title: Magnetic resonance imaging on disease reclassification among active surveillance candidates with low-risk prostate cancer: a diagnostic meta-analysis.
abstract: BACKGROUND
  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.
  
  
  METHODS
  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.
  
  
  RESULTS
  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%.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Department of Urology, Peking University First Hospital and Institute of Urology, National Research Center for Genitourinary Oncology, Beijing, China.
authors.forename: R
authors.identifier: 0000000170266937
authors.initials: R
authors.lastname: Guo
authors.affiliation: Department of Urology, Peking University First Hospital and Institute of Urology, National Research Center for Genitourinary Oncology, Beijing, China.
authors.forename: L
authors.initials: L
authors.lastname: Cai
authors.affiliation: Department of Urology, Peking University First Hospital and Institute of Urology, National Research Center for Genitourinary Oncology, Beijing, China.
authors.forename: Y
authors.initials: Y
authors.lastname: Fan
authors.affiliation: Department of Urology, Peking University First Hospital and Institute of Urology, National Research Center for Genitourinary Oncology, Beijing, China.
authors.forename: J
authors.initials: J
authors.lastname: Jin
authors.affiliation: Department of Urology, Peking University First Hospital and Institute of Urology, National Research Center for Genitourinary Oncology, Beijing, China.
authors.forename: L
authors.initials: L
authors.lastname: Zhou
authors.affiliation: Department of Urology, Peking University First Hospital and Institute of Urology, National Research Center for Genitourinary Oncology, Beijing, China.
authors.forename: K
authors.initials: K
authors.lastname: Zhang
mesh_terms: D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D011159:Population Surveillance; D011471:Prostatic Neoplasms / Q000175:diagnosis* / Q000453:epidemiology; D017594:Publication Bias; D012372:ROC Curve; D015203:Reproducibility of Results