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基于18F-FDG PET/CT代谢参数和代谢异质性的列线图在预测胃癌远处转移中的价值。

The value of a nomogram based on 18F-FDG PET/CT metabolic parameters and metabolic heterogeneity in predicting distant metastasis in gastric cancer.

作者信息

Zhang Guanjie, Shi Aiqi, Ding Xiaofang, Wang Jianlin

机构信息

Department of Nuclear Medicine, Second Affiliated Hospital of Fujian Medical University, Donghai Street No. 950, Fengze District, Quanzhou 362018, PR China.

Second Clinical School, Second Affiliated Hospital of Fujian Medical University, Donghai Street No. 950, Fengze District, Quanzhou 362018, PR China.

出版信息

Jpn J Clin Oncol. 2025 Mar 5;55(3):219-227. doi: 10.1093/jjco/hyae169.

Abstract

OBJECTIVE

To investigate the value of metabolic parameters and metabolic heterogeneity from pretreatment deoxy-2-[fluorine-18]-fluoro-D-glucose positron emission tomography/computed tomography (18F-FDG PET/CT) in predicting distant metastasis in gastric cancer.

METHODS

Eighty-six patients with pathologically confirmed gastric adenocarcinoma were included in this study. All patients underwent a whole-body 18F-FDG PET/CT scan before treatment. Clinicopathologic and imaging data were collected, including metabolic parameters such as maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of the primary gastric cancer lesions. Heterogeneity index (HI)-1 was expressed as the absolute value of the linear regression slopes between the MTVs at different SUVmax thresholds (40% × SUVmax, 80% × SUVmax), while HI-2 was expressed as the difference between SUVmax and SUVmean. Patients were randomly divided into training and validation cohorts at a 7:3 ratio. The correlation between the above parameters and distant metastasis in gastric cancer was analyzed using the training cohort. A nomogram prediction model was then established and later verified with the validation cohort. Finally, decision curve analysis was used to evaluate the clinical utility of the model.

RESULTS

This study included 86 patients with gastric cancer, with 60 (69.8%) in the training cohort and 26 (30.2%) in the validation cohort. There was no significant difference in the balanced comparison between both cohorts (all P > .05). Among all patients, 31 (36.0%) developed distant metastasis, while 55 (64.0%) did not. In patients who developed distant tumor metastasis, carcinoembryonic antigen, carbohydrate antigen (CA)12-5, CA19-9, CA72-4, MTV, TLG, and HI-1 were significantly higher than in patients without distant metastasis (all P < .05). Multivariate logistic regression analysis identified CA72-4 (OR: 1.151, 95% CI: 1.020-1.300, P = .023) and HI-1 (OR: 1.647, 95% CI: 1.063-2.553, P = .026) as independent risk factors for predicting distant metastasis in gastric cancer. The nomogram constructed from this analysis exhibited high predictive efficacy in the training (AUC: 0.874, 95% CI: 0.766-0.983) and validation (AUC: 0.915, 95% CI: 0.790-1.000) cohorts, providing a net clinical benefit for patients.

CONCLUSION

HI-1 is an independent risk factor for predicting distant metastasis in gastric cancer. A comprehensive prediction model combining HI-1 with the tumor marker CA72-4 can increase the net clinical benefit for patients.

摘要

目的

探讨治疗前脱氧 - 2 - [氟 - 18] - 氟 - D - 葡萄糖正电子发射断层扫描/计算机断层扫描(18F - FDG PET/CT)的代谢参数及代谢异质性在预测胃癌远处转移中的价值。

方法

本研究纳入86例经病理证实的胃腺癌患者。所有患者在治疗前均接受全身18F - FDG PET/CT扫描。收集临床病理及影像数据,包括原发性胃癌病灶的代谢参数,如最大标准化摄取值(SUVmax)、平均标准化摄取值(SUVmean)、代谢肿瘤体积(MTV)和总病灶糖酵解(TLG)。异质性指数(HI)-1表示不同SUVmax阈值(40%×SUVmax、80%×SUVmax)下MTV之间线性回归斜率的绝对值,而HI - 2表示SUVmax与SUVmean之间的差值。患者按7:3的比例随机分为训练组和验证组。使用训练组分析上述参数与胃癌远处转移之间的相关性。随后建立列线图预测模型,并用验证组进行验证。最后,采用决策曲线分析评估该模型的临床实用性。

结果

本研究纳入86例胃癌患者,训练组60例(69.8%),验证组26例(30.2%)。两组间均衡比较无显著差异(所有P>0.05)。所有患者中,31例(36.0%)发生远处转移,55例(64.0%)未发生远处转移。发生远处肿瘤转移的患者中,癌胚抗原、糖类抗原(CA)12 - 5、CA19 - 9、CA72 - 4、MTV、TLG和HI - 1显著高于未发生远处转移的患者(所有P<0.05)。多因素逻辑回归分析确定CA72 - 4(OR:1.151,95%CI:1.020 - 1.300,P = 0.023)和HI - 1(OR:1.647,95%CI:1.063 - 2.553,P = 0.026)为预测胃癌远处转移的独立危险因素。由此分析构建的列线图在训练组(AUC:0.874,95%CI:0.766 - 0.983)和验证组(AUC:0.915,95%CI:0.790 - 1.000)中显示出较高的预测效能,为患者提供了净临床获益。

结论

HI - 1是预测胃癌远处转移的独立危险因素。将HI - 1与肿瘤标志物CA72 - 4相结合的综合预测模型可为患者增加净临床获益。

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