Confidential: For Review Only

Much more medicine: Why big data means more

overdiagnosis

Journal: BMJ

Manuscript ID BMJ.2018.045709

Article Type: Analysis

BMJ Journal: BMJ

Date Submitted by the Author: 27-Jun-2018

Complete List of Authors: Vogt, Henrik; Norwegian University of Science and Technology, General Practice Research Unit, Department of Public Health and Nursing Green, Sara; University of Copenhagen, Section for History and Philosophy of Science, Department of Science Education; University of Copenhagen, Center for Medical Science and Technology Studies, Department of Public

Health Ekstrøm, Claus; University of Copenhagen, Biostatistics, Department of Public Health Brodersen, John; University of Copenhagen, Centre of Research & Education in General Practice Primary Health Care Research Unit, Zealand Region

Keywords: Precision medicine, Overdiagnosis, Big data, Personalised medicine, High definition medicine, Screening

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Confidential: For Review OnlyMuchmoremedicine:Whybigdata

screeningmeansmoreoverdiagnosis

Precisionmedicinebasedonanalysisofbigdatapromisesto

revolutionizediseasepreventionamongapparentlyhealthypeople.In

practice,itentailsanewformofmassivescreeningthatislikelyto

seriouslyaggravateoverdiagnosis,argueHenrikVogt,SaraGreen,

ClausEkstrøm,andJohnBrodersen.

Anewvisionforthefutureofmedicineiscurrentlyemerging,basedonthe

applicationofmachinelearningandothercomputationaltoolstogenomicsand

otherbigdataofunprecedentedvolumeandvariety(1).Thisvisionisvariously

calledprecisionmedicine,personalisedmedicine,highdefinitionmedicine,

quantifiedself,systemsmedicine,andP4medicine(predictive,preventive,

personalisedandparticipatory)(2-5).

Precisionmedicinebasedonbigdatacanbefocusedonclinicallymanifest

disease.However-asreflectedintheUSPrecisionMedicineInitiativeandthe

plannedAllofUsresearchprogram(6)-oneofitsmainpromisesisarevolution

indiseasepreventionintheapparentlywell(2).“Personalisation”or“precision”

inthiscontextmeansusingbig-datamethodstoaccountforvariationamong

individualsbystratifyingthemintonarrowsubgroupswithsimilarrisksand

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Confidential: For Review Onlytreatmentpotentials.Thisisproposedtoyieldnovelbiomarkers,hyper-

predictiveriskalgorithmsandearlierdetectionofdisease(2,3).

Theemergenceofthisnewdata-intensivepreventivemedicinecoincideswith

increasingawarenessofthedownsidesof“toomuchmedicine”(7-11).Wehere

showhowitislikelytoseriouslyaggravateoverdiagnosis.

Aneweraofscreening

Screeningistheearlydetectionofriskfactorsorasymptomaticpathological

conditionsinordertopreventmorbidityanddeath.

Whereastraditionalmedicalscreeningtypicallyinvolvesoneorafewvariables

testedatalimitedsetoftime-pointsonaselectgroupofindividuals,thevisionof

bigdataentailsanewformofscreeningofunprecedentedscope.Wecallthis

screening2.0.Toreflectthemulti-factorialnatureofdisease,testingwillherebe

bothmulti-level(fromthemoleculartothesocial),multi-dimensional(many

variables),highlydetailed(highresolution),andlongitudinal(showingdynamic

bodilychangesovertime)(4).Thesourcesofdatawillincludemolecular“omics”

technologies(e.g.,genomesequencing,proteomics,transcriptomics,

metabolomics),biobanks,healthregisters,electronichealthrecordsandimaging

technologies.Socialmediaandnewbiosensorscoupledtowearableelectronics

andsmart-phonesenablemonitoringofvariousbodilyprocessesand

behaviours.Theresultisthegatheringofdynamicdatacloudswithbillionsof

datapointsforeachindividualgearedtowardstheearliestpossibledetectionof

disease(2).

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Confidential: For Review Only

Aneweraofoverdiagnosis

Suchastrategyislikelytoincreaseoverdiagnosis.Earlydetectionofdiseasecan

bebeneficial,butonlywhenasymptomaticabnormalities(ariskfactoror

pathology),progresstoclinicallymanifestdisease(symptomsordeath).

Overdiagnosisoccursbecausebiologicalabnormalitiesoftendonotresultin

suchoutcomes.Overdiagnosishastworelatedcauses:overdetectionand

overdefinition(12).

Overdetection-unlikefalse-positivetests-isthedetectionofasymptomatic

conditionsthatdomeetcurrentlyagreedcriteriaforpathology,butwhichare

notdestinedtobecomeclinicallymanifestdisease(13).Itoccurswhen

abnormalitieseitherdisappearspontaneouslyorprogresssoslowlythatthe

persondiesfromothercausesbeforetheycausesymptoms.Overdefinitionstems

fromtheloweringofdiagnosticthresholdsorexpansionofdiseasedefinitionsto

includemoreconditionsthatareunlikelytocausesymptomsordeath.

Overdiagnosisisaproblembecausethoseoverdiagnosedaresubjecttowaste

andharm,butnobenefit,andbecauseitleadstoadditionaldiagnosticsand

overtreatment,withadditionalcostsandsideeffects(12).Weillustratethe

relationbetweenoverdiagnosisandscreeninginFigures1and2.

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Figure1:Thisfigureillustratesoutcomesofscreeninginapopulation,includingoverdiagnosis.AtstepAwehaveapopulationofapparentlyhealthy(asymptomatic)people.Wehereassume

thateveryoneinthispopulationisgoingtobescreened.Thispopulationisdividedintotwothroughamedicaldefinitionalprocess:Group1consistsofthosewho,accordingtocurrentmedicalconvention,donothavetheasymptomaticabnormality.Group2consistsofthosewhodo.DefiningmorepeopleintoGroup2,andscreeningthemall,funnelmorepeopletowardsoverdiagnosis(instepC).

AtstepBthereisscreeningfortheearlydetectionoftheasymptomaticabnormality.Thistestingsplitsthetwogroupsintofourtrajectories(green,orange,brownandyellow). Thegreenandorangetrajectoriesdependonthespecificityofthetest,theabilitytoruleoutthosewhodonothavetheasymptomaticabnormality.Thegreentrajectoryrepresentstruenegativesandtheorangerepresentsfalsepositivetests. Thebrownandyellowtrajectoriesaredefinedbythesensitivity,i.e.,theabilityofthetesttoidentifythoseindividualswhodohaveanasymptomaticabnormality.Inthebrowntrajectory,peopleareincorrectlydefinedashavingnoasymptomaticabnormalityduetoimperfectsensitivity(e.g.1%ofGroup2ifthesensitivityis99%).Aftertimeandfurtherobservation(stepC),peopleinthisgroupareeithershowntogetclinicallymanifestdiseasewhichwasmissedbythescreening(purpletrajectory)ortheundiscoveredabnormalityneverbecomesclinicallymanifest(pinktrajectory). Totrackoverdiagnosis,followtheyellowtrajectory.ItshowspeoplewhodoharbourasymptomaticabnormalitiesandarealsocapturedbythescreeningatstepB.Muchmorepeoplearefunnelledintothistrajectoryandtowardsoverdiagnosiswiththehigh-resolutionscreeningofbigdatawhich“detectseverything”(e.g.99%ofGroup2ifthesensitivityis99%).Aftertimeandfurtherobservation(stepC),theyellowtrajectorysplitsintotwo:Inthebluetrajectory,wefindpeoplewhoweredestinedtodevelopclinicallymanifestdisease.Thesearethepeoplewhopotentiallycangainfromearlydiagnosis(ifthereistreatment).However,intheredtrajectorywefindpeoplewhoarediagnosedwithanasymptomaticabnormality,butwhoarenotdestinedtogetclinicallymanifestdisease.Thisgroupisoverdiagnosed. Inordertoavoidatsunamiofoverdiagnosis,itiscrucialforprecisionmedicinetopredictpreciselywhichasymptomaticabnormalitieswillactuallybecomeclinicallymanifestdisease(illustratedbystepD).SuchpredictionsmusttheninformthedefinitionalprocessinstepAofwhatshouldberegardedasasymptomaticabnormalitiestobescreenedfor.Onlyinthiswaymaylowriskindividualsbe“undiagnosed”andoverdiagnosisavoided.

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Figure2Thisfigureshowsthevariationinthenaturalhistoryofasymptomaticabnormalitiesthatarescreenedforanditsrelationforoverdiagnosis.Italsoillustrateshowbigdatamedicine,likeafine-maskedsievewithextremegranularityandsensitivity,willbeabletodetectmorefiner-grainedabnormalitiesatanearlierstageofdiseasedevelopment(redline).Astheseabnormalitiesarelesslikelytobecomeclinicallymanifestdisease,thisincreasestheriskofoverdiagnosis.Adaptedfrom(13).

Thestepstowardsoverdiagnosis

Whatcanweexpectfrombigdatascreeningwithregardtooverdiagnosis?As

examples,considerthePioneer100studyandbiotechnologistCraigVenter's

PrecisionScreeningstudythatrecentlyspearheadedpreventiveprecision

medicine(14,15).Intheformer,alargenumberofvariableswererepeatedly

measuredover9monthsin108apparentlyhealthyindividualscreatinghuge,

dynamicdatacloudsofallindividuals.Theupshotwasthatmultiple

abnormalitiesweredetectedinallpreviouslywellparticipants.Similarly,

Venter'steamdetectedriskfactorsanddiseasesignsinalargeproportionofthe

population(15).Ratherthanrepresentingprecisionmedicine,such“wall-to-

wall”diagnosislikelyreflectsimprecisionandoverdetection.Whyisthis?

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Confidential: For Review OnlyAsillustratedinFigure1andanonlineinteractiveapplication1,the

proportionofpeopleoverdiagnosedinapopulationdependson:

• theproportionthatharbourconditionsthatthemedicalcommunitythinks

shouldbedefinedasasymptomaticabnormalitiesthatshouldbescreenedfor

anddiagnosedearly(atstepAinFigure1).Thisisinessenceadefinitional

process,whichisaffectedbyafocusonlowriskindividualsandthesettingof

lowdiagnosticthresholds(overdefinition).Thisdefinitionalprocessshouldbe

informedbylongitudinalstudiesandpredictionsofwhowillactuallygoonto

developclinicallymanifestdisease.

• theproportionofthosewithsuchanabnormalitythatisscreened(atstepB

inFigure1).

• thesensitivityofscreeningtests,i.e.abilitytopickupasymptomatic

abnormalities(atstepBinFigure1).

• theproportionofthosewhoaredefinedasharbouringanasymptomatic

abnormalitywhowillnotgoontodevelopclinicallymanifestdisease(seethe

redtrajectory,Figure1).

Below,wefirstconsidertheeffectsofscreening2.0onthesecondandthirdof

thesepointsandthenthefirstandfourth.

1https://ekstroem.shinyapps.io/estimating_over-diagnosis/

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Confidential: For Review OnlyThescreeningof“everyone”

Screening2.0willshiftmedicinefromasituationinwhichapparentlyhealthy

peoplearetestedonlytoalimitedextent,tooneinwhichtheaimisto

continuouslymonitorasmanypeopleaspossible,preferablyeveryone.

Increasedtestinginprecisionmedicineisdrivenbyaneedfordataonasmany

peopleaspossible,tocaptureallbiologicalvariationandstratifythepopulation,

andbyavailabilityofcheaperandmoreubiquitousself-monitoringtechnologies.

Thelatterenablepeopletoscreenthemselves,withoutmucheffort,andallowfor

continuousdatacollectionthroughmonitoringthatisminimallynoticeable.

Thedetectionof“everything”

Crucially,duetotheextremegranularityandcontinuousperformanceofthe

testing,thesensitivityofscreening2.0inpickingupwhateverisdefinedas

asymptomaticabnormalitieswillbecomeveryhigh.AsillustratedinFigures1

and2,thispromotesoverdiagnosis.Theexplicitaimofbigdataprecision

medicineis,asoneofitsadvocatesEricTopolhasputit,toturneveryoneinto

“highresolutionindividuals”(4).Theoretically,ifscreening2.0succeedsinits

goalofregistering“everything”abouteachbody,“everything”thatmedicine

definesasanasymptomaticabnormalitywillbedetected.

Concerning,thefourthpointabove-theproportionofthosewhoaredefinedas

harbouringanasymptomaticabnormalitywhowillnotgoontodevelopclinically

manifestdisease-dealingwithagenerallywellpopulationmeansthateach

personwillhavearelativelylowpre-testprobabilityofeachclinicallymanifest

disease.

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Confidential: For Review OnlyAvoidinganoverdiagnosistsunami

Whatdoesthismeanforoverdiagnosis?Thesensitivityofbigdatatestingwill

leadtothedetectionofanenormousamountofabnormalitiesinallindividuals.

Crucially,however,onlyalimitednumberofthesewillmanifestclinically.As

illustratedinFigure3andouronlineinteractivegraphicalapplication-the

probabilityofoverdiagnosisincreaseswiththenumberoffeaturesscreenedfor.

Toavoidatsunamiofoverdiagnosis,screening2.0ispremisedontheextremely

challengingtaskofpredictingjustwhichofthehostofdetectedabnormalities

thataredestinedtocausesymptomsordeath,andwhicharenot.Thismustthen

feedbackintoandinformmedicine´sdefinitionalprocessofwhatshouldbe

regardedasabnormal,screenedforanddiagnosed.Onlyifonecanidentify

«undiagnose»thosewhowillnotdevelopsymptomaticdisease,isoverdiagnosis

avoided.Importantly,thekeyparameterhereisnottheabilityofmedicalteststo

accuratelyidentifyabnormalitiesinthepresent(i.e.sensitivityandspecificityat

stepBinFigure1).Aswehaveshown,highsensitivityinthissenseincreasesthe

riskofoverdiagnosis.Rather,whatisneededarehighpredictivevalueswith

regardtowhowillnotandwhowillactuallygoontodevelopclinicallymanifest

diseaseinthefuture.Isbigdataprecisionmedicineupforthetask?

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Figure3Thetotalriskofanindividualbecomingoverdiagnosedincreasessubstantiallyasthenumberof

variables(abnormalities)thatarescreenedforincreases.Thisholdstrueeveniftheriskofoverdiagnosis

forasinglefeatureislow.Seeonlineinteractivegraphicalapplication:

https://ekstroem.shinyapps.io/estimating_over-diagnosis/.

Theunpredictabilityofcomplexbiologicalsystems

Asalgorithmscombiningmultiplegeneticvariantsandothervariableshave

alreadydocumented(16),bigdatamethodologiescansometimesimprove

predictivevalues.However,despitetechnologicalandscientificadvances,there

maybefundamentallimitationsinpredictingthetrajectoriesofbiological

abnormalitiesincomplexbiologicalsystems(17,18).

Onemajorsourceofunpredictabilityiscalledthebias-variancedilemmaor

”CurseofDimensionality”(5,19).Inordertoreflectthemulti-factorialcausal

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Confidential: For Review Onlynatureofcomplexsystems,onemayneedtoincludemanyvariables.Ingeneral,

highpredictivevalueofmedicaltests(lowtotalerror)requiresanunderlying

modeloralgorithmthatreflectsthecomplexityofthebiologicalsystem,yielding

bothhighaccuracy(validity)andhighprecision(reliabilityorrepeatability).

Reducedaccuracyiscalledbias;reducedprecisioniscalledvariance.The

dilemmais,thatuptoacertainpoint,theinclusionofmorevariablesleadsto

greateraccuracy(lessbias)andthusbetterpredictions.However,beyonda

certainthreshold,thevariancethenstartstoincrease,resultinginreduced

precision(seeFigure4).

Figure4Bias-varianceandthe”CurseofDimensionality”:Asthenumberofvariablesmeasured

increases,theaccuracyofthemodelincreases(i.e.,biasisreduced),butthevarianceincreases

(precisiondecreases).Precisionmedicinethusbecomesimprecisionmedicine,andthetotalerror

increased(i.e.totalpredictivepowerfalls)(Source:Fortman-Roe2012,http://scott.fortmann-

roe.com/docs/BiasVariance.html).

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Confidential: For Review OnlyThisisbothduetoexperimentalnoiseandtobiologicalvariationindisease

development.Inotherwords,itishardtoreliablymeasureandmodelmany

variablesatonceandpreciselydeterminethedevelopmentofacomplex

biologicalsystemthatmayfollowawiderangeofpossibletrajectories(5).

Moreover,theeffectsizesofeachcomponentthatcontributetodiseasemaybe

itselfbeinfluencedbyavarietyofcontext-dependentfactors,orbetoosmallto

bedetected(20).

Therearethuslimitstohowfarbigdatacantakeusinpredictingjustwhat

abnormalitieswillleadtosymptomaticdisease.Inacontextwhere“everything”

abnormalisdetected,theabilityofbigdatatodecreaseoverdiagnosisis

thereforelikelytobeoutpacedbyitsabilitytoincreasetheproblem.

Lackofknowledgeandspectrumbias

Likeafine-maskednet,high-resolutionscreeningislikelytodiscover

abnormalitiesthatmedicinepreviouslycouldnotcatchandthatweyetdonot

knowthenaturalprogressionof.Toavoidoverdiagnosisinbigdataprediction

medicine,wethereforeneedlongitudinalstudiesprovidingsuchknowledge.

However,atthispoint,wedonothavesuchstudies.Thiscanleadtoincreased

overdiagnosisduetotheproblemofspectrumbias(21).

Imaginethateachdiseaseconstitutesaspectrumofabnormalitiesfromlowto

highrisk.Spectrumbiasoccurswhennewtechnologiesdetectabnormalitiesin

newpartsofthespectrum,andoneassumesthattheycarrythesameriskas

thosethathavepreviouslydetectedandresearched.Instead,theyarelikelyto

carryloweractualriskastheywillgenerallybesmallerandhavingprogressed

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Confidential: For Review Onlylesstowardsdisease.Asoneexample,thewidelypromotedAliveCorsmart-

phoneapp,whichallowseachconsumertoproduceanECG,hasbeenproposed

forscreeningofatrialfibrillation(AF)topreventstrokes.However,whilethe

technologyincreasestheAFdetectionratefourfoldinpatients≥65yearsofage

withnohistoryofAF(22),thenewabnormalitiesdiscoveredlikelyconstitutea

lessharmfulpartoftheAFspectrum(23).

Questionsoftoleranceandpatience

Thedegreetowhichbigdatawillleadtooverdiagnosisthushingesonwhether

implementationoftechnologiesisrushed-orconductedwithcareful

considerationandpatience.Largeprognosticstudieswith10-20yearsoffollow-

upormoreareneededtogeneraterobustevidenceaboutthepredictivevalues

ofnewscreeningtests.

Severalculturaldriversofoverdiagnosishavebeenidentifiedintheliterature

(10,24,25).Theseincludetheexpectationthat”moremedicine”isalwaysbetter,

azero-tolerancetowardsdisease,anover-zealousfocusonearlydetectionof

abnormalities,andloweringofdiagnosticthresholds.Thisleadstooverdefinition

ofwhoshouldberegardedasharbouringabnormalitiesthatweshouldscreen

for(seestepAinFigure1).Curbingoverdiagnosisisthuspartlyaquestionof

tolerancetowardsuncertainty,risk,diseaseanddeathinlife.Suchtolerance

funnelsmorepeopleintoGroup1atstepAinFigure1,awayfrom

overdiagnosis.However,ifoneistojudgebythosestudiespioneeringscreening

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Confidential: For Review Onlyversion2.0,precisionmedicineshowsfewsignsofsuchtoleranceandpatience

(14,15).

Conclusion

While“toomuchmedicine”and“lessismore”havebeenslogansforpreventing

overdiagnosis(8,26),bigdatamedicinefacesthechallengeofturning“even

moremedicine”into“less”diagnosis,wasteandharm.Screening2.0hasthe

potentialtodetectahostofabnormalities.Butduetolimitationsinforetelling

whichofthemwillleadtosymptomaticdisease,itmayparadoxicallymanifestas

“imprecisionmedicine”,labellingeverybodywithamultitudeofabnormalitiesof

unknownfuturesignificance.Asaconsequence,”more”medicinewillnotturn

into”less”wasteandharm,butislikelytoresultinoverdiagnosisversion2.0.

Overdiagnosisshouldthusberecognisedasakeyproblemforthefutureofbig

dataand(im)precisionmedicine.Appropriatestudiesmustbemountedto

accountforit,andscreening2.0shouldwaituntilmoreisknownaboutpotential

benefitsandharms.

Key Messages

• Personalised and precision medicine promise to improve disease prevention, but will in practice entail a massive, new form of screening.

• Screening 2.0 will likely aggravate the problem of overdiagnosis by screening multiple variables in everybody with high resolution technologies.

• Screening 2.0 will lead to the detection of much more abnormalities of currently unknown significance and is likely to increase overdiagnosis.

• Big data based screening should become a main concern in preventing overdiagnosis, and preventing overdiagnosis should become a main concern in the implementation of preventive precision medicine.

Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf<http://www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous

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Confidential: For Review Onlythree years; no other relationships or activities that could appear to have influenced the submitted work.

The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, a worldwide licence (http://www.bmj.com/sites/default/files/BMJ%20Author%20Licence%20March%202013.doc) to the Publishers and its licensees in perpetuity, in all forms, formats and media (whether known now or created in the future), to i) publish, reproduce, distribute, display and store the Contribution, ii) translate the Contribution into other languages, create adaptations, reprints, include within collections and create summaries, extracts and/or, abstracts of the Contribution and convert or allow conversion into any format including without limitation audio, iii) create any other derivative work(s) based in whole or part on the on the Contribution, iv) to exploit all subsidiary rights to exploit all subsidiary rights that currently exist or as may exist in the future in the Contribution, v) the inclusion of electronic links from the Contribution to third party material where-ever it may be located; and, vi) licence any third party to do any or all of the above. All research articles will be made available on an Open Access basis (with authors being asked to pay an open access fee—see http://www.bmj.com/about-bmj/resources-authors/forms-policies-and-checklists/copyright-open-access-and-permission-reuse). The terms of such Open Access shall be governed by a Creative Commons licence—details as to which Creative Commons licence will apply to the research article are set out in our worldwide licence referred to above. Contribution statement: All authors contributed to the present argument as well as to the reviewing and writing of the manuscript, with HV providing the first draft and having a leading role in its development. All authors contributed to the development of the figures, CE and JB providing the first versions and CE providing the online interactive application.

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BMJ

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Figure 1

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BMJ

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Figure 2

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BMJ

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Figure 3

169x169mm (72 x 72 DPI)

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BMJ

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Figure 4

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BMJ

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BMJ

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