R0切除术后腹膜后脂肪肉瘤的预后因素:年龄、组织学类型、肿瘤分期和分化等级的研究。

IF 1.6 4区 医学 Q3 MEDICINE, RESEARCH & EXPERIMENTAL
American journal of translational research Pub Date : 2025-08-15 eCollection Date: 2025-01-01 DOI:10.62347/FQAD9826
Boyuan Zou, Xiaobing Chen, Haicheng Gao, Shibo Liu, Wenjie Li, Yingjiang Ye
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引用次数: 0

摘要

目的:本研究旨在确定影响R0切除术后腹膜后脂肪肉瘤(RPLS)患者无进展生存(PFS)的预后因素。方法:回顾性分析183例行R0切除术的RPLS患者的一般资料、临床病理资料、实验室参数及随访结果。根据随访结果,将患者分为无进展生存组(PFS, n=121)和疾病进展组(DP, n=62)。系统比较两组患者的一般资料、临床病理资料、实验室参数,并将有统计学意义的因素纳入Cox多元回归分析。通过Cox分析确定的重要预后因素进一步采用Kaplan-Meier (K-M)生存分析进行评估,作为构建预测模型的基础。对该模型的1年、3年和总体PFS预测进行了严格的评估。结果:多因素分析确定年龄(HR=1.034, 95% CI=1.011-1.057, P=0.003)、组织学亚型(以高分化脂肪肉瘤为参照)。去分化脂肪肉瘤:HR=0.130, 95% CI=0.029-0.578, P=0.007。黏液样/圆细胞脂肪肉瘤:HR=0.190, 95% CI=0.084 ~ 1.635, P=0.190。多形性脂肪肉瘤:HR=0.176, 95% CI=0.036-0.865, P=0.032。混合型脂肪肉瘤:HR=0.793, 95% CI=0.157-4.008, P=0.799)、肿瘤分期(HR=0.440, 95% CI=0.257-0.755, P=0.003)和肿瘤分化等级(HR=0.395, 95% CI=0.236-0.661, P)。结论:高龄、DDLPS、PLS、III-IV期疾病和肿瘤分化差是R0切除术后RPLS患者PFS缩短的独立预测因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prognostic factors in retroperitoneal liposarcoma after R0 resection: a study of age, histologic type, tumor stage, and differentiation grade.

Objective: This study aimed to identify prognostic factors affecting progression-free survival (PFS) in patients with retroperitoneal liposarcoma (RPLS) after R0 resection.

Methods: A retrospective analysis was conducted on 183 RPLS patients who underwent R0 resection, evaluating general information, clinicopathological data, laboratory parameters, and follow-up outcomes. Based on follow-up outcomes, patients were categorized into progression-free survival (PFS) group (PFS, n=121) and disease progression group (DP, n=62). The general information, clinicopathological data, and laboratory parameters of the two groups were systematically compared, with statistically significant factors subsequently incorporated into the Cox multivariate regression analysis. Significant prognostic factors identified through Cox analysis were further evaluated using Kaplan-Meier (K-M) survival analysis, serving as the foundation for constructing the predictive model. The model's performance was rigorously assessed for 1-year, 3-year, and overall PFS prediction.

Results: Multivariate analysis identified age (HR=1.034, 95% CI=1.011-1.057, P=0.003), histologic subtype (Well-differentiated liposarcoma as reference. Dedifferentiated liposarcoma: HR=0.130, 95% CI=0.029-0.578, P=0.007. Myxoid/round cell liposarcoma: HR=0.190, 95% CI=0.084-1.635, P=0.190. Pleomorphic liposarcoma: HR=0.176, 95% CI=0.036-0.865, P=0.032. Mixed-type liposarcoma: HR=0.793, 95% CI=0.157-4.008, P=0.799), tumor stage (HR=0.440, 95% CI=0.257-0.755, P=0.003), and tumor differentiation grade (HR=0.395, 95% CI=0.236-0.661, P<0.001) as independent risk factors. The predictive models demonstrated excellent discriminative ability: 1-year model (AUC=0.944, NB=0.05-0.80), 3-year model (AUC=0.861, NB=0.05-0.73), the overall mode (AUC=0.903, NB=0.03-0.90).

Conclusion: Advanced age, DDLPS, PLS, stage III-IV disease, and poor tumor differentiation were identified as independent predictors of shorter PFS in RPLS patients following R0 resection.

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American journal of translational research
American journal of translational research ONCOLOGY-MEDICINE, RESEARCH & EXPERIMENTAL
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