Suppr超能文献

通过整合中性粒细胞-淋巴细胞比值、血小板-淋巴细胞比值和 Ga-PSMA-PET 衍生的 SUVmax 值来优化前列腺癌患者的淋巴结分期。

Optimization of prostate cancer patient lymph node staging via the integration of neutrophil-lymphocyte ratios, platelet-lymphocyte ratios, and Ga-PSMA-PET-derived SUVmax values.

机构信息

Department of Nuclear Medicine, Disorders of Prostate Cancer Multidisciplinary Team, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha City, Hunan Province, China.

Department of Pathology, Disorders of Prostate Cancer Multidisciplinary Team, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha City, Hunan Province, China.

出版信息

Prostate. 2022 Nov;82(15):1415-1421. doi: 10.1002/pros.24415. Epub 2022 Jul 21.

Abstract

BACKGROUND

At present, standardized parameters for quantitatively evaluating Ga-PSMA-PET/CT outcomes when diagnosing lymph node metastasis in prostate cancer patients are lacking. Inflammatory hematological biomarkers offer value as robust predictors of certain cancer-related outcomes. The present study was thus developed to explore approaches to improving the utility of Ga-PSMA-PET/CT for diagnosing lymph node metastasis through the combined evaluation of inflammatory hematological markers in prostate cancer patients.

METHODS

Pretreatment patient details including age, initial TPSA levels, hematological findings, biopsy pathology results (Gleason score and ISUP grouping), radical pathology results, and imaging details were collected. Optimal cutoff values for each predictor then being determined based upon Youden's index, with univariate and multivariate analyses were then used to identify independent predictors of lymph node metastasis and used to construct a nomogram.

RESULT

Independent predictors of lymph node metastasis in this patient cohort included SUVmax (odds ratio [OR]: 30.549, 95% confidence interval [CI]: 10.855-85.973, p < 0.001), neutrophil-lymphocyte ratio (OR:8.221, 95%CI: 1.335-50.614, p = 0.023), platelet-lymphocyte ratio (OR:8.221, 95% CI: 1.335-50.614, p = 0.023), initial TPSA (OR:2.761, 95% CI: 1.132-6.733, p = 0.026), and clinical T-stage (T3 vs. T2, OR:11.332, 95% CI:3.929-32.681, p < 0.001; T4 vs. T2, OR:9.101, 95% CI:1.962-42.213, p = 0.005), with corresponding optimal cutoff values of 2.3 (area under the curve [AUC]: 0.873, sensitivity: 0.736, specificity: 0.902), 1.72 (AUC: 0.558, sensitivity: 0.529, specificity: 0.643), 83.305 (AUC: 0.651, sensitivity: 0.299, specificity: 0.979), and 21.875 (AUC: 0.672, sensitivity: 0.736, specificity: 0.601). Subsequent nomogram construction was associated with good predictive ability, with a C-index of 0.887(95% CI: 0.793-0.981) and an AUC of 0.924 (95% CI: 0.882-0.965).

CONCLUSION

SUVmax, the neutrophil-lymphocyte ratio, the platelet-lymphocyte ratio, initial TPSA, and clinical T-stage represent valuable independent predictors of lymph node metastasis in prostate cancer patients, offering an opportunity to further optimize lymph node staging for these patients.

摘要

背景

目前,用于定量评估前列腺癌患者淋巴结转移的 Ga-PSMA-PET/CT 结果的标准化参数缺乏。炎症性血液生物标志物可作为某些癌症相关结果的可靠预测因子。因此,本研究旨在通过联合评估前列腺癌患者的炎症性血液标志物,探讨如何提高 Ga-PSMA-PET/CT 对诊断淋巴结转移的效用。

方法

收集了患者的年龄、初始 TPSA 水平、血液学发现、活检病理结果(Gleason 评分和 ISUP 分组)、根治性病理结果和影像学细节等术前资料。然后,根据 Youden 指数确定每个预测因子的最佳截断值,再进行单因素和多因素分析,以确定淋巴结转移的独立预测因子,并构建列线图。

结果

该患者队列中淋巴结转移的独立预测因子包括 SUVmax(优势比[OR]:30.549,95%置信区间[CI]:10.855-85.973,p<0.001)、中性粒细胞-淋巴细胞比值(OR:8.221,95%CI:1.335-50.614,p=0.023)、血小板-淋巴细胞比值(OR:8.221,95%CI:1.335-50.614,p=0.023)、初始 TPSA(OR:2.761,95%CI:1.132-6.733,p=0.026)和临床 T 分期(T3 与 T2,OR:11.332,95%CI:3.929-32.681,p<0.001;T4 与 T2,OR:9.101,95%CI:1.962-42.213,p=0.005),相应的最佳截断值分别为 2.3(曲线下面积[AUC]:0.873,灵敏度:0.736,特异性:0.902)、1.72(AUC:0.558,灵敏度:0.529,特异性:0.643)、83.305(AUC:0.651,灵敏度:0.299,特异性:0.979)和 21.875(AUC:0.672,灵敏度:0.736,特异性:0.601)。随后的列线图构建与良好的预测能力相关,C 指数为 0.887(95%CI:0.793-0.981),AUC 为 0.924(95%CI:0.882-0.965)。

结论

SUVmax、中性粒细胞-淋巴细胞比值、血小板-淋巴细胞比值、初始 TPSA 和临床 T 分期是前列腺癌患者淋巴结转移的有价值的独立预测因子,为这些患者的淋巴结分期提供了进一步优化的机会。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验