confidential: for review only - bmj · precision medicine based on big data can be focused on...
TRANSCRIPT
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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Confidential: For Review Only
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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Figure 1
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Figure 2
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Figure 3
169x169mm (72 x 72 DPI)
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Figure 4
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