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Serum lipid profiles: novel biomarkers predicting advanced prostate cancer in patients receiving radical prostatectomy

机译:血清脂质谱:预测接受前列腺癌根治术患者晚期前列腺癌的新型生物标志物

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摘要

This study aimed to evaluate the role of serum lipid profiles as novel biomarkers in predicting pathological characteristics of prostate cancer (PCa). We retrospectively analyzed 322 consecutive patients with clinically localized PCa receiving radical prostatectomy (RP) and extended pelvic lymphadenectomy. Unconditional logistic regression was used to estimate the prostatectomy Gleason score (pGS), pathological stage and lymph node involvement (LNI) in RP specimens. Preoperative prostate-specific antigen (PSA) levels, biopsy GS (bGS), and preoperative tumor, node, metastasis staging were used as basic variables to predict postoperative pathological characteristics. Preoperative serum lipid profiles were introduced as potential predictors. A receiver operating characteristic (ROC) curve was used to determine predictive efficacy. Significant differences in pathological characteristics were observed among patients with normal and abnormal total cholesterol (TC), triglyceride (TG), and low-density lipoprotein (LDL) levels, with the exception of pGS in the TG group. Multivariable regression analysis revealed that the odds ratio for high levels of TC for LNI compared with normal TC levels was 6.386 (95% confidence interval [CI] 1.510–27.010), 3.270 (95% CI: 1.470–7.278) for high levels of TG for pT3–4 disease, and 2.670 (95% CI: 1.134–6.287) for high levels of LDL for pGS. The area under the ROC curve of the models with dyslipidemia was larger than that in models without dyslipidemia, in predicting pathological characteristics. Abnormal TC, TG, and LDL levels are significantly associated with postoperative pathological status in PCa patients. Together with preoperative PSA levels, bGS, and clinical stage, dyslipidemia is more accurate in predicting pathological characteristics.
机译:这项研究旨在评估血清脂质谱作为新型生物标志物在预测前列腺癌(PCa)病理特征中的作用。我们回顾性分析了322例连续接受临床局限性PCa的患者,他们接受了根治性前列腺切除术(RP)和骨盆淋巴结清扫术。使用无条件逻辑回归来评估RP标本中的前列腺切除术格里森评分(pGS),病理分期和淋巴结受累(LNI)。术前前列腺特异性抗原(PSA)水平,活检GS(bGS)以及术前肿瘤,淋巴结转移,转移分期均用作预测术后病理特征的基本变量。术前血清脂质分布被介绍为潜在的预测指标。接受者操作特征(ROC)曲线用于确定预测疗效。在总胆固醇(TC),甘油三酸酯(TG)和低密度脂蛋白(LDL)水平正常和异常的患者中观察到病理特征的显着差异,TG组中pGS除外。多变量回归分析显示,与正常TC水平相比,LNI高TC水平的优势比为6.386(95%置信区间[CI] 1.510–27.010),3.25%(95%CI:1.470–7.278)对于pT3-4疾病,pGS高水平LDL为2.670(95%CI:1.134-6.287)。在预测病理特征时,血脂异常模型的ROC曲线下的面积大于无血脂异常模型的ROC曲线下的面积。 TC,TG和LDL异常与PCa患者的术后病理状态显着相关。结合术前PSA水平,bGS和临床分期,血脂异常可以更准确地预测病理特征。

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