7% and CD8+ >36.6%) for PFS. A novel ICPI was established according to the number of risk factors and stratify patients into 3 risk groups: high, intermediate, and low-risk with 4-5, 2-3, 0-1 risk factors respectively. The hazard ratios for patients in the high and intermediate-risk groups than those in the low-risk were 27.640 and 2.758. The ICPI could stratify patients into different risk groups both in the training set (P < 0.0001), internal validation set (P = 0.0039) and external validation set (P = 0.04). Moreover, in patients treated with RCHOP-like therapy, the ICPI was also predictive (P < 0.0001). In comparison to FLIPI, FLIPI2, and PRIMA-PI (C-index, 0.613-0.647), the ICPI offered adequate discrimination capability with C-index values of 0.679. Additionally, it exhibits good performance based on the lowest AIC and highest likelihood ratio chi-square score.ConclusionsThe ICPI is a novel predictive model with improved prognostic performance for patients with de novo FL treated with R-CHOP/CHOP chemotherapy. It is capable to be used in routine practice and guides individualized precision therapy.
Funder
Foundation for Innovative Research Groups of the National Natural Science Foundation of China
Natural Science Foundation of Tianjin City
Chinese Society of Clinical Oncology
National Key New Drug Creation and Manufacturing Program, Ministry of Science and Technology
Cited by
3 articles.
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