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recurrenceordeathbecause,intheory,theycanovercomemanyofthebiasesthatmayaffect
case–controlorcohortstudies,asdiscussedinthenextsection.
Figure7.4 Cohortstudydesign.
StatisticalInferenceandValidity
Clinicians should understand issues affecting statistical significance and validity to
evaluatestudiesclaimingthatsomeexposurecausescancer,anewtherapyissuperiorto
standardtreatment,orascreeningtestcanimprovemortality.
StatisticalInference
Statisticalinferenceisaprocessofdrawingconclusionsfromdatabyhypothesistesting,
during which a decision is made either to reject or not reject a null hypothesis.
Hypothesistestinginvolvesthefollowingsteps:
1. Observationsaremadeandsummarizedbysomestatisticalparameters,suchasamean,a
proportion,orarelativerisk.
2. Aresearchquestionisstatedintermsofanullhypothesisclaimingnodifferencebetween
theobservedparameterandsometheoreticalvalue.
3. Astatisticaltestischosenbasedonthestudydesignandnatureoftheparametersbeing
studied.
4. The test statistic is calculated, and its associated p-value is read from the appropriate
statisticaltableorgeneratedfromastatisticalprogram.
5. Ap-valuelessthanthetraditional5%leadstothedecisiontorejectthenullhypothesis,
whereasa valuegreater than5% leadsto thedecisionnottoreject thenull hypothesis.
Errorsarepossiblewitheitherdecision.
6. Aconfidenceintervalmaybeconstructedfromthetestresultsanditdefinestherangein
which the true value of the parameter is expected to fall. Precision refers to a
characteristicofaparameterfallingintoanarrowconfidenceinterval,adesirablefeature
oflargestudies.
TypeIError
Thedegree of conflictbetweenthe parameterobservedandthat assumed by thenull
hypothesis is summarized by the p-value, alpha, or Type I error and indicates the
probability of incorrectly rejecting the null hypothesis. In practice, an alpha level is
chosenapriori,usuallyp=0.05;and if the association tested has a p-valuelessthan the
predeterminedalphalevel,thentheresultsareconsideredstatisticallysignificant.
TypeIIError
ATypeIIorbetaerrorindicatestheprobabilityoffailingtorejectthenullhypothesis
when,inreality,itisfalse.Tocalculateabetaerror,analternatehypothesismustbestated.
Power
Poweris1minus the betaerrorandreflectstheability ofastudy to detectan actual
effect. More precisely, power is the ability of a test statistic to detect differences of a
specified magnitude in test parameters. In planning a clinical trial, an investigator often
calculatesthepowerthatastudywillhavetodetectanassociation,givenacertainstudysize
andcertainassumptionsaboutthenatureoftheassociation.Smallclinicaltrialsthatfindno
significant difference among therapies may be cited as evidence of “no effect of therapy”
when the statistical power may have been well below the accepted target of 80% for a
meaningfuldifferenceinresponserates.
StatisticalDistributionsandTests
Therearenosimplerulesfordeterminingwhichstatisticaltestisappropriateinevery
situation.Thechoicedependsonwhetherthevariableisqualitative(nominal)orquantitative
(numerical), what assumptions are made about the distribution of the parameter being
measured, the nature of the study question, and the number of groups or variables being
studied.Forexample,achi-squaretestisusedtotestthenullhypothesisthatproportionsare
equalorthatnominalvariablesareindependent.Theunpairedt-testisusedtocomparetwo
means from independent samples, whereas the paired t-test compares the difference or
changeinanumericalvariableformatchedorpairedgroupsorsamples.
Statisticalinferenceallows one to address the question of whetherchancecouldhave
accounted for the observation. Mostly a p-value cutoff of 5% is used to answer this
question.However,itisimportanttonotethatwhenmanytestsareperformed,someresults
will be observed by chance. One way to address this multiple testing issue, called
Bonferronicorrection,istodividethealphalevelbythenumberoftestsbeingperformed.
Ifthismethodisusedand100testsareperformed,thenthealphalevelwillbe0.05/100or
0.0005. Adifferent bar is required in genome-wide association studies (GWAS), in which
risk predisposing variants are searched for using gene chips that can profile hundreds of
thousands of genetic variants. Typically, genetic variations called single nucleotide
polymorphisms (SNPs) are searched for and may number half a million or more. In such
studies, p-values on the order of 10−8 are common, and external validation is sought by
retestingtheassociationsidentifiedinanotherorevenseveraladditionaldatasets.
Validity
Validity has two components: internal validity and external validity.Internal validity
meansfreedomfrombias. Biasreferstoasystematicerrorin the design,conduct,or
analysisofastudythatresultsinamistakenconclusionandiscommonlydividedinto
observationbias,selectionbias,andconfounding.Theexternalvalidityofastudyrefers
totheabilitytogeneralizetheresultsobservedfromonestudypopulationtoanother.
ObservationBias
Observation bias or misclassification occurs when subjects are classified incorrectly
withrespecttoexposureordisease.Ifmisclassificationwasequallylikelytooccurwhether
the subject was a case or control or an exposed or nonexposed cohort member, then the
observationbiaswould benondifferentialand wouldcausetheRRto bebiased towardthe
nullvalue,1.Alternatively,ifmisclassificationwasmorelikelytooccurforcasethancontrol
subjects or for exposed than nonexposed cohort members, then the bias is differential and
mightresultin afalselyelevated (ordecreased)RR (e.g.,ifcasespreferentiallyrecalledor
admittedtoaparticularexposurecomparedwithcontrolsubjects).
Criteriaforexposureordiseaseshouldbeclearlydefinedtominimizeobservationbiasand,
wheneverpossible, exposureordisease confirmedfrom medical recordsor othermeansof
validation. Ideally, researchers recording the disease status in a cohort study or exposure
statusinacase–controlstudyshouldbe unawareofthe subject’sstudy grouporblindedto
key hypotheses. In a clinical trial, observation bias may be minimized by double
blindness,whenneitherthesubjectnortheinvestigatorknowswhichspecifictreatmentthe
subjectisreceiving.
SelectionBias
Selectionbiasisanerrorthatresultsfromsystematicdifferencesinthecharacteristics
ofsubjectswho are andarenot selected forstudy. For example, a selection bias might
occur in a case–control study if exposed cases did much better or worse than nonexposed
cases.Ifthe case group consisted of long-termsurvivors,thenthey might have a different
frequencyoftheexposurethannewlydiagnosedindividuals.Selectionbiasmayalsooccurin
theprocessofselectingcontrolsubjects;forexample,controlsubjectsmightbeselectedfrom
hospitalizedpatientsinadiseasecategorythat may, itself,relatetotheexposure.Selection
bias is less likely to occur in cohort studies since cases and controls are from the same
underlying population or in population-based case–control studies, where most cases in a
particular area are studied and representative controls are selected from the general
population.
Confounding
Confoundingoccurswhensomefactornotconsideredinthedesignoranalysisaccounts
for an association because that factor is correlated with both exposure and disease.
Potentialconfoundersforanycancerstudyareageandrace/ethnicity.Confoundingmaybe
controlled during the design of a study by matching cases to control subjects on key
confounding variables, or during the analytic phase of the study by stratification or
multivariate analysis. Stratifying means examining the association of interest within
groups that are similar with respect to a potential confounder, whereas multivariate
analysisisastatisticaltechniquethatcontrolsforseveralconfounderssimultaneously.
Inaclinicaltrial,confoundingisoftenaddressedbyrandomization;thatis,subjectsare
allocatedtotreatmentgroupsbyachancemechanismsuchthatprejudicesoftheinvestigator
orpreferencesbythesubjectdonotinfluenceallocationoftreatment.Inpractice,participant
randomizationassignmentscanbedeterminedusingcomputer-generatedrandomnumbersor
randomnumbertablesfoundinmoststatistictextbooks(11,12).Theinitialtableinthereport
of a clinical trial usually shows how the treatment groups compared with respect to age,
ethnicity,orotherimportantvariablestodemonstratewhetherrandomizationindeedbalanced
key variables. Similar tables are helpful in case–control and cohort studies to identify
potentialconfoundersanddescribethecharacteristicsofthepopulation.
OtherCriteriaforJudginganEpidemiologicStudy
Besides the important exercise of ruling out potential biases in a study, other criteria are
invoked to decide whether an epidemiologic association is likely to be causal. The wellknownBritish statisticianSir Austin BradfordHill iscreditedwith establishingthe criteria
thatepidemiologistsoftenuse injudgingwhetheranassociationislikely tobecausal(13).
Hilloriginallylistedninecriteria,whichhavebeenrestatedovertheyears,butinoneformor
another, are considered when regulatory or legal issues arise in connection with an
epidemiologic association. The following criteria are most important: temporality,
consistency, effect of removing the causal agent, strength of the association, dose–
response,andbiologiccredibility.
Temporality
Thatexposureprecedesdisease(temporality)isanobviousrequirement.Asdiscussedunder
“ObservationBias,”subjectsareinterviewedaboutexposuresaftertheirdiseaseisdiagnosed
inacase–controlstudy;therefore,casesmayciteexposuresthatbeganbecauseofsymptoms
ortreatment oftheir illnessresultingin“reversecausality.”Epidemiologistswhoconduct
case–controlstudies generally censor exposures forsometimeperiod priortodisease
diagnosistominimizethislimitation.
Consistency
Results that are in close agreement when repeated are said to be consistent. In the
contextofanepidemiologicassociation,RRs that are consistent among studies, especially
those in which different study methods have been used, provide evidence for a causal
association.However,thepossibilitythatasystematicbiashasaffectedallthestudiesshould
beconsidered.Consistencycanbeassessedinaformalmannerbyperformingastudycalled
ameta-analysis.
Inameta-analysis, resultsfromindependentstudiesexaminingthesame exposure(or
treatment) and outcome are combined, so that a more powerful test of the null
hypothesis may be conducted. As part of the meta-analysis, a test for heterogeneity is
performedtoindicatewhethertherehavebeenanystatisticaldifferencesamongtheresultsof
differentstudies.Themeta-analysishasbecomeanimportantcomponentofevidence-based
medical reviews. For example, oral contraceptive use was less common in ovarian cancer
casescomparedtocontrolsin45studies;whentheresultsofallstudieswerecombinedina
meta-analysis, women who had ever used oral contraceptives had an estimated 17%
reductioninovariancancerriskcomparedtowomenwhohadneverusedoralcontraceptives
(14).
RemovaloftheAgentResultsinaReductionofDiseaseFrequency
Indiseasescausedbyinfection,showingthattreatmentoftheinfectionorprotectionby
vaccination cured or prevented the disease would satisfy this criterion, and has been
clearly demonstrated for HPV vaccination and high-grade CIN. In chronic disease
epidemiology,this criterionmight beaddressed byshowing acorrelation betweencalendar
year and disease occurrence for an exposure that was relatively limited in time or has
changed over time. The increased incidence of endometrial cancer that followed the
expandeduseofestrogentherapyforthemenopauseandthedeclinethatfollowedthe
addition of a progestogen would satisfy this criterion. The decline in breast cancer
occurrencefollowingtheWomen’sHealthinitiativestudyshowinganincreasedincidenceof
the disease in women using combined hormone replacement therapy (HRT), and the
subsequentdecreaseduseofHRT,wouldbeanotherexample.
StrengthoftheAssociation
A common argument is that an RR or OR of 2 is a benchmark as the minimum for
associationslikelytobecausal(15).Bradford-Hillhimselfsaid:“Wemustnotbetooready
todismissacause-and-effecthypothesismerelyonthegroundsthattheobservedassociation
appears to be slight. There are many occasions in medicine where this is in truth so.” He
citedthecaseofcoronarythrombosisandsmoking.
Theargumentthatriskslessthan2cannotbecausalshouldberigorouslychallenged.
Anoverallsummaryrisklessthan2doesnotruleoutastrongerassociationforcertain
histologictypesofgynecologiccancer,certaincategoriesofexposure,orforwomenwith
certaincharacteristics.Thequestionofwhetheranassociationlessthan2canbecausalis
addressed by recent genome-wide association studies (GWAS), which test hundreds of
thousandsofgenetic variants called SNPs in cases and controls.Genome-wideassociation
studies(GWAS)haverevealed genetic polymorphicvariants that individualsareborn with
that may increase the risk for various cancers, including ovarian cancer.SNPs rs8170 and
rs2363956onchromosome19areassociatedwithORsof1.16and1.18forserousovarian
cancer, respectively. Though the magnitudes of these associations are small, these
associationsarealmostcertaintobereal basedonthreephasesofevaluationinover5,900
casesand13,000controls,andp-valuesof10−9and10
−11
,respectively(16).
Dose–Response
A dose–response (orbiologicgradient) referstoa consistent increase(ordecrease) in
risk,correspondingtoincreasinglevelsoftheexposure.Whetherthereisanassociationis
addressedbyasimple“yes”or“no” answertoaquestionaboutexposure.Individuals who
answer“yes”andhadaparticularexposureshouldbeaskedadditionalquestionsabout the
frequencyanddurationoftheexposure.Tocategorizedose–responseaspreciselyaspossible,
itisnecessarytocombinebothfrequencyandduration,similartowhatisdoneforsmoking
when“pack-years” are calculated(i.e., the numberof packs perdaysmoked multipliedby
thenumberofyearssmoked).Akeyissueincalculatingdose–responseiswhetherthosewho
have never had the exposure should be included in the calculation, or whether the dose–
responseshouldbecalculatedonlyforthosewhohavehadtheexposure.
BiologicCredibility
Biologiccredibilityrequiresthatweaskwhethertheassociationmakesbiologicsensein
termsofwhatisknownaboutthebiologyofthecancerortheexposure,and whether
animalorcelllineexperimentssupportanassociation.Anyepidemiologicstudyclaiming
anewassociationneeds toaddressthebiologic credibilityoftheassociation.Bradford-Hill
cautionedagainstmakingplausibilityanessentialcriterion:“Itwillbehelpfulifthecausation
wesuspectisbiologicallyplausible.ButthisisafeatureIamconvincedwecannotdemand.
Whatisbiologicallyplausibledependsuponthebiologicknowledgeoftheday”(13).
CancerRiskandPrevention
Risk factors for the gynecologic cancers are presented, along with the application of this
informationtocancerprevention.Table7.4summarizesmajorepidemiologicriskfactorsfor
cervical,endometrial,andovariancancers.
CervicalCancer
Invasivesquamouscellcarcinomaofthecervixistheendstageofaprocessbeginningwith
atypical transformation of cervical epithelium at the squamocolumnar junction, leading to
CINof advancing grades, andeventuallyinvasive disease. Risk factorsfor cervical cancer
are those associated with atypical transformation and those that influence persistence and
progressionofdisease.
Table7.4RiskFactorsforGynecologicCancers
Factor Cervix Endometrium Ovary
Sexual Increasedrisk
associatedwithcoitusat
anearlyage,multipleor
high-riskpartners
Increasedriskinwomen
whohavenevermarried
Increasedriskinwomen
whohavenevermarried
Contraception Barriermethods
protective;oral
contraceptivesmay
increaserisk
Oralcontraceptives
protective
Oralcontraceptivesand
tuballigationprotective
Childbirth Increasingriskwith
increasingparity
Decreasingriskwith
increasingparity
Decreasingriskwith
increasingparity
Ageatmenopause Noclearassociation Latemenopause
increasesrisk
Noclearassociation
Menopausalhormones Noclearassociation Increasedriskfrom
“unopposedestrogen”
Weakincreasedriskwith
“unopposedestrogen”
Familyhistory Weakevidenceof
familialtendency
MutationsofDNA
mismatchrepairgenes
increaserisk
MutationsofBRCA1,
BRCA2,andDNA
mismatchrepairgenes
increaserisk
Bodyhabitus/diet Carotene,vitaminC,and
folicacidpotentially
protective
Obesityastrongrisk
factor
Noclearassociation
Smoking Increasedrisk Decreasedrisk Conflictingevidence
Otherexposures HIVinfectionandgenetic
factorsrelatedto
immunecompetence
increaserisk
Associatedwith
estrogen-producing
tumorsoftheovary,liver
disease,tamoxifenuse,
diabetes
Foreignbodies(talc)per
vaginamayincrease
risk;acetaminophenmay
decreaserisk
Factorsassociatedwithatypical transformation largely relatetosexualpracticesthat
increase the opportunity for human papilloma virus (HPV) infection or decrease
immunecompetence.Earlyageatfirstintercoursemaybeimportant,becauseadolescence
isaperiodofheightenedsquamousmetaplasia,andintercourseatthistimemayincreasethe
likelihoodofatypicaltransformation(17).Intercoursewithmultiplepartners,orwithahighrisk partner who has had contact with multiple partners, increases the likelihood of her
exposuretoHPVandcervicalcancer(18–20).Anestimated79%ofwomenareinfectedwith
HPVatleastonceoveralifetime(21),thoughtheprevalenceatanygiventimepointismuch
lower and varies by age, peaking in the 20- to 24-year-old age group at 45% (22). HPV
infection is transient, with more than 90% of HPV infections cleared or suppressed to
undetectablelevelswithin5to7years.However,HPVprevalencestartstoriseatolderages,
likelyduetoreactivationwithnormalage-relateddeclineinimmunefunction(23).
The development of HPV vaccines offers an exciting approach to true primary
preventionofthisprevalentcancerworldwide(24).ThebivalentHPVvaccinestargetonly
oncogenicHPVtypes16and18,whichcauseanestimated70%ofcervicalcancers(25,26),
butvaccinestargetingupto9HPVtypesarenowavailable.AlthoughtheFDAapprovedthe
firstHPVvaccinesin2006andvaccinationcontinuestoincrease,in2013onlyabouthalfof
13- to 17-year-old girls had been vaccinated with at least one dose (27). Consequently,
screeningcontinuestobeanimportantcervicalcancerpreventivestrategy(26,28).
Whilemathematicalmodelssuggestthatmalevaccinationwouldreducecervicalcancer,but
onlyslightlymorethanvaccinationoffemalesalone(29,30),vaccinationofboysaged11
and12hasbeenrecommendedsince 2011forthepreventionofanal,penile,oral, and
head and neck cancers. Although implementation of HPV vaccination has gone fairly
smoothlyindevelopedcountries,thecostofthevaccine(morethan$300forthefullsetof
threedoses)hasmadedistributiondifficultindevelopingcountries,where80%ofcervical
cancersoccur(31).
GiventhehighprevalenceofHPVbutrelativelylowincidenceofcervicalcancer,factorsthat
distinguishthosewomen infectedwith HPVwhowillgoonto developcervical cancerare
important.Smoking isassociatedwith anincreasedrisk forcervical cancer,even after
adjustmentforseveralconfoundingfactors(32,33).Anassociationbetweensmokingand
cervical cancer has biologic credibility, because potentially mutagenic substances are
secreted in the cervical mucus of smokers (34). Furthermore, smoking decreases immune
function which could foster the persistence of an HPV infection (35). In third world
countries,chronicexposuretowoodsmokemayincreasetheriskforcervicalcancerinHPVinfectedwomen(36,37). Current oral contraceptive use is associated with an elevated
cervical cancer risk, particularly for those who have used them for more than 5 years.
However,therisk declinesafter cessation (38).Some have suggested anincreased risk for
women with higher parity, which could be due to hormonally related changes to the
squamocolumnarjunctionorattributabletoconfoundingfactors(39).Withrespecttodiet,
fruitandvegetables,particularly those rich in vitamin A, reducecervicalcancerrisk
(40–42).
Finally,progressionofCINislikelytobegreaterinimmunosuppressedwomen,suchas
thosewithHIVinfection,orafterkidneytransplantation(43,44).Furthermore,genome-
widestudiesofcervicalcancerthatidentifiedgeneticvariantsinthemajorhistocompatibility
complexthatarestronglyassociatedwithcervicalcancerrisk(43,45)lendsupporttotherole
ofimmunefunction.
EndometrialCancer
Cancerofthe endometrium can be divided into Type I cancers, consisting of tumors
with endometrioid histology, and the much less frequent Type II cancers, including
serousand clearcell tumors.Risk forType I adenocarcinomaof the endometrium is
largely attributed to increased estrogen exposure (46). States that lead to an excess of
estrogen over progesterone or to an increased lifetime exposure to estrogen increase
endometrial cancer risk. For instance, early age at menarche and late age at menopause
increase endometrial cancer risk (47–53). Similarly, obesity, which leads to increased
estrogen production through the peripheral conversion of androstenedione is an
importantendometrialcancerriskfactor.Theincidenceofendometrialcancerhasrisen
steadily with the prevalence of obesity and accounts for an estimated 57% of all
endometrial cancers in the United States (54). For the past decade, endometrial cancer
incidencehas increasedby 1%each yearandendometrialcancerdeaths haveincreased by
nearly 2% per year (3). Furthermore, more women are getting endometrial cancer before
menopause,whichmakestreatmentwithhysterectomymorecomplicated(55).
Endometrial cancer as a consequence of exogenous estrogen is demonstrated by the
impressiveevidencethatunopposedestrogenadministeredforthemenopauseincreases
the risk of endometrial cancer in a dose–response fashion (56). Tamoxifen, with its
estrogenantagonisteffectsinthebreastandagonisteffectsintheuterus,hasbeenshownto
increasetherisk ofendometrialcancerinclinical trialdata(57). Alternatively,menopausal
estrogen taken with a progestin has not been shown to increase the risk, and past use of
combination birth control pills decreases the risk of endometrial cancer (58,59). Clinical
trialshavesuggested verylow ratesofhyperplasiaoccurringwith acontinuousregimenof
0.625mgofconjugatedestrogenand2.5mgofmedroxyprogesteroneacetate(60).
Alternatively,protectivefactorsarethoseassociatedwithdecreasedestrogenproduction.
Surgicalcastration at an early age with retentionof the uterus is a strong protective
factor (61). Leanness and regular exercise lower estrogen levels and protect against
endometrial cancer (62,63). Smoking lowers estrogen and protects against endometrial
cancerbutobviouslycannotbeencouragedasapreventivemeasure(64).Endometrialcancer
asa consequence of decreased degradationofestrogen is illustrated bycasereports of the
diseaseinwomenwithcirrhosisoftheliver(65).
Althoughthemajorityofriskfactorsforendometrialcancerarenicelyexplainedbyestrogen
excess, some associations suggest other etiologic pathways warrant consideration. For