淋巴细胞浸润评分（LIS）及其与肿瘤细胞的最近邻距离（NNDTC）在骨巨细胞瘤（GCTB）中的预后价值目前尚未明确。本研究旨在表征 LIS 和 NNDTC，并检查它们与狄诺塞麦治疗反应、临床病理特征和患者预后的相关性。使用多重定量免疫荧光，在 253 个肿瘤标本中评估 LIS，而 NNDTC 使用 HALO 软件计算。随后，我们分析了这些参数与患者结果（无进展生存期 [PFS] 和总生存期 [OS]）、临床病理特征和地诺塞麦治疗反应性的关联。低 LIS 表明 PFS 和 OS 均较差（P < .001）。此外，LIS 与性别 (P = .046)、Enneking 分期 (P < .001)、Ki-67 表达 (P = .007) 和狄诺塞麦治疗反应性 (P = .005) 显着相关。较低的 CD8（肿瘤内部 [TI]）NNDTC 和 CD3 (TI) NNDTC 与较差的 PFS 相关（分别为 P = .003 和 .038），而较低的 CD8 (TI) NNDTC 与较差的 OS 相关（P = .038）。 001)，但 CD8（肿瘤浸润边缘）NNDTC 具有相反的效果 (P = .002)。此外，NNDTC 显示出与多种临床病理特征的相关性。重要的是，LIS 在预测 GCTB 临床结果方面优于 Enneking 和 Campanaci 分期系统。这些研究结果表明，LIS 是一种可靠的预测工具，可预测 GCTB 患者的临床相关结果和对狄诺塞麦治疗的反应。这些参数可能被证明有助于指导患者的预后风险分层和治疗优化。

The prognostic value of lymphocyte infiltration score (LIS) and its nearest neighbor distance to tumor cells (NNDTC) in giant cell tumor of bone (GCTB) is currently not well established. This study aims to characterize LIS and NNDTC and examine their correlation with denosumab treatment responsiveness, clinicopathologic features, and patient prognosis.Using multiplexed quantitative immunofluorescence, LIS was evaluated in 253 tumor specimens, whereas NNDTC was computed using HALO software. Subsequently, we analyzed the association of these parameters with patient outcomes (progression-free survival [PFS] and overall survival [OS]), clinicopathologic features, and denosumab treatment responsiveness.Low LIS was indicative of both poor PFS and OS (both P < .001). In addition, LIS was significantly associated with sex (P = .046), Enneking staging (P < .001), Ki-67 expression (P = .007), and denosumab treatment responsiveness (P = .005). Lower CD8+ (tumor interior [TI]) NNDTC, and CD3+ (TI) NNDTC were associated with worse PFS (P = .003 and .038, respectively), whereas lower CD8+ (TI) NNDTC was associated with worse OS (P = .001), but CD8+ (tumor infiltrating margin) NNDTC had the opposite effect (P = .002). Moreover, NNDTC showed a correlation with several clinicopathologic features. Importantly, LIS outperformed Enneking and Campanacci staging systems in predicting the clinical outcomes of GCTB.These findings suggest that LIS is a reliable predictive tool for clinically relevant outcomes and response to denosumab therapy in patients with GCTB. These parameters may prove to be useful in guiding prognostic risk stratification and therapeutic optimization for patients.