Clinical Epidemiology and Bio Statistics a Primer for Orthopaedic Surgeons - Kocher, Zurakowski - 2004

8/2/2019 Clinical Epidemiology and Bio Statistics a Primer for Orthopaedic Surgeons - Kocher, Zurakowski - 2004

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INICAL EPIDEMIOLOGY AND BIOSTATISTICS: A PRIMER FOR ORTHOPAEDIC SURGEONSinder S Kocher; David Zurakowskirnal of Bone and Joint Surgery; Mar 2004; 86, 3; ProQuest Nursing & Allied Health Source607

7

(OPYRIGJT l HE )OCR:A m BO AD )01:T 5L'RR, 1ORORA

CuRRENT CoNEPTS viEW

CLINI L EPIDMIOLOGY

ND BIOSTTISTIS:

A RIMR FOR RTHOPDI uRGONSBY NNDE S. KE, MD PH AD AD ZA, PD

lvestignto pe1Jor nt Hnvnr Meicnl School, Hnrnr School of Publc Hnlth, Boto nnclwtt

pidemology s th study of th dstributi on and determ nants of di sease frequncy'. In th th cntury Hppo-crats suggested that the developm nt of huma n disas mghtb rlatd to the extal and nta nvironmnt of anndiv idual. In the 1600s and 1800s in England john Grauntand Wil am ar uantifed vita statist cs on th basis ofbir th and death recods'. In the 180s john Snow assocatedchola with water contaminat ion in London by observinghgher choea rats n homes suppid by ctan wat sources'.Epidmological methods gradually volved with us of thecas contol study to dmonstrat an association btwnsmoing and u ng cancer use of th prospctv cohort studyto dtrmine is factos for cadiovascular dsase in theramngham Heart St udy, and use of the ra ndo mzd cl incatr al for th pol omye t is vacc ne Th videncebasd medi -c in and pat entdivd outcoms assessment movmentsbu rst onto the scn of clin ca mdc in i n th 980s and1990s as a res u t of contmporaneous medica socital andeconomc inuences. Pioneers such as Sacett and insteinemphasized eves of vidence and patint centeed outcomesassssmnt'". Wok by nnbrg and colagus vadarg smal aea varations n clinical practc wth some pa-

tients beng thty tims more likly to undergo an opativprocedue than other patients wi th dent ica symptoms meeybcause of their geographc locat on'. Addtonal crt ca re-sarch suggested that up to 40% of some sugical pocduresmight b na ppropriat and up to 85% of common medicalteatments were not igoousy validatd eanwhl thecosts of heal th car were rapidy r s ing to over two bi iondo a rs per day i nceasng from 2% of the gross domsticpoduct n 1960 to 16 .2% n 1997 Hath maintenanc or-ganiatons and ma nagd cae emgd I n addit ion incra sing fdral stat, and consumr ovrsght was brought tobea on th p ractic of cl i nica mdcne.

These forces hav d to an inceased focus on the ef-fctivness of cl nical ca Cincal epdmoogy prvdesth mthodoogy with which to assss this ffctivnss Thisaticl presents an ovrvew o f th concpts of study dsgnhypothss testing masus of tatmnt effct diagnostic

prformance vidncebased medcine outcomes assess-mnt data and statistical analys s Examples from the or-thopaedic l terature and a glossary of te rm no ogy (termsitalicid throughout the text) are povide d.

Study Design

I n observntion studies researchers obseve patent groupswithout a location of the ntervention wheras in expermet studies esearchrs allocate th teatment Experi mentalst ud s nvolvng humans ar calld trias Research studiesmay b etrspective maning that th e direction of inui ry isbackward fom th cases and that the events of interest tran -sped befor th o nset of th study A teatively st udies mayb prospetive meanng that the direction of inuy is for-ward from the cohot ncepton an d tha t th e events of interesttranspire ater th onset of th study (Fig . Cross-sectiostudis ar usd to survey on point in tim Logitudistudis fo low th sam patients ov multip e pon ts in time

All research studies are suscptib le to nvalid concu -sion due to bias confounding and chance Bins is the non -andom systmatc or in th dsign or conduct of a studyBias usual ly is not intentional however t is pevasve andn sidious or ms of bias can coupt a s tudy at any phaseincludng patient slction (slction and membership bias)study performanc (pformanc and nformaton bias) pa -tint followup ( nonspondr and tansfer bias) and outcomedtrmination ( dtction call acceptabil ty and intevewerbias) equent b iases n the orthopaedic lteratue include se-cton bas whn dssmiar groups a compared; nonsponder bas whn th follow up rat is ow; and intervwrbias whn th invstgator dtrmines the outcome A cofouder is a variabl that has ndpndnt associations withboth th idepedet (predctor) and dped t (outcome)variabls thus potntial ly distorting thi relationshp or xampl an associati on btwn kee laxit y and ante ior cruc -

at ligamnt inuy may be confounded by fmale sex sincewomn may hav grate kn laity and a high r ris of ante rior cruciate l igament in ury runt cnfoun drs in cln icalrsarch includ gndr ag socioeconomic status and co


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09

T !F O" O BO & )OIT Y JJOGO - FR RH

TABLE Hypthesis Testing*

xperien

o ocon

Aocon

oAoion

Correc

ype ( eror

ru

Aoiio

ype- ( eror

Correc

le proly of ype- eor owe= prolyo ype- ero

The efecs in a coh ot study ae eq uentl rpord in rmsof rentive risk (RR. Because aditional cohor studs areprospective hey can opmze followup and daa qualityand can mnimiz bias associaed wh scion inomaon and measuement n addon hy hav th corcttimesequnc to pod srong dnce regading associa

tions Hower hs studis ae cosy are logstca de-manding often qu a long imepeiod fo complion,and ae ineficient for he assessment of unusual oucomeso dseases

Eperimental study designs ma nove th us of concuren conrols, squenal contos (crossover trinls), or his-orica con rols Th oize ciicnl trinl RCT wihcncuen conros s th socalled gold standad o clinicalevidence as t povids the mos vald conclusons (ntal va-ldi ty) by minimizng th cts o bias and conoundng Rg-oous andomzation wh enough patients is he bst mans oaoding conoun ding Th pr fomance of a andomizd con-tol tal inolves h constuction of a proocl documnt thatepicitly establishs elgibli citera sample siz, infomdconsen andomzation ues fo stopping th tial bindngmeasuremen, monioring o complance assssmnt of safetand daa analsis Bcause alocaion s andom selecon bas ismnmized and conounders (known and unknown) horecally ae equaly distributed beween groups Blndng mnmi zes pefomance detection, nteviewe and accptabitybias Binding ma b pactced at fou eels: paicpants in -esgaos apping the nteventon oucme assssos andanalyss Itetio-to- tren nnlysis minmizes nonspondeand ransfe bas whil samplesize detemination nsurs ade-quae powe The ntntionoeat pincipe stats that all patiens should be anayed wihin th treatment group o whichthey were randomzd in orde to preseve he goals o andom -izat io A though the randomized clnical tral is e eptome ofclinical esearch dsigns the dsadvanages of such rias includeheir epense o gstics and time to compleion ccrual of pa-iens and accepance by clncians may be dicult With rapidly eolng chno ogy a new techniqu may qu ickly bcomwell acceped, making an esting andomizd clincal tial obsoete or a potenal andomizd clinical tial di fcul t o accptthcal, andomzed cinical trias requie clnical quipose( equal of teamnt options n he clinican's judgment) fornolment ntem sopping ules to avoid ham and o vau -at adverse events and ruy inomed consnt Fnaly, wh

Ct IIAL EPIJD GY ,\ B O'L .\TlI("A RFR R RH R 0'

andomid cinical ials ha clln inal valdiy somhav qusond hi gnaizabilit (trnal alidt b-caus th pracc patrn and the populaion of patiens enrold n a randomd cinical tial ma b o constainedand nonprsntati

hica considraions ae ininsic to h dsgn andconduc of clinical rsach studies Infomd consnt is ofpaamoun mpotanc and it s th oc us o m uch o thactiit of insitutional iw boads Invstigators shoudbe amliar with h umbg Code and the Dclaation ofelsnki as thy prtain to thical ssues of riss and benefitspoection of p vacy, and espect fo auonom' Hypothesis Testing

he pupose of hypohesis esing s o pemi genealizaionsfrom a snmple to th pop uato n fom whch t cam ypoh-esis testing confrms o futes th assrion tha the observedndings did not occu by chance alone bu ahe occurred

because of a true assocaton beween variables By de fault the hpothess of a stu d assts that there s no signcant association betwen ariables wheeas he alteatie hypothe-ss asserts that he is a sign fcan association I f the fndingsof a sud ar not signicant we cannot ect th nu l hypohesis wheas f th ndngs ae sgnfcant we can rejc thenull hypohesis and accep he alernative hypohesis

Thus, all rsach studies that are based on a samplemake an nfnce about the tuh n the oveal populationB construcing a x abe of he possibl outcomes o asudy ( ab !) , w can se that the infeence o a stu dy s co ec a signicant association is no found whn there s notru association o if a signicant association is found whenther is a tu associaion owee, a study can have wotypes of rors type-/ o nlphn error occ urs when a sgnican association s found when thee s no true associaton( esuling in a asposiive sud that rejecs a rue nul hpohesis) A tpe-11 or uetn j) ero wongl concludes hathere i s no signfcan associatio n ( resulting in a falsenegatiestud tha rjcts a t ru altenatve hpothesis )

The alpha lvl fs o the pobab ilt o a tpe! eror B convenion th alpha level of signcance is set a 005which means hat w accpt he fnding of a signicant association if thee is ss than a on in twent chance that the obseredassociation was due o chance aone Thus th p alue whch iscacuatd with a sais cal est is a masu of he stengh ofthe eidnc provdd b th data in avo o the nul hpohesis . If e p value is less a e alpha leve, the e evienceaganst the nul hpohess is stong enough for us o reect itand conclud that the esul is signifcan

P values fqunl ar used in clnical seach and aegven ga impoanc b jouals and eads; howeve thereis a stong movmn in biosatistics to demphasize p aluesbcause a signicanc l of p < 0.05 s abitay a stict cu o pont can b misleadng ( thee is itte di ffnc beweenp 0.049 and p 0051, but only the forme is considered s g-nfcan) he p vau gives no nfomation about the srengthof h association and th p aue may be stasticaly sign


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) O R A L O F BOI & 0 1 S ' R C E R Y J . O R \O " A NL' IB R R I

goup. Smal ampl z mal ffc iz and ag aianc all dca h po w of a udy. An undanding ofpow iu impoan in clinica ach o mnimz hu of o uc whn plannng a udy and o nu h a -l d y of a udy Sampl z caculaion a pfomd whn

a ud y bing plannd. Typca ly pow i a 80% apha a .5 h ffc i z and aianc a mad fompio daa o h liau and h quaion i old fo hncay amp iz ac ua on of pow a h u dy habn compldha i pohoc pow analyi i conoial and i d icuagd

Dagnostc Peormance

A diagnoic can u in fou poib cna o : l upo i f h i poi and h dia i p n 2 fal po f h i po and h da i an 3 u ngai f h i ngai and h dia i abnand 4) fal nga if h i ngai and h dia ipn abl I I ) . Th sst of a i h p cnag opopo on) of pan wih h dia who a claifid ahaing a po u f h h upoii a) wh 97% niiy impl ha of I pain wh hdia nnyn wi ha a poii Snii ha a low fal-nga a A ngai u of a highly n-ii ul dia ou SNou) h spcc of a ih pcnag o popoi on) of pan whou h d awho a clafi a hang a ngai u of h hunga a) wh 9 % pc c iy mpli ha of 00 pain wihou h da nn yon wll ha a nga-i . Spcific ha a ow fa-poi a poiiul of a highly pc u da n SP n) Sniiy and pcificy can b combnd ino a ing paamh lkld t LR, which h pobai y o f a u po- diidd by h poabliy of a fal poii. Sniyand pciciy can b ablihd in udi in whch h -ul of a diagnoic a compad wi h ho of h goldandad" of diagnoi in h am panfo xamp bycompaing h ul of magn c onanc maging w ih ahocopic findng.Sni i y and pciciy a chnica paam of di -agnoic ing pfomanc and ha impoan mplcaionfo cning and cinical pacc guidlin; how hya l lan in h ypica clinical ing bcau h clini -

can do no know whh h pain ha h d ia. hAB Dianosic es Peormance*

( L 1 P I I l I O ; B I O > I T I I <

A R R I O R R 'I IO P. l < S 0

.

. l

> . -

r r r = Q

0.4 -

.

.. .

cfcy

hg. 3

.

eceve-eai n caacec () cve a c nca ecin

e feenain eic ahi fm anien ynvi f e

n cen" Te fa e-iive ae ( ecficy) e n he

ai, an eniviy le n he y ai Te aea une he cve

eeen e vea anic emance a eicn le a

ianic e. a eec e e aea une he cuve 0

anm en e aea une e cve i 0 5

clncaly lan iu a h pobabi i y of h pan haingh da whn h u i poi pst prdc nlu[PP\J and h pbabiliy of h pan no haing h diawhn h ul i ngai nt pd nlu NP\j.h po and ngai pdic alu a pobab i i haqu an ima of h panc of h dia in h populaion and hy an b calculad wi h u of qua on ha u l Bay hom

h i an inhn adoff bwn nii y andpcic i y Bcau h i ypica ly om oap wn hdiad and nondiad goup wih pc o a diibui on h inigao can c a po i y c ion wi h aow falngai a o op miz niii y) o a o w fal-poii a o opimiz p c i ic i y ) ig 2 ) I n pac ic po-iiiy cia a lcd on h bai of h con qunc ofa fa-poii o a fanga diagnoi. I f h conquncof a fangai dagnoi ouwigh h conqunc of a

eae ive Dieae eave

Te ive

Te neave

a (e ive)

c (ale neaive)

b (fae iive)

(ue neaive)

Sen i iv y a/(a + c), eccy /(b + ) accacy (a + c)/(a b + c ), al e-neave ae 1 eniviy, fale-ive ae 1 ecificiy likeli a (+ ) enivi y/fal e-i ive ae, ikeli a () fae-neaive ae/ecificiy ive ecive

vaue [( eva lenc e)(eniviy)/ (eva ence)( en iv y) + 1 evalence)(1 ecifcy)] an neaive ecive vale (1 eva

lence)( ec fc y)]/( evalence)( eciiciy) + ( eva len ce)( enviy)].



T! r ) O L' R . OF BO E & ) 0 1 T S L'RGE RY I I S R GVOL '.\ I f ! ,\ -RC H 20 0

TABLE Tretment Eects*

2

( C A P D \ G Y . J T A T T C :

A P 0 RT I P .U J \ L 5L'J(, f0 :

Aderse Ees No Aderse ens

Expermenal group a

onrol oup c d

* Conro een rae CER j + d expermena l een rae EE R aja onol een odds CEO= /d expermenal een odds

EEO a/ relae s RR= EER/CER odds rao OR EEO/CEO reae rsk edon RRR EER CER/CER asole rsk redu

on ARR= EER CER, and numer needed o rea NN /ARR.

a po i t i d ago i o a codi t io ( uch a p ic ar thr i - o h h p i ch d r ) , a mor te co cho - Thi la ohip tw th i t ad pcc o a d iagot ic tet ca b porad wt h u o a reei'eroeratig f]teristi (RO wre A rc opatig char-acter t ic graph how th e lat ohip bw th u -po i ra ( e i i o th ax ad th fal poit iat peciicit o the x axi pottd at ach poblcuo (Fig. 3 . Oal l dagot c peromac ca alu -atd o h ai o h ara ud h rci opa gcharact t c cu .

Measures f EectMau o likl hood c ud probabl ad odd. Probnbiliyi a u me, bw 0 a d that dca how el a ti to occur o th bai o th u mbr o t per th umo ta. Th probai o had o a coi to i 0 O ih rati o o th poabilt o a et occui g to h poa-bili t o th o occurg. The odd o had comg upo a coi to 0 5/0 . . Bcau pobai t ad odd a re-latd th ca cotd wh odd poal( probabi l t .

?elntie risk (RR ) ca b dtrmid i a propccohort tud wh rlaie i qual th cdce o di -a th xpod cohot didd th cdc o d a th oexpod cohot (abl I ) . For xampl i a po-pc cohot ud o r wth dcic o h aocrucate l igam how a igcatl highr poporto oubqut kee iju r i i who ar ot ad wth arac ( 1 2 % tha hoe who ar ead wh a race 2 0% ,h rik rao i 64 .%/0% ) . Thi ca b trped aa 6.4 t m hgher o ubqu e jur i a krwth aeio crucia gam dficc who ot tratdwi h a bac tha uch a ki who tatd wt h a bac. A mi l ar meaum t i a retropci caco ro ud ( whch i cidc caot b dtmid) i h os raio (OR,whch i th rato o th odd o hag h dia i th tudgoup to th odd o haig h dia i th ctol group( Ta I l l ) .Facor that a ikl to cra h icidc, pra-lce mo ridi , or motal t o a diea ar cad i actor.Th ct o a actor that rduce th poab il t o a adroucom ca qua d b th lati k ductio ( RRR ,h aoute r reduco ( ARR ), ad th umbr edd otat ( NNT ) (bl I l l ) . Th c o a actor that cra h

probabii t o a adr outcom ca b qua tid th a-ti r k cra ( RR I , h abou r i icrea (A RI ) ad humb dd o ham ( N ) ( Tab I .

Outcmes Assessment

Proc rer o he medical care that a pat ci whaoutcom rr to th ul o that mdcal ca. Th empha

o th outcom amet momt ha ee patdridoutcom am Outm mau icud gc mea -u cod o pciic maue ad maur o patataco . Gec mau uch a h hort om36 ( 36), a ud to a halth atu or hea hrelaed qual t ol a ba ed o the Word Hath Ogaat o' mu p e-doma di io o health . od t o pec c mau reuch a h Itrat oa ocumtat io Commi ee( K co or th oat houlder co ar ued oae apct o a pc i c codit o o od tm. au opat t atiacto are ued to a aou compoet o caread hae dere appicato cu dg h auaio o qualo ca, hathca re deer, pati ctred mode o care,

ad cotuou quat mpoem _Th proce o delopg a outcome um

o dt i ig h cotruct dei g tem ca g -po cg m, ormg actor, ad creatg ca e . Alarg um o oucom trum ha dopedad ud wihout oma pchometric aemet o hei rel -abilt aidit ad rpoi to chag. Relini!ity erto th rpatabilt o a trume. terobserr relinbilitya d it obsrr rlinbility e to th repaabilt o the i -umt wh u d b d e oer ad th am e ob-rr at d t m poi rpctil Test-retest reinbilityca ad b ug h trumt o aluat th ampa o wo d rt occaio withou a ta chag h pati' medica au. Th ut a uuall portdwh u o th knn tatiti o i aca corlatio co-cit \nliiy r o whh th it um ma wha tppor o maur ott vnliity ae whhr a i -trum prtati o h chaacttic eg maurdaccodig to xpr coeu opiio ( ace ald t . riterionliiy a a itrumet ' rlatiohp to a accpdgoldadad iumet ost t ' iity ae whhera t umt ollow accptd hpoh ( co truc ) adpoduce eult cot with thoica xpca io Re-po i to chag a how a um' auchag o th da cou ad tamet.



613

T 1 1 1 ) O L' I { A I tH B o : - n & ) O I l S u iUd R Y B { ;Vo l L .\ c 86 - A NU 1 HR 3 i A R U

( 1 1 : I E P 1 1 > ,\ 1 1 0 C ' 1 > B I O 1 1 1 1 ' t P R 1 R H R I CI I P 1 S R . 0

TABLE IV Sttisticl Tests fo Comprng Independent Goups nd Ped Smples

Typ o Dt

Continuousorml

on-noml

orml

onnoml

rdil

Nomil

Sul

Nmbro Groups

2

2

3

3

3

2

3

2

Indpndt ops

Sudnt tst

MnnWhiny U st

Anlysis o n

KruskWll s st

Mnn-Whitny U s

Krusk-Wl l is st

Fish xt ts

Prson h -sq tst

Log-rnk ts

Prd Smpls

Prd t tst

Wiloxon sgdrnk tst

Rd-msurs nlyss of ri

dmn tst

Wiloxon sgnd-rk tst

Fdmn tst

MNm r tst

Cohrn Q tst

Condtionl logst rgrssion

vdence-Based Medcne appaia w cliica xpe ad te patiet ' ie alea d circmac " " . T typ of t io aked eidecebad mdic ar orgro d to pa ig to pcckowldg abo t maagig pati wo ae a particla di -order idec i graded o e a of dy deig e Table[ Lee of idece for imary Reeac Qeto I i trc-tio to tor of t i of e ul wit a empaio radomied ciical ia ad ca be od i e d ece-aed daaba Eidece Baed Medicie Reiew BM R fom Oid Tcologie te ocrae Daabae of Sytematic

Eice-bnse mece (EBM) o cocietio, x-plici ad dic io of crt bt dc ma kig de-ci io abot te cae of ididal pa et decebadmdc iegrate e et reearc edece wt clicalexprte ad pati al e. Te ep o dcead mdi-cie ole cortig d for ifomatio ito a awe abe qeo ackig dow te bet e dece o awertat qo; critcaly appaig t idc wt rgard ot aidi y mpact, ad appicabi lity; ad tgatig t crtca

Operaive

Acue Achies Tendon Ru I Operatie : 6_521Nonoperativ,-

4

We

Moderate Compcaion

Ml d Compcaion

3

We

3

ajor Compcation628

Moderate Complcaion

Mld Compicaion

1 7 .90 ; p=0 .66 I 60; P oo8lI t .oo; P = o.03ol 3 50 ; 008I 4.70 P = O. 73l 1 .oo01 t .oo 3 . so4.70

xtd- l d sion n yss tr or oti rss nonort mngmnt o Ah s

ndon rupt'. isio n nods r prsntd by srs h n nod s r prstd by i rls

nd trmi nl nod s rsntd by igls Mn otom uti lity sors r li std o th right o

th mn nod 0 o 10 utom obbilits r listd ndr th trmn nod til 0 o . p

ti rtmt is ord bus t hs h ighr xtd l 65 omd wth 68 .



614

) O L' R N M OF B O E & j O I T L C J B J > OR CV O U f 86- A J , . R 3 A R C I 4

Rviws Bs Evidnc, Clinca vidnc Natona GudlnClarnghous, CancrNt and MUNE and vidncbasdjouals (vicBn dici and AC ou nl Club

ytmni viV is a suay of th dcal l traurn whi ch xplic it t hods ar usd to prfor a horough ir-

au sarch and crt ca appaisa of studis. A spcaid tyo sys tatic viw s 1 tn - yi in wich quant i ta ivhods a usd o cobn th rsults ofsvral indpndntstudis usualy randoizd ci nica trials to poduc su-ary satstics. Fo xapl a sudy hat systacally rvwsth ltatu ( wt ci tia fo inclusion and xcusion o st ud -is for rports copa ing n ta LXatio n and a hrolasty orth tatn of ora nck actus and thn suarzsth o ucos and cpica tions is considrd a systatic vw n t ot a nd a study in which th invsgators sys-atically rviw h li tatu with crit a or ncl usion andxcluso n of studs a nd thn coi n th patint data o pr-for a nw statisca analysis s considrd a a an aysis" .

Cli nical pathways or c/iinl pct ic guidli CPG ar agoith s that a dvopd, on h basis o th bst availab v -dnc o standardi procsss and opii oucos yay aso pontia lly duc ros of osson and cosson ,rduc varaons in pactic attns and dcras costs

Dciio nnlyi s a thodoogica oo hat alowsuan tiatv vauat ion of dcson aking undr condiions ouncrtanty . h ational undryng x ict dcis on anal -ysis is that a dcson ust b ad, on undr crcustancsof uncrtainy, and a ational dcsion hoy otiis x-pcd vau h pocss of xpct dvalu dcision an aysisnvolvs h cation of a dcision t to strucur h dcsonpob, dtrin aon of outco obabil ts and u itis( patint values ) , fod-back anaysis o calculae t expecd

700

690

680

60

660

650

60

I I \ 1 P I I 101. 0 (' A i I A I " I :

R I R H l R 0 R T O A I l S R ( O >

valu o ach dcsion path o dtrin th oti a dcison-akng satgy ig. , an d sns t vi y anaysis to dtrnth c of varying ouco robabi l t is and u i i is ondcis ona kin g g . 5 ) . Dcs on anayss can dnti h o-al dcs ion stratgy and how this stratgy changs wt

va a t ons n ouco robab iis or pain valus his ro-css, whr usd xict ly or plicity, ingats w wthth nwr docorpatint odl of shard dcisio na kn g

onoic valuativ sudy dsigns in dicn ncudost dnicaton sudis costcivnss a naysis costntanalyss and cos -u y analyss . n - ii i i, h coss of roviding h trant ar idnd. n cotctiv n nlyi, h costs and c inica o uco a assssdand rotd as cos r cinica out n cot-bt nlyi, oth costs and ns a asurd n onay unts ncot-utility yi cos and ui ity ar asud and ar r-od as cost p ual iyadjusd lifya (QLY).iosttisticsh sca on whch a characsic is asurd has picatonso th way n wich inoation is suad and analydData can b catgorical ordinal or ont nuous. Cngoinl ntnindicat ys or catgois and can b tho ugh o as coun ts. hcatgoris do no psn an undlyng ordr. xapls in-clud gndr and a dchotoous ys/no succss/failur outco Cagorical data ar also cald nonal daa atgocadaa gnally a dscd in ts of proportons o cnt -ags and ar potd in tals or ar chas. f h s an inhrn ord aong cagoris, thn h data ar oin/ hnurs sn an ord but a no ncssaily o scal x -aps incud cancr stags and inury grads dinal daageerally are also descrbed in ems of roportons or ercen-

peative

+ onopeative

hshd u:

pMoomp_peative = 0 16

+V =

60

Fig. 5

60+

6 0000 00 006 00 0

0 5 0 8

Probabili ty (Moderate Complication- Operative)

eiiy aa lyi or operae er ooperaie maageme o ae Ach e edo

rpure e probabiy o a woud co mplaio rom operaie eame ared o he x

axi. The lie repree he expeed aue for e operaie ad oopeaie deiio Aboe

e hrehod aue p robaby of woud omplia io rom operae reame 6% oop

eaie reame i aored.



615

T i l )O L' R : ,\ 1 0 B : 1 & ) 0 S L' R G f R Y . J B O R CVOl L' \1 86- A N \ B F R 3 f I A RCH 2004

hg . 6

Data dsri btons

ags and a potd n tabls o bar chats. Cotiuous daa aobsevations on a continuum or whch th drncs bPnnumbs hav manng on a numrcal sca. Exampls nclud

ag, wght and dstanc. Whn a numica obsrvation canhav only ntg alus th scal of masumnt s call d dis-cete. Cont nuou s data ar gnrally dscrbd n trms of manand standad dva ton and ca n b rpord n tabs or gaphs

Data can b summaized in tms of masures of cn-tra tndncy such as 1 ea 1ein and 11oe, and n trmsof masus of disprsion, such as rang stnar deviatio,and pcntls Data can b chaactizd by drnt dstbu tions such as th noma Gaussan) distrbuton skwd di s

1 00

90

80

70

L 60Il> 50

40(

30

20

0

0

(55)(5 2)

0

(47)(46)

(43)(36)

2

( 1 1 I C\ L E P I D I O O ; \ A K I J B i l ' I , I I :

A P R I \ r R O R R T H O P A F D C L R C 0 '

t butons an d bmodal dstbutons g. 6 ) .Uivariae, o bvaat, ana lyss asssss th ationshp

of a sngl ndpndnt and a sngl dpendnt variab. Stats

tca tsts fo comparing man s of contnuou s variabls that a normally dstrbutd nclud th Studet t test for o ndpn-dnt groups and th paire t test fo pa d sampls. For contn -uous or catgocal varabls that ar not normally dstrbutd,nonpaamtc statstca tests fo comparng mdans ncudth Mannhtny U tst also known as th \ilcoxo k/1 1 test to compar to indpndnt groups and th Wilcoxosigedk test to compar pad samps (Tabl I V) . Aalysisof ariace (ANOV) s usd to compar mans of thr or

- Non-Fractue Pathologic actue

Logank tes 5. 19 , P 002

(33)(28)

3

(29)(25)

4

(23)(20)

5

Time Snce Surgey [yeas]ig 7

Kapan -Me ier estiated survivoshi p cuves comparng surviva ates between patents who had

osteosacoma with a pathoogc racture and those who had osteosarcoa withot a racte"

e estimated ates were sign cantly owe or patents with a pathoog c ractre ( log-an k

test = 519, p = 002). he erro bars arond te suvivorshp cuves repesent 95% condence

ntervas derived by Greenwood's forma Te n mbes of patients on wom the estiates were

based are sown n parentheses



T ) l R ' I l l l l & ) R t , R \ B . l R L ,\l l l \ 86- t\ \ B R 3 I R 2

more independent rops n whch the data ar normal dis -tribted. he main rsut is he tes which ieds a p alue indicatn whether there is an oerall sniican direnc odetermne i hr ar sinican dierences btwn in didal rops posthoc tess ar sed to per orm mti pl e par wise

comparisons betwen t he rops; these ests i ncu d the Bon-rroni uk, NwmanKus, Sch Fishr, and Dnnetpocedures he KruskaWa s test is used to compar media nso hree or more indpendent ops in sitations where thedata do not olow a normal distribution. he rskaastes is a non paramtric alteatie o an asis o ariance. Re-peaedmeasres anasis o ariance is sed or norma distributed ariabls when the stud has matched subjcts. henonparamtric test to compare medians amon thre or morematchd rops is caled he Friedman tes.

Statstica tests used to compare pr opoi ons or caeo r-cal or ordna arabs incude the Pearson chisqar tst orwo or more i nd ep nde nt roups and the Fsher xact test when

expected ce requncies ar sma e or ess). or matchedsampes, the cemar tes i s sed or two ariabls and the o-chran Q test is sd or hree or more ariabes Tab I)

Statistica sts ha ar sed to deermin associationsn cde the Pearson productmomen crreaton r) or nor-ma distrbted contnuous arabes Spearman rankordercrreaion rho) o nonparamtric ariabes, and endalrankcorreation or ordina ariabes

Suriorhi nnyi is used to ana e data whn the out-come o interest is the tim u n il an eent oc curs. A rop o patients is olowed to determine i the experienc th nt ointerest. he end pont n suriorship anass can b morai or a cli nica e nd p oint sch as reision o a tota join replace-ment aent is censored when the een o interest os notoccur to that in di d ua drin the std pr iod urial is theenth o me rom a patients entr ino he stud nt theeent o interes or unti the time o censorn. Th sratime or each patient s rare known when a sria cure isconstructed Insead the enth o time that the patents oaljoint replacement has sured so 1 or the enh o ime thatit sried beor it had to be resed s nown n patienshae not had a aiure at the end o the std perod bt remanat ris or are in the uture hese ar exampls in which in -ormation is censord because sa me s partia ob-sered Surorshp data ar pica anaed with s o theKn ir productmit method in which the surorshipreedom rom the n) s cacuated eer me tha an eentoccurs bt no at censored mes KapanMr analsis issed when he actua dae o he end point is known. nd pointsthat hae no ben rached are treaed as censord at the date oth as ol owup or he anass Surorship anass prodces a e tabe showin the n umber o i u rs occurr in within me interas and th nmber o patiens withdrawndr n the in tra surorshp cure can be p lottd o i us-trate the percenta o patiens ree om alue ntre ) onthe er ica axis an d the oowup time si nce h e srr o n thehornta axs Fi. 7 he 9% cndence ntras can beconsru cted arond the cure a seected mepoins with us

616

C L \ I E 1 0 ( ( ' l ' l \ l l l : R I \ R 0 R I \ I L U 0

ornwoods ormla Sriorship or d erent rou ps canbe compard b the lorank est or comparin the eqalit ohe crs .

Mutirite nyi expores relationships beween mu -tpe ariabes Regrio s a mehod o obanin a mathe

matcal reationship between an ocome ariab ( Y ) and anexpanator ariabe X) or a set o indepen dnt aiabes s) Linear reression s used when he oucome ariable is continu-os with he oa o n di n the ne that best predics Y m tipe reression ts data o a mode ha denes Y as a nci on o two or more exp lanator ariabes or pre dictors. Loisticreression s sed when the outcome ariabe is bnar or d -choomous, and it has become the most common orm o m ultiariate an alss or no nimereated otcomes Other reressionmethods ncd imetoeen daa Cox proportionahaardsreresson) and count data Poisson reresson) Reressonmode n s commonl sed to predict outcms, or t o estabshindependen associations conroin or cnoundin and

ienriy amon predcor or explanaor ariabes. For exam -ple lostic reression can be used to determne predcors oseptic arhr is rsus trans ient S}noits o he hip in children onthe basis o an arra o presentin demoraphc aborato, an dimain ariabes Simar linear reression can be used todeermine indpenden determinans o paten otcome measured with use o a continuous outcome ins rment . Becauseman arabls suall i nuence a partcua outcome, it s necessar o s mutariate analss he primar oa o mut ariate anasis is o ideni rom amon he man patent andsurica ariabls obsered and recorded, hose most related othe o ucome Mos mtiarate anases enerate a tremendosamount o inormation, and proper interprtaon reqires ex -per ise It is an adantae to hae a coeaue rai ned n stat icalmethodolo i nold n the mltiariae anass

OverviewEp idemoo and bostatisics are he essenal oos o clinical research. An ndersandn o std desn hpohesstesin, danosc perormance measures o ect oucomesassessment edencebased medicne and bosaisics is es -senta boh or the inestaor conductin cinca researchand or the practitioner nterpretn cincal research repors

NOTE: The authors thank Dr. Jams Wght ad Or Rbrt Marx for 1e r costructve coets

;inder S Kocher, ID, Davd !akow P Departe of Ortoaedc Surgey, C ld e\ o>p ta 30 0 Lo gwood Aeue Bmton, 021 1 5 - addT'' or oche: n d . oce c dre r rd d u

e or dd no ecee grt o obde fnd g po of I eh o repao o cp t. e dd o ecee y

et o oher ee> or coen o agee to ovde uceeb o coc n o coc e y d odected, o ageed o p ay o d ec a y e o a y each fu dfoudat o, educat oa t t o o ote car ae o onpro toga o w wc e au o ar aed or ,1"oc ia 1d .



T i l ) O U : I 0 B I & ) 0 1 : I SL'RC FRY l R \'OL 1 86- N \ ! 1 3 J\A RC I 20 04

617

( 1 1 : I C A E P J D I I O L O , y - B I ' .\ I , I U :A R I R l R R "I I O A I S R 0

Glossary

Absolute sk rduc on ( A R R ) : Di ffn n i f avum wn xpmna an n papann a a

Ah ( ty- ror : E n yp i es ng w a gn fan aia in i fun wn n u s gnfan aan ( jng a u nul hypohss) .T alp a lvl f ai al sgnfcancal y ( p < 0.05 y nvnn)

Ayss o c (A NOVA) : Sas ca mpaman am ng m gp ( F )

t ( ty- ! ) ro: E n yp es ing w ngn fan aa n fn wn i a gnfan aiain (jng a u alayp)

s: Syma n gn nu f a suyia an val y f uy

d: Elmn f uy gn n w pa n an/n ves gao rs n nw w n amn gpan w i in nl gp. T m 1nski1g fn

Cs-coo study: pv vana uy gna nvv n fyng cases w m f n an n wi u m an n lnga f y a xp f ns

Cs ss: pv vaina l y gn a a f pa n w an m f n w av ngn a pa a amn T n n gup.

Ctorc dt: aial w alu a ag ( nm

na via, qul a v aa ) .Csod dt: I n vivp analy an obsvaon w

um nn wn au pa n a n vn f n n ng n g flw

C- squ tst: Sas ca mpa ppin agial aa wn gup

C c prctc ud n (CPG ): ymaal y vp ina mn ign aniz procss f a an p m m f a fsp cf l n al iman

Coor su dy: pv ovana l suy gna nvlv i n fan f a gup gpw xp nin f in an n

fl lw g up gp fwa f u mf nes

Co: n mivaa anayi w m inpnnvaa a a n inpnn f a

Codto pobl ty: al y f an vn g vn aan vn a u

Codc tel (C : Q u a n pcson f mamn uualy p a 95% nfnnval w ang f valu wi n w i a 9% pa l y a valu i

Cofoud: A vaa a has npnn assocaon sw pnn an npnn aialu pnal y song n p.

Cosuc l dty : ym ppy f an um numn assssng w ns men fl lw ap yp (n)

Con l dy : ym ppy f an m n umn assssng w n umn pnai v f aai ng measur ( fa val y)

Co uous b: aal w valu a n umal na n nu m a of qual nval an a l av fan ( inva a numal , quana aa)

Coo for: Tm esc r be wn nfnngvaa a a n gn ana y f a yin mn im nfni ng

Corr on : ma f an p ng f aia in wn w vaa .

Cost t nyss: Enm valuain f nania mpa w h n a ma inmnay n T ul p a a a

Cost-ctss yss: Assesss n coss an l n a lm T rsul pd a a a f p lin al m.

Costdtcto yss: nly n a n mpnn f an nvnn. l p nmnay n

Costut y yss: n f nvnnan pann u il y f um. T ulfqny p a p qal y- aj se l fya (LY).

Cort: n xplanay nfning vaia n a a uy

Cto dty : ymi ppy f an m numn ng la n p an ap "g ana nsmn .

Cosso study: p xpimna l uy gn a nvlv a l ain f w m exprmnal a mn, n a n a pif anm am gup f pan

Coss-scto study: sainal uy gn a a a n ppula n a a ng l pn n m f xpu an um (y)

cso yss : pplaon f xp quan av m a anay pai ly an u l y f m n a a n n n n f una ny

nd r bl: um pn vaal sct sstcs: Sa, a man sana a

n ppn, an a se a f aa.scr sc Sal mau vaabls a a n

g vauesst buto: a an fqny f a aal ( aan

nmal skw ) ct s: T ma gn u f a ffn ni

l n al ly manngful I n pw anayi mn qu ampl

dcsd dc ( M) : Consc en os, xpl an j u f un n n m akng n au a f n vual paens



T i l ) < R .\ 0 1 lh: 1 & 0 ' 1 S L ' R . R Y I B O R ;01 L '\ N L 5 , R C /

Expermental study: ud dign n w c rn i ocd r l

Factor anaysis : i ic l od for nlzing ion-ip o ng of v b l o drin n dr ngd n ion .

Faure: Gen ric r d for n evn.sh er exact test: i ic d o copr poporion

in di wi pl iz.Hypotess: A en b ccpd or rcd on

bi of vidnc n d.Incdence: Proporion of new c of pcifc cond io n i n

popl on i du ing pcd i n rvl .Independent events: Evn wo occ rrnc no ffec on

p robbi i o f c o rIndependent varabe: Vrb ocid w ouco

of in con ib inforion bo oco in d diio n o providd b or vribl con-drd ino.

I ntenton-to t reat anayss: Mod of ni n ndozdc l n c l i n w i c p n rndo gnd o reen group r nlzd in n gropw or no rcved r n o copde d

Interacton: Relon ip bn wo indpendn vr blc y v diffrn ffec on dpndn vrbl.

Intea consstency: Pycorc p rop of n oucon rn rgdin g dgr o ic indv du i r rd o c or.

ln terobserver reabity : R ib l bewn rnd b o obrv.

Intraobserver reliabiity: Ribi l y bwn rnde b on obrve o d ffrn poin i n

Kap anMeer method: ic od ud n rvivor-ip n o i rviv r diffn i

appa statist c: iic d o ur inrobvr ndin robrvr r ib i .

Lkeood ratio (L R) : l iood gvn rloud b xpcd n pn i cond o n co-pd i l i iood n p in w ou con-di ion I i o of rpoi iv r o fpoiiv e.

Log ran test: S i ic ud o copr wo rvv c vwi cnord obv ionLongtudinal study: d n c pn i fo -owd ov p poin n i e

Matcng: Proc of in g o gop oognou forpoib con fon din g fcor

Mean: M of cnr ndnc. I e u of vdvidd b n br n p

Medan: u of cnrl ndncy. I i idd ob-rv ion 50 prcn i l

Meta-anayss: An vdncbd c rviw u qun i iv od o cobin ul ofevrl i ndpndn ud e o ode i c

8

C : ( .\ E'l . \ 0 ( ) ( ; y : i



T l ) o L R .I 0 B t & ) 0 1 S " , R Y

\'1 D 86 - A Jl " \ 1 R 3 A R C 2004

Receiv opeati ng chaacestic ( ROC) cve: Gaph showng he es 's pefomance as he elaions hp beween heue- posve rae and h e fase posve ae

Regsson Sastcal echnque for determnng he eaon sh p amo ng a se of varables

619

Rela ve isk (R R) Rao of h e ncence of h e dsease or ou tcome n he exposed cohot versus he ncdence in heunexposed cohor (cohor study )

Relave sk reduction ( R R R ) Popotona reucon navese even raes beween expemena and conogoups n a a

Reiab i y Measure of epoduc il y of a measuremenRetrospecve study: The drecon of nqui s backwad fom

he cases he evens trans pre efoe h e su onsetRobus: A stascal mehod n whch he tes statsc s no

affecte y volaon of unelng assumponsSamp: Suse of the popula onScon b as Ssema c eo n samplng he populaonSensivy: ropoon of paien s who have he oucome who

a classfed as havn g a posve esu Sensi vy anaysis: ehod n decson analss used o de

erm ne how vayng dffeen componens of a dec sonree or mode chan ges he concu sons

Skewnss: Sa isca measue of the asmme y of he ds buon of values for a vaia e

Specificiy: Poporion of paen s w hou the oucome whoae classfed as havng a negatve esul

C l I E P ! O i 1 > I I l "

A R R O R R O P R O

Sandard deviaon: Descpve sasc represen i ng h e eva on of n vdua l vaues fom he me an.

Suden s: Stas ical es for compar son of means eween wo ndepenen goups

Suvvorsp anaysis: Sascal mehod for anazng meo even daa

Sysemac revew: Evencease summa ry of he medcali eraue ha uses explc mehos o pefom a hoough eatue seach and crcal appasa of sudes

Tes-retest el abi l y: schome c poper of he conssenc of an n sumen a ffeen pons n t me whoua change n saus

Two-tald test Tes n whch he alternatve hypo thessspecfes a deva on from he nul hypohess n ehedecton

Unvara analyss Analyss of he elatonshp of a s ngle nependen and a sngle ependen vaiale ( vaiaeana ss ) .

Uti i y easue of paen desal o prefeence fo va ou s saes of health a n l lness

Vaidy: Degree o which a quesonnae or nsrumenmeasues wha s n ended o measue

Wlcoxon anksu m tes: on paamerc veson of he Su den es I s also known as he ann Whtney U tes

icoxon sgned ank es: Nonpaamec verson ofhe pare es fo comparing means beweenmached groups

References

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2 Oxman AD, ackett DL, Gyatt GH. Uses gdes to the med1cal literatue

How to get started Te Eviden ce-Based Med1c1ne Working Group JAMA.199327020935

3 Davido F Haynes B, ackett D mth R. v1dence based medicine BMJ.

995 30 10856

4 ackett D Rosenbeg WM . On te need for ev idence-based medicine

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5 ackett D Rosenberg WM, Gray JA , Haynes RB, Rcadson W. vidence

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6 taus E ackett D sng esearc find1ngs n cinica practce. BMJ.9983733942

7 Feinsten AR, pitz H. he epdemoogy o cance theapy Clinica problems of satistca srveys Arch Inen Me 969 23 7 86

8 Fenstein AR Prtcett A, cmf CR. The epidemiology of cancer theapy The clincal course data decsions and temporal demarcations Arch

Intern Med 969123 323449 Fenstein AR Ptcett A cimpf CR Te epidemioogy of cancer terapy

Te management of impeect data Arc1 Inter Med 1969144861

0 Wigt G Fenstein AR A comparative contrast of cl inimetrc an d psycho

metric metods for constructing in dexes and rating sca les J Cin Epidemiol1992452018

1 1 Wennbeg J, Gttelson A Small area vaatons 1n ealt cae deliverySiene 1973182:02-8

2 Wennberg , Gtteson A Vaat1ons medcal cae among small areas

Si Am 982246: 12034

13 Wennberg E Deang wit medica pracice vaaons: a poposa for act1onHeath Af (Milwood) 19843 632

4 Wennbeg E Otcomes research the art of making the rgt deci son

Internist 19903126 28

15 Wennberg JE Pactice variaions: why a the fuss lnernis 98 26 6-8

6 Wennbeg E Bun ker JP Banes B The need for assessg he otcome of

common medcal practices Annu Rev Pubi Heath 1980 1 : 2 795 .

Cassn MR Koseco J, Park RE, Wnsow CM Kan KL Merick N

Keesey J, Fnk A oomon DH, Book RH. oes Inappopriate se explan

geographic vaiations n the use of healt ca e sevces? A s tudy o hree

pocedres JAMA 987258:257

8 Kan KL, Koseco Cassn MR, Fynn MF Fnk A Pattaongse N

oomon DH Book RH Measng the clinica appopriateness of the se

of a procedre Can we do it? Med Care 988264522

9 Park RE, Fnk A Brook R H Cassn MR Kan KL Merck NJ Koseco J,

oomon DH Phys1c1an ratgs of appopate d1 cat1ons o r three poce

dues: teoretcal dca\ons vs indcaons used n pract1ce Am J Pubi

Healh 98979445

20 Mienson ML. Demanding media exelene: dotors and aountability 1nte information age. Chcago nvers1ty of Ch1cago Pess 1997

2 Katz J. The N uremberg Code and te Nembeg Ta A reapprasa JAMA

996 2 76 : 6626

22 Word Medica Assocation. Decaration of es1nk1 Recommendaons gding physicians n biomedica research volv1ng man sbjects JAMA 997

27:9256

23 Kocer M, Mandiga R , Mupy M, Godmann D, Haer M, unde! R, Eck-

nd K, Kasse R. A clic a pracce gdeline for treatment of septc arth

tis in cildren effcacy in improvng process of care and effect on oucome of

septc arhrts of the hi p J Bone Join! Surg Am. 200385 9949

24 Kocer M, DCano Zuakowski D, Mcei U. D1agnost1c pefomance

of clincal examination and selectve magnetic esonance mag1ng 1 the eval

aton of nraarticuar knee dsorders ciden and adoescents Am JSports Me 2001292926

25 Kocer M. ltrasonogaphic screeng fo developmental dysplas ia o he

hp: an ep1demioogc analyss (Pat Am J Orhop 200029:92933

26 Koce M Utrasonographc screeng for deveopmenta dyspasa of thep: an epidemologic analys1s art Am J Orhop 2001301924

27 Baron JA Uncertainty 1n Bayes Me Decis Making 9944465


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Documents

Clinical Epidemiology and Bio Statistics a Primer for Orthopaedic Surgeons - Kocher, Zurakowski - 2004