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Mahadevia PJ, Fleisher LA, Frick KD, Eng J, Goodman SN, Powe NR. Lung Cancer Screening With Helical Computed Tomography in Older Adult SmokersA Decision and Cost-effectiveness Analysis. JAMA. 2003;289(3):313–322. doi:10.1001/jama.289.3.313
Context Encouraged by direct-to-consumer marketing, smokers and their physicians
are contemplating lung cancer screening with a promising but unproven imaging
procedure, helical computed tomography (CT).
Objective To estimate the potential benefits, harms, and cost-effectiveness of
lung cancer screening with helical CT in various efficacy scenarios.
Design, Setting, and Population Using a computer-simulated model, we compared annual helical CT screening
to no screening for hypothetical cohorts of 100 000 current, quitting,
and former heavy smokers, aged 60 years, of whom 55% were men. We simulated
efficacy by changing the clinical stage distribution of lung cancers so that
the screened group would have fewer advanced-stage cancers and more localized-stage
cancers than the nonscreened group (ie, a stage shift). Our model incorporated
known biases in screening programs such as lead time, length, and overdiagnosis
Main Outcome Measures We measured the benefits of screening by comparing the absolute and
relative difference in lung cancer–specific deaths. We measured harms
by the number of false-positive invasive tests or surgeries per 100 000
and incremental cost-effectiveness in US dollars per quality-adjusted life-year
Results Over a 20-year period, assuming a 50% stage shift, the current heavy
smoker cohort had 553 fewer lung cancer deaths (13% lung cancer–specific
mortality reduction) and 1186 false-positive invasive procedures per 100 000
persons. The incremental cost-effectiveness for current smokers was $116 300
per QALY gained. For quitting and former smokers, the incremental cost-effectiveness
was $558 600 and $2 322 700 per QALY gained, respectively.
Other than the degree of stage shift, the most influential parameters were
adherence to screening, degree of length or overdiagnosis bias in the first
year of screening, quality of life of persons with screen-detected localized
lung cancers, cost of helical CT, and anxiety about indeterminate nodule diagnoses.
In 1-way sensitivity analyses, none of these parameters was sufficient to
make screening highly cost-effective for any of the cohorts. In multiway sensitivity
analyses, a program screening current smokers was $42 500 per QALY gained
if extremely favorable estimates were used for all of the influential parameters
Conclusion Even if efficacy is eventually proven, screening must overcome multiple
additional barriers to be highly cost-effective. Given the current uncertainty
of benefits, the harms from invasive testing, and the high costs associated
with screening, direct-to-consumer marketing of helical CT is not advisable.
Concerned smokers and their physicians are contemplating screening for
lung cancer with helical computed tomography (CT).1-4 Having
an average 5-year survival of 15%,5 lung cancer
is often diagnosed at advanced clinical stages when treatment is typically
noncurative. Therefore, physicians and their patients have long sought screening
methods to detect lung cancer at localized stages, when it can be surgically
removed and possibly cured.
Past attempts to screen for lung cancer with intensive screening regimens
using chest radiographs and sputum cytology found no reduction in lung cancer–specific
skepticism about whether lung cancer is amenable to early detection.11 Uncontrolled studies of helical CT screening report
detection of many small-sized lung cancers, when surgical resection and theoretical
cure is possible.12-19 However,
these findings are of unclear clinical significance due to the lack of control
groups and of long-term morbidity or mortality data in these trials. Some
contend that surgical treatment of these small-sized lung cancers should lower
mortality,20 whereas others are doubtful of
a mortality benefit due to tendency of some lung cancers to micrometastasize
even at apparently localized stages.18,21 Although
large randomized controlled trials evaluating helical CT as a screening test
for lung cancer are beginning, they are years from completion.22,23
Meanwhile, direct-to-consumer marketing4 and
media coverage of the helical CT trials has encouraged demand for lung cancer
the lack of evidence. Early dissemination of a screening technology raises
concerns such as consequences of false-positive and false-negative results,4 harms from invasive diagnostic tests,25 surgery,1 and considerable societal costs.26
We studied the potential benefits, harms, and cost-effectiveness of
annual helical CT screening under various scenarios of efficacy. Our research
aim was to gain insight into the important factors influencing screening efficacy
and potential economic and safety consequences of a widely disseminated lung
cancer screening program.
We performed a decision and cost-effectiveness analysis from the societal
perspective in which we simulated the clinical paths and health states that
persons would traverse having received or not received annual helical CT screening.
We considered parameters required for evaluating a screening program, such
as the characteristics of the participants (age, smoking status), characteristics
of the screening test (sensitivity, specificity), characteristics of the disease
(treatment and prognosis, quality of life), and characteristics of the screening
program itself (efficacy, biases inherent in screening). Probabilities for
these parameters,12-15,17,27-34 as
well as quality of life measured in the form of utilities35,36 and
obtained from the published literature and the Surveillance, Epidemiology,
and End Results (SEER) national cancer database27 (Table 1).
We performed a base-case analysis, which measures cost-effectiveness
using the estimate thought to be the most accurate for each parameter in the
model. We performed 1-way sensitivity analyses, which evaluate the impact
on cost-effectiveness of using more extreme estimates of each parameter. Through
sensitivity analyses, model parameters that are influential in determining
the cost-effectiveness of screening can be identified. Finally, we performed
multiway sensitivity analyses, which vary estimates across more than 1 parameter.
These analyses depict economic consequences across a range of favorable and
unfavorable circumstances. We created a Markov model to perform these analyses.43
Our study population consisted of 100 000 hypothetical 60-year-old
heavy smokers (>20 pack-years) who were eligible for lung resection surgery.
Fifty-five percent of the cohort were men. We chose this population since
they mirror participants in screening trials and are at higher lung cancer
risk than the overall population, making them more likely to benefit from
Because smoking cessation might impact the benefit of screening, we
performed separate analyses for 3 different cohorts of heavy smokers: persons
who were continuing smoking (current smokers), persons who had permanently
quit smoking at time of initial screening (quitting smokers), and persons
who had permanently quit 5 years prior to screening and survived to age 60
years (former smokers). We modeled annual screening from age 60 to age 80
years (20-year screening duration) with follow-up until age 100 years (40-year
time horizon for occurrence of clinical events). We terminated screening at
age 80 years since the incidence of lung cancer decreases afterward.28
Nonscreened Cohort. Smokers in the nonscreened group (Figure
1) face yearly transition probabilities of staying alive without
apparent lung cancer, developing and dying from lung cancer, or dying from
other causes. We obtained these incidence and mortality probabilities from
the SEER DevCan program28 (Table 1). We adjusted these measures for the 3 smoking cohorts using
estimates of relative risk corresponding to smoking cessation.44,45 All
probabilities were stratified by 5-year age groups and sex-adjusted to our
Persons diagnosed with suspicious lesions or symptoms suggestive of
lung cancer undergo invasive testing, with its potential harms. Those diagnosed
with lung cancer could have localized-stage non–small-cell lung cancer
(NSCLC), advanced-stage NSCLC, or small-cell lung cancer (SCLC). Upon entering
these disease states, persons undergo various clinical management strategies
(surgery vs radiation therapy vs chemotherapy) and have distinct prognoses.
Annual survival probabilities for each histological clinical stage were obtained
from the SEER program using lung and bronchus cancers that were invasive,
microscopically confirmed, actively followed, and with no other primary cancer.
We excluded SEER cases from nursing homes and those identified only by autopsy
data. We classified SEER cases into localized or advanced clinical stages
using the SEER-modified American Joint Committee Classification. Stage IA
and IB cases receiving curative resection (segmentectomy, lobectomy, or pneumonectomy)
were classified as the localized-stage NSCLC group and all other stages including
unresected stage IA through IB cases formed the advanced-stage NSCLC group.
We stratified all probabilities by age, histological-clinical staging, and
disease duration. We obtained the proportion of mortality attributable to
lung cancer vs other causes from SEER cause-of-death data.
Screened Cohort. Smokers undergoing screening have similar risks of developing lung cancer
but face a different course of events. Adherent smokers in the screened group
receive annual helical CT testing and based on its accuracy may be diagnosed
with indeterminate nodules that require additional monitoring and possible
invasive testing. We obtained probabilities for the frequency of indeterminate
nodules, screening sensitivity and specificity, and annual adherence from
helical CT trials that have reported baseline and annual repeat screening
data (Table 2).12-15,17
The timing of cancer diagnoses, the numbers of diagnoses, and the types
of cancers among screened individuals can be different than those who are
not screened. Screened persons could be diagnosed with lung cancers that do
not cause clinical disease (overdiagnosis bias) or are extremely slow-growing
and have long latency periods (length bias).46 Many
of these individuals might remain undiagnosed under no-screening conditions.
Evidence for these biases has been described in past screening trials.46,47 We estimated the degree of length
bias and overdiagnosis bias by comparing trial-specific observed diagnosis
rates with expected diagnosis rates (Table
1). Expected diagnosis rates were calculated using incidence probabilities
weighted for average trial-specific age, sex, and smoking composition.
Screening also creates a lead time (advancement in the date of diagnosis),
in which the timing of diagnostic testing, improvements in health, and costs
occur earlier than under no-screening conditions. We incorporated an average
1-year lead time for screening-detected lung cancers, extrapolated from published
lead times for lung cancer screening using chest radiographs48 and
tumor doubling times.13
Screening-detected cancers also have a different histological distribution.
Cancers detected by helical CT (ie, true-positive results) are usually peripherally
based cancers, while those missed by helical CT (ie, false-negative results)
are often hidden in endobronchial locations.13 Endobronchial
tumors are more frequently due to squamous cell carcinoma, while peripheral
tumors tend to represent adenocarcinoma. In a more complex model, we adjusted
lung cancer survival estimates to account for this histological predilection.
However, because this adjustment did not significantly impact our results,
the results shown are from a simpler model that did not incorporate this phenomenon.
Finally, screening should alter the clinical-stage distribution of cancers
such that advanced cancers are found earlier in localized stages. This is
frequently referred to as a downward stage shift. In our base-case scenario,
we assumed a 50% stage shift. For example, if the stage distribution for the
nonscreened group is 80% advanced and 20% localized, then a 50% stage shift
would result in a 40% advanced- and 60% localized-stage distribution for the
In sensitivity analyses we varied the degree of stage shift and also
examined the impact of a pseudo–stage shift. For lung cancer, a pseudo–stage
shift can occur if the advanced-stage cancers that have been "shifted" into
localized stages are biologically aggressive and carry a prognosis closer
to naturally occurring advanced-stage disease than to localized-stage disease.
Model Assumptions. We made several major assumptions for this study: (1) Only NSCLC underwent
a stage shift; SCLC did not experience a stage shift given its early metastatic
nature and low probability of cure. (2) Within histological and clinical stage
categories, the clinical management, time costs of treatments, treatment risks,
and subsequent prognoses were on average similar between screened and nonscreened
lung cancer cases. This assumption was removed for the pseudo–stage-shift
scenario. (3) The incidence of lung cancers in the screened group did not
increase due to the radiation exposure from CT scans. (4) Persons who became
nonadherent to screening remained nonadherent. Therefore, partial adherence
or intermittent screening was not modeled. (5) Lung cancer cases due to length
bias and overdiagnosis bias received the same costs, workup, and therapy as
all other lung cancer cases but had mortality probabilities similar to smokers
without lung cancer. (6) The quality of life for persons with screening-detected
localized NSCLC was higher than non–screening-detected localized NSCLC
since screening-detected cases typically do not have symptoms at the time
The costs of screening include the facility and professional fees associated
with helical CT screening, the monitoring of indeterminate nodules, and the
opportunity costs to get screening (Table
1). Cost of cancer care stratified by clinical stage and duration
of illness was obtained from a study using a SEER registry linked to a health
maintenance organization database with chart reviews.39 We
obtained costs for specific diagnostic tests and physician visits from the
American Medical Association's 2001 National Physician Fee Schedules Relative
Value Scale.37 We obtained the costs for informal
caregiving,40 treatment, and its complications
from the literature.29-33,41,42 All
costs were calibrated to 2001 US dollars using the medical component of the
consumer price index. Both costs and life-years were discounted 3% annually.
We obtained quality-of-life measurements for our health states from
a study of patients with NSCLC35 using results
from the EuroQoL multiattribute utility scale49 (Table 1). We used the median utility scores
for patients without and with metastasis as proxies for the localized and
advanced NSCLC/SCLC groups, respectively. Since duration of disease did not
statistically alter utilities, we used these scores as the average utility
for the remainder of case lifetime.
From a systematic review of cost-utility assessments in oncology, we
obtained the decrements in quality of life or disutilities for anxiety and
discomfort from having an unclear noncalcified nodule, invasive testing, surgery,
We measured the benefits of screening by comparing the absolute and
relative difference in lung cancer–specific deaths. We estimated the
number of screening tests performed and harms from invasive tests or surgery
and deaths from lung cancer for every 100 000 persons screened. Costs
were measured in US dollars and incremental effectiveness in quality-adjusted
life-years (QALYs) gained.
To explore the benefits, harms, and cost-effectiveness of screening
under different efficacy assumptions we varied the degree of stage shift and
examined the impact of a pseudo–stage shift. To examine the ideal age
range to start screening, we varied age at first screening from ages 45 to
80 years. To examine the time to reach cost-effectiveness, we varied the length
of follow-up from 1 to 40 years.
After performing 1-way sensitivity analyses to isolate influential parameters,
we examined the impact of simultaneously using highly favorable and unfavorable
estimates for the most influential model parameters other than stage shift.
For current smokers in the base-case scenario, there were 462 352
screening examinations over a 20-year period. Using a 50% stage shift assumption,
there were 4168 lung cancer deaths per 100 000 nonscreened persons compared
with 3615 lung cancer deaths per 100 000 screened persons, resulting
in an absolute mortality reduction of 553 deaths or a 13% relative mortality
reduction (Table 3). However,
there were also 1186 invasive tests or surgeries for benign lesions in the
screened group. The incremental cost-effectiveness of screening was $116 300
per QALY gained.
The incremental costs consumed by screening (Table 4) were between $4300 and $4600 for all smoking cohorts. However,
the incremental effectiveness of screening decreased with lower-risk cohorts;
there was a 0.039-QALY gain among current smokers, a 0.008-QALY gain among
quitting smokers, and a 0.002-QALY gain among former smokers. The incremental
cost-effectiveness for screening quitting smokers was $558 600 per QALY
gained and for former smokers was $2 322 700 per QALY. Thus, annual
screening with helical CT became progressively less cost-effective among smokers
with longer duration of smoking cessation.
Degree of Stage Shift. For current smokers, we varied the degree of stage shift from 0% to
100%. The stage shift required for screening to cost less than $50 000
per QALY was 91% for current smokers. Screening was dominated by no screening
if less than a 23% stage shift occurred. For quitting and former smokers,
a 100% stage shift was not sufficient by itself to reach $50 000 per
Age at First Screening. Cost-effectiveness varied with age at first screening in a U-shaped
fashion (Figure 2). For current
smokers, screening was most cost-effective when started between ages 55 and
65 years. For each smoking cohort, screening was most cost-effective when
started before the ages of peak lung cancer incidence (ages 67-72 years).
Screening was dominated by no screening for persons older than age 77 years
among current smokers, older than age 75 among quitting smokers, and older
than age 74 for former smokers. Screening was also dominated for persons younger
than age 48 for quitting smokers and persons younger than age 50 for former
Length of Follow-up. To assess how quickly the costs, QALYs, and cost-effectiveness of screening
would accrue, we varied the time horizon or duration of follow-up. We evaluated
the cumulative change in costs, QALYs, and incremental cost-effectiveness
for current smokers (Figure 3).
For the first 2 years, there was a net loss in QALYs due to the harms and
disutilities from testing and treatment. Gains in QALYs from screening and
treatment did not manifest until the third year of follow-up. There were significant
up-front costs for screening, with the largest increase occurring in the first
year. The incremental cost-effectiveness ratio approached $120 000 per
QALY gained after 19 years of follow-up.
Influential Model Parameters and Multiway Sensitivity Analysis. We performed sensitivity analysis on the remaining model parameters.
Parameters that changed incremental cost-effectiveness by more than 50% of
base case were classified as highly influential. In addition to stage shift,
nonadherence with screening, length bias, or overdiagnosis bias in the prevalence
year of screening, quality of life for screening-detected localized NSCLC,
costs for helical CT, and anxiety from expectant management of indeterminate
nodules were highly influential.
In a favorable estimate scenario (Table 3) using lower probabilities for annual nonadherence (3% instead
of 6.5%), lower estimates for length bias and overdiagnosis bias (150% of
incidence instead of 200%), better quality of life for localized-stage lung
cancers (0.88 instead of 0.83), lower costs per case for helical CT screening
($150 instead of $300), and no anxiety from indeterminate nodules, screening
led to 900 fewer lung cancer deaths (16% mortality reduction), 1520 false-positive
invasive procedures, and an incremental cost-effectiveness of $42 500
per QALY gained for current smokers. Using a similar scenario for the other
risk cohorts resulted in an incremental cost-effectiveness ratio of $75 300
per QALY gained for quitting smokers and $94 400 per QALY gained for
Under an unfavorable estimate scenario for current smokers (Table 3 shows point estimate changes),
there were 119 fewer lung cancer deaths in the screened group (4% relative
mortality reduction) and 993 individuals harmed. The incremental cost-effectiveness
of screening was dominated by no screening for all smoking cohorts. Increasing
nonadherence or the degree of length bias and overdiagnosis bias alone caused
the cost-effectiveness of screening to be dominated by no screening.
If screening resulted in a pseudo–stage shift whereby shifted
cancers had high potential for micrometastasis and did not carry the typical
favorable prognosis of localized NSCLC, screening resulted in 6 fewer lung
cancer deaths (0.1% relative mortality reduction) and 1186 false-positive
invasive procedures, and its cost-effectiveness was dominated by no screening.
Substantial debate about the use of imaging modalities such as helical
CT for lung cancer screening arises from the lack of definitive evidence about
its efficacy, high societal costs, and the potential for harm. In this study,
assuming a sizable stage shift and incorporating relevant considerations for
evaluating a screening program, we found that lung cancer screening with helical
CT is unlikely to be highly cost-effective for most heavy smokers.
While a scenario can be envisioned under which screening is cost-effective,
the likelihood of such a scenario manifesting itself is questionable. Multiple
barriers associated with screening must be overcome. These barriers include
nonadherence to screening, high screening costs, poor quality of life after
diagnosis, excess testing and procedures, excess diagnoses from length bias
and overdiagnosis bias, and having to wait many years to achieve the economic
and health benefit from screening.
The total societal cost for an annual helical CT screening program of
at-risk ever-smokers is very high. An estimated 50 million men and women in
the United States are ever-smokers between the ages of 45 and 75 years.26 If 50% of this group received periodic annual screening,
the program costs are approximately $115 billion (discounted) based on our
Our findings raise concern regarding direct-to-consumer marketing. Frequently,
screening advertisements found on the Internet and in newspapers tout the
benefits of early detection, do not clarify who is at high risk for lung cancer,
and do not mention the risks of finding indeterminate nodules. If the aforementioned
25 million individuals underwent 1-time helical CT screening only, we estimate
the number of individuals having indeterminate nodules diagnosed to be approximately
5 million. Even among high-risk groups, most nodules are noncancerous. If
screening were offered to groups at lower risk, the frequency of unnecessary
invasive testing or surgeries could increase because pulmonary nodules are
more likely to be benign in groups at lower risk.
For our simulated cohort, screening resulted in more than 1000 false-positive
cases undergoing invasive testing and/or surgery for benign lesions. Our estimate
is from the helical CT clinical trials, which used detailed radiographic monitoring
protocols to prevent unnecessary invasive procedures. Widespread dissemination
of screening could result in greater harm if quality-of-care standards are
lower in the general population. These findings warrant caution in direct-to-consumer
marketing. For those persons enquiring about helical CT screening, appropriate
informed consent should discuss the risk of harm and weigh the likelihood
of benefiting from screening.
Our finding that the risk profile of the screened population markedly
affects cost-effectiveness has important implications. Groups defined by simple
demographic factors, such as age or smoking status, may not be at high enough
risk to make routine, population-based screening cost-effective. Identification
of groups at even higher risk for screening is likely to be the most cost-effective
strategy, although this will limit screening to a smaller population. Clinical
factors, such as a history of asbestos exposure among smokers or the presence
of obstructive airway disease, may identify groups at higher risk. However,
many individuals with these characteristics may not qualify for surgery due
to the severity of comorbid conditions, making screening less beneficial.
Identification of high-risk groups through biomarkers may be promising. Recently,
Palmisano and colleagues50 found hypermethylation
of cancer-fighting genes in the sputum cells of smokers. Examination of sputum
specimens several years before cancer developed revealed that hypermethylation
antedated lung cancer in each of 21 persons who eventually developed lung
cancer. This specific biomarker or others developed in the future could identify
higher-risk groups for whom subsequent screening with an imaging modality
might be useful.
In this study, we make several assumptions that bias our model in favor
of screening. For example, we assumed that the radiation from the scans would
not increase risk of lung cancer. We assigned higher quality-of-life scores
for screening-detected localized-stage NSCLC compared with nonscreened cases.
By favoring screening efficacy, these assumptions make our conclusion about
the cost-ineffectiveness of screening more conservative.
There are several limitations to this study. First, our model did not
include benefits, harms, and costs for incidental diagnoses from screening.
For example, researchers at the Mayo Clinic CT screening program reported
incidental findings among 210 participants, including 51 abdominal aortic
aneurysms, 33 indeterminate renal masses, 35 adrenal masses, and 24 renal
calculi.15 The benefits, harms, and costs for
diagnosis and management of these conditions, although not firmly established,
could be substantial. However, we doubt that early detection of these incidental
findings would improve life expectancy enough to justify lung cancer screening
if screening for lung cancer is not by itself cost-effective. Second, this
study is a model of clinical practice rather than an examination of actual
clinical practice. However, our model incorporates the wealth of epidemiologic
data on lung cancer and does take into account the biases inherent in screening
programs. We also performed extensive sensitivity analyses that examined multiple
efficacy scenarios. Weighing the risks and benefits of these scenarios can
assist policy makers in making screening recommendations and setting guidelines.51 Such analyses may be particularly helpful when definitive
clinical trial data will not be available for years.23 Third,
our study did not incorporate costs associated with disability or lost productivity;
however, productivity costs may be a less-prominent parameter in our study
given the older age and the heavy comorbidities of the target population.
Finally, future advancements in lung cancer diagnosis and treatment could
make our results out of date.
In summary, we conclude that lung cancer screening with helical CT is
unlikely to be highly cost-effective without substantial reductions in mortality,
high rates of adherence, lower rates of overdiagnosis, and lower costs per
screening test. Given the uncertainty of efficacy, the possibilities of harm,
and the high costs associated with screening, direct-to-consumer marketing
of helical CT screening is not advisable.