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CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
结外自然杀伤/T 细胞淋巴瘤多参数预后模型的开发与验证：临床、病理和分子生物标志物的整合
英文原题：Development and validation of a multiparameter prognostic model for extranodal natural killer/T-cell lymphoma: Integration of clinical, pathological, and molecular biomarkers.
查看英文原题
Development and validation of a multiparameter prognostic model for extranodal natural killer/T-cell lymphoma: Integration of clinical, pathological, and molecular biomarkers.
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研究概要
NIPI 为 ENKTCL 提供了改进的风险分层，基于 QDB 的分析为个体化治疗提供了更高的精确度。该模型满足了 ENKTCL 预后评估中未满足的需求，值得进一步开展多中心验证。
研究思路结论见上方概要
目的
本研究的目标是通过整合临床和病理参数，开发并验证一种新的结外自然杀伤/T细胞淋巴瘤（ENKTCL）预后模型。
方法
我们回顾性分析了来自烟台毓璜顶医院病理科和南通大学附属医院的106例ENKTCL患者（2008-2020年），通过对免疫组化（IHC）标志物（年龄、MTP53、Ki-67、乳酸脱氢酶、血红蛋白、血小板与淋巴细胞比值）和定量斑点印迹（QDB）肿瘤微环境特征进行多因素Cox回归，构建了新型国际预后指数（NIPI）模型。
结果
该模型显示出显著的风险分层能力（P < 0.001），3年曲线下面积分别为0.72（IHC）和0.80（QDB），优于Ann Arbor分期（P > 0.05）及现有国际预后指数（P = 0.00036）/NK 细胞淋巴瘤预后指数（P = 0.00017）模型。基于QDB的实施表现出更优的预后区分能力（P = 0.00014），凸显了其用于精准个体化治疗的潜力。
展开英文摘要原文
OBJECTIVES
The objectives of the study are to develop and validate a novel prognostic model for extranodal natural killer/T-cell lymphoma (ENKTCL) by integrating clinical and pathological parameters. MATERIAL AND METHODS: We retrospectively analyzed 106 patients with ENKTCL (2008-2020) from the Department of Pathology of Yantai Yuhuangding Hospital and the Affiliated Hospital of Nantong University, constructing the novel international prognostic index (NIPI) model through multivariable Cox regression of immunohistochemistry (IHC) markers (age, MTP53, Ki-67, lactate dehydrogenase, hemoglobin, platelet-tolymphocyte ratio) and quantitative dot blot (QDB) tumor microenvironment features.
RESULTS
The model demonstrated significant risk stratification ( P < 0.001) with a 3-year area under the curve of 0.72 (IHC) and 0.80 (QDB), outperforming Ann Arbor staging ( P > 0.05) and existing international prognostic index ( P = 0.00036)/natural killer lymphoma prognostic index ( P = 0.00017) models. The QDB-based implementation showed superior prognostic discrimination ( P = 0.00014), highlighting its potential for precise individualized therapy.
CONCLUSION
NIPI provides improved risk stratification for ENKTCL, and QDB-based analysis offers enhanced precision in individualized therapy. This model addresses the unmet needs for ENKTCL prognostication and warrants further multicenter validation.
论文信息
- 作者
- Wu S、Liu Y、Jiang L、An L、Zhang Y、Pan Y、Song L、Wang Y
- 单位
- Department of Pathology, Yantai Yuhuangding Hospital, Yantai, China.China
- 期刊
- CytoJournal2026
- 原文标识
- PubMed 42022040 · DOI 10.25259/Cytojournal_34_2025
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