Health Economic Evidence for Liquid- and Tissue-based Molecular Tests that Inform Decisions on Prostate Biopsies and Treatment of Localised Prostate Cancer: A Systematic Review

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Review

–

Prostate

Cancer

Health

Economic

Evidence

for

Liquid-

and

Tissue-based

Molecular

Tests

that

Inform

Decisions

on

Prostate

Biopsies

and

Treatment

of

Localised

Prostate

Cancer:

A

Systematic

Review

Koen

Degeling

a,b

,

Amanda

Pereira-Salgado

a,b

,

Niall

M. Corcoran

c,d,e

,

Paul

C. Boutros

f,g,h,i,j

,

Peter

Kuhn

k,l,m

,

Maarten

J. IJzerman

a,b,n,o,

*

a_Cancer_Health_Services_Research,_Centre_for_Cancer_Research,_Faculty_of_Medicine,_Dentistry_and_Health_Sciences,_The_University_of_Melbourne,_Melbourne,

Australia;b_Cancer_Health_Services_Research,_Centre_for_Health_Policy,_Melbourne_School_of_Population_and_Global_Health,_Faculty_of_Medicine,_Dentistry_and

HealthSciences,TheUniversityofMelbourne,Melbourne,Australia;c_Department_of_Urology,_Frankston_Hospital,_Frankston,_Australia;d_Department_of

Surgery,TheUniversityofMelbourne,Melbourne,Australia;e_Division_of_Urology,_Royal_Melbourne_Hospital,_Melbourne,_Australia;f_Eli_and_Edythe_Broad

CenterofRegenerativeMedicineandStemCellResearch,UniversityofCalifornia,Los Angeles,CA,USA;g_Institute _for_Precision_Health,_University_of

California, Los Angeles, Los Angeles, CA,USA; h_Jonsson _{Comprehensive} _Cancer_Centre, _University _of _California, _Los _Angeles, _Los _Angeles, _CA,_USA;

i_Departments_of_Human_Genetics_and_Urology,_University_of_California,_Los_Angeles,_Los_Angeles,_CA,_USA;j_Department_of_Medical_Biophysics,_University_of

Toronto,Toronto,Canada; k_USC_Michelson_Center_for_Convergent_Biosciences,_University_of_Southern_California,_Los_Angeles,_CA,_USA;l_Department_of

BiologicalSciences,DornsifeCollegeofLetters,Arts,andSciences,UniversityofSouthernCalifornia,LosAngeles,CA,USA;m_Norris_{Comprehensive}_Cancer

Center,KeckSchoolofMedicine,UniversityofSouthernCalifornia,LosAngeles,CA,USA;n_Department_of_Cancer_Research,_Peter_MacCallum_Cancer_Centre,

Melbourne,Australia; o_Health_Technology_and_Services _Research,_Faculty_of_Behavioural, _Management_and_Social_Sciences,_Technical _Medical_Centre,

UniversityofTwente,Enschede,TheNetherlands

EUROPEAN UROLOGYOPENSCIENCE27 (2021)77–87 a v ai l a b l e a t w w w . s c i e n c e d i r e c t . c o m j o u r n al h o m e p a g e : w w w . e u - o p e n s c i e n c e . e u r o p e a n u r o l o g y . c o m Articleinfo Articlehistory: AcceptedMarch6,2021 AssociateEditor: GuillaumePloussard Keywords: Biomarker Bloodtest Budgetimpact Cost Cost-effectiveness Healtheconomics Liquidbiopsy

Localisedprostatecancer Tissue-basedtest Urinetest

Abstract

Context: Severalliquid-andtissue-basedbiomarkertests(LTBTs)areavailableto informtheneedforprostatebiopsiesandtreatmentoflocalisedprostatecancer (PCa) through risk stratification, but translation into routine practice requires evidenceoftheirclinicalutilityandeconomicimpact.

Objective: Toreviewandsummarisethehealtheconomicevidenceontheabilityof LTBTs to informdecisions on prostate biopsies and treatmentof localised PCa throughriskstratiﬁcation.

Evidenceacquisition: Asystematicsearch wasperformedintheEMBASE, MED-LINE,HealthTechnologyAssessment,andNationalHealthServiceHealthEconomic Evaluationdatabases.Eligiblepublicationswerethosepresentinghealtheconomic evaluationsofanLTBTtoselectindividualsforbiopsyorrisk-stratifyPCapatients fortreatment.Dataonthestudyobjectives,context,methodology,clinicalutility, andoutcomeswereextractedandsummarised.

Evidencesynthesis: Ofthe22studiesincluded,14werefocusedontest-informed biopsiesandeightontreatmentselection.Moststudiesperformed cost-effective-nessanalyses(n=7),followedbycosting(n=4)orbudgetimpactanalyses(n=3). Most(18of22)studiesconcludedthatbiomarkertestscoulddecreasehealthcare

*Correspondingauthor.UniversityofMelbourneCentreforCancerResearch,305GrattanStreet,

Melbourne,VIC3000,Australia.Tel.+61385598585.

E-mailaddress:maarten.ijzerman@unimelb.edu.au (M.J.IJzerman).

http://dx.doi.org/10.1016/j.euros.2021.03.002

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1. Introduction

Distinguishing between indolent and aggressive tumours remains a challenge in the diagnosis and management of localised prostate cancer (PCa). Existing clinical prognostic assays,such as digitalrectalexamination (DRE)andserum levelsofprostate-specificantigen(PSA),havelimited specifici-tyandsensitivityforearlyidentificationofaggressivetumours. TogetherwiththelackofcomprehensiveliquidbiopsiesinPCa care,thisisleadingtomanytissuebiopsiesandrepeatbiopsies thathavesubstantialcostandclinicalcomplications,suchas bleedingandinfection,leadingtomajorhealthandeconomic burdensonpatientsandsociety.Giventhataminorityofall PCas diagnosed represent life-threatening disease and that tissuebiopsieshavelimitedprecisioninpredictingtheclinical courseofthedisease,thehealthandeconomicburdenforPCa patientsandsocietyisfurtherincreasedbyoverdiagnosisthat mayleadtoovertreatment[1,2].

To reduce the burden of PCa, prospective evidence suggeststhatpatientswithlowandfavourable intermedi-ateriskPCa (PSA <10ng/mland Gleason 3+4 [grade group2])maybemanagedthroughactivesurveillance(AS)

[3,4]. The ProtecTstudy randomised 1643 patients with screen-detectedPCa,ofwhomapproximately80%hadlow or favourable intermediate risk, to AS, radical prostatec-tomy,orradiotherapyastheinitialmanagementstrategy

[5]. After median follow-up of 10yr, radical treatment reduced therisk ofdisease progression, but asignificant difference in PCa-specific or overall survival was not observed.Despitetheseresultsandthecommon complica-tionsassociatedwithradicaltreatmentsthatsubstantially impact qualityof life[5],severalreal-world studies have shownthatonly30–50%ofpatientswithlowriskand10– 15%ofthosewithintermediateriskareinitiallymanaged with ASin the USA, Germany, andAustralia [6–10]. This suggests that both under- and overtreatment of PCa continuetoposeasubstantialhealthandeconomicburden onpatientsandsociety.

Tobettertargettreatmentandtoreducethenumberof tissue biopsies, liquid and tissue-based biomarker tests

(LTBTs)havebeendevelopedtoimproveriskstratification of(suspected)localisedPCa.Thesetestshavetwospecific applications inthecontextoflocalised PCa bypredicting whetherpatients harbouranaggressivetumour:(1)they indicate which patients should undergo a repeat biopsy afteraninitialnegativebiopsyand(2)theyindicatewhich patientsarecandidatesforASandwhicharemostlikelyto benefitfromactivetreatment,suchasradicalorsystemic treatment. Although several LTBTs are authorised on the basisofextensivevalidationstudiesandarecommercially available, they have not yet been studied in prospective interventionaltrialsandarenotstronglyrecommendedfor localised disease in clinical guidelines of leading profes-sional societies, such as the European Association of Urology, American Urology Association, and American SocietyforClinicalOncology[3,11].TheNational Compre-hensive Cancer Network (NCCN) recommends consider-ation ofbiomarkersinselectingindividualsforaprostate biopsy to improve the specificity of screening [12]. The NCCNdoesnotrecommend routineuseofbiomarkersfor informing decisions on treatment, but suggests that patients with low- and favourable intermediate-risk PCa may consideruseofthetissue-basedDecipher, Oncotype Dx,andProlaristestsduringinitialriskstratification[13].

InadditiontoevidenceontheclinicalutilityofLTBTsin improvingoutcomes,healtheconomicevidenceisrequiredto justifythecostsoftheseteststoensuresuccessfultranslation towidespreadclinicaluse.Manycountriesaroundtheworld, suchastheUK,Canada,andAustralia,requireevidenceonthe cost-effectiveness or “value for money” of health care technologiesbeforetheiruseisreimbursedbypublichealth care systems.Althoughrecent clinical-evidence reviewsof these tests have suggested the need to include cost-effectiveness [14–16], a formal appraisal of the health economicevidencefortest-informedmanagementofPCais lacking.Wesoughttofillthisgapandprovideabasisforfuture study design enabling economic evaluations of LTBT by reviewingthecurrenthealtheconomicevidenceontheuseof LTBTstoinformtheneedfora(repeat)biopsyortreatment decisionsforlocalisedPCa.

costsorwouldbecost-effective.However,downstreamconsequencesand long-termoutcomesweretypicallynot includedinstudies thatevaluatedLTBTto informbiopsies. Long-term effectivenesswas modelled bylinking evidence fromdifferentsourcesinsteadofusingdatafromprospectivestudies. Conclusions: AlthoughstudiesconcludedthatLTBTswouldprobablybe cost-saving or -effective, the strength of this evidence is disputable because of concernsaroundthevalidityandtransparencyoftheassumptionsmade.This warrantsprospectiveinterventionaltrialstoinformhealtheconomicanalyses toensurecollectionofdirectevidenceofclinicaloutcomesbasedonLTBTuse. Patientsummary: Wereviewedstudies thatevaluatedwhetherblood,urine, andtissuetestscanreducethehealthandeconomicburdenofprostatecancer. Resultsindicatethatthesetestscouldbecost-effective,butclinicalstudiesof long-termoutcomesareneededtoconﬁrmtheﬁndings.

EUROPEAN UROLOGY OPENSCIENCE27(2021)77–87

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2. Evidenceacquisition

The review followed the Preferred Reporting Items for SystematicReviewsandMeta-analyses(PRISMA)guidelines

[17,18].Aprotocolforthisreviewwasnotpublishedbefore itwasconducted.

2.1. Eligibilitycriteria

Eligible publications were those reporting on model- or trial-based health economic evaluations of a liquid-(includingurine andblood) ortissue-based testtoselect individualsforaprostatebiopsyortorisk-stratifypatients withlocalisedPCafortreatment.Thestudywasnotlimited to full economic evaluations such as cost-benefit and -effectiveness analyses, and included costing studies (ie, costperpatientasthemainoutcome)andbudgetimpact analyses(ie,population-levelcostastheoutcome). Atest was considered to inform biopsies if it informed the decision to perform prostate biopsies in PCa patients or individualswhoaresuspectedofhavingPCabasedonPSA andDRE.Thisincludedtheuseofteststoinformtheneed for biopsies for patients on AS following diagnosis of a presumedclinicallyinsignificantcancer.Atestwas consid-ered to risk-stratify patients for treatment if it informed treatmentdecisions,includingdecisionsregardingadjuvant treatment. Only full-text publications written in English wereincluded.PublicationsinvestigatingstandardPSAonly werenot eligiblefor inclusion.Studiesinvestigating PSA-basedtestsbeyondstandardPSA,suchaspercentfreePSA andPSAdensity,wereeligibleforinclusion.Other publica-tions not eligible for inclusion were those focusing on screening or metastatic disease, cost-of-illness studies, reviews, commentaries, letters, conferenceabstracts, and thoseevaluatingmanagementoptionsonly.Norestrictions regardingtheyearofpublicationwereapplied.

2.2. Searchstrategyandstudyselection

The literature search was performed on September 16, 2020 using the Ovid platform to access the EMBASE, MEDLINE, Health Technology Assessment, and National HealthServiceHealthEconomicEvaluationDatabase plat-forms.Eachdatabasewassearchedindividuallyusingfour setsoffree-texttermstoidentifypublicationson(1)PCa,(2) economic evaluations, and (3) tests, and (4) to exclude publicationsonscreeningandmetastaticPCa.Onlygeneric termswereusedtoidentifyLTBTs;nospecificbiomarkeror testnameswereusedtoavoidselectionbiasbasedonprior knowledgeofcertainbiomarkersortests.Subjectheadings wereconsideredbutwerenotincludedinthefinalsearch strategy. No exclusion criteria were enforced during the searchtoavoiderroneousexclusionofeligiblepublications. The final database-specific searches are presented in SupplementaryTables1–4.

Tworeviewers(K.D.andA.P.S.)independentlyscreened titles and abstracts of 150 publications to check for consistency, after which one reviewer (K.D.) completed thescreening.Thefulltextsofincludedpublicationswere

independentlyreviewedbythesametworeviewersforfinal inclusionor exclusion.Disagreements betweenreviewers wereresolvedviaconsensus.Publicationswereexcludedif theywerenotfull-textarticles(eg,conferenceabstract),not aboutPCa,notahealtheconomicevaluationofaLTBT,orif theyfocussedonimagingonly.Thereferencesof publica-tionsincludedwerescreenedforfurtherarticlesofinterest.

2.3. Dataextractionandsynthesis

Onereviewer(K.D.)extracteddatafromallthepublications included using a predefined data extraction template. Informationwasextractedfor yearofpublication,journal ofpublication,source(s)offunding,conflict(s)ofinterest, test(s) considered,testapplication(ie,informbiopsiesor treatment), patient population, type of health economic analysis,healthoutcomesconsidered,strategiescompared, study perspective, geographicallocation, type of analysis (ie,trial-ormodel-based),timehorizon,costindexingyear, discount rates, modelling technique, model structure, model validation efforts, sensitivity analyses performed, uncertainty analyses performed, evidence approach, evi-dence for diagnostic performance, evidence for health outcomes, evidence for impact on clinical management, evidenceonpatientpreferences,economicoutcomes,and healthoutcomes.

Intermsofdatasynthesis,journalsofpublicationwere classifiedaccordingtotheirsubjectareasasmedical,health policy,ormultidisciplinaryaccordingtotheirsubjectarea andcategory onSCImagoJournal& CountryRank (www. scimagojr.com/). Potential conflicts of interests were determined according to the (industry) funding source and whether any author had industry or consultancy affiliations.Thehealtheconomicanalyseswerecategorised as costing, budget impact, or cost-effectiveness analyses, with multiplecategoriespotentiallyapplicable per publi-cation. Comparators were classified as standard of care (SOC),includingatest,orother(eg,whenincludingimaging only). Health and economic outcomes were summarised accordingtowhethertestuseincreasedordecreasedcosts and health outcomes and, for cost-effectiveness studies, whether their use was considered cost-effective by the originalauthors.Increasesinhealthoutcomesoflessthan 0.05 quality-adjustedlife years (QALYs) were considered negligibleincreases.Althougharbitrary,thisthresholdwas selectedandusedtosynthesisetheevidenceintoaformat informativetoreaders,inotherwords,toindicatewhether thedifferencewasconsideredmeaningful.Thethresholdis not a measure of statistical significance, as significance wouldrelatetothecertaintyratherthanthemagnitudeof thedifferenceinQALYs.

2.4. Riskofbiasandqualityofevidence

Intheabsenceofanestablishedmethodforassessingbias andmethodologicalqualityinhealtheconomicstudies,the riskofbiasinpublicationsandtheappropriatenessofthe methodswasassessedaspartoftheevidencesynthesison the basis of the study methods and evidence used. The

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ConsolidatedHealthEconomicEvaluationReporting Stan-dards(CHEERS)checklistwasusedtoassessthequalityof reporting[19].AlthoughtheCHEERSchecklistwas devel-opedasachecklistratherthanaqualityscoringtool,ithas been widely used to assess the quality of reporting for health economic studies in the absence of better alter-natives.Foreach publication,weassessed whichCHEERS itemswereapplicableandwhetherthosewerereported.A scoreforthequalityofreportingofapublicationonascale from0%to100%wasdefinedastheproportionofapplicable itemsreportedcomparedtothetotalnumberofapplicable CHEERSitems.

3. Evidencesynthesis

The literaturesearch yielded1535publications, ofwhich 317wereidentifiedasduplicates(Fig.1andSupplementary Tables 1–4). Of the 1218 unique publications, 1140 were excludedonthebasisoftitleandabstract.Afterassessment

ofthefull textoftheremaining78 publications,58 were excludedforvaryingreasons,mostcommonlybecauseofan inappropriatearticleformatorbecauseitwasastudyonly evaluating multiparametric magnetic resonance imaging (mpMRI;Fig. 1).Afteraddingtwopublicationstothesample basedoncross-referencing,thefinalnumberofpublications includedfordataextractionwas22.

3.1. Characteristicsofthestudiesincluded

Fourteenstudies(64%)focusedontheuseofteststoinform biopsies[20–33],thatis,whetheraninitialorrepeatbiopsy wastobeperformed,whereaseightstudies(36%)focused ontheuseoftestsforriskstratificationtoinformtreatment decisions[34–41].Tables1and2provideanoverviewofa subset ofthedata extracted fortestsaimedatinforming biopsiesandtreatmentofPCa,respectively.Anoverviewof all the data extracted is provided in Supplementary Tables 5 and 6. An overview of the tests evaluated and their characteristicsisprovided inTable 3. Notethatone study considered a hypothetical test [32], which is not includedinthistable.

Tests weremostlyevaluatedforuseintheUSA(10/22 studies, 45%) [35,22,26–28,36–38,40,41], followed by France (n=3,14%) [23,30,31] andthen Germany[21,30], Spain[20,30],andtheUK[33,34](n=2,each,9%).Canada

[39], EnglandandWales[24], HongKong [29],Italy[30], The Netherlands [25], and Sweden [32] were each the perspective in one study. Nine studies (41%) reported industry funding [23,26,30,31,33–35,37,40]. Another six studies (27%) did not disclose any funding source

[22,25,27,28,36,38], but three of these studies included authors with industry or consultancy affiliations

[22,27,38].Elevenstudies (50%)were publishedrelatively recently, from 2017 onwards. Most publications were in medical journals (n=15, 68%) [20,21,25,27,28,30,31,33– 35,37,38,40,41],followed byhealthpolicyjournals(n=6, 27%)[22–24,32,36,39]andmultidisciplinaryjournals(n=1, 5%)[29].

3.2. Qualityofreporting

Detailed scoringof the studiesaccording to the CHEERS checklist is presented in Supplementary Table 7. On average,thestudiesincludedreported81%ofthe applica-bleitems(median80%,range64–100%).CHEERSitemsthat were not appropriately reported by 20%or more of the studies to which they were applicable included: title; settingandlocation;effectivenessmeasure;health-related quality-of-lifepopulation;currencyandconversion; char-acterisation of uncertainty; source of funding; and con-flictsofinterest.Onaverage,publicationsinhealthpolicy journalsreportedmoreCHEERSitems(87%)comparedto papers in medical and multidisciplinary journals (79%). Althoughthisfindingisconcordantwithpreviousreviews ofhealtheconomicstudies[42,43],lowercompletenessof reporting isnot necessarilyassociatedwithlower meth-odological quality. Sample included (n = 20) Final sample (n = 22) Cross-references (n = 2) Excluded (n = 58) Reasons:

- Wrong article type (n = 39) - Imaging only (n = 10) - No biomarker (n = 4) - Not economic evaluation (n = 4) - Not prostate cancer (n = 1) Fulltext

(n = 78) Title and abstract

(n = 1218) Excluded (n = 1140) Duplicates (n = 317) Search result (n = 1535) EMBASE

(n = 1033) MEDLINE(n = 437) (n = 5)HTA NHSHEED(n = 60)

Fig.1–PRISMAflowchartofthestudyselectionprocess. HTA=HealthTechnologyAssessment;NHSHEED=NationalHealth ServiceHealthEconomicEvaluationDatabase.

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Table 1– Overview of the data extracted for 14 health economic studies on liquid- or tissue-based tests to inform decisions on the need for a prostate biopsy Publication Analysis Test(s)

considered DMA Patient population Comparison category Health outcome Geographical location Evidence approacha Diagnostic performance evidence Impact of test(s) on costs Impact of test(s) on health outcome Cost-effectiveness judgementc Bermudez-Tamayo et al, 2007[20]

CEA pfPSA Initial Bx Low risk Test vs SOC CCs detected,

prognostic utility, actual cases

Spain MBSS with

observational cost data

Literature Decrease Decrease Cost-effective

Schiffer et al, 2012[21]

CA UPA-PC Initial Bx Low risk or

higher

Test vs SOC NA Germany MBSS Observational

validation study

Decrease NA NA

Aubry et al, 2013[22]b

BIA ConﬁrmMDx Repeat Bx Repeat Bx

candidate

Test vs SOC NA USA MBSS Observational

validation study

Decrease NA NA

Malavaud et al, 2013[23]

BIA PCA3 Score Repeat Bx Repeat Bx candidate

Test vs SOC NA France Chart review with

simulated test results Decrease NA NA Nicholson et al, 2015[24] CEA PCA3 Score, PHI Repeat Bx Repeat Bx candidate Test vs SOC vs other QALYs England and Wales MBSS with modelled impact Observational validation studies Increase Negligible increase Not cost-effective Dijkstra et al, 2017[25]

CEA SelectMDx Initial Bx Low risk or higher

Test vs SOC QALYs Netherlands MBSS Observational

validation study Decrease Negligible increase Dominant Sanda et al, 2017[26] CA T2:ERG, PCA3 Score

Initial Bx Low risk or higher Test vs SOC vs other NA USA MBSS Observational validation study Decrease NA NA Voigt et al, 2017[27]b

BIA 4Kscore Initial Bx Low risk or higher

Test vs SOC NA USA Observational

study with modelled impact Decrease NA NA Sathianathen et al, 2018 [28]

CEA PHI, 4Kscore, SelectMDx, EPI

Initial Bx Low risk or higher

Test vs SOC QALYs USA MBSS Observational

validation studies Decrease Negligible increase Cost-effective Boutell et al, 2019[29]

CEA PHI Initial Bx Low risk Test vs SOC CCs missed,

unnecessary Bx

Hong Kong MBSS Observational

validation study Decrease Increase in CCs missed, decrease in unnecessary Bx Inconclusive Govers et al, 2019[30]

CEA SelectMDx Initial Bx Bx candidate Test vs SOC QALYs France,

Germany, Italy, Spain MBSS Observational validation study Decrease Negligible increase Dominant Mathieu et al, 2019[31]

CA PHI Initial Bx Low risk Test vs SOC NA France Observational

study with MBSS Observational validation study Increase NA NA Fridhammer et al, 2020 [32]

CEA Hypothetical Initial Bx Low risk Test vs SOC QALYs Sweden MBSS Assumption Decrease

(PSA 3.0–9.9 or 2.0–9.9 ng/ml) Increase (PSA 2.0–2.9 ng/ml) Decrease (PSA 3.0–9.9 ng/ml) Increase (PSA 2.0–2.9 or 2.0– 9.9 ng/ml) Cost-effective Kim et al, 2020[33]

CA PSAd, PHI Initial Bx Bx candidate Test vs other NA UK Observational

study with modelled impact

Observational validation study

Decrease NA NA

BIA = budget-impact analysis; CA = cost analysis; CEA = cost-effectiveness analysis; DMA = decision-making aim; Bx = biopsy; NA = not applicable; PSA = prostate-speciﬁc antigen; pfPSA = percent free PSA; UPA-P = urinary proteome analysis for prostate cancer; PHI = Prostate Health Index; EPI = ExoDx Prostate Intelli-Score; PSAd = PSA density; SOC = standard of care; mpMRI = multiparametric magnetic resonance imaging; CCs = cancer cases; QALYs = quality-adjusted life years; MBSS = modelling based on sensitivity and speciﬁcity; DT = decision tree; STM = state-transition model; DES = discrete event simulation.

a

Impact here refers to both health and economic outcomes for CEAs and economic outcomes for CAs or BIAs.

b

Obtained via cross-referencing.

c_{A dominant strategy improves health outcomes at lower costs, so it is better in terms of health and economic outcomes, whereas a cost-effective strategy improves health outcomes at higher costs, but the increase in costs}

is considered proportionate to the improvement in health, so the improvement in health is worth the increase in costs.

E U R O P E A N U R O L O G Y O P E N S C I E N C E 2 7 ( 2 0 2 1 ) 7 7 – 8 7 81

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Table 2– Overview of data extracted data for eight health economic studies on liquid- or tissue-based tests to facilitate treatment decisions for localised prostate cancer

Publication Analysis Test(s)

considered DMA Patient population Comparison category Health outcome Geographical location

Evidence approacha _Diagnostic

performance evidence Impact of test(s) on costs Impact of test(s) on health outcome Cost-effectiveness judgmentb

Calvert et al, 2003[34] CEA DNA-Ploidy Initial TS Localised NOS

Test vs other QALYs UK Modelling based on

sensitivity and speciﬁcity

Assumption Increase Increase Cost-effective

Zubek and Konski, 2009[35]

CEA ProstatePx Adjuvant TS Received RP Test vs SOC QALYs USA OBS with modelled

impact

NA Increase Increase Cost-effective

Reed et al, 2014[36] CEA NADiA ProsVue Slope

Adjuvant TS IR and HR of recurrence

Test vs SOC QALYs USA Retrospective study

with modelled impact

NA Increase Negligible

increase

Not cost-effective

Roth et al, 2015[37] CEA ProMark Initial TS LR and IR of recurrence

Test vs SOC QALYs USA OBS with modelled

impact Observational validation study Decrease Negligible increase Dominant Albala et al, 2016[38] CA OncotypeDX Initial TS Favourable IR

or LR

Test vs SOC NA USA OBS with historical

cohort NA Decrease (LR) Increase (IR) NA NA Health Quality Ontario, 2017[39]

BIA Prolaris Initial TS LR and IR Test vs SOC NA Canada OBS NA Increase NA NA

Lobo et al, 2017[40] CEA Decipher Adjuvant TS Received RP Test vs SOC vs other

QALYs USA OBS with clinical

vignette study

Chang et al, 2019[41] CEA OncotypeDX Initial TS Favourable IR or LR

Test vs SOC QALYs USA OBS with historical

cohort

BIA = budget-impact analysis; CA = cost analysis; CEA = cost-effectiveness analysis; DMA = decision-making analysis; TS = treatment strategy; NA = not applicable; NOS = not otherwise speciﬁed; RP = radical prostatectomy; HR = high risk; IR = intermediate risk; LR = low risk; SOC = standard of care; QALYs = quality-adjusted life years; OBS = observational study; DT: decision tree, STM: state-transition model.

a

Impact here refers to both health and economic outcomes for CEAs and economic outcomes for CAs or BIAs.

b

A dominant strategy improves health outcomes at lower costs, so it is better in terms of health and economic outcomes, whereas a cost-effective strategy improves health outcomes at increased costs, but the increase in costs is considered proportionate to the improvement in health, so the improvement in health is worth the increase in costs.

E U R O P E A N U R O L O G Y O P E N S C I E N C E 2 7 ( 2 0 2 1 ) 7 7 – 8 7 82

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3.3. LTBTstoinformtheneedforprostatebiopsies

Ofthe 14 studies focusingon theuse ofteststo provide informationontheneedforabiopsy,11(79%)focusedon theneedforaninitialbiopsy[20,21,25–33]andthree(21%) on the need for a repeat biopsy afteran initial negative tissuebiopsy[22–24].Thirteenstudies(93%)comparedthe useofatesttoSOC,oneofwhichalsoincludedastrategy withoutbiopsies[26]andanotheradditionallyinvestigated thecombinationoftests[24].Onestudycomparedseveral strategiesincludingtestsandimaging[33].

Most studies were cost-effectiveness analyses (n=7, 50%)[20,24,25,28–30,32],followedbycostanalyses(n=4, 29%)[21,26,31,33]andbudgetimpactanalyses(n=3,21%)

[22,23,27]. Five of the cost-effectiveness analyses used QALYs as the effectiveness outcome, which is the gold-standardeffectivenessoutcome inhealtheconomicsasit allowsforcomparisonacrossdiseases.Twelveof14studies adoptedahealthcarepayerperspective.Ninestudies(64%) considereda time horizon of 3yr or shorter. All studies were model-based, with decision tree analysis the tech-nique most frequently used (n=7, 50%). Six studies considered treatments in their model structure [25– 28,30,32]. No study presented model validation efforts. Three studies (21%) performed uncertainty analyses

[24,28,32].

Elevenoutof14 studies(79%)modelledtestoutcomes and subsequent management decisions based on the sensitivityandspecificityofthetestsandlinkedthosetest outcomestohealthandeconomicoutcomes,whereastwo

studiesusedobservationaldataondiagnosispatternsand linkedthosetohealthandeconomicoutcomes[27,33].One studyperformedachartreviewforwhichtestresultswere simulatedtoestimatehowmanybiopsiescouldhavebeen avoided[23].Forthe12studies thatusedsensitivityand specificity, ten derived the diagnostic performance from observational studies [21,22,24–26,28–31,33] and single studies derived this from literature [20] or made an assumption becausetheyinvestigated ahypotheticaltest

[32].Ofthesevencost-effectivenessanalyses,effectiveness outcomes were modelled based on literature in six

[20,24,25,28,30,32] and based on observational data in one study[29], although for thatstudy theeffectiveness outcomewasnotQALYsbutthenumberofmissedcancer casesandunnecessarybiopsies.Allstudiesassumedperfect compliance with the test recommendations, that is, clinician or patient preferences and practice variations werenotconsidered.

Elevenoutof13studies(85%)foundtheuseofteststobe cost-saving [20–23,25–30,33], ofwhichthose performing cost-effectiveness analyses found the use of tests cost-effective or dominant, that is, preferable in terms of effectiveness and costs. Two of these 13 studies (15%) foundthattheuseoftestswouldincreasecosts[24,31].One ofthesewastheonlyofficialhealthtechnologyassessment report, concluding that the use of two tests (evaluated separately) was not cost-effective [24]. The study that evaluatedahypotheticaltestfordifferentsubgroupsfound mixedresults,butoverallconcludedthatuseofatestwould becost-effective[32].

Table3–Overviewoftheliquid-andtissue-basedbiomarkertestsevaluatedinthehealtheconomicstudiesincludedinthereview

Testname Sampletype Biomarker(s) DMA Studies,n(%) References

ProstateHealthIndex Blood TotalPSA,freePSA,proPSA Biopsy 5(23) [24,28,29,31,33]

PCA3Score/PROGENSA Urine RelativelevelsofPCA3andKLK3RNA Biopsy 3(14) [23,24,26]

SelectMDx Urine DLX1,HOXC6andKLK3mRNA(thistestalsoconsiders clinicalvariables)

Biopsy 3(14) [25,28,30]

4Kscore Blood TotalPSA,freePSA,intactPSA,andhumanglandular kallikrein2

Biopsy 2(9) [27,28]

OncotypeDx Tissue mRNAlevelsof12cancer-relatedgenes(and5reference genes)involvedinstromalresponse,androgensignalling, cellularorganisation,andproliferation

Treatment 2(9) [38,41]

ConﬁrmMDx Tissue MethylatedGSTP1,APC,andRASSF1 Biopsy 1(5) [22]

Decipher Tissue mRNAlevelsof22genesinvolvedincelldifferentiation, proliferation,adhesion,motility,structure,cell-cycle progression,mitosis,immunemodulation,andother unknownfunction

Treatment 1(5) [40]

DNA-Ploidy Tissue AmountofDNAinthenucleiofprostatecancercells Treatment 1(5) [34]

ExoDxProstateIntelli-Score Urine ExosomalRNAforPCA3,SPDEF,andERG Biopsy 1(5) [28]

NADiAProsVueSlope Blood SupersensitivePSAkinetics Treatment 1(5) [36]

PercentfreePSA Blood FreePSA,totalPSA Biopsy 1(5) [20]

Prolaris Tissue mRNAlevelsof31cell-cycleprogressiongenesand15 controlgenes

Treatment 1(5) [39]

ProMark Tissue Relativeexpressionof8proteins(CUL2,DERL1,FUS, HSPA9,PDSS2,SMAD4,S6(P),andYBX1)

Treatment 1(5) [37]

ProstatePx Tissue Morphometricandantigenexpressionproﬁleofprostate cancercells

Treatment 1(5) [35]

PSAdensity Blood TotalPSA,prostatevolume Biopsy 1(5) [33]

T2:ERG Urine RelativelevelsofTMPRSS2:ERGandKLK3mRNA Biopsy 1(5) [26]

Urinaryproteomeanalysis Urine 12urinarypeptides,totalPSA,freePSA Biopsy 1(5) [21]

DMA=decision-makingaim;PSA=prostate-speciﬁcantigen.

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3.4. LTBTstoinformtreatmentdecisionsforconfirmedPCa

Oftheeightstudiesontheuseofteststoinformtreatment decisions,five(63%)focusedontheinitialtreatmentafter diagnosis[34,37–39,41]andthree(38%)on postprostatect-omy adjuvant treatment [35,36,40]. Four studies (50%) focusedon a low-andintermediate-riskpopulation [37– 39,41]andonestudyfocusedonanintermediate-and high-riskcohort[36],whereasothersdefinedthepopulationof interest as having undergone prostatectomy (n=2, 25%)

[35,40]orhavinglocaliseddisease(n=1,13%)[34].Seven studies(88%)comparedtheuseofatesttoSOC[35–41],one ofwhichalsoincludedastrategyinwhichallpatientswould receive adjuvant treatment [40]. One study compared a test-informed strategy to strategies inwhich allpatients would either enrol in a surveillance strategy or undergo prostatectomyintheinitialtreatmentphase[34].

Sixoftheeightstudieswerecost-effectivenessanalyses (75%)[34–37,40,41]andsinglestudiespresentedabudget impact[39]orcostinganalysis[38].Allcost-effectiveness analyseswereperformedusingQALYsastheeffectiveness outcome.Allstudiesadoptedahealthcarepayer perspec-tive.Singlestudiesconsideredatimehorizonof180d[38]

or5yr[39], whereas allotherstudies consideredatime horizonof10yrormore[34–37,40,41].Sevenoftheeight studies (88%) were model-based, with state-transition modelling the technique most frequently used (n=6, 86%) [34–37,40,41]. All state-transition models were structuredaccordingtohealthstates,whereasthestructure of the decision tree was mainly definedby the different treatmentoptions.Threeofthesevenmodel-basedanalyses (43%)presentedexternalvalidationforspecificpartsofthe model[36,37,41].Fouroftheeightstudies(50%)performed somesortofuncertaintyanalysis[35,35,36,37,40].

Sevenoftheeight studies(88%) mainlyused observa-tional data to link health and economic outcomes to observedtreatmentdecisionsbasedontestresults[35–41], whereas one study (13%) modelled test outcomes and subsequent treatment decisions based on the sensitivity and specificity of the test [34]. Of the studies using observationaldata,oneusedhistoricaldataforthecontrol strategy[38].Allsixcost-effectivenessanalysesmodelled effectivenessoutcomesbasedontheliterature.Twostudies (25%)assumedperfectcompliancewithtest recommenda-tions[34,35], thatis,clinicianorpatientpreferencesasa sourceofpracticevariationwerenotconsidered,whichis notexpectedtoberealistic.Theotherstudiesaccountedfor variation in following test recommendations in the real world, but to varying extents: five modelled treatment patternsasfoundintheobservationaldataused[36–39,41]

andoneusedaclinicalvignettestudyinwhichparticipants stated what their choice would be in varying scenarios

[40]. No study explicitly considered patient preferences regarding treatment options, but the observational data used infour studies do include this real-world variation

[37,37,38,39,41].

Sixof theeight studies (75%)found thatuseof atest wouldincrease thetotalcostsofcare[34–36,39–41],one study(13%)foundadecreaseincosts[37],andone study

foundcostsavingsforalow-riskcohortbutanincreasein costs for an intermediate-risk population [38]. All cost-effectivenessanalysesfoundthatLTBTuseresultsinbetter healthoutcomes,althoughthisincreasewasconsideredto be relatively small in magnitude for two studies by the reviewers[36,37].Fiveofthesixcost-effectivenessanalyses found that use of tests was cost-effective or dominant

[34,35,37,40,41],whereasonestudyfoundthattestusewas notcost-effective[36].

3.5. Discussion

We systematically reviewed 22 health economic studies evaluating17differentmoleculartestsaimedatinforming the needfora (repeat)biopsyor treatmentdecisions for localisedPCa.Overall,thesestudiessuggestthatLTBTuseto informtheneedforprostatebiopsiesandthetreatmentof PCa can be either cost-saving or -effective. In particular, tests aimedatinforming biopsydecisions were foundto resultincostsavingsbecauseofalowernumberofprostate tissue biopsies performed.LTBT useto informtreatment decisions couldpotentially becost-effective,that is,they improvehealthoutcomesatanacceptableincreaseincost, according to the authors. The encouraging results from thesestudies,however,donotalignwiththecurrentuptake oftestsinclinicalguidelinesorroutinepracticeoutsidethe USA.Thisdiscordanceislikelytobecausedbytheabsence of prospective interventional clinical studies on which healtheconomicevaluationsshouldbebased.Inaddition, ourreviewidentifiedmethodologicalchallengesexplaining why thecurrent studiesprovideinsufficientevidence for health care decision-makers to justify the incremental costs. These mainlyrelate to theshorttime horizons for whichoutcomesareevaluated,includinghowuseofthese testswillimpactclinicalmanagementinsubsequentstages ofthedisease,andseveralstructuralmodelassumptions.

ThestudiesthatevaluatedLTBTusetoinformtheneed forinvasivetissuebiopsieshadaparticularlynarrowfocus in terms of downstream health outcomes and costs. For example, most ofthese studies adopted short-termtime horizons and ignored the impact of false-negative test results or accounted for it in a limited way.The clinical utilityofLTBTsinchangingmanagementwasnot consid-ered in these studies at all and only indirectly in some studies focusingon PCatreatment.Ignoringtheseaspects mayresultsincost-effectivenessestimatesthatarebiased infavouroftests,asapreviousmodellingstudyinadvanced PCa demonstrated thatcompliance withtest resultsmay have a substantial impact on health economic outcomes

[44].AlthoughstudiesfocusingontreatmentofPCaoverall moreextensivelyaccountedfordownstreamconsequences, thenumberofstudieswaslowandtheyfocusedonspecific tests,leavingtheoveralljudgementonthe cost-effective-nessoftestsinthiscontextuncertain.

Giventhelackofprospectivecomparativeevidence,the studies reviewed can be considered early-stage health economicevaluationsthatareneitherdesignednorsuitable for providing definitive evidence for reimbursement. Nevertheless, these early economic models can inform

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furthertranslationof testsandtreatmentsbyprioritising additional clinical studies [45]. Despite beingearly-stage evaluations,overallthestudiesappraisedprovided insuffi-cient justificationof the evidence, model structures, and techniquesused.Thisisinlinewithotherreviewsofhealth economic studies in oncology [43,46]. Willis et al [47]

reviewedfivefulleconomicevaluationsofmpMRIforthe diagnosisprostatecancerandfoundsubstantial heteroge-neity in the questions posed, pathways modelled, and assumptionsmade.Theyconcludedthatthereisaneedfora betterstandardofreportingaroundkeymodelling assump-tionsandawiderrangeofsensitivityanalysestoexplorethe impactofstructuralassumptionsandtoreflectuncertainty arounddatainputsforthemodelparameters.Wesuggest thattransparentreportingmaybeevenmoreimportantfor early-stage analyses specifically, as these often require a largernumberandintensityofassumptionsbasedonmore limited evidence. Previous studies have additionally dis-cussedadeficiencyofpoliciesforhealtheconomicanalyses, aswell as a lack of reviewerswith knowledge of health economics, urging journals to provide authors and reviewers with guidance on cost-effectiveness studies

[42]. Given that the vastmajority of studies included in thisreview were published in medical journalsand that reportingqualitywasfoundtobelowerinthosejournals comparedtohealthpolicyjournalsaccordingtotheCHEERS checklist, this may have contributed to the lack of justificationidentified.

Despite the overall positive findings, the issues highlightedabovesuggestthathealtheconomicestimates may be overoptimistic and that, consequently, the cost-effectiveness of test-informed management of PCa is promisingbut warrantsadditional researchthrough pro-spectiveinterventionalstudies.Theobservationthatthree outofeightstudies withoutindustryinvolvementhadan overallnegativeconclusion(38%)comparedtoonlyoneout of 14 studies with clear industry involvement (7%) may furtheraddtoscepticismaboutthestrengthofthecurrently availablehealtheconomicevidence.Thisalsohighlightsthe needforinvestigator-initiatedclinicalstudiestostrengthen theevidencebaseforlong-termhealthoutcomes.Although controlled interventional studies are as necessary for biomarkersastheyareforpharmaceuticalsfromahealth economic perspective, consideration should be given to appropriate regulatory protection to ensure investments areprotectedfollowingpositivestudyresults.

Toadvancethetranslationoftestsonthebasisofhealth economic evidence, future studies should be aware of severalopportunities,mostofwhichrelatetothe percep-tionthattestsshouldnotbeconsideredinisolationbutas part of the broader clinical pathway. First, economic evaluations should be consideredfrom an early stage in the development process to collect as much relevant informationalongtheway,whichcouldreducethenumber ofassumptionsthatneedtobemadeinthehealtheconomic evaluation.Second,studiesfocusingontheuseoftestsin thediagnosticprocessshouldcollectdataonhowthetest willbeusedinpractice,oratleastexploretheimpact of compliance to test results in sensitivity analyses, and

realisticallyaccountfordownstreamconsequencesof false-negative test results. Third, studies focusing on the managementofPCashouldatleastaimtocollectdata on theimpactonactualdecisionsmadeandconsequent long-termhealththroughobservational studies.Fourth, uncer-taintyinoutcomesshouldbeexploredandreportedmore transparentlyintermsofbothmodelparametersandmodel assumptionsandstructure,ratherthanjustintermsof one-way sensitivity analysis of selected parameters. Finally, studiesshoulduseexistingreportingchecklists,suchasthe CHEERS checklist [19], to improve reporting on health economicevaluations.

Furtherresearch couldalsoinvestigatethepotentialof LTBTsto identifyasymptomaticmetastaticdisease during thediagnostic process.Suchearly detectioncouldleadto downstagingand,hence,betterlong-termhealthoutcomes. This review has certain limitations. Its findings are subjecttopublicationbias,asnotallstudiesmayhavebeen published,especiallystudieswithnegativefindings regard-ing thecost-effectivenessoftests.Theriskofpublication biasishighlightedbythesubstantialnumberofconference abstractsthatwereexcludedduringfull-textscreening,as full-textpublicationsmaynothavebeenpursuedforstudies withnegativefindings.TheCHEERSchecklistwasusedto appraisethereportingqualityofpublicationsintheabsence ofabetteralternative,butthischecklistwasnotdesignedto scorepublicationsandusingittodosomaybeconsidered subjective. In terms of data extraction, the lack of clear reportingandjustificationofmethods,modelling assump-tions, and analyses performed might have resulted in categorisationsthatreadersortheauthorsoftheoriginal papers might not fully agree with. Finally, some studies presentedarangeofanalyses thathadtobesummarised intoasinglecost-effectivenessjudgementatthediscretion ofthereviewers.

4. Conclusions

This review found that most health economic studies concludedthatLTBTscanbecost-savingor-effectivewhen usedtoselectindividualsforprostatebiopsiesortoinform decisions on the treatment of confirmed localised PCa throughriskstratification.Thesefindings warrantfurther research through prospective interventional studies to providerobustdataonclinicalutilityandlong-termhealth outcomes that will beessential to strengthen thehealth economicevidencebase.Suchinformationwillbecrucialto optimisereimbursementofthemostcost-effectivetestsby public health care systems so that outcomes can be improvedforthebroaderpopulation.

Authorcontributions:KoenDegelinghadfullaccesstoallthedatainthe

study andtakes responsibilityforthe integrity ofthe dataand the

accuracyofthedataanalysis.

Studyconceptanddesign:IJzerman.

Acquisitionofdata:Degeling,Pereira-Salgado.

Analysisandinterpretationofdata:Degeling,Pereira-Salgado,Corcoran,

Boutros,Kuhn,IJzerman.

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Draftingofthemanuscript:Degeling.

Critical revision of the manuscript for important intellectual content:

Pereira-Salgado,Corcoran,Boutros,Kuhn,IJzerman.

Statisticalanalysis:Degeling.

Obtainingfunding:Corcoran,IJzerman.

Administrative,technical,ormaterialsupport:None.

Supervision:IJzerman.

Other:None.

Financial disclosures: Koen Degeling certi_ﬁes that all con_ﬂicts of

interest, including speciﬁc ﬁnancial interests and relationships and

afﬁliationsrelevanttothesubjectmatterormaterialsdiscussedinthe

manuscript(eg,employment/afﬁliation,grantsorfunding,

consultan-cies,honoraria,stockownershiporoptions,experttestimony,royalties,

orpatents_ﬁled,received,orpending),arethe following:Maarten J.

IJzermanhasreceivedresearchsupportfromIlluminaInc.forprojects

relatedtowhole-genomesequencingandliquidbiopsies.PaulC.Boutros

sitsonscientiﬁcadvisoryboardsfor BioSymetrics Inc.andIntersect

Diagnostics Inc.Peter Kuhn is a royalty recipient, shareholder, and

advisorofEpicSciences.Theremainingauthorshavenothingtodisclose.

Funding/Supportandroleofthesponsor:Thisworkwaspartofthe

PRECEPT programfunded by the Prostate Cancer ResearchAlliance,

whichisajointinitiativebetweentheMovemberFoundationandthe

AustralianGovernment.PeterKuhnissupportedbyNCICancerCenter

supportgrantP30CA014089.

Acknowledgments:TheauthorswouldliketoacknowledgeMs.JuliaS.

Hofkesforhercontributiontoaninitialversionofthisreview.

Datasharing statement:Alldatageneratedoranalysedduring this

study are includedin this published articleand its supplementary

information_ﬁles.

AppendixA. Supplementarydata

Supplementary material related to this article can be found,intheonlineversion,atdoi:https://doi.org/10.1016/j. euros.2021.03.002.

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