Cáncer renal. ¿Cómo sacar el máximo partido a...

1

Cáncer renal. ¿Cómo sacar el

máximo partido a los

diferentes fármacos

disponibles?

Noviembre de 2009

Daniel Castellano

Servicio de Oncología Médica

Hospital 12 de Octubre

Presidente SOGUG

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 and

Bevacizumab plus IFN

(USA & EU 2007)3,4

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

2012 ESMO guidelines for clear-cell mRCC: Second-line therapy

Escudier B, et al. Ann Oncol. 2012;23(Suppl 7):vii65-vii71

Setting Treatment group Standard

recommendation Level of evidence

First-line

Good or intermediate prognosis

Sunitinib

Bevacizumab + IFN-α

Pazopanib

I A

II A

II A

Poor prognosis Temsirolimus II A

Second-line

Post-TKI Axitinib

Everolimus I A

II A

Post-cytokines Axitinib

Sorafenib

Pazopanib*

Sunitinib

I A

I A

II A

III A

Third-line Post-two TKIs Everolimus II A

¿Cómo sacar el máximo partido a los

diferentes fármacos disponibles?

• Relacionados con:

– Tumor

– Paciente

– Manejo del Fármaco

– Estrategia terapéutica

Implications for Therapy and Outcome

Burrell, Mcgranahan, Bartek and Swanton Nature 2013

Intertumour Heterogeneity Intratumour Heterogeneity Intercellular Heterogeneity

• Achieving cures in metastatic disease • Cost of cancer drug development • Cancer biomarker validation

65% mutations are heterogeneous and not present in every biopsy

Ubiquitous

Shared

Primary

Shared Mets

Private

Primary Mets

Gerlinger,Rowan, Horswell, Larkin et al NEJM 2012

Branched Evolution in ccRCC

WL Tam & RA Weinberg, Nat Med. 2013

Epithelial-Mesenchymal Transition (EMT)

EMT leads to

metastasis

WL Tam & RA Weinberg, Nat Med. 2013

http://www.nature.com/nm/

Enhancing Immune Responsiveness

Types of biomarker used in cancer management

Diagnostic biomarker Definition of tumour type,

stage and grade

e.g. BRAF V600 Screening biomarker Early detection of cancer in the general or at-risk populations

e.g. PSA antigen Pre-disposition

biomarker Identification of individuals at

risk of developing cancer

e.g. BRCA mutations

Prognostic biomarker Identification of the likely clinical disease course

e.g. MSKCC score Predictive biomarker Estimation of the individual

response to a specific treatment

e.g. HER-2 Pharmacodynamic

biomarker Changes after treatment

associated with target

modulation by an agent

e.g. PK analysis

Predictive factors for targeted therapy in RCC

None (yet)

Predicting Response to Treatment Based on Molecular/Genetic Markers

Molecular Marker Expression Level Predicted Response to Treatment

CAIX1 High Good response to immunotherapy

COX-21 High Good response to immunotherapy

HIF-1/HIF-22 High Good response to sunitinib

Genetic Marker Predicted Response to Treatment

Various nsSNPs3-6 Significant sunitinib toxicity/PFS

Loss of chromosomes 4, 9, or 17p4 Non-response to interleukin-2 (IL-2)

VHL loss-of-function mutation5 Good response to VEGF therapy

nsSNPs: nonsynonymous single nucleotide polymorphisms

1. Kim HL et al. J Urol. 2005;173:1496. 2. Patel PH et al. ASCO 2008. Abstract 5008. 3. Faber PW et al. ASCO 2008. Abstract 5009. 4. Jaeger E et al. ASCO 2008. Abstract 5043.

5. Choueiri TK et al. J Urol. 2008; [Epub ahead of print]. 6. Garcia-Donas J. Lancet Oncology 2011. Estudio SUTREN (SOGUG)




– Tumor

– Paciente



1Porta C, et al. Cancer Treat Rev 2010;36:16-23.

DISEASE

Good Intermediate Poor MSKCC

≥4 1 2–3

Lymph nodes Liver Lung Bone Brain

No. met sites

Site of mets

PATIENT

Histology Age

PS Comorbidities

Non-clear cell ≥65/70 years

Wound healing

Diabetes Renal

Clear cell <65/70 years

0 1 2 3

Haematological

Fatigue Thyroid

Cardiac disease ≤grade 2 >grade 2

Cirrhosis Controlled hypertension

TREATMENT Suitable for CK

Tumour shrinkage

Naïve

Unsuitable for CK

Prolong Disease

survival stabilization

History Realistic aim

Prior treatment

Prior CK Prior targeted therapy

Maintain qualityof life

Disease-related characteristics

• Number of metastatic sites

• Specific metastatic sites (e.g., brain)

• Symptomatic vs asymptomatic disease

• Histology (i.e., clear-cell vs. non-clear-cell) • MSKCC risk group

Patient-related characteristics

• Age

• Performance Status

• Comorbidities (e.g., cardiac, renal, etc...)




– Tumor

– Paciente



Toxicity

Management

Who will develop these toxicities?

Can these toxicities be prevented?

In which settings are toxicities most relevant?

Are certain toxicities associated with response?

Can dose adjustment based on toxicity be used to optimize therapy?

Toxicity ↔ Clinical Outcome

Hypothyroidism • Median PFS higher in sunitinib treated pts (n=40) who developed hypothyroidism (10.3 v 3.6 mos; P=0.047) (Wolter et al ASCO 2008)

• Similar results in a series of 87 pts receiving sunitinib or sorafenib (Schmidinger et al Cancer 2011) Fatigue • PFS and OS improved in pts who developed fatigue in a retrospective experience including 770 pts treated with sunitinib (Donskov et al Ann Oncol 2012)

• May be related to longer drug exposure Hand-foot syndrome • Median OS improved in pts who developed HFS (38.2 v 18.9 mos; P<0.001) in 770 pts who received sunitinib (Pusanov et al ECCO 2013)

• ORR also improved (66.5% v 31.8%) Pneumonitis • In a series of 46 pts receiving mTORi’s, 30% developed pneumonitis (Dabydeen et al Eur J Cancer 2012)

• Pts developing pneumonitis had a lower rate of progressive disease as best response (14% v 56%) Hypercholesterolemia • Cholesterol changes during temsirolimus assessed in a phase III study (Lee et al CCR 2012)

• Cholesterol increase associated with longer survival (HR =0.77, P<0.0001) and PFS (HR 0.81, P<0.0001)

“Working Group Toxicidades”

Trabajo en Equipo

Apple store: formato iPhone y iPad

Google store: formato Android

Clinical biomarker in RCCs

Molecular Marker Expression Level Predicted Response to TKI-s1

Hypertension High Good response/PFS-OS

Hormonal syndrome Low Good response/PFS

H-Foot syndrome High Good response/PFS-OS

Clinical Marker Predicted Response to mTOR´s

Pneumonitis Good response/PFS

Lymphopenia PFS?

Castellano D, Gore M, Ravaud A, Schmidinger M, et al. Cancer T Reviews 2012, in press

Programa de acceso expandido de Sunitinib: Escenario “Real

Evidencia de actividad de sunitinib en 4 subgrupos

Gore ME, et al. Lancet Oncol 2009

SLP

SG

Meses

5.6

9.2

5.1 6.7

7.8

13.4

11.3

18.2

*Hubo 503 pacientes con ECOG PS ≥2 evaluables para la SG

Mets Cerebr PS≥2 No cél clara Edad ≥65

(n=320) (n=582*) (n=588) (n=1,414)

20

16

12

8

4

0

COMPARZ Study Quality of Life Result: FACIT-Fatigue

First 6 months

Pati

ents

(%

)

90 80 70 60 50 40 30 20 10 0

PISCES Study Primary endpoint: Patient preference for study

treatments (Primary analysis population) 1

100

Preferred pazopanib Preferred sunitinib No preference

90% CI (for difference): 37.0-61.5; p<0.001 70% (n=80) 22% (n=25)

8% (n=9)

1. Escudier B, et al. ASCO 2012 oral presentation;abstract 4502.

Axitinib Dose Titration

Rini BI, Gruenwald V, Fishman MN, et al: Axitinib with or without dose titration for first-line metastatic renal cell carcinoma (mRCC): Unblinded results from a randomized phase II study. ASCO Meeting Abstracts 2013;31(6_suppl):LBA349.

No grade > 2 toxicity for ≥ 2 weeks

No antihypertensive medication

• Criteria for dose titration in AXIS:

Blood pressure < 150/90 mmHg Starting dose 5 mg bid N=359 (100%)

Dose reduction <5 mg bid N=88 (25%)

No dose change 5 mg bid N=139 (39%)

Dose escalation > 5 mg bid N=132 (37%)

Titration to:

7 mg bid

N=60 (17%)

Titration to:

10 mg bid

N=71 (23%)

Dose Titration

Rini BI, Gruenwald V, Fishman MN, et al: Axitinib with or without dose titration for first-line metastatic renal cell carcinoma (mRCC): Unblinded results from a randomized phase II study. ASCO Meeting Abstracts 2013;31(6_suppl):LBA349.

Tipo Tratamiento: - Secuencial

- Individualización

Control Complicaciones

Tumorales

Tratamiento Integral

Manejo Efectos Adversos

Medicina Basada Evidencia

(Est.Clínicos) Uso Racional de

Recursos

Beneficio Clínico

Manejo Integral Multidisciplinar del Carcinoma Renal Avanzado




– Tumor

– Paciente



Selecting first-line treatment:

Key considerations for the clinician

Robust

evidence

and guidelines

Patient

characteristics Experience

Efficacy is a key factor when selecting

first-line treatment, but there are also other considerations…

Achieving a continuum of care in mRCC

• Today, targeted agents are the standard of care for mRCC and long-term care may be achieved through effective therapy management

• But what is the most effective sequencing strategy?

Long-term continuum of care in mRCC

Efficacious

first-line

agents

Efficacious

second-line

agents

Efficacious

third-line

agents

Effective therapy management

INCREASE IN SURVIVAL … >24~36 months

No. en riesgo

Sunitinib: 375 240 156 54 10 1

IFN-α: 375 124 46 15 4 0

Sunitinib : Estudio fase III como tratamiento de primera línea en el CCR avanzado

Sunitinib

50 mg diario (Esquema 4/2)

N=375

IFN-α

3 MU SC, TIW primera semana,

6 MU SC, TIW segunda semana,

9 MU SC, TIW a partir de entonces

N=375

Criterios de elegibilidad

≥18 años de edad

CCRm

Histología de células claras

Sin tratamiento sistémico previo

Enfermedad medible por RECIST

ECOG PS 0 o 1

Función orgánica adecuada

N=750

ALEATOR I ZAC I ÓN

Motzer RJ, et al. N Engl J Med 2007

Motzer RJ, et al. ASCO 2007; Motzer RJ, et al. J Clin Oncol 2009

0 5 10 15 20 25 30

Tiempo (meses)

HR=0.538

(95% IC 0.439–0.658)

P<0.000001

Sunitinib Mediana: 11.0 meses (95% IC: 10.7–13.4)

IFN-α Mediana: 5.1 meses (95% IC: 3.9–5.6)

1.0

0.8

0.6

0.4

0.2

0

Pro

babili

dad d

e S

LP

Mediana de SG Mediana de la SLP (revisión central

independiente)

Pro

babili

ty o

f surv

ival

HR=0.821

(95% IC: 0.673–1.001)

P=0.051 (log-rank)

Sunitinib (n=375)

Mediana: 26.4 meses

(95% IC: 23.0–32.9)

IFN-α (n=375)

Mediana: 21.8 meses

(95% IC: 17.9–26.9)

Total deaths

Sunitinib 190

IFN-α 200

0 3 6 9 12 15 18 21 24 27 30 33 36

1.0

0.8

0.6

0.4

0.2

0

nMuertes/nRiesgo

Sunitinib 375 44/326 38/283 48/229 42/180 14/61 4/2

IFN-α 375 61/295 46/242 52/187 25/149 15/53 1/1

Tiempo (meses)

RECIST = Response Evaluation Criteria in Solid Tumors; ECOG = Eastern Cooperative Oncology Group; SLP = supervivencia libre de

progresión; SG = supervivencia global

N MedianPFS(95%CI)

Pazopanib 557 8.4mo(8.3,10.9)

Sunitinib 553 9.5mo(8.3,11.1)

HR(95%CI)=1.047(0.898,1.220)

COMPARZ Study Primary Endpoint: Progression-free Survival

(independent review)

Pazopanib

Sunitinib

The challenge of treatment in mRCC

• Benefits of tyrosine kinase inhibitors (TKIs) are

well established; however, there are limitations

– There are few complete responses

– Initial partial responses are followed by progression

– In other cases there is no objective benefit

• Drug resistance remains an ongoing obstacle to

successful treatment of mRCC

– Limits the success of therapy and reduces survival

rates

Motzer RJ, et al. J Clin Oncol 2009; Rini B, et al. J Clin Oncol 2010; Escudier B, et al. J Clin Oncol 2010; Escudier B, et al. N Engl J Med 2007; Hudes G, N Engl J Med 2007

Patterns of tumor progression on

VEGF or VEGFR inhibitors

Change i

n T

um

or

Measu

rem

ents

(%

)

Change i

n T

um

or

Measu

rem

ents

(%

)

Change i

n T

um

or

Measu

rem

ents

(%

)

Primary refractory Early progressors Late progressors

Group A Group B Group C

Two strategies for second-line treatment after progression on a TKI

1. Switch to an mTOR inhibitor (change mode of action)

TKI-mTOR-TKI

2. Switch to another TKI (continue VEGF inhibition)

TKI-TKI-mTOR

40

Everolimus + BSC (n=272)

Placebo + BSC (n=138)

Si hay progresión

A L E A T O R I Z A C I Ó

NN

2:1

• CCR metastático de células

claras

• 1 o 2 regímenes previos de

VEGFR-TKI

1er Análisis interino 2º Análisis interino Análisis final =

N=416

Motzer RJ, et al. Lancet. 2008; Escudier B, et al. ESMO 2008; Motzer RJ, et al. ASCO GU 2009

RECORD-1: Resultados (I)

SLP (todos los pacientes)

1.0

0.8

0.6

0.4

0.2

0

Pro

po

rció

n s

in

pro

gre

sió

n

Tiempo meses

0 2 4 6 8 10 12 14

Pacientes en riesgo

Everolimus 277 192 115 51 26 10 1 0

Placebo 139 47 15 6 2 0 0 0

Mediana de SLP (meses) Everolimus: 4.90 Placebo: 1.87 HR=0.33 (95% IC: 0.25–0.43) Log-rank P=<0.001

Everolimus Placebo

SG (todos los pacientes)

1.0

0.8

0.6

0.4

0.2

0 0 2 4 6 8 10 12 14 16 18 20 22 24

Pacientes en riesgo

Everolimus 227 267 240 204 164 155 131 101 61 30 6 0 0

Placebo 139 131 117 100 88 74 56 43 27 13 3 0 0

Mediana SG (meses) Everolimus: 14.78 Placebo: 14.39 HR=0.87 (95% IC: 0.65–1.17) Log-rank P=<0.001 Everolimus Placebo

Pro

po

rció

n s

in

pro

gre

sió

n

Tiempo meses

BSC = mejor tratamiento de soporte

41

RECORD-1: Resultados clave1,2

Criterios de elegibilidad

CCRm de células claras

Enfermedad progresiva en los 6 meses de de tratamiento con sunitinib, sorafenib o ambos

Permitido el tratamiento previo con Bevacizumab y citokinas

A L E A T O R I Z A C I Ó N

n=416

Everolimus 10 mg OD + BSC

Placebo + BSC

1.Motzer RJ, et al. Lancet 2008;372:449–56;

2.Motzer RJ, et al. Cancer 2010;18:4256–65.

Everolimus

+ BSC

Placebo

+ BSC

Post sunitinib Post sorafenib

Everolimus Placebo Everolimus Placebo

SLP (meses)2 4,9 1,9 3,9 1,8 5,9 2,8

ORR2 1.8% 0% - - - -

SG2 14,8 meses 14,4 meses - - - -

2:1

n=139

n=277

42

RECORD-1: Es realmente representativo de 2ª línea?

• La mayoría de los pacientes RECORD-1 son de 3ª línea

1.Zustovich F et al. Crit Rev Oncol Hematol 2011;doi:10.1016/j.critrevonc.2011.08.008;

2.Motzer RJ, et al. Cancer 2010;18:4256–65.

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

Two strategies for second-line treatment after progression on a TKI

1. Switch to an mTOR inhibitor (change mode of action)

TKI-mTOR-TKI

2. Switch to another TKI (continue VEGF inhibition)

TKI-TKI-mTOR

Treat until PD,

unmanageable AE,

or withdrawal of

consent

Axitinib* 5 mg BID (n = 361)

Primary endpoint: PFS (independent review committee [IRC])

Secondary endpoints: OS, ORR (RECIST), duration of response, safety, QoL

Patients with clear-cell mRCC, refractory to 1

previous first-line therapy (N = 723)

Sorafenib 400 mg BID

(n = 362)

Stratified by previous regimen, ECOG PS (0 vs 1)

*Starting dose 5 mg BID with option for dose titration to 10 mg BID.

Rini BI, et al. Lancet. 2011;378:1931-1939.

Phase III AXIS Study : Axitinib vs Sorafenib as Second-line Therapy for mRCC

Axitinib se asoció con tasas de respuesta significativamente

superiores a sorafenib

Mejor tasa de respuesta % Axitinib Sorafenib

Respuesta Parcial*

Estabilización de la enfermedad

Progresión de la enfermedad

Indeterminado

19.4

49.9

21.6

6.1

9.4

54.4

21.0

11.6

Risk ratio (95% CI) 2.1 (1.4–3.0)

*Axitinib vs. sorafenib: P = 0.0001

Rini B, et al. ASCO 2011

Axitinib prolonga significativamente la PFS versus

sorafenib

PFS según regimen anterior

Prior Treatment Regimen Axitinib

(n=361)

Sorafenib

(n=362) HR P value*

Cytokines (n=251)

IRC

Investigator

12.1

12.0

6.5

8.3

0.464

0.636

<0.0001

0.005

Sunitinib (n=389)

IRC

Investigator

4.8

6.5

3.4

4.5

0.741

0.636

0.011

0.0002

Temsirolimus (n=24)

IRC

Investigator

10.1

2.6

5.3

5.7

0.511

1.210

0.142

0.634

Bevacizumab (n=59)

IRC

Investigator

4.2

6.5

4.7

4.5

1.147

0.753

0.637

0.213

*One-sided log-rank test stratified by ECOG PS

Rini B, et al. ASCO 2011

Eficacia de axitinib se mantiene independientemente de PFS

anterior a sunitinib

TKI-TKI–mTOR

(n=152)

TKI–mTOR–TKI

(n=95) p value

Mediana PFS

36.5 meses

(95% CI,30.5–42.6)

29.3 meses

(95% CI, 23.6–34.9)

Not

significant

p= 0.059

Mediana SG 50.7 meses

(95% CI, 40.6–60.8)

37.8 meses

(95% CI, 34.2– 41.5)

significant

p = 0.004

El uso de dos TKIs seguidos de un inbidor de mTOR incrementó la

probabilidad de supervivencia comparado con el uso alternatvo de un

TKI y un inhibidor de mTOR (HR: 1.52, 95% CI, 1.09–2.12; p = 0.013)

Secuencia TKI–TKI–mTOR obtiene mejores resultados que

la secuencia TKI–mTOR–TKI ??

R. Iacovelli et al. European Journal of Cancer 2013;49(9):2134-2142

STUDY N ORR, % Median PFS, mo

Median OS, mo

Temsirolimus vs Sorafenib1

512 8% vs 8% 4.3 vs 3.9 12.3 vs 16.6

Everolimus vs placebo2 56 1.8% vs 0% 4.6 vs 1.8 NA (14.8 vs 14.4)

Axitinib vs Sorafenib3 389 19% vs 9% 4.8 vs 3.4 15.2 vs 16.5

Results of current second-line trials (Sunitinib pretreated only)

Numerally longest OS rates have been

Reported with Tki

1. Hutson et al abstract LBA22_PR ESMO 2012; 2. Motzer RJ et al. Cancer 2010; 3. Motzer et al abstract 793 PD ESMO 2012

Third-line therapy

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

Second-line treatment of mRCC: Phase III level of evidence

Sunitinib Pazopanib

1st-line 2nd-line (mPFS)

Axitinib (AXIS)

Everolimus (RECORD-1)

Sorafenib (AXIS/INTORSECT/SWITCH)

Temsirolimus (INTORSECT)

4.8 m

4.6 m

3.4 / 3.9 / 2.8 m

4.3 m

Placebo (RECORD-1) 1.9 m

3rd-line

Everolimus? Dovitinib? Sorafenib? Pazopanib?

Sunitinib Rechallenge? Nivolumab?

57

Cáncer renal. ¿Cómo sacar el

máximo partido a los

diferentes fármacos

disponibles?

Noviembre de 2009

Cáncer renal. ¿Cómo sacar el máximo partido a...

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