Assessing prognosis and prediction of treatment response in early rheumatoid arthritis

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Archer, R., Hock, E. orcid.org/0000-0002-8617-8875, Hamilton, J.
orcid.org/0000-0003-3326-9842 et al. (6 more authors) (2018) Assessing prognosis and
prediction of treatment response in early rheumatoid arthritis: systematic reviews. Health
Technology Assessment, 22 (66). pp. 1-294. ISSN 1366-5278
https://doi.org/10.3310/hta22660
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HEALTH TECHNOLOGY ASSESSMENT
VOLUME 22 ISSUE 66 NOVEMBER 2018
ISSN 1366-5278
Assessing prognosis and prediction of treatment
response in early rheumatoid arthritis:
systematic reviews
Rachel Archer, Emma Hock, Jean Hamilton, John Stevens, Munira Essat,
Edith Poku, Mark Clowes, Abdullah Pandor and Matt Stevenson
DOI 10.3310/hta22660

Assessing prognosis and prediction of
treatment response in early rheumatoid
arthritis: systematic reviews
Rachel Archer,* Emma Hock, Jean Hamilton,
John Stevens, Munira Essat, Edith Poku, Mark Clowes,
Abdullah Pandor and Matt Stevenson
School of Health and Related Research (ScHARR), University of Sheffield,
Sheffield, UK
*Corresponding author
Declared competing interests of authors: John Stevens isashareholder ofGlaxoSmithKline plc
(GSKHouse, Middlesex, UK), AstraZeneca plc (Cambridge, UK) and ShirePharmaceuticals Group plc
(Shire plc, Dublin, Republic ofIreland).
Published November 2018
DOI: 10.3310/hta22660
This reportshould be referenced as follows:
Archer R,HockE, Hamilton J,Stevens J, EssatM, PokuE, etal. Assessing prognosis and prediction
oftreatment responsein early rheumatoid arthritis: systematic reviews. Health TechnolAssess
2018;22(66).
HealthTechnology Assessment isindexed and abstracted in IndexMedicus/MEDLINE, Excerpta
Medica/EMBASE, ScienceCitation Index Expanded (SciSearch®) andCurrent Contents®/
Clinical Medicine.

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DOI:10.3310/hta22660 HEALTHTECHNOLOGYASSESSMENT2018 VOL.22 NO.66
Abstract
Assessing prognosis and prediction of treatment response in
early rheumatoid arthritis: systematic reviews
Rachel Archer,* Emma Hock, Jean Hamilton, John Stevens,
Munira Essat, Edith Poku, Mark Clowes, Abdullah Pandor
and Matt Stevenson
School ofHealth and Related Research(ScHARR), University of Sheffield, Sheffield, UK
*Corresponding author [email protected]
Background: Rheumatoid arthritis (RA)isa chronic,debilitating disease associated with reducedquality
oflife and substantial costs. It isunclear whichtests and assessment tools allow thebest assessment
ofprognosis in people withearly RA and whether ornot variables predict theresponse ofpatientsto
different drug treatments.
Objective: To systematically review evidence onthe useof selectedtests and assessment tools in patients
with early RA (1) in theevaluation ofaprognosis (review1) and(2) aspredictive markersof treatment
response (review2).
Data sources:Electronic databases(e.g. MEDLINE, EMBASE, TheCochrane Library, Webof Science
Conference Proceedings; searchedto September2016), registers, keywebsites, hand-searching of
reference lists of included studies and keysystematic reviews andcontact withexperts.
Study selection: Review 1–primary studies on thedevelopment, externalvalidation andimpact of
clinical prediction models for selected outcomesin adultearly RA patients. Review2–primary studies
on theinteraction between selected baselinecovariates and treatment (conventional and biological
disease-modifying antirheumatic drugs)on salient outcomesin adult early RA patients.
Results: Review1–22modeldevelopmentstudiesandonecombinedmodeldevelopment/externalvalidation
studyreporting39clinicalpredictionmodelswereincluded.Fiveexternalvalidationstudiesevaluatingeight
clinicalpredictionmodelsforradiographicjointdamagewerealsoincluded.c-statisticsfrominternalvalidation
rangedfrom0.63to0.87forradiographicprogression(differentdefinitions,sixstudies)and0.78to0.82for
theHealthAssessmentQuestionnaire(HAQ).Predictiveperformanceinexternalvalidationsvariedconsiderably.
Threemodels[(1)ActivecontrolledStudyofPatientsreceivingInfliximabforthetreatmentofRheumatoid
arthritisofEarlyonset(ASPIRE)C-reactiveprotein(ASPIRECRP),(2)ASPIREerythrocytesedimentationrate
(ASPIREESR)and(3)BehandelingsStrategie(BeSt)]wereexternallyvalidatedusingthesameoutcomedefinition
inmorethanonepopulation.Resultsoftherandom-effectsmeta-analysissuggestedsubstantialuncertainty
intheexpectedpredictiveperformanceofmodelsinanewsampleofpatients.Review2–12studieswere
identified.Covariatesexaminedincludedanti-citrullinatedprotein/peptideanti-body(ACPA)status,smoking
status,erosions,rheumatoidfactorstatus,C-reactiveproteinlevel,erythrocytesedimentationrate,swollenjoint
count(SJC),bodymassindexandvascularityofsynoviumonpowerDopplerultrasound(PDUS).Outcomes
examinedincludederosions/radiographicprogression,diseaseactivity,physicalfunctionandDiseaseActivity
Score-28remission.TherewasstatisticalevidencetosuggestthatACPAstatus,SJCandPDUSstatusatbaseline
maybetreatmenteffectmodifiers,butnotnecessarilythattheyareprognosticofresponseforalltreatments.
Mostoftheresultsweresubjecttoconsiderableuncertaintyandwerenotstatisticallysignificant.
©Queen’sPrinterandControllerofHMSO2018.ThisworkwasproducedbyArcheretal.underthetermsofacommissioningcontractissuedbytheSecretaryofStatefor
HealthandSocialCare.Thisissuemaybefreelyreproducedforthepurposesofprivateresearchandstudyandextracts(orindeed,thefullreport)maybeincludedinprofessional v
journalsprovidedthatsuitableacknowledgementismadeandthereproductionisnotassociatedwithanyformofadvertising.Applicationsforcommercialreproductionshould
beaddressedto:NIHRJournalsLibrary,NationalInstituteforHealthResearch,Evaluation,TrialsandStudiesCoordinatingCentre,AlphaHouse,UniversityofSouthamptonScience
Park,SouthamptonSO167NS,UK.
ABSTRACT
Limitations: The meta-analysis in review 1 was limited bythe availability ofonly asmall number of
external validation studies. Studies rarely investigated theinteraction between predictors and treatment.
Suggested research priorities: Collaborative research (including theuse ofindividual participant data)
is neededto furtherdevelop andexternally validate theclinical predictionmodels. Theclinical prediction
models should bevalidated with respectto individual treatments. Futureassessments of treatment by
covariate interactions should followgood statistical practice.
Conclusions: Review 1–uncertainty remains overthe optimal prediction model(s) for use in clinical
practice. Review2–in general, therewas insufficient evidence thatthe effect oftreatment dependedon
baseline characteristics.
Study registration: This study isregistered asPROSPERO CRD42016042402.
Funding: TheNational Institute for Health Research HealthTechnology Assessment programme.
vi
NIHRJournalsLibrary www.journalslibrary.nihr.ac.uk
DOI:10.3310/hta22660 HEALTHTECHNOLOGYASSESSMENT2018 VOL.22 NO.66
Contents
List oftables xi
List offigures xiii
Glossary xvii
List ofabbreviations xix
PlainEnglish summary xxi
Scientificsummary xxiii
Chapter1Background 1
Description ofthehealth problem 1
Clinical featuresof rheumatoid arthritis 1
Epidemiology 1
Aetiology 1
Management of rheumatoid arthritis 1
Measurementofkey outcomesin rheumatoid arthritis 2
Backgroundtoprognosis research 3
Key concepts inprognosis research 3
Definition ofaprognostic model 4
Clinical prediction modeldevelopment 4
Measures ofpredictive model performance(binary outcomes) 5
External validation 5
Backgroundtostratified medicine research 6
Developing treatment-specific clinical prediction models 6
Issues associated with subgroup analyses 6
Assessing treatment bycovariate interactions 6
Assessing treatment bycovariate interactions in this review 7
Interpretation ofthe evidence regarding patient and/or diseasecharacteristics 7
Chapter2Review question andobjectives 11
Reviewquestion 11
Assessment structure 11
Overall objectives ofthe assessment 11
Chapter3Methodsfor the assessment ofprognosisand prediction of treatment
responseinearly rheumatoid arthritis 13
Assessment structure 13
Scopingofthe assessment 13
Justification ofreview approach 13
Review 1: clinical prediction models 14
Review 2: prediction oftreatment response 14
©Queen’sPrinterandControllerofHMSO2018.ThisworkwasproducedbyArcheretal.underthetermsofacommissioningcontractissuedbytheSecretaryofStatefor
HealthandSocialCare.Thisissuemaybefreelyreproducedforthepurposesofprivateresearchandstudyandextracts(orindeed,thefullreport)maybeincludedinprofessional vii
journalsprovidedthatsuitableacknowledgementismadeandthereproductionisnotassociatedwithanyformofadvertising.Applicationsforcommercialreproductionshould
beaddressedto:NIHRJournalsLibrary,NationalInstituteforHealthResearch,Evaluation,TrialsandStudiesCoordinatingCentre,AlphaHouse,UniversityofSouthamptonScience
Park,SouthamptonSO167NS,UK.