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L’innovazione in

oncologia e le nuove frontiere della lotta al

cancro

Carmine Pinto

Presidente Nazionale AIOM

I Corso Nazionale AIOM

Giornalisti Medico-Scientifici e Oncologi Medici

Parma, 18-19 Giugno 2015

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1971 un anno importante………

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Bailar and Smith, NEJM 1986

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Innovazione e sopravvivenza

De Vita e Rosenberg, NEJM 2012

2010 Immunotherapy

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Key Investments to Launch the Precision Medicine Initiative:

Complementing robust investments to broadly support research, development, and innovation, the President’s 2016 Budget will provide a $215 million investment for the National Institutes of Health (NIH), together with the Food and Drug Administration (FDA), and the Office of the National Coordinator for Health Information Technology (ONC) to support this effort, including:

$130 million to NIH for development of a voluntary national research cohort of a million or more volunteers to propel our understanding of health and disease and set the foundation for a new way of doing research through engaged participants and open, responsible data sharing.

$70 million to the National Cancer Institute (NCI), part of NIH, to scale up efforts to identify genomic drivers in cancer and apply that knowledge in the development of more effective approaches to cancer treatment.

$10 million to FDA to acquire additional expertise and advance the development of high quality, curated databases to support the regulatory structure needed to advance innovation in precision medicine and protect public health.

$5 million to ONC to support the development of interoperability standards and requirements that address privacy and enable secure exchange of data across systems.

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Innovazione in Oncologia

 Innovazione nei cambiamenti

 Innovazione nelle cure

 Innovazione nella sostenibilità

(10)

Cambiamenti e innovazione in Oncologia

 Cambiano la popolazione ed i pazienti

 Cambiano l’idea e le prospettive di “cura”

 Cambiano le modalità e l’accesso all’informazione

 Cambiano le risorse e l’idea di sostenibilità

 Cambiano le richieste dei “guariti” da tumore

(11)

Multimorbidità in pazienti con carcinoma del colon-retto

Van Leersum et al , Int J Cancer 2012

27.339 pazienti con CCR, Registro Tumori di Eindhoven (NL), periodo 1995-2010

(12)

Italiani con precedente diagnosi di tumore

AIOM-AIRTUM, I numeri del cancro 2014

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Nuove problematiche

 La definizione di “guarito da tumore”

 Le risorse e la sostenibiltà

 I “nuovi” bisogni

 I “nuovi” modelli organizzativi

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La definizione di “guarito da tumore”

(15)

Nuovi ammalati

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Terapie mirate su target molecolari nei primi cinque tumori per incidenza

AIOM – AIRTUM “I numeri del cancro” 2014

Melanoma

(17)

Capecitabina 52%

Vinorelbina

9% Temozolomide

7%

Nib 32%

Erlotinib 11%

Imatinib 4%

Lapatinib 5%

Sorafenib 5%

Sunitinib 7%

Gori et al, Tumori, 2013

32%

SURVEY AIOM 2010 - Trattamenti

(581 pazienti; periodo 1/01/10 - 30/06/10)

 Terapie oncologiche orali (chemioterapici e farmaci biologici) rappresentano il 17% dei trattamenti prescritti

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Tossicità ”storiche”

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Ipilimumab e vemurafenib nei pazienti con melanoma

(20)

Nuovi e vecchi strumenti di informazione

(21)

…..prevenzione su base

molecolare…

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…..terapia su base

molecolare…

(23)

Innovazione in Oncologia

 Innovazione nei cambiamenti

 Innovazione nelle cure

 Innovazione nella sostenibilità

(24)

Innovazione nella cura

 Nuove tecnologie in chemioterapia

 Tecnologia liposomiale

 Nanotecnologia

 Personalizzazione su target molecolari

 Farmaci di II generazione e combinazioni/sequenze

 Farmaci per resistenze secondarie

 Immunoterapia

 Farmaci mirati per check-point

 Farmaci di II generazione e combinazioni/sequenze

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nab-Paclitaxel is The First Tumor-Targeted Nanomedicine to Leverage the Natural Transport Properties of Albumin

130 nm in size^1,2

1. Desai et al. SABCS. 2004 [Abstract 1071].

2. Kratz et al. J Control Release. 2008;132(3):171-183.

3. Peters, Jr. Adv Protein Chem. 1985;37:161-245.

4. Desai. Drug Delivery Report. 2008;Winter 2007/2008(16):35-41.

5. Paal et al. Eur J Biochem. 2001;268:2187-2191.

Albumin Paclitaxel nab-Paclitaxel

complex

nab-Paclitaxel individual molecule

4–14 nm in size^3,4

• A single molecule of albumin can bind up to 6 or 7 molecules of paclitaxel⁵

(27)

[TITLE]

Presented By David Goldstein, MD at 2014 Gastrointestinal Cancers Symposium

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Finalità della valutazione molecolare nella personalizzazione dei trattamenti

 Selezione dei pazienti per resistenza/sensibilità ad un farmaco “targeted”

 Definizione delle sensibilità/resistenze primarie

 Definizione delle resistenze acquisite/secondarie

 Vantaggio clinico (attività/tossicità)

 Razionalizzazione della spesa

(29)

Agente Biomarker Tumore Indicazione registrativa in Italia (AIFA)

Imatinib c-Kit mutato GIST Metastatico, adiuvante alto rischio

Trastuzumab HER2 iperespressione/

amplificazione

Carcinoma mammario Carcinoma gastrico

Adiuvante, neoadiuvante, metastatico in monoterapia o in combinazione con chemioterapia

Metastatico in combinazione con cisplatino e 5- fluorouracile/capecitabina

Pertuzumab HER2 iperespressione/

amplificazione Carcinoma mammario Metastatico o ricorrente localmente in I linea in combinazione con docetaxel e trastuzumab

TDM-1 HER2 iperespressione/

amplificazione Carcinoma mammario Metastatico o ricorrente localmente dopo trastuzumab e tassani in monoterapia

Lapatinib HER2 iperespressione/

amplificazione Carcinoma mammario Metastatico/avanzato in combinazione con capecitabina in pazienti in progressione dopo trastuzumab

Cetuximab RAS wild type Carcinoma del colon-retto Metastatico in combinazione con chemioterapia o in monoterapia

Panitumumab RAS wild type Carcinoma del colon-retto Metastatico pretrattato in monoterapia

Metastatico in combinazione con chemioterapia

Gefitinib EGFR mutato Adenocarcinoma

del polmone Stadio IIIB-IV

Erlotinib EGFR mutato Adenocarcinoma del

polmone Stadio IIIB-IV

Afatinib EGFR mutato Adenocarcinoma del

polmone Stadio IIIB-IV

Crizotinib EML4-ALK fusione NSCLC Stadio IIIB-IV

Vemurafenib BRAF mutato Melanoma Metastatico/inoperabile

Dabrafenib BRAF mutato Melanoma Metastatico/inoperabile

Terapia dei tumori solidi “personalizzata” biomarker-dipendente

(30)

HER2 inhibitors - Trastuzumab and Pertuzumab

 Preferentially inhibits ligand- independent HER2 signaling

 Prevents shedding of HER2 ECD

 Flags cells for destruction by the immune system

 Inhibits formation of HER2 dimer pairs

 Suppresses multiple HER signalling pathways, leading to a more comprehensive blockade of HER2- driven signalling

 Flags cells for destruction by the immune system

HER2 receptor

Trastuzumab

Pertuzumab

Subdomain IV of HER2

Dimerization domain of HER2

Junttila et al, Cancer Cell 2009

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HER2 - Breast cancer

HER2- 80%

Δ=15.7 months Δ=4.8 months

(32)

Targeted Therapies for HER2+ Breast Cancer:

Trastuzumab, Lapatinib, and T-DM1

T-DM1

Antibody: Trastuzumab

HER2

Trastuzumab

32

Lapatinib

Nucleus

Spector NL, Blackwell KL. J Clin Oncol 2009; Nelson MH, et al. Ann Pharmacother 2006;

Lewis Phillips GD, et al. Cancer Res 2008.

P P

P

P P

P

Emtansine Cytotoxic:

DM1 Stable linker:

MCC

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EMILIA Study - Overall Survival Interim Analysis

496 469 438 364 296 242 195 155 129 97 74 52 31 17 7 3 2 1 0 495 484 461 390 331 277 220 182 149 123 96 67 46 29 16 5 2 0 0 Cap + Lap

T-DM1

No. at risk: Time (mos)

Proportion surviving

0.0 0.2 0.4 0.6 0.8 1.0

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36

77.0% 65.4%

47.5%

84.7%

Median (mos) No. events Cap + Lap 23.3 129

T-DM1 NR 94

Stratified HR=0.621 (95% CI, 0.48, 0.81) P=0.0005

Efficacy stopping boundary P=0.0003 or HR=0.617

Unstratified HR=0.63 (P=0.0005).

NR=not reached. K Blackwell et al, ASCO 2012

(34)

HER2 – Gastric cancer

HER2+ 20%

HER2- 80%

• GATSBY Study: T-DM1

• JACOB Study: pertuzumab

(35)

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Gefitinib - Studio IPASS

Erlotinib – Studio EURTAC

Afatinib - Studio LUX-Lung 3

Mok et al, NEJM 2009

Rosell et al, Lancet Oncology 2012 Sequist et al, J Clin Oncol 2013

TKi in I linea nel NSCLC con mutazioni di EGFR

(37)

Terapia dei tumori solidi “personalizzata”

biomarker-dipendente – EGFR polmone

EGFRm 16%

EGFRwt 84%

Moran and Sequist, J Clin Oncol Med 2012

(38)

[TITLE]

Presented By Robert Charles Doebele, MD, PhD at 2013 ASCO Annual Meeting

(39)

[TITLE]

Presented By Robert Charles Doebele, MD, PhD at 2013 ASCO Annual Meeting

(40)

Camidge et al, Nat Rev Clin Oncol 2014

Mechanisms of acquired biological

resistance to EGFR TKIs in NSCLC

(41)

EGFR-T790 Positive

EGFR-T790 Negative

(42)

T790 positive

T790 negative PFS

(months)

9.6 2.8

95% CI 8.3 - NR 2.1 – 4.3

(43)

(44)

PFS in 270 centrally confirmed T790M+

patients

Sequist et al, ASCO 2015

(45)

Systematic resistance to ALK inhibitors

ALK

Non-Dominant

ALK Dominant

Doebele et al. J Clin Oncol 30, 2012 (suppl; abstr 7504)

(46)

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Alectinib in crizotinib-pretreated ALK+

NSCLC: response in phase II trial

Ou et al, ASCO 2015

(48)

Genomic alterations affecting actionable signaling pathways in mCRC

Garraway (modified), J Clin Oncol 2013

MET

(49)

4% 6%

40%

4% 3% NRAS

Exon 2, 3 and 4 KRAS and NRAS mutations

Smith et al, Br J Cancer 2010

All RAS wild type ≈ 45%

KRAS wild type ≈ 60%

(50)

KRAS/RAS - Colorectal cancer

FOLFIRI + Cet vs FOLFIRI

(CRYSTAL Study)

OS (months) Δ (months) HR Author

Unselected 19.9 vs 18.6 1.3 HR=0.878

p=0.0419

Van Cutsem, NEJM 2009,

JCO 2011

KRAS wt 23.5 vs 20.0 3.5 HR=0.796

p=0.0093

Van Cutsem, NEJM 2009,

JCO 2011

RAS wt 28.4 vs 20.2 8.2 HR=0.69

p=0.0024

Ciardiello, ASCO 2014

(51)

KRAS/RAS - Colorectal cancer

FOLFOX + Pan vs FOLFOX

(PRIME Study)

OS (months) Δ (months) HR Author

KRAS wt 23.9 vs 19.7 4.2 HR=0.83

p=0.072

Doiuillard, JCO 2010

RAS wt 26.4 vs 20.2 5.8 HR=0.69

p=0.043

Douillard, NEJM 2013

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PIK3CA wt PIK3CA m

(55)

Aspirin as secondary prevention Study outline

Retrospective norwegian cohort study combining cancer follow-up and prescription history

Bains et al, Abstract 3504, ASCO 2015

(56)

Aspirin as secondary prevention Survival

Bains et al, Abstract 3504, ASCO 2015

HR 0.86

(0.81-0.91)

P <0.001

HR 0.75

(0.70-0.81)

P <0.001

(57)

Target molecular therapy in melanoma

Huang and Marais, Nature Reviews 2009

(58)

BRAF - Melanoma

Chapman et al, N Eng J Med 2011 Haushild et al, Lancet 2012

(59)

Nazarian et al. Nature 2010; Johannessen et al. Nature 2010; Poulikakos et al. Nature 2011; Shi et al. Nature Com 2012; Villanueva et al.

Cancer Cell 2010; Wagle et al. JCO 2011, Strausman et al. AACR 2012

Resistance to BRAF inhibition

Survival

BRAF^V600E

MEK

ERK P

P

BRAF inh

NRAS^Q61

COT

CRAF COT

overexpression

A. MEK-dependent progression

MEK1 mutations NRAS

mutations

BRAF^V600 truncation BRAF^V600 amplification

PDGFRb IGF1R cMET

PI3K

AKT

B. MEK-independent progression

RTK overexpression

RTK ligand overexpression

(60)

Spectrum of resistance

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COMBI-d: Progression-free Survival

Long GV, et al. Lancet. Accepted April 2015.

Time (months)

Dabrafenib

Events: 162 (76%)

Median PFS 8.8 mo (95% CI:5.9–9.3)

HR 0.67 (95% CI:

0.53, 0.84) P < .001

Progres sion -fre e Surv iv al

1.0

0.8

0.6

0.4

0.2

0

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34

211 196 164 137 125 96 84 80 71 70 65 61 38 26 6 0 0 0 212 177 139 109 96 81 65 52 47 40 35 31 19 16 4 0 0 0 Dabrafenib + trametinib

Number at risk

Dabrafenib + placebo

Dabrafenib + Trametinib

Events: 139 (66%)

Median PFS 11.0 mo (95% CI:8.0–13.9)

(62)

COMBI-d: Overall Survival

Time (months)

Dabrafenib Died: 123 (58%)

Median OS = 18.7 mo (95% CI:15.2–23.7)

HR 0.71 (95% CI: 0.55, 0.92)

P = .011

2-yr OS 51%

2-yr OS 42%

Ov erall Surv iv al

1.0

0.8

0.6

0.4

0.2

0

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 0

Dabrafenib + Trametinib Died: 99 (47%)

Med OS = 25·1 mo (95% CI:19.2-NR)

1-yr OS = 74%

1-yr OS = 68%

Dabrafenib+Trametinib med follow up 20 mo (range 0-30 mo);

Dabrafenib med follow up 16 mo (range 0-32 mo).

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coBRIM Updated Investigator-Assessed PFS

Presented By James Larkin at 2015 ASCO Annual Meeting

(64)

[TITLE]

Presented By Lecia V. Sequist, MD, MPH at 2013 ASCO Annual Meeting

(65)

BRCA status and PARPi in ovarian cancer

BRACAm in platinum-sensitive vs platinum-resistant 38% vs 17% (Dann et al, Gynecol Oncol 2012)

(66)

[TITLE]

Presented By Caroline Robert, MD, PhD at 2014 ASCO Annual Meeting

(67)

[TITLE]

Vismodegib

(68)

[TITLE]

(69)

[TITLE]

(70)

[TITLE]

(71)

PTEN genomic alterations lead to a convergent PTEN-negative phenotype in the resistant lesions

Left Lung Lobe

Progression Periaortic lymph node

Right Lung Lobe

PTEN K342_splice Progression

Responding

PTEN loss

PTEN WT

Juric et al, Nature 2015 Courtesy of Maurizio Scaltriti

(72)

Whole exome sequencing reveals an additional PTEN 339fs mutation in the lung metastatic lesion

Breast primary

tumor

Lung metastasis

Lymph node

Courtesy of Maurizio Scaltriti

(73)

Immunotarget-terapia nei tumori solidi

 Melanoma, NSCLC

 Identificazione di fattori predittivi

 Combinazione e sequenze con immunotarget-terapia, farmaci biologici e chemio/radioterapia

 Durata del trattamento

 Valutazione di efficacia

 Nuove tossicità

(74)

[TITLE]

Presented By Scott N. Gettinger, MD at 2014 ASCO Annual Meeting

Target immunotherapy

(75)

Tumor-guided PD-1 blockade treatment selection

Presented By Michael Atkins at 2015 ASCO Annual Meeting

(76)

Tumor-guided PD-1 blockade treatment selection

Presented By Michael Atkins at 2015 ASCO Annual Meeting

(77)

[TITLE]

Presented By Scott N. Gettinger, MD at 2014 ASCO Annual Meeting

(78)

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Ribas el al, Clinical Cancer Res 2012

(80)

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Slide 6

Presented By Jedd Wolchok at 2015 ASCO Annual Meeting

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Slide 10

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Slide 11

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Slide 13

(85)

OS at the Second Interim Analysis

Presented By Lynn Schuchter at 2015 ASCO Annual Meeting

Keynote-

006

(86)

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CheckMate 017 (NCT01642004) - Study Design

One pre-planned interim analysis for OS

At time of DBL (December 15, 2014), 199 deaths were reported (86% of deaths required for final analysis)

The boundary for declaring superiority for OS at the pre-planned interim analysis was P <0.03

Patients stratified by region and prior paclitaxel use

Nivolumab 3 mg/kg IV Q2W

until PD or unacceptable toxicity

n = 135

Docetaxel 75 mg/m²IV Q3W

n = 137

Randomize 1:1

• Primary Endpoint:

– OS

• Additional Endpoints:

̶ Investigator-assessed ORR

̶ Investigator-assessed PFS

̶ Correlation between PD-L1 expression and efficacy

̶ Safety

̶ Quality of life (LCSS)

• Stage IIIb/IV SQ NSCLC

• 1 prior platinum doublet-based chemotherapy

• ECOG PS 0–1

• Pre-treatment (archival or fresh) tumor samples required for PD-L1 analysis

N = 272

Brahmer et al, NEJM 2015

(88)

Overall Survival

Symbols represent censored observations Nivolumab

Docetaxel

135 113 86 69 52 31 15 7 0

137 103 68 45 30 14 7 2 0

Number of Patients at Risk Time (months)

Nivolumab

Docetaxel 1-yr OS rate = 42%

1-yr OS rate = 24%

OS (%)

Nivolumab n = 135

Docetaxel n = 137 mOS mo,

(95% CI)

9.2 (7.3, 13.3)

6.0 (5.1, 7.3)

# events 86 113

HR = 0.59 (95% CI: 0.44, 0.79), P = 0.00025

24 21

18 15

12 9

6 3

0 100

90

80

70

60

50

40

30

10

0 20

(89)

OS by PD-L1 Expression

mOS (mo) Nivolumab Docetaxel

PD-L1 ≥1% 9.3 7.2

PD-L1 <1% 8.7 5.9

PD-L1 ≥5% 10 6.4

PD-L1 <5% 8.5 6.1

PD-L1 ≥10% 11 7.1

PD-L1 <10% 8.2 6.1

1% PD-L1 Expression level 5% PD-L1 Expression level 10% PD-L1 Expression level

Nivolumab PD-L1+

Nivolumab PD-L1–

Time (months)

24 21 18 15 12 9 6 3 0

Time (months)

24 21 18 15 12 9 6 3 0 Time (months)

24 21 18 15 12 9 6 3 0 100

90 80 70 60 50 40 30

10 0 20

OS (%)

24 21 18 15 12 9 6 3 0 100

90

80

70

60

50

40

30

10

0 20

Docetaxel PD-L1+

Docetaxel PD-L1–

(90)

(91)

CheckMate 057 (NCT01673867) Study Design

 PD-L1 expression measured using the Dako/BMS automated IHC assay^14,15

 Fully validated with analytical performance having met all pre-determined acceptance criteria for sensitivity, specificity, precision, and robustness

a Maintenance therapy included pemetrexed, bevacizumab, or erlotinib (not considered a separate line of therapy); ^bPer RECIST v1.1 criteria as determined by the investigator.

Randomize 1:1

• Stage IIIB/IV non-SQ NSCLC

• Pre-treatment (archival or recent) tumor samples required for PD-L1

• ECOG PS 0–1

• Failed 1 prior platinum doublet

• Prior maintenance therapy allowed^a

• Prior TKI therapy allowed for known ALK translocation or EGFR mutation

N = 582

Nivolumab 3 mg/kg IV Q2W

n = 292

Docetaxel 75 mg/m²IV Q3W

n = 290

• Primary Endpoint – OS

• Additional Endpoints – ORR^b

– PFS^b – Safety

– Efficacy by tumor PD-L1 expression – Quality of life (LCSS)

Patients stratified by prior maintenance therapy and line of therapy (second- vs third-line)

Paz-Ares et al, ASCO 2015

(92)

Overall Survival

Symbols represent censored observations.

Nivolumab (n = 292)

Docetaxel (n = 290)

mOS, mo 12.2 9.4

HR = 0.73 (96% CI: 0.59, 0.89); P = 0.0015

Nivolumab

Docetaxel 1-yr OS rate = 51%

1-yr OS rate = 39%

292 232 194 169 146 123 62 32 9 0

290 244 194 150 111 88 34 10 5 0

Nivolumab Docetaxel

Number of Patients at Risk

OS (%)

Time (months)

100

90

80

70

60

50

40

30

10

0 20

27 21

18 15

12 9

6 3

0 24

(93)

Nivo Doc Nivo Doc

100 90 80 70 60 50 40 30

10 0 20

Time (months) 100

90 80 70 60 50 40 30

10 0 20

24 21 18 15 12 9 6 3

0 27

Time (months)

24 21 18 15 12 9 6 3

0 27

Symbols represent censored observations.

OS by PD-L1 Expression

mOS (mo)

Nivo 10.4

Doc 10.1

mOS (mo) Nivo 17.2

Doc 9.0

mOS (mo)

Nivo 9.9

Doc 10.3

mOS (mo) Nivo 19.4

Doc 8.0

Time (months)

≥5% PD-L1 expression level

<5% PD-L1 expression level

mOS (mo) Nivo 18.2

Doc 8.1

mOS (mo) Nivo 9.7

Doc 10.1

HR (95% CI) = 0.59 (0.43, 0.82)

Time (months)

<1% PD-L1 expression level

OS (%)

HR (95% CI) = 0.90 (0.66, 1.24)

HR (95% CI) = 0.43 (0.30, 0.63)

HR (95% CI) = 1.01 (0.77, 1.34)

OS (%)

Time (months) Time (months)

<10% PD-L1 expression level HR (95% CI) = 0.40 (0.26, 0.59)

HR (95% CI) = 1.00 (0.76, 1.31)

24 21 18 15 12 9 6 3

0 27

100 90 80 70 60 50 40 30

10 0 20

100 90 80 70 60 50 40 30

10 0 20

24 21 18 12 15

9 6 3

0 27

24 21 18 15 12 9 6 3

0 27

100 90 80 70 60 50 40 30

10 0 20

24 21 18 15 12 9 6 3

0 27

100 90 80 70 60 50 40 30

10 0 20

(94)

Pembrolizumab (MK-3475) in Patients With Extensive-Stage Small Cell Lung Cancer: Preliminary Safety and Efficacy <br />Results from KEYNOTE-028

(95)

Change From Baseline in Tumor Size <br />(RECIST v1.1, Investigator Review)

Ott et al, ASCO 2015

(96)

Innovazione in Oncologia

 Innovazione nei cambiamenti

 Innovazione nelle cure

 Innovazione nella sostenibilità

(97)

“Moral necessity: Price must reflect worth”

Kantarjian, J Clin Oncol 2013

(98)

Ellis et al, J Clin Oncol 2014

(99)

Misura del prezzo dei farmaci anti-tumorali

 Attualmente il prezzo dei nuovi farmaci viene misurato da

 Rapporto costo/efficacia

 Prolungamento della vita del paziente in anni

 Anni di vita guadagnati (QALs)

• Complessivamente rispetto al precedente decennio il range

del prezzo degli agenti anti-tumorali risulta duplicato da $

4.500 a più di $10.000 per mese

(100)

(101)

Ipotesi di “Valore” e “Costo”

Valore Costo

Prolungamento ≥1/3 dell’aspettativa di vita nel setting di pazienti considerato (attesa di vita 12 mesi incremento significativo ≥16 mesi; attesa di vita 6 mesi incremento significativo ≥8 mesi)

I fascia

Farmaci ad efficacia intermedia II fascia Prolungamento statisticamente significativo

<15% dell’aspettativa di vita nel setting di pazienti considerato

III fascia

(102)

Presented By Leonard Saltz at 2015 ASCO Annual Meeting

(103)

We must be cost sensitive

Presented By Svetomir Markovic at 2015 ASCO Annual Meeting

(104)

Quali prospettive per garantire l’accesso ai farmaci

 Innovazione, sostenibilità e appropriatezza vanno correlati alla organizzazione del sistema sanitario e del percorso assistenziale

 In fase di disegno di uno studio clinico e di interpretazione dei risultati da parte delle autorità regolatorie considerare la rilevanza clinica dei risultati statisticamente significativi

 Inplementazione della ricerca per individuare fattori predittivi (biologici e clinici) di sensibilità/resistenza

 I vantaggi dell’introduzione di un farmaco vanno considerati nell’ambito di una strategia terapeutica (miglioramenti addizionali) e dell’intero processo diagnostico-terapeutico

 Rivisitazione dei sistemi di rimborso e costi sulla base dell’effectiveness e dei dati di registri a termine definito, e prospettiva di un fondo nazionale per i farmaci oncologici