Immunotherapy vs Best Supportive Care for Patients With Hepatocellular Cancer With Child-Pugh B Dysfunction

Claudia Angela Maria Fulgenzi; Bernhard Scheiner; Antonio D’Alessio; Aman Mehan; Giulia F Manfredi; Ciro Celsa; Naoshi Nishida; Celina Ang; Thomas U Marron; Linda Wu; Anwaar Saeed; Brooke Wietharn; Antonella Cammarota; Tiziana Pressiani; Matthias Pinter; Rohini Sharma; Jaekyung Cheon; Yi-Hsiang Huang; Pei-Chang Lee; Samuel Phen; Anuhya Gampa; Anjana Pillai; Andrea Napolitano; Caterina Vivaldi; Francesca Salani; Gianluca Masi; Marianna Silletta; Federica Lo Prinzi; Emanuela Di Giacomo; Bruno Vincenzi; Dominik Bettinger; Robert Thimme; Arndt Vogel; Martin Schönlein; Johann von Felden; Kornelius Schulze; Henning Wege; Peter R Galle; Mario Pirisi; Joong-Won Park; Masatoshi Kudo; Lorenza Rimassa; Amit G Singal; Paul El Tomb; Susanna Ulahannan; Alessandro Parisi; Hong Jae Chon; Wei-Fan Hsu; Giorgia Ghittoni; Calogero Cammà; Benedetta Stefanini; Franco Trevisani; Edoardo G Giannini; Alessio Cortellini; David James Pinato

doi:10.1001/jamaoncol.2024.2166

. 2024 Jul 18;10(9):1253–1258. doi: 10.1001/jamaoncol.2024.2166

Immunotherapy vs Best Supportive Care for Patients With Hepatocellular Cancer With Child-Pugh B Dysfunction

Claudia Angela Maria Fulgenzi ^1,², Bernhard Scheiner ^1,³, Antonio D’Alessio ^1,⁴, Aman Mehan ¹, Giulia F Manfredi ^1,⁴, Ciro Celsa ^1,⁵, Naoshi Nishida ⁶, Celina Ang ⁷, Thomas U Marron ⁷, Linda Wu ⁷, Anwaar Saeed ⁸, Brooke Wietharn ⁸, Antonella Cammarota ^9,¹⁰, Tiziana Pressiani ¹⁰, Matthias Pinter ³, Rohini Sharma ¹, Jaekyung Cheon ¹¹, Yi-Hsiang Huang ^12,^13,¹⁴, Pei-Chang Lee ^15,¹⁶, Samuel Phen ¹⁷, Anuhya Gampa ¹⁸, Anjana Pillai ¹⁹, Andrea Napolitano ²⁰, Caterina Vivaldi ²¹, Francesca Salani ^21,²², Gianluca Masi ²¹, Marianna Silletta ², Federica Lo Prinzi ², Emanuela Di Giacomo ², Bruno Vincenzi ², Dominik Bettinger ²³, Robert Thimme ²³, Arndt Vogel ²⁴, Martin Schönlein ²⁵, Johann von Felden ²⁶, Kornelius Schulze ²⁶, Henning Wege ²⁶, Peter R Galle ²⁷, Mario Pirisi ⁴, Joong-Won Park ²⁸, Masatoshi Kudo ⁶, Lorenza Rimassa ^9,¹⁰, Amit G Singal ^15,¹⁶, Paul El Tomb ²⁹, Susanna Ulahannan ²⁹, Alessandro Parisi ³⁰, Hong Jae Chon ¹¹, Wei-Fan Hsu ³¹, Giorgia Ghittoni ³², Calogero Cammà ⁵, Benedetta Stefanini ³³, Franco Trevisani ³³, Edoardo G Giannini ^34,³⁵, Alessio Cortellini ^1,², David James Pinato ^1,^4,^✉

¹Department of Surgery and Cancer, Imperial College London, Hammersmith Hospital, London, England

²Operative Research Unit of Oncology, Fondazione Policlinico Universitario Campus Bio-Medico, Rome, Italy

³Division of Gastroenterology and Hepatology, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria

⁴Department of Translational Medicine, University of Piemonte Orientale, Novara, Italy

⁵Gastroenterology and Hepatology Unit, Department of Health Promotion, Mother and Child Care, Internal Medicine & Medical Specialties, University of Palermo, Palermo, Italy

⁶Department of Gastroenterology and Hepatology, Kindai University Faculty of Medicine, Osaka, Japan

⁷Department of Medicine, Division of Hematology/Oncology, Tisch Cancer Institute, Mount Sinai Hospital, New York, New York

⁸Department of Medicine, Division of Medical Oncology, Kansas University Cancer Center, Kansas City

⁹Department of Biomedical Sciences, Humanitas University, Milan, Italy

¹⁰Medical Oncology and Hematology Unit, Humanitas Cancer Center, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy

¹¹Medical Oncology, Department of Internal Medicine, CHA Bundang Medical Center, CHA University, Seongnam, Korea

¹²Healthcare and Services Center, Taipei Veterans General Hospital, Taipei, Taiwan

¹³Division of Gastroenterology and Hepatology, Taipei Veterans General Hospital, Taipei, Taiwan

¹⁴Institute of Clinical Medicine, Faculty of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan

¹⁵Division of Gastroenterology and Hepatology, Taipei Veterans General Hospital, Taipei, Taiwan

¹⁶Faculty of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan

¹⁷Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas

¹⁸Medical Oncology/TSET Phase 1 Program, Stephenson Cancer Center, Section of Gastroenterology, University of Oklahoma, Oklahoma City

¹⁹Hepatology & Nutrition, the University of Chicago Medicine, Chicago, Illinois

²⁰The Royal Marsden National Health Service Foundation Trust, London, England

²¹Unit of Medical Oncology 2, Azienda Ospedaliero- Universitaria Pisana, Pisa, Italy

²²Scuola Superiore Sant’Anna Pisa, Interdisciplinary Research Center, Pisa, Italy

²³Department of Gastroenterology, Hepatology, Endocrinology and Infectious Diseases, Freiburg University Medical Center, University of Freiburg, Freiburg, Germany

²⁴Hannover Medical School, Hannover, Germany

²⁵Department of Oncology, Hematology and Bone Marrow Transplantation with Section of Pneumology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany

²⁶Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany

²⁷Department of Internal Medicine I, University Medical Center Mainz, Mainz, Germany

²⁸National Cancer Centre Hospital, Goyang, South Korea

²⁹Stephenson Cancer Center, Oklahoma City, Oklahoma

³⁰Department of Oncology, Università Politecnica delle Marche, Azienda Ospedaliero-Universitaria delle Marche, Ancona, Italy

³¹Center for Digestive Medicine, Department of Internal Medicine, China Medical University Hospital, Taichung, Taiwan

³²Gastroenterology Unit, Belcolle hospital, Viterbo, Italy

³³Semeiotics and Liver and Alcohol-Related Disease Unit, Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy

³⁴Gastroenterology Unit, Department of Internal Medicine, University of Genoa, Genoa, Italy

³⁵IRCCS Ospedale Policlinico San Martino, Genoa, Italy

Accepted for Publication: February 22, 2024.

Published Online: July 18, 2024. doi:10.1001/jamaoncol.2024.2166

Correction: This article was corrected on September 19, 2024, to fix errors in Figure 1.

^✉

Corresponding Author: David James Pinato, MD, PhD, Imperial College London, Department of Surgery & Cancer, Room 138 ICTEM Building Level 1, Hammersmith Hospital, Du Cane Road, London, W12 0HS (david.pinato@imperial.ac.uk).

Author Contributions: Drs Fulgenzi and Cortellini had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Drs Cortellini and Pinato are joint senior authors.

Concept and design: Fulgenzi, Scheiner, D’Alessio, Manfredi, Marron, Bettinger, Wege, Pirisi, Cortellini, Pinato.

Acquisition, analysis, or interpretation of data: Fulgenzi, Scheiner, D’Alessio, Mehan, Celsa, Nishida, Ang, Marron, Wu, Saeed, Wietharn, Cammarota, Pressiani, Sharma, Cheon, Huang, Lee, Phen, Gampa, Pillai, Napolitano, Vivaldi, Salani, Masi, Silletta, Lo Prinzi, Di Giacomo, Vincenzi, Bettinger, Thimme, Vogel, Schönlein, von Felden, Schulze, Wege, Galle, Park, Kudo, Rimassa, Singal, El Tomb, Ulahannan, Parisi, Chon, Hsu, Ghittoni, Cammà, Stefanini, Trevisani, Giannini, Cortellini, Pinato.

Drafting of the manuscript: Fulgenzi, Mehan, Marron, Cammarota, Lo Prinzi, Stefanini, Pinato.

Critical review of the manuscript for important intellectual content: Fulgenzi, Scheiner, D’Alessio, Manfredi, Celsa, Nishida, Ang, Marron, Wu, Saeed, Wietharn, Cammarota, Pressiani, Sharma, Cheon, Huang, Lee, Phen, Gampa, Pillai, Napolitano, Vivaldi, Salani, Masi, Silletta, Di Giacomo, Vincenzi, Bettinger, Thimme, Vogel, Schönlein, von Felden, Schulze, Wege, Galle, Pirisi, Park, Kudo, Rimassa, Singal, El Tomb, Ulahannan, Parisi, Chon, Hsu, Ghittoni, Cammà, Trevisani, Giannini, Cortellini, Pinato.

Statistical analysis: Fulgenzi, Napolitano, El Tomb, Cortellini.

Obtained funding: von Felden, Pinato.

Administrative, technical, or material support: D’Alessio, Mehan, Nishida, Marron, Saeed, Cammarota, Huang, Lee, Salani, Masi, Bettinger, von Felden, Galle, Park, El Tomb, Ghittoni.

Supervision: Scheiner, Marron, Pressiani, Lee, Vincenzi, Bettinger, Thimme, Pirisi, Kudo, El Tomb, Chon, Cortellini, Pinato.

Conflict of Interest Disclosures: Dr Scheiner reported personal fees from AbbVie, Ipsen, Gilead, Eisai, and Roche and grants from AstraZeneca and Eisai outside the submitted work. Dr D’Alessio reported personal fees from Roche, AstraZeneca, and Chugai outside the submitted work. Dr Celsa reported personal fees from Eisai, MSD, AstraZeneca, and Roche outside the submitted work. Dr Marron reported service on advisory and/or data safety monitoring boards for Rockefeller University, Regeneron, AbbVie, Merck, Bristol-Meyers Squibb, Boehringer Ingelheim, Atara, AstraZeneca, Genentech, Celldex, Chimeric, DrenBio, Glenmark, Simcere, Surface, G1 Therapeutics, NGMbio, DBV Technologies, Arcus, Fate, Ono, Larkspur, and Astellas and grants from the National Institutes of Health (National Cancer Institute), the Cancer Research Institute, Regeneron, Genentech, Bristol-Myers Squibb, Merck, and Boehringer Ingelheim. Dr Saeed reported personal fees from AstraZeneca, Bristol-Myers Squibb, Merck, Exelixis, Pfizer, Xilio Therapeutics, Taiho, Amgen, Autem Therapeutics, KAHR Medical, Arcus Therapeutics, and Daiichi Sankyo and grants from AstraZeneca, Bristol-Myers Squibb, Merck, Clovis, Exelixis, Actuate therapeutics, Incyte Corporation, Daiichi Sankyo, Five Prime Therapeutics, Amgen, Innovent biologics, Dragonfly Therapeutics, Oxford Biotherapeutics, Arcus Therapeutics, and KAHR Medical outside the submitted work. Dr Pressiani reported personal fees from Bayer, Ipsen and Astra Zeneca and research support from Roche Bayer, and AstraZeneca during the conduct of the study. Dr Cheon reported grants from Bayer. Dr Huang reported grants from Gilead, AstraZeneca, and BMS and nonfinancial support from Eisai and MSD outside the submitted work. Dr Pillai reported personal fees from Eisai, Genentech, Exelixis, AstraZeneca, and Replimune outside the submitted work. Dr Vivaldi reported personal fees from Roche, AstraZeneca, MSD, Taiho Oncology, Servier, and BMS; nonfinancial support from Roche, AstraZeneca, and MSD; and speaking fees from Terumo outside the submitted work. Dr Bettinger reported personal fees from Gore and Falk Foundation and grants from Gilead outside the submitted work. Dr Vogel reported personal fees from Roche, MSD, BMS, AstraZeneca,Eisai, Terumo, and Beigene outside the submitted work. Dr Wege reported personal fees from Roche, AstraZeneca, and Eisai outside the submitted work. Dr Galle reported personal fees from Roche, BMS, MSD, AstraZeneca, Eisai, Ipsen, Guerbet, Boston Scientific, and Lilly and grants from Bayer outside the submitted work. Dr Park reported grants from Ono-BMS, Roche, AstraZeneca, and MSD during the conduct of the study as well as personal fees from Roche, AstraZeneca, Bigene, and Eisai outside the submitted work. Dr Kudo reported personal fees from Eisai and Chugai outside the submitted work. Dr Rimassa reported personal fees from AstraZeneca, Basilea, Bayer, BMS, Eisai, Elevar Therapeutics, Exelixis, Genenta, Hengrui, Incyte, Ipsen, IQVIA, Jazz Pharmaceuticals, MSD, Nerviano Medical Sciences, Roche, Servier, Taiho Oncology, and Zymeworkss outside the submitted work. Dr Singal reported personal fees from Genentech/Roche, AstraZeneca, Eisai, Bayer, Exelixis, Boston Scientific, Sirtex, FujiFilm Medical Sciences, Exact Sciences, Glycotest, Universal Dx, Freenome, GRAIL, and HistoSonics outside the submitted work. Dr Ulahannan reported grants from AbbVie, Adlai Nortye, ArQule, Astra Zeneca, Atreca, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene Corporation, Ciclomed LLC, Erasca, Evelo Biosciences, Exelexis, G1 Therapeutics, GlaxoSmithKline GSK, IGM Biosciences, Incyte, Isofol, Klus Pharma, Macrogenics, Merck, Mersana Therapeutics, OncoMed Pharmaceuticals, Pfizer, Regeneron Pharmaceuticals, Revolution Medicines, Synermore Biologics Co, Takeda, Tarveda Therapeutics, Tesaro, Tempest Therapeutics, and Vigeo Therapeutics Inc during the conduct of the study as well as grants from AbbVie, Adlai Nortye, ArQule, AstraZeneca, Atreca, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene Corporation, Ciclomed, Erasca, Evelo Biosciences, Exelexis, G1 Therapeutics, GlaxoSmithKline GSK, IGM Biosciences, Incyte, Isofol, Klus Pharma, Macrogenics, Merck Co, Mersana Therapeutics, OncoMed Pharmaceuticals, Pfizer, Regeron Pharmaceuticals, Revolution Medicines, Synermore Biologics Co, Takeda, Tarveda Therapeutics, Tesaro, Tempest Therapeutics, and Vigeo Therapeutics Inc outside the submitted work. Dr Chon reported grants from Roche, Bayer, Celgene Cancer Care Links, AstraZeneca, Ono Pharma Korea, Eisai, Sanofi, Servier, MSD Oncology, Menarini, BMS, Sillajen, and GreenCross Cell outside the submitted work. Dr Hsu reported grants from China Medical University Hospital, and the National Science Council outside the submitted work. Dr Cammà reported personal fees from Roche, Eisai, AstraZeneca, and AbbVie outside the submitted work. Dr Giannini reported personal fees from Roche, AstraZeneca, and Eisai-MSD during the conduct of the study. Dr Cortellini reported personal fees from MSD, BMS, Roche, Regeneron, Sanofi, GSK, OncoC4, and AstraZeneca outside the submitted work. Dr Pinato reported personal fees from Roche, Astra Zeneca, Eisai, Mina Therapeutics, Starpharma, Lift Biosciences, Boston Scientific, and Avamune and grants from GSK, MSD, BMS outside the submitted work. No other disclosures were reported.

Data Sharing Statement: See Supplement 2.

Additional Contributions: We thank Dean Long-Bin Jeng, PhD, Hsueh-Chou Lai, PhD, and Hung-Wei Wang, MD, China Medical University 1 Hospital, for their assistance in data collection. They were not compensated for their contributions.

^✉

Corresponding author.

PMCID: PMC11258634 PMID: 39023864

Key Points

Question

Do patients with unresectable hepatocellular carcinoma (HCC) and suboptimal liver function benefit from immunotherapy vs best supportive care?

Findings

In this case series of 343 patients with Child-Pugh class B liver dysfunction, immunotherapy-based systemic therapy was associated with significant reduction in the risk of death compared with best supportive care.

Meaning

The results of this study suggest that immunotherapy may be a safe and effective option for patients with unresectable HCC and suboptimal liver function.

Abstract

Importance

Whether patients with Child-Pugh class B (CP-B) cancer with unresectable hepatocellular carcinoma (uHCC) benefit from active anticancer treatment vs best supportive care (BSC) is debated.

Objective

To evaluate the association of immune checkpoint inhibitor (ICI)–based therapies vs BSC with overall survival (OS) of patients with uHCC and CP-B liver dysfunction.

Design, Setting, and Participants

This retrospective, multicenter, international clinical case series examined data of patients with CP-B with uHCC who were receiving first-line ICI-based regimens from September 2017 to December 2022 whose data were extracted from an international consortium and compared with a cohort of patients with CP-B receiving BSC. Patients were treated in tertiary care centers across Europe, US, and Asia in routine clinical practice. After applying the inclusion criteria, 187 and 156 patients were left in the ICI and BSC groups, respectively. The propensity score was calculated for the following variables: age, alpha-fetoprotein levels, Child-Pugh score, extrahepatic spread, portal vein tumor thrombosis, cirrhosis, ascites, and baseline Eastern Cooperative Oncology Group performance status.

Exposures

Patients in the ICI group received first-line systemic therapy with either atezolizumab plus bevacizumab (A+B) (n = 141) or nivolumab (n = 46).

Main Outcomes and Measures

OS in the inverse probability of treatment weighting (IPTW) populations was the main outcome, and it was estimated with Kaplan-Meier method; univariable Cox regression test was used to make comparisons between the 2 groups.

Results

The median age was 66 (IQR, 61-72) and 73 (IQR, 66-81) years in the ICI (33 women [18%]) and BSC groups (41 women [26%]), respectively. In the IPTW populations, median OS was significantly longer in the ICI group (7.50 months; 95% CI, 5.62-11.15) compared with BSC (4.04 months; 95% CI, 3.03-5.03; hazard ratio, 0.59; 95% CI, 0.43-0.80; P < .001). Multivariable analysis confirmed that ICI exposure was associated with a reduction of approximately 50% in the risk of death (hazard ratio, 0.55; 95% CI, 0.35-0.86; P < .001), and the presence of portal vein tumor thrombosis, an Eastern Cooperative Oncology Group performance score of greater than 1, and alpha-fetoprotein levels of 400 ng/mL or greater were associated with increased risk of death.

Conclusions and Relevance

The results of this case series provide comparative evidence of improved survival in association with ICI treatment compared with BSC in patients with uHCC with CP-B liver dysfunction.

This case series examines the association of immune checkpoint inhibitor–based therapies vs best supportive care with the overall survival of patients with unresectable hepatocellular carcinoma and Child-Pugh class B liver dysfunction.

Introduction

Hepatocellular carcinoma (HCC) is the most common primary liver tumor that generally arises via chronic liver inflammation and coexists with liver cirrhosis in up to 70% to 80% of the cases.¹ Liver dysfunction is not only associated with the prognosis, but may also affect the safe delivery of systemic anticancer therapy.² Concerns about the metabolism of chemotherapy and targeted therapies have led clinical trials for HCC to exclude patients with Child-Pugh (CP) class B (CP-B) liver dysfunction, promoting the widespread recommendation of best supportive care (BSC) for these patients.³

Despite the lack of level 1 evidence, recently published data on immune checkpoint inhibitors (ICIs) have provided encouraging (albeit uncontrolled) evidence for the use of immunotherapy in patients with CP-B liver dysfunction.⁴ However, most of the evidence produced to date has been uncontrolled and based on single-arm studies of selected patients with CP-B liver dysfunction, and whether delivering immunotherapy changes the natural history of patients with CP-B liver dysfunction and HCC remains debated. To satisfy this research question, we conducted a retrospective study building on 2 multicenter registries to comparatively evaluate the outcomes of ICI-based regimens with BSC.

Methods

Study Population

Ethical approval was granted by the Imperial College Tissue Bank and by local institutional review boards at each participating institution. Oral consent was provided to use deidentified data. Clinical data of patients affected by unresectable HCC (uHCC) with a CP liver function class B (score, 7-9) at the time of HCC diagnosis were extracted from an international consortium collecting data of consecutive patients with advanced/uHCC receiving ICI-based systemic treatment across Europe, the US, and Asia and from the Italian Liver Cancer dataset (eMethods 1 and eFigure 1 in Supplement 1).

Statistical Analysis

The main objective of the study was to compare outcomes of patients with CP-B liver dysfunction who were receiving immunotherapy-based active systemic anticancer treatment or BSC for uHCC. Details about the statistical analysis are reported in eMethods 2 in Supplement 1. Statistical analyses were carried out using R Studio, version 4.1.2 (R Foundation). The 2-tailed α level for all analyses was set at .05.

Results

Baseline Characteristics

We selected 187 patients with CP-B with uHCC who were not amenable to locoregional therapy treated with ICI-based therapies and 158 patients with CP-B with similar staging characteristics who received BSC only. In the ICI group, 141 were treated with atezolizumab plus bevacizumab (A+B), whereas 46 received nivolumab. Baseline characteristics are summarized in Table 1 and eTable 1 in Supplement 1.

Table 1. Differences in the Baseline Characteristics in the Active Treatment and Best Supportive Therapy Groups.

Characteristic	No. (%)		P value	Adjusted P value
Characteristic	Active treatment (n = 187)	BSC (n = 158)	P value	Adjusted P value
Age, median (range), y	66 (61-72)	73 (66-81)	<.001	.002
Age, y
≤69	95 (51)	134 (85)	<.001	.002
>69	92 (49)	24 (15)	<.001	.002
Sex
Female	33 (18)	41 (26)	.06	>.99
Male	154 (82)	117 (74)	.06	>.99
Origin
Asia	54 (29)	0	<.001	.002
Outside Asia	133 (71)	158 (100)	<.001	.002
BCLC
B	33 (18)	13 (8)	.01	.18
C or D	154 (82)	145 (92)	.01	.18
AFP, ng/mL
<400	101 (55)	125 (79)	.001	.02
≥400	86 (45)	33 (21)	.001	.02
Child-Pugh score/class
7-8	165 (88)	124 (78)	.02	.24
9	22 (12)	43 (22)	.02	.24
ALBI score
2	93 (50)	67 (43)	.33	>.99
3	94 (50)	91 (57)	.33	>.99
Cirrhosis
Yes	168 (90)	152 (96)	.02	.38
No	19 (10)	6 (4)	.02	.38
Ascites
Yes	122 (65)	119 (75)	.04	.70
No	65 (35)	39 (25)	.04	.70
Etiology
Viral	105 (56)	102 (65)	.11	>.99
Nonviral	82 (44)	56 (35)	.11	>.99
HBV
Yes	50 (27)	27 (17)	.03	.51
No	137 (73)	131 (83)	.03	.51
HCV
Yes	48 (26)	79 (50)	<.001	.002
No	139 (74)	79 (50)	<.001	.002
PVTT
Yes	115 (61)	63 (40)	<.001	.002
No	72 (39)	95 (60)	<.001	.002
EHS
Yes	92 (48)	24 (26)	<.001	.002
No	95 (52)	134 (74)	<.001	.002
ECOG score
>1	21 (11)	82 (52)	<.001	.002
0 or 1	166 (89)	75 (48)	<.001	.002

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Abbreviations: AFP, alpha-fetoprotein; ALBI, albumin-bilirubin; BCLC, Barcelona Clinic Liver Cancer; BSC, best supportive care; ECOG, Eastern Cooperative Oncology Group; EHS, extrahepatic spread; HBV, hepatitis B virus; HCV, hepatitis C virus; PVTT, portal vein tumoral thrombosis.

Outcomes for the Study Population

The median follow-up for the population receiving active treatment was 10.63 months (95% CI, 9.30-11.96) and 23.42 months for the BSC cohort (95% CI, 13.22-33.62). Details about outcomes for the whole cohort are reported in eResults 1 in Supplement 1.

IPTW Survival Analyses

In the IPTW populations, patients receiving active treatment reported a significantly longer median overall survival (OS) compared with BSC (7.50 months [95% CI, 5.62-11.15] vs 4.04 months [95% CI, 3.03-5.03]; hazard ratio [HR], 0.59; 95% CI, 0.43-0.80; P < .001; Figure). The IPTW-fitted multivariable analysis, including the groups of interest and those variables with an standard mean difference of greater than 0.10 after the weighting (eTable 3 in Supplement 1), confirmed ICI exposure to be significantly associated with a reduction in the risk of death (HR, 0.55; 95% CI, 0.40-0.74; P < .001), portal vein tumor thrombosis (PVTT), alpha-fetoprotein (AFP) levels of 400 ng/mL or greater, and an Eastern Cooperative Oncology Group (ECOG) performance status (PS) of greater than 1 conferred an increased risk of death (HR, 2.02; 95% CI, 1.53-2.66; P < .001; HR, 1.75; 95% CI, 1.32-2.31; P < .001; HR, 1.31; 95% CI, 1.00-1.73; P = .06; Table 2). Barcelona Clinic Liver Cancer stage was not included in the model to avoid collinearity; the single components were included as single variable (PVTT, extrahepatic spread, and ECOG PS). As reported for the unweighted population, the year of diagnosis did not have a prognostic association with the weighted models (eTables 4 and 5 in Supplement 1).

Figure. — B, Stratified according to the type of treatment (nivolumab and atezolizumab + bevacizumab [A+B]). HR indicates hazard ratio.

Table 2. Inverse Probability Treatment–Weighted Univariable and Multivariable Cox Regression Models for Overall Survival.

Characteristic	Univariable		Multivariable
Characteristic	HR (95% CI)	P value^a	HR (95% CI)	P value^b
Treatment (active treatment -BSC)	0.59 (0.43-0.80)	<.001	0.55 (0.40-0.74)	<.001
Age (≤69 y to >69 y)	0.94 (0.68-1.30)	.70
Sex (male-female)	1.31 (0.90-1.90)	.16	1.18 (0.86-1.61)	.31
BCLC (C/D-B)	1.25 (0.87-1.80)	.24
AFP (≥400 to <400)	1.67 (1.15-2.43)	.01	1.75 (1.32-2.31)	<.001
ALBI grade (3-2)	0.89 (0.65-1.22)	.46	NA	NA
Child-Pugh (9 to 7/8)	1.07 (0.68-1.68)	.78	NA	NA
Cirrhosis (yes-no)	0.64 (0.36-1.15)	.14	NA	NA
PVTT (yes-no)	2.04 (1.47-2.82)	<.001	2.02 (1.53-2.66)	<.001
EHS (yes-no)	1.35 (0.95-1.83)	.10	1.12 (0.81-1.54)	.48
Viral (yes-no)	0.92 (0.62-1.36)	.66	1.01 (0.75-1.31)	.93
Ascites (yes-no)	1.18 (0.88-1.58)	.28	0.90 (0.68-1.20)	.47
ECOG score (>1 to 0/1)	1.10 (0.74-1.62)	.65	1.31 (1.00-1.73)	.06

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Abbreviations: AFP, alpha-fetoprotein; ALBI, albumin-bilirubin; BCLC, Barcelona Clinic Liver Cancer; BSC, best supportive care; ECOG, Eastern Cooperative Oncology Group; EHS, extrahepatic spread; HR, hazard ratio; NA, not applicable; PVTT, portal vein tumoral thrombosis.

^{^a}

Harmonic mean P value for the model: P = .001.

^{^b}

Harmonic mean P value for the model: P < .001.

Subgroup Analyses

The benefit from the treatment was preserved in all the subgroups of interest, as well as in those characterized by worse prognosis in the multivariable model. A positive interaction with the treatment was found with AFP levels, albumin-bilirubin grade, and ascites (eTable 6 and eFigure 3 in Supplement 1).

Objective Response Rate and Progression-Free Survival

In the treatment group, objective response rates and disease control rates were 14.3% and 56.2%, respectively. The median progression-free survival for patients receiving active treatment was 3.16 months (95% CI, 2.93-4.34) (eFigure 4A and eResults 2 in Supplement 1).

Safety Profile

Overall, in the treatment group, 112 patients experienced at least 1 adverse event (AE); therefore, the incidence of all-cause AEs in treatment recipients was 58.9%. Twenty patients (10.7%) experienced at least 1 grade 3 or higher AE. No grade 5 AEs were reported during the treatment (eResults 3 in Supplement 1).

Discussion

During the last decade, the clinical outcomes of patients with uHCC have substantially improved.^5,6 However, clinical trials testing systemic therapies have consistently excluded those patients falling outside stringent CP class A criteria. Therefore, treatment allocation for patients with moderate liver dysfunction (CP-B) remains controversial.⁷ To fill this gap, we comparatively assessed clinical outcomes of patients with CP-B who were receiving ICIs vs BSC whose data were in large, multicenter, international registries.

In our IPTW analyses, treatment with A+B or nivolumab was associated with a statistically significant improvement in OS vs BSC independently from baseline characteristics. In the double-adjusted multivariable model, presence of PVTT and AFP levels of 400 ng/mL or greater emerged as independent factors that were associated with an increased risk of death. Patients with PVTT and AFP levels of 400 ng/mL or greater represent a population characterized by poorer survival even in the context of combination immunotherapy studies⁸ but who still benefit from ICI combinations in the presence of well-preserved liver function.⁹ Our subgroup analyses, despite being merely exploratory, suggested that the benefit of active treatment was maintained even in the presence of PVTT and elevated AFP levels, with a positive interaction between the treatment and AFP levels. From one side, this indicates that immunotherapy could be effective in the presence of more advanced oncological features; from the other, it suggests stratification factors for future trials enrolling patients with CP-B. As previously shown, our study confirmed that anti–programmed cell death 1 and anti–programmed cell death 1 ligand 1/vascular endothelial growth factor combination therapy was characterized by an acceptable safety profile, with incidence and severity of AEs consistent with data in patients with CP class A.^5,10,11

Treatment discontinuations secondary to AEs were less than 10%, the proportion of grade 3 or higher AEs was 11%, and bleeding events were 13.2%, suggesting that patients with CP-B can tolerate immunotherapy without significant concerns. Even if direct comparison between A+B vs nivolumab was outside the scope of this article, a significant difference in efficacy between the 2 strategies did not emerge from our data in terms of OS, progression-free survival, and overall treatment duration.

Limitations

There were several limitations that applied to our study: the retrospective design was accompanied by an inherent risk of selection bias and unmeasured confounders that cannot be fully addressed even after adopting stringent statistical adjustments. Furthermore, in the absence of central adjudication of efficacy and safety outcomes, toxic effects and radiologic response data may have experienced interrater heterogeneity. Lastly, without prospective allocation and randomization, positive associations between treatment allocation and survival cannot be interpreted as causative.

Conclusions

To our knowledge, this case series was the first to provide a comparative assessment in the efficacy of ICI-based therapies in patients with advanced HCC and CP-B liver dysfunction. In the absence of high-quality, prospective, comparative data against placebo, our results, strengthened by stringent propensity score weighting methods, potentially provide a useful benchmark for estimating survival benefit in patients with CP-B to further assess ICI-based therapies in dedicated prospective studies.

Supplement 1.

eTable 1. Differences in baseline characteristics according to the treatment arm

eTable 2. Univariable and multivariable Cox regression models for overall survival in the whole population

eTable 3. Baseline characteristics and SMD before and after weighting in the SACT and BSC arms

eTable 4. Univariable and multivariable Cox regression models for overall survival in the whole population including the time at diagnosis

eTable 5. Univariable and multivariable Cox regression models for overall survival in the weighted population. including the time at diagnosis

eTable 6. Univariable subgroup analysis for overall survival in the weighted population

eTable 7. Univariable and multivariable Cox regression models for progression free survival

eFigure 1. Consort diagram for the study population

eFigure 2. Kaplan-Meier plots for overall survival (OS) in the BSC and ICI-exposed unweighted populations

eFigure 3. Forest plot of subgroup analysis of overall survival

eFigure 4. Kaplan-Meier plots for progression free survival (PFS) in the ICI-exposed population

eMethods 1. Study population

eMethods 2. Statistical analyses

eResults 1. Results in the whole population

eResults 2. Radiological response and progression free survival

eResults 3. Safety profile

eReferences.

jamaoncol-e242166-s001.pdf^{(735.5KB, pdf)}

Supplement 2.

Data sharing statement

jamaoncol-e242166-s002.pdf^{(16KB, pdf)}

References

1.Galati G, Massimo Vainieri AF, Maria Fulgenzi CA, et al. Current treatment options for HCC: from pharmacokinetics to efficacy and adverse events in liver cirrhosis. Curr Drug Metab. 2020;21(11):866-884. doi: 10.2174/1389200221999200918141239 [DOI] [PubMed] [Google Scholar]
2.Fulgenzi CAM, D’Alessio A, Ogunbiyi O, et al. Novel immunotherapy combinations in clinical trials for hepatocellular carcinoma: will they shape the future treatment landscape? Expert Opin Investig Drugs. 2022;31(7):681-691. doi: 10.1080/13543784.2022.2072726 [DOI] [PubMed] [Google Scholar]
3.Reig M, Forner A, Rimola J, et al. BCLC strategy for prognosis prediction and treatment recommendation: the 2022 update. J Hepatol. 2022;76(3):681-693. doi: 10.1016/j.jhep.2021.11.018 [DOI] [PMC free article] [PubMed] [Google Scholar]
4.Fessas P, Kaseb A, Wang Y, et al. Post-registration experience of nivolumab in advanced hepatocellular carcinoma: an international study. J Immunother Cancer. 2020;8(2):e001033. doi: 10.1136/jitc-2020-001033 [DOI] [PMC free article] [PubMed] [Google Scholar]
5.Finn RS, Qin S, Ikeda M, et al. ; IMbrave150 Investigators . Atezolizumab plus bevacizumab in unresectable hepatocellular carcinoma. N Engl J Med. 2020;382(20):1894-1905. doi: 10.1056/NEJMoa1915745 [DOI] [PubMed] [Google Scholar]
6.Finn RS, Kudo M, Merle P, et al. LBA34 primary results from the phase III LEAP-002 study: lenvatinib plus pembrolizumab versus lenvatinib as first-line (1L) therapy for advanced hepatocellular carcinoma (aHCC). Ann Oncol. 2022;33(suppl 7). doi: 10.1016/j.annonc.2022.08.031 [DOI] [Google Scholar]
7.Pinter M, Scheiner B, Pinato DJ. Immune checkpoint inhibitors in hepatocellular carcinoma: emerging challenges in clinical practice. Lancet Gastroenterol Hepatol. 2023;8(8):760-770. doi: 10.1016/S2468-1253(23)00147-4 [DOI] [PubMed] [Google Scholar]
8.Fulgenzi CAM, Cheon J, D’Alessio A, et al. Reproducible safety and efficacy of atezolizumab plus bevacizumab for HCC in clinical practice: results of the AB-real study. Eur J Cancer. 2022;175:204-213. doi: 10.1016/j.ejca.2022.08.024 [DOI] [PubMed] [Google Scholar]
9.Fulgenzi CAM, Scheiner B, Korolewicz J, et al. Efficacy and safety of frontline systemic therapy for advanced HCC: A network meta-analysis of landmark phase III trials. JHEP Rep. 2023;5(5):100702. doi: 10.1016/j.jhepr.2023.100702 [DOI] [PMC free article] [PubMed] [Google Scholar]
10.Kudo M, Matilla A, Santoro A, et al. CheckMate 040 cohort 5: a phase I/II study of nivolumab in patients with advanced hepatocellular carcinoma and Child-Pugh B cirrhosis. J Hepatol. 2021;75(3):600-609. doi: 10.1016/j.jhep.2021.04.047 [DOI] [PubMed] [Google Scholar]
11.Fulgenzi CAM, D’Alessio A, Airoldi C, et al. Comparative efficacy of novel combination strategies for unresectable hepatocellular carcinoma: a network metanalysis of phase III trials. Eur J Cancer. 2022;174:57-67. doi: 10.1016/j.ejca.2022.06.058 [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement 1.

eTable 1. Differences in baseline characteristics according to the treatment arm

eTable 2. Univariable and multivariable Cox regression models for overall survival in the whole population

eTable 3. Baseline characteristics and SMD before and after weighting in the SACT and BSC arms

eTable 4. Univariable and multivariable Cox regression models for overall survival in the whole population including the time at diagnosis

eTable 5. Univariable and multivariable Cox regression models for overall survival in the weighted population. including the time at diagnosis

eTable 6. Univariable subgroup analysis for overall survival in the weighted population

eTable 7. Univariable and multivariable Cox regression models for progression free survival

eFigure 1. Consort diagram for the study population

eFigure 2. Kaplan-Meier plots for overall survival (OS) in the BSC and ICI-exposed unweighted populations

eFigure 3. Forest plot of subgroup analysis of overall survival

eFigure 4. Kaplan-Meier plots for progression free survival (PFS) in the ICI-exposed population

eMethods 1. Study population

eMethods 2. Statistical analyses

eResults 1. Results in the whole population

eResults 2. Radiological response and progression free survival

eResults 3. Safety profile

eReferences.

jamaoncol-e242166-s001.pdf^{(735.5KB, pdf)}

Supplement 2.

Data sharing statement

jamaoncol-e242166-s002.pdf^{(16KB, pdf)}

[cbr240013r1] 1.Galati G, Massimo Vainieri AF, Maria Fulgenzi CA, et al. Current treatment options for HCC: from pharmacokinetics to efficacy and adverse events in liver cirrhosis. Curr Drug Metab. 2020;21(11):866-884. doi: 10.2174/1389200221999200918141239 [DOI] [PubMed] [Google Scholar]

[cbr240013r2] 2.Fulgenzi CAM, D’Alessio A, Ogunbiyi O, et al. Novel immunotherapy combinations in clinical trials for hepatocellular carcinoma: will they shape the future treatment landscape? Expert Opin Investig Drugs. 2022;31(7):681-691. doi: 10.1080/13543784.2022.2072726 [DOI] [PubMed] [Google Scholar]

[cbr240013r3] 3.Reig M, Forner A, Rimola J, et al. BCLC strategy for prognosis prediction and treatment recommendation: the 2022 update. J Hepatol. 2022;76(3):681-693. doi: 10.1016/j.jhep.2021.11.018 [DOI] [PMC free article] [PubMed] [Google Scholar]

[cbr240013r4] 4.Fessas P, Kaseb A, Wang Y, et al. Post-registration experience of nivolumab in advanced hepatocellular carcinoma: an international study. J Immunother Cancer. 2020;8(2):e001033. doi: 10.1136/jitc-2020-001033 [DOI] [PMC free article] [PubMed] [Google Scholar]

[cbr240013r5] 5.Finn RS, Qin S, Ikeda M, et al. ; IMbrave150 Investigators . Atezolizumab plus bevacizumab in unresectable hepatocellular carcinoma. N Engl J Med. 2020;382(20):1894-1905. doi: 10.1056/NEJMoa1915745 [DOI] [PubMed] [Google Scholar]

[cbr240013r6] 6.Finn RS, Kudo M, Merle P, et al. LBA34 primary results from the phase III LEAP-002 study: lenvatinib plus pembrolizumab versus lenvatinib as first-line (1L) therapy for advanced hepatocellular carcinoma (aHCC). Ann Oncol. 2022;33(suppl 7). doi: 10.1016/j.annonc.2022.08.031 [DOI] [Google Scholar]

[cbr240013r7] 7.Pinter M, Scheiner B, Pinato DJ. Immune checkpoint inhibitors in hepatocellular carcinoma: emerging challenges in clinical practice. Lancet Gastroenterol Hepatol. 2023;8(8):760-770. doi: 10.1016/S2468-1253(23)00147-4 [DOI] [PubMed] [Google Scholar]

[cbr240013r8] 8.Fulgenzi CAM, Cheon J, D’Alessio A, et al. Reproducible safety and efficacy of atezolizumab plus bevacizumab for HCC in clinical practice: results of the AB-real study. Eur J Cancer. 2022;175:204-213. doi: 10.1016/j.ejca.2022.08.024 [DOI] [PubMed] [Google Scholar]

[cbr240013r9] 9.Fulgenzi CAM, Scheiner B, Korolewicz J, et al. Efficacy and safety of frontline systemic therapy for advanced HCC: A network meta-analysis of landmark phase III trials. JHEP Rep. 2023;5(5):100702. doi: 10.1016/j.jhepr.2023.100702 [DOI] [PMC free article] [PubMed] [Google Scholar]

[cbr240013r10] 10.Kudo M, Matilla A, Santoro A, et al. CheckMate 040 cohort 5: a phase I/II study of nivolumab in patients with advanced hepatocellular carcinoma and Child-Pugh B cirrhosis. J Hepatol. 2021;75(3):600-609. doi: 10.1016/j.jhep.2021.04.047 [DOI] [PubMed] [Google Scholar]

[cbr240013r11] 11.Fulgenzi CAM, D’Alessio A, Airoldi C, et al. Comparative efficacy of novel combination strategies for unresectable hepatocellular carcinoma: a network metanalysis of phase III trials. Eur J Cancer. 2022;174:57-67. doi: 10.1016/j.ejca.2022.06.058 [DOI] [PubMed] [Google Scholar]

PERMALINK

Immunotherapy vs Best Supportive Care for Patients With Hepatocellular Cancer With Child-Pugh B Dysfunction

Claudia Angela Maria Fulgenzi, MD

Bernhard Scheiner, PhD

Antonio D’Alessio, MD

Aman Mehan, MD

Giulia F Manfredi, MD

Ciro Celsa, PhD

Naoshi Nishida, MD

Celina Ang, MD

Thomas U Marron, PhD

Linda Wu, MD

Anwaar Saeed, MD

Brooke Wietharn, MD

Antonella Cammarota, MD

Tiziana Pressiani, MD

Matthias Pinter, PhD

Rohini Sharma, PhD

Jaekyung Cheon, MD

Yi-Hsiang Huang, PhD

Pei-Chang Lee, MD

Samuel Phen, MD

Anuhya Gampa, MD

Anjana Pillai, PhD

Andrea Napolitano, PhD

Caterina Vivaldi, PhD

Francesca Salani, MD

Gianluca Masi, PhD

Marianna Silletta, PhD

Federica Lo Prinzi, MD

Emanuela Di Giacomo, MD

Bruno Vincenzi, PhD

Dominik Bettinger, PhD

Robert Thimme, PhD

Arndt Vogel, PhD

Martin Schönlein, MD

Johann von Felden, MD

Kornelius Schulze, PhD

Henning Wege, PhD

Peter R Galle, PhD

Mario Pirisi, PhD

Joong-Won Park, PhD

Masatoshi Kudo, PhD

Lorenza Rimassa, MD

Amit G Singal, MD

Paul El Tomb, MD

Susanna Ulahannan, MD

Alessandro Parisi, MD

Hong Jae Chon, PhD

Wei-Fan Hsu, PhD

Giorgia Ghittoni, MD

Calogero Cammà, PhD

Benedetta Stefanini, MD

Franco Trevisani, PhD

Edoardo G Giannini, PhD

Alessio Cortellini, PhD

David James Pinato, MD, PhD

Key Points

Question

Findings

Meaning

Abstract

Importance

Objective

Design, Setting, and Participants

Exposures

Main Outcomes and Measures

Results

Conclusions and Relevance

Introduction

Methods

Study Population

Statistical Analysis

Results

Baseline Characteristics

Table 1. Differences in the Baseline Characteristics in the Active Treatment and Best Supportive Therapy Groups.

Outcomes for the Study Population

IPTW Survival Analyses

Figure. Overall Survival (OS) in the Best Supportive Care (BSC) and Immune Checkpoint Inhibitor (ICI)–Exposed Inverse Probability of Treatment Weighting Populations.

Table 2. Inverse Probability Treatment–Weighted Univariable and Multivariable Cox Regression Models for Overall Survival.