Selective detection of histologically aggressive prostate cancer: an Early Detection Research Network Prediction model to reduce unnecessary prostate biopsies with validation in the Prostate Cancer Prevention Trial.

Abstact

Limited survival benefit and excess treatment because of prostate-specific antigen (PSA) screening in randomized trials suggests a need for more restricted selection of prostate biopsy candidates by discerning risk of histologically aggressive versus indolent cancer before biopsy.

Subjects undergoing first prostate biopsy enrolled in a multicenter, prospective cohort of the National Cancer Institute Early Detection Research Network (N = 635) were analyzed to develop a model for predicting histologically aggressive prostate cancers. The control arm of the Prostate Cancer Prevention Trial (N = 3833) was used to validate the generalization of the predictive model.

The Early Detection Research Network cohort was comprised of men among whom 57% had no cancer, 14% had indolent cancer, and 29% had aggressive cancer. Age, body mass index, family history of prostate cancer, abnormal digital rectal examination (DRE), and PSA density (PSAD) were associated with aggressive cancer (all P < .001). The Early Detection Research Network model outperformed PSA alone in predicting aggressive cancer (area under the curve [AUC] = 0.81 vs 0.71, P < .01). Model validation in the Prostate Cancer Prevention Trial cohort accurately identified men at low (<10%) risk of aggressive cancer for whom biopsy could be averted (AUC = 0.78; 95% confidence interval, 0.75-0.80). Under criteria from the Early Detection Research Network model, prostate biopsy can be restricted to men with PSAD >0.1 ng/mL/cc or abnormal DRE. When PSAD is <0.1 ng/mL/cc, family history or obesity can identify biopsy candidates.

A predictive model incorporating age, family history, obesity, PSAD, and DRE elucidates criteria whereby ¼ of prostate biopsies can be averted while retaining high sensitivity in detecting aggressive prostate cancer.

Authors
  • Ankerst DP
  • Regan MM
  • Rubin MA
  • Salami S
  • Sanda MG
  • Thompson IM
  • Wei JT
  • Williams SB
PubMed ID
Appears In
Cancer, 2012, 118 (10)