Guo R, Cai L, Fan Y, Jin J, Zhou L, Zhang K
Department of Urology, Peking University First Hospital and Institute of Urology, National Research Center for Genitourinary Oncology, Beijing, China.
Prostate Cancer Prostatic Dis. 2015 Sep;18(3):221-8. doi: 10.1038/pcan.2015.20. Epub 2015 May 19.
Active surveillance (AS) is an increasingly important attempt to avoid overtreatment of patients who harbor clinically insignificant disease while offering curative treatment to those in whom disease is reclassified as higher risk after an observation period and repeat biopsy. We aim to evaluate the diagnostic performance of magnetic resonance imaging (MRI) in predicting upgrading on confirmatory biopsy in men with low-risk prostate cancer (PCa) on AS.
We searched the PubMed for pertinent studies up to November 2014. We used standard methods recommended for meta-analyses of diagnostic test evaluations. The analysis was based on a summary receiver operating characteristic (SROC) curve. Meta-regression analysis was used to assess the effects of some confounding factors on the results of the meta-analysis. The potential presence of publication bias was tested using the Deeks' funnel plots.
Seven studies provided the diagnostic data on MRI and AS of PCa, comprising 1028 patients. The pooled estimates of MRI on disease reclassification among AS candidates were as follows: sensitivity, 0.69 (95% confidence interval (CI), 0.44-0.86); specificity, 0.78 (95% CI, 0.53-0.91); positive likelihood ratio, 3.1 (95% CI, 1.6-6.0); negative likelihood ratio, 0.40 (95% CI, 0.23-0.70); and diagnostic odds ratio, 8 (95% CI, 4-16). The P-value for heterogeneity was <0.001. We found that the SROC curve is positioned toward the desirable upper left corner of the curve, and the area under the curve was 0.79 (95% CI, 0.76-0.83). For a pretest probability of 0.20, the corresponding positive predictive value (PPV) was 0.44 and the negative predictive value (NPV) was 0.91. MRI may reveal an unrecognized significant lesion in 33.27% of patients, and biopsy of these areas reclassified 14.59% of cases as no longer fulfilling the criteria for AS. In addition, when no suspicious disease progression (66.34%) was identified on MRI, the chance of reclassification on repeat biopsy was extremely low at 6.13%.
MRI, especially multiparametric (MP)-MRI, has a moderate diagnostic accuracy as a significant predictor of disease reclassification among AS candidates. The high NPV and specificity for the prediction of biopsy reclassification upon clinical follow-up suggest that negative prostate MRI findings may support a patient remaining under AS. Although the PPV and sensitivity for the prediction were relatively low, the presence of a suspicious lesion >10 mm lesion may suggest an increased risk for disease progression.
主动监测（AS）是一项日益重要的尝试，旨在避免对患有临床意义不显著疾病的患者进行过度治疗，同时为那些在观察期和重复活检后疾病被重新分类为高风险的患者提供根治性治疗。我们旨在评估磁共振成像（MRI）在预测接受AS的低风险前列腺癌（PCa）男性患者确诊活检时疾病升级方面的诊断性能。
我们检索了截至2014年11月的PubMed上的相关研究。我们使用了推荐用于诊断试验评估的荟萃分析的标准方法。分析基于汇总的受试者工作特征（SROC）曲线。荟萃回归分析用于评估一些混杂因素对荟萃分析结果的影响。使用Deeks漏斗图检验潜在的发表偏倚。
七项研究提供了关于PCa的MRI和AS的诊断数据，包括1028例患者。MRI对AS候选者疾病重新分类的汇总估计如下：敏感性为0.69（95%置信区间（CI），0.44 - 0.86）；特异性为0.78（95%CI，0.53 - 0.91）；阳性似然比为3.1（95%CI，1.6 - 6.0）；阴性似然比为0.40（95%CI，0.23 - 0.70）；诊断比值比为8（95%CI，4 - 16）。异质性的P值<0.001。我们发现SROC曲线位于曲线理想的左上角，曲线下面积为0.79（95%CI, 0.76 - 0.83）。对于0.20的验前概率，相应的阳性预测值（PPV）为0.44，阴性预测值（NPV）为0.91。MRI可能在33.27%的患者中发现未被识别的显著病变，对这些区域进行活检后，14.59%的病例被重新分类为不再符合AS标准。此外，当MRI未发现可疑疾病进展（66.34%）时，重复活检时重新分类的可能性极低，为6.13%。
MRI，尤其是多参数（MP）-MRI，作为AS候选者中疾病重新分类的重要预测指标，具有中等诊断准确性。对临床随访时活检重新分类预测的高NPV和特异性表明，前列腺MRI阴性结果可能支持患者继续接受AS。尽管预测的PPV和敏感性相对较低，但存在>10毫米的可疑病变可能提示疾病进展风险增加。
