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An Investigational Immuno-therapy Study of Nivolumab Compared to Sorafenib as a First Treatment in Patients With Advanced Hepatocellular Carcinoma

Phase 3
Completed
Conditions
Hepatocellular Carcinoma
Interventions
Registration Number
NCT02576509
Lead Sponsor
Bristol-Myers Squibb
Brief Summary

The purpose of this study is to determine if nivolumab or sorafenib is more effective in the treatment of Advanced Hepatocellular Carcinoma.

Detailed Description

Not available

Recruitment & Eligibility

Status
COMPLETED
Sex
All
Target Recruitment
743
Inclusion Criteria
  • Histologically confirmed advanced hepatocellular carcinoma, not eligible for surgical and/or locoregional therapies; or progressive disease after surgical and /or locoregional therapies
  • Locoregional therapy for hepatocellular carcinoma (HCC) must be completed at least 4 weeks prior to the baseline scan
  • Child-Pugh Class A
  • Eastern Cooperative Oncology Group (ECOG) performance status (PS) 0 or 1
Exclusion Criteria
  • Known fibrolamellar HCC, sarcomatoid HCC, or mixed cholangiocarcinoma and HCC
  • Prior liver transplant
  • Active, known, or suspected autoimmune disease

Other protocol-defined inclusion/exclusion criteria apply

Study & Design

Study Type
INTERVENTIONAL
Study Design
PARALLEL
Arm && Interventions
GroupInterventionDescription
SorafenibSorafenibSorafenib specified dose on specified days
NivolumabNivolumabNivolumab specified dose on specified days
Primary Outcome Measures
NameTimeMethod
Overall Survival (OS)time from the date of randomization to the date of death due to any cause, assessed up to June 2019 (approximately 41 months)

OS is defined as the time from the date of randomization to the date of death due to any cause in all randomized participants. Participants who are alive will be censored at the last known alive dates.

Based on Kaplan-Meier Estimates.

Secondary Outcome Measures
NameTimeMethod
Objective Response Rate (ORR) Per BICR RECIST 1.1the date of randomization and the date of first objectively documented progression or the date of subsequent anti-cancer therapy, whichever occurs first, assessed up to May 2019 (approximately 40 months)

ORR is defined as the proportion of participants whose best overall response (BOR) is either a complete response (CR) or partial response (PR). BOR is defined as the best response designation, as determined based on BICR-assessed tumor response according to RECIST 1.1, recorded between the date of randomization and the date of first objectively documented progression or the date of subsequent anti-cancer therapy, whichever occurs first. For participants without documented progression or subsequent anti-cancer therapy, all available response designations will contribute to the BOR determination. For a BOR of CR or PR, the initial response assessment must be confirmed by a consecutive assessment no less than 4 weeks (28 days) later.

Estimate of (Nivolumab - Sorafenib) is based on CMH method of weighting, stratified by stratification factors

Progression-Free Survival (PFS)time from the date of randomization to the date of the first objectively documented tumor progression or death, assessed up to May 2019 (approximately 40 months)

PFS is defined as the time from the date of randomization to the date of the first objectively documented tumor progression as assessed by BICR according to RECIST 1.1 or death due to any cause in all randomized participants. Participants who die without a reported prior progression and without initiation of subsequent anti-cancer therapy will be considered to have progressed on the date of their death. Participants who did not progress or die will be censored on the date of their last tumor assessment. Participants who did not have baseline tumor assessment will be censored on the date they were randomized. Participants who did not have any on study tumor assessments and did not die will be censored on the date they were randomized. Participants who started any subsequent anti-cancer therapy without a prior reported progression will be censored at the last tumor assessment prior to subsequent anti-cancer therapy.

Efficacy Based on PD-L1 Expression - OS and PFSthe date of randomization and the date of first objectively documented progression or the date of subsequent anti-cancer therapy, whichever occurs first, assessed up to May 2019 (approximately 40 months)

PD-L1 expression is defined as the percent of tumor cell membrane staining in a minimum of 100 evaluable tumor cells per Dako PD-L1 IHC assay unless otherwise specified. This is referred as quantifiable PD-L1 expression. If the PD-L1 staining could not be quantified, it is further classifies as:

Indeterminate: Tumor cell membrane staining hampered for reasons attributed to the biology of the tumor biopsy specimen and not because of improper sample preparation or handling.

Not evaluable: Tumor biopsy specimen was not optimally collected or prepared (e.g. PD-L1 expression is neither quantifiable nor indeterminate).

PD-L1 status is a dichotomized variable using an X% cut-off for quantifiable PD-L1 expression:

* PD-L1 \> X %: ≥ X % PD-L1 expression

* PD-L1 \< X %: \< X % PD-L1 expression where X% denotes the PD-L1 expression cut-off of 1%. Additional cut off values may also be explored.

Confidence interval based on the Clopper and Pearson method.

Efficacy Based on PD-L1 Expression - ORRthe date of randomization and the date of first objectively documented progression or the date of subsequent anti-cancer therapy, whichever occurs first, assessed up to May 2019 (approximately 40 months)

PD-L1 expression is defined as the percent of tumor cell membrane staining in a minimum of 100 evaluable tumor cells per Dako PD-L1 IHC assay unless otherwise specified. This is referred as quantifiable PD-L1 expression. If the PD-L1 staining could not be quantified, it is further classifies as:

Indeterminate: Tumor cell membrane staining hampered for reasons attributed to the biology of the tumor biopsy specimen and not because of improper sample preparation or handling.

Not evaluable: Tumor biopsy specimen was not optimally collected or prepared (e.g. PD-L1 expression is neither quantifiable nor indeterminate).

PD-L1 status is a dichotomized variable using an X% cut-off for quantifiable PD-L1 expression:

* PD-L1 \> X %: ≥ X % PD-L1 expression

* PD-L1 \< X %: \< X % PD-L1 expression where X% denotes the PD-L1 expression cut-off of 1%. Additional cut off values may also be explored.

Confidence interval based on the Clopper and Pearson method.

Trial Locations

Locations (138)

Local Institution - 0055

🇮🇹

Milan, Italy

Local Institution - 0039

🇦🇹

Graz, Austria

Local Institution - 0075

🇧🇪

Bruxelles, Belgium

Local Institution - 0091

🇧🇪

Leuven, Belgium

Local Institution - 0095

🇺🇸

Philadelphia, Pennsylvania, United States

Local Institution - 0077

🇧🇪

Liege, Belgium

UT Southwestern Medical Center

🇺🇸

Dallas, Texas, United States

Local Institution - 0093

🇺🇸

New York, New York, United States

Local Institution - 0019

🇺🇸

Philadelphia, Pennsylvania, United States

Local Institution - 0016

🇺🇸

Charlotte, North Carolina, United States

Local Institution - 0083

🇺🇸

New York, New York, United States

Local Institution - 0054

🇮🇹

Benevento, Italy

Local Institution - 0042

🇨🇦

Quebec, Canada

Local Institution - 0058

🇮🇱

Petah-tikva, Israel

Local Institution - 0030

🇩🇪

Tuebingen, Germany

Local Institution - 0071

🇫🇷

La Tronche, France

Local Institution - 0072

🇫🇷

Lille Cedex, France

Local Institution - 0073

🇫🇷

Montpellier Cedex, France

Local Institution - 0011

🇭🇰

Hong Kong, Hong Kong

Local Institution - 0063

🇮🇹

Orbassano, Italy

Local Institution - 0107

🇯🇵

Kurume-shi, Fukuoka, Japan

Local Institution - 0032

🇩🇪

Regensburg, Germany

Local Institution - 0062

🇮🇹

Bergamo, Italy

Local Institution - 0033

🇩🇪

Munich, Germany

Local Institution - 0082

🇮🇱

Haifa, Israel

Local Institution - 0028

🇨🇿

Olomouc, Czechia

Local Institution - 0101

🇯🇵

Hiroshima, Japan

Local Institution - 0115

🇯🇵

Saga-shi, Saga, Japan

Local Institution - 0123

🇰🇷

Seoul, Korea, Republic of

Local Institution - 0060

🇮🇱

Jerusalem, Israel

Local Institution - 0130

🇯🇵

Sapporo-shi, Hokkaido, Japan

Local Institution - 0105

🇯🇵

Kanazawa-shi, Ishikawa, Japan

Local Institution - 0064

🇮🇹

Siena, Italy

Local Institution - 0085

🇪🇸

Majadahonda - Madrid, Spain

Local Institution - 0037

🇩🇪

Essen, Germany

Local Institution - 0112

🇯🇵

Yokohama-shi, Kanagawa, Japan

Local Institution - 0125

🇰🇷

Daegu, Korea, Republic of

Local Institution - 0100

🇯🇵

Chiba City, Chiba, Japan

Local Institution - 0096

🇷🇺

Moscow, Russian Federation

Local Institution - 0124

🇰🇷

Seoul, Korea, Republic of

Local Institution - 0014

🇸🇬

Singapore, Singapore

Local Institution - 0127

🇯🇵

Ogaki-shi, Gifu, Japan

Local Institution - 0102

🇯🇵

Sapporo-shi, Hokkaido, Japan

Local Institution - 0079

🇬🇧

Glasgow, Lanarkshire, United Kingdom

Local Institution - 0122

🇰🇷

Seoul, Korea, Republic of

Local Institution - 0116

🇰🇷

Goyang-si, Korea, Republic of

Local Institution - 0108

🇯🇵

Musashino-shi, Tokyo, Japan

Local Institution - 0013

🇸🇬

Singapore, Singapore

Local Institution - 0129

🇨🇳

Kaohsiung County, Taiwan

Local Institution - 0106

🇯🇵

Osaka-Sayama-Shi, Osaka, Japan

Local Institution - 0117

🇰🇷

Seoul, Seocho-gu, Korea, Republic of

Local Institution - 0119

🇰🇷

Seoul-si, Korea, Republic of

Local Institution - 0120

🇨🇳

Taipei, Taiwan

Local Institution - 0045

🇵🇱

Wroclaw, Poland

Local Institution - 0133

🇨🇳

Taichung, Taiwan

Local Institution - 0121

🇨🇳

Tainan, Taiwan

Local Institution - 0087

🇸🇪

Stockholm, Sweden

Local Institution - 0010

🇪🇸

Santiago Compostela, Spain

Local Institution - 0020

🇺🇸

Los Angeles, California, United States

Local Institution - 0061

🇺🇸

Chicago, Illinois, United States

Local Institution - 0026

🇺🇸

Seattle, Washington, United States

University of Washington - Seattle Cancer Care Alliance

🇺🇸

Seattle, Washington, United States

Local Institution - 0131

🇯🇵

Chiyoda-ku, Tokyo, Japan

Ochsner Clinic Foundation

🇺🇸

New Orleans, Louisiana, United States

Local Institution - 0139

🇨🇳

Beijing, Beijing, China

Local Institution - 0140

🇨🇳

Beijing, Beijing, China

Local Institution - 0141

🇨🇳

Beijing, Beijing, China

Local Institution - 0161

🇨🇳

Guangzhou, Guangdong, China

Local Institution - 0144

🇨🇳

Guangzhou, Guangdong, China

Local Institution - 0158

🇨🇳

Nanning, Guangxi, China

Local Institution - 0148

🇨🇳

Changsha, Hunan, China

Local Institution - 0162

🇨🇳

Changsha, Hunan, China

Local Institution - 0135

🇨🇳

Nanjing, Jiangsu, China

Local Institution - 0136

🇨🇳

Changchun, Jilin, China

Local Institution - 0163

🇨🇳

Changchun, Jilin, China

Local Institution - 0151

🇨🇳

Shanghai, Shanghai, China

Local Institution - 0146

🇨🇳

Hangzhou, Zhejiang, China

Local Institution - 0015

🇺🇸

San Francisco, California, United States

Local Institution - 0084

🇺🇸

San Francisco, California, United States

Local Institution - 0017

🇺🇸

San Antonio, Texas, United States

Local Institution - 0066

🇺🇸

Birmingham, Alabama, United States

Local Institution - 0088

🇸🇪

Goteborg, Sweden

Local Institution - 0067

🇫🇷

Paris Cedex 13, France

Local Institution - 0068

🇫🇷

Pessac, France

Local Institution - 0081

🇬🇧

Liverpool, United Kingdom

Local Institution - 0103

🇯🇵

Matsuyama-shi, Ehime, Japan

Local Institution - 0110

🇯🇵

Kawasaki-shi, Kanagawa, Japan

Local Institution - 0012

🇭🇰

Hong Kong, Hong Kong

Local Institution - 0128

🇨🇳

Taoyuan County, Taiwan

Scott & White Memorial Hospital And Clinic

🇺🇸

Temple, Texas, United States

Local Institution - 0050

🇺🇸

Madison, Wisconsin, United States

Local Institution - 0005

🇦🇺

Camperdown, New South Wales, Australia

Local Institution - 0007

🇦🇺

Adelaide, South Australia, Australia

Local Institution - 0001

🇦🇺

Clayton, Victoria, Australia

Local Institution - 0038

🇦🇹

Wien, Austria

Local Institution - 0003

🇦🇺

Prahran, Victoria, Australia

Local Institution - 0008

🇦🇺

Nedlands, Western Australia, Australia

Local Institution - 0043

🇨🇦

Calgary, Alberta, Canada

Local Institution - 0044

🇨🇦

Vancouver, British Columbia, Canada

Local Institution - 0164

🇨🇳

Hefei, Anhui, China

Local Institution - 0137

🇨🇳

Beijing, Beijing, China

Local Institution - 0152

🇨🇳

Fuzhou, Fujian, China

Local Institution - 0157

🇨🇳

Guangzhou, Guangdong, China

Local Institution - 0142

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Harbin, Heilongjiang, China

Local Institution - 0169

🇨🇳

Changzhou, Jiangsu, China

Local Institution - 0138

🇨🇳

Xi'an, Shan3xi, China

Local Institution - 0166

🇨🇳

Dalian, Liaoning, China

Local Institution - 0159

🇨🇳

Tianjin, Tianjin, China

Local Institution - 0145

🇨🇳

Shanghai, Shanghai, China

Local Institution - 0173

🇨🇳

Hangzhou, Zhejiang, China

Local Institution - 0029

🇨🇿

Brno, Czechia

Local Institution - 0027

🇨🇿

Hradec Kralove, Czechia

Local Institution - 0069

🇫🇷

Lyon, France

Local Institution - 0070

🇫🇷

Rennes Cedex, France

Local Institution - 0074

🇫🇷

Toulouse Cedex 9, France

Local Institution - 0167

🇩🇪

Frankfurt, Germany

Local Institution - 0036

🇩🇪

Berlin, Germany

Local Institution - 0034

🇩🇪

Hamburg, Germany

Local Institution - 0059

🇮🇱

Tel Aviv, Israel

Local Institution - 0035

🇩🇪

Mainz, Germany

Local Institution - 0113

🇯🇵

Suita, Osaka, Japan

Local Institution - 0111

🇯🇵

Kyoto-shi, Kyoto, Japan

Local Institution - 0126

🇯🇵

Shinjuku-ku, Tokyo, Japan

Local Institution - 0114

🇯🇵

Mitaka-shi, Tokyo, Japan

Local Institution - 0118

🇰🇷

Jeollanam-do, Korea, Republic of

Local Institution - 0009

🇪🇸

Pamplona, Spain

Local Institution - 0056

🇵🇱

Warszawa, Poland

Local Institution - 0065

🇪🇸

Alicante, Spain

Local Institution - 0040

🇨🇭

Basel, Switzerland

Local Institution - 0041

🇨🇭

Bern, Switzerland

Local Institution - 0099

🇨🇳

Taipei, Taiwan

Local Institution - 0132

🇨🇳

Tainan, Taiwan

Local Institution - 0080

🇬🇧

London, Greater London, United Kingdom

Local Institution - 0078

🇬🇧

London, Greater London, United Kingdom

Local Institution - 0002

🇦🇺

Heidelberg, Victoria, Australia

Local Institution - 0104

🇯🇵

Yokohama-shi, Kanagawa, Japan

Local Institution - 0031

🇩🇪

Leipzig, Germany

Local Institution - 0023

🇵🇱

Gdansk, Poland

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