Abstract
Background/Aims
Atezolizumab and bevacizumab have shown promising results for the treatment of advanced hepatocellular carcinoma (HCC) in clinical trials. In this study, the real-world efficacy and safety of atezolizumab and bevacizumab in treating advanced HCC were evaluated.
Methods
In this retrospective study of patients at a Korean tertiary cancer center, 111 patients with Barcelona Clinic Liver Cancer stage B or C HCC received atezolizumab and bevacizumab as first-line therapy from May 2022 to June 2023. We assessed the progression-free survival (PFS), overall response rate (ORR), disease control rate (DCR), and adverse events.
Results
Patients with Barcelona Clinic Liver Cancer stage C HCC and Child-Pugh class A liver function were included in the study. The median PFS was 6.5 months, with an ORR of 27% and a DCR of 63%. Several factors, including the albumin-bilirubin grade, age, C-reactive protein and α-fetoprotein in immunotherapy score, macrovascular invasion, lung metastases, and combined radiotherapy, were found to significantly influence PFS (p<0.05). Patients with peritoneal seeding showed an higher ORR. The safety profile was consistent with that observed in clinical trials.
Conclusions
Atezolizumab and bevacizumab demonstrated real-world efficacy in the treatment of advanced HCC, with ORRs and DCRs aligning with those observed in clinical trials. Variations in PFS and ORR based on specific risk factors highlight the potential of atezolizumab and bevacizumab in precision medicine for advanced HCC. (Gut Liver, Published online June 27, 2024)
Keywords: Hepatocellular carcinoma, Liver neoplasms, Systemic therapy, Immunotherapy
INTRODUCTION
Advanced hepatocellular carcinoma (HCC) remains a leading cause of cancer-related deaths worldwide, with increasing incidence and mortality rates globally.1,2 Despite advancements in diagnosis and management, HCC presents significant challenges due to late diagnosis and limited effective treatment options in advanced stages.3,4
The combination of atezolizumab, a programmed death-ligand 1 inhibitor, and bevacizumab, an anti-vascular endothelial growth factor antibody, has emerged as a promising treatment for patients with advanced HCC.5 This combination has shown significant benefits in clinical trials, including improved survival rates and better tolerability compared to previous standard therapies.6 The synergistic action of atezolizumab and bevacizumab, targeting both tumor cells and the tumor microenvironment, represents a paradigm shift in the management of advanced HCC.7
Despite the clinical promise of atezolizumab-bevacizumab, there remains a notable gap in understanding its real-world effectiveness and application. Many studies have focused on controlled clinical trial settings, which may not fully represent the diverse patient populations encountered in routine clinical practice. Our study aimed to bridge this gap by evaluating the real-world application and effectiveness of atezolizumab and bevacizumab in treating patients with advanced HCC. We also performed a comprehensive analysis of prognostic factors in patients with advanced HCC receiving atezolizumab and bevacizumab.
MATERIALS AND METHODS
1. Study population and design
This single-center, retrospective study was conducted at Samsung Medical Center, a tertiary hospital in South Korea, focusing on patients treated with atezolizumab and bevacizumab for advanced HCC between May 2022 and June 2023 (n=128). Patients were included if they had a diagnosis of advanced HCC according to the regional guidelines and received atezolizumab and bevacizumab treatment.8,9 We excluded patients with incomplete medical records, those who did not have a response evaluation before June 2023 or transferred before response evaluation, and those who received fewer than three cycles of atezolizumab and bevacizumab (n=17). The patients received 1,200 mg of atezolizumab plus 15 mg/kg of body weight of bevacizumab intravenously every 3 weeks. Treatment continued until disease progression, unacceptable toxicity, or patient withdrawal.
The study was conducted in accordance with the Declaration of Helsinki. The Institutional Review Board of the Samsung Medical Center approved the study and waived the requirement for informed consent, as only de-identified data that were routinely collected during patient visits were used (IRB number: 2024-01-028).
2. Data collection and study variables
Demographic characteristics, past medical history, etiology of liver disease, prior local treatments, and Eastern Cooperative Oncology Group performance status were collected through comprehensive electronic medical record reviews. Blood test results including neutrophil counts, lymphocyte counts, albumin, total bilirubin, platelet counts, prothrombin time, aminotransferase, C-reactive protein, α-fetoprotein (AFP), and protein induced by vitamin K absence or antagonist (PIVKA) levels at baseline were collected. Cirrhosis was defined as the presence of any of the following characteristics: coarse liver echotexture and nodular liver surface on imaging; clinical features of portal hypertension (e.g., ascites, splenomegaly, and varices); and platelet count <100×10³/μL). All patients underwent comprehensive imaging assessments within 1 month prior to initiating atezolizumab and bevacizumab treatment. Dynamic liver and pelvis computed tomography (CT), magnetic resonance imaging, chest CT, bone scan, and positron emission tomography-CT scans were selectively used to evaluate the presence of distant metastasis, macrovascular invasion, and other high-risk features, such as Vp4 portal vein tumor thrombus, bile duct invasion, and extensive liver infiltration (defined as the involvement of more than 50% of the liver parenchyma).6
3. Outcome and safety assessment
The primary outcome was progression-free survival (PFS). PFS was defined as the time from treatment initiation to disease progression or death from any cause. The secondary outcome was the best-response rates defined as complete response (CR), partial response (PR), stable disease, and progressive disease. Response evaluations were conducted every three cycles using Response Evaluation Criteria in Solid Tumors (RECIST 1.1) and modified RECIST for HCC (mRECIST) criteria.10,11 These criteria were employed to standardize the assessment of tumor response and progression.
Safety was evaluated by clinical examination and laboratory test results. Treatment-related adverse events were reported using CTCAE version 5.0, a standardized classification developed by the National Cancer Institute for reporting the severity of adverse effects in clinical trials involving cancer therapies.
4. Analysis of prognostic factors and statistics
Categorical variables are reported as numbers and percentages and compared using the chi-square test or Fisher exact test, as appropriate. Continuous variables are reported as median range or mean±standard deviation and compared using the Student t-test or the Mann-Whitney U test. Survival curves were calculated using the Kaplan-Meier method and compared using the log-rank test. Univariable and multivariable Cox proportional hazard models were used to determine the independent risk factors for PFS. We only included the variables of age, sex, Eastern Cooperative Oncology Group performance status, neutrophil-to-lymphocyte ratio (NLR) at a threshold of 4.0, albumin-bilirubin (ALBI) grade, the C-reactive protein and α-fetoprotein in immunotherapy (CRAFITY) score, PIVKA-II, etiology categorized as viral or non-viral, and the presence or absence of high-risk features to avoid overlapping variables.
We stratified patients based on several key factors, including etiology (viral vs non-viral), NLR (>4.0 vs ≤4.0), Child-Turcotte-Pugh class, ALBI grade, CRAFITY score, Barcelona Clinic Liver Cancer (BCLC) stage, and the presence of high-risk features, and then compared PFS using Kaplan-Meier curves and the log-rank test. Statistical significance was set at a p-value of <0.05. Statistical analyses were performed using R version 4.1.2 software (R Foundation for Statistical Computing, Vienna, Austria).
RESULTS
1. Baseline characteristics
Table 1 shows the demographic and clinical characteristics of the 111 patients in our study. The patients were predominantly male (78%), with a median age of 61 years. The majority of the patients had Child-Turcotte-Pugh grade A liver function (92%) and Eastern Cooperative Oncology Group performance status 0 (87%). In terms of disease characteristics, 82% were at BCLC stage C, with macrovascular invasion in 38% and high-risk features in 33%. Lung metastasis (26%), lymph node metastasis (27%), and bone metastasis (17%) were the most prevalent metastasis sites. The most common etiology was hepatitis B virus infection (71%). Additionally, 60% had received prior local therapy, with 19% showing transarterial chemoembolization refractoriness.
Table 1.
Baseline Characteristics
| Characteristic | Value (n=111) |
|---|---|
| Age, yr | 61 (52–69) |
| Male sex | 87 (78.4) |
| Hypertension | 59 (53.2) |
| Diabetes mellitus | 33 (29.7) |
| Dyslipidemia | 26 (23.4) |
| ECOG PS | |
| 0 | 97 (87.4) |
| 1 | 14 (12.6) |
| NLR | 2.59 (1.86–3.79) |
| Albumin, g/dL | 3.90 (3.60–4.30) |
| Total bilirubin, mg/dL | 0.70 (0.50–0.90) |
| Platelet count, ×109/L | 172 (118–226) |
| ALBI grade | |
| 1 | 61 (55.0) |
| 2 | 50 (45.0) |
| PT INR | 1.07 (1.01–1.11) |
| Alanine aminotransferase, IU/L | 29 (18–41) |
| C-reactive protein, mg/dL* | 0.6 (0.2–2.2) |
| α-Fetoprotein, ng/mL | 55.7 (6.6–1,762) |
| PIVKA-II, mAU/mL* | 545.5 (58.0–5,041) |
| CRAFITY score | |
| 0 | 23 (20.7) |
| 1 | 39 (35.1) |
| 2 | 13 (11.7) |
| Not available | 36 (32.5) |
| CTP score | |
| 5 | 75 (67.6) |
| 6 | 27 (24.3) |
| 7 | 9 (8.1) |
| CTP class | |
| A | 102 (91.9) |
| B | 9 (8.1) |
| BCLC stage | |
| B | 20 (18.0) |
| C | 91 (82.0) |
| Macrovascular invasion | 42 (37.8) |
| High-risk features† | 37 (33.3) |
| Vp4 PVTT | 21 (18.9) |
| Bile duct invasion | 6 (5.4) |
| Liver infiltration ≥50% | 18 (16.2) |
| Distant metastasis | |
| Lung | 29 (26.1) |
| Lymph node | 30 (27.0) |
| Bone | 19 (17.1) |
| Peritoneal seeding | 9 (8.1) |
| Adrenal | 5 (4.5) |
| None | 19 (17.1) |
| Etiology | |
| Alcohol use | 7 (6.3) |
| HBV infection | 79 (71.2) |
| HCV infection | 8 (7.2) |
| Others | 17 (15.3) |
| Prior local therapy | 67 (60.4) |
| TACE refractoriness | 21 (18.9) |
Data are presented as median (interquartile range) or number (%).
ECOG PS, Eastern Cooperative Oncology Group performance status; NLR, neutrophil-to-lymphocyte ratio; ALBI, albumin-bilirubin; PT, prothrombin time; INR, international normalized ratio; PIVKA, protein induced by vitamin K absence; CRAFITY, C-reactive protein and α-fetoprotein in immunotherapy; CTP, Child-Turcotte-Pugh; BCLC, Barcelona Liver Cancer; PVTT, portal vein tumor thrombosis; HBV, hepatitis B virus; HCV, hepatitis C virus; TACE, transarterial chemoembolization.
*Missing information on C-reactive protein for 36 patients, PIVKA-II for 1 patient; †Patients with high-risk features overlap among subcategories, with some counted in multiple categories.
2. PFS and overall survival
During the median follow-up of 5.1 months (2.5 to 6.1 months), the median PFS was 6.5 months (5.1 to 8.9 months). Median overall survival was not reached. The observed 12-month survival rate was 79.1% (Fig. 1).
Fig. 1.
Progression-free survival (A) and overall survival (B) of patients receiving atezolizumab and bevacizumab.
PFS was compared according to liver disease etiology, BCLC stage, the presence of high-risk features, and ALBI grade (Fig. 2). No statistically significant difference between non-viral and viral groups was found in the analysis of PFS categorized by etiology. Similarly, no significant difference in PFS was observed when the patients were stratified according to BCLC stage B and C, and no significant differences were observed between patients with and without high-risk features. However, patients with ALBI grade 1 had significantly longer PFS compared to those with ALBI grade 2 (p<0.05). The NLR did not show significant results (p=0.95), while the CRAFITY score was associated with a statistically significant difference in PFS (p=0.017) (Fig. 3).
Fig. 2.
Comparison of progression-free survival according to predefined prognostic factors. (A) Etiology, (B) BCLC stage, (C) the presence of high-risk features, and (D) ALBI grade. ALBI, albumin-bilirubin; BCLC, Barcelona Liver Cancer.
Fig. 3.
Comparison of progression-free survival based on potential prognostic factors. (A) Neutrophil-to-lymphocyte ratio and (B) CRAFITY score.
3. Objective response rate and disease control rate
Among 111 patients, the disease control rate (DCR), defined as the sum of CRs, PRs, and stable disease, was calculated. Out of the cohort, five patients (4.5%) achieved CR, while 25 patients (22.5%) exhibited PR, and 40 patients (36%) maintained stable disease. Consequently, the DCR for this study was 63%. The overall response rate (ORR), which was the proportion of patients who achieved either CR or PR, was found to be 27%.
Tables 2 and 3 present a comparative analysis of baseline characteristics based on the presence of an objective response among the study participants. Age, sex, and etiology did not differ significantly across the best-response categories (p=0.297, p=0.777, and p=0.162, respectively). The AFP levels were markedly higher in the progressive disease group (p=0.004). The analysis did not reveal any significant differences in PIVKA or C-reactive protein levels across the best-response categories. The NLR, Child-Turcotte-Pugh class, CRAFITY score, and BCLC staging did not show statistical significance in relation to the best treatment response. Notably, patients with peritoneal seeding had a higher likelihood of CR (p<0.001). Also, those who received combined radiotherapy had significantly better overall responses (CR 20% and PR 44%). Other factors, such as lung, lymph node, bone metastasis, and prior local treatment, were not significantly associated with the best response.
Table 2.
Comparison of Baseline Characteristics According to the Best Response
| Characteristic | CR (n=5) | PR (n=25) | SD (n=40) | PD (n=41) | p-value |
|---|---|---|---|---|---|
| Age, yr | 64.0±17.4 | 60.7±10.8 | 62.0±11.2 | 57.6±10.8 | 0.297 |
| Male sex | 3 (60.0) | 20 (80.0) | 32 (80.0) | 32 (78.0) | 0.777 |
| Etiology | 0.162 | ||||
| Non-viral | 0 | 4 (16.0) | 13 (32.5) | 7 (17.1) | |
| Viral | 5 (100) | 21 (84.0) | 27 (67.5) | 34 (82.9) | |
| ALBI grade | 0.090 | ||||
| 1 | 5 (100) | 15 (60.0) | 23 (57.5) | 18 (43.9) | |
| 2 | 0 | 10 (40.0) | 17 (42.5) | 23 (56.1) | |
| AFP, ng/mL | 40.8 (40.7–160) | 6.8 (3.0–196) | 22.1 (7.4–543) | 343.0 (21.9–32,750) | 0.004 |
| PIVKA-II, mAU/mL | 575 (443–710) | 631 (54.0–7,481) | 401 (71.0–5,126) | 580 (58.0–4,776) | 0.991 |
| CRP, mg/dL | 0.2 (0.1–0.4) | 0.9 (0.2–2.5) | 0.8 (0.2–2.1) | 0.7 (0.2–3.9) | 0.414 |
| NLR | 0.896 | ||||
| ≤4.0 | 4 (80.0) | 18 (72.0) | 32 (80.0) | 32 (78.0) | |
| >4.0 | 1 (20.0) | 7 (28.0) | 8 (20.0) | 9 (22.0) | |
| CTP class | 0.313 | ||||
| A | 5 (100.0) | 22 (88.0) | 39 (97.5) | 36 (87.8) | |
| B | 0 | 3 (12.0) | 1 (2.5) | 5 (12.2) | |
| CRAFITY score* | 0.337 | ||||
| 0 | 3 (75.0) | 6 (35.3) | 7 (29.2) | 7 (23.3) | |
| 1 | 1 (25.0) | 9 (52.9) | 14 (58.3) | 15 (50.0) | |
| 2 | 0 | 2 (11.8) | 3 (12.5) | 8 (26.7) | |
| BCLC | 0.324 | ||||
| B | 1 (20.0) | 4 (16.0) | 7 (17.5) | 8 (19.5) | |
| C | 4 (80.0) | 21 (84.0) | 33 (82.5) | 33 (80.5) | |
| Macrovascular invasion | 0 | 11 (44.0) | 15 (37.5) | 16 (39.0) | 0.324 |
| High-risk features | 0 | 9 (36.0) | 15 (37.5) | 13 (31.7) | 0.401 |
| Prior local treatment | 4 (80.0) | 16 (64.0) | 21 (52.5) | 26 (63.4) | 0.544 |
| Combined RT | 1 (20.0) | 11 (44.0) | 10 (25.0) | 2 (4.9) | 0.002 |
| Lung metastasis | 0 | 3 (12.0) | 12 (30.0) | 14 (34.1) | 0.110 |
| LN metastasis | 1 (20.0) | 10 (40.0) | 10 (25.0) | 9 (22.0) | 0.411 |
| Bone metastasis | 2 (40.0) | 5 (20.0) | 6 (15.0) | 6 (14.6) | 0.513 |
| Peritoneal seeding | 3 (60.0) | 4 (16.0) | 2 (5.0) | 0 | <0.001 |
Data are presented as mean±standard deviation, number (%), or median (interquartile range).
CR, complete response; PR, partial response; SD, stable disease; PD, progressive disease; ALBI, albumin-bilirubin; AFP, a-fetoprotein; PIVKA, protein induced by vitamin K absence or antagonist; CRP, C-reactive protein; NLR, neutrophil-to-lymphocyte ratio; CTP, Child-Turcotte-Pugh; CRAFITY, C-reactive protein and α-fetoprotein in immunotherapy; BCLC, Barcelona Liver Cancer; RT, radiotherapy; LN, lymph node.
*Missing information on CRAFITY score for 36 patients.
Table 3.
Comparison of Baseline Characteristics According to Objective Response
| Characteristic | Objective response (n=30) | No objective response (n=81) | p-value |
|---|---|---|---|
| Age, yr | 63.2 (52.3–70.2) | 60.0 (51.5–68.4) | 0.496 |
| Male sex | 23 (76.7) | 64 (79.0) | 0.994 |
| Etiology | 0.302 | ||
| Non-viral | 4 (13.3) | 20 (24.7) | |
| Viral | 26 (86.7) | 61 (75.3) | |
| ALBI grade | 0.195 | ||
| 1 | 20 (66.7) | 41 (50.6) | |
| 2 | 10 (33.3) | 40 (49.4) | |
| AFP, ng/mL | 8.6 (3.4–196.0) | 102.0 (8.8–7,457) | 0.010 |
| PIVKA-II, mAU/mL | 603.0 (57.0–2,348) | 500.0 (59.5–5,062) | 0.965 |
| CRP, mg/dL | 0.4 (0.1–1.7) | 0.7 (0.2–2.8) | 0.532 |
| NLR | 0.704 | ||
| ≤4.0 | 22 (73.3) | 64 (79.0) | |
| >4.0 | 8 (26.7) | 17 (21.0) | |
| CTP class | 0.958 | ||
| A | 27 (90.0) | 75 (92.6) | |
| B | 3 (10.0) | 6 (7.4) | |
| CRAFITY score* | 0.280 | ||
| 0 | 9 (42.9) | 14 (25.9) | |
| 1 | 10 (47.6) | 29 (53.7) | |
| 2 | 2 (9.5) | 11 (20.4) | |
| BCLC | 1.000 | ||
| B | 5 (16.7) | 15 (18.5) | |
| C | 25 (83.3) | 66 (81.5) | |
| Macrovascular invasion | 11 (36.7) | 31 (38.3) | 1.000 |
| High-risk features | 9 (30.0) | 28 (34.6) | 0.821 |
| Prior local treatment | 20 (66.7) | 47 (58.0) | 0.543 |
| Combined RT | 12 (40.0) | 12 (14.8) | 0.009 |
| Lung metastasis | 3 (10.0) | 26 (32.1) | 0.035 |
| LN metastasis | 11 (36.7) | 19 (23.5) | 0.250 |
| Bone metastasis | 7 (23.3) | 12 (14.8) | 0.439 |
| Peritoneal seeding | 7 (23.3) | 2 (2.5) | 0.001 |
Data are presented as median (interquartile range) or number (%).
ALBI, albumin-bilirubin; AFP, a-fetoprotein; PIVKA, protein induced by vitamin K absence or antagonist; CRP, C-reactive protein; NLR, neutrophil-to-lymphocyte ratio; CTP, Child-Turcotte-Pugh; CRAFITY, C-reactive protein and α-fetoprotein in immunotherapy; BCLC, Barcelona Liver Cancer; RT, radiotherapy; LN, lymph node.
*Missing information on CRAFITY score for 36 patients.
4. Predictors associated with PFS
In the Cox regression analysis for PFS, age (adjusted hazard ratio [HR], 0.97; 95% confidence interval [CI], 0.94 to 0.00; p=0.024), ALBI grade 2 (adjusted HR, 2.22; 95% CI, 1.13 to 4.34; p=0.020), CRAFITY score 2 (adjusted HR, 3.74; 95% CI, 1.34 to 10.40; p=0.012), macrovascular invasion (adjusted HR, 2.27; 95% CI, 1.06 to 4.87; p=0.035), lung metastasis (adjusted HR, 3.94; 95% CI, 1.96 to 7.91; p<0.001), and combined radiotherapy (adjusted HR, 0.15; 95% CI, 0.04 to 0.55; p=0.004) were significant factors (Table 4).
Table 4.
Univariable and Multivariable Cox Regression Analyses of Progression-Free Survival
| Variable | Univariable analysis | Multivariable analysis | |||
|---|---|---|---|---|---|
| HR (95% CI) | p-value | HR (95% CI) | p-value | ||
| Age, yr | 0.97 (0.95–0.99) | 0.004 | 0.97 (0.94–1.00) | 0.024 | |
| Male sex | 0.77 (0.43–1.35) | 0.357 | |||
| ALBI grade | 0.047 | 0.020 | |||
| 1 | Reference | Reference | |||
| 2 | 1.66 (1.01–2.73) | 2.22 (1.13–4.34) | |||
| CRAFITY score | |||||
| 0 | Reference | Reference | |||
| 1 | 2.07 (0.96–4.48) | 0.064 | 1.49 (0.64–3.49) | 0.353 | |
| 2 | 3.66 (1.47–9.12) | 0.005 | 3.74 (1.34–10.40) | 0.012 | |
| Etiology | |||||
| Non-viral | Reference | ||||
| Viral | 1.34 (0.71–2.52) | 0.364 | |||
| Macrovascular invasion | 1.42 (0.93–2.53) | 0.093 | 2.27 (1.06–4.87) | 0.035 | |
| Bile duct invasion | 0.77 (0.24–2.45) | 0.652 | |||
| Liver infiltration >50% | 1.61 (0.85–3.04) | 0.141 | |||
| Lung metastasis | 2.44 (1.44–4.15) | <0.001 | 3.94 (1.96–7.91) | <0.001 | |
| LN metastasis | 0.92 (0.52–1.62) | 0.768 | |||
| Bone metastasis | 0.74 (0.37–1.46) | 0.387 | |||
| Combined RT | 0.40 (0.20–0.81) | 0.011 | 0.15 (0.04–0.55) | 0.004 | |
HR, hazard ratio; CI, confidence interval; ALBI, albumin-bilirubin; CRAFITY, C-reactive protein and α-fetoprotein in immunotherapy; LN, lymph node; RT, radiotherapy.
5. Predictors associated with objective response
Table 5 presents the results of the univariable and multivariable logistic regression analyses assessing predictors associated with an objective response. The analysis revealed peritoneal seeding as a significant predictor, with a hazard ratio of 21.22 (95% CI, 2.36 to 190.01; p=0.006) in the univariable analysis and 20.53 (95% CI, 2.11 to 198.72; p=0.009) in the multivariable analysis. Other factors, including age, sex, BCLC stage, ALBI grade, NLR, CRAFITY score, and etiology, did not demonstrate significant associations with objective responses in either analysis. Factors like prior local treatment, macrovascular invasion, bile duct invasion, lymph node metastasis, and bone metastasis were also found to be non-significant. However, combined radiotherapy was significantly associated with better objective responses, with a hazard ratio of 9.86 (95% CI, 1.90 to 51.10; p=0.006).
Table 5.
Univariable and Multivariable Logistic Regression Analyses of Objective Response
| Variable | Univariable analysis | Multivariable analysis | |||
|---|---|---|---|---|---|
| HR (95% CI) | p-value | HR (95% CI) | p-value | ||
| Age, yr | 1.02 (0.97–1.06) | 0.439 | |||
| Male sex | 0.79 (0.25–2.46) | 0.688 | |||
| BCLC stage | 0.898 | ||||
| B | Reference | ||||
| C | 1.09 (0.30–3.89) | ||||
| ALBI grade | 0.103 | 0.074 | |||
| 1 | Reference | Reference | |||
| 2 | 0.42 (0.15–1.19) | 0.30 (0.08–1.13) | |||
| NLR | 0.417 | ||||
| ≤4.0 | Reference | ||||
| >4.0 | 1.58 (0.52–4.74) | ||||
| CRAFITY score | |||||
| 0 | Reference | ||||
| 1 | 0.54 (0.18–1.62) | 0.269 | |||
| 2 | 0.28 (0.05–1.59) | 0.151 | |||
| Etiology | |||||
| Non-viral | Reference | ||||
| Viral | 2.71 (0.55–13.34) | 0.219 | |||
| Prior local treatment | 1.23 (0.38–3.96) | 0.727 | |||
| Macrovascular invasion | 0.74 (0.23–2.37) | 0.615 | |||
| Bile duct invasion | 0.85 (0.08–8.66) | 0.891 | |||
| Liver infiltration >50% | NA | 0.993 | |||
| Lung metastasis | 0.31 (0.08–1.18) | 0.085 | |||
| LN metastasis | 1.58 (0.52–4.74) | 0.417 | |||
| Bone metastasis | 1.56 (0.49–4.96) | 0.448 | |||
| Peritoneal seeding | 21.22 (2.36–190.01) | 0.006 | 20.53 (2.11–198.72) | 0.009 | |
| Combined RT | 5.00 (1.24–20.14) | 0.023 | 9.86 (1.90–51.10) | 0.006 | |
HR, hazard ratio; CI, confidence interval; BCLC, Barcelona Liver Cancer; ALBI, albumin-bilirubin; NLR, neutrophil-to-lymphocyte ratio; CRAFITY, C-reactive protein and α-fetoprotein in immunotherapy; LN, lymph node; RT, radiotherapy; NA, not available.
6. Safety
Among 111 patients, 41 (36.9%) developed at least one treatment-related adverse event. Mucositis (n=12), thyroid dysfunction (n=10), proteinuria (n=8), skin rash (n=6), variceal bleeding (n=4), and gastric or duodenal ulcer bleeding (n=3) were frequently reported adverse events.
DISCUSSION
A median PFS of 6.5 months was observed in this real-world study evaluating atezolizumab and bevacizumab for treating advanced HCC. The treatment showed an ORR of 27% and a DCR of 63% among the patients. Our study showed a higher ORR in patients with peritoneal seeding, which remained significant even after adjusting for confounding factors. Also, younger age, higher CRAFITY score, and the presence of macrovascular invasion and lung metastasis were associated with shorter PFS, whereas combined radiotherapy was associated with longer PFS. These factors can potentially be used to optimize strategies for systemic therapy in patients with advanced HCC.
Compared to the IMbrave 150 trial, which reported a PFS of 6.9 months, an ORR of 30%, and a DCR of 74%, our real-world study of atezolizumab and bevacizumab treatment in patients with advanced HCC yielded similar PFS, but slightly lower ORRs and DCRs.5,6 A contributing factor to these differences could be the higher proportion of patients with high-risk features in our study, which was 33% compared to 19% in IMbrave 150.6 Additionally, our cohort likely included a greater number of patients at more advanced stages of the disease, which might explain the observed discrepancies in response rates. A large real-world study investigating the efficacy and safety of atezolizumab and bevacizumab reported a PFS of 6.9 months, an ORR of 30.8%, and a DCR of 77.7%.12 However, this study included 31.1% of patients with BCLC stage B and had a lower proportion of extrahepatic metastasis at 51.7% compared to our study. The somewhat lower ORR and DCR observed in our study could be attributed to variations in patient baselines, with our study possibly including patients with more advanced disease stages.
Interestingly, our study found a significant association between peritoneal seeding and improved ORRs. Several case reports have indicated the successful treatment of HCC with peritoneal seeding using atezolizumab and bevacizumab.13,14 Although the mechanism is not fully understood, the observed responsiveness of peritoneal seeding in HCC to atezolizumab and bevacizumab may be related to specific aspects of tumor biology or the immune environment and response. Thus, further research is needed to explore these factors. Understanding the mechanisms could also aid in predicting patient responses to treatment, potentially guiding more effective strategies.
Recently, the CRAFITY score, combining AFP and C-reactive protein levels, has been proposed as a prognostic tool for HCC patients receiving immunotherapy.15,16 Its ease of availability, objectiveness, and applicability make the CRAFITY score useful for decision-making in daily clinical practice. Our study also found that the CRAFITY score was a significant factor in predicting PFS, underlining its potential utility in managing HCC patients undergoing atezolizumab and bevacizumab treatment. Our study observed that younger patients had a shorter PFS in multivariable analysis, a finding that aligns with a previous study suggesting a potential link between younger age and more aggressive tumor biology in HCC.17 HCC patients with lung metastasis are known to have poor prognoses.18 Several studies indicated that the lung is a common metastasis site in HCC and is associated with poorer outcomes compared to no lung metastasis.19,20 In our study, we observed that the presence of lung metastasis in patients treated with atezolizumab and bevacizumab was associated with shorter PFS. This finding suggests that even with the use of atezolizumab and bevacizumab, patients with lung metastasis are at a higher risk of disease progression. Therefore, careful and vigilant monitoring is necessary for patients with lung metastasis undergoing atezolizumab and bevacizumab treatment.
In contrast to AFP, which has consistently been identified as a significant prognostic factor in previous studies,15,21,22 PIVKA-II was not identified as a significant factor in our multivariate analysis. While AFP is a well-established prognostic factor, studies showing a similar association for PIVKA-II are comparatively limited. This lack of evidence underscores the need for further research to explore the prognostic relevance of PIVKA-II. Such studies could provide further insight into the potential utility of PIVKA-II as a biomarker in patients receiving atezolizumab and bevacizumab.
Since our study was retrospective, treatment-related adverse events might have been underreported. However, there were no unpredictable and clinically significant treatment-related adverse events. Clinically significant bleeding events, such as variceal bleeding and ulcer bleeding, were reported in seven out of 111 patients who received atezolizumab and bevacizumab for HCC in our cohort.
Our study had limitations due to its small sample size and retrospective nature, which may limit the generalizability of our results and introduce potential biases. Owing to the small sample size, we might not have found significant results for some variables. Future research with larger sample sizes and prospective designs is needed. However, this study’s strength lies in its real-world data, providing valuable insight into the effectiveness of atezolizumab and bevacizumab treatment for patients with advanced HCC. Despite its smaller sample size, the study reflects actual clinical practice, offering a pragmatic perspective on patient outcomes and treatment responses. We also performed a comprehensive analysis of prognostic factors affecting PFS in HCC patients treated with atezolizumab and bevacizumab.
In conclusion, our study offers valuable insight into the real-world effectiveness of atezolizumab and bevacizumab in treating patients with advanced HCC. Although our study suggests the potential benefits of atezolizumab and bevacizumab, it also brings to light the variability in patient responses according to several prognostic factors, indicating its potential clinical usefulness for tailored treatment approaches.
ACKNOWLEDGEMENTS
This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HR20C0025).
Footnotes
CONFLICTS OF INTEREST
No potential conflict of interest relevant to this article was reported.
AUTHOR CONTRIBUTIONS
Study concept and design: B.G.S. Data acquisition: B.G.S. Data analysis and interpretation: B.G.S. Manuscript draft: B.G.S., Y.H.P. Data analysis plan and data management: B.G.S. Drafting of the manuscript: B.G.S., Y.H.P. Critical revision of manuscript for important intellectual content: B.G.S., M.J.G., W.K., D.H.S., G.Y.G., Y.H.P., M.S.C., J.H.L. Obtained funding: Y.H.P. Overall study supervision: Y.H.P. All authors participated in the preparation of the manuscript and have seen and approved the final version.
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available upon request.
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