
==== Front
Ther Adv Med Oncol
Ther Adv Med Oncol
TAM
sptam
Therapeutic Advances in Medical Oncology
1758-8340
1758-8359
SAGE Publications Sage UK: London, England

10.1177/17588359241274625
10.1177_17588359241274625
Original Research
Cost-effectiveness analysis of durvalumab plus tremelimumab as first-line therapy in patients with unresectable hepatocellular carcinoma
Liao Weiting *Department of Medical Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
West China Biomedical Big Data Center, Sichuan University, Chengdu, China
Formal analysis Investigation Methodology Project administration Software Writing – original draft
Xu Huiqiong *Division of Abdominal Tumor Multimodality Treatment, Cancer Center, West China Hospital, Sichuan University/West China School of Nursing, Sichuan University, Chengdu, China
Formal analysis Investigation Writing – original draft
Hutton David Department of Health Management and Policy, University of Michigan, Ann Arbor, MI, USA
Methodology Supervision Writing – review & editing
Wu Qiuji Department of Medical Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
West China Biomedical Big Data Center, Sichuan University, Chengdu, China
Formal analysis Resources Validation Visualization
Yang Yang Department of Medical Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
West China Biomedical Big Data Center, Sichuan University, Chengdu, China
Investigation Methodology Validation Visualization
Feng Mingyang Department of Medical Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
West China Biomedical Big Data Center, Sichuan University, Chengdu, China
Software Validation Visualization
Lei Wanting Department of Medical Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
West China Biomedical Big Data Center, Sichuan University, Chengdu, China
Software Validation Visualization
Bai Liangliang Department of Medical Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
West China Biomedical Big Data Center, Sichuan University, Chengdu, China
Resources Supervision Validation
Li Junying Thoracic Oncology Ward, Cancer Center, West China Hospital, Sichuan University, GuoXue 37, Chengdu 610041, China
Conceptualization Investigation Project administration Supervision Writing – review & editing
https://orcid.org/0000-0003-3079-1352
Li Qiu Department of Medical Oncology, Cancer Center, West China Hospital, Sichuan University, GuoXue 37, Chengdu 610041, China
West China Biomedical Big Data Center, Sichuan University, Chengdu, China
Conceptualization Funding acquisition Project administration Resources Supervision Visualization Writing – review & editing
lijunying3535@163.com
fbqiu9@163.com
* These authors contributed equally

18 9 2024
2024
16 175883592412746256 1 2024
5 7 2024
© The Author(s), 2024
2024
SAGE Publications Ltd unless otherwise noted. Manuscript content on this site is licensed under Creative Commons Licenses
https://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
Background:

The HIMALAYA trial found that durvalumab plus tremelimumab significantly prolonged progression-free survival and overall survival in patients with unresectable hepatocellular carcinoma (HCC) compared with sorafenib.

Objective:

This study aimed to investigate the cost-effectiveness of durvalumab plus tremelimumab compared with sorafenib in the first-line HCC setting.

Design:

A Markov model-based cost-effectiveness analysis.

Methods:

We created a Markov model to compare healthcare costs and clinical outcomes of HCC patients treated with durvalumab plus tremelimumab in the first-line setting compared with sorafenib. We estimated transition probabilities from randomized trials. Lifetime direct healthcare costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios were calculated for first-line durvalumab plus tremelimumab compared with sorafenib from a US payer’s perspective.

Results:

In the base case, first-line durvalumab plus tremelimumab was associated with an improvement of 0.29 QALYs compared with sorafenib. While both treatment strategies were associated with considerable lifetime expenditures, first-line durvalumab plus tremelimumab was less expensive than sorafenib ($188,405 vs $218,584). The incremental net monetary benefit for durvalumab plus tremelimumab versus sorafenib was $72,762 (valuing QALYs at $150,000 each). The results of durvalumab plus tremelimumab were better in terms of costs and health outcomes in patients with HBV-related HCC and high alpha-fetoprotein levels.

Conclusion:

First-line durvalumab plus tremelimumab was estimated to be dominant for the treatment of unresectable HCC compared with sorafenib from a US payer’s perspective.

cost-effectiveness
dual immunotherapy
first-line therapy
hepatocellular carcinoma
Markov model
The HIMALAYA trial
Science and Technology Department of Sichuan Province Funding Project 2016FZ0108, 18ZDYF1981 cover-dateJanuary-December 2024
typesetterts1
==== Body
pmcIntroduction

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and is a significant and growing cause of cancer-related death in the United States. 1 Previously approved agents for first-line therapy, such as sorafenib, lenvatinib, and bevacizumab combined with atezolizumab, have focused on angiogenesis 2 . In the last few years, immune-checkpoint inhibitors (ICIs) have revolutionized cancer therapy and have gained an increased interest in the treatment of HCC. 3

Durvalumab (programmed death ligand 1 inhibitor) plus tremelimumab (cytotoxic T lymphocyte associate protein-4 inhibitor) showed high efficacy and low toxicity in phase I and II clinical trials. 4 The randomized, open-label, sponsor-blind, multicenter, global, phase III HIMALAYA trial 5 was therefore designed to evaluate Single Tremelimumab Regular Interval Durvalumab (STRIDE) versus sorafenib in patients with unresectable HCC who had not been previously treated with systemic therapy. The median overall survival (OS) was 16.43 months (95% CI, 14.16–19.58) with STRIDE and 13.77 months (95% CI, 12.25–16.13) with sorafenib. 5 The frequency of grade 3/4 treatment-emergent adverse events (AEs) is comparable in STRIDE patients (50.5%) and sorafenib patients (52.4%). The first combination of anti-PD-L1 and anti-CTLA4 antibodies for HCC treatment showed an acceptable and manageable toxicity profile. Based on these exciting results, FDA approved this combined therapy as the first-line treatment for advanced HCC. 6

Evidence-based treatments are limited for advanced HCC, 7 once a new intervention is on the market, the availability and cost-conscious priority for patients’ choice become an essential issue. Hereby, this study aimed to investigate the cost-effectiveness of durvalumab plus tremelimumab compared with sorafenib in advanced HCC from a US payer’s perspective.

Methods

Target population and treatment

Based on the HIMALAYA study, 5 a total of 393 patients were assigned to receive STRIDE, and 389 patients received sorafenib. The STRIDE regimen contained 300 mg of tremelimumab for one dose plus 1500 mg of durvalumab every 4 weeks. The 400 mg of sorafenib was given twice daily. Treatment continued until progression, unacceptable toxicity, consent withdrawal, or other discontinuation criteria were met. 5 After treatment discontinuation, 40.7% and 45.0% of patients in the STRIDE and sorafenib arms, received subsequent second-line anticancer therapy, respectively. This cost-effectiveness study followed the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) reporting guideline, 8 shown in Supplemental Table 1.

Markov model

Long-term costs and health outcomes were simulated with a Markov model. The Markov model (Figure 1) simulated three health states: progression-free, progression, and death. The model assumed that patients transitioned from progression-free status to death via a progression state, as performed in previous cost-effectiveness analyses.9,10 Transitions between the health states were based on 1.5-month cycles. All the costs and quality-adjusted life-years (QALYs) were discounted at 3% per year, 11 with a lifetime horizon of 10 years.

Figure 1. Markov model.

Cost estimate

Only direct costs were considered including the costs for the regimen, costs for AE management, costs of drug administration, costs of subsequent active treatment, costs of best supportive care, and costs of terminal care per patient, displayed in Table 1. The costs for subsequent active treatment, best supportive care, and terminal care per patient came from a cost-effectiveness analysis of first-line treatments in advanced HCC. 12 The cost for drugs was based on the Red Book accessed in 2023. 13 The cost for durvalumab was $466.79 per 50 mg for a 6-week cost of $21,005.55. The cost for tremelimumab was $3120 per 20 mg, for a 300 mg dose cost of $46,800. The cost for sorafenib was $210.83 per 200 mg for a cost of $35,419.44 per 6 weeks. We considered costs for the following adverse effects: diarrhea, palmar–plantar erythrodysesthesia syndrome, and hypertension because these side effects were the most frequently and clinically relevant grade 3 or 4 events in the trial. Costs of treating AEs 14 as well as drug administration 15 came from the published papers. All the costs were inflated to 2023 values using the Medical-Care Inflation data set. 16

Table 1. Input parameters.

Parameter	Value (ranges)	Distribution	References	
Cost input, $	
 Durvalumab per 50 mg	466.79 (326.75–606.83)	Gamma	13	
 Tremelimumab per 20 mg	3120 (2184–4056)	Gamma	13	
 Sorafenib per 200 mg	210.83 (147.58–274.08)	Gamma	13	
 Drug administration	171.9 (120.3–223.5)	Gamma	15	
 Diarrhea per event	1455.79 (1019.05–1892.53)	Gamma	14	
 Palmar–plantar erythrodysesthesia syndrome per event	10.22 (7.15–13.29)	Gamma	14	
 Hypertension per event	2.94 (2.06–3.82)	Gamma	14	
 Subsequent active treatment per patient	127,815.17 (89,470.62–166,159.72)	Gamma	12	
 Subsequent best supportive care per patient	43,751.83 (30,626.28–56,877.38)	Gamma	12	
 Terminal care per patient	9313.37 (6519.36–12,107.38)	Gamma	12	
Any subsequent second-line therapy, %	
 Durvalumab plus tremelimumab	40.7 (28.49–52.91)	Beta	5	
 Sorafenib	45 (31.5–58.5)	Beta	5	
Survival model	
 OS in tremelimumab plus durvalumab arm	λ = 0.050412548; γ = 0.89420967	Weibull	5	
 PFS in tremelimumab plus durvalumab arm	λ = 0.160334; γ = 0.8417336	Weibull	5	
 OS in sorafenib arm	λ = 0.045278557; γ = 1.020906757	Weibull	5	
 PFS in sorafenib arm	λ = 0.1184374; γ = 1.09299874	Weibull	5	
Utility	
 Progression-free	0.76 (0.53–0.99)	Beta	14,24,25	
 Progression	0.68 (0.48–0.88)	Beta	14,24,25	
Grade 3–4 AE probabilities in tremelimumab plus durvalumab arm, %	
 Diarrhea	4.4 (3.08–5.72)	Beta	5	
 Palmar–plantar erythrodysesthesia syndrome	0 (0–0)	Beta	5	
 Hypertension	1.8 (1.26–2.34)	Beta	5	
Grade 3–4 AE probabilities in sorafenib arm, %	
 Diarrhea	4.3 (3.01–5.59)	Beta	5	
 Palmar–plantar erythrodysesthesia syndrome	9.1 (6.37–11.83)	Beta	5	
 Hypertension	6.1 (4.27–7.93)	Beta	5	
AE, adverse event; OS, overall survival; PFS, progression-free survival.

Transition probability estimate

The GetData Graph Digitizer 17 was used to extract the data points on the Kaplan–Meier curve. The Kaplan–Meier OS and progression-free survival curves of durvalumab plus tremelimumab and sorafenib obtained from the Weibull regression and empirical Kaplan–Meier curves in the HIMALAYA trial are shown in Supplemental Figure 1.18,19 We used the Weibull distribution in our analysis as it is a flexible method widely utilized in survival analysis for cancer patients.20–23 Transition probabilities were calculated using the formula: p(t) = 1 − exp[λ(t − 1)γ − λtγ] where λ represented the scale of the distribution, γ represented the shape of the distribution, and t was the Markov cycle. The survival curves for each strategy are depicted in the modeled survival curve. The input survival parameter in either group is shown in Table 1.

Utility estimate

Health state utility scores were derived from previously published literature: 0.76 for the progression-free state and 0.68 for the progressed disease.14,24,25

Outcomes

We measured costs in 2023 dollars and QALYs. For an intervention that was both more expensive and had higher QALYs, we calculated an incremental cost-effectiveness ratio (ICER) which is the incremental cost divided by the incremental effectiveness. We assumed the willingness-to-pay for QALYs was $150,000 from a US payer’s perspective. 26 In cases where an intervention may be less expensive with higher QALYs, the interpretation of the magnitude of the ICER becomes problematic, so we calculated outcomes in terms of incremental net monetary benefit (INMB) which was computed as the increased QALYs multiplied by the willingness-to-pay and subtract the incremental costs. Using this approach, if an INMB ⩾ 0, the intervention of interest would be considered cost-effective relative to the alternative.27,28 This can be particularly useful for sensitivity analysis.

Sensitivity analysis

The hazard ratio (HR) between durvalumab plus tremelimumab and sorafenib that was used to estimate the scale parameters was calculated using the following equation: HR × γRT. 29 We assumed a constant reduced hazard of progression and death with durvalumab plus tremelimumab compared to sorafenib. We varied the HR in sensitivity analysis. Further subgroup analyses were performed for the prespecified subgroups that were reported in the HIMALAYA trial by varying the HRs for OS. During one-way sensitivity analyses, model parameters were varied across the ranges outlined in Table 1 to determine the impact on the NMB. The costs and utility values were varied within a ±30% range, while the survival parameters were varied with a ±20% range. To investigate the uncertainty of cost-effectiveness, we performed a probabilistic sensitivity analysis with 10,000 Monte Carlo simulations, each time randomly sampling from the distribution of model inputs.

Results

Base-case analysis

The results from the base-case analysis are shown in Table 2. The total lifetime costs for durvalumab plus tremelimumab are $188,405, while costs for sorafenib are $218,584. The QALYs for durvalumab plus tremelimumab are 1.75 and that for sorafenib are 1.46. This makes durvalumab plus tremelimumab dominant (cost-saving) when compared to sorafenib. Valuing QALYs at $150,000 each, the value of the durvalumab plus tremelimumab treatment strategy is $73,899, and that for sorafenib is $1137, leading to the INMB of $72,762 for durvalumab plus tremelimumab compared to sorafenib.

Table 2. Cost and outcome results in the base-case analysis.

Results	Durvalumab plus tremelimumab	Sorafenib	
QALYs	1.75	1.46	
Life years	2.47	2.07	
Total cost, $	188,405	218,584	
ICER, $/QALY	−106,307		
NMB	73,899	1137	
INMB	72,762		
Cost-effectiveness	Dominant		
ICER, incremental cost-effectiveness ratio; INMB, incremental net monetary benefit; QALYs, quality-adjusted life-years; NMB, net monetary benefit.

Deterministic sensitivity analyses

The tornado diagram for durvalumab plus tremelimumab is shown in Figure 2. Discount rate, the OS of durvalumab plus tremelimumab, and the cost of durvalumab are the major sensitive parameters comparing durvalumab plus tremelimumab to sorafenib. Subgroup analysis showed that varying the HR of durvalumab plus tremelimumab compared with sorafenib across the subgroup in the HIMALAYA trial did lead to durvalumab plus tremelimumab having a positive INMB when compared to sorafenib (Table 3). Durvalumab plus tremelimumab achieved the most beneficial results in terms of health outcomes and costs, in the group with HBV-related HCC and high AFP level, with the INMB of $88,336.

Figure 2. Tornado diagram of one-way sensitivity analyses.

NMB, net monetary benefit; WTP, willingness-to-pay; OS, overall survival; PFS, progression-free survival.

Table 3. Subgroup analysis of cost-effectiveness by varying the hazard ratios of overall survival.

Subgroup	OS HR	INMB (95% CI)	ICER, $/QALY	Cost-effectiveness probability at WTP = $100,000 (%)	Cost-effectiveness probability at WTP = $150,000 (%)	
All the patients	0.78 (0.66–0.92)	72,762 (59,564–85,944)	−106,307	86	91	
Sex: male	0.73 (0.61–0.88)	78,024 (63,122–92,036)	−94,616	87	93	
Sex: female	1.02 (0.67–1.56)	51,330 (18,853–84,771)	−214,031	79	82	
Age at randomization: <65 years	0.82 (0.65–1.04)	68,771 (49,787–87,133)	−117,300	84	90	
Age at randomization: ⩾65 years	0.73 (0.58–0.93)	78,024 (58,699–95,880)	−94,616	87	93	
PD-L1 expression: positive	0.85 (0.65–1.11)	65,898 (44,639–87,133)	−126,737	84	89	
PD-L1 expression: negative	0.83 (0.65–1.11)	67,802 (44,639–87,133)	−120,321	85	89	
Etiology of liver disease: HBV	0.64 (0.48–0.86)	88,336 (64,962–109,821)	−77,840	90	95	
Etiology of liver disease: HCV	1.06 (0.76–1.49)	48,278 (22,188–74,829)	−250,125	78	82	
Etiology of liver disease: nonviral	0.74 (0.57–0.95)	76,946 (56,998–97,194)	−96,796	87	92	
ECOG performance status at baseline: 0	0.79 (0.63–0.98)	71,747 (54,516–89,554)	−108,903	86	91	
ECOG performance status at baseline: 1	0.74 (0.57–0.95)	76,946 (56,998–97,194)	−96,796	87	92	
Macrovascular spread: yes	0.78 (0.57–1.07)	72,762 (47,535–97,194)	−106,307	86	91	
Macrovascular spread: no	0.77 (0.63–0.93)	73,790 (58,699–89,554)	−103,802	86	91	
Extrahepatic invasion: yes	0.67 (0.53–0.84)	84,771 (66,845–102,623)	−82.922	89	94	
Extrahepatic invasion: no	0.87 (0.67–1.11)	64,036 (44,639–84,770)	−133,704	84	89	
Mascular invasion = yes and/or extrahepatic spread = yes	0.73 (0.59–0.89)	78,024 (62,217–94,582)	−94,616	88	92	
Mascular invasion = no and/or extrahepatic spread = no	0.79 (0.58–1.06)	71,747 (48,278–95,880)	−108,903	86	91	
Region: Asia (except Japan)	0.71 (0.54–0.92)	80,218 (59,564–101,239)	−90,467	88	93	
Region: Rest of world (includes Japan)	0.82 (0.66–1.02)	68,771 (51,330–85,944)	−117,300	85	90	
AFP at baseline: <400 ng/ml	0.82 (0.63–1.05)	687,71 (49,028–89,554)	−117,300	85	90	
AFP at baseline: ⩾400 ng/ml	0.64 (0.45–0.91)	88,336 (60,438–114,374)	−77,840	90	95	
BCLC score: B	0.87 (0.57–1.33)	64,036 (30,654–97,194)	−133,704	84	88	
BCLC score: C	0.76 (0.63–0.91)	74,829 (60,438–89,554)	−101,385	87	91	
BCLC, Barcelona Clinic Liver Cancer; CI, confidence interval; ECOG, Eastern Cooperative Oncology Group; HR, hazard ratio; ICER, incremental cost-effectiveness ratio; INMB, incremental net monetary benefit; QALY, quality-adjusted-life year; NMB, net monetary benefit; OS, overall survival; WTP, willingness-to-pay.

Probabilistic sensitivity analysis

In 10,000 simulations, durvalumab plus tremelimumab was often dominant and would be considered cost-effective in 86% (valuing QALYs at $100,000) and 91% (valuing QALYs at $150,000) of iterations (Table 3). The majority of simulations fell in the southeast quadrant of the incremental cost-effectiveness plane, indicating durvalumab plus tremelimumab as a dominant strategy (Figure 3). The result for Monte Carlo simulations is shown in Table 4.

Figure 3. Cost-effectiveness scatterplot.

WTP, willingness-to-pay; QALYs, quality-adjusted life-years.

Table 4. Monte Carlo simulations.

Results	Durvalumab plus tremelimumab	Sorafenib	
Cost, $	
 Mean	188,894	217,864	
 Standard deviation	33,364	43,575	
 Median	186,525	215,215	
 IQR	165,660–210,115	187,206–245,622	
Effectiveness, QALYs	
 Mean	1.75	1.46	
 Standard deviation	0.26	0.22	
 Median	1.74	1.45	
 IQR	1.57–1.91	1.31–1.60	
IQR, interquartile range; QALY, quality-adjusted life-year.

Discussion

This study showed a single priming dose of tremelimumab plus once-monthly durvalumab is dominant (cost-saving) in patients with unresectable HCC compared with sorafenib. Generally, the cost-effectiveness of STRIDE versus sorafenib remained consistent across the subgroups.

The most influential parameters in our model were the discount rate, the Weibull OS gamma parameter in the durvalumab plus tremelimumab group, the cost of durvalumab, and the utilities of the progression and progression-free health states. The high cost of tremelimumab could pose a significant obstacle to the widespread utilization of this medication. This may decrease its accessibility and affordability for patients.

To the best of our knowledge, this is the first cost-effectiveness analysis of durvalumab plus tremelimuab in advanced HCC and was the only regimen yet found to be cost-effective or dominant compared with sorafenib in the first-line setting from a US payer’s perspective. Another approved immunotherapy combination therapy of atezolizumab and bevacizumab was not a cost-effective strategy compared with sorafenib for the first-line treatment of unresectable HCC in the USA.12,25 Of note, participants who took STRIDE had a lower relative risk of experiencing a decline in their quality of life compared to those who took sorafenib. 30 Though we assumed equal utility values for both treatments in our model-based analysis due to the lack of STRIDE utility data, STRIDE was found to be the dominant treatment option, making our conclusion solid.

The etiology of HCC affects the immune response and reprograms the unique tumor microenvironment. 31 In the subgroup analysis, the most dominant subgroup to treat with durvalumab plus tremelimumab was HBV-infected patients. This is because highly suppressive PD-1hi Treg cells that are associated with a poor prognosis are selectively enriched in HBV-related versus non-viral HCCs, 32 which could provide an opportunity for anti-CTLA4 blockade to be effective in HBV-related HCC. 33 Another beneficial subgroup for durvalumab plus tremelimumab was patients with AFP levels higher than 400 ng/ml. Intriguingly, AFP is a well-known negative prognostic factor for survival in HCC, but immunotherapy should not be withheld solely due to high AFP level. 34 Based on the results of cost-effectiveness and efficacy, first-line dual immunotherapy with durvalumab plus tremelimumab should be prioritized for HBV-related HCC and patients with AFP high level ⩾400 ng/ml. Of note, for patients with non-viral etiology of chronic liver disease, the only regimen confirmed to significantly improve OS, compared with sorafenib, is durvalumab plus tremelimumab. 35 In this population, the INMB was $76,946 for durvalumab plus tremelimumab, showing good value.

A network meta-analysis of phase III trials showed that anti-PD-1 therapy with nivolumab was associated with a lower proportion of AEs, whereas among ICI combinations, durvalumab plus tremelimumab reported the lowest risk of AEs. 36 The grade 3 or 4 AEs occurred in 50.5% and 52.4% of patients receiving STRIDE and sorafenib in the HIMALAYA study. Based on our study, the total cost of AE management in the durvalumab plus tremelimumab group was also much lower than that in the sorafenib group. Therefore, durvalumab plus tremelimumab brought a lower toxicity-related cost burden.

The HIMALAYA was the first trial to demonstrate the benefit of dual ICIs, representing a new treatment option. 2 Dual immunotherapy is usually presumed to not be cost-effective; however, our model-based cost-effectiveness study indicated that reasonable application of immunotherapy not only brings significant efficacy, fewer AEs, and survival advantages but also can be dominant compared with first-line targeted therapy. Implementing scientific administration orders and reasonable combination therapies wound prolong patient survival and enhance overall cost-effectiveness.

This study has some limitations. First, clinical efficacy inputs were based on the randomized controlled trial, rather than real-world evidence of efficacy, which may limit generalizability. Second, the health-related quality-of-life associated with disease used came from previous literature. Third, although the calibrated survival curves based on the Weibull distribution matched well with the trial, assumptions about survival parameters remain a concern. To mitigate this limitation, we conducted extensive sensitivity analyses, demonstrating that STRIDE remained cost-effective across a broad spectrum of model inputs. Furthermore, the comparator in this cost-effectiveness analysis chose sorafenib, the long-standing standard first-line therapy in advanced HCC. As therapeutic advances have dramatically evolved, 37 future cost-effectiveness analyses should consider comparing to constantly updating first-line therapies in advanced HCC.

Conclusion

Based on this Markov model study, first-line durvalumab plus tremelimumab is dominant compared with sorafenib in patients with unresectable HCC from a US payer’s perspective.

Supplemental Material

sj-docx-1-tam-10.1177_17588359241274625 – Supplemental material for Cost-effectiveness analysis of durvalumab plus tremelimumab as first-line therapy in patients with unresectable hepatocellular carcinoma

Supplemental material, sj-docx-1-tam-10.1177_17588359241274625 for Cost-effectiveness analysis of durvalumab plus tremelimumab as first-line therapy in patients with unresectable hepatocellular carcinoma by Weiting Liao, Huiqiong Xu, David Hutton, Qiuji Wu, Yang Yang, Mingyang Feng, Wanting Lei, Liangliang Bai, Junying Li and Qiu Li in Therapeutic Advances in Medical Oncology

None.

Declarations

ORCID iD: Qiu Li https://orcid.org/0000-0003-3079-1352

Supplemental material: Supplemental material for this article is available online.

Ethics approval and consent to participate: Not applicable.

Consent for publication: Not applicable.

Author contributions: Weiting Liao: Formal analysis; Investigation; Methodology; Project administration; Software; Writing – original draft.

Huiqiong Xu: Formal analysis; Investigation; Writing – original draft.

David Hutton: Methodology; Supervision; Writing – review & editing.

Qiuji Wu: Formal analysis; Resources; Validation; Visualization.

Yang Yang: Investigation; Methodology; Validation; Visualization.

Mingyang Feng: Software; Validation; Visualization.

Wanting Lei: Software; Validation; Visualization.

Liangliang Bai: Resources; Supervision; Validation.

Junying Li: Conceptualization; Investigation; Project administration; Supervision; Writing – review & editing.

Qiu Li: Conceptualization; Funding acquisition; Project administration; Resources; Supervision; Visualization; Writing – review & editing.

Funding: The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The work was financially supported by Science & Technology Department of Sichuan Province Funding Project (Nos. 2016FZ0108 and 18ZDYF1981). The funding had no role in study design, data collection, analysis or interpretation or in writing the report.

The authors declare that there is no conflict of interest.

Availability of data and materials: The datasets generated and analyzed during the present study are available from the corresponding author on reasonable request.
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References

1 Altekruse SF Henley SJ Cucinelli JE , et al . Changing hepatocellular carcinoma incidence and liver cancer mortality rates in the United States. Am J Gastroenterol 2014; 109 (4 ): 542–553.24513805
2 de Castria TB Khalil DN Harding JJ , et al . Tremelimumab and durvalumab in the treatment of unresectable, advanced hepatocellular carcinoma. Fut Oncol 2022; 18 (33 ): 3769–3782.
3 Donne R Lujambio A. The liver cancer immune microenvironment: therapeutic implications for hepatocellular carcinoma. Hepatology 2022; 77 (5 ): 1773–1796.
4 Kelley RK Sangro B Harris W , et al . Safety, efficacy, and pharmacodynamics of tremelimumab plus durvalumab for patients with unresectable hepatocellular carcinoma: randomized expansion of a Phase I/II Study. J Clin Oncol 2021; 39 (27 ): 2991–3001.34292792
5 Abou-Alfa GK Lau G Kudo M , et al . Tremelimumab plus durvalumab in unresectable hepatocellular carcinoma. NEJM Evid 2022; 1 (8 ): a2100070.
6 https://www.fda.gov/drugs/resources-information-approved-drugs/fda-approves-tremelimumab-combination-durvalumab-unresectable-hepatocellular-carcinoma (accessed 4 February 2023).
7 Wagle NS Spencer JC. Challenges for measuring cost-effectiveness of immunotherapy in unresectable hepatocellular carcinoma. Jama Netw Open 2021; 4 (4 ): e215476.
8 Husereau D Drummond M Petrou S , et al . Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement. Value Health 2013; 16 (2 ): e1–e5.
9 Zhan M Zheng H Yang Y , et al . Cost-effectiveness analysis of neoadjuvant chemoradiotherapy followed by surgery versus surgery alone for locally advanced esophageal squamous cell carcinoma based on the NEOCRTEC5010 trial. Radiother Oncol 2019; 141 : 27–32.31431378
10 Liao W Xu H Hutton D , et al . Cost-effectiveness analysis of fourth- or further-line ripretinib in advanced gastrointestinal stromal tumors. Front Oncol 2021; 11 : 692005.34938653
11 Sanders GD Neumann PJ Basu A , et al . Recommendations for conduct, methodological practices, and reporting of cost-effectiveness analyses: second panel on cost-effectiveness in health and medicine. J Am Med Assoc 2016; 316 (10 ): 1093–1103.
12 Su D Wu B Shi L. Cost-effectiveness of atezolizumab plus bevacizumab vs sorafenib as first-line treatment of unresectable hepatocellular carcinoma. Jama Netw Open 2021; 4 (2 ): e210037.33625508
13 IBM. RED BOOK online, http://www.micromedexsolutions.com (accessed 10 February 2023).
14 Liao W Huang J Hutton D , et al . Cost-effectiveness analysis of cabozantinib as second-line therapy in advanced hepatocellular carcinoma. Liver Int 2019; 39 (12 ): 2408–2416.31544330
15 Zhang X Wang J Shi J , et al . Cost-effectiveness of atezolizumab plus bevacizumab vs sorafenib for patients with unresectable or metastatic hepatocellular carcinoma. Jama Netw Open 2021; 4 (4 ): e214846.
16 Inflation M. Tom’s inflation calculator, https://www.halfhill.com/inflation_js.html (accessed 1 May 2023).
17 GetData Graph Digitizer, http://getdata-graph-digitizer.com/download.php (accessed 4 April 2023).
18 Guyot P Ades AE Ouwens MJ , et al . Enhanced secondary analysis of survival data: reconstructing the data from published Kaplan-Meier survival curves. Bmc Med Res Methodol 2012; 12 : 9.22297116
19 Hoyle MW Henley W. Improved curve fits to summary survival data: application to economic evaluation of health technologies. Bmc Med Res Methodol 2011; 11 :139.21985358
20 Liao M Jiang Q Hu H , et al . Cost-effectiveness analysis of utidelone plus capecitabine for metastatic breast cancer in China. J Med Econ 2019; 22 (6 ): 584–592.30808230
21 Plana D Fell G Alexander BM , et al . Cancer patient survival can be parametrized to improve trial precision and reveal time-dependent therapeutic effects. Nat Commun 2022; 13 (1 ): 873.35169116
22 Ding D Hu H Shi Y , et al . Cost-effectiveness of pembrolizumab plus axitinib versus sunitinib as first-line therapy in advanced renal cell carcinoma in the U.S. Oncologist 2021; 26 (2 ): e290–e297.
23 Wan XM Peng LB Ma JA , et al . Economic evaluation of nivolumab as a second-line treatment for advanced renal cell carcinoma from US and Chinese perspectives. Cancer 2017; 123 (14 ): 2634–2641.28301684
24 Camma C Cabibbo G Petta S , et al . Cost-effectiveness of sorafenib treatment in field practice for patients with hepatocellular carcinoma. Hepatology 2013; 57 (3 ): 1046–1054.23299720
25 Wen F Zheng H Zhang P , et al . Atezolizumab and bevacizumab combination compared with sorafenib as the first-line systemic treatment for patients with unresectable hepatocellular carcinoma: a cost-effectiveness analysis in China and the United states. Liver Int 2021; 41 (5 ): 1097–10104.33556230
26 Neumann PJ Cohen JT Weinstein MC. Updating cost-effectiveness—the curious resilience of the $50,000-per-QALY threshold. New Engl J Med 2014; 371 (9 ): 796–797.25162885
27 Reed SD. Statistical considerations in economic evaluations: a guide for cardiologists. Eur Heart J 2014; 35 (25 ): 1652–1656.24801070
28 Liao W Huang J Wu Q , et al . Concurrent chemoradiotherapy with nedaplatin versus cisplatin in stage II-IVB nasopharyngeal carcinoma: a cost-effectiveness analysis. Oral Oncol 2019; 93 : 15–20.31109691
29 Wu B Miao Y Bai Y , et al . Subgroup economic analysis for glioblastoma in a health resource-limited setting. PLoS One 2012; 7 (4 ): e34588.
30 Abou-Alfa GK Lau G Kudo M , et al . Plain language summary of the HIMALAYA study: tremelimumab and durvalumab for unresectable hepatocellular carcinoma (liver cancer). Fut Oncol 2023; 19 (38 ): 2505–2516.
31 Llovet JM Castet F Heikenwalder M , et al . Immunotherapies for hepatocellular carcinoma. Nat Rev Clin Oncol 2022; 19 (3 ): 151–172.34764464
32 Lim CJ Lee YH Pan L , et al . Multidimensional analyses reveal distinct immune microenvironment in hepatitis B virus-related hepatocellular carcinoma. Gut 2019; 68 (5 ): 916–927.29970455
33 Finn RS Qin S Ikeda M , et al . Atezolizumab plus bevacizumab in unresectable hepatocellular carcinoma. New Engl J Med 2020; 382 (20 ): 1894–1905.32402160
34 Scheiner B Pomej K Kirstein MM , et al . Prognosis of patients with hepatocellular carcinoma treated with immunotherapy—development and validation of the CRAFITY score. J Hepatol 2022; 76 (2 ): 353–363.34648895
35 Fulgenzi C 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 ): 100702.37025943
36 Fulgenzi C 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 : 57–67.35970037
37 Yang C Zhang H Zhang L , et al . Evolving therapeutic landscape of advanced hepatocellular carcinoma. Nat Rev Gastro Hepat 2023; 20 (4 ): 203–222.
