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Health economic valueof brain atrophy and lesion monitoringin MS management

  • Writer: Milan Walraevens
    Milan Walraevens
  • Sep 14, 2020
  • 5 min read

Updated: May 13

Sep 14, 2020

How improved monitoring can reduce loss of QALY and health economical costs


Multiple Sclerosis (MS) is a chronic neurological disease, affecting  2.8 million people worldwide. As the disease is currently incurable, the focus of MS therapies is to slow down the relapses and disability progression. Today, over 20 disease-modifying treatments are clinically approved for relapsing-remitting MS (RRMS). However, providing the best treatment for each patient remains a major challenge as over 26% of patients are on a suboptimal treatment for 3.9 years1,2. It is shown that the monitoring of MRI lesions and brain atrophy allows the prediction of disability progression, relapses, and treatment effects3. This is implemented by the NEDA-4 criteria (No Evidence of Disease Activity-4), a treatment decision guideline taking into consideration MRI disease activity and atrophy in addition to the occurrence of clinical relapses and disability progression. The use of these criteria results in a 3.1 times higher probability to detect treatment failure, reducing the average time on suboptimal treatment to 1.3 years4,5


To implement the NEDA-4 criteria into clinical practice, solutions for the accurate and reproducible assessment of MRI lesions and atrophy are needed. Today, visual identification of new and enlarging lesions is time-consuming and prone to intra-rater and inter-rater variability, whereas subtle, yet relevant, annual brain atrophy changes can't be visually perceived6,7,8,9. The need for quantification of lesion and brain volume changes in clinical practice has propelled the development of automated brain volumetric software solutions. To ensure accurate and relevant results for individual patients, several factors such as acquisition protocol, method, quality control, and interpretation need to be taking into consideration.  


The early identification of treatment failure can prompt the switch to a more effective treatment sooner, which could prevent irreversible damage from taking place10. As such, early detection of therapy failure followed by a treatment switch is associated with improved outcomes. Brain atrophy and lesion monitoring have therefore the potential to improve Quality-adjusted Life Years (QALY’s) and cost-effectiveness for hospitals and insurance.


Health economic impact of brain atrophy and lesion monitoring

The economic benefit of including brain atrophy and lesion monitoring in the management of MS is related to both the imaging and radiological reporting workflow, as well as the improved treatment of RRMS patients. In the United States, where nearly 1M people live with a diagnosis of MS11, this impact could amount up to $644M of annual saved costs for imaging and treatment management as illustrated below.


Economic benefit for treatment management


The impact of the close monitoring of MRI lesions and brain atrophy in the therapy management of RRMS patients results from the ability to stop sub-optimal treatments earlier and to switch treatments earlier. The earlier the therapy starts, the more disease progression and irreversible damage can be prevented, the higher the health economic gain.

The calculation of this potential economic benefit for treatment management, taking the United States as an example, is based on the following statistics:

-Number of therapy switches per year: 8969-Cost medication:  $ 88 000 / year (nationalmssociety.org)-Number of years on a failing drug without NEDA-4: 3.9 2-Number of years on a failing drug with NEDA-4: 1.25 4-Average loss of QALYs / year: (without treatment): 0.255 12-Failing treatment: 26% 1-Percentage of RRMS patients on disease-modifying drugs: 70% 13

This translates into a potential annual cost reduction of $544 million when failing treatments are stopped, which is approximately $1945 per treated patient per year. In addition, $20,000 to $200,000/QALY could be saved due to the non-linear effect of the medication14.


Economic benefit for imaging and radiological reporting

The economic benefits for the radiology department result from the reduction in the use of imaging contrast and faster radiological reading. 

Studies have demonstrated that new T2 lesions are a reliable measure for active inflammation, meaning they could replace the role of Gadolinium enhancing lesions in 75% of the cases15. This approach is in line with the warning issued by the FDA towards the safe use of gadolinium and guidelines recommending the limitation of contrast-usage to cases with unexpected clinical deterioration or when reassessing the diagnosis of MS. 


Tracking new- and enlarging lesions, without disrupting the clinical workflow, requires the use of automated software. Such software allows the proactive monitoring of disease activity, outside the critical 3-4 week time window for contrast.

The calculation of the potential economic benefit for imaging and radiological reporting, taking the United States as an example, is based on the following statistics:

-The average number of scans per year per MS patient: 1-Cost Gadolinium: $117 16-The percentage of cases for which contrast could be replaced: 75%5-Hourly cost radiologist: $ 279 17

This translates into a potential annual cost saving of $100M for the reduction of contrast use and efficiency gains in radiology. The savings per radiological report are $88 for contrast reduction when using automated software.

 

In conclusion, the inclusion of brain atrophy and lesion monitoring in the treatment evaluation of MS could substantially benefit the management of MS. It has the potential to significantly improve the QALY of patients and has health economic benefits for various healthcare stakeholders by improving treatment management and reducing contrast usage. 



References


  1. Sa JS et al. Relapsing–Remitting Multiple Sclerosis: Patterns of Response to Disease-Modifying Therapies and Associated Factors: A National Survey, Neurol Ther. 2014 Dec; 3(2): 89–99.

  2. Rio, J et al., Change in the clinical activity of multiple sclerosis after treatment switch for suboptimal response. European Journal of Neurology 2012;19:899–904

  3. Popescu et al. Brain atrophy and lesion load predict long term disability in multiple sclerosis. BMJ 2013 http://dx.doi.org/10.1136/jnnp-2012-304094

  4. Rojas JI et al., Brain atrophy as a non-response predictor to interferon-beta in relapsing-remitting multiple sclerosis. Neurological Research 2014;37(7):615-618. 

  5. Smeets D et al., Clinical Use of Brain MRI Biomarkers for Multiple Sclerosis: A Health Economical Study in the United States, RSNA 2017, SSC12-01

  6. Altay EE, et al. Reliability of Classifying Multiple Sclerosis Disease Activity Using Magnetic Resonance Imaging in a Multiple Sclerosis Clinic. JAMA Neurol. 2013;70(3):338–344. doi:10.1001/2013.jamaneurol.211

  7. Wang J et al., Neuroradiologists Compared with Non-Neuroradiologists in the Detection of New Multiple Sclerosis Plaques American Journal of Neuroradiology Jul 2017, 38 (7) 1323-1327; DOI 10.3174/ajnr.A5185

  8. Dahan A, et al. Computer-Aided Detection Can Bridge the Skill Gap in Multiple Sclerosis Monitoring. J Am Coll Radiol. 2018;15(1 Pt A):93-96. doi:10.1016/j.jacr.2017.06.030

  9. van Heerden J et al., Improving Multiple Sclerosis Plaque Detection Using a Semiautomated Assistive Approach. American Journal of Neuroradiology Aug 2015, 36 (8) 1465-1471; DOI: 10.3174/ajnr.A4375

  10. Río J,  et al. Measures in the first year of therapy predict the response to interferon beta in MS. MustScler 2009; 15:848-853.doi: 10.1177/1352458509104591

  11. Wallin MT et al., The prevalence of MS in the United States, Neurology. 2019; 92:e1029-e104

  12. Kobelt G, et al., Costs and quality of life in multiple sclerosis - A cross-sectional study in the United States. Neurology, 2006b. 66(11): p. 1696–1702. 

  13. Atlas of MS: https://www.atlasofms.org/map/global/epidemiology/number-of-people-with-ms

  14. Chalmer TA, et al. Early versus later treatment start in multiple sclerosis: a register-based cohort study. Eur J Neurol. 2018;25(10):1262-e110. doi:10.1111/ene.13692

  15. Mattay RR, et al. Do All Patients with Multiple Sclerosis Benefit from the Use of Contrast on Serial Follow-Up MR Imaging? A Retrospective Analysis. AJNR Am J Neuroradiol. 2018; 10.3174/ajnr.A5828

  16. Drugs.com : http://drugs.com/

  17. Auntminnie: https://www.auntminnie.com/



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