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University of Groningen Health Economic Models for Relapsing-Remitting Multiple Sclerosis Hernandez , Luis Gabriel DOI: 10.33612/diss.173519209 IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below. Document Version Publisher's PDF, also known as Version of record Publication date: 2021 Link to publication in University of Groningen/UMCG research database Citation for published version (APA): Hernandez , L. G. (2021). Health Economic Models for Relapsing-Remitting Multiple Sclerosis. University of Groningen. https://doi.org/10.33612/diss.173519209 Copyright Other than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons). The publication may also be distributed here under the terms of Article 25fa of the Dutch Copyright Act, indicated by the “Taverne” license. More information can be found on the University of Groningen website: https://www.rug.nl/library/open-access/self-archiving-pure/taverne- amendment. Take-down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Downloaded from the University of Groningen/UMCG research database (Pure): http://www.rug.nl/research/portal. For technical reasons the number of authors shown on this cover page is limited to 10 maximum. Download date: 08-10-2021

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University of Groningen

Health Economic Models for Relapsing-Remitting Multiple SclerosisHernandez , Luis Gabriel

DOI:10.33612/diss.173519209

IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite fromit. Please check the document version below.

Document VersionPublisher's PDF, also known as Version of record

Publication date:2021

Link to publication in University of Groningen/UMCG research database

Citation for published version (APA):Hernandez , L. G. (2021). Health Economic Models for Relapsing-Remitting Multiple Sclerosis. University ofGroningen. https://doi.org/10.33612/diss.173519209

CopyrightOther than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of theauthor(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons).

The publication may also be distributed here under the terms of Article 25fa of the Dutch Copyright Act, indicated by the “Taverne” license.More information can be found on the University of Groningen website: https://www.rug.nl/library/open-access/self-archiving-pure/taverne-amendment.

Take-down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediatelyand investigate your claim.

Downloaded from the University of Groningen/UMCG research database (Pure): http://www.rug.nl/research/portal. For technical reasons thenumber of authors shown on this cover page is limited to 10 maximum.

Download date: 08-10-2021

Chapter 1

Introduction

10

CHAPTER 1

DISEASE BACKGROUND

Multiplesclerosis (MS) isadisease thataffects thecentralnervoussystem(CNS),causingprogressiveinflammationofthebrainandspinalcordanddemyelinationofneurons.[1,2]Thediseaseischaracterizedbyperiodsofrelapse(i.e.,episodesofneurologicaldysfunction)andremission,whichleadtoprogressiveaccumulationofdisabilityandneurodegeneration.[1]Although thecauseofMS isnotcompletelyknown, there isageneral consensus thatit likely involves a multitude of environmental (e.g., sunlight exposure, infectious agentsparticularlyEpstein–Barrvirus,vitaminD)andgeneticfactors.[2]

MSistheleadingcauseofnon-traumaticCNSmorbidityandmortalityinyoungandmiddle-aged adults.[3-5] MS leads to progressive disability, cognitive impairment, limitations inmobility,vision,andspeech,pain,fatigue,spasticity,gastrointestinalandurinarydysfunction,and emotional, psychological, andmental problems,[1, 6, 7]which negatively impact thequalityoflife(QoL)ofpeoplewithMS.[8,9]

In2016,anestimated30.1per100,000peopleworldwidehadMS, representinga10.4%increasesince1990.[10]Thehighestage-standardizedprevalenceofMSareinhigh-incomeNorthAmerica,westernEurope,andAustralasia,withestimatesof164.6,127.0,and91.1per100,000people,respectively.[10]Thelowestage-standardizedprevalenceofMSareineasternsub-SaharanAfrica,centralsub-SaharanAfrica,andOceania,withestimatesof3.3,2.8,and2.0per100,000people,respectively.[10]Globally,therewere18,932deathsduetoMSin2016,withthemortalityintheUnitedStates(US)beingthehighest(3,862deaths).[10]

FORMS OF MULTIPLE SCLEROSIS

Theprogression of the disease varies by patient, andover time, ranging froma clinicallyasymptomatic course to an aggressive course with rapid accumulation of disability.[11]Althoughclinicalpresentationisvariable,therearetwoclinicalmechanismsthatdefinethecourseofMS:[12]

• Relapses of acute neurologic symptoms, a result of inflammatory-mediated acutedemyelination,endingeitherwithapartialorcompleteremission.

• Diseaseprogression,thesteadyandirreversibleaccumulationofsymptoms,whichisthoughttoresultfromchronicandprogressiveaxonaldegeneration.

Basedon these twomechanisms,MScanbecategorized into two typesofdiseasebasedon phenotype: relapsing-remitting and progressive. Relapsing-remitting disease includesclinically isolated syndrome (CIS) and relapsing-remitting multiple sclerosis (RRMS).Progressivedisease includessecondaryprogressivemultiplesclerosis(SPMS)andprimary-

11

INTRODUCTION

progressiveMS(PPMS),whicharedifferentiatedbydiseaseonset,rateofprogression,andseverityofdisease.[11,13-15]Allmaybeclassifiedfurtherasactiveornotactive,determinedbytheoccurrenceofrelapsesand/oractivitysignalsfrommagneticresonanceimaging(MRI)activity (i.e., gadolinium-enhancing lesions,new/enlargingT2 lesions).[15] Figure1 showsthedifferentdiseasephenotypesofMS.

Figure 1. Disease phenotypes of multiple sclerosisSource:Adaptedfrom:Lublinetal.(2014)[15]*Activity=clinicalrelapsesand/orMRI(gadolinium-enhancingMRIlesions;newenlargingT2lesions)†Progressionmeasuredbyclinicalevaluation,assessedatleastannually.Ifassessmentsarenotavailable,activityandprogressionare“indeterminate.”Abbreviations:CIS=clinicallyisolatedsyndrome;MRI=magneticresonanceimaging;MS=multiplesclerosis;RRMS=relapsing-remittingmultiplesclerosis

Clinicallyisolatedsyndromeisafirstepisodeofneurologicsymptomscausedbyinflammationanddemyelination in theCNS. Theepisodemust last for at least24hours.Although thisepisodeischaracteristicofMS,itdoesnotyetmeetthecriteriaforadiagnosisofMSbecausepeoplewhoexperienceaCISmayormaynotdevelopMS.[16]

RRMS is themost common among all phenotypes ofMS.[15, 16] Approximately 85% ofpatientswithMSareinitiallydiagnosedwithRRMSduringthefirstyearsoftheirdiagnosis.[16, 17] RRMS is characterized by clearly defined alternating episodes of unpredictableinflammatoryattacks(relapses)thatcanlastfordays,weeks,ormonths,andcanresult inneurologicdisabilityfromwhichthereisfullorpartialrecovery.[15,16]However,recoverytends tobecomediminishedwith repeated relapses, resulting inaccumulatingneurologic

12

CHAPTER 1

damageandconsequentdisability.[11,13,18]RRMScan lasts foreight to20years, afterwhichpatientstransitiontoSPMS.[16,19]DuringSPMS,thereisaprogressiveworseningofneurologicalfunction(i.e.,accumulationofdisability)overtime.[15,16]

PPMS is characterized by worsening neurological function from the onset of symptoms,without early relapses or remission.[15, 16] Approximately 15% of people with MS arediagnosedwithPPMS.[15,16]

DisabilityaccumulationovertimeamongpatientswithMSisoftenquantifiedusingtheKurtzkeExpandedDisabilityStatusScale(EDSS),whichmeasuresdisabilityinseveralfunctionalandneurologicalsystems.Thestatusofdisabilityisassignedtooneof20categoriesonascaleof 0–10,with 0 being normal neurological examination and 10.0 being death due toMS(Table1).TheEDSSisusedtomeasuredisabilityinambulationandeightfunctionalsystems:pyramidal, cerebellar, brain stem, sensory, bowel and bladder, visual, cerebral total, andcerebralmentation.[20]Scores0to4.5representnormalambulationandmeasuredisabilitybasedonneurologicalexamination,whilescoresof5.0andaboverepresentprogressivelossofwalkingability.[20]

Table 1. Kurtzke Expanded Disability Status Scale

Score MS severity Disability status0 Normalneurologicalexamination1.0 Mild Nodisability,minimalsignsinoneFS1.5 Nodisability,minimalsignsinmorethanoneFS2.0 MinimaldisabilityinoneFS2.5 MilddisabilityinoneFSorminimaldisabilityintwoFS3.0 ModeratedisabilityinoneFSormilddisabilityinthreeorfourFS.Fullyambulatory3.5 FullyambulatorybutwithmoderatedisabilityinoneFSandmorethanminimaldisabilityin

severalothers4.0 Moderate Fullyambulatorywithoutaid,self-sufficient,upandaboutsome12hoursadaydespite

relativeseveredisability;abletowalkwithoutaidorrestsome500meters4.5 Fullyambulatorywithoutaid,upandaboutmuchoftheday,abletoworkafullday,may

otherwisehavesomelimitationoffullactivityorrequireminimalassistance;characterizedbyrelativelyseveredisability;abletowalkwithoutaidorrestsome300meters

5.0 Ambulatorywithoutaidorrestforabout200meters;disabilitysevereenoughtoimpairfulldailyactivities(workafulldaywithoutspecialprovisions)

5.5 Ambulatorywithoutaidorrestforabout100meters;disabilitysevereenoughtoprecludefulldailyactivities

6.0 Intermittentorunilateralconstantassistance(cane,crutch,brace)requiredtowalkabout100meterswithorwithoutresting

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INTRODUCTION

Score MS severity Disability status6.5 Severe Constantbilateralassistance(canes,crutches,braces)requiredtowalkabout20meters

withoutresting7.0 Unabletowalkbeyondapproximatelyfivemetersevenwithaid,essentiallyrestrictedto

awheelchair;wheelsselfinstandardwheelchairandtransfersalone;upandaboutinawheelchairsome12hoursaday

7.5 Unabletotakemorethanafewsteps;restrictedtowheelchair;mayneedaidintransfer;wheelsselfbutcannotcarryoninstandardwheelchairafullyday;mayrequiremotorizedwheelchair

8.0 Essentiallyrestrictedtobedorchairorperambulatedinwheelchair,butmaybeoutofbeditselfmuchoftheday;retainsmanyself-carefunctions;generally,haseffectiveuseofarms

8.5 Essentiallyrestrictedtobedmuchoftheday;hassomeeffectiveuseofarms;retainssomeself-carefunctions

9.0 Confinedtobed;canstillcommunicateandeat9.5 Totallyhelplessbedpatient;unabletocommunicateeffectivelyoreat/swallow10.0 DeathduetoMS

Sources:Kurtzke,etal.1983[20];MultipleSclerosisTrust,2012.[21]Abbreviations:FS=functionalsystem;MS=multiplesclerosis

APPROVED TREATMENTS FOR RRMS

Disease-modifying treatments (DMTs) are the current standard of care for patients withRRMS. Short courses of corticosteroids are occasionally given, but,while the side effectsassociatedwith their long-termuse arewell established, their efficacy is not proven.[22]Chemotherapeutic agents, such as cyclophosphamide, are occasionally used in cases ofsevererelapsingMS.[23]

EighteenDMTsarecurrentlyapprovedbytheUSFoodandDrugAdministration(FDA)andavailableforthetreatmentofpatientswithRRMS.[23-26]Theseare:

• Injectablemedicationso Avonex®(interferonβ-1a),approvedin1996o Betaseron/Betaferon®(interferonβ-1b),approvedin1993o Copaxone®(glatirameracetate),approvedin1996o Extavia®(interferonβ-1b),approvedin2009o Glatopa® (glatiramer acetate, generic equivalent of Copaxone® 20 mg),

approvedin2015o PlegridyTM(pegylatedinterferon[peginterferon]β-1a),approvedin2014o Rebif®(interferonβ-1a),approvedin1998

• Oralmedicationso Aubagio®(teriflunomide),approvedin2012o Gilenya®(fingolimod),approvedin2010o Mavenclad®(cladribine),approvedin2019o Mayzent®(siponimod),approvedin2019o Tecfidera®(dimethylfumarate),approvedin2013o Vumerity®(diroximelfumarate),approvedin2013

14

CHAPTER 1

o Zeposia®(ozanimod),approvedin2020• Infusedmedications

o Lemtrada®(alemtuzumab),approvedin2014o Novantrone®(mitoxantrone),approvedin2000o OcrevusTM(Ocrelizumab),approvedin2017o Tysabri®(natalizumab),approvedin2006

DMTs reduce the frequency and severity of relapses, delay the accumulation of physicaldisability,andprovidesymptomatictreatmentasneededfordepression,bladderdysfunction,orwalking impairment,amongother symptoms.[27]However, these treatmentshavenotshownsustainedreversalofdamagealreadydone.They treat the inflammatoryaspectofthedisease,butnoavailabletreatmentscanenhancetheCNSrepairthroughremyelinationorneuroaxonalprotection.[27]InjectableDMTs,mainlyusedasfirst-linetherapies,arefacedwith the issues of tolerance and adherence impacting their durable efficacy.[28] Second-line treatments for RRMShave significantly improved efficacy profiles relative to first-linecounterparts,butarecommonlyassociatedwithmoreserioussideeffects.[28]

DespitetheavailabilityofmultipleDMTs,includingthefirstgenericintheUS,theacquisitioncostsofDMTshavecontinuedto increaseovertime,[29-31]accounting forapproximately75%of the totalhealthcarecosts forpeoplewithMS.[32,33] Increasingacquisitioncostspresentachallengetodecisionmakers,payers,andstakeholderswhoneedtounderstandthecosteffectivenessof these treatments todeterminewhether theyshouldbeadoptedand reimbursed;[34, 35] increasing acquisition costs can also restrict patients access toeffectivebutexpensivedrugsthatnolongerpass“cost-effectiveness”thresholdsduetotheirhighacquisitioncost.[30]

Challenge: ThehighandgrowingnumberofDMTsforthetreatmentofpatientswithRRMScombinedwiththeirhighacquisitioncostsarelikelytocontinueincreasingthedemandforinformationaboutthecost-effectivenessoftheseDMTs.

HEALTH ECONOMIC MODELS IN RRMS

Health economic models have been widely used in economic evaluations of medicalinterventions to provide decision makers, payers, and stakeholders with the informationneeded todeterminewhether those interventions shouldbeadoptedor reimbursed.[36]Formorethantwodecades,numerouseconomicevaluationshavebeenconductedtoassessthecost-effectivenessofDMTsforthetreatmentofRRMS.[34,37-44]Economicmodelshavebeenusedtoprojecttheshort-andlong-termclinicalandeconomicconsequencesofDMTs,assessingtheircost-effectiveness,basedondata fromvariousclinicalandepidemiological

15

INTRODUCTION

studies.[34,37-43]

Theyear2001wasaturningpointinthewaymodelsfortheeconomicevaluationofDMTsin RRMS were designed and structured, with the development of the School of Healthand Related Research (ScHARR) Markov cohort model.[45-47] The ScHARR model wascommissionedbytheNationalInstituteforHealthandCareExcellence(NICE)intheUnitedKingdom(UK)aftereconomicmodelsevaluatingthecost-effectivenessofbetainterferonsandglatirameracetateinMSwerefoundunsatisfactory.[45]BeforetheScHARRmodel,economicmodelsofDMTsinRRMSwereverydiverseintermsofmodelstructureandassumptions,andoftendidnotcapturethecomplexcourseofprogressionassociatedwiththedisease.[45]Sinceitsdevelopment,allofthemodelstakingaUKperspectivearedescribedasbeingbasedexplicitlyontheScHARRmodel.[45]SomemodelsstructuredfromtheperspectiveofothercountriesarebasedontheScHARRmodel;somearebasedonthemodeldevelopedbyBelletal.(2007),alsoaMarkovcohortmodel,whichdiffersfromtheScHARRmodelonthenumberofEDSSlevelsthataregroupedtogethertodefinehealthstates.[48]

Since2001,basedontheScHARRmodel,economicmodelsevaluatingthecost-effectivenessofDMTsinRRMShavegenerallyusedaMarkovcohortmodelingapproach,characterizingthecourseofthediseaseintermsofchangesintheEDSS,[20]andtheoccurrenceofrelapsesovertime.[45-47]Thesemodelsinclude19healthstates:RRMSEDSSlevels0,1to1.5,2to2.5,…,9to9.5,SPMSEDSSlevels2to2.5,3to3.5,…,9to9.5,anddeath.Ahypotheticalcohortofpatients,allwithRRMS,startswithaninitialEDSSdistribution.Everymodelcycle(usuallyoneyear),patientswithRRMSmay:1)remainatthesameEDSSlevelwithRRMS,2)worsentoahigherEDSSlevel(increasingdisability),3)improvetoalesserEDSSlevel,4)progresstoSPMS,or5)die.OncepatientsprogresstoSPMS,theycannotreturntoalesserEDSSlevelortoRRMS;theycanonlymovetoahigherEDSSlevel,stayatthesameEDSSlevel,ordie.Patientscanexperiencerelapsesatanytime,withriskofrelapsebasedondiseasephase(i.e.,RRMSversusSPMS)andEDSSlevel.Treatmentactstodelaydisabilityworsening(i.e., transition to a higher EDSS level) and to reduce the frequency of relapses. Patientsreceivingtreatmentcanexperiencetreatment-relatedadverseevents(AEs)atanytimeandcandiscontinuetreatmentbecauseofvariouspre-definedreasons.ThetypicalstructureoftheseeconomicmodelsisshowninFigure2.

16

CHAPTER 1

Figure 2. General model structure of economic models of DMTs for RRMSSource:Adaptedfrom:Hernandezetal.(2016)[53]Ovalsrepresenthealthstates.Rectanglesrepresenteventsthatpatientscanexperienceatanytime.Treatment-relatedAEsandtreatmentdiscontinuationcanonlyoccurforpatientsreceivingtreatment.Abbreviations:AE=adverseevent;DMT=disease-modifyingtherapy;EDSS=ExpandedDisabilityStatusScale;RRMS=relapsing-remittingmultiplesclerosis;SPMS=secondary-progressivemultiplesclerosis;StateN=currentEDSSstate

Modeling the Natural History of Disability Progression in Health Economic Models in RRMSChangesindisabilityovertime(i.e.,improvementandworsening)havebeenmodeledbasedontransitionsbetweenhealthstatesthataredefinedbasedonEDSSlevels.[34,37-43,45]Thesetransitionsarebasedonatransitionprobabilitymatrix,whichincludestheprobabilitiesofmovingfromonehealth state (i.e., EDSS level) to another. Table 2 shows an exampleof a transitionprobabilitymatrixbetweenEDSSlevels.[49]AsshowninthetransitionprobabilitymatrixinTable2,atthebeginningofanygivenyear,apatientwithanEDSSlevelof2–2.5hasan49.4%probabilityofremainingatthatEDSSlevel,and21.5%,8.8%,1.1%,and0.2%probabilitiesofworseningtoanEDSSlevelof3–3.5,4–4.5,5–5.5,and6–6.5,respectively,attheendofthatyear.

Table 2. Example of transition matrix between EDSS levels

EDSS at year x

EDSS at year x+1 0 1–1.5 2–2.5 3–3.5 4–4.5 5–5.5 6–6.5 7–7.5 8–8.5 9–9.5 Total

0 0.311 0.289 0.313 0.070 0.016 0.001 0.000 0.000 0.000 0.000 1.0001–1.5 0.178 0.231 0.420 0.127 0.039 0.004 0.001 0.000 0.000 0.000 1.0002–2.5 0.060 0.130 0.494 0.215 0.088 0.011 0.002 0.000 0.000 0.000 1.0003–3.5 0.019 0.055 0.299 0.322 0.241 0.044 0.013 0.003 0.004 0.000 1.0004–4.5 0.005 0.017 0.127 0.251 0.410 0.121 0.048 0.014 0.007 0.000 1.0005–5.5 0.001 0.004 0.033 0.096 0.252 0.295 0.211 0.085 0.023 0.000 1.0006–6.5 0.000 0.001 0.009 0.034 0.123 0.257 0.329 0.190 0.056 0.001 1.0007–7.5 0.000 0.000 0.003 0.013 0.057 0.169 0.308 0.257 0.189 0.004 1.0008–8.5 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.995 0.005 1.0009–9.5 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 1.000 1.000

Patientscantransitiontoadeathhealthstateatanytime.Theprobabilityofdeathistypicallyobtainedfromage-and gender-specific all-causemortality risks for the general population, from actuarial life tables, over imposingstandardizedmortality ratios to model mortality due toMS. TheMSmortality ratios vs. the general populationincreasewiththeEDSS,rangingfrom1.432forEDSS1-1.5to6.454forEDSS9-9.5.[50,51]Abbreviations:EDSS=ExpandedDisabilityStatusScale;MS=multiplesclerosis

17

INTRODUCTION

ToinformthetransitionprobabilitymatrixofdisabilityprogressionduringRRMS,themajorityofexistingeconomicmodels,includingtheScHARRmodel,[46]haveconsistentlyuseddatafromtheLondon,Ontario,Canada(LondonOntariohereafter)dataset.[45,52]OtherstudieshavecombinedplacebodatafromRCTsofDMTsinRRMSwithdatafromtheLondon,Ontariodataset.[49,53,54]AlltheNICEappraisalsforDMTsinRRMShaveusedoneofthesetwoapproaches.[39-43,45]Despitebeingwidelyused,theLondonOntariodatasethasseverallimitationsandhasbeensubjecttomultiplecritiques:[55-59]

• Datawerecollectedmorethanthreedecadesago,reflectingthenaturalhistoryofMSinacohortfromthe1970sand1980s.[35]PatientsworsentosevereEDSSlevelsfaster thanexpected,whichmaynot reflect the rateofworseningamongpatientswithRRMStreatedincurrentclinicalsettingsgiventheadvancesinbestsupportivecareanddiseaseprognosis.[35,59]

• IneconomicmodelsofDMTs forRRMS, thecourseofdisabilityhasbeenmodeledbased on transitions between EDSS levels.[35, 38, 44, 45] However, the LondonOntariodatasetmeasureddisabilitybasedontheDSS,[52]andmappingalgorithmsfromDSStoEDSShavenotbeenpublished.

• The LondonOntario dataset contains retrospectively smoothedDSS data, rather thanactualscorescollectedinrealtime;thiscensorspatientimprovementsregardingdisability.[60]DatafromrecentRCTsofDMTsinRRMSandobservationsincurrentclinicalpracticehaveshownthatpatientscanimprovedinEDSS.[39,40,42,43,49,54,61]

• TheratesofdisabilityprogressioninMSvaryconsiderablybetweenpopulations.[10,62]Factorssuchassex,ageofMSonset,smoking,lowvitaminDlevels(particularlyinpeoplewholivefartherfromtheequator),stress,andlowlevelsofphysicalactivitycan influence disability inMS.[63, 64] Thus, natural history data from a particularcohortorcountry (e.g.,London,Ontario [Canada])mightnotbegeneralizabletoadifferentcohortorcountryofinterest.

• TheLondonOntariodatasetanditscorrespondingtransitionprobabilitymatricesarenot available in the public domain. InNICE appraisals, thesematrices aremarkedasconfidentialandarenotdisclosed.Publishedstudiesusingtransitionprobabilitymatrices derived from the London Ontario dataset do not report the actualprobabilitiesusedinthemodelandjustreferencethedataset.Twostudiesevaluatingthecost-effectivenessofdimethylfumarateforthetreatmentofRRMSintheUSandCanadapresented the actual transitionprobabilitymatrix used tomodel disabilityprogression over time. This matrix combined data from the placebo arms of theCONFIRMandDEFINERCTsofdimethylfumaratewithdatafromtheLondon,Ontariodataset.[49,54]Theactual transitionmatrix from theLondonOntariodatasetandthestepstoderivethecombinedtransitionprobabilitymatrixwerenotpresented.

In 2014, Palace and colleagues derived new transition probability matrices of disabilityprogression fromanewnaturalhistory cohort from theBritishColumbia,Canada (British

18

CHAPTER 1

Columbiahereafter) dataset.[60] Thesematrices sought to address someof the issues intheselecteduntreatedcohortfromLondonOntario,aswellasdeficienciesintheanalyticalapproach used to derive the transition probability matrices.[60] However, the BritishColumbiadatasetalsohaslimitations.[60]

• Thedataweretruncatedasoftheendof1995,thelastyearwhenDMTswerenotwidelyavailableinBritishColumbia.[60]ThenaturalhistoryofMSmayhavechangedsince1995andtheratesofprogressionmaynotreflectthoseofpatientswithRRMSwhoaretreatedincurrentclinicalsettings,giventheadvancesinbestsupportivecareanddiseaseprognosis.[35,59]

• Studies suggest that the rates of disability progression vary considerably acrosspopulations.[10,62]Thenaturalhistorydatacollectedfromaparticularcohort(BritishColumbia)mightnotbegeneralizabletoadifferentcohortorcountryofinterest.[35]

• RRMSandSPMSwerenotconsideredasseparatestates(i.e.,thetransitionprobabilitymatricesderivedfromtheBritishColumbiadatasetincludedpatientswithbothRRMSandSPMS).

o ThecomparativeefficacyofDMTsversusplacebo(i.e.,noDMT)hasbeenincorporatedineconomicmodelsasahazardratioappliedtothenaturalhistory transitionprobabilitymatrix todelaydisabilityworsening. If thetreatmenteffectofDMTsisappliedtothetransitionprobabilitymatricesderived from theBritishColumbiadataset,DMTswouldbeassumed tohaveatreatmenteffectintheprogressionofpatientswithSPMS.

o Economic models of DMTs in RRMS typically model RRMS and SPMSas separate stages of MS, with different annual relapse rates, diseasemanagement costs, QALYs, and mortality risks.[35, 39, 40, 42, 43, 53,61]ToappropriatelyusethetransitionprobabilitymatricesderivedfromtheBritishColumbiadatasetineconomicmodels,patientsshouldnotbeallowedtoprogresstoSPMSasaseparatestateinthemodel.Inaddition,theannualrelapseratesandalltheeconomicinputsrelatedtoSPMS(i.e.,costs andQALYs) should be either excluded, or included as aweightedaveragebetweenRRMSandSPMS.

Duetothe limitations in theirsourcedatasets, thetransitionprobabilitymatricesusedtomodeldisability inpatientswithRRMShavebeensourcesofuncertaintyacrosseconomicmodelsofDMTs.Thesetransitionmatricesarethebasisforcalculatingtherelativeefficacyand cost-effectiveness of DMTs versus placebo (i.e., no treatment) and between DMTs,which informcomplexreimbursementandpriceadjustmentdecisions.This isconsistentlycommenteduponinNICEtechnologyappraisals.[55-59,65]

19

INTRODUCTION

Challenge: Itisessentialtohaveaclearunderstandingofhowtheeconomicmodelsusedincost-effectivenessstudiesofDMTsforRRMShaveprogressedovertime,whatapproacheshavebeendeveloped,andwhatissuesremainandhowtheycouldbeaddressed.

Challenge: It isessentialtoidentifyanalternativecohortofuntreatedpatientstoinformthecourseofthediseaseineconomicmodelsofDMTsforRRMS,toaddress(someof)thelimitationsoftheexistingmatricesderivedfromtheLondon,Ontario,andBritishColumbiadatasets.

ENDPOINTS IN CLINICAL TRIALS OF DMTS FOR RRMS

TheEDSShasbeenthemostcommonlyusedendpointtomeasuredisabilityprogressioninRCTsofRRMS,[66,67]anditiswellunderstoodandacceptedbytheneurologyandregulatorycommunities.[68-71]However, theEDSShas several limitations, including:high intra- andinter-observervariability,[72]it isanordinalscaleandthedifferencesbetweencontiguousscoresarevariable,[72,73]itisnon-linearandthetimespentinthemiddlescoresisshortest,withpeaksatEDSS1.0–3.0and6.0–7.0,[72]EDSS levels4.0–7.5areprimarilydeterminedbasedonthedistancepeoplecanwalkandtheneedforanassistivedevice,[20]anditcannotdetectchangesinpeoplewithseveredisabilityandinvariousdomainsrelevantinMS(e.g.,upperextremityfunction,cognition).[72,73]

The MS Functional Composite (MSFC) was proposed as an alternative to address thelimitations of the EDSS.[74, 75] The MSFC includes three measures: the Timed 25-FootWalk(T25FW)testforambulatoryfunction,the9-HolePegTest(9HPT)forupper-extremityfunction, and the Paced Auditory Serial Addition Test (PASAT) for cognition.[74, 75] Thescorefromeachmeasureisfirstconvertedtoaz-score,forwhichthemeanandstandarddeviationofthepooledstudypopulationatbaselinearetypicallyusedforreference.Thenallz-scoresareequallyweightedintoacompositez-score,withhigherscoresindicatingbetterperformance.[76] Although the MSFC covers multiple major MS domains and has beenreportedtobehighlyreliableandcorrelatedwiththeEDSS,health-relatedqualityoflife,andotherimportantclinicalandeconomicindicators,itsresponsivenessisnotalwaysbetterthanEDSSandalsohasseverallimitations.[70,73,74,77-81]ThisisbecausetheMSFCdoesnotcoverallkeyMSdomains,suchasvision,andcanhavefloorandceilingeffectstopatientsatverymildandseveredisabilitylevels.[82]Furthermore,PASATscoresarestronglyimpactedbypractice.[81,83]Moreimportantly,MSFCz-scoreisaffectedbythereferencepopulation,makingtheresultsdifficulttobeinterpretedandcomparedacrossstudies.Asaresult,theMSFChasnotyetbeenwidelyacceptedasanalternativetotheEDSSbyregulators.

TheMSFC has been used as an endpoint in clinical trials ofMS, although five times less

20

CHAPTER 1

thanEDSS.[68]Whenused,theMSFChasgenerallybeenasecondaryendpointalongwiththeEDSS.[66,67,84,85]ToaddresstheindividuallimitationswiththeEDSSandtheMSFC,endpoints combining theEDSSwith theMSFC,or theMSFC individual components, havebeenproposedandusedtoassesstheefficacyofDMTsinclinicaltrialsofRRMS.[69,86,87]

AlthoughtheuseofmultipleandcompositeendpointscouldimprovethesensitivitytodetectchangeindisabilityinpatientswithRRMSinclinicaltrials,itisunclearwhethercombiningsuchadditionalmeasuresofdisabilitywiththeEDSScanappropriatelymodelthecourseofthediseaseinaneconomicmodel(comparedwithcharacterizingthecourseofthediseaseonlyintermsofchangesintheEDSSandtheoccurrenceofrelapses),andiftheycantranslateitintomeaningfuloutcomesforpayersanddecisionmakers,suchasQALYsandcosts.

Challenge: BeforeintroducingadditionaldisabilityendpointsineconomicmodelsofDMTsforRRMS,tosupplementtheEDSSandtheoccurrenceofrelapsesinthecharacterizationofthediseasecourse,itisnecessarytodeterminewhethertheadditionalendpoints(e.g.,T25FW,9HPT,PASAT)translateintomeaningfuloutcomesforpayersanddecisionmakers,suchasQALYsandcosts.

Challenge: Ifmultipledisabilityscales(e.g.,EDSS,T25FW,9HPT)aresignificantpredictorsofpatients’qualityoflife,theyshouldbeconsideredintheeconomicmodelsofDMTsforRRMS to appropriately characterize the course of the disease and assess the long-termclinical and economic implications of DMTs (e.g., QALYs), which may not be accuratelyassessediftheEDSSistheonlydisabilitymeasureusedintheeconomicmodel.

OBJECTIVES AND STRUCTURE OF THE THESIS

TheaimofthisthesisistodevelopanewmodelingframeworkfortheeconomicevaluationofDMTsforRRMS,whichcanaddressthechallengesfoundincurrenteconomicevaluationsin MS. This new framework can be then used by payers and decision makers for theassessmentor re-assessmentofDMTs, to informreimbursementdecisions fornewDMTs,andtodeterminepotentialpriceadjustmentsforcurrentlyapprovedandreimbursedDMTs.

The thesis is comprised of seven chapters. Chapter 1 provides the relevant backgroundinformation,problemformulation,andobjectivesof thethesis.Chapters 2 to 5dealwithoneormoreoftheidentifiedissuesandpavethewaytowardsthedevelopmentofanewmodelingframeworkfortheeconomicevaluationofDMTsforRRMS(Chapter 6).Chapter 7 summarizes the findings and implications from all prior chapters and concludes withrecommendations.

21

INTRODUCTION

Challenge: ThehighandgrowingnumberofDMTsforthetreatmentofpatientswithRRMScombinedwiththeirhighacquisitioncostsarelikelytocontinueincreasingthedemandforinformationaboutthecost-effectivenessoftheseDMTs.

• Chapter 2presentsaneconomicmodeldevelopedtoassess thecost-effectivenessofPlegridyTM(peginterferonβ-1a)comparedwithotherself-injectableDMTsforthetreatmentof RRMS, from theNationalHealth Service andpersonal social servicesperspective inScotland.ThismodelwasdevelopedwhenPlegridyTMwasseekingtoobtainreimbursementacrossdifferentcountriesandwasusedaspartoftheapprovalin January 2015 by the Scottish Medicines Consortium (SMC). The strengths andlimitationsoftheeconomicmodelareidentified,aswellasthepotentialfuturework.

Challenge:Itisessentialtohaveaclearunderstandingofhowtheeconomicmodelsusedincost-effectivenessstudiesofDMTsforRRMShaveprogressedovertime,whatapproacheshavebeendeveloped,andwhatissuesremainandhowtheycouldbeaddressed.

• Chapter 3 presentsa systematic literature reviewofmodelingapproaches in cost-effectivenessanalysesofDMTs forRRMS.Thesystematic literature review focusedonprovidingadetaileddescriptionofeconomicmodelspublishedbetween1January2012 to 24 December 2017 and their components, describing how themodelingapproachesandassumptionsdifferacrossstudies,identifyingareasforimprovementandfuturedevelopment,anddiscussingthechallengesinconductingfutureeconomicevaluationsoftreatmentsforRRMS.

Challenge: BeforeintroducingadditionaldisabilityendpointsineconomicmodelsofDMTsforRRMS,tosupplementtheEDSSandtheoccurrenceofrelapsesinthecharacterizationofthediseasecourse,itisnecessarytodeterminewhethertheadditionalendpoints(e.g.,T25FW,9HPT)translateintomeaningfuloutcomesforpayersanddecisionmakers,suchasQALYsandcosts.

• InChapter 4Iassessifdisabilitymeasures–T25FW,9HPT,andPASAT–significantlycontributeadditionalinformationonmeaningfuloutcomesfordecisionmakers,suchasutilitytocalculateQALYs,whichwouldotherwisenotbecapturedbytheEDSSandrelapses.IfadditionaldisabilitymeasuressignificantlypredictutilityafteraccountingfortheeffectoftheEDSSandrelapses,theseadditionalmeasuresofdisabilitycouldbeconsideredinfutureeconomicevaluationsofDMTsinRRMS.

22

CHAPTER 1

Challenge: It isessentialtoidentifyanalternativecohortofuntreatedpatientstoinformthecourseofthediseaseineconomicmodelsofDMTsforRRMS,toaddress(someof)thelimitationsoftheexistingmatricesderivedfromtheLondon,Ontario,andBritishColumbiadatasets.

Challenge:Ifmultipledisabilityscales(e.g.,EDSS,T25FW,9HPT)aresignificantpredictorsofpatients’qualityoflife,theyshouldbeconsideredintheeconomicmodelsofDMTsforRRMS to appropriately characterize the course of the disease and assess the long-termclinical and economic implications of DMTs (e.g., QALYs), which may not be accuratelyassessediftheEDSSistheonlydisabilitymeasureusedintheeconomicmodel.

• In Chapter 5, I propose a new disease model for RRMS and for SPMS, utilizingdatafromtheplaceboarmsofvariouspivotalRCTsforDMTsavailablethroughtheMultiple Sclerosis Outcome Assessments Consortium (MSOAC) Placebo Database.[88, 89] The proposed disease models for RRMS and SPMS are developed usingdiscretely integratedconditionedevent (DICE)simulation,[90]andcharacterize thecourseofthediseasebaseddisabilityimprovementsandworseningintheEDSSandT25FWovertime,aswellasbytheoccurrenceofrelapses.ChangesintheEDSSandT25FW,andtheoccurrenceofrelapses,aremodeledbasedoninterrelatedpredictiveequations(i.e.,changesinonearelikelytotriggerchangesintheothers,concurrentlyorata latertimepoint).Theresultsof the facevalidityof themodel,assessedbypresentingtheproblemformulation,theproposedstructureofthemodels,thefinalpredictiveequations,andassumptionstotwoclinicalexperts inMS,aswellas theresultsofthemodelvalidationareincludedinthischapter.

InChapter 6, the diseasemodels proposed in Chapter 5 are transformed into economicmodelstoassessthecost-effectivenessofDMTsforRRMS.ThiseconomicmodelisdevelopedtounderstandtheimpactonincrementalQALYsandtheincrementalcost-effectivenessratiowhenusing interrelateddisabilitymeasures(i.e.,EDSSandT25FW)andtheoccurrenceofrelapses,comparedwithonlyconsideringtheEDSSandtheoccurrenceof relapses,whenassessingthecost-effectivenessofDMTs.

Chapter 7summarizesthefindingsandimplicationsfromallpriorchaptersandconcludeswith recommendations for the development of future economic models of DMTs forRRMS, aswell as their potential impact on the assessment or re-assessment ofDMTs byreimbursementagencies.Futureareasofresearchinthisfieldarealsoproposed.

23

INTRODUCTION

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INTRODUCTION