Prognostic factors and predictive models Vincenzo Ficarra Associate Professor of Urology, University of Padova, Italy Scientific Director OLV Robotic Surgery Institute, Aalst, Belgium

RCC Prognostic Factors Kidney Cancer LocalizedMetastatic Clinical Laboratory ? Bioptical Surgery Pathological Molecular Cytogenetic Medical therapies Clinical Laboratory

RCC Oncologic Outcomes Kidney cancer Diagnosis Localized Local/Distant recurrence Death Metastatic Disease RFS PFS OS CSS PFS

Postoperative counseling Postoperative surveillance protocols Definition of selection criteria for ongoing adjuvant trials Role of Integrated staging systems in non-metastatic RCC

Clinical Prognostic Factors Age Gender Performance Status Mode of presentation (Symptoms) Clinical tumour size Clinical staging (cTNM)

Performance Status ECOG Karakiewicz P., Ficarra V. et al. Eur J Cancer 2007; 43:

Mode of presentation

Models predicting recurrence after NT: Preoperative parameters Symptoms Clinical size Symptoms Clinical size Gender Clinical size Symptoms Nodes (Imaging) Necrosis (imaging)

Models predicting survival after NT: Preoperative parameters Accuracy: 84-88% (external) Karakiewicz P. et al. Eur Urol 2009; 55:

Preop. Karakiewicz nomogram (3364 pts) Gontero P. and SATURN Project members (submitted to BJU Intern) c index (1 year) 87.8 ( ) c index (2 yrs) 87 ( ) c index (5 yrs) 84 ( ) c index (10 yrs) 85.9 ( )

Models predicting survival after NT: Preoperative parameters Accuracy: 70-73% (external) Kutikov A. et al. J Clin Oncol 2009; 28:

Pathologic Prognostic Factors Tumour extension (TNM) Tumour size Histologic Subtypes Grading Necrosis Sarcomatoid de-differentiation Microvascular invasion

T1  7 cm T1  7 cm T1a  4 cm  4 cm T1a  4 cm  4 cm T1b > cm > cm T1b > cm > cm T2 > 7 cm > 7 cm T2 > 7 cm > 7 cm T2a > 7 - ≤ 10 cm T2b > 10 cm TNM, 1997 Evolution of the TNM staging system for organ-confined RCC TNM, 2002 TNM, 2009

TNM, 2009 Version – Why ? Frank I et al. J. Urol. 2005; 173: patients with unilateral, sporadic pT2 RCC treated with radical nephrectomy or nephron sparing surgery between 1970 and 2000

Validation of the 2009 TNM version Novara G et al. Eur Urol 2010; 58: ,339 patients with RCC surgically treated between 1997 and 2007

Waalkes S et al. Eur. Urol. 2011; 59: Validation of the 2009 TNM version

T3aFat and adrenal invasion Fat invasion or V1 T3b V1 – V2V2 T3c V3V3 T4Outside Gerota’s fasciaOutside Gerota’s fascia and adrenal invasion TNM, 2002 Development of the TNM staging system for locally advanced RCC TNM, 2009

Validation of the 2009 TNM version Novara G et al. Eur Urol 2010; 58: ,339 patients with RCC surgically treated between 1997 and 2007

Redefining pT3 RCC: Fat invasion + Venous involvement V1 V2 V1+fat inv V2+fat inv V1-2+adrenal inv

Redefining pT3 RCC: Fat invasion + Venous involvement Margulis V. et al. Cancer 2007; 109:

Clear Cell Papillary Chromophobe Oncocitoma

clear cell papillary RCC Tubulocystic RCCOncocytic papillary RCC RCC with prominent leiomyomatous proliferation

Prognostic Value of Histologic Subtypes Capitanio U. et al BJU Inter 2008: 103:

Prognostic Value of Histologic Subtypes Capitanio U. et al BJU Inter 2008: 103:

Histologic Subtypes and definition of other histologic factors Clear CellPapillaryChromophobe Nuclear grading++++- Nucleolar grading -++- Coagulative necrosis Microvascular invasion +?? Sarcomatoide de-diff. +++

Fuhrman Nuclear Grading Grade 1Grade 2 Grade 3 Grade 4

Fuhrman nuclear grading 14,064 cases (clear cell RCC) Sun M. et al Eur Urol 2009; 56: 775

Sika D et al Am J Surg Pathol Sep;30(9): Nucleolar Grade but not Fuhrman Grade Is applicable to Papillary RCC

Fuhrman nuclear grading in papillary RCC Nucleolar grading Nuclear grading Klatte T et al J Urol. 2010; 183:

A novel tumor grading scheme for Chromophobe Renal Cell Carcinoma Paner et al Am J Surg Pathol. 2010; 34:

Prognostic Value of Coagulative necrosis in clear cell Sengupta S. et al Cancer 2005; 104:

Prognostic Value of Coagulative necrosis in clear cell Klatte T. et al J Urol 2009; 181:

Prognostic Value of Coagulative necrosis in papillary RCC Sengupta S. et al Cancer 2005; 104:

Prognostic Value of Coagulative necrosis in papillary RCC Klatte T. et al Clin Cancer Res 2009; 15: 1162

Prognostic Value of Coagulative necrosis in chromophobe RCC Amin MB et al Am J Clin Surg Pathol 2008; 32: Independent predictors of aggressive chromophobe RCC

Prognostic Value of Sarcomatoid dedifferentiation

Cheville JC et al Am J Surg Pathol 2004; 28:

Models predicting recurrence after NT: Postoperative parameters Accuracy: 74% (internal) % (external) Kattan M. et al J Urol 2001; 166: 63-67

Models predicting recurrence after NT: Postoperative parameters Accuracy: 75-81% (external) Zisman A. et al JCO 2002; 20: Cindolo L., Ficarra V., et al Cancer 2005; 104:

Models predicting recurrence after NT: Postoperative parameters Accuracy: 82% (internal) – 78-79% (external) Sorbellini M. et al J Urol 2005; 173: 48-51

Models predicting recurrence after NT: Postoperative parameters Accuracy: 84% (internal) – 80% (external) T stage (TNM, 2002) Score - pT1a 0 - pT1b 2 - pT2 3 - pT3-4 4 N stage - pNx-pN0 0 - pN1-2 2 Tumor Size Score - less than 10 cm or greater 1 Nuclear Grade - Grade Grade Grade 4 3 Necrosis - absent 0 - present 1 Leibovich B. et al Cancer 2003; 97:

Stage, Size, Grade and Necrosis (SSGN) Score e RFS Leibovich B. et al Cancer 2003; 97: (0-2) (3-5) (> 6)

Adjuvant therapy in RCC: planned trials TrialSponsorTreatmentPrimary outcome Histologic subtypes Stratification tools Scheduled conclusion ARISERWilexGirentuximab vs Placebo RFS, OSClear cellpT, Grading 9/2013 ASSURENCI/SWOK/ ECOG Sunitinib vs Sorafenib vs Placebo RFSClear cell & non-clear cell pT, Grading 4/2016 S-TRACPfizerSunitinib vs Placebo RFSClear cell & non-clear cell UISS1/2012 SORCE 9 Medical Research Council (UK) Sorafenib vs Placebo RFSClear cell & non-clear cell Leibovich score 8/2012 EVERESTNCI/SWOGEverolimus vs Placebo RFSClear cell & non-clear cell pT Grading 8/2013 PROTECTGlaxo SmithKline Pazopanib vs Placebo RFSProminent clear cell pT, Grading 10/2015

Models predicting survival after NT: Postoperative parameters N0/M0 N+/M+ Zisman A. et al JCO 2002; 20:

Patard JJ, Ficarra V. et al JCO 2004; 22: External validation of the UCLA Integrated Staging System 3,199 confined RCC and 1,083 metastatic RCC C index: – 0.863C index: – 0.776

Models predicting survival after NT: Postoperative parameters Frank I et al 2002; 168: T stage (TNM, 1997) Score - pT1 0 - pT2 1 - pT3a-b-c 2 - pT4 0 N stage - pNx-pN0 0 - pN1-2 2 M stage - M0 0 - M1 4 Tumor Size Score - less than 5 cm or greater 2 Nuclear Grade - Grade Grade Grade 4 3 Necrosis - absent 0 - present 2 (SSGN) Score accuracy: 75-88% (external)

Ficarra V., Martignoni G. et al J Urol 2006; 175: Concordance index: 0.88 External validation of the SSIGN Score (slides revision)

Models predicting survival after NT: Postoperative parameters Karakiewicz P., Ficarra V. et al JCO 2007; 25: Accuracy: 75-89% (external)

Molecular markers for RCC Belldegrun As et al Eur Urol Suppl 2007; 6:

Molecular markers for RCC Klatte T. et al Cancer Epidemiol Biomarkers 2009; 18: concordance index 0.90

Cytogenetic nomogram for clear cell RCC Klatte T. et al. J Clin Oncol 2009; 27: concordance index 0.89

Motzer (MSKCC) criteria Motzer RJ. et al. J Clin Oncol 2002; 20: Serum calcium >10 mg/dl Hemoglobin less than sex-specific limits LDH more than 1.5x normal Karnofsky performance status Interval from initial RCC diagnosis to treatment

Motzer (MSKCC) criteria Motzer RJ. et al. J Clin Oncol 2002; 20:

Models predicting survival for RCC before targeted therapy era Sun M. Ficarra V. et al. Eur Urol 2011; 60: Motzer, 2002Motzer, 2004Mekhail, 2005Escudier, 2007Negrier, 2002 Immun KPS N° sites M+ LDH Hb Corrected Ca Diagn-IFN RT N+ Hepatic M+ Lung M+ Neutrophil count

External validation of Motzer criteria in patients treated with Bevacizumab + IFN Karakiewicz P. et al. Eur Urol 2011; 60: Accuracy: 52-62%

Models predicting prognosis in mRCC treated with targeted therapy AuthorCasesTarget populationVariablesAccuracy (%) Choueiri, NT + VEGF inhibitors PS, Platelet, Neutrophil, cCa, time diagnosis- treatment NR Motzer, SunitinibPS, LDH, Hb, cCa, Lung and liver M+, prior NT, Numb. M+, time diagnosis-treatment 63% (internal) Heng, VEGF inhibitorsPS, Hb, cCa, Neutrophile, Platelet, time diagnosis-treatment 73% (internal) Karakiewicz, Bevacizumab + IFN Age, PS, albumin, alkaline phosphatase, time diagnosis-treatment 70-75% (internal) Manola, 20113,748Targeted therapyPS, numb M+, previous IFN/IL, Hb, LDH, WBC, ALP, cCa 71% (internal) 74% (external)

Ljungberg B. et al Eur Urol 2010; 58:

ESMO Guidelines on Renal Cell Carcinoma Escudier B. et al Ann Oncol 2010; 21 (Suppl 5):

Predictive models based on traditional clinical or pathological parameters significantly improve the prognostic accuracy These models can be used to select patients suitable for adjuvant protocols, plan the more appropriate follow-up, and perform careful patient counselling. Take home messages

Motzer criteria were formally validated only in patients treated with bevacizumab + IFN and their accuracy resulted very low New predictive models generated in the targeted therapy era must be further evaluated and tested Take home messages