Detection & Risk Stratification for Early Stage Prostate Cancer

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1 Detection & Risk Stratification for Early Stage Prostate Cancer Andrew J. Stephenson, MD, FRCSC, FACS Chief, Urologic Oncology Glickman Urological and Kidney Institute Cleveland Clinic

2 Risk Stratification: Prognosis Natural history proportion of men who could avoid therapy Small proportion benefit from treatment Men who die despite curative treatment Bill-Axelson et al. N Engl J Med 2005

3 Risk Stratification: Early Detection Proportion of men who do not benefit from screening and may be harmed Small proportion benefit from screening Men who die despite screening Schroder et al. N Engl J Med 2009

4 Topics Detection Prediction of Biologically indolent disease Progression on surveillance Curable cancer with treatment Clinical failure or PCSM after treatment

5 Topics Detection Prediction of Biologically indolent disease Progression on surveillance Curable cancer with treatment Clinical failure or PCSM after treatment

6 Prostate Cancer with PSA < 4 PSA (ng/ml) % Cancer % Cancers that are Biopsy Gleason 7-10 < Thompson et al. N Engl J Med 2004

7 PSA for Early Detection of Prostate Cancer Diagnosis problem PSA < 4 ng/ml: poor sensitivity No normal PSA where cancer risk is zero No clear PSA threshold for biopsy biopsy everyone? Overdetection problem PSA threshold will biopsy rate by 2-3x Over diagnosis 50% for screening at 4-yr intervals ERSPC: Over treatment NNT 50:1 PLCO: No evidence of reduction in PCSM with screening

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10 Confounders & Improvements BMI Statin use Other Biologic markers PCA3 Gene Fusions SNP s Hamilton et al. J Natl Cancer Inst 2008

11 Novel Prostate Cancer Markers PSA: prostate-specific, but not cancer-specific PCA3: prostate-specific, non-coding mrna over-expressed in prostate cancer epithelium PCA3 RNA PSA RNA Ca BPH N Prospective analysis of PCA3 in 1589 men with PSA > 2.5 or DRE+ undergoing Bx Test Sensitivity Specificity PPV* NPV* PCA3 >35 46% 81% 71% 59% PSA > 4 86% 20% 53% 58% No association with Gleason score or quantity of cancer Drewnowska et al. ASCO 2009

12 Improving PSA Specificity Cancer by Age 75 Advanced Cancer by Age 75 PSA > 1 ng/ml at age is associated with 3.7x risk of clinically-detectable prostate cancer and 7-22x risk of advanced disease (T3 and/or bone mets) by age 75 Lilja et al. Nature Rev Cancer 2008; Lilja et al. J Clin Oncol 2007; Ulmert et al. BMC Med 2008

13 Genetic risk Witte. Nat Rev Genet 2008

14 Genetic Risk Witte. Nat Rev Genet 2008

15 No SNP or combo associated with PSA, tumor grade, advanced stage Zheng et al. N Engl J Med 2008

16 Do SNPs Have Empiric Predictive Value? Base model: Age, PSA, FH 5 SNPs: 8q24,17q12, & 17q24.3 Base model: Age, Stage, Grade, PSA, FH, Rx 5 SNPs: 8q24,17q12, & 17q24.3 Prostate Cancer Risk Prostate Cancer Specific Mortality Salinas et al. Prostate 2009

17 Topics Detection Prediction of Biologically indolent disease Progression on surveillance Curable cancer with treatment Clinical failure or PCSM after treatment

18 Nomograms for Predicting Indolent Disease Kattan 2003 AUC.79 Steyerberg 2007 Screening population (Rotterdam ERSPC) AUC.76 Dong 2008 US contemporary screening population AUC.77

19 Biologic Markers of Indolent Disease PCA3 Total tumor volume <.5cc Dominant tumor volume <.5cc AUC 0.76 Nakanishi et al. J Urol 2008

20 Biologic Markers of Aggressive Disease: Gene Fusion Cumulative Incidence Ratio: 2.7 Dimichaelis et al. Oncogene 2007

21 Topics Detection Prediction of Biologically indolent disease Progression on surveillance Curable cancer with treatment Clinical failure or PCSM after treatment

22 Active Surveillance: Predictors of Progression Carter et al. J Urol 2007

23 Topics Detection Prediction of Biologically indolent disease Progression on surveillance Curable cancer with treatment Clinical failure or PCSM after treatment

24 Stephenson et al. J Natl Cancer Inst 2006;

25 Stephenson et al. J Natl Cancer Inst 2006;

26 Stephenson et al. J Natl Cancer Inst 2006;

27 Topics Detection Prediction of Biologically indolent disease Progression on surveillance Curable cancer with treatment Clinical failure or PCSM after treatment

28 Systems Pathology and Outcomes Model Outcome CI Nomogram BCR.85 Cox Clinical Failure.84 Systems Path I Clinical Failure.81 Image analysis + quantitative IHC Systems Path II Clinical Failure.85 Donovan et al. J Clin Oncol 2008; Eggener et al. Cancer 2009

29 Long-Term (15 yr) Prostate Cancer Specific Mortality after Radical Prostatectomy N = 24, 414 ( ) Modeling Cohort (N = 11,521) Cleveland Clinic, MSKCC, Baylor, Michigan Validation Cohort (N = 12, 893) Johns Hopkins 638 surviving pts with FU > 15 years 10 Stephenson et al. ASCO 2009

30 Predictors of Prostate Cancer-Specific Mortality G8-10 SVI G4+3 G3+4 G3+3 LNI EPE OC Pathological Gleason score 8-10 and seminal vesicle invasion are prime determinants of prostate cancer-specific mortality Stephenson et al. ASCO 2009

31 Predictors of Prostate Cancer-Specific Mortality G8-10 SVI G4+3 G3+4 G3+3 LNI EPE OC Little distinction between Gleason 4+3 vs. 3+4 Stephenson et al. ASCO 2009

32 Predictors of Prostate Cancer-Specific Mortality G8-10 SVI G4+3 G3+4 G3+3 LNI EPE OC Isolated extraprostatic extension similar to organ-confined cancer Stephenson et al. ASCO 2009

33 Nomogram Predicting 15-year PCSM Externally-validated concordance index: 0.92 Stephenson et al. ASCO 2009

34 Comparison of Nomograms in Oncology Zero ability to predict Need to move this way Predict Perfectly Breast (Gail) Brachytherapy: PSA Pancreatic Lung Metastatic AIPC: OS RP Preop: PSA Sarcoma Gastric Renal Cell RP Postop: PSA Radiotherapy: PSA RP Postop: PCSM PCSM can be predicted with unprecedented (and near-perfect) accuracy once the pathological features of prostate cancer are known

35 Frequently Asked Question What s the best way to treat my prostate cancer?

36 Prostate Cancer Meta-gram Treatment options Outcomes Surveillance RP IMRT Brachy Proton-beam RT Cryotherapy HIFU Complications BCR DSS OS Nguyen and Kattan. Cancer 2009

37 Individualized outcome prediction Take a gander at mah wuhmun! It s surveillance for me, Tex. Enter patient-specific variables: PSA, age, race, Gleason, # cores, etc Most favorable Least favorable Nguyen and Kattan. Cancer 2009

38 Risk Assessment Paradigms: Early Detection Past PSA cutoff PSAD, PSAV Current Continuous Risk Models Nomograms Risk Calculator New markers Future Individual Risk Assessment age 40 Genetic testing Risk of any cancer Risk of any & biologically significant cancer Risk of any & biologically significant cancer Biopsy Biopsy Prevention & Selective Biopsy

39 "What are my chances, Doc?" Prediction is very difficult, especially if it's about the future Niels Bohr

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