PD-L1 expression is associated with poor prognosis, although this relationship is unclear in bone marrow-derived haematologic malignancies, including multiple myeloma. We aimed to determine whether PD-L1 expression could predict the prognosis of newly diagnosed multiple myeloma (NDMM). We evaluated 126 NDMM patients (83, retrospectively; 43, prospectively) who underwent bone marrow examinations. Bone marrow aspirates were analysed for PD-L1 expression, categorized as low or high expression, using quantitative immunofluorescence. High PD-L1 expression could independently predict poor overall survival (OS) (95% CIâ=â1.692-8.346) in multivariate analysis. On subgroup analysis, high PD-L1 expression was associated with poor OS (95% CIâ=â2.283-8.761) and progression-free survival (95% CIâ=â1.024-3.484) in patients who did not undergo autologous stem cell transplantation (ASCT) compared with those who did. High PD-L1 expression was associated with poor OS despite frontline treatments with or without immunomodulators. Thus, PD-L1 expression can be a useful prognosis predictor in NDMM patients, whereas ASCT may be used in patients with high PD-L1 expression. We developed a prognostic nomogram and found that a combination of PD-L1 expression in bone marrow plasma cells and clinical parameters (age, cytogenetics, and lactate dehydrogenase) effectively predicted NDMM prognosis. We believe that our nomogram can help identify high-risk patients and select appropriate treatments.
PD-L1 expression in bone marrow plasma cells as a biomarker to predict multiple myeloma prognosis: developing a nomogram-based prognostic model.
骨髓浆细胞中 PD-L1 表达作为预测多发性骨髓瘤预后的生物标志物:建立基于列线图的预后模型
阅读:5
作者:Lee Byung-Hyun, Park Yong, Kim Ji Hye, Kang Ka-Won, Lee Seung Jin, Kim Seok Jin, Kim Byung Soo
| 期刊: | Scientific Reports | 影响因子: | 3.900 |
| 时间: | 2020 | 起止号: | 2020 Jul 28; 10(1):12641 |
| doi: | 10.1038/s41598-020-69616-5 | 研究方向: | 细胞生物学 |
| 疾病类型: | 骨髓瘤 | ||
特别声明
1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。
2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。
3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。
4、投稿及合作请联系:info@biocloudy.com。
