Publication
Article
The American Journal of Managed Care
Author(s):
We estimated the long-term risks and benefits of disease modifying therapies. Benefits were favored by natalizumab with minimal increased risks in the negative anti-JC virus population.
Objectives:
To estimate the long-term comparative effectiveness of first-line treatment in patients negative for anti-JC virus (JCV) antibodies with glatiramer acetate (GA), fingolimod, or natalizumab for relapsing-remitting multiple sclerosis (RRMS).
Study Design:
We developed a simulation model to estimate the average 20-year clinical risks and benefits of GA, fingolimod, and natalizumab for RRMS patients initially negative for anti-JCV antibodies.
Methods:
Model inputs included published natural history progressions of the Expanded Disability Status Scale (EDSS), treatment effects from randomized controlled trials on slowing disease progression and reducing relapse rates, risk of progressive multifocal leukoencephalopathy (PML), and utility preference scores. Outputs were long-term risks (PML risk and other non-PML risks), benefits (average relapse rate and time to disability [EDSS >7]), and quality-adjusted lifeyears (QALYs).
Results:
Compared with GA, natalizumab resulted in 4.6 fewer relapses, 0.6 more years of disabilityfree time, 0.0165 more cases of PML per treated patient, and an incremental 1.2 QALYs gained. Compared with fingolimod, natalizumab resulted in 1.7 fewer relapses, 0.1 more years of disabilityfree time, 0.0165 more cases of PML per treated patient, and an incremental 0.4 QALYs gained. The probability that incremental QALYs favored natalizumab over GA was 0.963 and natalizumab over fingolimod was 0.720.
Conclusions:
Average QALYs, a measure that aggregates across risks and benefits, favored natalizumab, suggesting more aggressive early intervention with natalizumab in the negative anti-JCV population. For certain decision makers, more evidence may be needed to further reduce the uncertainty in these comparative projections prior to making population-based adoption decisions.
Am J Manag Care. 2013;19(4):278-285Long-term clinical benefits were favored by natalizumab with minimal increased risks in the negative anti-JC virus population.
Multiple sclerosis (MS) is a chronic and morbid condition of the central nervous system. Recent US approval of disease- modifying therapies (DMTs) including fingolimod and natalizumab for relapsing-remitting MS (RRMS) provide new options for the management of the disease. The ultimate treatment goal of any DMT is to delay or prevent the long-term disability of MS while minimizing DMT-related risks. This long-term treatment goal often remains untested in randomized controlled trials.1,2
Randomized controlled trials of DMTs in RRMS lack evidence of long-term clinical benefits and risks, as follow-up periods are typically limited to 1 to 2 years. Markov models are commonly used to project the long-term cost-effectiveness of DMTs for RRMS.3-10 Thompson and colleagues used a Markov model to examine the long-term risk-benefit or comparative-effectiveness of natalizumab as compared with interferon beta-1-alpha prior to available evidence on the risk stratification of patients treated with natalizumab.11
Natalizumab treatment based on post-marketing surveillance is associated with a risk of progressive multifocal leukoencephalopathy (PML) of 2.13 per 1000 patients treated per year.12 PML is often a fatal viral disease characterized by progressive inflammation and damage to the white matter.13 PML is caused by a pathogenic form of the JC virus (JCV).12 The increased risk of PML has limited natalizumab’s use as a first-line DMT in RRMS. A 2-step assay was developed for detecting and confirming the presence of anti-JCV antibodies in human serum and plasma.14 As described in the January 2012 revised natalizumab US Food and Drug Administration (FDA) label,15 this assay can stratify the risk of PML for prospective natalizumab patients where the majority of PML risk falls on approximately 55% of RRMS patients who test positive for anti-JCV antibodies.13 The ability to stratify prospective natalizumab patients by JCV status gives rise to the following question: should natalizumab be considered first-line therapy for JCV-negative patients?
There is a need to fill critical gaps in the comparative effectiveness of DMTs for RRMS to facilitate clinical decision making. Available evidence suggests the ability to minimize PML risk for natalizumab by targeting negative anti-JCV antibody patients. Further, the long-term risks and benefits associated with natalizumab treatment should be compared with other DMTs, including fingolimod, the first oral DMT approved by the FDA in 2010. Our objective was to estimate the long-term comparative effectiveness of first-line treatment in RRMS patients initially negative for anti-JCV antibodies with glatiramer acetate (GA), fingolimod, or natalizumab.
METHODSModel Description
Figure 1
We created a Markov simulation model spreadsheet that followed good practices for decision analytic modeling in health technology evaluations.16 We used this model to project the long-term clinical benefits, risks, and quality-adjusted life-years (QALYs) of a cohort of RRMS patients negative for anti-JCV antibodies who were DMT treatment—naïve and had begun treatment with GA, fingolimod, or natalizumab (). We selected GA as a representative of standard first-line agents because it is a market leader in the United States and 3 head-to-head trials comparing GA with interferons suggest no significant difference in clinical efficacy.17-19
We simulated a cohort of patients who progressed through health states defined by the Expanded Disability Status Scale (EDSS).20 Each year, patients could remain in their current EDSS state, progress to the next EDSS state, experience PML (for natalizumab-treated patients), or experience death due to all other causes. EDSS states were in 0.5 increments between 0 and 10 (no EDSS state of 0.5 existed and an EDSS of 10 was death due to MS). In all EDSS states, patients could experience an MS relapse or not experience a relapse during each yearly cycle.
This research was considered exempt by the Colorado Multiple Institutional Review Board.
We made the following model assumptions:
• During a 1-year cycle, patients could not improve in terms of their EDSS state (patients could not transition to a lower EDSS state).
• Patients were measured over a 20-year time period (consistent with a prior risk-benefit model).11
• The average starting age was 30 years (consistent with DMT clinical trials and prior models).1,8,11
• There was a 0% discount rate for future years of life (cost-effectiveness models typically discount future costs and clinical consequences at 3% per year in order to estimate the net present value of costs and consequences). Since our objective was to project the findings in clinical terms (comparative effectiveness, not cost-effectiveness) over the 20-year time horizon, a 0% discount rate was warranted. The 0% discount rate is synonymous with projecting 20-year survival (with quality adjustment) and therefore holds more face validity than discounting survival for this clinical objective.
• The average clinical efficacy for patients negative or positive for anti-JCV antibodies would be the same as observed from clinical trials.
• There was a 2% annual seroconversion risk of JCVnegative to JCV-positive status over the 20 years,14 and constant annual risk of PML from years 2 to 20 (PML incidence is shown to be constant from 2 to 6 years of natalizumab exposure time).12
• There was no prior immunosuppressant use in those that seroconverted to JCV-positive status (immunosuppressant therapy in combination with JCV-positive status is associated with higher risk of PML, but 90.4% to 97.3% of patients followed in large MS cohort studies do not have prior immunosuppressant use).12
• There was no additional risk of cardiac or other death risk related to fingolimod.
• Equal effect on relapse rate and EDSS changes regardless of relapse rate or EDSS level at outset, ie, clinical effectiveness is the same for individuals with less or more severe disease.
• Continuous treatment with each agent, and no switching to an alternative agent over time, regardless of clinical change.
RRMS Natural History Projections
eAppendices A
B
The London, Ontario, Canada, MS cohort study tracked the 25-year progression of RRMS patients prior to DMTs (best supportive care only).21 Best supportive care in the London, Ontario, cohort was defined as symptom control, physiotherapy, psychiatric and social support, and disability aids. A patientlevel analysis of the London, Ontario, MS cohort was done by Tappenden and colleagues for the purposes of estimating EDSS initial state distribution, as well as the EDSS transitions for best supportive care.7 Tappenden and colleagues combined the information from the London, Ontario, cohort on best supportive care with other literature sources to estimate the cost-effectiveness of beta interferons and GA compared with best supportive care.7 We used Tappenden’s EDSS initial state distribution for all comparators, as well as the EDSS transitions for best supportive care as a foundation for EDSS transitions of DMTs added on to best supportive care, 7 and ,7 available at www.ajmc.com).
The initial EDSS state distribution was consistent with DMT RCTs for GA, fingolimod, and natalizumab. Approximately 88% of patients in the model started in EDSS states 0 through 2.5 (minimal to mild disability) for all DMT scenarios. The average EDSS scores in previous RCTs of DMTs are in the 2 to 3 range.1,22 We used the National Center for Health Statistics estimates for the annual gender- and agespecific all-other cause mortality.23
eAppendix C
We used relapse rates specific to EDSS state for best supportive care that were consistent with Tappenden and colleagues from the Patzold data9,24 (9). Patzold and colleagues reported relapse rates for best supportive care over a 19-year time period and showed that relapses decreased with increased disease exposure. We tested the validity of the modeled relapse rates by comparing the 1- and 2-year projected average annual relapse rates of best supportive care with that of the placebo arms of a natalizumab RCT.1
DMT Projections—Modeling Treatment-Specific Risks and Benefits
Table 1
We compared 3 DMT strategies: GA 20-mg subcutaneous administration daily, fingolimod 0.5-mg oral (pill) administration daily, and natalizumab 300-mg intravenous administration every 4 weeks. We used the relative changes in relapse rates and EDSS progression from the pivotal RCTs for GA versus placebo,25 fingolimod versus placebo,22 and natalizumab versus placebo26 (9,12,22,25-27). Due to a concern that the underlying risk of relapses may have decreased over calendar time, we modeled relative changes in risks because relative changes are thought to be more robust across ranges of underlying risk.28
The annual risk of PML per natalizumab-treated patient with negative anti-JCV status was 0.00009 (95% confidence interval [CI], 0.000001 to 0.00048), whereas natalizumab-treated patients that seroconverted to positive anti-JCV status (and were assumed to have no prior immunosuppressant use) had an annual risk of PML of 0.00056 (95% CI, 0.00036-0.00083) for <2 years of natalizumab exposure and an annual risk of PML of 0.0046 (95% CI, 0.0037-0.0056) for >2 years of natalizumab exposure (Table 1). We tested the average risk for patients regardless of JCV antibody or immunosuppressant use status as a sensitivity analysis (2.13 per 1000 patients treated per year).12
Net Health Effect Projections (QALY)
eAppendix D
The QALY is a measure that incorporates both morbidity and mortality. Health-related quality of life utilities make up the “quality-adjusted” dimension of the QALY and survival makes up the “life-year” dimension. Utility values are anchored at 0 for death and 1 for perfect health. Utility values and survival are estimated for health states and specific risks and benefits. For each time interval of survival, the utility weight is multiplied by the survival time and summed overall survival times, thus producing QALYs.29 The QALY allows for the translation of independent risks and benefits into 1 common outcome measure. We assumed a utility weight for the EDSS health states that was consistent with the Tappenden and colleagues AHRQ report9 (9). The range of utility scores was from 0.97 for an EDSS score of 0 to —0.4 for an EDSS score of 9.5 (a utility score lower than 0 is valued worse than death). A utility of –0.4 (assumed to be the worst possible living health state) was assigned to the year in which a patient experienced PML. The following year, patients with PML were assumed to die. This is a conservative assumption that stacks the evidence against natalizumab, and was similarly modeled in Thompson and colleagues.11 A base-case disutility value of –0.013 was used to capture the non-PML risks associated with DMTs such as flulike symptoms and hepatotoxicity.27 Given the lack of evidence linking preference scores to non-PML DMT-related risks, the same disutility value for non-PML risks was assigned across all 3 DMTs for the base case. We assumed a disutility associated with a relapse of —0.22 for an average duration of 46 days.9
Analyses
We projected the 20-year average long-term risks (PML risk and disutility associated with other non-PML treatment risks), benefits (average relapse rate and time to disability, EDSS >7), and QALYs by DMT strategy. We compared incremental (absolute) risks, benefits, and QALYs for: fingolimod versus GA, natalizumab versus GA, and natalizumab versus fingolimod. We assessed the proportional weights of the clinical benefits and risks in terms of incremental QALYs to determine what risks and benefits are important drivers of incremental value. For example, for natalizumab versus GA, we assumed the same relapse reduction and PML risk for natalizumab and GA to determine the impact that differences in progression had on incremental QALYs. Then we repeated this step for assessing differences in relapses and PML risk while holding constant the other benefits/risks.
One-way sensitivity analyses included varying the time horizon of the model (2- and 10-year results), discounting future clinical consequences by 3% per year, changing the modeled cohort to include a representative RRMS population regardless of JCV status, and a “break-even” analysis. In the “break-even” analysis, we varied relative EDSS progression, relative relapse rate, PML risk, and disutility of treatment to determine the input value for the preferred DMT (the DMT with >0 incremental QALYs) that would have resulted in an incremental QALY equal to 0.0. The probabilistic sensitivity analyses used uncertainty in inputs defined by probability distributions to generate 95% credible intervals of the outputs. The probabilistic sensitivity analyses allowed for a Bayesian interpretation of the incremental findings (ie, the probability that the incremental QALYs were greater than 0, given the current evidence).30 Therefore, we do not interpret results in the traditional frequentist frame with null hypotheses and P values but rather interpret the likelihood of the incremental findings favoring a particular intervention given the current evidence. The likelihood or probability that 1 DMT was favored over another in terms of QALYs was reported in the main results.
RESULTSBase-Case Results
Table 2
Compared with GA, fingolimod resulted in 2.9 (95% credible interval, 1.3-4.5) fewer relapses, 0.5 (95% —0.4 to 2.2) more years of disability-free time, and an incremental 0.8 (95% –0.5 to 2.5) QALYs gained (). The probability that the incremental QALYs favored fingolimod over GA was 0.858. Compared with GA, natalizumab resulted in 4.6 (95% 3.2-6.1) fewer relapses, 0.6 (95% —0.2 to 2.2) more years of disability free time, 0.0165 (95% 0.0155-0.0191) more cases of PML per treated patient, and an incremental 1.2 (95% –0.1 to 2.8) QALYs gained. The probability that the incremental QALYs favored natalizumab over GA was 0.963. Compared with fingolimod, natalizumab resulted in 1.7 (95% 0.5-3.1) fewer relapses, 0.1 (95% –0.4 to 0.8) more years of disabilityfree time, 0.0165 (95% 0.0155-0.0191) more cases of PML per treated patient, and an incremental 0.4 (95% –0.7 to 1.4) QALYs gained. The probability that the incremental QALYs favored natalizumab over fingolimod was 0.720. All DMTs were associated with –0.26 (95% –0.41 to –0.10) QALYs due to non-PML risks.
Linking Clinical Risks and Benefits to the QALY
Figure 2
The percentage contribution in terms of specific benefits to the incremental QALY was 87% for slowing EDSS progression and 13% for reducing relapse rates for fingolimod versus GA (). Non-PML risks were assumed to be the same and therefore did not contribute to the incremental QALY. The percentage contribution in terms of specific benefits and risks to the incremental QALY was 81% for slowing EDSS progression, 12% for reducing relapse rates, and 7% for the increased PML risk for natalizumab versus GA. The percentage contribution in terms of specific benefits and risks to the incremental QALY was 74% for slowing EDSS progression, 10% for reducing relapse rates, and 17% for the increased PML risk for natalizumab versus fingolimod.
Sensitivity Analyses
Assuming a time horizon of 2 years, we found the incremental QALYs to be 0.02, 0.04, and 0.01 for fingolimod versus GA, natalizumab versus GA, and natalizumab versus fingolimod, respectively. Assuming a time horizon of 10 years of treatment, we found the incremental QALYs to be 0.23, 0.37, and 0.14. Assuming a 3% discount per year for future outcomes, we found the incremental QALYs over a 20-year time horizon to be 0.52, 0.81, and 0.29. The 3% discount assumption attenuates the incremental QALYs toward 0 but does not impact the likelihood that the incremental QALYs would be >0 for all pairwise comparisons. Assuming a modeled cohort without regard to JCV status, we found the incremental QALYs over a 20-year time horizon to be 0.76, 0.98, and 0.22 for fingolimod versus GA, natalizumab versus GA, and natalizumab versus fingolimod, respectively. Without regard to JCV status, the likelihood that the incremental QALYs >0 was unchanged for fingolimod versus GA (0.858), 0.949 for natalizumab versus GA, and 0.645 for natalizumab versus fingolimod.
Table 3
Relative risk for EDSS progression, relative risk for relapse rates, increased PML risk for natalizumab, and disutilities for treatment were ranged to determine the break-even point on particular inputs in terms of incremental QALYs (). For example, in order to break even in terms of incrementalQALYs, the PML annual risk per person for the negative anti- JCV population would need to be increased from 0.00009 to 0.0113 (a 125-fold increase) for natalizumab (natalizumab vs GA), and from 0.00009 to 0.0039 (a 43-fold increase) for natalizumab (natalizumab vs fingolimod).
DISCUSSION
Our base-case findings suggest that initial treatment with natalizumab compared with GA or fingolimod in an initially JCVnegative population yields on average lower relapses, trending toward more time until disability, and a very small increased risk of PML. Natalizumab achieved the highest QALYs compared with GA or fingolimod, suggesting that on average, the benefits may outweigh the risks, particularly in the JCV-negative population. The probabilistic sensitivity analysis generated uncertainty in the incremental QALY findings. The likelihood that 20-year incremental QALYs favored natalizumab was 0.963 compared with GA and was 0.720 compared with fingolimod. For certain decision makers, more evidence may be needed to further reduce the uncertainty in these comparative projections prior to adopting earlier intervention with natalizumab. However, arguments have been made that when comparators have passed the regulatory hurdle, the treatment strategy that maximizes net health gains (eg, QALYs) should be considered for the purposes of treatment adoption decisions.31 Value of information methods can aid in deciding whether additional evidence should be gathered to reduce the uncertainty in treatment adoption decisions.31
Our break-even analysis posited that the average risk of PML for the negative anti-JCV population would need to be 125, or 43 times higher than observed for natalizumab’s risk-benefit profile to equal that of GA’s or fingolimod’s, respectively. Without regard to JCV antibody status, the average risk of PML would still need to be 4.3 or 1.8 times higher than observed for natalizumab’s risk-benefit profile to equal that of GA’s or fingolimod’s, respectively, suggesting that natalizumab remains the favored DMT on average. Our study results that favor natalizumab assuming risk neutrality are consistent with the findings from a survey of 200 MS patients. Calfee found that many MS patients want the freedom to be able to decide in consultation with their physician to incur a 1-in-1000 (or even greater) risk of a fatal side effect so long as the drug is significantly more effective.32 A total of 55% of survey patients reported as either definitely or probably opting for a drug with the above-mentioned risk-benefit profile. Our study’s decision-analytic approach could further facilitate such complex patient-physician treatment decisions.
In linking clinical risks and benefits to the incremental QALY, we determined that slowing EDSS progression was a major contributor to all pairwise treatment comparisons. In other words, EDSS progression was a driver of the incremental QALYs over a 20-year time horizon. This finding is consistent with clinical expectations and the goals of therapy. Relapse rates decline with duration of MS and therefore are not the primary clinical benefit over the long-term course of the disease.
The 2-year time horizon sensitivity analysis suggested that very little difference was observed across DMTs in terms of the global health outcome of QALYs. Time to disability was not differentiated over the 2-year time horizon and relapse reductions did not translate into meaningful benefits in terms of QALYs over 2 years. Annualized relapse rates over the 2-year time horizon were generally consistent with RCTs. For example, the RCT evidence on natalizumab yielded an annualized relapse rate of 0.24 whereas placebo (best supportive care) was 0.75.26 The model generated an annualized relapse rate of 0.23 for natalizumab and 0.72 for best supportive care. This level of consistency supports the face validity of the simulation model. The 10-year time horizon started to show signs of differentiation between DMTs. However, over 10 years, incremental QALYs remained less than 0.5 for all DMT comparisons.
The findings add to the comparative effectiveness research literature on DMTs. First, we included and compared recent FDA-approved DMTs for RRMS and focused on the JCVnegative population in order to minimize the risk of PML for natalizumab-treated patients. No other known study stratifies the population based on JCV status to investigate long-run risks and benefits for newer and older DMTs. Second, similar to Thompson and colleagues,11 we linked clinical risks and benefits to QALYs. In doing so, we were able to weigh risks and benefits to aid in population-based decision making. Finally, as further evidence emerges, the framework we presented may be replicated for future comparative-effectiveness evaluations of current and pipeline DMTs and additional subpopulations.
We did not include all DMTs in this study, namely the interferons (3 head-to-head trials showed similar efficacy to GA)17-19 and teriflunomide. We used the best available evidence on risk of PML associated with natalizumab for patients who were initially negative for anti-JCV antibodies and added a sensitivity analysis using the average observed risk of PML without regard to JCV status based on current post-marketing observations.12 Stratification by previous immunosuppressant exposure can further differentiate the PML risk in JCV-positive patients and should be evaluated in future studies.13 Evidence on the risks of all DMTs, especially the newer agents, may change with longer use and more widespread utilization in diverse populations. Recent reports of deaths in fingolimod- treated patients potentially due to cardiac risk factors could significantly alter the QALY determinations.
We assumed risk neutrality when aggregating across risks and benefits for the purposes of estimating incremental QALYs. For risk-averse patients, one could undergo a trade-off exercise to determine the level of risk they are willing to accept for a given benefit.11 Due to a lack of evidence, this study did not evaluate the risks and benefits of switching or differential discontinuation of treatment. This limitation is consistent with intention-to-treat analyses used in the trials to estimate efficacy. EDSS transitions for best supporting care (no DMT) were based on a cohort from the 1980s.21 Although risk of PML associated with natalizumab is emerging, the risk is still relatively unknown beyond 6 years of natalizumab exposure.12
Finally, we made the assumption to not allow improvement in terms of EDSS across yearly time intervals. Due to this assumption, our findings may be conservative for DMTs that can show not only a delay in EDSS progression, but improvements in disease status for some patients. Not allowing improvement in EDSS is consistent with past projection models in MS,3-11 but this assumption should be relaxed in future models if DMT clinical evidence supports improvements in disease status. For example, outcome measures from trials that emphasize mean EDSS over various time intervals as well as patient-centered quality of life would be helpful in projecting more comprehensive long-term comparative effectiveness.
In conclusion, long-term clinical benefits were favored by natalizumab with minimal increased risk of PML in the negative anti-JCV population. Average QALYs, a measure that aggregates across risks and benefits, favored natalizumab, suggesting more aggressive early intervention with natalizumab in the negative anti-JCV population. For certain decision makers, more evidence may be needed to further reduce the uncertainty in these comparative projections prior to adopting earlier intervention with natalizumab. Arguments have been made to extend the time horizon of DMT RCTs to 5 or 10 years.33 In practice, a head-to-head RCT of many DMTs for 5 to 10 years will be difficult to achieve. In the absence of long-term RCTs, we used traditional and standardized methodology from the cost-effectiveness field for the purposes of quantifying comparative- effectiveness research goals. Comparative-effectiveness models like this may be used to compare additional DMTs to provide projections about long-term risks and benefits in many different patient subpopulations, estimate the uncertainty in the comparative findings, and guide the design of future evidence generation.
Author Affiliations: From Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado (JDC, RBM, KN), Aurora, CO; Department of Neurology (AM, JRC, TLV), University of Colorado School of Medicine, Aurora, CO.
Funding Source: This research was funded in part by The Agency for Healthcare Research and Quality as part of the Colorado Comparative Effectiveness Research K12 Training Program: K12 HS019464. No other funding source was directly tied to this study.
Author Disclosures: The authors (JDC, RBM, AM, JRC, TLV, KN) report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.
Authorship Information: Concept and design (JDC, RBM, AM, JRC, TLV, KN); acquisition of data (JDC, RBM); analysis and interpretation of data (JDC, RBM, AM, JRC, TLV, KN); drafting of the manuscript (JDC, AM, JRC, TLV, KN); critical revision of the manuscript for important intellectual content (RBM, AM, JRC, TLV, KN); statistical analysis (JDC, RBM); provision of study materials or patients (RBM); obtaining funding (JDC); and supervision (AM, JRC, TLV, KN).
Address correspondence to: Jonathan D. Campbell, PhD, Assistant Professor, University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences, Anschutz Medical Campus, Department of Clinical Pharmacy, Mail Stop C238, 12850 E Montview Blvd, V20-1205, Aurora, CO 80045. E-mail: Jon.Campbell@ucdenver.edu.1. Goodin DS, Cohen BA, O’Connor P, et al. Assessment: the use of natalizumab (Tysabri) for the treatment of multiple sclerosis (an evidence-based review): report of the Therapeutics and Technology Assessment Subcommittee of the American Academy of Neurology. [Review] [40 refs]. Neurology. 2008;71(10):766-773.
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