Open Access, Peer-reviewed
pISSN 2005-0380   eISSN 2005-0399
    J Gynecol Oncol. 2024;35:e58. Forthcoming. English.
    Published online Jan 24, 2024.
    https://doi.org/10.3802/jgo.2024.35.e58
    © 2024. Asian Society of Gynecologic Oncology, Korean Society of Gynecologic Oncology, and Japan Society of Gynecologic Oncology
    Original Article

    Cost-effectiveness of tisotumab vedotin as a second- or third-line therapy for cervical cancer

    Gengwei Huo,1,2,3,4,* Wenjie Liu,1,2,3,4,* and Peng Chen1,2,3,4
      • 1Department of Thoracic Oncology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
      • 2National Clinical Research Center for Cancer, Tianjin, China.
      • 3Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin, China.
      • 4Tianjin’s Clinical Research Center for Cancer, Tianjin, 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. Email: chenpengdoc@sina.com

      *Gengwei Huo and Wenjie Liu contributed equally to this work.
    Received November 21, 2023; Revised December 12, 2023; Accepted January 05, 2024.

    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.

    Abstract

    Objective

    To evaluate the cost-effectiveness of tisotumab vedotin to treat recurrent or metastatic cervical cancer in second- or third-line from the U.S. payer perspective.

    Methods

    A Markov model with three-state was employed to simulate recurrent or metastatic cervical cancer patients who were administered either tisotumab vedotin or investigator’s choice of chemotherapy based on the phase III, open-labeled innovaTV 301 randomized clinical trial. The data on cost and health preferences were collected from the literature.

    Results

    Tisotumab vedotin generated an additional 0.25 quality-adjusted life-years (QALYs) compared to chemotherapy, but at an additional cost of $206,779. This results in incremental cost-effectiveness ratios of $839,107.88 per QALY. The results of the univariate sensitivity analysis indicated that cost of tisotumab vedotin, utility of progressive disease and progression-free survival had the greatest impacts on the outcomes. Probability sensitivity analysis showed that tisotumab vedotin had a 0% chance of being considered cost-effective.

    Conclusion

    Tisotumab vedotin was unlikely cost-effective compared to chemotherapy for recurrent or metastatic cervical cancer patients at a willingness-to-pay threshold of $150,000/QALY from the perspective of a U.S. payer. Lowering the prices of tisotumab vedotin could potentially enhance its cost-effectiveness.

    Synopsis

    The cost-effectiveness of tisotumab vedotin for recurrent or metastatic cervical cancer was first analyzed. The incremental cost-effectiveness ratio of tisotumab vedotin compared to chemotherapy was $839,107.88/quality-adjusted life-year. Tisotumab vedotin may not be a cost-effective option when compared to chemotherapy.

    Keywords
    Tisotumab Vedotin; Cervical Cancer; Quality-Adjusted Life Years; Cost-Effectiveness Analysis

    INTRODUCTION

    In 2020, there were 604,127 reported cases of cervical cancer worldwide, resulting in 342,000 deaths [1]. Among these cases, the United States alone accounted for an estimated 13,960 cases and approximately 4,310 deaths [2]. Human papillomavirus (HPV), recognized as the most prevalent sexually transmitted infection globally, is responsible for 90%–95% of squamous cell cervical cancers, rendering it one of the most preventable forms of cancer [3].

    Prophylactic vaccination against HPV has been a successful primary prevention method, significantly reducing the burden of HPV infection and related lesions. This approach stands out as the most cost-effective public health measure in combating cervical cancer [4]. In addition to vaccination, the implementation of Pap smear and HPV testing, as well as the utilization of mobile health interventions, have played a crucial role in secondary preventions strategies for cervical cancer. The introduction of new screening methods like p16/Ki67 and HPV self-testing has further enhanced the effectiveness of these preventive measures [5].

    However, owing to limited healthcare resources, there are still considerable geographic disparities in cervical cancer incidence. Approximately 90% of cases occur in lower- and middle-income countries. Certain geographic regions consistently experience high incidence rates, making cervical cancer the second most common type of cancer affecting women and the third most significant contributor to cancer-related deaths [6]. In developing nations lacking routine screening, more than 70% of cervical cancer cases are diagnosed at an advanced or metastatic stage. In contrast, in developed countries, initial discovery at the metastatic stage occurs in only about 5% of cases [7].

    Notwithstanding remarkable therapeutic advancements over the past two decades, around 30% of cervical cancer patients are still at risk of disease relapse, even after receiving initial optimal care [8]. The majority of patients who experience recurrent or metastatic disease will receive systemic treatment encompassing chemotherapy with or without the addition of an angiogenesis inhibitor. Over the past few years, pembrolizumab and cemiplimab, 2 antibodies that inhibit programmed cell death 1, have demonstrated promising outcomes in the treatment of patients with recurrent or metastatic cervical cancer (r/mCC) [9, 10, 11]. Despite the advancements made in immunotherapy for recurrent or metastatic disease during the initial treatment stages, there are still limitations in the available choices in later treatment lines. The development of new innovative mechanisms of action drugs for the treatment of r/mCC is of utmost urgency.

    Tisotumab vedotin is a medication that belongs to the class of antibody-drug conjugates (ADCs). The combination of tisotumab and monomethyl auristatin E harnesses the power of both targeted therapy and cytotoxic chemotherapy, offering a potential breakthrough in cancer treatment [12]. In the phase II, multicenter, single-arm, open-label study innovaTV 204, tisotumab vedotin demonstrated remarkable and long-lasting antineoplastic effectiveness, accompanied by controllable and well-tolerated safety characteristics in patients with previously treated r/mCC. The confirmed objective response rate (ORR) was 24%, composed of 7% complete and 17% partial responses [13]. On September 20, 2021, the U.S. Food and Drug Administration (FDA) announced tisotumab vedotin as the first antibody-drug conjugate approved as a treatment for r/mCC. The approval of tisotumab vedotin’s marketing application was accelerated based on positive results from the innovaTV 204 study. In the following phase III, open-labeled randomized innovaTV 301 trial [14], specific data were presented at the 2023 European Society for Medical Oncology conference. Tisotumab vedotin significantly improved progression-free survival (PFS) and overall survival (OS) compared with the investigator's choice of chemotherapy in second-line or third-line treatment for patients with r/mCC. The median overall survival (mOS) for the tisotumab vedotin group and the investigator’s choice chemotherapy group was 11.5 and 9.5 months, respectively, demonstrating a significant difference (p=0.004) with a hazard ratio (HR) of 0.70 (95% confidence interval [CI]=0.54–0.89). The 12-month OS rates were 48.7% and 35.3%, respectively. In terms of PFS, the tisotumab vedotin group had an median progression-free survival (mPFS) of 4.2 months, while the investigator’s choice chemotherapy group had an mPFS of 2.9 months, with an HR of 0.67 (95% CI=0.54–0.82; p<0.001). The 6-month PFS rates were 30.4% and 18.9%, respectively. The ORR was 17.8% and 5.2% (p<0.001), and the disease control rate (DCR) was 75.9% and 58.2%. The median duration of response (DOR) was 5.3 and 5.7 months, respectively. Regarding treatment-related adverse events (TRAEs), the incidence rate of any-grade events was 87.6% with tisotumab vedotin and 85.4% with the investigator’s choice chemotherapy. The rate of grade ≥3 adverse events (AEs) was lower with tisotumab vedotin (29.2%) than the investigator’s choice chemotherapy (45.2%).

    Tisotumab vedotin has shown promising outcomes and manageable side effects in the treatment of r/mCC. However, the evaluation of its cost-effectiveness is essential due to its relatively high drug cost and the lack of previous pharmacoeconomic analyses on tisotumab vedotin. Conducting further research in this area is essential to assess the economic implications of using tisotumab vedotin as a second- or third-line therapy option. We aim to provide a comprehensive and evidence-based assessment of the economic value of tisotumab vedotin in comparison to chemotherapy from the perspective of payers in the U.S. The results derived from the present investigation will provide valuable insights for decision-makers and healthcare practitioners, assisting them to make judicious determinations regarding the allocation of limited healthcare resources.

    MATERIALS AND METHODS

    1. Model construction

    The TreeAge Pro 2022 software (version 2022.1.2) was used to construct Markov model to elucidate the economic implications and clinical outcomes associated with tisotumab vedotin. The model framework encompasses three distinct health states that are mutually exclusive: PFS, progressive disease (PD), and death (Fig. S1). PFS and death were defined as the initial and terminal states. Patients in the PFS state could transition to PD or death after the initial treatment, and those who received subsequent treatments in the PD state might deteriorate towards death. There was also a possibility of remaining in the same condition after a cycle. However, regardless of the effectiveness of salvage therapy, patients could not return to the former state once the disease progressed. Every three weeks constituted a model cycle, and model horizon was set as a lifetime. The primary outcomes of our analysis included overall costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios (ICERs). The computational framework employed half-cycle correction and incorporated a 3% annual discount rate to estimate the cost estimation and life expectancy projection [15].

    2. Participants in the model structure

    The fundamental clinical information was obtained from the innovaTV 301 trial [14]. The trial included female patients with r/mCC, with a median age of 50, who had previously received chemotherapy with or without bevacizumab and/or PD-(L)1 inhibitors. These patients randomized allocation procedure to assign participants into two distinct groups, ensuring a balanced distribution in a 1:1 proportion: the tisotumab vedotin group and the investigator's choice chemotherapy group (gemcitabine, vinorelbine, topotecan, pemetrexed, or irinotecan). Patients in the tisotumab vedotin group received 2.0 mg/kg of the drug intravenously every 3 weeks until disease progression or unacceptable side effects occurred. The investigator's choice chemotherapy group had several options for chemotherapy regimens, each administered at specific doses: gemcitabine: 1,000 mg/m2 IV on Days 1 and 8, every 3 weeks; vinorelbine: 30 mg/m2 IV on Days 1 and 8, every 3 weeks; topotecan: 1 mg/m2 IV on Days 1 to 5, every 3 weeks; pemetrexed: 500 mg/m2 IV on Day 1, every 3 weeks; irinotecan: 100 mg/m2 IV weekly for 4 weeks, with a treatment cycle every 6 weeks.

    Since detailed treatment plans have not been released, it is presumed that after disease recurrence, 50% of the patients received additional anticancer therapy, while the remaining patients received best supportive care. The chemotherapy for additional therapy included docetaxel (75 mg/m2 IV on Day 1, every 3 weeks). All patients received one-time end-of-life care during the terminal stage prior to their deaths. The dosage of the drug was determined based on an average body surface area of 1.86 m2 for women in the United States [16]. All patients received six cycles of chemotherapy, followed by regular follow-up.

    3. Costs estimates

    The evaluation of costs was carried out from the perspective of American third-party public healthcare payers. We considered health resource utilization and direct medical expenses, encompassing drug procurement, disease management, drug administration, and TRAEs (Table 1). We extracted drug prices from the Centers for Medicare & Medicaid Services [17]. The expenses associated with the TRAEs management, administration of medication, best supportive care, end-of-life palliative care, and disease management (which includes costs related to hospitalization, computed tomography, and laboratory examinations) were obtained from pre-existing databases that have been published previously [18, 19, 20, 21, 22, 23]. Based on the innovaTV 204 trial and clinical practice, costs associated with computed tomography scans were performed at baseline, and then at 6-week intervals for the first 30 weeks, followed by 12-week intervals [13]. Laboratory testing and administration cost were documented in every treatment cycle. To account for inflation and reflect the values of U.S.D. 2023, we employed the American Consumer Price Index (CPI) for cost adjustments. In order to adjust for inflation and ensure consistency with the year 2023, the Tom’s Inflation Calculator was utilized for cost inflation [26]. A willingness-to-pay (WTP) threshold of $150,000 per QALY was employed to analyze the outcomes [20].

    Table 1
    Model parameters and distributions

    4. Survival and progression transition estimates

    The GetData Graph Digitizer software (version 2.22) was used to extrapolate the transition probabilities from the PFS and OS curves of the innovaTV 301 trial. We used R software (version 4.2.1; R Foundation for Statistical Computing, Vienna, Austria) to reconstruct patient-level data. Subsequently, we applied various parametric functions, such as Weibull, exponential, gamma, Gompertz, generalized gamma, log-normal, and log-logistic, to fit the reconstructed survival data. To determine the appropriate parametric distributions, we evaluated them using the Akaike information criterion (AIC) and Bayesian information criterion (BIC) (Fig. S2, Table S1). The concept of the “area under the PFS curve” is employed to represent the cumulative number of patients in the “pre-progression” health state throughout the course of time. Similarly, the “area above the OS curve” serves as a measure for the cumulative number of patients in the “death” health state, while the region between the OS and PFS curves characterizes the cumulative number of patients in the “post-progression” health state. We utilized Microsoft Excel software to calculate time-dependent transition probabilities for the 2 groups of patients, incorporating data from innovaTV 301 trial. These probabilities were then extrapolated to cover a lifetime horizon. The transition probabilities values for each model cycle were calculated using the formula: Transition Probabilities (tu)=1−exp{λ(t−u)γ−λtγ}, λ>0, γ>0. Where u denotes the model cycle, and tu denotes the arrival at state t following u cycles. Each age group of the background death rates were assessed using United States female life tables (Table S2) [27].

    5. Health-state utilities

    The health utility values for PFS, PD, and death were obtained from previously published investigations and were determined to be 0.817, 0.779, and 0, respectively [24]. To calculate treatment-specific estimates of expected QALYs, we multiplied the proportions of patients in the “pre- and post-progression” health states by the corresponding utility estimates, which were discounted over time. These results were then accumulated over time. Similar to conventional research approaches, the initial cycle of the models includes the decrease in QALYs associated with AEs, with primary emphasis on severe treatment-related AEs (grade ≥3) occurring at an incidence rate of 5% or higher, as mild AEs typically do not require treatment or result in significant treatment expenses [15, 27, 28].

    6. Univariate and probabilistic sensitivity analyses

    The impact of key parameters on the ICER was evaluated through a one-way sensitivity analysis. The results were presented in the form of a tornado diagram, which summarized the range of values for each parameter and their influence on the ICER. Based on the 95% CIs, we sequentially varied the parameters within their specified lower and upper bounds. The reported values were utilized whenever available, or in cases where they were not provided, the standard error was assumed to be 20% of the point estimate. A total of 1,000 Monte Carlo simulations were employed to illustrate the sensitivity analysis regarding the probability. This involved simultaneously and randomly varying preset parameters according to specific distribution patterns. The costs follow gamma distributions, while the proportion and utility follow beta distributions (Table 1).

    RESULTS

    The mPFS and mOS values derived from our simulation aligned closely with those documented in the innovaTV 301 trial. Specifically, our model estimated an mPFS of 4.22 months for the tisotumab vedotin group, and 2.83 months for the chemotherapy group. These findings are in agreement with the innovaTV 301 trial results, which reported an mPFS of 4.2 months for the tisotumab vedotin group and 2.9 months for the chemotherapy group. With regards to mOS analysis, our models estimated an OS of 11.47 months for the tisotumab vedotin group and 9.53 months for the chemotherapy group. These projections align closely with the innovaTV 301 trial data, which reported an OS of 11.5 months for the tisotumab vedotin group and 9.5 months for the chemotherapy group (Table S3).

    1. Base case results

    In the context of our Markov model, the cumulative costs reached $293,641 for the tisotumab vedotin group and $86,862 for the chemotherapy group. The tisotumab vedotin group resulted in 1.15 QALYs, while the chemotherapy group resulted in 0.90 QALYs. As a result, tisotumab vedotin gained an increase by 0.25 QALYs at an extra cost of $206,779 compared to chemotherapy. This led to an ICER of $839,107.88/QALY, exceeding the pre-set WTP threshold of $150,000 per QALY (Table 2).

    Table 2
    Base-case results of the model

    2. Sensitivity analysis

    The tornado diagram in Fig. 1 demonstrates the significant impact of specific parameters on the ICER, including the cost of tisotumab vedotin, utility of PD and PFS, and discount rate. Other variables have minimal impact on the outcome. The robustness of our model outcomes is validated when all parameters vary within their respective ranges and there is no intersection between the generated ICER and the WTP values.

    Fig. 1
    Tornado diagram for univariate sensitivity analyses.
    ICER, incremental cost-effectiveness ratio; PD, progressive disease; PFS, progression-free survival.

    To explore the spatial distribution of data points, we conducted a Monte Carlo simulation with a sample size of 1,000. The results show that all scattered points are positioned in the first quadrant of the coordinate axis and lie above the WTP line. This suggests that the utilization of tisotumab vedotin may lead to more QALYs and an increase in cost (Fig. 2). Furthermore, the probability sensitivity analysis reveals a 0% chance for tisotumab vedotin to be deemed cost-effective for patients using a WTP threshold of $150,000 per QALY (Fig. 3).

    Fig. 2
    Incremental cost-effectiveness scatter plot diagram for tisotumab vedotin plus chemotherapy versus chemotherapy.
    WTP, willingness-to-pay.

    Fig. 3
    The cost-effectiveness acceptability curves for probabilistic sensitivity analyses.

    DISCUSSION

    According to our model findings, our base case analysis suggest that tisotumab vedotin yields higher health outcomes (1.15 QALYs vs. 0.90 QALYs) but is not considered cost-effective (an ICER of $839,107.88/QALY, exceeding the WTP threshold of $150,000 per QALY) compared to chemotherapy in patients with r/mCC. The probabilistic sensitivity analyses indicate that tisotumab vedotin is not considered cost-effective alternative, as it exceeds the WTP threshold of $150,000 per QALY when compared to chemotherapy.

    With significant efficacy demonstrated in various clinical trials, such as innovaTV 201 [29], innovaTV 204 [13], innovatv-205 [30], innovaTV-206 [31], and innovaTV-301 [14], which have either published their results or are currently ongoing to evaluate the use of tisotumab vedotin as monotherapy or in combination therapies for first-line or pretreated r/mCC, tisotumab vedotin has already shown promise as a potential breakthrough therapy for cervical cancer patients. However, the high costs associated with innovative treatments often raise concerns about their accessibility and affordability.

    The high cost of tisotumab vedotin has the most significant impact on the sensitivity analysis in this model. Despite the variation in the cost of tisotumab vedotin across a range (134.61–201.914 $/mg), the ICER remains higher than $150,000 per QALY, indicating a lack of cost-effectiveness. Therefore, a practical solution to achieving cost-effectiveness in treatment is to reduce the price of tisotumab vedotin.

    The current pricing system for anti-cancer drugs in the healthcare insurance system places a considerable burden. The high costs of these medications directly contribute to the rising healthcare expenditures. While the FDA’s accelerated approval of tisotumab vedotin represents an important step towards providing a more effective treatment strategy for r/mCC patients, it is essential to consider the affordability and sustainability issues arising from the higher price of tisotumab vedotin from the perspective of third-party public healthcare payers. Additionally, from the patient’s point of view, the high cost may lead to economic toxicity as they are required to bear a portion of the medical expenses that may not be fully covered by health insurance. The economic toxicity of medication can result in patients with financial constraints interrupting, postponing, or abandoning the treatment regimen [32].

    One potential solution is to initiate negotiations between pharmaceutical companies, payers, and relevant stakeholders to determine fair pricing for tisotumab vedotin. By engaging in open and transparent discussions, it becomes possible to achieve a balance between incentivizing innovation and ensuring affordability. Additionally, these negotiations should also seek to broaden insurance coverage to include tisotumab vedotin as part of essential healthcare services. It is important to recognize that balancing accessibility and affordability is challenging. While negotiating price reductions and expanding insurance coverage are feasible strategies, they should be implemented alongside measures to ensure the sustainability of the healthcare system. This may involve monitoring and evaluating the cost-effectiveness of innovative drugs, promoting competition among pharmaceutical companies, and exploring alternative payment models.

    The utility values of PD and PFS status are 2 other significant factors that impact the sensitivity analysis in this model. The health utility data used to evaluate the utility of PFS and PD status was derived from published studies [24]. In addition, a wide range of utility values was utilized for sensitivity analyses. The findings indicated that the variations in utility values did not affect the conclusions, thereby suggesting that tisotumab vedotin is unlikely to be cost-effective, even when considering utility values at their highest and lowest levels.

    The results of this cost-effectiveness analysis of tisotumab vedotin are highly significant in the field of cervical cancer treatment. This study, being the first of its kind, provides crucial insights into the economic viability and value of using this innovative targeted antibody-drug conjugate that targets tissue factor. The findings of this study can help healthcare providers improve cost management and explore more economically viable approaches to delivering medical services. They can offer patients comprehensive information about treatment options, including efficacy, costs, and potential economic advantages of different medication regimens. These results empower patients to make well-informed decisions regarding their treatment. Hospital administrators can effectively control and reduce expenses within the U.S. healthcare system framework. Furthermore, managers can use economic evaluation to assess the value of utilizing these drugs in the hospital and identify alternative treatments that provide relative cost-effectiveness. In light of these findings, informed choices can be made to select treatment plans that not only yield positive outcomes but also align with financial feasibility. This will optimize the quality and efficiency of healthcare services while ensuring the long-term financial sustainability of hospitals.

    There are some limitations in this study. Firstly, relying on Medicare reimbursement as an estimation of costs may not fully capture potential differences in reimbursement rates from other public or commercial sources in the United States healthcare system. The lack of transparency regarding commercial drug costs further complicates the inclusion of commercial reimbursement rates in cost-effectiveness analyses. However, the sensitivity analyses conducted in this study address this limitation by considering the variability in reimbursement rates. Secondly, in line with the majority of prior research, our focus was exclusively on AEs of grade ≥3 and with an incidence rate of ≥5%. Utilizing this method carries the possibility of underestimating the ICER, however, the treatment expenses and AEs of mild-grade and infrequent AEs exert minimal influence on the final outcomes. Thirdly, due to the lack of complete publication of detailed results from the innovaTV 301 trial, certain data is currently unavailable to us. For example, we did not include local lesion radiotherapy, surgeries, immunotherapy, and only focused on mono-chemotherapy and best supportive care when considering the treatment following disease progression. This omission limits the real-world applicability as patients advance to this stage. However, these factors have minimal impact on the results of ICER. Despite the aforementioned limitations, our research offers invaluable initial insights into the cost-effectiveness of tisotumab vedotin in treating r/mCC, taking into account the perspective of payers in the United States.

    In summary, from the perspective of U.S. payers, it is projected that tisotumab vedotin may not offer cost-effectiveness for the treatment of r/mCC patients when compared to chemotherapy. This projection is based on a WTP threshold of $150,000 per QALY. Lowering the price of tisotumab vedotin may lead to positive economic outcomes, which can help clinicians make better decisions regarding the treatment of r/mCC. Nevertheless, it is crucial to acknowledge that this study possesses certain methodological constraints, necessitating the acquisition of additional clinical and economic real-world data of superior quality. Through prioritizing the collection of such data, a robust evidence foundation can be established to ascertain the worth of diverse therapeutic alternatives within the field of oncology.

    SUPPLEMENTARY MATERIALS

    Table S1

    AIC and BIC statistics for alternate parametric survival distributions

    Click here to view.(28K, xls)

    Table S2

    Background mortality rate

    Click here to view.(28K, xls)

    Table S3

    Comparison of mPFS and mOS in the innovaTV 301 trial with model-estimated data

    Click here to view.(27K, xls)

    Fig. S1

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

    Click here to view.(488K, ppt)

    Fig. S2

    Comparison of OS (A, B) and PFS (C, D) curves for original trial data and model-estimated data.

    Click here to view.(592K, ppt)

    Notes

    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 (No.2022ZD064), China, 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., L.W.

    • Formal analysis: H.G., L.W.

    • Software: H.G., L.W.

    • Supervision: C.P.

    • Writing - original draft: H.G., L.W., C.P.

    • Writing - review & editing: H.G., L.W., C.P.

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