Huang Jiaguo, Sun Ji, Hua Runmiao, Fan Yi, Wang Kai, Zheng Liying, Qian Biao
Department of Urology, Affiliated Xiaoshan Hospital, Hangzhou Normal University, Hangzhou, China.
Department of Urology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Front Oncol. 2024 Feb 21;14:1268800. doi: 10.3389/fonc.2024.1268800. eCollection 2024.
This study aims to explore the predictive value of the Controlling Nutritional Status (CONUT) score for prostate cancer (PCa) diagnosis.
The data of 114 patients who underwent prostate needle biopsies from June 2020 to December 2022 were retrospectively analyzed. The relationship between CONUT score and various clinical factors as well as PCa diagnosis was evaluated.
The pathological results classified patients into the PCa (n = 38) and non-PCa (n = 76) groups. Compared with the non-PCa group, the PCa group exhibited statistically significant differences in age, prostate-specific antigen (PSA), PSA density (PSAD), the proportion of PI-RADS ≥ 3 in mpMRI, and the CONUT score, prostate volume, lymphocyte count, and total cholesterol concentration ( < 0.05). ROC curve analyses indicated the diagnostic accuracy as follows: age (AUC = 0.709), prostate volume (AUC = 0.652), PSA (AUC = 0.689), PSAD (AUC = 0.76), PI-RADS ≥ 3 in mpMRI (AUC = 0.846), and CONUT score (AUC = 0.687). When CONUT score was combined with PSA and PSAD, AUC increased to 0.784. The AUC of CONUT score combined with PSA, PSAD, and mpMRI was 0.881, indicates a higher diagnostic value. Based on the optimal cut-off value of CONUT score, compared with the low CONUT score group, the high CONUT score group has a higher positive rate of PCa diagnosis ( < 0.05).
CONUT score is an excellent auxiliary index for PCa diagnosis in addition to the commonly used PSA, PSAD, and mpMRI in clinical practice. Further prospective trials with a larger sample size are warranted to confirm the present study findings.
本研究旨在探讨控制营养状况(CONUT)评分对前列腺癌(PCa)诊断的预测价值。
回顾性分析2020年6月至2022年12月期间114例行前列腺穿刺活检患者的数据。评估CONUT评分与各种临床因素以及PCa诊断之间的关系。
病理结果将患者分为PCa组(n = 38)和非PCa组(n = 76)。与非PCa组相比,PCa组在年龄、前列腺特异性抗原(PSA)、PSA密度(PSAD)、mpMRI中PI-RADS≥3的比例、CONUT评分、前列腺体积、淋巴细胞计数和总胆固醇浓度方面存在统计学显著差异(<0.05)。ROC曲线分析显示诊断准确性如下:年龄(AUC = 0.709)、前列腺体积(AUC = 0.652)、PSA(AUC = 0.689)、PSAD(AUC = 0.76)、mpMRI中PI-RADS≥3(AUC = 0.846)和CONUT评分(AUC = 0.687)。当CONUT评分与PSA和PSAD联合时,AUC增加至0.784。CONUT评分与PSA、PSAD和mpMRI联合的AUC为0.881,表明诊断价值更高。基于CONUT评分的最佳截断值,与低CONUT评分组相比,高CONUT评分组PCa诊断的阳性率更高(<0.05)。
CONUT评分是临床实践中除常用的PSA、PSAD和mpMRI外用于PCa诊断的优秀辅助指标。需要进一步进行更大样本量的前瞻性试验以证实本研究结果。