algoritmo terapÉutico en cÁncer renal · algoritmo terapÉutico en cÁncer renal dra. cristina...

ALGORITMO

TERAPÉUTICO EN

CÁNCER RENAL

Dra. Cristina Suárez

Hospital Universitari Vall d´Hebron

Vall d´Hebron Institute of Oncology (VHIO)

• Introducción

• Tratamiento de primera línea en carcinoma renal de

células claras (RCC)

• Pronóstico bueno e intermedio

• Mal pronóstico

• Tratamiento de segunda línea en RCC

• TKI vs mTOR

• Tratamiento de tercera línea en RCC

• Otras consideraciones

• Valoración radiológica

• Nefrectomía en M1 de debut

• Conclusiones

Introducción

El carcinoma renal metastásico (mRCC) es un tumor

resistente a los tratamientos clásicos

Tradicionalmente las terapias sistémicas contra el mRCC

estaban basadas en citoquinas (IL-2 e IFN-α)

Avances en el conocimiento de la biología molecular del

RCC han cristalizado en terapias efectivas basadas en

dianas moleculares específicas

The increasingly challenging

field of mRCC

Early 1940s:

experiments with

cytotoxic

chemotherapy1

Early 1980s: IFN-α and high-dose IL-2

used for RCC treatment

High-dose IL-2 approved in the USA

(1995). High treatment-related

toxicity; small number of durable

responses2

Sorafenib (USA 2005, EU 2006)3,4

Temsirolimus (USA & EU 2007)3,4

Bevacizumab plus IFN

(USA 2009 & EU 2007)

Everolimus

(USA & EU 2009)3,4

Pazopanib

(USA 2009, EU 2010)3,4

Sunitinib (USA & EU 2006)3,4

Axitinib (USA & EU 2012)

Tivozanib,

Dovitinib

1. Abeloff MD, et al. Clinical Oncology 4th ed. Philadelphia, PA; 2. Coppin C, et al. Cochrane

Database Syst Rev 2005;1:CD001425; 3. U.S. Food and Drug Administration

(www.accessdata.fda.gov); 4. European Medicines Agency (http://www.ema.europa.eu/).

http://www.accessdata.fda.gov

The increasingly challenging

field of mRCC

Early 1940s:

experiments with

cytotoxic

chemotherapy1

Early 1980s: IFN-α and high-dose IL-2

used for RCC treatment

High-dose IL-2 approved in the USA

(1995). High treatment-related

toxicity; small number of durable

responses2

Sorafenib (USA 2005, EU 2006)3,4

Temsirolimus (USA & EU 2007)3,4

Bevacizumab plus IFN

(USA 2009 & EU 2007)

Everolimus

(USA & EU 2009)3,4

Pazopanib

(USA 2009, EU 2010)3,4

Sunitinib (USA & EU 2006)3,4

Axitinib (USA & EU 2012)

Tivozanib,

Dovitinib Cabozantinib/

Nivolumab

.....

1. Abeloff MD, et al. Clinical Oncology 4th ed. Philadelphia, PA; 2. Coppin C, et al. Cochrane

Database Syst Rev 2005;1:CD001425; 3. U.S. Food and Drug Administration

(www.accessdata.fda.gov); 4. European Medicines Agency (http://www.ema.europa.eu/).

http://www.accessdata.fda.gov

RCC is not one disease

Clear cell

75%

Type

Incidence (%)

Associated mutations VHL

Papillary type 1

5%

MET

Papillary type 2

10%

FH

Chromophobe

5%

BHD

Oncocytoma

5%

BHD

Proximal Nephron Distal Nephron

BHD = Birt-Hogg-Dubé; FH = fumarate hydratase; MET = mesenchymal epithelial transition factor;

VHL = von Hippel-Lindau.

Pfaffenroth EC and Linehan WM. Expert Opin Biol Ther. 2008;8:779–790.

mRCC prognosis MSKCC risk factor model:

Cytokine era

Median overall survival (OS)

0 risk factors (favorable risk): 30 months (n=164)

1 or 2 risk factors (intermediate risk): 14 months (n=348)

3, 4, or 5 risk factors (poor risk): 5 months (n=144)

Years following systemic therapy

Su

rviv

al, %

100

80

60

40

20

0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

MSKCC Criteria 20022,3

KPS <80%

Time from diagnosis to

first treatment <12 months

Hemoglobin <LLN

LDH >1.5 x ULN

Corrected serum calcium >10.0 mg/dL

Greater number of risk factors* = worse prognosis1

*Risk factors: <1 year from nephrectomy, KPS <80, low HGB, high corrected calcium, high LDH. HGB = hemoglobin. 1. Motzer RJ, et al. J Clin Oncol. 1999;17:2530–2540;

2. Motzer RJ, et al. J Clin Oncol. 2002;20:289–296; 3. Motzer RJ, et al. J Clin Oncol. 2004;22:454–463.

• Introducción

• Tratamiento de primera línea en carcinoma renal

de células claras (RCC)


• Mal pronóstico


• TKI vs mTOR





• Conclusiones

¿Qué nos recomiendan

las guías?

• Introducción




• Mal pronóstico


• TKI vs mTOR





• Conclusiones

Estudios fase III en primera línea en

pacientes de pronóstico bueno e

intermedio

BEVACIZUMAB

SUNITINIB

PAZOPANIB

Características comunes de los pacientes

incluidos en los estudios fase III con

bevacizumab/sunitinib/pazopanib

Carcinoma renal metastásico de células claras

No más de 2 factores de mal pronóstico (90-95%)

Nefrectomizados (~90%)

Treatment naïve

Estudios fase III en primera línea en

pacientes de pronóstico bueno e

intermedio

BEVACIZUMAB

SUNITINIB

PAZOPANIB

Matching placebo (n=145) Pazopanib 800 mg

once daily (n=290)

Patients with advanced/

metastatic RCC

(N=435)

Randomization 2:1

Phase III study Pazopanib in first line RCC

Stratification

• ECOG performance

status

0 versus 1

• Prior nephrectomy

• Treatment-naïve

(n=233) versus one

cytokine failure (n=202)

1. Sternberg et al. J Clin Oncol 2010;28:1061-1068

Option to receive pazopanib

via an open-label study at

progression

Sunitinib vs Pazopanib

COMPARZ: COMParing the efficacy, sAfety and

toleRability of paZopanib vs. sunitinib

Sunitinib

50 mg once daily

4 weeks on/2 weeks off,

n=553

Pazopanib 800 mg once daily

continuous dosing,

n=557

Randomised 1:1

(n=1110)

Asian sub study

n=183†

+

Key eligibility • Advanced RCC,

clear-cell histology

• No prior systemic

therapy

• Measurable disease

• KPS ≥70

• Adequate organ function

HRQoL

assessments

Original global study

n=927*

• Stratification factors:

• Karnofsky 70/80 vs. 90/100

• Prior nephrectomy (yes vs. no)

• Baseline lactate dehydrogenase (>1.5 vs. ≤1.5 x upper limit of normal)

HRQoL: Health-related quality of life 1. Motzer RJ, et al. N Engl J Med 2013; 369:722-731.

*NCT00720941 † NCT01147822

COMPARZ PFS independent review

N Median PFS, Mos

(95% CI)

Pazopanib 557 8.4 (8.3–10.9)

Sunitinib 553 9.5 (8.3–11.1)

HR: 1.05 (95% CI: 0.9–1.22)

Pts at risk, n

557

553

361

351

245

249

136

147

105

111

61

69

46

48

19

18

13

10

1

3

Pazopanib

Sunitinib

1.0

0.8

0.6

0.4

0.2

0

Pro

po

rtio

n o

f P

ts P

rog

ress

ion

-Fre

e

0 4 8 12 16 20 24 28 32 36 40 Months

Motzer RJ, et al. N Engl J Med. 2013;369:722–731.

1. Motzer RJ, et al N Engl J Med 2013; 369:722-731

OS

HR (95% CI ): 0.91 (0.76-1.08)

Lower

95% CI

Median

months

Upper

95% CI

Pazopanib 26.2 28.4 35.6

Sunitinib 25.3 29.3 32.5

Total number of events: 502 (out of 650 required)

OS data are not yet mature

Analysis of overall survival

• Introducción




• Mal pronóstico


• TKI vs mTOR





• Conclusiones

Criterios de Eligibilidad

● Histologically confirmed,

measurable (RECIST)

advanced (stage IV or

recurrent) RCC

● No prior systemic therapy

● Karnofsky PS ≥60

● Fasting serum cholesterol

≤350 mg/dL, triglycerides

≤400 mg/dL

● Minimum of 3 poor-risk

features required*

(n=207) R

A

N

D

O

M

I

S

A

T

I

O

N

(n=209)

(n=210)

IFN

Escalación de dosis

18 MU s.c. t.i.w.

Temsirolimus

25 mg/m2 i.v. q.w.

+

Temsirolimus

15 mg/m2

i.v. q.w.

IFN

6 MU

s.c. t.i.w.

Objetivo primario: Supervivencia Global

(N=626)

*Factores de riesgo

● LDH >1.5× ULN

● Hgb < LLN

● Corrected calcium >10 mg/dL

● Time from diagnosis to first treatment <1 year

● Karnofsky PS 60−70

● Multiple organ sites of metastasis Hudes G, et al. N Engl J Med 2007

Pivotal Phase III study of temsirolimus

first-line in mRCC

Baseline Characteristics Subgroups (ITT

Patient Population)

IFN Temsirolimus IFN +

Temsirolimus Total

ITT Population 207 209 210 626

Subgroups by Protocol-defined Prognostic Factors:

>3 of 6 Factors, n(%) 196 (95%) 195 (93%) 198 (94%) 589 (94%)

<3 of 6 Factors 11 (5%) 14 (7%) 12 (6%) 37 (6%)

TOTAL 207 209 210 626 (100%)

Hudes et al. N Engl J Med. 2007;356:2271-2281.

Temsirolimus: Incremento de supervivencia global

del 49% vs IFN-a en pacientes de mal pronóstico

1.00

0.75

0.50

0.25

0

Supervivencia Global Supervivencia Libre de

Progresión

Months

IFN-a + temsirolimus

Temsirolimus

IFN-a

Pro

ba

bili

ty o

f su

rviv

al

0 5 10 15 20 25 30 35

Mediana SG

Temsirolimus: 10.9 meses

IFN-a: 7.3 meses

Temsirolimus + IFN-a: 8.4 meses

0

0.25

0.50

0.75

1.00

0 5 10 15 20 25 30 Months

Pro

po

rtio

n p

rogre

ssio

n-f

ree

Temsirolimus

IFN-a + temsirolimus

IFN-a

Medians SLP

Temsirolimus: 5.5 meses

IFN-a: 3.1 meses

Temsirolimus + IFN-a: 4.7 meses

Hazard ratios

Temsirolimus vs IFN-a: 0.73 (95% CI: 0.58–0.92); P=0.008

Temsirolimus + IFN-a vs IFN-a: 0.96 (95% CI: 0.76–1.20); P=0.70

1. Motzer RJ, et al. J Clin Oncol. 2009;27:3584–3590; 2. Escudier B, et al. J Clin Oncol. 2009;27(Suppl 15S):5020 (Abstract);

3. Rini B, et al. J Clin Oncol. 2009;27(Suppl 15S):LBA5019 (Abstract); 4. Sternberg C, et al. J Clin Oncol. 2010;28:1061–1068;

5. NICE final appraisal determination 2010; 6. Hudes G, et al. N Engl J Med. 2007;356:2271–2281;

7. Motzer RJ et al. N Engl J Med. 2013;369:722–731-.

First-line treatment landscape

Study N ORR (%) Median PFS (months)

Final Median OS (months)

Phase III

Sunitinib vs. IFN-α1 750 31 vs. 12 11 vs. 5 p<0.001

26.4 vs. 21.8 p=0.051

Bev + IFN-α vs. IFN-α2 649 31 vs. 12 10.4 vs. 5.5

p<.001

23.3 vs. 21.3

p=0.1291

Bev + IFN-α vs. IFN-α3 732 25.5 vs. 13.1 8.4 vs. 4.9 p<0.0001

18.3 vs. 17.4 p=0.069

Pazopanib vs. placebo4 233 32 vs. 3 11.1 vs. 2.8

p<0.0000001

22.9 vs. 23.55

p=0.525

Temsirolimus vs. IFN-α6

626 8.6 vs. 4.8 5.5 vs. 3.1

p<0.001

10.9 vs. 7.3

p=0.0069

Pazopanib vs. sunitinib7

1110 31 vs. 25 8.4 vs. 9.5

Non-inferior

28.4 vs. 29.3

Non-inferior

• Introducción




• Mal pronóstico


• TKI vs mTOR





• Conclusiones

SEGUNDA LÍNEA EN RCC

• Cambio de mecanismo de acción

mTOR (Everolimus): RECORD

• Seguir inhibiendo la vía VEGF TKI

(Axitinib): AXIS

• mTOR vs TKI (INTORSECT)

PFS Prolonged Following 1

vs 2 prior TKIs





(Axitinib): AXIS


Preclinical and clinical

data support

persistance VEGF

reliance in this setting

Change mechanism of action after failure of

initial VEGF TKI presumes that RCC changes

from reliant on VEGF to reliant on mTOR at

progression

Progression-free Survival (IRC Assessment)

1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0

Subjects at risk, n

Axitinib

Sorafenib

0 2 4 6

361 256 202 145 362 224 157 100

mPFS, mo 95% CI Axitinib 6.7 6.3-8.6

Sorafenib 4.7 4.6-5.6

P<0.0001 (log-rank)

Stratified HR 0.665

(95% CI 0.544-0.812)

8 10 12 14 16 18 20

Time (months)

96 64 38 20 10 1 0 51 28 12 6 3 1 0

IRC = Independent Review Committee 12

AXIS - OVERALL SURVIVAL Patients with previous sunitinib

Motzer RJ, et al. Ann Oncol 2012;23(Suppl 9): Abstract 793PD (ESMO 2012)

Overall Survival in Patients Previously Treated with Sunitinib

Motzer RJ, et al. Ann Oncol. 2012:23(Suppl 9): Abstract 793PD.

P = .4902,

Survival Time, Months





(Axitinib): AXIS


Response to First and Second VEGF-Targeted Therapies

Response to first-line (%)

Response to second-line (%)

CR/PR SD PD

CR/PR (n = 72) 14 36 50

SD (n = 175) 10 50 40

PD (n = 76) 11 34 55

Al-Marrawi et al. ASCO 2011 [Abstract a4555]

• Retrospective data from the International

mRCC Database Consortium: among

464 patients, response to second VEGF

targeted therapy was not associated with

response to first agent

– Even among those who progressed

on first TKI, ~45% achieve benefit

(CR, PR or SD) on the second (table)

• No correlation between first PFS and second

PFS: Pearson correlation coefficient 0.025,

P = 0.59 (graph)

• Median OS from start of first-line therapy:

26.5 months

• Even patients who fail to respond to a

first VEGF-targeted agent may benefit

from a second

¿Y si empezamos con un

inhibidor de mTOR?

• Introducción




• Mal pronóstico


• TKI vs mTOR





• Conclusiones

75

Model Structure

1st line

PFS

Progres

s

Die*

Treatment naive mRCC patients With good or intermediate prognosis

2nd line

PFS

Progres

s

Die*

1st line therapy 2nd line therapy 3rd-5th line

3rd-5th

line

PFS

Progres

s

Die*

*Mortality in first-line is simulated by applying an age-related background mortality – in subsequent therapy lines the mRCC

related

morality was applied based on pivotal trial evidence,

Phase III study of third-line treatment with

dovitinib in patients with mRCC

Primary endpoints: PFS

Secondary endpoints: OS, ORR, safety, patient-reported outcomes

Eligibility

mRCC with clear-cell component

One prior

VEGF-targeted

therapy and one

prior mTOR

inhibitor therapy

Karnofsky PS ≥70%

Sorafenib

400 mg

twice daily

Dovitinib

500 mg/day

5 days on/2 days off

R

A

N

D

O

M

I

Z

A

T

I

O

N

N=564

www.clinicaltrials.gov (NCT01223027)

Progression-free survival (central)

100

80

60

40

20

0

0 3 6 9 12 15 18 21

Months

Pro

bab

ilit

y (

%)

even

t-fr

ee

284 148 41 20 3 1 1 0 Dovitinib

286 152 42 12 2 1 0 0 Sorafenib

n/N Median, months

(95% CI)

Hazard ratio

(95% CI)

Dovitinib 209/284 3.7 (3.5-3.9) 0.86 (0.72-1.04)

p=0.063a Sorafenib 231/286 3.6 (3.5-3.7)

Patients at risk

a1-sided based on

stratified log-rank test

Motzer RJ. ESMO 2013; Abstract E17-7035

RECORD-1: Provides evidence for third- or

subsequent line treatment

In RECORD 1, almost 80% of patients were treated with

everolimus third-line or later1,2

First- line

Second- line

Third- line

Fourth-line

n=82

n=104

n=141

n=89

First- line

Second- line

Third- line

First- line

Second- line

First- line

79%

21%

mTOR fifth-line

mTOR fourth-

line

mTOR third- line

mTOR second-

line

1. Zustovich F, et al. Crit Rev Oncol Hematol. 2012;

2. Motzer RJ, et al. Cancer. 2010

RECORD-1: Everolimus is an effective third-line

option in patients treated with prior sunitinib

and sorafenib

Calvo E, et al. Eur J Cancer. 2012;48:333–339

n Everolimus median PFS

Placebo median PFS

HR (95% CI)

1 prior VEGFR-TKI 308 5.4 1.9 0.32 (0.24–0.43)

p<0.001

2 prior VEGFR-TKIs 108 4.0 1.8 0.32 (0.19–0.54)

p<0.001

Another option is to re-challenge with a drug used earlier

Sunitinib rechallenge: Effect of treatment

between 1st and 2nd sunitinib treatment

Characteristic (n=23) N (%)

Median (range) time between first sunitinib

and rechallenge (months)

6.7 (1.3–22)

Treatment received between first sunitinib and rechallenge

VEGF inhibitor(s)

mTOR inhibitor

Both VEGF inhibitor and mTOR inhibitor

Other systemic therapy

Radiotherapy

Surgery

6 (26%)

3 (13%)

6 (26%)

4 (17%)

4 (17%)

2 (9%)

Starting dose for initial / rechallenge (mg)

50 / 50

50 / 37.5

50 / 25

37.5 / 50

10 (43%)

9 (39%)

2 (9%)

2 (9%)

Rini B, et al. ASCO-GU 2010; Abstract 319

Recommended dose of sunitinib is 50 mg/day 4/2

• Introducción




• Mal pronóstico


• TKI vs mTOR





• Conclusiones

EVALUACIÓN RADIOLÓGICA EN mRCC

Leon L et al. Target Oncol 2013

• Introducción




• Mal pronóstico


• TKI vs mTOR





• Conclusiones

Nefrectomía Citorreductiva en CRm+

Flanigan RC et al. J Urol. 2004;171:1071.

• Mediana de

SG; 13.6 vs

7.8 meses

con IFN-a

solo

• Reducción

de riesgo

relativo de

muerte en un

31%

(p = 0.002)

EAU y NCCN Guidelines; recomiendan

Nefrectomía Citorreductora (NE = 1B)

previa a tto sistémico con citokinas

ESTUDIOS EN MARCHA SOBRE EL PAPEL

DE LA NEFRECTOMÍA EN EIV DE DEBUT

• Introducción




• Mal pronóstico


• TKI vs mTOR





• Conclusiones

Bueno/Intermedio Malo PRONÓSTICO:

1ª LÍNEA: Sunitinib Pazopanib Bevacizumab

+ IFN Temsirolimus

2ª LÍNEA: Axitinib

(Sorafenib) Everolimus

3ª LÍNEA: Everolimus Sorafenib

Sunitinib

Sorafenib

ALGORITMO TERAPÉUTICO EN

CÁNCER RENAL

Bueno/Intermedio Malo PRONÓSTICO:

1ª LÍNEA: Sunitinib Pazopanib Bevacizumab

+ IFN Temsirolimus

2ª LÍNEA: Axitinib

(Sorafenib) Everolimus

3ª LÍNEA: Everolimus Sorafenib

Sunitinib

Sorafenib

ALGORITMO TERAPÉUTICO EN

CÁNCER RENAL

Debemos buscar factores

predictivos que nos

permitan seleccionar a los

pacientes

Choose any agent you want…

But use it well

Chris Ryan, ASCO 2010

MUCHAS GRACIAS…..

algoritmo terapÉutico en cÁncer renal · algoritmo terapÉutico en cÁncer renal dra. cristina...

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