
==== Front
J Gynecol Oncol
J Gynecol Oncol
JGO
Journal of Gynecologic Oncology
2005-0380
2005-0399
Asian Society of Gynecologic Oncology; Korean Society of Gynecologic Oncology; Japan Society of Gynecologic Oncology

38606824
10.3802/jgo.2024.35.e83
Original Article
Uterine Corpus
Cost-effectiveness of atezolizumab plus chemotherapy for advanced/recurrent endometrial cancer
https://orcid.org/0000-0003-3781-3323
Huo Gengwei 1234*
https://orcid.org/0009-0003-1982-3365
Song Ying 5*
https://orcid.org/0000-0003-3463-0708
Chen Peng 1234
1 Department of Thoracic Oncology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
2 National Clinical Research Center for Cancer, Tianjin, China.
3 Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin, China.
4 Tianjin’s Clinical Research Center for Cancer, Tianjin, China.
5 Department of Pharmacy, Jining No.1 people’s Hospital, Jining, China.
Correspondence to Peng Chen. Department of Thoracic Oncology, Tianjin Medical University Cancer Institute and Hospital; National Clinical Research Center for Cancer; Key Laboratory of Cancer Prevention and Therapy of Tianjin; Tianjin’s Clinical Research Center for Cancer, Binshui Road, Tianjin 300060, China. chenpengdoc@sina.com
*Gengwei Huo and Ying Song contributed equally to this work.

9 2024
03 4 2024
35 5 e8307 12 2023
18 2 2024
11 3 2024
© 2024. Asian Society of Gynecologic Oncology, Korean Society of Gynecologic Oncology, and Japan Society of Gynecologic Oncology
2024
Asian Society of Gynecologic Oncology, Korean Society of Gynecologic Oncology, and Japan Society of Gynecologic Oncology
https://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Objective

This study assessed the cost-effectiveness of atezolizumab in combination with chemotherapy for patients with advanced or recurrent endometrial cancer (EC) from the U.S. payer’s perspective.

Methods

A cost-effectiveness study was conducted using a Markov model based on ENGOT-en7/MaNGO/AtTEnd clinical trials. The population consisted of patients with EC, stratified by mismatch repair-deficient (dMMR) and mismatch repair-proficient (pMMR) subgroups. The model simulated patients receiving either atezolizumab plus chemotherapy or chemotherapy alone. Cost, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratio (ICER) were calculated using a Willingness-to-Pay (WTP) threshold of $150,000/QALY. Sensitivity analyses were performed.

Results

Adding atezolizumab to chemotherapy in dMMR EC resulted in an incremental gain of 3.31 QALYs but at an additional cost of $855,042, leading to an ICER of $258,391.07/QALY compared to chemotherapy alone. In pMMR EC, there was a gain of 0.50 QALYs with an additional cost of $140,502, resulting in an ICER of $279,239.72/QALY. The overall ICER for EC was $216,459.34/QALY. Scenario analysis indicated that administering atezolizumab for a maximum of 2 years improved cost-effectiveness in dMMR EC, with an ICER of $70,695.96/QALY falling within the predetermined WTP threshold.

Conclusion

For patients with advanced or recurrent EC, the combination of atezolizumab and chemotherapy may not prove cost-effective. However, administering atezolizumab for a limited period of maximum 2 years could improve cost-effectiveness in dMMR EC.

Synopsis

The cost-effectiveness of atezolizumab was assessed for the first time in advanced/recurrent endometrial cancer (EC). Atezolizumab plus chemotherapy may not prove cost-effective in advanced/recurrent EC. Administering atezolizumab for a maximum of 2 years led to improved cost-effectiveness in mismatch repair-deficient EC.

Atezolizumab
Endometrial Cancer
Economics, Pharmaceutical
Immunotherapy
China anti-cancer association HER2 target Chinese research fund CETSDSSCORP239018 Tianjin education commission for higher education, China 2022ZD064 Tianjin key medical discipline (specialty) construction project TJYXZDXK-010A
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pmcINTRODUCTION

Endometrial cancer (EC) is one of the most common types of gynecological malignancies. According to estimates by the American Cancer Society, there were approximately 66,200 newly diagnosed cases of EC and 13,030 related deaths in the U.S. in 2023 [1]. While the majority of patients are diagnosed with localized disease at an early stage, leading to a favorable 5-year survival rate of 95%, individuals with metastatic or recurrent disease have lower treatment response rates and a poor prognosis [2]. The 5-year survival rate for patients experiencing a recurrence of pelvic disease is 55%, but this drops to 17% for those with recurrent disease that has spread beyond the pelvic region [3].

For a considerable period of time, chemotherapy has been widely accepted as the established treatment approach for patients diagnosed with advanced or recurrent EC. Over the past 2 decades, advancements in the field of immunobiology and the implementation of immune checkpoint blockade therapy in cancer treatment have greatly fueled the investigation of immunotherapy as a promising strategy for managing EC [4].

On October 20, 2023, the results of the ENGOT-en7/MaNGO/AtTEnd trial were published [5]. This phase III study with placebo control examined the combination of atezolizumab with carboplatin and paclitaxel (ACP) in patients with advanced or recurrent EC. The trial revealed significant differences in treatment outcomes between the 2 mismatch repair-deficient (dMMR) and mismatch repair-proficient (pMMR) EC cohorts.

Specifically, the dMMR EC cohort demonstrated a 12-month progression-free survival (PFS) rate of 62.7% and an overall survival (OS) rate of 86.8%. In contrast, the pMMR EC cohort had a much lower 12-month PFS rate of 39.5% and an OS rate of 77.8%. These differences persisted at the 24-month mark as well, with the dMMR EC cohort showing a 50.4% PFS rate and a 75.0% OS rate. On the other hand, the pMMR EC cohort experienced poorer outcomes, with a 21.3% PFS rate and a 57.4% OS rate.

Given the differing treatment outcomes seen in different patient groups and the high cost of atezolizumab, it is crucial to conduct further research to evaluate its cost-effectiveness in each subgroup. Additionally, assessing the cost-effectiveness of medical interventions can help decision-makers and healthcare providers allocate limited resources more efficiently. Therefore, our analysis focuses on assessing the cost-effectiveness of combining atezolizumab with chemotherapy for advanced or recurrent EC patients. Specifically, we categorize them into dMMR and pMMR subgroups from the perspective of U.S. payers.

MATERIALS AND METHODS

1. Participants and interventions

In our research, we utilized data from the ENGOT-en7/MaNGO/AtTEnd trial [5] to develop our model and gather primary clinical information. This trial focused on patients with advanced or recurrent EC and divided them into dMMR and pMMR subgroups. The median age of the participants was 64 years.

The first group, referred to as the ACP group with 360 patients, received a combination of ACP. Specifically, patients in this group were given intravenous atezolizumab (1,200 mg), carboplatin (area under the curve [AUC]=5), and paclitaxel (175 mg/m2) every 3 weeks for the initial 6 cycles. After that, they continued to receive intravenous atezolizumab (1,200 mg) every 3 weeks until disease progression occurred. In order to explore different scenarios, we also conducted simulations where atezolizumab was administered for a maximum period of 2 years instead of until disease progression.

The second group, known as the carboplatin/paclitaxel (CP) group with 189 patients, received intravenous administration of carboplatin (AUC=5) and paclitaxel (175 mg/m2) every 3 weeks for 6 cycles, followed by regular follow-up.

Since detailed treatment plans for disease recurrence were not provided, we made assumptions based on clinical practice. In the ACP group, it was assumed that 50% of the patients would receive doxorubicin (60 mg/m2) every 3 weeks for 6 cycles, while the remaining patients would receive best supportive care as subsequent anticancer therapy. On the other hand, in the CP group, one-third of the patients would receive atezolizumab, one-third would receive doxorubicin, and one-third would receive best supportive care following disease recurrence.

2. Model construction

The development of the Markov model to evaluate the economic and clinical implications of atezolizumab involved using TreeAge Pro 2022 software. We then conducted statistical analysis using R 4.2.1 software [6]. Our model framework consisted of 3 distinct health states: PFS, progressive disease (PD), and death (Fig. S1).

PFS was considered the initial state, while death was the final state. Patients in the PFS state had the potential to transition to PD or death after receiving initial treatment. Patients receiving subsequent treatments in the PD state could deteriorate towards death. There was also a possibility of remaining in the same health condition after each cycle. However, once the disease progressed, regardless of salvage therapy effectiveness, patients could not return to the previous state. The model time horizon was set between the ages of 64 and 82, which coincides with both the median age of the patients from the ENGOT-en7/MaNGO/AtTEnd trial and the life expectancy at birth for U.S. females [57].

The primary outcomes of our analysis included overall costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios (ICERs). Half cycle correction and a 3% annual discount rate was used when calculating costs and life expectancy [89] (Table S1).

3. Costs estimates

The analysis of costs was performed from the perspective of U.S. healthcare payers who function as third-party entities in the public sector. We considered the utilization of direct medical expenses and health resources, encompassing drug procurement, disease management, drug administration, and treatment related adverse events (AEs) (Table S1). The drug dosage was determined based on the average body surface area of women in the U.S., which measures 1.84 m2 [6].

The drug prices were accessed from the Centers for Medicare & Medicaid Services [10], while expenses related to medication administration, supportive care, end-of-life palliative care, and disease management (which includes costs related to hospitalization, computed tomography, and laboratory examinations) were sourced from published databases [611121314]. Following previous similar studies and standard clinical practice, computed tomography scans were conducted every 9 weeks during the initial treatment period for the first 12 months, and then every 12 weeks until PD was identified [15]. The cost of laboratory testing and physician visits during the follow-up period is consistent with the frequency of computed tomography scans follow-ups.

To adjust for inflation and account for the values of U.S. dollar 2023, we incorporated the American Consumer Price Index for cost adjustments. Specifically, we utilized Tom’s Inflation Calculator to inflate the costs in alignment with the year 2023 [16]. For the analysis of outcomes, we employed the same Willingness-to-Pay (WTP) threshold as previous literature, which is $150,000 per QALY [8].

4. Survival and progression transition estimates

The ENGOT-en7/MaNGO/AtTEnd trial estimated the transition probability by extrapolating the PFS and OS curves using GetData Graph Digitizer software, version 2.22 [6]. To generate simulated patient data, we used the algorithm developed by Hoyle and Henley [17]. We fitted survival functions such as log-normal, log-logistic, exponential, gamma, gengamma, Weibull, and Gompertz distributions to the curve. The fitting process aimed to achieve the best fit based on Akaike/Bayesian information criteria and visual inspection of the graphs (Tables S2, S3, S4, Figs. S2 and S3).

To represent the cumulative number of patients in the preprogression health state over time, we utilized the concept of the cumulative area under the PFS curve. Similarly, the area above the OS curve was used to measure the total number of patients in the death health state. Additionally, the region between the PFS and OS curves characterized the cumulative number of patients in the postprogression health state.

For calculating time-dependent transition probabilities for the 2 patient groups, we used Microsoft Excel software and incorporated data from the ENGOT-en7/MaNGO/AtTEnd trial. These probabilities were then extrapolated to cover the model time horizon. The formula used to calculate the transition probability values for each model cycle is as follows: Transition Probabilities (tu)=1−Exp{λ(t−u)γ−λtγ}, (λ>0, γ>0). Here, u represents the model cycle, and tu represents the arrival at state t following u cycles. The background death rates for each age group were assessed using life tables for females in the U.S. (Table S5) [7].

5. Health-state utilities

In our study, the health utility values for PFS, PD, and death, which were derived from published investigations [9], were set at 0.817, 0.779, and 0, respectively. Following conventional research methodologies, our primary focus was on severe treatment-related AEs (grade ≥3) with an incidence rate of 5% or higher [18]. Given that mild AEs typically do not require intervention or incur significant treatment costs, we placed greater emphasis on severe AEs. The initial iteration of our models included the reduction in QALYs associated with all AEs [19] (Table S1).

6. Univariate and probabilistic sensitivity analyses

A comprehensive sensitivity analysis was performed in this study. Within this analysis, clinical parameters were systematically adjusted within a specified range to account for potential deviations of up to 20% from their baseline values. The variations resulting from these adjustments were visually represented with a tornado diagram. To conduct the sensitivity analysis, we employed 1,000 Monte Carlo simulations. In these simulations, pre-defined parameters were randomly and simultaneously varied based on specific distribution patterns. Specifically, cost-related factors were modeled using gamma distributions, while proportions and utilities followed beta distributions (Table S1).

RESULTS

1. Model validation

The obtained median PFS and median OS values in our simulation demonstrated concordance with the results reported in the ENGOT-en7/MaNGO/AtTEnd trial. The simulation exhibited an overall accuracy exceeding 99% (Table S6).

2. Base case results

In the dMMR cohort, the ACP group incurred total costs of $1,078,558 compared to the CP group’s costs of $223,517. The ACP group achieved 6.11 QALYs, while the CP group achieved 2.80 QALYs. As a result, individuals receiving ACP gained an additional 3.31 QALYs at an extra cost of $855,042 compared to the CP group. This led to an ICER of $258,391.07/QALY, which surpasses the predetermined WTP threshold of $150,000/QALY (Table 1).

Table 1 The results of the model’s base-case evaluation

Group	Costs ($*)	ΔCosts ($*)	QALYs	ΔQALYs	ICER ($*/QALY)	
dMMR CP	223,517	-	2.80	-	-	
dMMR ACP	1,078,558	855,042	6.11	3.31	258,391.07	
pMMR CP	190,908	-	2.51	-	-	
pMMR ACP	331,410	140,502	3.02	0.50	279,239.72	
Overall CP	200,568	-	2.62	-	-	
Overall ACP	377,601	177,033	3.44	0.82	216,459.34	
ACP, atezolizumab plus carboplatin/paclitaxel; CP, carboplatin/paclitaxel; dMMR, mismatch repair-deficient; ICER, incremental cost-effectiveness ratio; pMMR, mismatch repair-proficient; QALY, quality-adjusted life-year.

*U.S. dollar.

Moving on to the pMMR cohort, the ACP group had total costs of $331,410 compared to the CP group’s costs of $190,908. The ACP group achieved 3.02 QALYs, whereas the CP group achieved 2.51 QALYs. Consequently, individuals receiving ACP experienced a net gain of 0.50 QALYs, at an extra cost of $140,502 compared to the CP group. This resulted in an ICER of $279,239.72/QALY, which also surpasses the predetermined WTP threshold (Table 1).

Taking into account the overall cohort, the ACP group had total costs of $377,601 while the CP group had costs of $200,568. The ACP group achieved 3.44 QALYs, whereas the CP group achieved 2.62 QALYs. Consequently, individuals receiving ACP gained an additional 0.82 QALYs at an extra cost of $177,033 compared to the CP group. This resulted in an ICER of $216,459.34/QALY, once again surpassing the predetermined WTP threshold (Table 1).

3. Sensitivity analysis

The tornado diagram, as shown in Fig. 1, illustrates the significant impact of specific parameters on the ICER in this study. It is noteworthy that the cost of atezolizumab and the utility of PD/PFS have a substantial influence on the ICER, while other variables have a negligible effect on the outcome. By allowing all parameters to vary within their respective ranges, it is evident that there is no intersection between the generated ICER and the WTP values, indicating the robustness of our model's outcomes.

Fig. 1 Tornado diagram illustrating the results of univariate sensitivity analyses for dMMR EC (A), pMMR EC (B), and overall EC (C).

ACP, atezolizumab plus carboplatin/paclitaxel; CP, carboplatin/paclitaxel; dMMR, mismatch repair-deficient; EC, endometrial cancer; EV, expected value; ICER, incremental cost-effectiveness ratio; PD, progressive disease; PFS, progression-free survival; pMMR: mismatch repair-proficient.

To analyze the spatial distribution of data points, a Monte Carlo simulation was carried out with a sample size of 1,000 individuals. The results indicate that all scattered data points are exclusively located in the first quadrant of the coordinate axis and above the WTP threshold line. This observation suggests that the use of atezolizumab may result in a higher number of QALYs gained, along with increased costs that exceed the predetermined WTP threshold, as depicted in Fig. 2.

Fig. 2 Scatter plot diagrams showing the incremental cost-effectiveness of atezolizumab plus chemotherapy compared to chemotherapy alone in dMMR EC (A), pMMR EC (B), and overall EC (C).

ACP, atezolizumab plus carboplatin/paclitaxel; CP, carboplatin/paclitaxel; dMMR, mismatch repair-deficient; EC, endometrial cancer; pMMR: mismatch repair-proficient; WTP, Willingness-to-Pay.

Additionally, the probability sensitivity analysis demonstrates a definitive 100% likelihood of atezolizumab not meeting the cost-effectiveness criteria when using the predetermined WTP threshold (Fig. 3).

Fig. 3 The cost-effectiveness acceptability curves were generated through probabilistic sensitivity analyses for dMMR EC (A), pMMR EC (B), and overall EC (C).

ACP, atezolizumab plus carboplatin/paclitaxel; CP, carboplatin/paclitaxel; dMMR, mismatch repair-deficient; pMMR, mismatch repair-proficient.

4. Scenario analyses

Table 2 presents the findings from scenario analyses. We conducted simulations where atezolizumab was administered for a maximum period of 2 years rather than until disease progression. Among patients with dMMR, the ACP group experienced a reduction in total costs amounting to $350,813, whereas the CP group saw a decrease of $116,873 in expenses. As a result, the ICER for this subgroup was calculated as $70,695.96 per QALY, falling within the predetermined WTP threshold. In the case of the pMMR and overall cohorts, although each group exhibited a decline in total costs, the respective ICER values were determined to be $295,050.72 per QALY and $204,176.90 per QALY, exceeding the WTP threshold.

Table 2 The results of the model’s scenario evaluation

Group	Costs ($*)	ΔCosts ($*)	QALYs	ΔQALYs	ICER ($*/QALY)	
dMMR CP	116,873	-	2.80	-	-	
dMMR ACP	350,813	233,940	6.11	3.31	70,695.96	
pMMR CP	111,064	-	2.51	-	-	
pMMR ACP	259,521	148,457	3.02	0.50	295,050.72	
Overall CP	112,437	-	2.62	-	-	
Overall ACP	279,424	166,987	3.44	0.82	204,176.90	
ACP, atezolizumab plus carboplatin/paclitaxel; CP, carboplatin/paclitaxel; dMMR, mismatch repair–deficient; ICER, incremental cost-effectiveness ratio; pMMR, mismatch repair-proficient; QALY, quality-adjusted life-year.

*U.S. dollar.

The tornado diagram for dMMR scenario analyses reveals that the utility of PFS and the cost of atezolizumab have the most significant influence on the ICER, whereas other variables have a minimal impact on the outcome. When the parameters are varied within their respective ranges, there is no overlap between the calculated ICER and the WTP values, indicating the robustness of our findings (Fig. S4). The results from the Monte Carlo simulation for dMMR scenario analyses clearly show that all scattered data points fall below the WTP threshold line (Fig. S5). This provides a definitive indication of a 100% likelihood that atezolizumab meets the cost-effectiveness criteria when the predetermined WTP threshold is used (Fig. S6).

DISCUSSION

Our findings suggest that the combination of atezolizumab with chemotherapy does not demonstrate favorable economic characteristics. Among patients with dMMR EC, there is a significantly better survival benefit compared with pMMR, gaining an additional 3.09 QALYs. However, even with this benefit, the ICER still exceeds the predetermined WTP threshold. This is likely due to the longer PFS period resulting from prolonged use of atezolizumab, which leads to higher drug costs. Notably, the costs per cycle of atezolizumab had a notable influence on the sensitivity analyses. Despite varying within a certain range ($7,931.712 to 11,897.568 per cycle), the ICERs remained above the predetermined WTP threshold of $150,000/QALY, indicating a lack of cost-effectiveness.

In order to explore alternative scenarios, our scenario analysis focuses on comparing the pharmacoeconomic characteristics of administering atezolizumab for a maximum period of 2 years versus continuing its use until disease progression. During our simulations with different durations of atezolizumab usage, we made an interesting discovery. In dMMR EC cases, we observed that administering atezolizumab for a maximum of 2 years led to improved cost-effectiveness. The ICER of $70,695.96/QALY remains under the predetermined WTP threshold of $150,000/QALY, indicating that this treatment option is considered cost-effective. Furthermore, the results from our sensitivity analysis also support this conclusion.

It is important to note that currently, there are limited clinical trials comparing the impact of 2 durations of atezolizumab treatment-for up to 2 years versus until disease progression-on survival outcomes in EC. In fact, determining the optimal duration of immunotherapy in the management of advanced solid tumors remains controversial. A meta-analysis involving nearly 23,000 solid tumor patients showed that for those with advanced disease, using immunotherapy until disease progression did not improve treatment efficacy compared to using it for up to 2 years [20]. Future research should prioritize exploring the optimal duration of immunotherapy and its potential influence on survival outcomes. If the results indicate that the duration of atezolizumab treatment does not significantly affect survival, this would suggest that shorter durations, such as those in the ACP therapeutic regimen, could offer favorable pharmacoeconomic features.

The introduction of combination therapy, which combines immune checkpoint inhibitors with chemotherapy for the treatment of EC, holds notable clinical significance [51521]. This innovative approach has demonstrated considerable potential in benefiting numerous patients. However, a critical consideration is the substantial cost of these antitumor agents, which can lead to economic toxicity for patients with carcinoma. Economic toxicity, as defined in [22], encompasses the financial burden incurred by patients due to out-of-pocket medical expenses not covered by health insurance. Numerous studies have highlighted that such economic toxicity frequently contributes to treatment discontinuation, delays, or even abandonment [22].

In the context of U.S. healthcare insurance, striking a balance between access to innovative treatments and financial protection for patients is crucial [23]. Healthcare systems should, therefore, focus on strategies that provide patients with cutting-edge therapies while minimizing their financial burdens. One effective strategy could be negotiating lower prices for atezolizumab. This way, cost-effectiveness can be achieved through a delicate balance of drug pricing and insurance coverage. Furthermore, by adjusting the treatment duration of atezolizumab, healthcare costs may be contained without sacrificing clinical benefits.

The ENGOT-en7/MaNGO/AtTEnd trial has illuminated the different treatment outcomes observed between patients with dMMR and pMMR EC. Notably, those with dMMR EC showed higher 12-month and 24-month PFS rates compared to patients with pMMR EC. Similarly, they also experienced better OS rates. This variation in treatment response has implications for cost-effectiveness, especially when considering atezolizumab administration for up to 2 years. According to the analysis, a maximum 2-year course of atezolizumab emerges as a more financially viable option for patients with dMMR EC.

Given these findings, the MMR status has emerged as a critical factor in designing treatment strategies for EC patients. EC can be classified into 4 distinct subgroups based on genetic markers: Polymerase epsilon (POLE) ultramutated, MSI hypermutated, copy-number (CN) low, and CN high. These subgroups exhibit varying prognosis, recurrence risks, and mortality rates. Notably, the POLE ultramutated subgroup has the most favorable prognosis, while the CN high subgroup faces the least favorable outcomes. Patients with an ultra-mutated (POLE) or hyper-mutated (dMMR) profile tend to respond favorably to immune checkpoint inhibitors. A newer model, known as the Proactive Molecular Risk Classifier for Endometrial Cancer and based on the Institute of Medicine guidelines, has demonstrated its validity for both hysterectomy and diagnostic specimens, such as endometrial biopsies [2425]. Additionally, the presence of microsatellite instability-high or dMMR is associated with a higher tumor mutational burden, leading to a strong response to immune checkpoint inhibitors across different cancer types. However, a significant proportion of EC patients belong to the microsatellite stable (MSS) subtype, highlighting the urgent need to identify effective immunotherapeutic targets for this group. Recent studies have shown a promising correlation between LAG-3 expression and PD-L1 expression, suggesting that immunotherapy targeting LAG-3 could benefit MSS EC patients who may not respond well to immune checkpoint inhibitors [26].

After conducting a comprehensive analysis, we have discovered evidence that emphasizes the cost-effectiveness attributes of combining atezolizumab with chemotherapy. This finding has important implications for policy-making and practical implementation, as it effectively reduces the medical burden and promotes innovative measures to enhance the accessibility of high-value pharmaceutical products. According to our research, including atezolizumab in medical insurance reimbursement during the initial 2 years can significantly decrease the ICER.

The utility values of PFS and PD exerted a certain degree of influence on our model. We obtained the values of these 2 parameters from previously published health effect values related to EC patients [9]. In order to evaluate the impact of these parameter values on the model, sensitivity analysis was conducted. The results showed that within a range of ±20% variation, the conclusions of the model did not change, confirming good stability of the model.

To the best of our knowledge, this study is the first to conduct a cost-effectiveness analysis of atezolizumab in EC. However, it is important to recognize the limitations of this research. Firstly, we focused only on AEs of grade ≥3 with an occurrence rate of ≥5%, which is consistent with previous studies. This approach may lead to an underestimation of the ICER. Nevertheless, the treatment costs and impact on overall outcomes caused by low-grade and low-frequency AEs are minimal. Secondly, due to the incomplete publication of detailed results from the ENGOT-en7/MaNGO/AtTEnd trial, certain data are currently unavailable to us. Once updated results become available, we will need to conduct a new cost-effectiveness analysis to verify our findings.

Despite these limitations, our study provides valuable insights into the cost-effectiveness of combining atezolizumab with chemotherapy for advanced or recurrent EC, from the perspective of U.S. payers. Conducting further studies on atezolizumab and assessing its health outcomes could provide additional guidance for physicians and medical decision-making departments.

A notable question for future research to address is the optimal duration of immunotherapy maintenance. Currently, there are discrepancies in treatment durations among various drugs: dostarlimab can be extended up to 3 years, pembrolizumab lasts up to 2 years, while atezolizumab and durvalumab are administered only until disease progression or unacceptable toxicity occurs. Nevertheless, further investigation into the ideal treatment duration for each drug is crucial to maximize survival benefits for patients, minimize unnecessary side effects, and enhance cost-effectiveness. Through rigorous research, we aim to identify the most effective immunotherapy strategies tailored to different patient populations and disease types, ultimately to improve patients' quality of life and prolong their survival.

From the perspective of a payer in the U.S., combining atezolizumab with chemotherapy may not be cost-effective for patients with advanced or recurrent EC. On the other hand, limiting the administration of atezolizumab to a maximum of 2 years could potentially enhance cost-effectiveness in the treatment of dMMR EC.

SUPPLEMENTARY MATERIALS

Table S1

Model parameters and distributions

Table S2

AIC and BIC statistics for alternate parametric survival distributions in dMMR endometrial cancer

Table S3

AIC and BIC statistics for alternate parametric survival distributions in pMMR endometrial cancer

Table S4

AIC and BIC statistics for alternate parametric survival distributions in overall endometrial cancer

Table S5

Background mortality rate

Table S6

The difference between the ENGOT-en7/MaNGO/AtTEnd trial observed the mPFS and mOS, and the current cost-effectiveness model estimated data

Fig. S1

The Markov model simulated with 3 health states: progression-free survival, progressed disease and death.

Fig. S2

OS curves illustrating the original trial results and model-derived estimates in dMMR ACP group (A), dMMR CP group (B), pMMR ACP group (C), pMMR CP group (D), overall ACP group (E), and in overall CP group (F).

Fig. S3

PFS curves illustrating the original trial results and model-derived estimates in dMMR ACP group (A), dMMR CP group (B), pMMR ACP group (C), pMMR CP group (D), overall ACP group (E), and in overall CP group (F).

Fig. S4

Tornado diagram illustrating the results of univariate sensitivity analyses for dMMR scenario analyses.

Fig. S5

Scatter plot diagrams showing the incremental cost-effectiveness of atezolizumab plus chemotherapy compared to chemotherapy alone in dMMR scenario analyses.

Fig. S6

The cost-effectiveness acceptability curves were generated through probabilistic sensitivity analyses for dMMR scenario analyses.

Funding: This work was funded by China anti-cancer association HER2 target Chinese research fund (No. CETSDSSCORP239018), the key project of science and technology development fund of Tianjin education commission for higher education, China (No.2022ZD064), and Tianjin key medical discipline (specialty) construction project (TJYXZDXK-010A).

Conflict of Interest: No potential conflict of interest relevant to this article was reported.

Author Contributions: Conceptualization: C.P.

Data curation: H.G., S.Y.

Formal analysis: H.G., S.Y.

Software: H.G.

Supervision: C.P.

Writing - original draft: H.G., S.Y., C.P.

Writing - review & editing: H.G., S.Y., C.P.
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