prognostic factors and predictive models vincenzo ficarra associate professor of urology, university...

Prognostic factors and predictive models

Vincenzo Ficarra

Associate Professor of Urology, University of Padova, ItalyScientific Director OLV Robotic Surgery Institute, Aalst, Belgium

RCC Prognostic Factors

Kidney Cancer

Localized MetastaticClinicalLaboratory? Bioptical

Surgery

PathologicalMolecular

Cytogenetic

Medical therapies

ClinicalLaboratory

RCC Oncologic Outcomes

Kidney cancerDiagnosis

Localized Local/Distant recurrence

Death

MetastaticDisease

RFS

PFS

OSCSS

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: 1023-29

Karakiewicz P., Ficarra V. et al. Eur J Cancer 2007; 43: 1023-29

Mode of presentation

Models predicting recurrence after NT:Preoperative parameters

SymptomsClinical size

SymptomsClinical size

GenderClinical sizeSymptoms

Nodes (Imaging)Necrosis (imaging)

Models predicting survival after NT:Preoperative parameters

Accuracy: 84-88% (external)

Karakiewicz P. et al. Eur Urol 2009; 55: 287-295

Preop. Karakiewicz nomogram (3364 pts)Preop. Karakiewicz nomogram (3364 pts)

Gontero P. and SATURN Project members (submitted to BJU Intern)

c index (1 year)87.8 (84.4-91.4)

c index (2 yrs)87 (84.4-89.5)

c index (5 yrs)84 (82.3-87.1)

c index (10 yrs) 85.9 (83.2-88.6)

Models predicting survival after NT:Preoperative parameters

Accuracy: 70-73% (external)

Kutikov A. et al. J Clin Oncol 2009; 28: 311-317

Pathologic Prognostic Factors

• Tumour extension (TNM)

• Tumour size

• Histologic Subtypes

• Grading

• Necrosis

• Sarcomatoid de-differentiation

• Microvascular invasion

T1 T1 7 cm7 cm

T1aT1a 4 cm 4 cm 4 cm 4 cm

T1bT1b > 4 - 7 cm > 4 - 7 cm > 4 - 7 cm > 4 - 7 cm

T2 T2 > 7 cm> 7 cm > 7 cm > 7 cm

T2aT2a > 7 - ≤ 10 cm > 7 - ≤ 10 cm

T2bT2b > 10 cm> 10 cm

TNM, 1997TNM, 1997

Evolution of the TNM staging system for organ-confined RCC

TNM, 2002TNM, 2002 TNM, 2009TNM, 2009

TNM, 2009 Version – Why ?TNM, 2009 Version – Why ?

Frank I et al. J. Urol. 2005; 173: 380-384

544 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: 588-95

5,339 patients with RCC surgically treated between 1997 and 2007

Waalkes S et al. Eur. Urol. 2011; 59: 258-263

Validation of the 2009 TNM version

T3a Fat and adrenal invasion Fat invasion or V1

T3b V1 – V2 V2

T3c V3 V3

T4 Outside Gerota’s fascia Outside 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: 588-95

5,339 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: 2439-44

Clear Cell

Papillary

Chromophobe

Oncocitoma

clear cell papillary RCC

Tubulocystic RCC Oncocytic papillary RCC

RCC with prominent leiomyomatous proliferation

Prognostic Value of Histologic Subtypes

Capitanio U. et al BJU Inter 2008: 103: 1496-1500

Prognostic Value of Histologic Subtypes

Capitanio U. et al BJU Inter 2008: 103: 1496-1500

Histologic Subtypes and definition of other histologic factors

Clear Cell Papillary Chromophobe

Nuclear grading +++ + -

Nucleolar grading

- ++ -

Coagulative necrosis

+++ + ++

Microvascular invasion

+ ? ?

Sarcomatoide de-diff.

+++ +++ +++

Fuhrman Nuclear GradingGrade 1 Grade 2

Grade 3 Grade 4

Fuhrman nuclear grading14,064 cases (clear cell RCC)

Sun M. et al Eur Urol 2009; 56: 775

Sika D et al Am J Surg Pathol. 2006 Sep;30(9):1091-6.

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: 2143-2147

A novel tumor grading scheme forChromophobe Renal Cell Carcinoma

Paner et al Am J Surg Pathol. 2010; 34: 1233-1240

Prognostic Value of Coagulative necrosis in clear cell

Sengupta S. et al Cancer 2005; 104: 511-520

Prognostic Value of Coagulative necrosis in clear cell

Klatte T. et al J Urol 2009; 181: 1558-64

Prognostic Value of Coagulative necrosis in papillary RCC

Sengupta S. et al Cancer 2005; 104: 511-520

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: 1822-34

Independent predictors of aggressive chromophobe RCC

Prognostic Value of Sarcomatoiddedifferentiation

Prognostic Value of Sarcomatoiddedifferentiation

Cheville JC et al Am J Surg Pathol 2004; 28: 435-441

Models predicting recurrence after NT:Postoperative parameters

Accuracy: 74% (internal) - 61-84% (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: 4559-4566Cindolo L., Ficarra V., et al Cancer 2005; 104: 1362-1371

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 0 - 10 or greater 1

• Nuclear Grade - Grade 1-2 0 - Grade 3 1 - Grade 4 3

• Necrosis - absent 0 - present 1

Leibovich B. et al Cancer 2003; 97: 1663-71

Stage, Size, Grade and Necrosis (SSGN) Score e RFS

Leibovich B. et al Cancer 2003; 97: 1663-71

(0-2)

(3-5)

(> 6)

Adjuvant therapy in RCC: planned trials

Trial Sponsor Treatment Primary outcome

Histologic subtypes

Stratification tools

Scheduled conclusion

ARISER Wilex Girentuximab vs Placebo

RFS, OS Clear cell pT, Grading

9/2013

ASSURE NCI/SWOK/ECOG

Sunitinib vsSorafenib vsPlacebo

RFS Clear cell & non-clear cell

pT,Grading

4/2016

S-TRAC Pfizer Sunitinib vsPlacebo

RFS Clear cell & non-clear cell

UISS 1/2012

SORCE9 Medical Research Council (UK)

Sorafenib vsPlacebo

RFS Clear cell & non-clear cell

Leibovich score

8/2012

EVEREST NCI/SWOG Everolimus vsPlacebo

RFS Clear cell & non-clear cell

pTGrading

8/2013

PROTECT GlaxoSmithKline

Pazopanib vsPlacebo

RFS Prominent clear cell

pT, Grading

10/2015

Models predicting survival after NT:Postoperative parameters

N0/M0

N+/M+

Zisman A. et al JCO 2002; 20: 4559-4566

Patard JJ, Ficarra V. et al JCO 2004; 22: 3316-3322

External validation of the UCLA Integrated Staging System

3,199 confined RCC and 1,083 metastatic RCC

C index: 0.765 – 0.863 C index: 0.584 – 0.776

Models predicting survival after NT:Postoperative parameters

Frank I et al 2002; 168: 2395-2400

• 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 0 - 5 or greater 2

• Nuclear Grade - Grade 1-2 0 - Grade 3 1 - Grade 4 3

• Necrosis - absent 0 - present 2

(SSGN) Score accuracy: 75-88% (external)

Ficarra V., Martignoni G. et al J Urol 2006; 175: 1235-1239Concordance 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: 1316-1322

Accuracy: 75-89% (external)

Molecular markers for RCC

Belldegrun As et al Eur Urol Suppl 2007; 6: 477-483

Molecular markers for RCC

Klatte T. et al Cancer Epidemiol Biomarkers 2009; 18: 894-900

concordance index 0.90

Cytogenetic nomogram for clear cell RCC

Klatte T. et al. J Clin Oncol 2009; 27: 746-753

concordance index 0.89

Motzer (MSKCC) criteria

Motzer RJ. et al. J Clin Oncol 2002; 20: 289-296

• 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: 289-296

Models predicting survival for RCC before targeted therapy era

Sun M. Ficarra V. et al. Eur Urol 2011; 60: 640-661

Motzer, 2002 Motzer, 2004 Mekhail, 2005 Escudier, 2007 Negrier, 2002

Immun Immun Immun Immun Immun

KPS KPS KPS N° sites M+ N° sites M+

LDH   LDH LDH  

Hb Hb Hb Hb  

Corrected Ca Corrected Ca Corrected Ca Corrected Ca  

Diagn-IFN   Diagn-IFN Diagn-IFN Diagn-IFN

    RT    

    N+    

    Hepatic M+   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: 48-56

Accuracy: 52-62%

Models predicting prognosis in mRCC treated with targeted therapy

Author Cases Target population Variables Accuracy (%)

Choueiri, 2007

120 NT + VEGF inhibitors

PS, Platelet, Neutrophil, cCa, time diagnosis-

treatment

NR

Motzer, 2008 375 Sunitinib PS, LDH, Hb, cCa, Lung and liver M+, prior NT,

Numb. M+, time diagnosis-treatment

63%(internal)

Heng, 2009

645 VEGF inhibitors PS, Hb, cCa, Neutrophile, Platelet,

time diagnosis-treatment

73%(internal)

Karakiewicz, 2011

628 Bevacizumab + IFN

Age, PS, albumin, alkaline phosphatase,

time diagnosis-treatment

70-75%(internal)

Manola, 2011 3,748 Targeted therapy PS, numb M+, previous IFN/IL, Hb, LDH, WBC,

ALP, cCa

71%(internal)

74%(external)

Ljungberg B. et al Eur Urol 2010; 58: 398-406

ESMO Guidelines on Renal Cell Carcinoma

Escudier B. et al Ann Oncol 2010; 21 (Suppl 5): 137-139

• 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