THRDEDToN Clinical Epidemiology THE ESSENTIALS RobertH.Fletcher,M.D.,M.sc. Professor Department of AmbulatoryCare andPrevention Harvard MedicalSchoolnndHarvard Community HealthPlan Department of Epidemiology,HarvardSchoolof PublicHealth Department of Medicine,BrighamandWomen'sHospital Boston,Massachusetts Suzanne W.Fletcher,MD., M.sc. Professor Department of Ambulatory Care andPrevention HarvardMedicalSchoolandHarvardCommunity HealthPlan Department of Epidemiology, HarvardSchool of PublicHealth Department of Medicine,Brigham and Women's I Iospital Boston,Massachusett Edward H. Wagner,MD., M.P.H. Director,Center for I [ealth Studies Croup Health Cooperdtive of Puget Sound Professor of Ht'alth Services University of Washington Seilttlc,Washington Williams&Wilkins A tRI Y 0""'''''''"'''0''''''''0'',,",' ''',,'''' hl'"" """, 0"'''''0'" "," 0\Y''',,01O'','' 'A" Edlto,- T"nolily S,Sattertleld Mmmo'ng Edllor:Crystal Taylm Productl"" COOrdllliJrur.Haymond1::.Hetor Copy Editor,CandaceB,Levy,Phn Designer:NormanW_Oeh lliustrntkmPfilflfl'"Mario Typesetter.lapsco,Inc"Akron,PennsylvanIa Printer& Binder: VIctor GraphiCS,Inllchasbloodpressureorserum sodium. Then,too,dinicianf>arc inclinedtobelieve that their therapies are successful. (Most patientf>would not want a physician who felt otherwise.) This attitude, so impurtant in thl' prdctice of medicine, makes clinical obser-vationsparticularlyvulnerahletobiaf>. Althoughd07ensof biase;,havebeendefined(4),most fallintoone of three browhencomparisonsaremadebehveengroupsofp"-tientsthilt differ in \vays,other thanthemainfactorstmder study, that affect Table1.4 BiasinClinicalObservation Seloctlon bias occurs whcrlr;mnparytoob,>ervl'thl'effectsof herpesvirus frccof theother factorsrelatedtoincreased'>l'xualactivity(5). Selection bias and confounding bias are not mutually exclusive. They are describedseparately,however, because they present problems at different CHAPTER1!INTRODUCTION9 MAINQUESTION ,c SJ{,2 c- - - - --.It Cti/vical -:es.However, random variationcannever be totally eliminated, so chance should always be consideredwhen assessing the results of clini-calobservations. Therelationshipbetwl'enbiasandchanceisillustratedinFigure1.2. Themeasurement ofdiastolicblood onasinglppatient istaken asanexample.Truebloodpressurecanbeobtainedbyanintraarterial carulUla, which is SOmm Hg forthis patient.But this method is not possible forroutinemeasurements;bloodpressureisordinarilymeasuredindi-., r::: o ~ 1l o '0 ~ 1: E :> z True blood pressure (intraarterial cannula) CHAPTER1IINTRODUCTION11 Blood pressure measurement (sphygmomanometer) l.. I. Chance . .1 .1 ----Bias----8090 Diastolic Blood Pressure(mm Hg) Figure 1.2.Relationship between bias and chance:Blood pressure measurements by Intraarterialcannulaandsphygmomanometer. rectly,usingasphygmomanometer.Thesimplerinstrumentisproneto error,ordeviationsfromthetruevalue.Inthefigure,theerror isrepre-sentedbyallofthesphygmomanometerreadingsfallingtotherightof the truevalue.The deviationof sphygmomanometer readingstothe right (bias)mayhaveseveralexplanations-forexample,apoorlycalibrated sphygmomanometer,thewrongcuffsize,oradeafclinician.Biascould alsoresultif differentsoundswerechosentorepresentdiastolicblood pressure.Theusualendpoints-phaseIVandphaseVKorotkoff sounds-tend to be aboveandbelowthetrue diastolicpressure,respec-tively,andeventhatisunpredictableinobesepeople.Individualblood pressurereadingsarcalsosubjecttoerrorbecauseofrandomvariation in measurement,asillustratedbythespreadof thesphygmomanometer readingsaroundthe mean value(90mm Hg). The two sources of error-bias and chance-are not mUhlally exclusive. InmostsirnatioIlS,botharepresent.Themainreasonfordistinguishing betweenthetwoisthattheyarchandled differently. Biascanintheorybepreventedbyconductingclinicalinvestigations properly or corrected through proper data analysis.Tfnot eliminated, bias oftencanbe detected by thediscerningreader.Most ofthis bookisabout howtorecognizE',avoid,orminimizebias.Chance,ontheotherhand, 12CLINICALEPIDEMIOLOGY cannotbeeliminated,butitsinfluencecanbereducedbyproper design of research, and the remaining error can beby statistics. Statistics canalso helpremovethe effects of known biases.However, no amount of statisticaltreatment cancorrect forunknown biases indata.Some statisti-cianswouldgosofarastosuggestthatstatisticsnotbeappliedtodata vulnerable to biasbecauseof poor researchdesign,forfear of givingfalse respectabilitytomisleadingwork. INTERNALANDEXTERNALVALIDITY Whenmakinginferencesaboutapopulationfromobservationsona sample,twofundamentalquestionsarise(Fig.1.3):First,aretheconclu-sionsoftheresearchcorrectforthepeopleinthe sample?Second,if so, doesthe sample representfairlythepopulationofinterest? Internalvalidityisthe degrcctowhichtheresults of astudy are correct forthe sample of patients being studied. It is"internal" because it applies totheconditionsoftheparticulargroupofpatients being observedand not necessarilyto others.The internal validityof clinical researchisdeter-mined byhowwellthedesign,datacollection,andanalysesarecarried out and isthreatenedby allofthe biasesand random variationdiscussed above. For a clinical observation to be usefuL internal validity is a necessary but not sufficient condition. Externalvalidity (genl'ralizabiiity)isthedegreetowhichthe resultsof an Allpatients with the condition of interest ?' ,, EXTERNAL VALIDITY (generalizability) Figure1.3.Internalandexternalvalidity. INTERNAL VALIDITY selection bias measurement, confounding bias ...chance1 CHAPTER1IINTRODUCTION13 observationholdtrueinothersettings.for anindividual physician,itis an answertothe question,"Assuming thatthe res-:.i1tsof ashtdy aretrue, do they apply tomy patient as well?" Gcneralizability expresses the valid-ity of assuming that patients ina study are comparable with other patients. Anwtimpeachablestudy,withhighinternalvalidity,maybetotally misleading if itsresultsaregenera liz('dtothewrong patients. ExampleWhat istheriskthatanabdominalaorticaneurysmwillrup-ture?Clinicians seeing with ant;'urysmsmust have thisinformation to make wise dITision" about the need for elective surgical repair. The answer dt.'pendsonwhichkindsofpatientsarcdescribed.Amongpatientswith aneurysmsurgt;'ryiscommonlyadvised, thoseseen inreferralcentershaveabout a10times greaterrateofrupture during5yt'arsoffollow-upthanthoseinthegencralpopulation(Fig1.4) (6).Thismaybebecausepatientsincentersarereferredforsymptomsor sih'llSofimpendingrupture.If cliniciansinoffict'practiceweretousethe results of research from reft.'rra I centers to predict rupture, they would greatly overestimate theriskandmakethewrong decisionabout thenecd forelectivesurgicalrepair. The generalizability of clinical observations, eventhose with highinter-nalvalidity,isamatter ofopinion aboutwhichreasonablepeople might disagree. ExampleThePhysician'sHealthStudyshowedthatlow-dost'aspirin (325rug every other day)prevented myocardial infarction in mille physicians " ,.. -l "' 30 20 10 Population Referral centers Figure1.4.Samplingbias:Rangeofriskofrupture(shadedarea)Inthenext5 years of abdominalaortic aneurysm5.0 cmindiameter) according to whether the patientISfromthegeneralpopulationorareferralcenter(6). 14CLINICALwithoutknowncoronary heart (7).The11,037randomly assignedtotakt'hada440lower rak (,fmyocardiJIinfarctionthan the11,034assignedtotab- plilcebo_The studywas C"arl'fuliyconductedand a researchdesign;findingshave stoodupwellto Howt'vt'r,only healthymalewere in the study.Whentheresults ofthe,>tudvIverefirst hadtoderidewhetheritwas justifiedto liive aspirin to women, pt'opl, with many risk andpatients who acealreadyknowntohave coronary dis7. Koran LM.TIle of clinicalmethods, data andjudgnwnt.N Engl J Med1975;293:642-646,695-701. MainlandDRemarkson clinical ClinCht"m1'171; 17:267-274. MurphyEA.Th,'logicof medicine.Baltimon"JohnsJ JopkinsUniversity1'176 CJJ, DH, PatrickDl..M('Jsuring health-relatedquality oflife.AnnIntern Med 1 >-'" z 0.40 w '" ,, > ,, , ,... , , 0.4 StageB.- > ., ..., , '" , "Stage A 0.6 z w , '" , Cutoff Point , -0.20 ..2.5 ng/mL 5.0 ng/mL ..0.8 10.0 ng/mL O ~__~__-L__-L__-L__~ 0.200.400.600.801.00 1-SPECIFICITY --------Figure 3.6.ROC curve for CEA as a diagnostic test for colorectal canCer,according tostageof disease,Thesensitivityandsp8cificityof atestvarywiththeslageof disease.(RedrawnfromFletcherRH.Carclnoembryonlcantigen,AnnInternMed 1986; 104:66-73,) tice,however,severalcharacteristicsofpatients,suchat;stageandseverity of disease, may be related both tothe sensitivityandspecificity of atet;tand totheprevalence, because different kinds of patients arefmmdinhigh- and low-prevalencesituations.Usingatesttoscreenfordiseaseillustratesthis point(see Chapter 8forafullerdiscussion of screening).Screeninginvolves theuscofthetestinan I--w en> 0-0.1-0 0 w a: 0. __ 80 60 40 20 0 sensitivity/specificity \\, 80/8090/9099/99 1/511101/501/100 PREVALENCE 1/10001/10,000 Figure 3.8.Positive predictive value according to sensitivity,specificity,andpreva lenceof disease. Current effortstoprevent transmissionof acquired immunodeficiency syndrome (AIDS)through bloodproducts isanother example of the effect of disease prevalence on positivepredictivevalue. ExampleA blood testforantibodiesto human immunodeficiency(HIV)isusedto screenblood Atone cutoff pOint,thesensitivity97,8/"andthespl;'cificityis90.4%.In1985,thepositivepredictiVl;'valueof thl;'test was estimatedfromthe prevalence of infectiouslUlitstobl;'nomore than 1/10,000. Thus therewouldbe 9,250false-positivetest resultsforeVl;'ry true-positiVI;'result(8).Almost10,000unitswouldhavetobediscardedor investigiltedfurthertoprevent onetransfusionofcontaminatedblood.The authors concludedthat,forthis emotionally charged subject, "careful adher-I;'ncetotheprinciplesofdiagnostictestevaluationwillavoid expectations." Butthesituationchanged.Astheprevalence of HIV infectionincreased inthegeneral population,the positive predictiv(' value of the screeningtest improved.Inapublicationayearlater,theprevalenceofinfectedunits among67,190testedwas25/10,000,andatsimilarlevelsof sensitivity and specificity,the pOSitiVI;'predictive valuewouldbe 2.5;':"much higher than a fewyearsbefore(9). ESTIMATINGPREVALENCE How can clinicians estimate theprevalence or probabilityof diseasein a patient to determine the predictive value of a test result? There are several sources of infonnation:the medical literature, localdatabases, and clinical judgment.Althoughtheresultingestimateofprevalenceisseldomvery precise,errorisnotlikelytobesogreatastochangeclinicaljudgments CHAPTER3!DIAGNOSIS61 thatarebasedontheestimate.Inanycase,theprocessisboundtobe moreaccuratethan implicit judgment alone. Tngeneral, prevalence is more important than sensitivity and specificity indeterminingpredictivevalue(seefig.3.8).Onereasonwhythisisso isthatprevalencecommonlyvariesoverawiderrange.Prevalenceof diseasecanvaryfromafractionofapercenttonear certaintyinclinical settings,depending ontheage,gender,rit.kfactors,and clinicalfindings of the patient. Contrast the prevalence of liver disease in a healthy,young adult who uses no drugs, illicit or otherwise, and consumes only occasional alcohol,withthat ofajaundicedintravenous druguser.Bycurrent stan-dards,cliniciansarenotparticularlyinterestedinkstswithsensitivities andspecificitiesmuchbelow50'Yo,butifbothsensitivityandspecificity are99%,thetestisconsideredagreatone.Inotherwords,inpractical termssensitivityand specificityrarely varymorethantwofold. INCREASINGTHEPREVALENCEOFDISEASE Considering the relationship between the predictive value of atest and prevalence, it is obviously tothe advantage to apply diagnostic topatientswithanincreasedlikelihoodof havingthediseasebeing sought.In factasFigure 3.8 shows, diagnostic tests aremost helpfulwhen thepresenceof diseaseisneitherverylikelynor veryunlikely. ThE'Teareavarietyof waysin whichtheprobabilityofadiseasecan beincreasedbeforeusing adiagnostictest. ReferralProcess Thereferralprocessisoneofthemostcommonwaysinwhichthe probabilityofdiseaseisincreased.Referraltoteachinghospitalwards, clinics,andemergencydepartmentsincreasesthechancethatsignificant diseasewilltmderliepatients'complaints.Therefore,relativelymoreag-gressiveuse of diagnostictestsmightbe justifiedinthesesettings.Inpri-marycarepractice,ontheotherhand,andparticularlyamongpatients without complaints,thechanceof findingdisease isconsiderably smaller, and testsshouldbeusedmore sparingly. ExampleWhilepracticinginamilitaryclinic,oneoftheauthorssaw hundreds of people with headache, rar!;'l), ordered diagnostic tests, andnever encounteredapatientwithasevereunderlyingcaUSt'ofheadache.(Itis lUllikdy that important conditions were missedbC'causethe clinic wasvirtu-.,lIyth!;'onlysource of medical carefortheSl;'patients and proloneedfollow-upwasavailable.)However,duringtheweekbackinamedicalresi-dency,apatientvisitingthehospital'Semergencydepartment becauseofa headachesimilartotheonesmanagedinthemilitarywasfoundtohavea cerebellar Because cliniciansmay work at different extremes of theprevalence spec-trumat various timesintheirclinicalpractices,theyshould bear in mind 62CLINICALEPIDEMIOLOGY that the intensity of diagnostic evaluation mayneedtobe adjustedto suit thespecificsituation. SelectedDemographic Groups Inagivensetting,physicians can increasetheyieldof diagnostictests byapplyingthemtodemographic groups knowntobeathigherriskfor adisease.1\manof65is15timesmorelikelytohavecoronaryartery diseaseasthecause of atypicalchestpainthanawomanof30ithusthe electrocardiographicstresstest,aparticulardiagnostictestforcoronary disease,islessusefulinconfirmingthediagnosisintheyoungerwoman thaninthE'olderman(10).Similarly,asickle-celltestwouldobviously have a higher positive predictive value among blacksthan amongwhites. Specifics of the ClinicalSituation The specificsof theclinicalsituationare clearlythestrongest influence onthedecisiontoordertests.Symptoms,signs,anddiseaseriskfactors all raise or lower the probability of finding a disease. For example, a woman with chest painismore likelyto have coronary diseaseifshe hastypical angina and hypertension and she smokes. As a result, an abnormal electro-cardiographicstresstestismorelikelytorepresentcoronarydiseasein such a woman than in persons with nonspecific chest pain and no coronary riskfactors. The valueof applying diagnostic teststopersonsmore likelytohave a particular illnessisintuitivelyobvious tomost doctors. Nevertheless, with theincreasingavailabilityofdiagnostictests,itiseasytoadoptaless selectiveapproachwhenorderingtests.However,thelessselectivethe approach,thelowertheprevalenceof thedisl:'aseislikelytobeandthl:' lowerwillbethepositivI:'predictivevalue ofthetest. The magnitude of this effect can be largerthan most of us mightthink. ExampleFactors that influence the interpretation of an abnormal electro-cardiographic stress test an:,in Figure 3.9. It that the positive predictive valu(' forcoronary artery (CAD) associated with an dbnor-maltestcanvaryfrom1_7to99.8%,depending onage, symptoms, andthe degrecofabnormalityof thetest.Thusan cx('rcisetest inanasymptomatic 3.'i-year-oldmanshowing1mmSTse).,'lllentdepressionwillbeafabe-positive test inmore than 98% of cases.The same testresult ina60-yedf-old manwith typicalrmginabyhistorywillbeassociatedwithcoronaryartery diseasein more than 90%of (to). Becauseof this effect,physicians must interpret similartest results dif-ferentlyindifferent clinicalsituations.A negative stresstest in an asymp-tomatic35-year-oldmanmerelyconfirmsthealreadylowprobabilityof coronary artery disease,but apositivetest usually will be misleadingifit is usedto sl:'archforunsuspected disease, as has been done among joggers, airlinepilots,andbusinessexecutives.Theoppositeappliestothe65-100 gO W :J 80 ~ '" > 70 w_ : = ~ 60 I - ~ 00 -'" iilo 50 a:a: "0 40 w"-30 " t: 20 '" 0 .. 10 0 Age Symptom Prevalence of CAD(%) CHAPTER3IDIAGNOSIS63 c:::J0.5-1.0mm _> 2.5mm 30-3960-6960-69 NoneNoneAtypical angina 1.g12.367.1 60-69 Typical angina 94.3 Figure 3.9.Effect of disease prevalence onpositive predictive value of a diagnostic test.Probability of coronary artery disease Inmenaccording to age,symptoms,and depressionof $T segment on electrocardiogram.(Data fromDiamondGA,Forrester JS. Analysis of probability as an aid in the clinical diagnosis of coronary artery disease. NEnglJMed1979;300:1350-1358.) year-oldman withtypicalangina.Inthiscase,thetestmay be helpfulin confirming disease but not in excludingdisease.The testismostusefulin intermediate situations,in which prevalence isneither very highnor very low.Forexample,a60-year-oldmanwithatypicalchestpainhasa6n:, chanceofcoronaryarterydiseasebeforestresstesting(seeFig.3.9);but afterward, with greater than2.5mm STsegment depression, he has a99% probability of coronary disease. Becauseprevalence of diseaseissuch apowerfuldeterminant of how usefuladiagnostic test willbe, cliniciansmust consider theprobability of diseasebeforeorderingatest.Untilrecently,cliniciansreliedon clinical observationsandtheirexperiencetoestimatethepretest probabilityofa disease.Researchusinglargeclinicalcomputerdatabanksnowprovide 64CLINICALEPIDEMIOlOGY quantitative estimates of the probability of disease, given various combina-tionsof clinicalfindings(11). IMPLICATIONSFORTHEMEDICALLITERATURE Publisheddescriptionsof diagnostictestsofteninclude,inadditionto sensitivityandspecificity,some conclusions abouttheinterpretationof a positive or negativetest,i.e.,predictivevalue.Thisisdone,quiterightly, toprovide information directlyusefulto clinicians.But thedataforthese areoftengathered in universityteaching hospitals wherethe prevalenceofscriousdiseaseisrelativelyhigh.Asaresult,statements aboutpredictivevalueinthemedicalliteraturemay bemisle,ldingwhen thetestisappliedinlesshighly selectedsettings.Whatisworse,authors oftencomparetheperformanccof atestinanumber of patientsknown tohavethediseaseand anequalnumber of patientswithoutthedisease. This is an efficient way to describe sensitivity and specificity. However, any reported positive predictive value fromsuch srudies means little because it hasbeendeterminedforagroupofpatientsinwhichtheprevalenceof diseasewas setbytheinvestigators at 50(10. LikelihoodRatios Likelihoodratios are an alternativewayof describingtheperformance ofadiagnostictest.Theysummarizethesamekindofinformationas sensitivityandspecificityandcanbeusedtocalculatetheprobabilityof diseaseafterapoo;itiveor negativetest. ODDS Becauseuseof likelihoodratiosdepends on odds,tounderstandthem it isfirt>tnecessary to distinguishodds fromprobability.Probability-used to express sensitivity,specificity,andpredictive value-is theproportion of peopleinwhomaparticularcharacteristic,suchasapositivetest,is present.Odds,ontheotherhand,istheratioof twoprobabilities.Odds andprobabilitycontainthesameinformation,butexpressitdifferently. Thetwocanbeinterconvertedusing formulas: Odds=Probabilityof event 1- Probabilityof event Probability- Odds-'- I+ Odds Thesetermsshouldbefamiliartomostreadersbecausethey areusedin everyday conversation.For example, we may say that the odds are 4:1that the Seattle willwintonight or that they have an 80%probabil-ityof wiIming. DEFINITIONS ThelikelihoodfIItiuforaparticularvalueof adiagnostictestisdefined asthe probability ofthattestresult in peoplewiththedisease dividedby theprobabilityoftheresultinpeople withoutdisease.f.ikelihoodratios CHAPTER3!DIAGNOSIS65 expresshowmany timesmore(orless)likelyatestresultistobefmmd indiseased,compared withnondiseased,people.If atest isdichotomous (positive/negative)twotypesoflikelihoodratiosdescribeitsabilityto discriminate betweendiseasedand nondiseasedpeople:one isassociated with apositivetestandtheother with anegativetest(seeFig.3.2). In the pharyngitis example (see Fig. 3.3), the data can be used to calculate likelihoodratios forstreptococcal pharyngitis inthe presence of apositive or negative test (clinicaldiagnosis). Apositive test isabout 2.5times more likelytobemade inthepresence ofstreptococcalpharyngitis than in the absenceof it.If thecliniciansbelievedstreptococcalpharyngitiswasnot present,thelikelihood ratioforthis negativetest was 0.3':);theodds were about 1:2.6that a negative clinical diagnosis would be made inthe presence of streptococcalpharyngitis compared with theabsenceofthedisease. USESOFLIKELIHOODRATIOS Pretestprobability(prevalence)can be convertedtopretest odds using the formula presented earlier. Likelihood ratios canthen be used to convert pretest odds toposttest odds,by meansof thefollowingformula: Pretest oddsXLikelihoodratio=Posttest odds Posttestodds can,inturn,beconvertedbacktoaprobability,usingthe formuladescribedearlierinthischapter.Tntheserelationships,pretest odds contains the same information as prior probability (prevalence), likeli-hoodratios the same as sensitivity /specificity, and posttest odds the same at.positivepredictivevalue(posttestprobability). Themain advilntageoflikelihoodratiosisthattheymake it easierfor ustogobeyondthesimpleilndclumsyclassificationofatestresuitas either abnormill or normal, as is usually done when describing the accuracy ofadiagnostictestonly intermsofsensitivityandspecificityat asingle cutoffpoint.Obviously,diseaseismorelikelyinthepresenceof anex-tremely abnormilltest result than it is foramarginalone.With likelihood ratios, it is possible to summarize the information contained in a test result at different levels.One can definelikelihoodratiosforany number of test results,overtheentirerangeofpossiblevalues.Inthisway,information representedbythe degreeof abnormality,ratherthanthe crude presence or absenceofit,isnotdiscarded.In computing likelihoodratiosacrossa rangeoftestresults,sensitivityreferstotheabilityof that particular test result toidentifypeople with thedisease,notindividualswiththat result or worse.The Silmeistrueforthecalculationofspecificity. Thuslikelihoodratioscanaccommodatethecommonandreasonable clinicalpracticeofputtingmoreweightonextremelyhigh(orlow)test results thanon borderline oneswhen estimating theprobability (orodds) thataparticular diseaseispresent. 66CLINICALEPIDEMIOLOGY ExampleHow accurate isst'rum thyroxine (T4)alone as a forhypo-thyroidism? Thisquestionwas addressedinastudy of120ambulatory gen-eralmedicalpatit.'nts suspected of having hypothyroidism (12).Patients were diagnosedasbeinghypothyroidifserumthyrotropin(TSH)elt.'vakd and if subsequent evaluations, including other thyroid tests andresponseto treatment,wereconsistentwithhypothyroidism.TheauthorsShtdiedthe initial T,level in 27 patients withhypothyroidism and 93patients whn were foundnottoIlave it to determine how ac(.:uratt'lythe simple test alone might have hypothyroidism. Asexpected,likl;'lihoodratiosforhypothyroidismwert'highestforlow levelsofTt andlowestforhighll;'wls(Table3.2).The lowestinthe dbtriblltion of T ,s 4.0 pg/ dL) were onlyin patients with hypothyroid-ism,i.e.,theseIt'wls rtlledinthe diagnosis.The highest ll;'\'els(>8_0 pg/dL) werenotseeninpatil;'ntswithhypothyroidism,i.e.,theprt'senceofthese levelsruled out the disease. Theauthorsconcludedthat"itmaybepossibletoachievecost withoutlo,"sofdiagnosticaccuracybyusingasingletotalItmeasure-mentfortht'initialevaluationofsuspectedhypothyroidisminselected patients." Thelikelihoodratiohasseveralother advantages over sensitivityand specificityasadescriptionoftestpE'rformance.Theinfonnationcontrib-utedby the test issummariLed in one number instead of two.The calcula-tionsnecessaryforobtainingposttestoddsfrompretestoddsareeasy. Table 3.2 Distributionof Valuesfor Serum ThyroxineinHypothyroidandNormalPatients, withCalcutationof LikelihoodRatios' TolalSerum Illyroxifle 1!-''J/dL) B--,> c--'> Figure3.10.Senalandparalleltesting. tSensitivity tSpecificity tSensitivity tSpecificity Multiple tests in parallel generally increase the sensitivity and, therefore, thenegativepredictivevalueforagivendiseaseprevalence abovethose ofeachindividualtest.Ontheotherhand,specificityandpositivepre-dictive value are lowered. That is, disease is less likely to be missed (parallel testingisprobablyonereasonreferralcentersseemtodiagnosedisease that local phYbicians miss), but false-positive diagnoses are also more likely tobemade(thusthepropensityfornverdiagnosinginsuchcentersas well).Thedegreetowhichsensitivityandnegativepredictivevaluein-creasesdepends on the extent to which the tests identify patients with the disease missed by theother testsused.forexample,iftwotestsare used inparallelwith60andSO"{.sensitivities,thesensitivityoftheparallel testingwillbe only SO'Yoif thebettertestidentifiesallthecasesfound by thelesssenbitivetest.If thetwotestseach detectallthecasesmissedby theother,thesensitivity ofparalleltestingis,ofcourse,10m!".Tfthehvo testsarecompletelyindependentofeachother,thenthesensitivityof paralleltestingwould be92'\"0. Paralleltestingisparticularlyusefulwhentheclinicianisfacedwith theneedforaverysensitivetestbuthasavailableonlytwoormore CHAPTER3/DIAGNOSIS69 relativelyinsensitiveonesthatmeasuredifferentclinicalphenomena.By usingthetestsinparallel,theneteffeetisameresensitivediagnostic strategy.Theprice,however,is('valuationortreatmentofsomepatients without thedisease. xam}liePSi\.anddigitalreclalexamarcbothinst'ositivelestsforthe diagnosiSof prostate cancer (7).Tahle 3.3shows theirsensitivity,andpredietiw'valuesinthescreeningsetting(menwithoutsymptoms). Whenthetwott'stsarcusedinparallel,thesensitivityincreasesbutthe specificityfalls.Thepositivepredictivl;'vlllueislowerthilllfor['SA testingalone. SERIALTESTING Physicians most commonly use serial testingstrategies inclinical situ __-L__ 20406080 1-SPECIFICITY('Yo) 100 Figure 3,12,Hle responsivenessot two questionnaire measuresof healthstatus. Distinguishingbetweenelderlypatientswithandwithout a major Interveningillness. (AdaptedfromWagnerEH,LaCroixAZ,GrothausLC,HechtJA.Responsiveness ofhealthstatusmeasurestochangeamongolderadults.JAmGeriatrSoc 1993;41 :241-248.) CHAPTER3!DIAGNOSIS73 bents for whom the test might beusefulinpractice. In addition, knowledge ofthefinaldiagnosisshould notbiastheof thetest results orviceversa.Changingthecutoffpointbetweennormalandabnormal changessensitivityandspecificity.Likelihoodratiosareanotherwayof describingtheaccuracyof adiagnostictest. Thepredictivevalueof atestisthemostrelevantcharacteristicwhen clinicians interpret test results.It isdeterminednot only by sensitivity and specificity of thetest but also by the prevalence of the disease,whichmay change fromsettingtosetting.Usuallyit isnecessary touseseveraltests, eitherinparallelorinseries,toachieveacceptablediagnosticcertainty. Responsiveness,atest'sabilitytodetectchangeinclinicalstatus,isalso judged bythe samen.-,'o-by-twotable. REFERENCES JointNationalCommittee onDetection,b'alu,ltion,andTreatmentofHighBloodl'res-MIre.Thefifthreportofthl"JointNatlOnalCommitteeonLkkdinn,Evaluation,and Treatment of HighJ3luodPressure(JNCV).ArchlnkmMeJ1993;Ei3:154-HO. 2.CatalonaWJ;dat.Measurement of antigeninserum as Jkst for NEnglJMed3j0 0.0. 0 .. .. 60 0> " .. ". 0>0 f:! 20 0 50 A B c 60708090100 Excessdeath rate attributableto BP >90 mmHg Prevalenceof elevatedBP at variouslevels Percent excess deathsattributable tovariouslevelsof hypertension 110120130 DiastolicBloodPressure (mmHg) Figure5.4.Relationshipsamongattributablerisk,prevalenceofriskfactor,and populationriskforhypertension.(AdaptedfromTheHypertensionDetectionand Follow-up Cooperative Group.MildhypertensivesInthehypertensiondetection and follow-upprogram.AnnNY AcadSCI1978;304:254-266.) having adiastolic bloodpressure>',10mm Hg,most hypertensive people are just over 90 mm Hg, and very few are in the highest category mm Hg).Asaresult,the greatest percentage of excess deaths in the population (58.4/,,)isattributabletorelativelylow-gradehypertension,90-105mm Hg(Fig.5.4C).Paradoxically,then,physicianscouldsavemorelivesby effectivetreatmentofmildhypertensionthanseverehypertension.This fact,so counterintuitive to clinicalthinking, has beentermed "the preven-tionparadox"(9). Measures of populationrisk are le:;sfrequently encountered in the clini-CHAPTER:1IRISK109 cillliteraturethilnaremeasuresofindividualrisk,e.g.,attributableand relativerish..ButapMticuiarclinicalpracticei; muchapopulation forthed()('torasisacommunityforhealthpolicymakers.howthe pn.'valence of exposure affects community risk can be important in the care of individualpatients. for instance,whencannot give ahistory or when exposure isdifficultforthemtorecognize,we dependontheusual prevalence of exposure to estimate the likelihood of various diseases. When consideringtreatablecausesof cirrhosisinaNorthAmericanpatient,for example, it would be more profitable to consider alcohol than schistosomes, inasmuch as fewNorth Americillls are exposedtoSchistosomamllflsoni.Of course',onemighttakeaverydifferent intheNiledelta,where schistosomes aTe prevalent and the people, who are mostly Muslims, rardy drink alcohol. Summary Risk factorsare characteristics that are associated withan increasedrisk ofbecomingdiseased.Whetherornotaparticularriskfactor dcause of disease,itspresenceallowsonetopredicttheprobabilitythatdisease willoccur. Mostsuspectedriskfactorscannot bemanipulated forthepurposes of an experiment, so itisusually necessary to study risk by simply observing people's experiencewith riskfactorsanddisease.One wayof doing soto select a cohort of people, some members of which aTeand some of which arcnot exposedtoariskfactor,andobservethe subsequentincidenceof dis('ase.Althoughitisscientificallypreferableto studyriskbymeansof cohortstudies,thisapproachisnotalwaysfeasiblebecauseofthetime, effort,and expense it entails. WhendiseaseratesarecomparedamonggroupswithdiffeH'ntexpo-su res to a risk factor,the results can be expressed in several ways. A ttribut-ableriskistheexcessincidenceofdiseaserelatedtoexposure.Relative riskisthenumberoftimesmorelikelyexposedpeoplearetobecome diseasedrelativetononexposedpeople.Theimpactofariskfactoron groups ofpeopletakesintoaccountnot onlytheriskrelatedtoexposure but theprevalence ofexposure aswell. REI-FI.:ENCES I.WeissNS,LiffjM.An"()untingforth ~ -=CQ .c> ... -. c ~ 0::> ~ ( J ) a. 415=80%112=50% 100%III100%11100% Time(Years) Figure 6.5.A typicalsurvivalcurve,withdetailforonapartofthecurve. probabilityofsurviving,;;mdonthehorizontal axisistheperiodoftime followingthebeginning of observiltion.Often,thenumbers of patients at risk at various points intime are shown to give some idea of the contribu-tionof chancetotheobservedrates. Theprobabilityof surviving to anypoint intimeisestimated fromthe cumulative probability of surviving each of the time intervals that preceded it.Time intervals can be made as small asnecessary; in Kaplan-Meir ansibilitythatsilicon1;' breastimplants maycause autoimmune '>ymptomsofrh1;'umaticdiseas1;'.A studywas,therefore,done of 156womenwithsiliconebreast implants"nd rhE'umaticdiseasecomplaints (5).Thepatientswereconsecutiv1;'nderralsto three rheumatologists who were knownfortheir interest in silicone implants and rheumatic disease.Serologic t e ~ t sinthe women were compared tothose ofwomenwithoutimplantsbutwithfibromyalgiaandtotestsinwomen withimplantsbutnorheumaticsymptoms.Theclinicalfindingsinthe womenwithimplantsandcompldintsweredescribed;mostdidnotfulfill criteriaforrheumatoidarthritisandmosthadnormalimmunologictests. However,l4patientshad,>cleroderma-likei l l n e ~ sandabnormalserology thatWilSnot foundin thecomparbon groups. Becauseofthepossible biases thatcanoccurintheassemblyofpatientsforthiscaseseries,theiluthors werecautiousabouttheirfindings,concludingthat"the hypothesesraised inthis study and other,>should betestedinlarge, population-based studies." Publication ofthefirstsuchsludy doesnot support thehypothesis (6). MIGRATIONBIAS Migrationbias,anotherformof selectionbias,can occurwhenpatients inonegroupleavetheiroriginalgroup,droppingoutof thestudyalto-gether or movingtoone of the other groups under study. If these changes takeplaceonasufficientlylargescale,theycanaffectthevalidityof conclusions. Innearly all shtdies, somemembersof anoriginal group drop out over timc. If these dropouts occur randomly, suchthat the characteristics of lost subjectsinonegroupareontheaveragesimilartothoselostfromthe other,thennobiaswouldheintroduced.Thisissowhetherornotthe number of dropoutsislargeorthenumberissimilarin thegroups.But ordinarilythecharacteristicsof lostsubjectsarcnotthesamcinvarious groups.Thcreasonsfordroppingout-death,recovery,sideeffcctsof CHAPTER6IPROGNOSIS127 treatment,etc.-areoftenrelatedtoprognosisandmayalsoaffectone group more than another.Asa resuit, groups in a cohort that were compa-rableat theoutsetmaybecomelesssoastimepasses. Astheproportionofpeopleinthecohortwhoarenotfollowedup increases, the potential forbias increases.It isnot difficult to estimate how largethisbiascouldbe.Alloneneedsisthenumberofpeopleinthe cohort,thenumber not accOluttedfor,andtheobserved outcomeratc. ExampleThompsonetal.describedthelong-term ofgastro-gastrostomy (7)./\ cohort of123morbidlyobese patients was studied 19-47 months aftersurgpry. Successwas defined ashilVinglostmore than30%of excesswei);ht. Only103patients(tl4%)couldbelocated.Inthese,thl;'successrateof was60/103(581uccessesor allfailures. Patientsmayalsocrossoverfromnnegrouptoanotherinthecohort duringtheir follow-up.Wheneverthisoccurs,theoriginalreasons forpa-tientsbeinginonegrouportheothernolongerapply.Tfexchangeof patients between groupstakesplaceonalargescale,it can diminishthe observeddifferenceinriskcomparedtowhat might havebeen observed if the original groups had remained intact. Migration bias due to crossover ismoreoftenaprobleminriskthaninprognosisstudiel:>,becauserisk shldiesoftengoonformanyyears.Ontheotherhand,migrationfrom one grouptoanother canbeused intheanalysisofastudy. ExampleTherelationshipbetweenlifestyleandmortalitywasstudied byclassifying10,269HarvardCollegpaluIrcI1.ibyphysicalactivity,smoking status,weight,andblood in1%6andagainin1977(tl).Mortality rateswerethenobservedovera9yearperiodfrom1977to1985.It recognized that original classificaliol{s might change, obscuring any relation-shipthatmight between \if!:';;tyleandmortality.Todealwiththis,the investigatorsdefinedfourcategories:l11enwhomaintainedhigh-risklife-styles,thosewhochangedfromlow- tohigh-risklifestyles,thosewho chang!;'dfromhigh- tolow-risklifestylf's,andthosewhomaintained101'.'-risk lifestyles.Aft!;'radjusting forother riskfactors,men who increasedtheir physical activityfromlowtomodprate amounts,'-luitsmoking,lostweight to normallevels,and/or becamenormo\ensivl;'allhad lower mortality than men who maintainedor adopted high-risk characteristics,but not as low as thl'ratesforalumniwho neverhildanyriskfactors_ 128CLINICALEPIDEMIOLOGY MEASUREMENTBIAS Measurementhias is possible if patients in one ,?,roup stand a better chance of havingtheir outcome detectedthanthosein another group.Obviously, someoutcomes,suchasdeath,cardiovascularcatastrophes,andmajor cancers,arc so obtrusivethattheyaretmlikelytobemissed.Butforless dear-cutoutwmes-the specificcauseofdeath,subclinicaldisease,side effects,or disability-measurement biascan occurbecauseofdifferences inthemethodswithwhichtheoutcome issought or classified. Measurementbiascanbeminimizedinthreegeneralways.Onecan ensurethat thosewho makethe observations areunaware of the group to whicheachpatient belongs,canset carefulrulesfordecidingwhether or notanoutcome eventhasoccurred(andfollowtherules),and can apply effortstodiscoverevents equallyin allgroups inthestudy. Example and studiedtheoutcomeofp,ltienh-.wIth asymptomaticneck (9).Atotalof500asymptomilticpiltientswith cervicalbnlilswere observedforupto4 years.i'atientswereclassifiedac-cording tothe degrec of initial carotid drterybyDoppler rarhy. Olltcomes were changeindegree of carotid andincidence of cerebralischemk events. Toavoidbiasedmeasun.'lnents,theauthorsestimatedcarotid usingestablished,explicitcriteridfurinterprt.'tingDoppler scanslAMA SUCCESTEDREADrI\;GS EddyDM(ed)Common bcrel'llingtests,I'hi!.1delphi,',An1('ri(",mCollege ofPhysici,lns,1991 GuldbloomlUI,Lawn'nct'RS,Pr,'ventingdisease:beyondtlwrh..tori(",Nt'wYork: Springer-Verlag,I'Jtsare appliedtothe datato give atl'l;t I;tatistic,whichinturn can be usedto om\{' up with a probability oferror(Pig.9.2).Thetestsareof the111111h.llpofhe.c.i.s,the propol;itionthat thereisnotruedifferenceinoutcome benveen thehvotreatment groups. Thif>device isformathematicillreasons, not because "no differencc" il;the working f;cientifichypothesis of the study.One ends upYt'jectingthenull hypothef>is(concludingthereisa difference) or failingtoreject it (conclud-ingthefeif>no difference). Some commonlyused st,ltislicall{'sts are listedin Table 9.1.The validity CHAPTER9ICHANCE191 Data Test Estimate of Statistical statistic Compare to probability that teststandard observed value distribution could beby (using tables, chance alone etc.) Figure9.2.Statisticaltesting. Table 9.1 Some Statistical TechniquesCommonly UsedinClinical Research Totest thestatIStICalsiglllfJc;anceof adifference Between twoor moreproporlions(wilenthereisa largenumber of obscrvatlons) Fisher's exact Betweenlwoproportions(whenthereISa smallnumber of observalions) Mann-WhitneyU Studentt Belweentwomedians Betweentwomeans BetwecntwoorInmemeansFtest 70 desenvetheextent of aSSoCiation RegressioncoeffiCient animJepenrJent(predictor)variableanda dependent (outcome)vallable Pearson's rBetweentwo w:mablcs Tomodel the effectsof multiplevariables LogisticregressionOna dichotomousoutCOITIC CoxproportionalhacardsOna time-to-event outcome of eachtest depends on certainassumptiont.about the data. If thedataat hand do not satisfy these assumptions, the resulting p" may be misleading. Adiscussion of how thesestatit.ticaltestt.arederived and calculatedand oftheassumptionsonwhichtheyrcstCdnbefoundinanybiostatistics textbook. ExampleThe chi squan' (X') for nominal data (counts)is mort: ea:,ily understood thim anJsoCdnbe usedtoillustratehow testing works_thefollowingdatafromarandomizedtrialof twoWdYSof initiatinganticoagulationwithheparin:awt'lght-baseddosingnomogram and t.t,mdardcafe (4).The outcomea partialthromboplastin time (PTT) exceedingthetherapeuticwithin24hrof bcgirming anticoagu),,-tion.InthenomogrilmgrouphOofh2 didso;inthe care grO\lp,37of 4,s(77%). 192CLINICALEPIDEMIOLOGY ObservedRates Nomogram SlanrJardcare Totill Yes 60 3i 97 I 'iT [xceedrngNo , 11 13 Tulal 62 48 110 Howlikelywoulditbe forastudy ofthissizetoobserveadifference inratesat;greatasthit;or greaterif therewereinfactnodifferencesin effectivenet;s?That depends onhowfartheobserved depart from whatmighthilvebcC'nexpectedifthetreatmentt;wereofsimilarvalue ilndonlyrandom variationcausedthemtodifferinthe samples studied. If treatmenthadnocffectonoutcome,applyingthesuccessrateforthe pl'often look bilckward intime andthiltrestricts their value as amCilnS of studyingprognosisor GlUf>('-(1nd-dfectrelationships. Case-ControlStudies Tofindout whether afindingor posf>iblecause really ismore common inpatientswith agivendisease,Oil('npeds,1study with severalfeatures. First ilnd foremost,in ibk Ciluse- it is necessaryto controlfor a 11other important differences intheanalysisof thefindings. Casereports and case cannottilkeusthisfdr.Neither cancohort studies in many situations, bcc(1use it is not feasibleto accrue enough cases toruleouttheplilyofchance.Cdf>e-controlstud ips,studies that compare thefrequencyof apurportedriskfdctor(g('lll'w11ycillledthe "exposure") inagroupof casesanditgroupof controls,havethesefeatures. Exposure to Risk Factor CHAPTER10ISTUDYINGCASES213 Uisease Figure10.1.Thedesignof case-controlstudies. DESIGN The basicdesignof acase-controlstudyisdiagrammedinFigure10.1. Patients who have the disease and a group of otherwise similar people who do not have the disease are selected. The researchers then look backward in time to determine the frequency of exposure in the two groups. These data can beused to estimate the relatiye risk of disease related to the characteris-ticof interest. ExampleDoes the use of nonsteriodal ,mtiinflJmmatory drugs increurein and controb, andthatthelargt'lynmfinedtoold",rmpn. 214CLINICALEPIDEMIOLOGY Whdtismcantby::;imi/ar?Thereissomecontroversyaboutthi:-..Ina cohortstudyoftheriskofNSi\lDsforremldi:-.easl',simil(.'-controistudies has beentotet;thypotheses about theetiologyofdisease.Morerecently,investigatort.haveexploitedthe advantagesofthecasC'-controldesigntot.tudyquestionsrelatedtothe provision andqualityof healthCMe. Example1scerebralpalsy andfetaldeath preventable? British investiga-tors(16)useda casIC-controldesign tocompare the antepartum care received by141babi!;'sdevelopingcerebral palsyand62dying intrapartum or neona-tally.Eachcasewasmatchedwithtwohedlthy babies born atthe sametimIC ,mdplace.Afailuretotoofseverefetalwasmore commonamongthancontrolsbutonlyaccountedforav,'rysmdli percentage ofbabit'swithcerebralpalsy. Becausemot;tt;eriousadverseeffectsofpoor-qualitymedicalcareare relativelyrare,thecase-controldesignprovidet;anefficientstrategyfor eX3miningtherelationshipbetweendeviationsfromguidelinesorother protocolsand poor outcomes. Summary Muchofmedicalprogressisderivedfromthecarefulstudyofsick individuals. Cat;ereports are studies of just afewpatients, e.g.,-;:10.They are auseful means of describingunusual presentations of disease, eX3min-ingthemechanismsofdisease,andrnisinghypothesesabout causesand treatments.However,casereports3reparticularlypronetobias3nd chance.C3seseries-studies oflilfgercollectionsof patients-still t;uffer fromtheabsence of areferencegroupwithwhichtocompare theexperi-enceof thecasesandfromsampling casesatvarioustimesinthecourse oftheir disease. Incase-controlstudies,agroupofcasesiscomparedwithasimilar groupof noncases(controls).Amajoradvantageresidesin theabilityto assemblecaset;fromtreatment centers or dit;caseregistriesasopposedto findingthemorwaitingforthemtodeVl'lopinadefinedpopulationat risk.Thus case-control studies aremuch less expensive and muchquicker toperformthancohort studies and the only feasiblestrategy forstudying riskfactorsforfldictory results in casc control research.Am JMed1979;6fi:556-564. In.Gaffney G.Sellers S,Fiav(:I1V,SquierM,Johnson A.Case-controlofintrapartum ("arl'.("('n"hralpols],.andpenn.{!al d"Jth.BrMed J 1994;301:1:743-750. CHAPTER10ISTUDYINGCASES227 SUGGESTEDREADINGS [