Risk factors for POD24 in patients with previously untreated follicular lymphoma: a systematic review and meta-analysis

• Published in: Annals of hematology Vol. 101; no. 11; pp. 2383 - 2392
• Main Authors: Gao, Fenghua, Zhang, Tingting, Liu, Hengqi, Li, Wei, Liu, Xianming, Qiu, Lihua, Li, Lanfang, Zhou, Shiyong, Qian, Zhengzi, Dong, Sitong, Zhao, Sai, Wang, Xianhuo, Zhang, Huilai
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.11.2022; Springer Nature B.V
• Subjects: Hematology; Lymphoma; Medicine; Medicine & Public Health; Meta-analysis; Oncology; Review Article; Risk factors; Follicular lymphoma; Systematic review; POD24; Risk factors; Meta-analysis
• ISSN: 0939-5555; 1432-0584
• DOI: 10.1007/s00277-022-04914-8

Progression of disease within 24 months (POD24) is strongly associated with a poor outcome in patients with follicular lymphoma (FL). Our study aimed to identify the potential risk factors for POD24 in patients with FL. Medline, EMBASE and the Cochrane Library were systematically searched from the earliest record to September 2020. Studies investigating the prognostic factors for POD24 in patients with newly diagnosed grade 1-3a FL were included. Among 10,014 pieces of literature, a total of 90 studies investigating 82 risk factors were included for qualitative analysis. Meta-analyses were performed in 31 studies with 11 factors. Results showed that elevated sIL-2R, β2m and LDH, total metabolic tumour volume > 510 cm 3 , vitamin D < 20 ng/mL, grade 3a and lymphoma-associated macrophages/high-power field ≥ 15 were significantly associated with an increased risk of POD24. No significant association was found between POD24 and the ALC/AMC ratio, sex, T effector signature or EZH2 genetic alteration. Additionally, minimal residual disease, Ki-67, PD-1 and TP53 were analysed narratively. Overall, this is the first study that comprehensively analysed the prognostic factors associated with POD24 in FL patients. We have confirmed the significance value of several common prognostic factors as well as others not commonly included in clinical study, helping to construct an integrated and more efficient model.