Methodological Challenges in Dutch HTA of Non-Oncological Orphan Drugs: A Retrospective Analysis and Price Comparison Using different Pricing Models

Methodological Challenges in Dutch HTA of Non-Oncological Orphan Drugs: A Retrospective Analysis and Price Comparison Using different Pricing Models | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Methodological Challenges in Dutch HTA of Non-Oncological Orphan Drugs: A Retrospective Analysis and Price Comparison Using different Pricing Models Jelle Walraven, Mahtab Kaveh, Carin Uyl - de Groot This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6569819/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 08 Jan, 2026 Read the published version in Orphanet Journal of Rare Diseases → Version 1 posted 5 You are reading this latest preprint version Abstract Background Cost-effectiveness analyses can have limited informative value for pricing and reimbursement decisions for orphan drugs. In cases where cost-effectiveness cannot be reliably assessed or achieved, value-based pricing principles may not be applicable. As a result, alternative pricing models have been proposed. It remains unclear how these alternative approaches compare to one another and to traditional value-based pricing. This study aims to explore and compare these pricing models in the context of orphan drugs. Methods All cost-effectiveness assessments of non-oncological orphan drugs published by the Dutch National Health Care Institute between 2015 and 2024 were analyzed to identify methodological challenges and recommended value-based price estimates. For each treatment, prices were also estimated using a cost-plus pricing model and a discounted cash-flow model. These estimates were then compared to value-based prices and public list prices. Results Cost-effectiveness assessments of 12 different therapies were found, 11 of which provide information for determining a value-based price. All assessment reports cited major uncertainties or unresolved issues in one or more of the following areas: (1) lack of a suitable comparator, (2) sub-optimal disease understanding, (3) limited evidence to inform models, (4) effect uncertainty and (5) flawed QoL measurement. Only one single treatment was found to be cost-effective at the appropriate threshold. Recommended value-based prices were found to fall below (1 therapy), within (6 therapies) or above (4 therapies) the price ranges of the two alternative models. Conclusion Challenges cited in literature are present in Dutch assessments of the cost-effectiveness of orphan drugs. Although these issues cause considerable uncertainty, they do not negate CEA’s current ability to inform decision-making. Still, orphan drugs tend to be far from cost-effective, providing a challenge for patient access that is both timely and financially feasible. Alternative models like cost-plus pricing and discounted cash-flow tend to generate even lower price estimates and rely on considerable assumptions, making them unlikely to offer a viable solution in their current state. Health economic assessment cost-effectiveness analysis pharmaceutical pricing orphan drugs orphan diseases Figures Figure 1 Figure 2 1. Introduction Cost-effectiveness analysis (CEA) is a prevalent method to help inform decision-makers regarding pricing and reimbursement of new therapies. For new pharmaceutical therapies seeking reimbursement on an added value claim in the Netherlands, the CEA is mandatory (1). The central outcome of interest is the incremental cost-effectiveness ratio (ICER), which represents the ratio between incremental costs and incremental health benefits, typically expressed as the additional cost per QALY gained. The ICER is benchmarked against a predefined willingness-to-pay threshold to determine the maximum price that ought to be paid for a treatment and what discount is required on the initial list price to justify reimbursement. This approach is known as value-based pricing. Although CEA is not the only factor in reimbursement decisions, it plays a significant role, as the ICER is used to inform price negotiations between manufacturers and payers. When it comes to orphan drugs, however, two issues undermine the informative value of CEA for pricing and reimbursement decisions. First, the inherent characteristics of rare diseases complicate health economic assessments, reducing the feasibility of robust economic evaluations and increasing uncertainty (2). Second, orphan drugs typically do not show cost-effectiveness under the traditional economic evaluation criteria (2–4). HTA agencies understand, and sometimes even accept, these limitations of value-based pricing for orphan drugs. Still, when cost-effectiveness cannot be adequately assessed or achieved, value-based pricing can pose an obstacle to timely access, as CEA’s ability to reliably estimate a price that should be acceptable to both payers and pharmaceutical companies is hindered. As a result, other approaches, such as cost-plus pricing (CPP) and the discounted cash flow (DCF) method have recently been suggested in case conducting a CEA is unfeasible or when a drug fails to realistically meet the cost-effectiveness threshold (5,6). Interestingly, these models for determining 'fair' or 'reasonable' prices for (orphan) drugs have been published from opposing perspectives, despite using similar parameters. One approach seeks to determine the maximum price the payer should be willing to pay, whereas the other estimates the minimum price that pharmaceutical companies should consider acceptable. These new pricing models have seen little application and minimal comparison with the more value-based pricing approach. This paper describes the challenges incurred with CEA-informed value-based pricing of orphan drugs in literature and Dutch HTA practice. Additionally, it presents price estimates using two alternative approaches which are compared to value-based prices in the Netherlands. 2. Background Although the methodological challenges and low probability of cost-effectiveness associated with orphan drugs are not new but are increasingly relevant to pricing and reimbursement conditions, as is demonstrated by two recent cases from the Netherlands. 2.1 Methodological challenges A number of different factors inherent to orphan drugs can negatively impact the practical feasibility and uncertainty of CEA (7). A practical example from the Netherlands is the case of atidarsagene autotemcel. Limited data availability caused considerable uncertainty about utilities and treatment effectiveness between patient subgroups. Disagreement on response classification and treatment effect durability further complicated the assessment(8). Despite the payer’s willingness to accept a higher price and thus exceeding the willingness-to-pay threshold due to the unique circumstances, no agreement on an acceptable price could initially be reached. Reimbursement of Atidarsagene autotemcel was temporarily declined for a period as a result. 2.2 Unfavourable cost-effectiveness Although proper pharmacoeconomic modelling practices may address these inherent issues, most (ultra-)orphan drugs will not meet conventional criteria for cost-effectiveness (3). While there seems to be a certain willingness to get these therapies to patients despite their uncertainty, high cost and low probability of being cost-effective both in general (4) and in the Netherlands specifically (9), there seems to be a limit to such tolerance. A recent example is olipudase alfa. In a historical first, the CEA report submitted by the registration holder was not formally assessed by the HTA agency the Dutch National Healthcare Institute (ZIN), as the submitted ICER’s of €1.070.000 and €1.600.000 million clearly indicated the treatment is not cost-effective. No conclusions were drawn regarding the quality of the analysis, but a full assessment of the treatment’s cost-effectiveness was not expected to result in a reliable price estimate. Olipudase alfa was nonetheless recommended for reimbursement on the condition that price negotiations would result in a cost-effective price (10). 2.3 Alternative pricing approaches In cases where cost-effectiveness cannot be properly assessed or reasonably achieved, and value-based pricing principles can thus not be applied, a non-arbitrary method is still needed to justify prices that are justifiable for both the supplier as well as the payer in a context where market principles do not apply. Two alternative approaches have recently been proposed: cost-plus pricing and the discounted cashflow method. 2.3.1 Cost-plus pricing Certain researchers have argued that if an orphan drug does not meet the cost-effectiveness threshold, other mechanisms should be used to determine a just and reasonable price (Fellows and Hollis, 2013). This approach considers the interest of payers as it seeks to determine a maximum price that ought to be paid to acquire these therapies. Since pharmaceutical firms cite higher average costs in justification of higher orphan drug prices, the price is based on the incurred costs and a pre-determined profit margin. Various authors have applied CPP models to specific orphan drugs (11,12). A more universal model has been proposed by the International Association of Mutual Benefit Societies (13). 2.3.2 Discounted cash flow Other authors have adopted a supply-side perspective, postulating that pharmaceutical innovation is driven by profit-seeking companies and that drug prices must be sufficiently high for companies to commit to such a risky endeavour (14). They argue that the business valuation principles guiding investment decisions in the pharmaceutical industry could also be utilized for public price setting. When the ICER exceeds the threshold, a DCF analysis could be performed in which expected future returns are contrasted to upfront investment using a risk-adjusted capital cost threshold. This could help determine a price at which companies are sufficiently incentivized to develop new drugs for rare diseases (15). 2.3.3 Comparing both approaches Strikingly, both CPP and DCF rely on similar determinants, despite fundamentally opposing view on what forms the basis of a reasonable price. It is, however, unclear how the price estimates resulting from these two approaches compare to each other and to the traditional value-based pricing method in the context orphan drugs. This paper aims to address just that matter. 3. Methods All CEA reports on non-oncological orphan drugs published by ZiN between 2015 (introduction of the new ‘lock’ HTA procedure) and 2024 were collected in order to identify methodological challenges. Prices for these treatments were then re-determined using the CPP model by AIM (13) and the DCF model by Nuijten et al. (14,15) and compared to the value-based prices and public list prices. 3.1 Analysis of CEA reports A complete list of Dutch HTA assessments was extracted from the pharmaceutical lead time dashboard of the Dutch Ministry of Health (16) and cross-referenced with EMA’s register of orphan designations (17). Matches were manually checked for pharmacoeconomic reports. All resulting reports were systematically reviewed by both authors for explicitly mentioned methodological challenges. These challenges were then categorized. 3.2 CPP and DCF price estimates For the price estimates, Excel versions of the CPP model by AIM and the DCF model by Nuijten et al. were obtained through their respective developers. Both models share the same key variables, which are outlined in Table 1 . The approach differs in two aspects, however. The first lies in the conceptualization of expected return. AIM’s CPP model allows for a fixed profit margin whereas the DCF model employs a risk-adjusted discount rate. In both models, the same base percentage is used. The second is probability of success, which is only included in the DCF model. The DCF model explicitly incorporates the probabilities of successfully progressing through the stages of clinical development, whereas the standard DCF approach assumes that the cost of failure is already embedded in the overall R&D investment. To facilitate comparison between both models, equal values are used. Since no data is available on the R&D investment for all therapies, the default minimum and maximum values of AIM’s model (€250.000.000 and €2.500.000) were used to establish a range. Of these R&D expenditures, 42% is attributed to Europe, as it represents 42% of the population of main markets for the innovative drugs. Subsequently, 4.58% is attributed to the Netherlands as AIM advocates differential pricing based on gross domestic product per capita (13). Table 1 provides an overview of the common input parameters and their respective sources. The exact values for the production costs, innovation bonus and patients treated for each treatment are provided in appendix A as they are different for each therapy. Table 1 Model input parameters Variable Value Source R&D investment € 250.000.000 and € 2.500.000.000 AIM Production costs Varies per therapy (Appendix A) Treatment SMPC Sales and medical information 30% AIM Expected return 8% AIM Innovation bonus Varies per therapy (Appendix A) Treatment FT Allocation base NL 1,9236% AIM Patients treated NL Varies per therapy (Appendix A) ZIN Success rate 100% Assumed 3.3 CEA price estimates Value-based prices for the drugs were estimated by applying the recommended discount to the list price posed by the pharmaceutical company for each treatment. For onasemnogene abeparvovec, risdiplam and lumacaftor / ivacaftor the CEA value-based price is the average of the value-based price of both CEA sub-groups, since insufficient data in the HTA reports prevented the calculation of a weighted average price based on the expected patient distribution across sub-groups. The value-based price of cannabidiol is based on the average dose scenario rather than the maximum dose scenario. For nusinersen, only the SMA type 2/3 subgroup was considered, as the type 1 subgroup did not result in a meaningful discount. 4. Results 4.1 Orphan drugs with CEA A complete set of non-oncological orphan drugs with a pharmacoeconomic assessment was developed through the steps outlined in Fig. 2 . Oncological drugs were excluded since they may hold orphan status for certain indications whereas other indications are not granted such a status. Through this process, 12 completed HTA reports with a CEA were found, of which 3 were resubmissions of reports that were initially rejected based on insufficient methodological quality. One report was accepted despite the structural uncertainty making the results unfit for decision making because it was deemed unlikely that resubmission and reassessment would lead to sufficient improvement (18). The reports contain the CEA results of 12 different treatments on 18 patient sub-groups, providing ICER’s for 17 out of these sub-groups. An overview of these results is presented in Table 2 (full page at end of manuscript). 4.2 Methodological challenges ICER’s estimated for 11 out of the 12 treatments were deemed appropriate for reimbursement decision-making, despite the methodological challenges and uncertainty involved. All reports mentioned major sources of uncertainty or unresolved discussion points listed in the concluding section of the assessment report, which addresses transparency, methodology, inaccuracy, bias, and lack of evidence. One of the CEA models was described as having a subjective character as a result of the heavy reliance on judgement-based estimates for both utilities and costs (19). Identified challenges were grouped into five overarching categories. 4.2.1 Lack of a suitable comparator Only three (20–22) were compared head-to-head to another treatment for at least one patient subgroup. One other treatment was compared with the standard of care which consisted of a variety of pharmaceutical and non-pharmaceutical care (19). The remaining treatments were compared with best supportive care (while also being added to best supportive care). In one instance (23), an attempt was made to compare trial results with a competing treatment. However, the small study populations introduced bias and significant uncertainty, making the data unsuitable for reliable comparison. Three therapies were assessed using only data from single-arm studies (8,23,24) for at least one patient sub-group, as a consequence of the extreme rarity of the disease or ethical considerations involving young enfants. CEA’s, by definition, seek to compare two treatment alternatives. The absence of such an alternative deteriorates the basis for determining the true value of these treatments in comparison to existing alternatives. 4.2.2 Sub-optimal disease understanding A lack of evidence and understanding of the disease lead to systematic uncertainty in the fundamental elements of the model. One frequently mentioned issue concerns the basic definition of health states, resulting in arbitrary definitions of health states (19,25) or overly complex measures with limited clinical relevance (26). Another issue reported is the absence of validated measurement instruments for certain patient (age) groups (8,25) and the inability of existing instruments to capture the full range of outcomes (24). In two instances, the registration holder indicated that the primary measurement instruments were either not sensitive enough to detect clinically relevant changes (24) or not suitable for linking utilities to costs (18). Lack of evidence on disease progression was cited to also complicate modelling of long-term implications for both the treatment and control arm (8,23,24,26). 4.2.3 Limited evidence to inform models Another issue mentioned is the limited data that is available to inform the model. In one instance, this lack of sufficient data compelled the registration holder to a less appropriate modelling method (26). In another case, the informing study lacked sufficient statistical power to support the model’s health state structure (27). Small populations have also been reported to complicate the extrapolation of survival (21,23,28), thus adding more uncertainty to the model outcomes. Other issues cited include medically plausible transitions between health states not being observed in the collected data (18), utility values for health states being deemed unreliable (23,26) and low confidence in the classification of outcomes (8,29). 4.2.4 Effect uncertainty The relatively short period over which evidence was gathered added to the uncertainty of the assessments. Extrapolation of short-period data carried the risk of overestimation (23,24) and left unresolved uncertainty regarding the sustainability of the treatment effect (8,18,22,24). The absence of long-term evidence is sometimes crudely addressed by freezing patients in their last recorded health state, leading to unrealistic assumptions about disease progression (19,26). The absence of data on long-term complications is another cited source of uncertainty (21,26). This issue is particularly relevant for treatments targeting younger patients, where upfront costs come with expected benefits later in life, leading to considerable uncertainty from a CEA perspective. These challenges introduce considerable uncertainty to both treatment outcomes and costs over a life-long time horizon. 4.2.5 Flawed QoL measurement In Dutch pharmacoeconomic assessments, results are required to be reported in a cost-per-incremental-QALY format, which presents another hurdle. First and foremost no QoL data are collected in five pivotal clinical studies (8,18,23,24,29). In some instances missing QoL data can be justified through the patients’ very young age (8,23,24,29) or inability to communicate effectively due to their condition (19). In such cases, alternative approaches like vignette studies (8,18,19) were used, which lack methodological robustness and objectivity. In other instances, QoL is not assessed via the preferred (Y-)EQ-5D questionnaire but through disease specific instruments instead (21,22,29). The results are then ‘mapped’ to EQ-5D derived utilities. Registration holders have signalled that this approach may still not be appropriate because of limited sensitivity (19) or poor predictive capabilities (22). Another cited approach is mapping utility values to health states using utilities derived from a similarly indicated treatment (24) or by employing utility values from other patient sub-groups (23,29) as proxies. These approaches to QoL measurement have a tendency to produce uninformative utilities with poor face validity. The results can be a clinically implausible amount of worse than death health states (8,23), poor differentiation between health states (24) or counterintuitively high valuation (22,25). 4.3 Unfavourable cost-effectiveness Table 2 (full page at end of manuscript) contains the results from the CEA across all 12 HTA reports. Only one treatment was deemed cost-effective at the relevant threshold (19). However, significant uncertainty led ZIN to recommend a 20% discount based on an alternative scenario. Another treatment was initially found to dominate the comparator, but the comparator itself was not cost-effective. After applying a recommended discount of 90% to the comparator’s price, the treatment was no longer cost-effective (21). In reports where such an estimate is provided, the probability of cost-effectiveness is close to zero percent. Such results often lead to disconcerting discount recommendations. For instance, a 100% discount would still not result in the treatment being cost effective at the highest threshold due the high costs of complementary standard care combined with the survival benefits of the treatment (29). It is worth noting that the discount recommendations are not always solely based on the CEA result. Other factors may also have impacted these recommendations, such as low additional health gain compared to standard treatment (20), future label extensions (22) and the supplier holding a monopoly in that specific disease area (22). 4.4 Alternative price calculations The estimated CCP price, DCF price, value-based price and list price of each treatment are presented in Table 3 . Figure 2 visualises these results, expressing the price estimates as a percentage of ZIN value based price. List prices are excluded from the figure because their values would distort the interpretability of the figure. The percentage values can be found in Appendix B. Table 3 Price estimates for CPP, DCF, CEA and list price CPP price DCF price CEA price List price Min Max Min Max ZIN Supplier Avacopan € 4.414 € 10.620 € 4.802 € 16.973 € 14.016 € 70.080 Atidarsagene autotemcel € 610.626 € 4.774.258 € 1.014.154 € 8.881.543 € 790.625 € 2.875.000 Pegcetacoplan € 46.615 € 358.418 € 76.291 € 661.662 € 47.408 € 316.050 Risdiplam € 6.997 € 32.707 € 9.276 € 57.656 € 35.957 € 256.835 Cannabidiol € 4.367 € 10.465 € 4.715 € 16.103 € 23.948 € 29.935 Tafamidis € 3.814 € 6.278 € 3.810 € 8.399 € 98.042 € 122.552 Onasemnogene abeparvovec € 240.525 € 1.073.252 € 314.831 € 1.888.309 € 175.050 € 1.945.000 Ivacaftor/tezacaftor/elexacaftor € 4.833 € 13.768 € 5.459 € 22.192 € 110.250 € 220.500 Givosiran € 58.163 € 473.901 € 97.972 € 878.467 € 331.393 € 552.322 Nusinersen € 17.340 € 57.570 € 20.579 € 96.443 € 374.850 € 249.900 Lumacaftor / ivacaftor € 5.021 € 18.353 € 6.058 € 30.884 € 30.489 € 169.386 The prices estimate derived from the CPP and DCF show significant variation between therapies and between one another. The same holds for the price estimates compared to the value-based prices recommended by ZIN. On first sight, the price estimations resulting from the CPP and DCF models show no consistent relationship to one another or the value-based price. Still, certain relationships can be discerned: Value-based price is below CPP range and below DCF range (1 therapy) Value-based price is within CPP range but below DCF range (2 therapies) Value-based price is within CPP range and within DCF range (1 therapy) Value-based price is above CPP range but within DCF range (3 therapies) Value-based price is above CPP range and above DCF range (4 therapies) Three findings in particular are of interest. The first of which is defined through the first category, where value-based estimates are below the lowest DCF and CPP estimates. This indicates that, even under the most optimistic circumstances with regard to R&D spending, it would not be feasible to develop and market onasemnogene abeparvovec at a cost-effective price in the Netherlands. Second, there is a group of therapies where the value-based price far exceeds the CPP and DCF price estimates, even at the highest level of R&D expenditure. Indicating that despite the small target population, development and marketing of the therapy should be feasible at a cost-effective price. Third, the DCF price estimates tend to be higher than the DCF estimates. This does not necessarily have to be the case, however, as is demonstrated by the price estimates for tafamidis when assuming an R&D investment of € 250.000.000. 5. Discussion This study examined the methodological issues and reported outcomes of all CEA’s on non-oncological orphan drugs published by ZIN in the period between 2015 and 2024 and compared the value-based price with estimates derived from the CPP and DCF models. 5.1. Analysis of CEA reports Through a systematic approach, 12 completed HTA reports for non-oncological orphan drugs with a CEA were identified. The reports contain the CEA results of 12 different treatments on 18 patient sub-groups, providing ICER’s for 17 out of these sub-groups. Methodological challenges frequently cited literature are indeed cited in Dutch HTA reports, although the number of issues and level of detail in which they were discussed differs significantly between assessments. These challenges do not undermine the use of CEA to support decision making, as is supported by earlier reviews (4) and the fact that 11 out of 12 CEA’s were deemed of sufficient quality to support decision-making. The high level of uncertainty stemming from these challenges may, however, result in an eventual net health loss when the financial risk caused by this uncertainty is borne by the payer. With the exception of cannabidiol, no treatment was regarded to be cost-effective or to have a probability of cost-effectiveness higher than 6% at their respective thresholds. Consequently, the majority of the recommended discounts exceeded 75%. The high discount recommendations, therapeutic benefits of these treatments and lack of alternatives highlight the paradoxical challenge of obtaining patient access at both timely and at reasonable costs. 5.2 Price estimates The CPP price estimates are heavily influenced by the ratio of production cost to R&D. This ratio, in turn, is dependent on the compound and the amount of patients. These effects further enhanced depending on the innovation bonus, affecting both the low and high estimates, thereby also determining the range between the two. This explains why tafamidis, a small molecule with high patient number and relatively modest innovation bonus, has the smallest price range whereas givosiran has the largest due to the higher production cost, low patient number and average innovation bonus. Interestingly, under the CPP method treatments with higher production costs are allowed a higher level of profitability in absolute terms than treatments with lower production costs. As with the CPP model, the price estimates are mostly influenced by the patient numbers. Increases in R&D expenditure will have a stronger impact on treatments where this increase can be spread out amongst fewer patients. The profit (excluding the innovation bonus) allowed for treatments remains constant regardless of the number of patients or the investment amount, as it is calculated as a fixed percentage of the R&D investment, which itself does not vary. The DCF price estimates tends to be higher than those based on the CPP model. This changes, however as patient numbers increase. This can be explained by the different approaches both models take to profit. Because the total profit for DCF is a fixed amount of the R&D investment whereas the profit in the total profit in the CPP model is variable and higher for higher patient numbers. This means that patient numbers rise high enough, the CPP price estimate will therefore be higher than the DCF estimate. This is demonstrated in the case of tafamidis, where the lower CPP estimate exceeds the lower DCF estimate. The value-based prices determined by ZIN show no consistent relationship to the CPP and DCF price ranges. Given the vastly different model determinants, this is unsurprising. Expected patient numbers and production cost very relevant to CPP and DCF, but of no consequence for CEA. Conversely, factors like willingness-to-pay thresholds and comparator price discounts are not included in the CPP and DCF models. The valuation of clinical effects in CPP and DCF through the use of innovation bonuses is vastly different from the more sophisticated approaches used in value-based pricing to determine incremental clinical value. 5.3 Alternative pricing models The alternative pricing models, in their current state, appear to have their own limitations and assumptions. First, the data required to perform these price calculations are sparsely available. Pharmaceutical companies are reluctant to be transparent about the real cost and investment of newly launched drugs, which means that industry averages or rules of thumb have to be relied upon which can easily be dismissed as not being appropriate or representative for the specific situation. The same applies to estimates for the success probability and return rates. Other variables that significantly influence the resulting price, such as the number of patients treated, are challenging to predict accurately at the time a treatment is introduced to the market. A provisional comparison between the predicted patient numbers prior to market access and the actual numbers during market access, as reported by ZIN, suggests that actual patient figures can deviate significantly from initial projections. A more implicit assumption that underlies these models that may still stand in the way of their actual implementation is that of a predetermined and unchanging market landscape. The aim of these models is to predetermine a price that allows known costs to be recouped with a fixed profit. However, scientific or market developments can readily undermine the entire underlying premise of certainty for payer and supplier that is the appeal of these models. This is demonstrated by the fact that three out of the twelve therapies in included in this study are registered for the treatment of spinal muscular atrophy in a span of less than five years, which is considerably shorter than the time horizons that the CPP and DCF model operate on. 5.4 Strengths and weaknesses This paper aimed to identify challenges in CEA and value-based pricing for orphan drugs and to test two recently proposed alternative pricing approaches. The strength of this study lies in the verification of problems and application of solutions to orphan drug pricing found in literature, rather than assessment of the quality of the CEA’s themselves. Certain limitations of this this study need to be addressed. The scope of this paper was limited to non-oncological orphan drugs that have received a formal assessment of cost-effectiveness by ZIN. This also means that these assessments adhere to the quality standards, criteria and perspective of ZIN which may vary from other HTA agencies. Moreover, the strong assumptions that underlie these pricing models also apply to the price estimates performed in this study. Although these are inherent to the pricing approaches, they significantly complicate the interpretability and reliability of the prices and highlighting the need for cautious application and thorough contextualization 5.5 Future research The authors concur with the recommendations from a recent Dutch review of pricing models, including value-based pricing, CPP and DCF, which emphasizes the need for future research to improve transparency around the true cost and risks associated with the development of new (orphan) drugs and creation of integrated differential pricing frameworks (30). Such insights could be valuable to the pharmaceutical industry, payers, and decision-makers as they navigate the complex and often contentious process of ensuring patient access to necessary treatments. 6. Conclusion Challenges in CEA cited in literature are present in Dutch HTA reports for orphan drugs. Although these issues cause considerable uncertainty, they do not yet negate CEA’s current ability to inform decision-making. Still, orphan drugs tend to be far from cost-effective, providing a challenge for patient access that is both timely and financially feasible. It is unlikely that current alternative pricing models in the form of CPP and DCF will provide a solution to this issue as they to estimate lower prices for these drugs than CEA and involve significant assumptions and uncertainty. Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Consent for publication Not applicable. Competing interests MK is an employee of Sanofi, a publicly traded company that markets (orphan) pharmaceuticals. JW does not have any competing interests. CUdG does not have any competing interests. Funding No funding was provided for this research. Author’s contributions MK made a substantial contributions to the conception and design of the research; the analysis and interpretation of the HTA reports; and has drafted and substantively revised the manuscript. JW made a substantial contributions to the conception and design of the research; the acquisition analysis and interpretation of the HTA reports; and has drafted and substantively revised the manuscript. CUdG made substantial contributions to the conception of the research. All authors read and approved the final manuscript Acknowledgements The authors thank L. Wormhoudt, PhD, for his involvement in the supervision of the project. Authors’ information Not applicable. Footnotes Not applicable References Zorginstituut Nederland. Richtlijn voor het uitvoeren van economische evaluaties in de gezondheidszorg. 2024. https://www.zorginstituutnederland.nl/publicaties/publicatie/2024/01/16/richtlijn-voor-het-uitvoeren-van-economische-evaluaties-in-de-gezondheidszorg. Accessed 2025 Mar 26. Nicod E, Annemans L, Bucsics A, Lee A, Upadhyaya S, Facey K. HTA programme response to the challenges of dealing with orphan medicinal products: process evaluation in selected European countries. Health Policy . 2019 Feb;123(2):140–51. Drummond MF, Wilson DA, Kanavos P, Ubel P, Rovira J. Assessing the economic challenges posed by orphan drugs. Int J Technol Assess Health Care . 2007 Jan;23(1):36–42. Schuller Y, Hollak CEM, Biegstraaten M. The quality of economic evaluations of ultra-orphan drugs in Europe: a systematic review. Orphanet J Rare Dis . 2015 Jul 30;10(1):92. Fellows GK, Hollis A. Funding innovation for treatment for rare diseases: adopting a cost-based yardstick approach. Orphanet J Rare Dis . 2013 Nov 16;8:180. Nuijten M, Van Wilder P. The impact of early phase price agreements on prices of orphan drugs. BMC Health Serv Res . 2021 Mar 12;21:222. Pearson I, Rothwell B, Olaye A, Knight C. Economic modeling considerations for rare diseases. Value Health . 2018 May;21(5):515–24. Zorginstituut Nederland. Pakketadvies sluisgeneesmiddel atidarsagene autotemcel (Libmeldy®) voor de behandeling van metachromatische leukodystrofie (MLD). 2022. https://www.zorginstituutnederland.nl/publicaties/adviezen/2022/09/27/pakketadvies-sluisgeneesmiddel-atidarsagene-autotemcel-libmeldy. Accessed 2025 Mar 26. Zorginstituut Nederland. Beoordeling van weesgeneesmiddelen. https://www.zorginstituutnederland.nl/over-ons/werkwijzen-en-procedures/adviseren-over-en-verduidelijken-van-het-basispakket-aan-zorg/beoordeling-van-geneesmiddelen/beoordeling-van-weesgeneesmiddelen. Accessed 2025 Mar 26. Zorginstituut Nederland. Pakketadvies sluisgeneesmiddel olipudase alfa (Xenpozyme®) voor de behandeling van de ziekte van Niemann-Pick. 2024. https://www.zorginstituutnederland.nl/publicaties/adviezen/2024/08/21/pakketadvies-olipudase-alfa-xenpozyme. Accessed 2025 Mar 26. Uyl-de Groot CA, Löwenberg B. Sustainability and affordability of cancer drugs: a novel pricing model. Nat Rev Clin Oncol . 2018 Jul;15(7):405–6. Thielen FW, Heine RJSD, van den Berg S, Ham RMTT, Uyl-de Groot CA. Towards sustainability and affordability of expensive cell and gene therapies? Applying a cost-based pricing model to estimate prices for Libmeldy and Zolgensma. Cytotherapy . 2022 Dec;24(12):1245–58. International Association of Mutual Benefit Societies. AIM proposes to establish a European drug pricing model for fair and transparent prices for accessible pharmaceutical innovations. https://www.aim-mutual.org/wp-content/uploads/2019/12/AIMfairpricingModel.pdf. Accessed 2025 Mar 26. Nuijten M, Fischer HJ, Van der Meijden J. Evaluation and valuation of the price of expensive medicinal products: application of the discounted cash flow to orphan drugs. Int J Rare Dis Disord. 2018 Dec 31;1(1):5. Nuijten M, Vis J. Evaluation and valuation of innovative medicinal products. J Rare Dis Res Treat . 2016 Dec 3;2(1):1–11. Ministerie van Volksgezondheid. Dashboard doorlooptijden geneesmiddelen. https://www.farmatec.nl/prijsvorming/dashboard-doorlooptijden-geneesmiddelen. Accessed 2025 Mar 26. European Medicines Agency. Download medicine data. https://www.ema.europa.eu/en/medicines/download-medicine-data. Accessed 2025 Mar 26. Zorginstituut Nederland. Pakketadvies sluisgeneesmiddel voretigene neparvovec (Luxturna®) bij de behandeling van visusverlies door erfelijke retinale dystrofie met bi-allelische RPE65-mutaties. 2020. Zorginstituut Nederland. GVS-advies cannabidiol (Epidyolex®) als aanvullende behandeling bij 2 ernstige epileptische aandoeningen. 2022. https://www.zorginstituutnederland.nl/publicaties/adviezen/2022/07/04/gvs-advies-cannabidiol-epidyolex. Accessed 2025 Mar 26. Zorginstituut Nederland. GVS-advies avacopan (Tavneos®). 2022. https://www.zorginstituutnederland.nl/publicaties/adviezen/2022/04/20/gvs-advies-avacopan-tavneos. Accessed 2025 Mar 26. Zorginstituut Nederland. Pakketadvies geneesmiddel pegcetacoplan (Aspaveli®) voor de behandeling van paroxismale nachtelijke hemoglobinurie (PNH). 2022. https://www.zorginstituutnederland.nl/publicaties/adviezen/2022/09/16/pakketadvies-sluisgeneesmiddel-pegcetacoplan-aspaveli Zorginstituut Nederland. GVS-advies elexacaftor/tezacaftor/ivacaftor (Kaftrio®) in combinatie met ivacaftor (Kalydeco®). 2021. Zorginstituut Nederland. Pakketadvies sluisgeneesmiddel onasemnogene abeparvovec (Zolgensma®) bij de behandeling van spinale musculaire atrofie (SMA). 2021. https://www.zorginstituutnederland.nl/publicaties/adviezen/2021/05/06/pakketadvies-sluisgeneesmiddel-onasemnogene-abeparvovec-zolgensma. Accessed 2025 Mar 26. Zorginstituut Nederland. Pakketadvies sluisgeneesmiddel risdiplam (Evrysdi®) bij 5q spinale spieratrofie (SMA). 2022.https://www.zorginstituutnederland.nl/publicaties/adviezen/2022/07/15/pakketadvies-sluisgeneesmiddel-risdiplam-evrysdi. Accessed 2025 Mar 26. Zorginstituut Nederland. GVS-advies uitbreiding vergoedingsvoorwaarden lumacaftor/ivacaftor (Orkambi®) voor de behandeling van cystische fibrose. 2016.https://www.zorginstituutnederland.nl/publicaties/adviezen/2016/12/15/gvs-advies-lumacaftor-ivacaftor-orkambi-bij-cystische-fibrose-cf-bij-patienten-van-12-jaar-en-ouder-die-homozygoot-zijn-voor-de-f508del-mutatie-in-het-cftr-gen-herbeoordeling. Accessed 2025 Mar 26. Zorginstituut Nederland. GVS-advies givosiran (Givlaari®) bij de behandeling van acute hepatische porfyrie. 2021. https://www.zorginstituutnederland.nl/publicaties/adviezen/2021/02/02/gvs-advies-givosiran-givlaari-bij-de-behandeling-van-acute-hepatische-porfyrie. Accessed 2025 Mar 26. Zorginstituut Nederland. GVS-advies tafamidis (Vyndaqel®) bij de behandeling van ATTR amyloïdose. 2020. https://www.zorginstituutnederland.nl/publicaties/adviezen/2020/12/03/gvs-advies-tafamidis-vyndaqel. Accessed 2025 Mar 26. Zorginstituut Nederland. GVS-advies weesgeneesmiddel tafamidis (Vyndaqel®) bij de behandeling van transthyretine-amyloïdose met cardiomyopathie (ATTR-CM). 2021. https://www.zorginstituutnederland.nl/publicaties/adviezen/2021/08/11/gvs-advies-tafamidis-vyndaqel-bij-de-behandeling-van-attr-cm. Accessed 2025 Mar 26. Zorginstituut Nederland. Pakketadvies sluisgeneesmiddel nusinersen (Spinraza®) voor de behandeling van spinale musculaire atrofie (SMA). 2018. https://www.zorginstituutnederland.nl/publicaties/adviezen/2018/02/07/pakketadvies-nusinersen-spinraza-voor-de-behandeling-van-spinale-musculaire-atrofie-sma. Accessed 2025 Mar 26. Manders EA, van den Berg S, de Visser SJ, Hollak CEM. 30. Drug pricing models, no ‘one-size-fits-all’ approach: a systematic review and critical evaluation of pricing models in an evolving pharmaceutical landscape. Eur J Health Econ. 2024 Nov 4. Tables Table 2 is available in the Supplementary Files section. Supplementary Files Table2.docx Cite Share Download PDF Status: Published Journal Publication published 08 Jan, 2026 Read the published version in Orphanet Journal of Rare Diseases → Version 1 posted Editorial decision: Major revision 12 Aug, 2025 Reviewers agreed at journal 20 May, 2025 Reviewers invited by journal 15 May, 2025 Editor assigned by journal 02 May, 2025 First submitted to journal 30 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6569819","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":457242721,"identity":"3f85599c-0b46-41d8-b0bb-b2cc267c500f","order_by":0,"name":"Jelle Walraven","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+UlEQVRIiWNgGAWjYBACxgYg8QDMZD4A4UGABX4tCWAmWwKyFgn8VkG08BgQp4W5gcfwQ+Ieu8R+6Z6PD3/uuBPNwN5j9oFxB24tjA08xhIJz5ITZ845u9mY98yz3AaeM8YzGM/g08K7QSLhALOxwY3cbdKMbYdzGyRyjBkY2/Bq2fwj4UC9sf2NnOc/f4K0yL8hqGUb0JbDcgYSOWwMvGBbeAhoaeb/ZpFw4LicxI00Y2netme5bTxpxQyJeLQYtrcl3/hwoJqHf0byw48/2+7k9rMf3szwsc0Gt5ZmVP4BBjYQlYBTAwODPBr/AB61o2AUjIJRMFIBAHoWU6bncWNpAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0009-0007-9859-3754","institution":"Erasmus Universiteit Rotterdam Erasmus School of Health Policy and Management","correspondingAuthor":true,"prefix":"","firstName":"Jelle","middleName":"","lastName":"Walraven","suffix":""},{"id":457242722,"identity":"11acab07-d717-4e79-ada5-4db3f1fbd454","order_by":1,"name":"Mahtab Kaveh","email":"","orcid":"","institution":"Erasmus University Rotterdam Rotterdam School of Management: Erasmus Universiteit Rotterdam Rotterdam School of Management","correspondingAuthor":false,"prefix":"","firstName":"Mahtab","middleName":"","lastName":"Kaveh","suffix":""},{"id":457242723,"identity":"e87a1d65-954b-4e3d-92eb-f4fc609399cf","order_by":2,"name":"Carin Uyl - de Groot","email":"","orcid":"","institution":"Erasmus Universiteit Rotterdam Erasmus School of Health Policy and Management","correspondingAuthor":false,"prefix":"","firstName":"Carin","middleName":"Uyl -","lastName":"de Groot","suffix":""}],"badges":[],"createdAt":"2025-05-01 07:00:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6569819/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6569819/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13023-025-04181-6","type":"published","date":"2026-01-08T15:59:29+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":83147826,"identity":"8785594e-b5d4-4c4c-9c0b-c45e208553af","added_by":"auto","created_at":"2025-05-20 13:22:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":56854,"visible":true,"origin":"","legend":"\u003cp\u003eIncluded reports\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-6569819/v1/100383c89fdeed5f686d723b.png"},{"id":83147827,"identity":"72ceadd5-cedd-4946-bf3a-c0e79c683cc4","added_by":"auto","created_at":"2025-05-20 13:22:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":233940,"visible":true,"origin":"","legend":"\u003cp\u003ePrice estimates for CPP, DCF and CEA\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-6569819/v1/d42ba6f13c0e00044ec284c1.png"},{"id":100070912,"identity":"e3b5125c-37ac-4362-8448-153408825ee9","added_by":"auto","created_at":"2026-01-12 16:18:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1258817,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6569819/v1/8ddeb9ab-5a8e-46fc-bb6f-969fbd74400b.pdf"},{"id":83147825,"identity":"0f9649a7-0d0e-4dce-83b9-7eafa735b9d1","added_by":"auto","created_at":"2025-05-20 13:22:11","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":21868,"visible":true,"origin":"","legend":"","description":"","filename":"Table2.docx","url":"https://assets-eu.researchsquare.com/files/rs-6569819/v1/b648578a6acef1ff70116af7.docx"}],"financialInterests":"","formattedTitle":"\u003cp\u003eMethodological Challenges in Dutch HTA of Non-Oncological Orphan Drugs: A Retrospective Analysis and Price Comparison Using different Pricing Models\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eCost-effectiveness analysis (CEA) is a prevalent method to help inform decision-makers regarding pricing and reimbursement of new therapies.\u0026nbsp;For new pharmaceutical therapies seeking reimbursement on an added value claim in the Netherlands, the CEA is mandatory (1). The central outcome of interest is the incremental cost-effectiveness ratio (ICER), which represents the ratio between incremental costs and incremental health benefits, typically expressed as the additional cost per QALY gained. The ICER is benchmarked against a predefined willingness-to-pay threshold to determine the maximum price that ought to be paid for a treatment and what discount is required on the initial list price to justify reimbursement. This approach is known as value-based pricing. Although CEA is not the only factor in reimbursement decisions, it plays a significant role, as the ICER is used to inform price negotiations between manufacturers and payers.\u003c/p\u003e\n\u003cp\u003eWhen it comes to\u0026nbsp;orphan drugs, however, two issues undermine the informative value of CEA for pricing and reimbursement decisions.\u0026nbsp;First, the inherent characteristics of rare diseases complicate health economic assessments, reducing the feasibility of robust economic evaluations and increasing uncertainty (2). Second, orphan drugs typically do not show cost-effectiveness under the traditional economic evaluation criteria (2\u0026ndash;4). HTA agencies understand, and sometimes even accept, these limitations of value-based pricing for orphan drugs. Still, when cost-effectiveness cannot be adequately assessed or achieved, value-based pricing can pose an obstacle to timely access, as CEA\u0026rsquo;s ability to reliably estimate a price that should be acceptable to both payers and pharmaceutical companies is hindered.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAs a result, other approaches, such as cost-plus pricing (CPP) and the discounted cash flow (DCF) method have recently been suggested in case conducting a CEA is unfeasible or when a drug fails to realistically meet the cost-effectiveness threshold (5,6). Interestingly, these models for determining \u0026apos;fair\u0026apos; or \u0026apos;reasonable\u0026apos; prices for (orphan) drugs have been published from opposing perspectives, despite using similar parameters. One approach seeks to determine the maximum price the payer should be willing to pay, whereas the other estimates the minimum price that pharmaceutical companies should consider acceptable. These new pricing models have seen little application and minimal comparison with the more value-based pricing approach.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis paper describes the challenges incurred with CEA-informed value-based pricing of orphan drugs in literature and Dutch HTA practice. Additionally, it presents price estimates using two alternative approaches which are compared to value-based prices in the Netherlands.\u003c/p\u003e"},{"header":"2. Background","content":"\u003cp\u003eAlthough the methodological challenges and low probability of cost-effectiveness associated with orphan drugs are not new but are increasingly relevant to pricing and reimbursement conditions, as is demonstrated by two recent cases from the Netherlands.\u003c/p\u003e \u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Methodological challenges\u003c/h2\u003e \u003cp\u003eA number of different factors inherent to orphan drugs can negatively impact the practical feasibility and uncertainty of CEA (7). A practical example from the Netherlands is the case of atidarsagene autotemcel. Limited data availability caused considerable uncertainty about utilities and treatment effectiveness between patient subgroups. Disagreement on response classification and treatment effect durability further complicated the assessment(8). Despite the payer\u0026rsquo;s willingness to accept a higher price and thus exceeding the willingness-to-pay threshold due to the unique circumstances, no agreement on an acceptable price could initially be reached. Reimbursement of Atidarsagene autotemcel was temporarily declined for a period as a result.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Unfavourable cost-effectiveness\u003c/h2\u003e \u003cp\u003eAlthough proper pharmacoeconomic modelling practices may address these inherent issues, most (ultra-)orphan drugs will not meet conventional criteria for cost-effectiveness (3). While there seems to be a certain willingness to get these therapies to patients despite their uncertainty, high cost and low probability of being cost-effective both in general (4) and in the Netherlands specifically (9), there seems to be a limit to such tolerance.\u003c/p\u003e \u003cp\u003eA recent example is olipudase alfa. In a historical first, the CEA report submitted by the registration holder was not formally assessed by the HTA agency the Dutch National Healthcare Institute (ZIN), as the submitted ICER\u0026rsquo;s of \u0026euro;1.070.000 and \u0026euro;1.600.000\u0026nbsp;million clearly indicated the treatment is not cost-effective. No conclusions were drawn regarding the quality of the analysis, but a full assessment of the treatment\u0026rsquo;s cost-effectiveness was not expected to result in a reliable price estimate. Olipudase alfa was nonetheless recommended for reimbursement on the condition that price negotiations would result in a cost-effective price (10).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Alternative pricing approaches\u003c/h2\u003e \u003cp\u003eIn cases where cost-effectiveness cannot be properly assessed or reasonably achieved, and value-based pricing principles can thus not be applied, a non-arbitrary method is still needed to justify prices that are justifiable for both the supplier as well as the payer in a context where market principles do not apply. Two alternative approaches have recently been proposed: cost-plus pricing and the discounted cashflow method.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.3.1 Cost-plus pricing\u003c/h2\u003e \u003cp\u003eCertain researchers have argued that if an orphan drug does not meet the cost-effectiveness threshold, other mechanisms should be used to determine a just and reasonable price (Fellows and Hollis, 2013). This approach considers the interest of payers as it seeks to determine a maximum price that ought to be paid to acquire these therapies. Since pharmaceutical firms cite higher average costs in justification of higher orphan drug prices, the price is based on the incurred costs and a pre-determined profit margin. Various authors have applied CPP models to specific orphan drugs (11,12). A more universal model has been proposed by the International Association of Mutual Benefit Societies (13).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.3.2 Discounted cash flow\u003c/h2\u003e \u003cp\u003eOther authors have adopted a supply-side perspective, postulating that pharmaceutical innovation is driven by profit-seeking companies and that drug prices must be sufficiently high for companies to commit to such a risky endeavour (14). They argue that the business valuation principles guiding investment decisions in the pharmaceutical industry could also be utilized for public price setting. When the ICER exceeds the threshold, a DCF analysis could be performed in which expected future returns are contrasted to upfront investment using a risk-adjusted capital cost threshold. This could help determine a price at which companies are sufficiently incentivized to develop new drugs for rare diseases (15).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.3.3 Comparing both approaches\u003c/h2\u003e \u003cp\u003eStrikingly, both CPP and DCF rely on similar determinants, despite fundamentally opposing view on what forms the basis of a reasonable price. It is, however, unclear how the price estimates resulting from these two approaches compare to each other and to the traditional value-based pricing method in the context orphan drugs. This paper aims to address just that matter.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3. Methods","content":"\u003cp\u003eAll CEA reports on non-oncological orphan drugs published by ZiN between 2015 (introduction of the new \u0026lsquo;lock\u0026rsquo; HTA procedure) and 2024 were collected in order to identify methodological challenges. Prices for these treatments were then re-determined using the CPP model by AIM (13) and the DCF model by Nuijten et al. (14,15) and compared to the value-based prices and public list prices.\u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Analysis of CEA reports\u003c/h2\u003e \u003cp\u003eA complete list of Dutch HTA assessments was extracted from the pharmaceutical lead time dashboard of the Dutch Ministry of Health (16) and cross-referenced with EMA\u0026rsquo;s register of orphan designations (17). Matches were manually checked for pharmacoeconomic reports. All resulting reports were systematically reviewed by both authors for explicitly mentioned methodological challenges. These challenges were then categorized.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2 CPP and DCF price estimates\u003c/h2\u003e \u003cp\u003eFor the price estimates, Excel versions of the CPP model by AIM and the DCF model by Nuijten et al. were obtained through their respective developers. Both models share the same key variables, which are outlined in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The approach differs in two aspects, however. The first lies in the conceptualization of expected return. AIM\u0026rsquo;s CPP model allows for a fixed profit margin whereas the DCF model employs a risk-adjusted discount rate. In both models, the same base percentage is used. The second is probability of success, which is only included in the DCF model. The DCF model explicitly incorporates the probabilities of successfully progressing through the stages of clinical development, whereas the standard DCF approach assumes that the cost of failure is already embedded in the overall R\u0026amp;D investment. To facilitate comparison between both models, equal values are used. Since no data is available on the R\u0026amp;D investment for all therapies, the default minimum and maximum values of AIM\u0026rsquo;s model (\u0026euro;250.000.000 and \u0026euro;2.500.000) were used to establish a range. Of these R\u0026amp;D expenditures, 42% is attributed to Europe, as it represents 42% of the population of main markets for the innovative drugs. Subsequently, 4.58% is attributed to the Netherlands as AIM advocates differential pricing based on gross domestic product per capita (13). Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e provides an overview of the common input parameters and their respective sources. The exact values for the production costs, innovation bonus and patients treated for each treatment are provided in appendix A as they are different for each therapy.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eModel input parameters\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSource\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR\u0026amp;D investment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026euro; 250.000.000 and \u0026euro; 2.500.000.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAIM\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProduction costs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVaries per therapy (Appendix A)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTreatment SMPC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSales and medical information\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAIM\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExpected return\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAIM\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInnovation bonus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVaries per therapy (Appendix A)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTreatment FT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAllocation base NL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,9236%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAIM\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatients treated NL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVaries per therapy (Appendix A)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eZIN\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSuccess rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAssumed\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.3 CEA price estimates\u003c/h2\u003e \u003cp\u003eValue-based prices for the drugs were estimated by applying the recommended discount to the list price posed by the pharmaceutical company for each treatment. For onasemnogene abeparvovec, risdiplam and lumacaftor / ivacaftor the CEA value-based price is the average of the value-based price of both CEA sub-groups, since insufficient data in the HTA reports prevented the calculation of a weighted average price based on the expected patient distribution across sub-groups. The value-based price of cannabidiol is based on the average dose scenario rather than the maximum dose scenario. For nusinersen, only the SMA type 2/3 subgroup was considered, as the type 1 subgroup did not result in a meaningful discount.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Orphan drugs with CEA\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA complete set of non-oncological orphan drugs with a pharmacoeconomic assessment was developed through the steps outlined in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Oncological drugs were excluded since they may hold orphan status for certain indications whereas other indications are not granted such a status. Through this process, 12 completed HTA reports with a CEA were found, of which 3 were resubmissions of reports that were initially rejected based on insufficient methodological quality. One report was accepted despite the structural uncertainty making the results unfit for decision making because it was deemed unlikely that resubmission and reassessment would lead to sufficient improvement (18). The reports contain the CEA results of 12 different treatments on 18 patient sub-groups, providing ICER\u0026rsquo;s for 17 out of these sub-groups. An overview of these results is presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e (full page at end of manuscript).\u003c/p\u003e\u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Methodological challenges\u003c/h2\u003e \u003cp\u003eICER\u0026rsquo;s estimated for 11 out of the 12 treatments were deemed appropriate for reimbursement decision-making, despite the methodological challenges and uncertainty involved. All reports mentioned major sources of uncertainty or unresolved discussion points listed in the concluding section of the assessment report, which addresses transparency, methodology, inaccuracy, bias, and lack of evidence. One of the CEA models was described as having a subjective character as a result of the heavy reliance on judgement-based estimates for both utilities and costs (19). Identified challenges were grouped into five overarching categories.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003e4.2.1 Lack of a suitable comparator\u003c/h2\u003e \u003cp\u003eOnly three (20\u0026ndash;22) were compared head-to-head to another treatment for at least one patient subgroup. One other treatment was compared with the standard of care which consisted of a variety of pharmaceutical and non-pharmaceutical care (19). The remaining treatments were compared with best supportive care (while also being added to best supportive care). In one instance (23), an attempt was made to compare trial results with a competing treatment. However, the small study populations introduced bias and significant uncertainty, making the data unsuitable for reliable comparison. Three therapies were assessed using only data from single-arm studies (8,23,24) for at least one patient sub-group, as a consequence of the extreme rarity of the disease or ethical considerations involving young enfants. CEA\u0026rsquo;s, by definition, seek to compare two treatment alternatives. The absence of such an alternative deteriorates the basis for determining the true value of these treatments in comparison to existing alternatives.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e4.2.2 Sub-optimal disease understanding\u003c/h2\u003e \u003cp\u003eA lack of evidence and understanding of the disease lead to systematic uncertainty in the fundamental elements of the model. One frequently mentioned issue concerns the basic definition of health states, resulting in arbitrary definitions of health states (19,25) or overly complex measures with limited clinical relevance (26). Another issue reported is the absence of validated measurement instruments for certain patient (age) groups (8,25) and the inability of existing instruments to capture the full range of outcomes (24). In two instances, the registration holder indicated that the primary measurement instruments were either not sensitive enough to detect clinically relevant changes (24) or not suitable for linking utilities to costs (18). Lack of evidence on disease progression was cited to also complicate modelling of long-term implications for both the treatment and control arm (8,23,24,26).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003e4.2.3 Limited evidence to inform models\u003c/h2\u003e \u003cp\u003eAnother issue mentioned is the limited data that is available to inform the model. In one instance, this lack of sufficient data compelled the registration holder to a less appropriate modelling method (26). In another case, the informing study lacked sufficient statistical power to support the model\u0026rsquo;s health state structure (27). Small populations have also been reported to complicate the extrapolation of survival (21,23,28), thus adding more uncertainty to the model outcomes. Other issues cited include medically plausible transitions between health states not being observed in the collected data (18), utility values for health states being deemed unreliable (23,26) and low confidence in the classification of outcomes (8,29).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003e4.2.4 Effect uncertainty\u003c/h2\u003e \u003cp\u003eThe relatively short period over which evidence was gathered added to the uncertainty of the assessments. Extrapolation of short-period data carried the risk of overestimation (23,24) and left unresolved uncertainty regarding the sustainability of the treatment effect (8,18,22,24). The absence of long-term evidence is sometimes crudely addressed by freezing patients in their last recorded health state, leading to unrealistic assumptions about disease progression (19,26). The absence of data on long-term complications is another cited source of uncertainty (21,26). This issue is particularly relevant for treatments targeting younger patients, where upfront costs come with expected benefits later in life, leading to considerable uncertainty from a CEA perspective. These challenges introduce considerable uncertainty to both treatment outcomes and costs over a life-long time horizon.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003ch2\u003e4.2.5 Flawed QoL measurement\u003c/h2\u003e \u003cp\u003eIn Dutch pharmacoeconomic assessments, results are required to be reported in a cost-per-incremental-QALY format, which presents another hurdle. First and foremost no QoL data are collected in five pivotal clinical studies (8,18,23,24,29). In some instances missing QoL data can be justified through the patients\u0026rsquo; very young age (8,23,24,29) or inability to communicate effectively due to their condition (19).\u003c/p\u003e \u003cp\u003eIn such cases, alternative approaches like vignette studies (8,18,19) were used, which lack methodological robustness and objectivity. In other instances, QoL is not assessed via the preferred (Y-)EQ-5D questionnaire but through disease specific instruments instead (21,22,29). The results are then \u0026lsquo;mapped\u0026rsquo; to EQ-5D derived utilities. Registration holders have signalled that this approach may still not be appropriate because of limited sensitivity (19) or poor predictive capabilities (22). Another cited approach is mapping utility values to health states using utilities derived from a similarly indicated treatment (24) or by employing utility values from other patient sub-groups (23,29) as proxies. These approaches to QoL measurement have a tendency to produce uninformative utilities with poor face validity. The results can be a clinically implausible amount of worse than death health states (8,23), poor differentiation between health states (24) or counterintuitively high valuation (22,25).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Unfavourable cost-effectiveness\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e (full page at end of manuscript) contains the results from the CEA across all 12 HTA reports. Only one treatment was deemed cost-effective at the relevant threshold (19). However, significant uncertainty led ZIN to recommend a 20% discount based on an alternative scenario. Another treatment was initially found to dominate the comparator, but the comparator itself was not cost-effective. After applying a recommended discount of 90% to the comparator\u0026rsquo;s price, the treatment was no longer cost-effective (21). In reports where such an estimate is provided, the probability of cost-effectiveness is close to zero percent. Such results often lead to disconcerting discount recommendations. For instance, a 100% discount would still not result in the treatment being cost effective at the highest threshold due the high costs of complementary standard care combined with the survival benefits of the treatment (29). It is worth noting that the discount recommendations are not always solely based on the CEA result. Other factors may also have impacted these recommendations, such as low additional health gain compared to standard treatment (20), future label extensions (22) and the supplier holding a monopoly in that specific disease area (22).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Alternative price calculations\u003c/h2\u003e \u003cp\u003eThe estimated CCP price, DCF price, value-based price and list price of each treatment are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e visualises these results, expressing the price estimates as a percentage of ZIN value based price. List prices are excluded from the figure because their values would distort the interpretability of the figure. The percentage values can be found in Appendix B.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrice estimates for CPP, DCF, CEA and list price\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCPP price\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eDCF price\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCEA price\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eList price\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eZIN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSupplier\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAvacopan\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026euro; 4.414\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026euro; 10.620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026euro; 4.802\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026euro; 16.973\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026euro; 14.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026euro; 70.080\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAtidarsagene autotemcel\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026euro; 610.626\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026euro; 4.774.258\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026euro; 1.014.154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026euro; 8.881.543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026euro; 790.625\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026euro; 2.875.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePegcetacoplan\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026euro; 46.615\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026euro; 358.418\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026euro; 76.291\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026euro; 661.662\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026euro; 47.408\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026euro; 316.050\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRisdiplam\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026euro; 6.997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026euro; 32.707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026euro; 9.276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026euro; 57.656\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026euro; 35.957\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026euro; 256.835\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCannabidiol\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026euro; 4.367\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026euro; 10.465\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026euro; 4.715\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026euro; 16.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026euro; 23.948\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026euro; 29.935\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTafamidis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026euro; 3.814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026euro; 6.278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026euro; 3.810\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026euro; 8.399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026euro; 98.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026euro; 122.552\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOnasemnogene abeparvovec\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026euro; 240.525\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026euro; 1.073.252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026euro; 314.831\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026euro; 1.888.309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026euro; 175.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026euro; 1.945.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIvacaftor/tezacaftor/elexacaftor\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026euro; 4.833\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026euro; 13.768\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026euro; 5.459\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026euro; 22.192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026euro; 110.250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026euro; 220.500\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGivosiran\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026euro; 58.163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026euro; 473.901\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026euro; 97.972\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026euro; 878.467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026euro; 331.393\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026euro; 552.322\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNusinersen\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026euro; 17.340\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026euro; 57.570\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026euro; 20.579\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026euro; 96.443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026euro; 374.850\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026euro; 249.900\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLumacaftor / ivacaftor\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026euro; 5.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026euro; 18.353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026euro; 6.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026euro; 30.884\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026euro; 30.489\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026euro; 169.386\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eThe prices estimate derived from the CPP and DCF show significant variation between therapies and between one another. The same holds for the price estimates compared to the value-based prices recommended by ZIN. On first sight, the price estimations resulting from the CPP and DCF models show no consistent relationship to one another or the value-based price. Still, certain relationships can be discerned:\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eValue-based price is below CPP range and below DCF range (1 therapy)\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eValue-based price is within CPP range but below DCF range (2 therapies)\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eValue-based price is within CPP range and within DCF range (1 therapy)\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eValue-based price is above CPP range but within DCF range (3 therapies)\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eValue-based price is above CPP range and above DCF range (4 therapies)\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eThree findings in particular are of interest. The first of which is defined through the first category, where value-based estimates are below the lowest DCF and CPP estimates. This indicates that, even under the most optimistic circumstances with regard to R\u0026amp;D spending, it would not be feasible to develop and market onasemnogene abeparvovec at a cost-effective price in the Netherlands. Second, there is a group of therapies where the value-based price far exceeds the CPP and DCF price estimates, even at the highest level of R\u0026amp;D expenditure. Indicating that despite the small target population, development and marketing of the therapy should be feasible at a cost-effective price. Third, the DCF price estimates tend to be higher than the DCF estimates. This does not necessarily have to be the case, however, as is demonstrated by the price estimates for tafamidis when assuming an R\u0026amp;D investment of \u0026euro; 250.000.000.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"5. Discussion","content":"\u003cp\u003eThis study examined the methodological issues and reported outcomes of all CEA\u0026rsquo;s on non-oncological orphan drugs published by ZIN in the period between 2015 and 2024 and compared the value-based price with estimates derived from the CPP and DCF models.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e5.1. Analysis of CEA reports\u003c/h2\u003e \u003cp\u003eThrough a systematic approach, 12 completed HTA reports for non-oncological orphan drugs with a CEA were identified. The reports contain the CEA results of 12 different treatments on 18 patient sub-groups, providing ICER\u0026rsquo;s for 17 out of these sub-groups.\u003c/p\u003e \u003cp\u003eMethodological challenges frequently cited literature are indeed cited in Dutch HTA reports, although the number of issues and level of detail in which they were discussed differs significantly between assessments. These challenges do not undermine the use of CEA to support decision making, as is supported by earlier reviews (4) and the fact that 11 out of 12 CEA\u0026rsquo;s were deemed of sufficient quality to support decision-making. The high level of uncertainty stemming from these challenges may, however, result in an eventual net health loss when the financial risk caused by this uncertainty is borne by the payer.\u003c/p\u003e \u003cp\u003eWith the exception of cannabidiol, no treatment was regarded to be cost-effective or to have a probability of cost-effectiveness higher than 6% at their respective thresholds. Consequently, the majority of the recommended discounts exceeded 75%. The high discount recommendations, therapeutic benefits of these treatments and lack of alternatives highlight the paradoxical challenge of obtaining patient access at both timely and at reasonable costs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e5.2 Price estimates\u003c/h2\u003e \u003cp\u003eThe CPP price estimates are heavily influenced by the ratio of production cost to R\u0026amp;D. This ratio, in turn, is dependent on the compound and the amount of patients. These effects further enhanced depending on the innovation bonus, affecting both the low and high estimates, thereby also determining the range between the two. This explains why tafamidis, a small molecule with high patient number and relatively modest innovation bonus, has the smallest price range whereas givosiran has the largest due to the higher production cost, low patient number and average innovation bonus. Interestingly, under the CPP method treatments with higher production costs are allowed a higher level of profitability in absolute terms than treatments with lower production costs.\u003c/p\u003e \u003cp\u003eAs with the CPP model, the price estimates are mostly influenced by the patient numbers. Increases in R\u0026amp;D expenditure will have a stronger impact on treatments where this increase can be spread out amongst fewer patients. The profit (excluding the innovation bonus) allowed for treatments remains constant regardless of the number of patients or the investment amount, as it is calculated as a fixed percentage of the R\u0026amp;D investment, which itself does not vary.\u003c/p\u003e \u003cp\u003eThe DCF price estimates tends to be higher than those based on the CPP model. This changes, however as patient numbers increase. This can be explained by the different approaches both models take to profit. Because the total profit for DCF is a fixed amount of the R\u0026amp;D investment whereas the profit in the total profit in the CPP model is variable and higher for higher patient numbers. This means that patient numbers rise high enough, the CPP price estimate will therefore be higher than the DCF estimate. This is demonstrated in the case of tafamidis, where the lower CPP estimate exceeds the lower DCF estimate.\u003c/p\u003e \u003cp\u003eThe value-based prices determined by ZIN show no consistent relationship to the CPP and DCF price ranges. Given the vastly different model determinants, this is unsurprising. Expected patient numbers and production cost very relevant to CPP and DCF, but of no consequence for CEA. Conversely, factors like willingness-to-pay thresholds and comparator price discounts are not included in the CPP and DCF models. The valuation of clinical effects in CPP and DCF through the use of innovation bonuses is vastly different from the more sophisticated approaches used in value-based pricing to determine incremental clinical value.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e5.3 Alternative pricing models\u003c/h2\u003e \u003cp\u003eThe alternative pricing models, in their current state, appear to have their own limitations and assumptions. First, the data required to perform these price calculations are sparsely available. Pharmaceutical companies are reluctant to be transparent about the real cost and investment of newly launched drugs, which means that industry averages or rules of thumb have to be relied upon which can easily be dismissed as not being appropriate or representative for the specific situation. The same applies to estimates for the success probability and return rates. Other variables that significantly influence the resulting price, such as the number of patients treated, are challenging to predict accurately at the time a treatment is introduced to the market. A provisional comparison between the predicted patient numbers prior to market access and the actual numbers during market access, as reported by ZIN, suggests that actual patient figures can deviate significantly from initial projections.\u003c/p\u003e \u003cp\u003eA more implicit assumption that underlies these models that may still stand in the way of their actual implementation is that of a predetermined and unchanging market landscape. The aim of these models is to predetermine a price that allows known costs to be recouped with a fixed profit. However, scientific or market developments can readily undermine the entire underlying premise of certainty for payer and supplier that is the appeal of these models. This is demonstrated by the fact that three out of the twelve therapies in included in this study are registered for the treatment of spinal muscular atrophy in a span of less than five years, which is considerably shorter than the time horizons that the CPP and DCF model operate on.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003e5.4 Strengths and weaknesses\u003c/h2\u003e \u003cp\u003eThis paper aimed to identify challenges in CEA and value-based pricing for orphan drugs and to test two recently proposed alternative pricing approaches. The strength of this study lies in the verification of problems and application of solutions to orphan drug pricing found in literature, rather than assessment of the quality of the CEA\u0026rsquo;s themselves.\u003c/p\u003e \u003cp\u003eCertain limitations of this this study need to be addressed. The scope of this paper was limited to non-oncological orphan drugs that have received a formal assessment of cost-effectiveness by ZIN. This also means that these assessments adhere to the quality standards, criteria and perspective of ZIN which may vary from other HTA agencies.\u003c/p\u003e \u003cp\u003eMoreover, the strong assumptions that underlie these pricing models also apply to the price estimates performed in this study. Although these are inherent to the pricing approaches, they significantly complicate the interpretability and reliability of the prices and highlighting the need for cautious application and thorough contextualization\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003e5.5 Future research\u003c/h2\u003e \u003cp\u003eThe authors concur with the recommendations from a recent Dutch review of pricing models, including value-based pricing, CPP and DCF, which emphasizes the need for future research to improve transparency around the true cost and risks associated with the development of new (orphan) drugs and creation of integrated differential pricing frameworks (30). Such insights could be valuable to the pharmaceutical industry, payers, and decision-makers as they navigate the complex and often contentious process of ensuring patient access to necessary treatments.\u003c/p\u003e \u003c/div\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eChallenges in CEA cited in literature are present in Dutch HTA reports for orphan drugs. Although these issues cause considerable uncertainty, they do not yet negate CEA\u0026rsquo;s current ability to inform decision-making. Still, orphan drugs tend to be far from cost-effective, providing a challenge for patient access that is both timely and financially feasible. It is unlikely that current alternative pricing models in the form of CPP and DCF will provide a solution to this issue as they to estimate lower prices for these drugs than CEA and involve significant assumptions and uncertainty.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003cbr\u003e\u003c/strong\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003cbr\u003e\u003c/strong\u003eMK is an employee of Sanofi, a publicly traded company that markets (orphan) pharmaceuticals.\u003cbr\u003e\u0026nbsp;JW does not have any competing interests.\u003c/p\u003e\n\u003cp\u003eCUdG does not have any competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003cbr\u003e\u003c/strong\u003eNo funding was provided for this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMK made a substantial contributions to the conception and design of the research; the analysis and interpretation of the HTA reports; and has drafted and substantively revised the manuscript.\u003c/p\u003e\n\u003cp\u003eJW made a substantial contributions to the conception and design of the research; the acquisition analysis and interpretation of the HTA reports; and has drafted and substantively revised the manuscript.\u003c/p\u003e\n\u003cp\u003eCUdG made substantial contributions to the conception of the research.\u003c/p\u003e\n\u003cp\u003eAll authors read and approved the final manuscript\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003cbr\u003e\u003c/strong\u003eThe authors thank L. Wormhoudt, PhD, for his involvement in the supervision of the project.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; information\u003cbr\u003e\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFootnotes\u003cbr\u003e\u003c/strong\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eZorginstituut Nederland. Richtlijn voor het uitvoeren van economische evaluaties in de gezondheidszorg. 2024. https://www.zorginstituutnederland.nl/publicaties/publicatie/2024/01/16/richtlijn-voor-het-uitvoeren-van-economische-evaluaties-in-de-gezondheidszorg. Accessed 2025 Mar 26.\u003c/li\u003e\n \u003cli\u003eNicod E, Annemans L, Bucsics A, Lee A, Upadhyaya S, Facey K. HTA programme response to the challenges of dealing with orphan medicinal products: process evaluation in selected European countries.\u0026nbsp;\u003cem\u003eHealth Policy\u003c/em\u003e. 2019 Feb;123(2):140\u0026ndash;51.\u003c/li\u003e\n \u003cli\u003eDrummond MF, Wilson DA, Kanavos P, Ubel P, Rovira J. Assessing the economic challenges posed by orphan drugs.\u0026nbsp;\u003cem\u003eInt J Technol Assess Health Care\u003c/em\u003e. 2007 Jan;23(1):36\u0026ndash;42.\u003c/li\u003e\n \u003cli\u003eSchuller Y, Hollak CEM, Biegstraaten M. The quality of economic evaluations of ultra-orphan drugs in Europe: a systematic review.\u0026nbsp;\u003cem\u003eOrphanet J Rare Dis\u003c/em\u003e. 2015 Jul 30;10(1):92.\u003c/li\u003e\n \u003cli\u003eFellows GK, Hollis A. Funding innovation for treatment for rare diseases: adopting a cost-based yardstick approach.\u0026nbsp;\u003cem\u003eOrphanet J Rare Dis\u003c/em\u003e. 2013 Nov 16;8:180.\u003c/li\u003e\n \u003cli\u003eNuijten M, Van Wilder P. The impact of early phase price agreements on prices of orphan drugs.\u0026nbsp;\u003cem\u003eBMC Health Serv Res\u003c/em\u003e. 2021 Mar 12;21:222.\u003c/li\u003e\n \u003cli\u003ePearson I, Rothwell B, Olaye A, Knight C. Economic modeling considerations for rare diseases.\u0026nbsp;\u003cem\u003eValue Health\u003c/em\u003e. 2018 May;21(5):515\u0026ndash;24.\u003c/li\u003e\n \u003cli\u003eZorginstituut Nederland. Pakketadvies sluisgeneesmiddel atidarsagene autotemcel (Libmeldy\u0026reg;) voor de behandeling van metachromatische leukodystrofie (MLD). 2022. https://www.zorginstituutnederland.nl/publicaties/adviezen/2022/09/27/pakketadvies-sluisgeneesmiddel-atidarsagene-autotemcel-libmeldy. Accessed 2025 Mar 26.\u003c/li\u003e\n \u003cli\u003eZorginstituut Nederland. Beoordeling van weesgeneesmiddelen. https://www.zorginstituutnederland.nl/over-ons/werkwijzen-en-procedures/adviseren-over-en-verduidelijken-van-het-basispakket-aan-zorg/beoordeling-van-geneesmiddelen/beoordeling-van-weesgeneesmiddelen. Accessed 2025 Mar 26.\u003c/li\u003e\n \u003cli\u003eZorginstituut Nederland. Pakketadvies sluisgeneesmiddel olipudase alfa (Xenpozyme\u0026reg;) voor de behandeling van de ziekte van Niemann-Pick. 2024. https://www.zorginstituutnederland.nl/publicaties/adviezen/2024/08/21/pakketadvies-olipudase-alfa-xenpozyme. Accessed 2025 Mar 26.\u003c/li\u003e\n \u003cli\u003eUyl-de Groot CA, L\u0026ouml;wenberg B. Sustainability and affordability of cancer drugs: a novel pricing model.\u0026nbsp;\u003cem\u003eNat Rev Clin Oncol\u003c/em\u003e. 2018 Jul;15(7):405\u0026ndash;6.\u003c/li\u003e\n \u003cli\u003eThielen FW, Heine RJSD, van den Berg S, Ham RMTT, Uyl-de Groot CA. Towards sustainability and affordability of expensive cell and gene therapies? Applying a cost-based pricing model to estimate prices for Libmeldy and Zolgensma.\u0026nbsp;\u003cem\u003eCytotherapy\u003c/em\u003e. 2022 Dec;24(12):1245\u0026ndash;58.\u003c/li\u003e\n \u003cli\u003eInternational Association of Mutual Benefit Societies. AIM proposes to establish a European drug pricing model for fair and transparent prices for accessible pharmaceutical innovations. https://www.aim-mutual.org/wp-content/uploads/2019/12/AIMfairpricingModel.pdf. Accessed 2025 Mar 26.\u003c/li\u003e\n \u003cli\u003eNuijten M, Fischer HJ, Van der Meijden J. Evaluation and valuation of the price of expensive medicinal products: application of the discounted cash flow to orphan drugs. Int J Rare Dis Disord. 2018 Dec 31;1(1):5.\u003c/li\u003e\n \u003cli\u003eNuijten M, Vis J. Evaluation and valuation of innovative medicinal products.\u0026nbsp;\u003cem\u003eJ Rare Dis Res Treat\u003c/em\u003e. 2016 Dec 3;2(1):1\u0026ndash;11.\u003c/li\u003e\n \u003cli\u003eMinisterie van Volksgezondheid. Dashboard doorlooptijden geneesmiddelen. https://www.farmatec.nl/prijsvorming/dashboard-doorlooptijden-geneesmiddelen. Accessed 2025 Mar 26.\u003c/li\u003e\n \u003cli\u003eEuropean Medicines Agency. Download medicine data. https://www.ema.europa.eu/en/medicines/download-medicine-data. Accessed 2025 Mar 26.\u003c/li\u003e\n \u003cli\u003eZorginstituut Nederland. Pakketadvies sluisgeneesmiddel voretigene neparvovec (Luxturna\u0026reg;) bij de behandeling van visusverlies door erfelijke retinale dystrofie met bi-allelische RPE65-mutaties. 2020.\u003c/li\u003e\n \u003cli\u003eZorginstituut Nederland. GVS-advies cannabidiol (Epidyolex\u0026reg;) als aanvullende behandeling bij 2 ernstige epileptische aandoeningen. 2022.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003ehttps://www.zorginstituutnederland.nl/publicaties/adviezen/2022/07/04/gvs-advies-cannabidiol-epidyolex. Accessed 2025 Mar 26.\u003c/p\u003e\n\u003col start=\"20\"\u003e\n \u003cli\u003eZorginstituut Nederland. GVS-advies avacopan (Tavneos\u0026reg;). 2022. https://www.zorginstituutnederland.nl/publicaties/adviezen/2022/04/20/gvs-advies-avacopan-tavneos. Accessed 2025 Mar 26.\u003c/li\u003e\n \u003cli\u003eZorginstituut Nederland. Pakketadvies geneesmiddel pegcetacoplan (Aspaveli\u0026reg;) voor de behandeling van paroxismale nachtelijke hemoglobinurie (PNH). 2022.\u003cbr\u003e\u0026nbsp;https://www.zorginstituutnederland.nl/publicaties/adviezen/2022/09/16/pakketadvies-sluisgeneesmiddel-pegcetacoplan-aspaveli\u003c/li\u003e\n \u003cli\u003eZorginstituut Nederland. GVS-advies elexacaftor/tezacaftor/ivacaftor (Kaftrio\u0026reg;) in combinatie met ivacaftor (Kalydeco\u0026reg;). 2021.\u003c/li\u003e\n \u003cli\u003eZorginstituut Nederland. Pakketadvies sluisgeneesmiddel onasemnogene abeparvovec (Zolgensma\u0026reg;) bij de behandeling van spinale musculaire atrofie (SMA). 2021.\u003cbr\u003e\u0026nbsp;https://www.zorginstituutnederland.nl/publicaties/adviezen/2021/05/06/pakketadvies-sluisgeneesmiddel-onasemnogene-abeparvovec-zolgensma. Accessed 2025 Mar 26.\u003c/li\u003e\n \u003cli\u003eZorginstituut Nederland. Pakketadvies sluisgeneesmiddel risdiplam (Evrysdi\u0026reg;) bij 5q spinale spieratrofie (SMA). 2022.https://www.zorginstituutnederland.nl/publicaties/adviezen/2022/07/15/pakketadvies-sluisgeneesmiddel-risdiplam-evrysdi. Accessed 2025 Mar 26.\u003c/li\u003e\n \u003cli\u003eZorginstituut Nederland. GVS-advies uitbreiding vergoedingsvoorwaarden lumacaftor/ivacaftor (Orkambi\u0026reg;) voor de behandeling van cystische fibrose. 2016.https://www.zorginstituutnederland.nl/publicaties/adviezen/2016/12/15/gvs-advies-lumacaftor-ivacaftor-orkambi-bij-cystische-fibrose-cf-bij-patienten-van-12-jaar-en-ouder-die-homozygoot-zijn-voor-de-f508del-mutatie-in-het-cftr-gen-herbeoordeling. Accessed 2025 Mar 26.\u003c/li\u003e\n \u003cli\u003eZorginstituut Nederland. GVS-advies givosiran (Givlaari\u0026reg;) bij de behandeling van acute hepatische porfyrie. 2021.\u003cbr\u003e\u0026nbsp;https://www.zorginstituutnederland.nl/publicaties/adviezen/2021/02/02/gvs-advies-givosiran-givlaari-bij-de-behandeling-van-acute-hepatische-porfyrie. Accessed 2025 Mar 26.\u003c/li\u003e\n \u003cli\u003eZorginstituut Nederland. GVS-advies tafamidis (Vyndaqel\u0026reg;) bij de behandeling van ATTR amylo\u0026iuml;dose. 2020.\u003cbr\u003e\u0026nbsp;https://www.zorginstituutnederland.nl/publicaties/adviezen/2020/12/03/gvs-advies-tafamidis-vyndaqel. Accessed 2025 Mar 26.\u003c/li\u003e\n \u003cli\u003eZorginstituut Nederland. GVS-advies weesgeneesmiddel tafamidis (Vyndaqel\u0026reg;) bij de behandeling van transthyretine-amylo\u0026iuml;dose met cardiomyopathie (ATTR-CM). 2021.\u003cbr\u003e\u0026nbsp;https://www.zorginstituutnederland.nl/publicaties/adviezen/2021/08/11/gvs-advies-tafamidis-vyndaqel-bij-de-behandeling-van-attr-cm. Accessed 2025 Mar 26.\u003c/li\u003e\n \u003cli\u003eZorginstituut Nederland. Pakketadvies sluisgeneesmiddel nusinersen (Spinraza\u0026reg;) voor de behandeling van spinale musculaire atrofie (SMA). 2018.\u003cbr\u003e\u0026nbsp;https://www.zorginstituutnederland.nl/publicaties/adviezen/2018/02/07/pakketadvies-nusinersen-spinraza-voor-de-behandeling-van-spinale-musculaire-atrofie-sma. Accessed 2025 Mar 26.\u003c/li\u003e\n \u003cli\u003eManders EA, van den Berg S, de Visser SJ, Hollak CEM. 30. Drug pricing models, no \u0026lsquo;one-size-fits-all\u0026rsquo; approach: a systematic review and critical evaluation of pricing models in an evolving pharmaceutical landscape. Eur J Health Econ. 2024 Nov 4.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 2 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"orphanet-journal-of-rare-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ojrd","sideBox":"Learn more about [Orphanet Journal of Rare Diseases](http://ojrd.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ojrd/default.aspx","title":"Orphanet Journal of Rare Diseases","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Health economic assessment, cost-effectiveness analysis, pharmaceutical pricing, orphan drugs, orphan diseases","lastPublishedDoi":"10.21203/rs.3.rs-6569819/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6569819/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCost-effectiveness analyses can have limited informative value for pricing and reimbursement decisions for orphan drugs. In cases where cost-effectiveness cannot be reliably assessed or achieved, value-based pricing principles may not be applicable. As a result, alternative pricing models have been proposed. It remains unclear how these alternative approaches compare to one another and to traditional value-based pricing. This study aims to explore and compare these pricing models in the context of orphan drugs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll cost-effectiveness assessments of non-oncological orphan drugs published by the Dutch National Health Care Institute between 2015 and 2024 were analyzed to identify methodological challenges and recommended value-based price estimates. For each treatment, prices were also estimated using a cost-plus pricing model and a discounted cash-flow model. These estimates were then compared to value-based prices and public list prices.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCost-effectiveness assessments of 12 different therapies were found, 11 of which provide information for determining a value-based price. All assessment reports cited major uncertainties or unresolved issues in one or more of the following areas: (1) lack of a suitable comparator, (2) sub-optimal disease understanding, (3) limited evidence to inform models, (4) effect uncertainty and (5) flawed QoL measurement. Only one single treatment was found to be cost-effective at the appropriate threshold. Recommended value-based prices were found to fall below (1 therapy), within (6 therapies) or above (4 therapies) the price ranges of the two alternative models.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChallenges cited in literature are present in Dutch assessments of the cost-effectiveness of orphan drugs. Although these issues cause considerable uncertainty, they do not negate CEA’s current ability to inform decision-making. Still, orphan drugs tend to be far from cost-effective, providing a challenge for patient access that is both timely and financially feasible. Alternative models like cost-plus pricing and discounted cash-flow tend to generate even lower price estimates and rely on considerable assumptions, making them unlikely to offer a viable solution in their current state.\u003c/p\u003e","manuscriptTitle":"Methodological Challenges in Dutch HTA of Non-Oncological Orphan Drugs: A Retrospective Analysis and Price Comparison Using different Pricing Models","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-20 13:22:06","doi":"10.21203/rs.3.rs-6569819/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2025-08-13T00:40:51+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-05-20T13:09:08+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-15T17:42:33+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-02T08:24:15+00:00","index":"","fulltext":""},{"type":"submitted","content":"Orphanet Journal of Rare Diseases","date":"2025-05-01T03:00:26+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"orphanet-journal-of-rare-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ojrd","sideBox":"Learn more about [Orphanet Journal of Rare Diseases](http://ojrd.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ojrd/default.aspx","title":"Orphanet Journal of Rare Diseases","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"41c78267-bc4f-4821-9adb-a3b53b80b2ab","owner":[],"postedDate":"May 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-12T16:16:36+00:00","versionOfRecord":{"articleIdentity":"rs-6569819","link":"https://doi.org/10.1186/s13023-025-04181-6","journal":{"identity":"orphanet-journal-of-rare-diseases","isVorOnly":false,"title":"Orphanet Journal of Rare Diseases"},"publishedOn":"2026-01-08 15:59:29","publishedOnDateReadable":"January 8th, 2026"},"versionCreatedAt":"2025-05-20 13:22:06","video":"","vorDoi":"10.1186/s13023-025-04181-6","vorDoiUrl":"https://doi.org/10.1186/s13023-025-04181-6","workflowStages":[]},"version":"v1","identity":"rs-6569819","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6569819","identity":"rs-6569819","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}