A framework provided an outline toward the proper evaluation
of potential screening strategies
Wim J. Adriaensena,*, Cathy Mathe€ ıa, Frank J. Buntinxa,b, Marc Arbync
aCentre of General Practice, Department of Public health and Primary Care, Katholieke Universiteit Leuven, Kapucijnenvoer 33, Blok J,
3000 Leuven, Belgium
bDepartment of General Practice, Maastricht University, 6200 MD Maastricht, The Netherlands
cUnit of Cancer Epidemiology, Scientific Institute of Public Health, Juliette Wytsmanstreet 14, 1050 Brussels, Belgium
Accepted 17 September 2012; Published online 6 February 2013
Objectives: Screening tests are often introduced into clinical practice without proper evaluation, despite the increasing awareness that
screening is a double-edged sword that can lead to either net benefits or harms. Our objective was to develop a comprehensive framework
for the evaluation of new screening strategies.
Study Design and Setting: Elaborating on the existing concepts proposed by experts, a stepwise framework is proposed to evaluate
whether a potential screening test can be introduced as a screening strategy into clinical practice. The principle of screening strategy eval-
uation is illustrated for cervical cancer, which is a template for screening because of the existence of an easily detectable and treatable
Results: The evaluation procedure consists of six consecutive steps. In steps 1e4, the technical accuracy, place of the test in the screen-
ing pathway, diagnostic accuracy, and longitudinal sensitivity and specificity of the screening test are assessed. In steps 5 and 6, the impact
of the screening strategy on the patient and population levels, respectively, is evaluated. The framework incorporates a harm and benefit
trade-off and cost-effectiveness analysis.
Conclusion: Our framework provides an outline toward the proper evaluation of potential screening strategies before considering im-
plementation. ? 2013 Elsevier Inc. All rights reserved.
Keywords: Cancer screening; Screening evaluation; Cervical cancer; Screening strategy; Harm benefit; Framework
Almost 40 years ago, Wilson and Jungner , for the
World Health Organization, formulated a number of criteria
(called ‘‘principles’’), which a screening strategy should
meet. One of the criteria was that there should be a suitable
of the target disease. Unfortunately, still no comprehensive
guideline exists concerning the assessment of screening
strategies. Moreover, the specific context of screening ap-
plied to large groups of apparently healthy persons among
whom the disease usually is rare, makes the evaluation of
screening strategies a difficult, delicate, and costly exercise.
In this article, we propose a comprehensive framework
for the evaluation of new screening strategies, using cervical
cancer screening as a case example. When dealing with
terms such as screening tests, strategies, or programs, clear
definitions should be made. Evaluation of a potential screen-
ing strategy, involving a new screening test, comprises the
test, patient, and population level. Generally, it includes
the determination of age ranges and screening intervals
and assessment of its cost-effectiveness. Although the effec-
tiveness of a screening program depends on the properties of
the screening test itself, other factors including natural his-
tory of the disease, screening organization, level of partici-
pation of the target population, compliance with follow-up
and efficacy of workup, and treatment of the screen-
detected lesion also determine the success [2e5]. The eval-
uation of screening programs in all their aspects, however,
lies beyond the scope of this article, which focuses on the
evaluation of new screening strategies.
Our reasoning starts from the assumption that before
a possible screening strategy is considered, a clear decision
has been made on the exact aim and the general target of
the intervention. The aim should be formulated as the net
benefit for the screenees and in terms of avoiding
Conflict of interest statement: the authors report no biomedical finan-
cial interests or potential conflicts of interest.
* Corresponding author. Tel.: þ32-1633-2730; fax: +32(0)16 337 480.
E-mail address: firstname.lastname@example.org (W.J. Adriaensen).
0895-4356/$ - see front matter ? 2013 Elsevier Inc. All rights reserved.
Journal of Clinical Epidemiology 66 (2013) 639e647
What is new?
? The development of a comprehensive framework
building further on the existing concepts, based
on a stepwise evaluation process including a harm
and benefit trade-off and cost-effectiveness analy-
sis of the screening tests before introduction into
clinical practice as a screening strategy.
What is the implication and what should change
? New screening tests should go through a proper
evaluation process before considering implementa-
tion as a screening strategy, to avoid doing more
harm than benefit.
worsening public health. The broad target population can
be, depending on the target condition, either an age and
sex subgroup of the general population or a high-risk sub-
group, for example, people working or living in specific
conditions or exposed to risk factors . These general
ideas will guide the researcher to precise screening inter-
vals and target populations chosen for the individual obser-
vational studies and trials.
1.1. Methodological considerations that are specific for
the evaluation of a screening strategy
When people actively present with a health problem that
requires treatment, they accept that the diagnostic process
or treatment carries some risk of inflicting harm. When
the same processes are applied to healthy people, the ac-
ceptable level of risk is much lower. Additionally, motiva-
tion for screening often is encouraged by invitations and
often includes some degree of social pressure.
1.1.1. Cervical cancer screening
Screening can effectively prevent cervical cancer. The
International Agency for Research on Cancer estimated that
well-organized cytologic screening for cervical cancer pre-
cursors every 3e5 years between ages of 35 and 64 years
can reduce the incidence of cervical cancer by 80% or more
among the women screened . Nevertheless, cervical can-
cer was worldwide the third most common cancer in
women and the fourth most common cause of cancer death
and even the most common cause in many developing
countries in 2008 . It occurs at a relatively young age
when women are actively involved in their careers or caring
for their families, resulting in proportionally more life-
years lost compared with most cancers . The rationale
of cervical cancer cytologic screening is to identify and
treat high-grade cervical intraepithelial neoplasia (CIN) or
precancerous lesion and prevent its progression to invasive
cancer. The mean time of initial dysplasia to invasion is at
least 10 years, and the probability of detection increases as
the preclinical phase progresses [9,10]. Removing these
precursor lesions is effective in avoiding progression to in-
vasive malignancy. Although screening for cervical cancer
is well established, there were until recently no randomized
clinical trials to demonstrate its effectiveness. The observa-
tional evidence, however, showing a reduced incidence of
and mortality from cervical cancer is widely accepted
[11,12]. The recognition of a strong causal relationship be-
tween the persistent high-risk human papillomavirus (HPV)
infection of the genital tract and occurrence of cervical can-
cer has resulted in the development of several HPV detec-
tion systems providing new preventive strategies that could
potentially result in an even greater reduction in incidence
and mortality than cytology.
1.1.2. Outcome of screening
The main purpose of screening is to reduce the disease-
specific mortality. Therefore, the primary indicator of effect
is the observed disease-specific mortality compared with
the expected mortality in the absence of screening, best ex-
pressed in terms of absolute risk difference or its reciprocal,
the number needed to screen. In addition, several alterna-
tive end points can be used as a proxy. Table 1 shows a list
of indicators used to establish effectiveness of cervical can-
cer screening ranked by decreasing level of evidence .
Studyingcervicalcancermortality isparticularly difficult
because the certified cause of death often does not indicate
the exact anatomical origin but rather is indicated as death
from uterine cancer. An alternative end point can be all-
cause mortality as has been advocated for breast cancer
, but a significant effect on all-cause mortality is rarely
demonstrable with screening. In cervical cancer screening,
vical cancer incidence, is a convincing end point, but reach-
monitor over many years. CIN3 as a direct precursor ofinva-
sive cancer is an acceptable proxy outcome of effectiveness
. The increased detection of CIN2þ or CIN3þ is clini-
cally not so relevant as they rarely progress to cancer ,
leading to overtreatment. Consequently, outcomes 6 and 7
in Table 1 should not be targeted by a screening strategy.
1.1.3. Screening for low-prevalent diseases
Contradictory to most diagnostic studies, in screening,
the prevalence of disease, especially for cancer, is typically
low. This has an impact on the predictive values. Sensitivity
is an indicator of the proportion of detected and missed
prevalent predisease and determines the effectiveness. A
very high specificity is needed to minimize the number of
false-positive test cases. However, a high specificity can
still be associated with high absolute numbers of false-
positive test results (and thus anxiety, costs, and additional
procedures in a lot of people) in case of low prevalence, for
640 W.J. Adriaensen et al. / Journal of Clinical Epidemiology 66 (2013) 639e647
instance in a population that is well covered by HPV vac-
cination. A sensitivity and specificity of 90% can relate
to around 78%, 92%, and 97% of false-positive results if
the outcome prevalence is 3%, 1%, and 0.3%, respectively,
proportions we are dealing with in screening situations.
1.1.4. Benefits and harms of screening
What should a screening intervention in healthy people
achieve? With regard to cervical cancer, people who profit
from screening are those who (1) would have died of the
cancer but are cured, owing to earlier detection; (2) would
have been successfully treated for their cancer anyhow, but
whose quality of life is improved owing to earlier detection
(down staging) and less mutilating treatment; and (3) do not
have a cancer or cancer precursor and are reassured by the
negative results of a screening test that correctly shows that
they do not have the disease.
However, screening can also be harmful. People who
might be harmed by screening are those who (1) die from
a screen-detected cancer and whose clinical course was not
improved by treatment; (2) have cancer that normally would
have showed up clinically at a later point of life, but whose
mortality and morbiditydo notdiffer compared with without
early detection; (3) have screen-detected nonprogressive
treatment; (4) have cancer or progressive precursor but have
of security and delayed effective diagnoses and possibly de-
layed diagnosis and treatment; and (5) have a false-positive
result, which results in anxiety or unnecessary further inves-
tigation and treatment. A screening strategy may cause both
benefit or harm [2,4].
1.2. Important biases in studies that evaluate the effects
mortality (or incidence of overt disease when the screening
targets preclinical disease) as the outcome and intention-to-
treat analysis is the only study design that allows unbiased
comparison ofoutcomes inscreened andunscreened groups.
All the observational studies are prone to biases, which
can be summarized into two broad types of bias: selection
and information biases. There are, however, some biases
particularly important for studies evaluating screening strat-
egies. In observational studies comparing screened and
unscreened people, those whose disease was diagnosed
through screening can appear to survive longer than those
who presented with symptoms, even if there is no benefit
from screening. This is caused by clinical symptoms pre-
senting later in the natural history compared with abnormal
screening results, which is called ‘‘lead time bias.’’ In addi-
of screening are more likely to be indolent, slow growing, or
less aggressive than tumors in nonscreened patients who
present with symptoms or in the interval between two sched-
uled rounds of screening (interval cancers). This phenome-
non is referred to as ‘‘length bias’’ and results in the false
conclusion that patients die less or later if their cancer is
detected by screening. Overdiagnosis is an extreme more
general case of length bias: it refers to the detection of non-
progressive (pre)disease, which would never have caused
overt disease. This results in unnecessary treatment and, at
the very least, cause anxiety and possible adverse effects
[17,18]. Whether a screen-detected predisease is an over-
diagnosis cannot be determined in the individual case.
In the case of HPV-based cervical cancer screening, for
example, the extent of overdiagnosis can be estimated from
randomized trials, in which an initially elevated incidence
of cancer or precursor in the HPV arm during the first
screening rounds persists during subsequent years or
screening rounds [6,19].
In a diagnostic study, all subjects, test positives and test
negatives, should receive the reference test or gold standard
to assess the accuracy of the test . However, in screen-
ing, because of ethical or cost considerations, especially
when the ascertainment of true disease status requires inva-
sive testing, either none or a small proportion of patients
whose test results are negative, may receive the reference
test. This results in an inflated estimate of the sensitivity
and an underestimated estimate of the specificity. However,
this verification bias does not influence the relative sensitiv-
ity (5detection rate of confirmed disease among subjects
with positive screen test Avs. screen test B) nor the relative
positive predictive value (PPV) in studies comparing the ef-
fect of two or more screening tests [13,21].
Assessment of the gold standard knowing the screen test
result includes a serious risk of overestimation of both the
sensitivity and specificity. Therefore, in diagnostic re-
search, in which the objective is to evaluate the cross-
sectional accuracy of a screening test, verification should
be performed independently. This can be difficult when
screening test and gold standard are based on the same prin-
ciple, for instance in case of visual inspection with acetic
acid screening (visual inspection of the cervix after applica-
tion of acetic acid) validated using colposcopy. It is usually
assumed that colposcopy followed by histologic examina-
tion of material obtained from suspected areas provides
a valid ascertainment of the true disease status, making it
Table 1. Possible outcome measures for benefit in cervical cancer
1. Reduction of all-cause mortality
2. Reduction of mortality from cervical cancer: (quality-adjusted)
3. Reduction of morbidity due to cervical cancer: incidence of
4. Reduction of incidence of cancer (including microinvasive cancer)
5. Reduction of incidence of CIN3 or worse (CIN3þ)
6. Increased detection rate of either CIN3þ or CIN2þ
7. Increased test positivity with increased, similar, or reduce positive
Abbreviation: CIN, cervical intraepithelial neoplasia.
641W.J. Adriaensen et al. / Journal of Clinical Epidemiology 66 (2013) 639e647
the gold standard. Recent prospective studies, however,
suggested that up to 50% of prevalent precancers might
be missed during colposcopy [22,23], which also has a high
interobserver variability. Random biopsies from normal-
appearing regions and follow-up can be used to compensate
partially for the lack of sensitivity of colposcopy.
2. A framework for the evaluation of screening
Introducing a new screening strategy in clinical practice
requires the evaluation of its characteristics as an added
value to the existing procedures. Guidelines regarding
appropriate study designs to address questions on benefits
of screening for disease precursors in which the target dis-
ease is not yet present and in which the management is re-
stricted to screen positives are urgently needed . We
propose a stepwise framework for the evaluation of screen-
ing strategies building further on the work by Van den Bruel
et al.  and Haynes and You  for the evaluation of di-
agnostic tests, possible diagnostic trial designs described by
Lijmer and Bossuyt , and detailed concepts proposed by
Arbyn et al. , Pepe et al. , and Harris et al. 
At each step, questions are raised which are progres-
sively more relevant for the screening strategy, providing
(ideal or laboratory circumstances)
Is the test able to distinguish between samples with and without the
preclinical disease in laboratory condition?
Assess analytical sensitvity
What is the test's intended role in the clinical pathway
(Real clinical situation)
Among a clinically relevant population, does the test distinguish
between those with and without the preclinical disease?
--> cross-sectional study
Assess clinical sensitivity
Longitudinal clinical sensitivity
(Real clinical situation)
Can a given biomarker or precursor, predict presence or
development of preclinical and overt disease?
--> Retro- or prospective longitudinal study
Assess longitudinal clinical sensitivity
What is the nature of the (pre-)disease when detected?
--> Prospective longitudinal study
false-positive rate, detection rate
Impact on a patient level
(Real clinical situation)
Do patients who undergo the screening strategy fare better (in their
ultimate outcome) than similar patients who do not?
--> Randomized control trial
Assess reduction burden of (pre-)disease in the total population
Impact on a population level and cost-effectiveness
Do health outcomes in the whole society improve by introducing the
new screening strategy at an acceptable cost?
--> Randomized health service study
--> Econometric analysis
--> Screening cohort linked to cancer registries
Level of Evidence
Fig. 1. Evaluation of a new screening strategy.
642W.J. Adriaensen et al. / Journal of Clinical Epidemiology 66 (2013) 639e647
a higher level of evidence, but requiring also a more strin-
gent study design and resources. Not all proposed study de-
signs will be necessary, only the best possible design that is
appropriate for the intended place of the test in the screen-
ing pathway. It is important to stress that no further re-
search is planned when results at a certain step are
unsatisfactory, and the strategy is only definitely evaluated
if all the steps of the checklist have been addressed, taking
all relevant aspects of health into consideration [2e5,28].
2.1. Step 1: Technical or analytical accuracy
Is the test able to distinguish between samples with
and without the preclinical disease in laboratory
Every screening test under evaluation should be assessed
with respect to its technical accuracy. The technical accu-
racy of a test refers to its ability to produce usable informa-
tion under research conditions. First, a correlation between
disease should be established. Then, the analytical sensitiv-
ity of a test is its ability to detect a well-defined preclinical
condition or specified quantity of a biomarker. The analyti-
cal specificity refers to the ability of an assay to detect only
that specific biomarker or preclinical condition and not
closely related biomarkers or preclinical conditions. The re-
producibility is the ability to obtain the same test results on
repeated testing or observations. Reproducibility is influ-
enced by analytical variability and observer interpretation.
ror) and inaccuracy (systematic error or bias).
2.2. Step 2: Place in clinical pathway
What is the test’s intended role in the clinical
New screening tests will eventually become a part of
a clinical pathway. Knowing whether a new test is intended
to replace an existing test, act as a triage for subjects being
positive for the existing screen test (aiming to increase the
specificity of the existing screening strategy) or act as an
add-on screening test (aiming to increase the sensitivity
of the screening strategy), is crucial . In the add-on op-
tion, we can distinguish two suboptions: all subjects receive
the two tests, or the new test is offered only to those who
are negative with existing test. This potential place will de-
termine the characteristics the new test needs to have and
guide the researcher in the choice of the study designs that
will (not) be needed to evaluate its efficacy. However, be-
sides the results from these targeted studies and trials, the
strategy’s costs, participation rates, and so forth can ulti-
mately result into a different optimal place of the screening
strategy in the clinical pathway (steps 4e6).
HPV DNA testing has been considered as a potentially
useful screening test solely (replacing cytology), as a triage
test, or in combination with a papanicolaou (PAP) smear
(add-on option) to detect cervical cancer precursors. As
a candidate to replace PAP smear as the primary screening
test, HPV DNA detection should have either better diag-
nostic sensitivity or less harm (higher specificity) or both.
Studies have shown that HPV DNA testing with validated
assays such as the hybrid capture 2 test and general HPV
primers GP5þ/6þ polymerase chain reaction is indeed
substantially more sensitive in identifying CIN2, CIN3,
or cancer than cytology at cutoff of atypical squamous cells
of undetermined significance (ASCUS) or low-grade
squamous intraepithelial lesion (LSIL), but it is less spe-
A related study question is whether a new marker can im-
prove an existing triage procedure. Until recently, women
with minor cytologic abnormalities were followed by repeat
the hybrid capture 2 assay is more sensitive and equally spe-
cific in finding high-grade CIN compared with repeat
cytology . HPV testing could therefore be a better triage
strategy than repeat cytology to select thosewomen with mi-
nor cytologic lesions in a PAP smear who require referral for
diagnosis and treatment.
2.3. Step 3: Diagnostic accuracydcross-sectional study
In a clinically relevant population, does the test dis-
tinguish between those with and without the preclin-
The accuracy of a screening test is the test’s ability to cor-
rectly detect or exclude a precursor or early stage of disease
in a clinically relevant population. It should be noted that an
increased analytical sensitivity does not necessarily imply an
increased detection of preclinical disease in a relevant pop-
ulation (clinical sensitivity) (Table 2). Cross-sectional accu-
racy of a screening test is most comprehensively evaluated
in a clinical setting in which all women irrespective of the
screening test resultdor at least all test positives and a ran-
dom sample of all test negativesdare submitted to verifica-
tion by a valid reference standard without prior knowledge
of the screen result. The use of a random sample of test neg-
atives requires weighting of the results during analysis.
It should be noticed that correction for verification bias by
additional verification of test-negative cases can yield erro-
neous results (sometimes even more biased than the original
verification bias) if subjects are not selected at random .
The clinical sensitivity and specificity are used as outcomes
if the biomarker is measured on a binary scale, or receiver
operating characteristic curves are set up in case of a test
with a continuous or ordinal scale.
For example, the rather low sensitivity of PAP smear
and the high proportion of unsatisfactory samples prompted
the development of new technologies such as new sampling
devices and liquid-based cytology (LBC). A candidate-
screening test for the replacement of conventional PAP
643W.J. Adriaensen et al. / Journal of Clinical Epidemiology 66 (2013) 639e647
smear should at least have equal diagnostic accuracy. Only
a few studies are available with complete assessment using
a gold standard, which permits evaluation without verifica-
tion bias [33e35]. Available studies did not reveal a statis-
tically significant difference between conventional and
LBC in clinical sensitivity or specificity for detecting CIN2.
If multiple tests are evaluated and at least one test is very
sensitive, the extent of verification bias is reduced because
virtually all women with CIN2/3 or CIN3 undergo diagnos-
tic evaluation. When, for example, two screening tests are
applied to the same study subjects and all subjects positive
for one or both tests are verified with an acceptable refer-
ence standard, unbiased estimation of each test’s positive
predictive value, and the relative sensitivity and detection
rate of true positives is possible [13,21,36]. Thus, although
the true absolute sensitivity cannot be determined, test per-
formance can be ranked in an unbiased fashion.
So, measurement of sensitivity relative to a reference
standard offers a good framework to compare alternative
screening tests. However, an RCT may be needed to evalu-
ate the performance of the new screening strategy at the pa-
tient and population levels (steps 4e6), even if a new test
fares no better compared with an existing screening test
conducted with the same reference standard. For example,
although no statistical difference could be showed between
LBC and the conventional assay, the proportion of unsatis-
factory samples is lower in LBC, and the interpretation re-
quires less time. The cost of an individual LBC test is
considerably higher, but it allows ancillary testing such as
Note that it is important to clearly define the relevant
threshold of disease, for instance CIN2 or worse CIN2þ
or CIN3þ. Whether the detection of more CIN2þ corre-
sponds with progressive disease rather than with regressive
disease cannot be assessed from cross-sectional studies.
2.4. Step 4: Longitudinal sensitivity
Can a given biomarker or precursor, predict presence
or development of preclinical and overt disease?
2.4.1. Retrospective design
After the cross-sectional evaluation in subjects with
known outcome, a retrospective longitudinal study can be
set up if a relevant biobank is installed for some time, to
provide evidence regarding the capacity of the biomarker
to detect present or future disease or its precursor (longitu-
dinal sensitivity), if earlier detection is wanted (Table 2).
Also, the impact of covariates should be explored to better
select possible appropriate subpopulations and determine
a screening interval if repeated screening is of interest.
A biobank-based caseecontrol study on archived cervi-
cal smears from women with cervical cancer selected from
a cancer registry and matched controls can enable the de-
tection of HPV DNA in the most recent and earlier samples
. The sample selection should be representative of the
samples that would be collected from a target population.
Such study is only feasible if such a biobank is available
and accessible and if the biomarker is not prone to degrada-
tion over time or the samples are not collected to a prespe-
cified time schedule .
2.4.2. Prospective design
tients over time with a well-conducted longitudinal observa-
tional or randomized study to have proof for a substantial
likelihood of progression (longitudinal sensitivity) and
knowledgeaboutthenatureof progressive precursors.A pro-
umentation. Results from such a study can also clarify the
level of overdiagnosis, although time can be an issue when
death of cancer is the adopted end point. For cervical cancer,
ning European trials, which permits the estimation of over-
diagnosis with a reasonable study size and duration .
2.5. Step 5: Impact on the patient level
Do patients who undergo this screening strategy fare
better (in their ultimate health outcomes) than similar
patients who do not?
Table 2. Different screening strategy sensitivities
Cervical cancer example
(two HPV tests)
Analytical Ability to detect a specified quantity of
a biomarker or defined preclinical
condition in laboratory conditions
A test is analytically sensitive when a
minimal amount of expression
yields a positive signal
HPV test 2 is positive even when the
viral load is very low, whereas HPV
test 1 is positive only beyond a
higher viral load cutoff.
HPV test 2 is more often positive than
test 1, but it does not detect more
CIN2þ than test 1.
Certain HPV-positive subjects do not
yet have disease (currently false
positives) but can develop the
disease in subsequent years (future
true positives) or regress (future
Clinical (cross-sectional) Ability to pick up subjects with
Patients with disease or predisease
Clinical (longitudinal) Sensitivity to pick up current and
future clinically relevant disease
The capacity to detect early disease
(present or incipient)
Abbreviations: HPV, human papillomavirus; CIN, cervical intraepithelial neoplasia.
644 W.J. Adriaensen et al. / Journal of Clinical Epidemiology 66 (2013) 639e647
The final aim of screening is to prevent the burden of
overt disease with minimal harm caused and not simply
to detect preclinical disease. For cervical cancer screening,
harms may include overdiagnosis and unnecessary treat-
ment, long-term anxiety because of labeling, test-related
anxiety, discomfort, time investment, and minor or major
adverse reactions (pain, hematoma, anaphylaxis, etc.)
[2e4,28]. By balancing the benefits against the harms,
a net benefit on patient health can be derived. To have direct
evidence on effectiveness or at least evidence on overdiag-
nosis of regressive predisease with minimal bias, different
groups need to be screened, managed, and treated accord-
ing to different strategies and followed over time to observe
the possible occurrence of disease. Only an RCT or a well-
designed cohort study comparing large populations can
provide conclusive evidence on the net benefit and actual
impact of screening because observational studies are prone
to selection bias and to confounding by other known and
unknown variables that can explain differences between
Thus, both steps 4 and 5 can be covered by an RCT, al-
though sometimes a retro- or prospective observational
study can be preferred before or instead of an RCT. An
RCT may not always be necessary or feasible because of
ethical considerations or large sample sizes needed. PAP
smear screening for instance was never evaluated in a ran-
domized trail because of this reasons. Nevertheless, the ep-
idemiologic evidence indicates a very substantial beneficial
effect of cytologic screening on cervical cancer incidence
and mortality. Also, the effects of randomized trials may
not be generalizable as the high-quality setting of trials
run by dedicated scientists may be different from normal
clinical care. This can be avoided by applying the new
screening strategies within the routine screening activity.
An acceptable methodological approach is the initial intro-
duction of the new policy in a random selection of regions
or birth cohorts using the other regions as nonintervention
groups (randomized health care design). In such case, ran-
domization is not performed at the level of the individual
but on the level of region or birth cohort (clustered random-
ized clinical trial). With this strategy, very large research
funds are not required and results apply to a real health care
network and not merely to the research setting. This ap-
proach has been successfully applied in Finland to evaluate
the new cervical cancer screening strategies .
In population-based randomized clinical trials in five
European Union (EU) member states (Finland, Italy,
Sweden, The Netherlands, and the United Kingdom), cytol-
ogy screening is currently being compared with primary
HPV screening or combined cytology/HPV screening. In
all arms of these trials, the incidence of CIN2 and CIN3
in screen negatives can be assessed based on detection rates
in 3e5 years after initial screening. The outcomes of these
European trials, observed in the second screening round,
supplemented by mathematical modeling, and taking into
accountcosts, psychosocialaspects,and women’s
preferences, are believed to be pivotal for defining the final
future screening policy in the EU .
2.6. Step 6: Impact on the population level and cost-
Do health outcomes in the whole society improve by
introducing the new screening strategy at an accept-
Often, the ‘‘real-world dimension’’ differs from that of
a ‘‘trial dimension,’’ so cost-effectiveness analyses, econo-
metrical analyses, and models of the different modalities
of application or triage/management can provide us with
a more comprehensive and broader picture. Our final goal
is the reduction of the burden of cancer on the total popu-
lation. Any type of burden should be outweighed against
benefit to improve patient outcome. This step goes beyond
individual harms and benefits but also addresses the accept-
ability for the society in terms of costs. Table 3 presents an
overview of the cost components attributed to screening.
A decrease in either specificity of a test or prevalence of
disease can increase the costs rapidly. Loss in specificity of
a screen test can be limited by raising the screening inter-
val, increasing the age at onset of screening, and raising
the cutoff for test positivity. However, all such changes will
be assessed against the possible losses in sensitivity.
Cost-effectiveness of a candidate-screening strategy
should preferentially be assessed by means of an economet-
rical analysis based on observed results of a well-organized
RCT. Reliable mathematical models can be used to esti-
mate the final outcome per unit of cost. They should rely
on accurate and complete estimates of performance includ-
ing measures of imprecision and should only be made after
a net benefit on patient health has been established. Math-
ematical models can also be used to explore the impact of
multiple variables, such as changes in target population,
screening frequency, compliance of the population, and
management options that cannot all be included in random-
ized trials (sensitivity analyses). In a pioneering series of
studies by van Ballegooijen [40e42], mathematical model-
ing has been used to assess which program designs are
likely to be most cost-effective and identify critical areas
of uncertainty in which research is particularly needed
. Major conclusions from these studies were that the
longitudinal performance of the HPV screening strategy
was critical for achieving cost-effectiveness because the
high cost and lower specificity of HPV screening compared
Table 3. Cost components 
? Cost price of the screening strategy (including overscreening), fees,
and administrative and logistical costs
? Cost for follow-up and treatment of false positives
? Cost for follow-up and treatment of true positives
? Human costs (time spent, anxiety and discomfort, and side effects)
? Consequences of delay in the detection of cancer
? Need for repeat tests
645 W.J. Adriaensen et al. / Journal of Clinical Epidemiology 66 (2013) 639e647
with cytology-based screening needs to be compensated for
by a longer screening interval to become cost-effective.
Prevalence of disease, availability of resources in terms
of staff and technology, expectations and acceptability by
the population, and financial costs of an intervention largely
differ between countries and regions. Therefore, the results
of population-based evaluations in one region can therefore
never be translated as such to a different region, but studies
(depending on which aspects are different) will have to be
Screening strategies are often introduced into clinical
practice without proper evaluation. We have proposed
a stepwise framework to evaluate new screening strategies,
in which an increasing level of evidence is gathered but re-
quire progressively more stringent and expensive studies.
Regional, national, or international authorities should im-
pose requirements for testing and implementing new
screening strategies, as currently has been done in a number
of countries. Together with other recently published crite-
ria, our framework may be helpful in defining such require-
ments, which should lead toward a net benefit in general
health of the individual at an acceptable cost for society.
All authors contributed substantially to conception and
design, revised the article critically for important intellec-
tual content, and gave final approval of the version to be
Special thanks should be given to the the Belgian Foun-
dation Against Cancer (Brussels, Belgium) for providing
the financial means.
M.A. received financial support from the Belgian Foun-
dation Against Cancer (Brussels, Belgium), the Interna-
tional Agency for Research on Cancer (IARC, Lyon,
France), the 7th Framework Programme of DG Research
of the European Commission through the PREHDICT
project (grant no. 242061, coordinated by the Vrije Univer-
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