Trends in administrative prevalence of multiple sclerosis and utilization patterns of disease modifying drugs in Germany

Holstiege, Jakob; Akmatov, Manas K.; Klimke, Kerstin; Dammertz, Lotte; Kohring, Claudia; Marx, Christine; Frahm, Niklas; Peters, Melanie; Ellenberger, David; Zettl, Uwe K.; Stahmann, Alexander; Bätzing, Jörg

doi:10.1016/j.msard.2022.103534

Cited by 12 publications

(13 citation statements)

References 9 publications

(13 reference statements)

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“…The total number of people with DMT prescriptions in Australia continuously increased over the last 10 years, with subsequent higher total DMT costs to the government, which is in alignment with other studies from Australia and other countries. 5,13,14 The main attributes of the increasing prescription trend may include increasing incidence and prevalence of MS stemming from the changes in risk factors and the expansion of diagnostic criteria, [15][16][17] a greater variety of available DMT options and better accessibility to subsidised DMTs. 18 As a result of the increasing prescriptions, the total costs that the Australian Government paid for DMTs increased.…”

Section: Discussionmentioning

confidence: 99%

“…9,10,24 The shifting trend from classical injectable DMTs to Group 2 oral DMTs aligns with previous studies. 13,14,25 The cause of this shift may include convenience of administration, better efficacy and the consideration of safety profile, dosage and medicine adherence. 8,26,27 However, there was a significant inter-state/territory variation on how long it took Group 2 DMTs to become more frequently prescribed than Group 1.…”

Section: Discussionmentioning

confidence: 99%

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The disease-modifying therapy utilisation and cost trend for multiple sclerosis in Australia between 2013 and 2022

Zhao,

Taylor,

Campbell

et al. 2023

Mult Scler

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Background: The MS disease-modifying therapies (DMTs) prescribing landscape in Australia have changed over time. Objectives: This study evaluated the utilisation and cost trends of MS-related DMTs in Australia over 10 years and investigated differences between States/Territories. Methods: The prescription and costs of 16 DMTs were extracted from the Pharmaceutical Benefits Scheme for 2013–2022. Descriptive approaches analysed the total number of people prescribed DMTs and total DMT costs per 10,000 population, proportions of prescriptions/costs by DMT groups and the number of people prescribed each individual DMT and costs of each DMT over the 10-year period. All estimates were for Australia and each State/Territory individually. Results: The number of people prescribed DMT and costs per 10,000 population had substantial growth between 2013 and 2022: 125%/164% for Australia, and 94%–251%/129%–373% for individual States/Territories. Higher efficacy group accounted for 54% of total people prescribed DMTs in 2013 and 75% in 2022. Fingolimod was the most popular DMT until 2020, then was dominated by ocrelizumab. The trends of individual DMT prescriptions and costs differed between states particularly in Western Australia (WA), Tasmania and Northern Territory (NT). Conclusion: DMT prescriptions and costs continuously increased over the last decade, particularly for higher efficacy DMTs, and their trends differed between States/Territories.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

The disease-modifying therapy utilisation and cost trend for multiple sclerosis in Australia between 2013 and 2022

Zhao,

Taylor,

Campbell

et al. 2023

Mult Scler

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“…From 2020 to 2022, the proportion of patients who started their therapy on a category 1 drug decreased by 14.7%, whereas the percentage of patients starting their therapy with a high-efficacy drug increased by 12.5% indicating that the EHT approach is gradually gaining ground in Germany, with more pronounced adoption in certain regions, mainly around Berlin. While German claims data analyses for 2010–2017 35 and 2012–2019 36 showed that prescriptions for interferons (category 1 medication) decreased over time, the increase in category 3 medication was not yet detectable in the observed periods.…”

Section: Discussionmentioning

confidence: 91%

Shifting from the treat-to-target to the early highly effective treatment approach in patients with multiple sclerosis – real-world evidence from Germany

Papukchieva,

Stratil,

Kahn

et al. 2024

Ther Adv Neurol Disord

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Background: While evidence highlights the effectiveness of initiating disease-modifying therapy with a high-efficacy medication for multiple sclerosis (MS) patients with poor prognostic factors, it remains unclear whether this approach has been adopted by a broad range of MS providers in Germany yet. Objective: To assess the adoption of the early highly effective treatment (EHT) compared to the treat-to-target treatment approach with the option of escalating treatment efficacy over time in Germany based on real-world evidence data. Design: Patient-level pharmacy dispensing data from the Permea platform were analysed from 2020 to 2022. Methods: In total, 29,529 therapy beginners (>18 years) were included to analyse shifts in treatment approaches over time and switching behaviour. Medication classification adhered to the German Society of Neurology guidelines and designated fumarates, glatiramer acetate, teriflunomide and interferons as low-efficacy category 1 medications; cladribine and S1P-modulators as medium-efficacy category 2 medications; and alemtuzumab, natalizumab, ocrelizumab, ofatumumab and rituximab (off-label) as high-efficacy category 3 medications. Results: Our results show that 70.0% of patients redeemed their first prescription for category 1 medication, 16.3% for category 2 and 13.7% for category 3 medications. The proportion of prescriptions filled shifted from 2020 to 2022 with a decrease of 14.7% for category 1 drugs and an increase of 12.5% for category 3 drugs. 93.2% of patients stayed on their initially prescribed medication category. 3.2% of category 1 and 3.7% of category 2 therapy beginners escalated to category 3 medication. 3.4% of category 3 medication users de-escalated their treatment to category 1 or category 2. Conclusion: While most individuals started their treatment according to the treat-to-target approach and remained on their initially prescribed medication category, there has been a steadily increasing shift towards the EHT approach since 2020. These insights demonstrate that, while not officially recommended by German guidelines, MS providers increasingly adopt the EHT approach.

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“…Such DDIs can result from the concomitant use of drugs that interfere with blood clotting, e.g., by affecting the number or function of platelets. For mitoxantrone, a cytostatic agent that is still used in exceptional MS cases in Germany [ 10 , 59 ], reductions in platelet count were described after repeated infusions [ 60 ]. This appears to be compatible with DDIs of type 27 predicted for patients receiving mitoxantrone together with antiplatelet or anticoagulant drugs such as acetylsalicylic acid ( n = 5) or rivaroxaban ( n = 1) [ 61 ].…”

Section: Discussionmentioning

confidence: 99%

Update and Application of a Deep Learning Model for the Prediction of Interactions between Drugs Used by Patients with Multiple Sclerosis

Hecker,

Frahm,

Zettl

2023

Pharmaceutics

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Patients with multiple sclerosis (MS) often take multiple drugs at the same time to modify the course of disease, alleviate neurological symptoms and manage co-existing conditions. A major consequence for a patient taking different medications is a higher risk of treatment failure and side effects. This is because a drug may alter the pharmacokinetic and/or pharmacodynamic properties of another drug, which is referred to as drug-drug interaction (DDI). We aimed to predict interactions of drugs that are used by patients with MS based on a deep neural network (DNN) using structural information as input. We further aimed to identify potential drug-food interactions (DFIs), which can affect drug efficacy and patient safety as well. We used DeepDDI, a multi-label classification model of specific DDI types, to predict changes in pharmacological effects and/or the risk of adverse drug events when two or more drugs are taken together. The original model with ~34 million trainable parameters was updated using >1 million DDIs recorded in the DrugBank database. Structure data of food components were obtained from the FooDB database. The medication plans of patients with MS (n = 627) were then searched for pairwise interactions between drug and food compounds. The updated DeepDDI model achieved accuracies of 92.2% and 92.1% on the validation and testing sets, respectively. The patients with MS used 312 different small molecule drugs as prescription or over-the-counter medications. In the medication plans, we identified 3748 DDIs in DrugBank and 13,365 DDIs using DeepDDI. At least one DDI was found for most patients (n = 509 or 81.2% based on the DNN model). The predictions revealed that many patients would be at increased risk of bleeding and bradycardic complications due to a potential DDI if they were to start a disease-modifying therapy with cladribine (n = 242 or 38.6%) and fingolimod (n = 279 or 44.5%), respectively. We also obtained numerous potential interactions for Bruton’s tyrosine kinase inhibitors that are in clinical development for MS, such as evobrutinib (n = 434 DDIs). Food sources most often related to DFIs were corn (n = 5456 DFIs) and cow’s milk (n = 4243 DFIs). We demonstrate that deep learning techniques can exploit chemical structure similarity to accurately predict DDIs and DFIs in patients with MS. Our study specifies drug pairs that potentially interact, suggests mechanisms causing adverse drug effects, informs about whether interacting drugs can be replaced with alternative drugs to avoid critical DDIs and provides dietary recommendations for MS patients who are taking certain drugs.

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Trends in administrative prevalence of multiple sclerosis and utilization patterns of disease modifying drugs in Germany

Cited by 12 publications

References 9 publications

The disease-modifying therapy utilisation and cost trend for multiple sclerosis in Australia between 2013 and 2022

The disease-modifying therapy utilisation and cost trend for multiple sclerosis in Australia between 2013 and 2022

Shifting from the treat-to-target to the early highly effective treatment approach in patients with multiple sclerosis – real-world evidence from Germany

Update and Application of a Deep Learning Model for the Prediction of Interactions between Drugs Used by Patients with Multiple Sclerosis

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