EPIDEMIOLOGIA Y FACTORES DE RIESGO
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EPIDEMIOLOGIA Y FACTORES DE EPIDEMIOLOGIA Y FACTORES DE RIESGORIESGO
CANCER DE RICANCER DE RIÑONÑON
Prof. Dr. L. M. Antón AparicioProf. Dr. L. M. Antón AparicioC.H.U. A CoruñaC.H.U. A Coruña
EPIDEMIOLOGYEPIDEMIOLOGYDEMOGRAPHIC ASPECTS• Incidence• Age / race• International incidence
PROGNOSTIC FACTORS• Anatomic factors• Histologic factors• Clinical factors• Molecular markers
RISK FACTORS• General• Gigarette smoking• Obesity / Dietary factors• Hypertension / Drug• Hormonal• Occupation• Transplantation / Dialysis
PREDICTOR MODELS• Concept• Objective• Historical - perspective
DEMOGRAPHIC ASPECTSDEMOGRAPHIC ASPECTS• Accounts for 2% all new cares worldwide• Twice as common men vs women• Mean age at diagnosis early 60s• Incidence rates rising each year EU & USA
↑ incidental finding improved imaging technology↑ incidence of late-stage has been observed↓ autopsies
• Incidence rates age/race adjunted white (m/w) black (m/w). 13.8/6.6 16.8/8.0
• International rate ↑ variability ↑ role for exogemous risk• Internacional incidence (Figure)
2002 RCC World Incidence and Mortality Rates, Stratified by Region
Renal cancer incidence
0 1 2 3 4 5 6 7 8 9 10
Western AfricaMiddle Africa
South Central AsiaMelanesia
East AfricaMicronesia
Northern AfricaSoutheastern Asia
PolynesiaEastern Asia
Southern AfricaCaribbean
Western AsiaSouth America
Central AmericaSouthern EuropeNorthern Europe
Central and Eastern EuropeWestern Europe
Australia/New ZealandNorthern America
Wo
rld
Reg
ion
s
Rates per 100,000
Renal cancer mortality
Ries LAG, et al. SEER Cancer Statistics Review, 1975-2002.
RISK FACTORSRISK FACTORS (I)(I)• GENERAL - Sporadic vs familial forms (two to fourfold)
- Different types of genetic predispositions- Case – Control / Cohort studies (Table I & II)
• CIGARETTE SMOKING- Meta-analysis (m vs w) smokers
1.5 1.2 relative risk 2.0 1.6 increased risk
• OBESITY- ↑ 1.07 per unit /body mass relative risk- Mechanism unknown
- Hormonal change steroid hormonal IGF-I
- Lipid peroxidation DNA adducts
• HYPERTENSION- Hypertension ranging 1.3 to 2 relative risk- Mechanism unknown
- renal injury
RISK FACTORSRISK FACTORS (II)(II)• ANALGESIC / DIURETICS / ANTI-HYPERTENSIVES
- Phenacetin containing drug ??- ASS derivates ??- Hydrochlorothiazide / Furosemide ??
• DIETARY FACTORS- Protein / alcohol consumption ¿?- Fruit / vegetable consumption protective effects
• HORMONAL / REPRODUCTIVE FACTORS- Oral contraception ¿reduced risk?- Hysterectomy / ophorectomy in consistent- Menarche / menopause not affect risk
• OCCUPATION- Jobs / industries asbestos ¡!
petroleum works ¿?solvent trichloro ethylene ??
• TRANSPLANTION / DIALISIS- Duration of dialysis increased risk- Mechanism of action acquired renal cystic disease
PROGNOSTIC FACTORS (I)PROGNOSTIC FACTORS (I)• ANATOMIC FACTORS • Tumor size
• Tumor extesion/ adrenal involvement
• Venous involvement
• Lymph node involvement
• Metastasis
• HISTOLOGIC FACTORS • Tumor grade (TNM)
• Histologic morphology
• Tumor necrosis
• Microvascular invasion
• Sarcomatoid features
• CLINICAL FACTORS • Performance status
• Laboratory abnormalitis
• Paraneoplastic syndrome
• Thrombocytosis
• MOLECULAR MARKERS • Angiogenesis
• Proliferation
• Apoptosis
• Others
PROGNOSTIC FACTORS PROGNOSTIC FACTORS (II)(II)
• ANATOMIC FACTORS
• Tumor size 5-year cancer-specific survival (rate)
T1
T2
T3
Range
Range
Range
91% to 60%
74% to 71%
67% to 37%
(T1a T1b)
(T2a T2b)
(T3a T3b)
• Tumor extensión
• Adrenal involvement 5-year cancer-specific survival (rate)
Similar to T4
• Venous involvement
RV
IVC
IVC
3-year cancer-specific survival (rate)
70%
63% (below diaphragma)
23% (above diaphragma)
• Lymph node
N+ Range
2-year cancer-specific survival (rate)
10% to 20%
PROGNOSTIC FACTORS (III)PROGNOSTIC FACTORS (III)HISTOLOGIC FACTORS
• Histologic morphology 5-year cancer-specific survivalMain subtypes Clear cell 70%-80% 68%
Papillary 10% 15% (type 2 more aggressive) 87.4%Chromophobe 5% 86.9%Collecting duct 1% (Medullary Ca. Poor prognosis)
• Tumor necrosisIncidence Clear cell 28% Papillary 47% Chromophobe 20%Independent predictor of survival (twice the risk of death)Indipendent predictor of poor out come (clear cell risk ratio 1.95)
• Microvascular invasionIndicence 25% to 28%Independent predictor of disease recurrenceIndependent predictor of cancer-specific survival
• Sarcomatoid fraturesFound in less than 5%High – grade forms of RCCAssociated with a poor outcome
PROGNOSTIC FACTORS (IV)PROGNOSTIC FACTORS (IV)CLINICAL FACTOR
• Performance status 5-year cancer-specific survivalECOG-PS 0 81%ECOG-PS ≥1 51%
Independend prognostic factor of survival in mRCC Independent predictor of poor outcome
• Paraneoplastic syndromeCachexia – related findings: anorexia, malaise, weight lossOverall incidence 14-8%Independent predictor of both poor prognosis and / or outcomeSignificantly affect recurrence free survival, cancer-specific survival
• Laboratory abnomalities- Thrombocytosis / Anemia- Serum Calcium- Serum lactate dehydrogenase- Hypoalbuminemia
MOLECULAR PROGNOSTIC FACTORSMOLECULAR PROGNOSTIC FACTORS
Hypoxia inducibleCAIXCAXIICXCR4VEGFILGF-1
Proliferationki-67
Cell cycle regulationP53Bcl-2PTENCyclin AP27
Cell adhesionEpCAMEMAE-cadherina-CateninCadherin-6
MiscellaneousGelsolin
VimentinCA125CD44Androgen receptorsCaveolin-1VEGFR
MOLECULAR MARKERS MOLECULAR MARKERS (I)(I)
MOLECULAR MARKERSMOLECULAR MARKERS (II)(II)
HIPOXIA INDUCIBLE FACTORS↑ HIF-1α expression: an independent predictor of survival (Clear cell)
↓ CA Ix expression: an independent prognostic indicator poor survival (m RCC)
an predictor with response to IL-2
VHL alterations: an independent predictor of cancer-free survival
an independent predictor of disease-free survival
VEGF
VEGF-A / VEGF-2: higher expression (papillary) / lower expression (clear)
VEGF-A, VEGFR-1, VEGFR-2:
(↑ epithelium)
independent predictor lymp node involvemt
independent predictor disease-free survival
VEGFR-3
(↓ low endothelial)
independent predictor lymph node involvement
independent predictor disease-free survival
MOLECULAR MARKERS (III)MOLECULAR MARKERS (III)REGULATOR APOPTOSIS
p53 • Tumor-suppressor gene
incidence range 16% to 57%
↑ papillary, metastatic
overexpression: independent predictor poor survival
independent prognostic disease progression (clear)
indipendent predictor disease recurrence
BCl-2 • Survival protein
incidence range 10% to 80%
Expression: significant correlation higher tumor grade
correlated with improved overall survival
associated with lower stage & grade
not predict disease-free or disease-specific survival
not correlated with recurrence & metastasis
Smac/DIABLO • caspase family proteins
incidence: lower
+ expression: inversely correlated with tumor grade
- expression: worse cancer-specific survival
MOLECULAR MARKERS (III)MOLECULAR MARKERS (III)REGULATOR CELL CYCLE
p27
↓ expression
• regulated proliferation G1/s transition
Cyclin-dependent kinases
Higher-grade & large tumor size
Independent predictor poor disease & specific survival
PTEN • Tumor – suppressor protein
PI3K – AKT – mTOR signaling pathway
+ Expression:
↓ Expression:
Loss expression:
Found to correlate with pAKT & HIF-1α expression
Independent predictor poor survival (m clear RCC)
Increased in all RCC
↓ loss: Clear cell RCC & sarcomatoid features
pAKT:
SGK:
Collecting duct (89%)
Sarcomatoid (61%)
High-grade 73%
High-stage 50%
Clear cell (58%)
Clear cell (41%)
31%
30%
ADHESION MOLECULES
EpCAM
Eph A2
Frequently absent (clear cell RCC)
Independent predictor improved disease- specific survival
Associated larger tumor size
Predictor decrease-free recurrence & overall survival
P53 is an independent predictor of tumor recurrence and P53 is an independent predictor of tumor recurrence and progression after nephrectomy in patients with localized renal progression after nephrectomy in patients with localized renal
cell carcinomacell carcinoma
193 localized RCC
TMA: CA9, CA12, gelsolin, p53 EpCAM and pTEN
15% tumor recurrence
Univariate analysis: T stage, grade, ECOG, Ki67, EpCAM and p53 were significantly associated with recurrence (p<0.05)
Multivariate analysis: T stage, ECOG, and p53 were the 3 most significant predictors of tumor recurrence
RR: 37.7%
RR: 14.4%
Shvarts, O, Seligson D, Lam J et al. J Urol; 2005: 725-728
Kim, H. L. et al. Clin Cancer Res 2004;10:5464-5471
Using protein expression to predict Using protein expression to predict survival in RCCsurvival in RCC
318 RCC patients
TMA: Ki67, p53, gelsolin, CA9, CA12, PTEN, EpCAM and vimentin
CA9
PTEN
CA12
EpCAM
Ki-67
P53
Vimentin
gelsolin
WORSE
SURVIVAL
Kim, H. L. et al. Clin Cancer Res 2004;10:5464-5471
A prognostic model based on a combination of clinical and A prognostic model based on a combination of clinical and molecular predictorsmolecular predictors
Multivariate analysis: p53, CA9, vimentin were statistically significant predictors of survival independent of the clinical variables metastasis status, T stage, ECOG and grade.
Prognostic systems based on protein expression profiles for clear cell RCC performed better than standard clinical predictors
INTEGRATED PREDICTION MODELSINTEGRATED PREDICTION MODELSConcept: Integration of independent prognostic indicators into
comprehensive out come models
Objetive: To facilitate patient counselingTo identify patients who might benefit from therapy
Historical perspective1986 Maldazys JD J Urol 136:376-3791988 Elson PJ Cancer Res 48: 7310-73132001 Kattan MW J Urol 166: 63-67
UISS 2001 Zisman A J Clin Oncol 10: 1649-1657(UCLA)2002 Zisman A J Clin Oncol 20: 4559-4560
SSIGN 2002 Frank I J Urol 168: 2395-2400(Mayo Clinic)
MSKCC 2004 Motzer RJ J Clin Oncol 22: 454-463(Memorial)2005 Mekhail TM J Clin Oncol 23: 832-841(Cleveland
Clinic)
Types Preoperative models: Yayciogly and CindoloPostoperative models: Kattan momogram
Risk Groups for Advanced RCCRisk Groups for Advanced RCC
Risk GroupsNo. of Risk
Factors
2-Year Survival Rate,
%Favorable Risk 0 45
Intermediate Risk 1-2 17
High Risk ≥ 3 3
Motzer RJ, et al. J Clin Oncol. 1999;17:2530-2540.
Pretreatment features associated with shorter survivalLow Karnofsky performance status (< 80%)
High lactate dehydrogenase level (> 1.5 x normal)
Low hemoglobin level
High serum calcium
Absence of nephrectomy
Motzer, R. J. et al. J Clin Oncol; 17:2530 1999
Survival stratified according to risk groupSurvival stratified according to risk group
MS: 20m
MS: 10mMS: 4m
Copyright © American Society of Clinical Oncology
Zisman, A. et al. J Clin Oncol; 19:1649-1657 2001
Fig 3. Kaplan-Meier survival analysis of the study population according to the UISS categories
Comprehensive staging systems for Comprehensive staging systems for localized and metastatic RCClocalized and metastatic RCC
KattanKattan(localized)(localized)
FrankFrank(localized)(localized)
(SSIGN)(SSIGN)
ZismanZisman(localized (localized
and metastatic)and metastatic)
(UISS)(UISS)Tumor subtypes All Clear cell All
Prognostic indicators
TNM, size, histology, symptons
TNM, size, grade, necrosis
TNM, grade, ECOG
Prognostic information
recurrence survival survival
Comparison of Predictive Accuracy of Four PrognosticComparison of Predictive Accuracy of Four PrognosticModels for Nonmetastatic Renal Cell Carcinoma afterModels for Nonmetastatic Renal Cell Carcinoma after
NephrectomyNephrectomy
Cindolo L, Patard JJ, Chiodini et al. Cancer 2005; 1362-1371
2404 patients
Kattan and UISS postoperative models
Cindolo and Yaycioglu preoperative models
KATTAN MODEL WAS THE MOST KATTAN MODEL WAS THE MOST ACCURATE IN PREDICTING ACCURATE IN PREDICTING
PROGNOSISPROGNOSIS
Factores pronóstico desfavorables Factores pronóstico desfavorables dependientes del paciente de uso comúndependientes del paciente de uso común
Presentación con síntomas de enfermedadPérdida de peso (>10% de masa corporal)ECOG2-3Reactantes de fase agudao VSG > 30o Proteína C Reactiva elevada
Anemiao Hb< 10g/dl en mujero Hb< 12 g/dl en varón
HipercalcemiaFosfatasa alcalina elevadaHipoalbuminemiaTrombocitosis
Factores pronóstico desfavorables Factores pronóstico desfavorables dependientes del paciente no consolidadosdependientes del paciente no consolidados
• Edad
• Sexo
• Raza
• Localización geográfica
• Nivel socioeconómico
Factores pronóstico desfavorables Factores pronóstico desfavorables dependientes del tumor de uso comúndependientes del tumor de uso común
Macroscópicos Afectación de márgenes quirúrgicos
Metástasis Presencia de múltiples metástasis Afectación hepática o pulmonar Presencia de trombo en sistema venoso
Microscópicos TNM (factor pronóstico más importante descrito) Grado nuclear necrosis
Tipo histológico Células claras convencional Carcinoma de conductos colectores Sarcomatoide
Morfología nuclear: área aumentada y formas variables Contenido en DNA: aneuploidía Marcadores de proliferación
Ki-67 elevada Ag-NOR (proteínas nucleolares argirófilas) elevado
Factores pronóstico desfavorables Factores pronóstico desfavorables dependientes del tumor no consolidadosdependientes del tumor no consolidados
• Fase S elevada
• PCNA elevado
• P-53, bcl2, p21
• Factores de crecimiento
• Moléculas de adhesión celular
• Angiogénesis
CONCLUSIONCONCLUSIONThe last decade has lead to the gradual transition from the use of solitary clinical factors as prognostic markers to the introduction of systems that integrate molecular and genetic markers.
These markers will eventually enhance our ability to predict individual tumor behavior and stratify patients into more sophisticated risk categories.
They also can select patients for targeted biological therapies and transform the management of this malignancy in the near future.