Recommendations for CRC screening from 3 organizations

The recommendations from the 3 organizations for CRC screening tests are presented in Table 1 . Although similar evidence was reviewed by these 3 groups, there were differences in the test strategies recommended. The USPSTF and the ACS-MSTF-ACR present a menu of options, whereas the ACG presents preferred strategy options. The USPSTF formally evaluated risks and benefits of screening for the average risk patient and concluded that there was insufficient evidence at this time to recommend CTC or stool DNA testing for the general population. Both of these tests were included in the ACS-MSTF-ACR and ACG recommendations, but with the caveat that the interval of screening with the stool DNA test is not yet established. Furthermore, there has been discussion of the minimum size of polyp detected by CTC for referral to colonoscopy. (The ACS-MSTF-ACR did recommend that all CTC polyps of 6 mm or larger would be referred for colonoscopy.)

Tests recommended in common by all 3 groups are colonoscopy and the more sensitive FOBTs (fecal immunochemical tests [FIT] [preferred] or guaiac Hemoccult SENSA, Beckman Coulter, Brea, CA, USA). Flexible sigmoidoscopy every 5 years in conjunction with a sensitive FOBT (SENSA or FIT) every 2 to 3 years is recommended by the USPSTF, whereas flexible sigmoidoscopy alone or Hemoccult II alone is not recommended. However, the ACS-MSTF-ACR include flexible sigmoidoscopy and barium enema as individual tests in their recommendations.

The ACS-MSTF-ACR also classify the screening tests as (1) those that can prevent cancer through early detection of adenomas as well as detect CRC (recommended tests of colonoscopy every 10 years, flexible sigmoidoscopy every 5 years, CTC every 5 years, and double-contrast barium enema every 5 years) and (2) those that can primarily detect CRC early (recommended tests of annual guaiac-based FOBT with high test sensitivity for cancer, annual FIT with high test sensitivity for cancer, or stool DNA test with high sensitivity for cancer, interval uncertain). High test sensitivity for cancer was defined as 50% or greater for testing at one point in time. Furthermore, the ACS-MSTF-ACR guidelines state that the primary goal of screening should be to prevent CRC.

The ACG recommends that clinicians have access to a preferred strategy as an alternative to a menu of options. The ACG recommends the cancer prevention test of colonscopy as the first option, and then the FIT as the first alternative. Additional alternative tests include flexible sigmoidoscopy every 5 to 10 years, CTC every 5 years, Hemoccult SENSA annually, and stool DNA testing every 3 years. The ACG also grades its recommendations according to the amount of evidence supporting the recommendation and the benefit versus risk of the strategies. Colonoscopy, FIT, annual Hemoccult SENSA, and FIT have recommendation level 1B, which denotes strong recommendation with moderate quality evidence.

Thus, recommendations from different organizations vary because the rationale behind their recommendations differs.

Comparative effectiveness research to compare CRC screening tests

In comparing screening tests, both the risk and benefits of screening for each particular test are considered. Risks are commonly represented by the costs and benefits by life-years gained (LYG). Incidence or mortality reduction obtained with screening can also be used to represent benefits. Comparative effectiveness research is the conduct and synthesis of research comparing the benefits and harms of various interventions and strategies for preventing, diagnosing, treating, and monitoring health conditions in real-world settings. The purpose is to improve health outcomes by developing and disseminating evidence-based information to patients, clinicians, and other decision makers about which interventions are most effective for which patients under specific circumstances.

In this article the cost-effectiveness of the recommended CRC screening tests is discussed, and in particular the relationship of colonoscopy to other tests for screening in the average risk population. FOBT (Hemoccult II, Hemoccult SENSA, FIT), flexible sigmoidoscopy alone with and without biopsy, flexible sigmoidoscopy with annual Hemoccult II and with annual Hemoccult SENSA, and colonoscopy are included. Because the CMS has not approved either CTC or stool DNA testing for CRC screening, there are no Medicare reimbursement rates for these tests. Our previous results of CEAs that we carried out for CMS in relationship to CT colonoscopy to assess a potential reimbursement level are summarized. Stool DNA testing is not included in this CEA. The capsule endoscopy is not discussed because there is insufficient evidence for effectiveness and it has not been included in any screening guidelines to date.

CEA of CRC screening tests has been conducted with varying cost structures and assumptions and has produced varying conclusions. In 2002, Pignone and colleagues provided a systematic review of CEA for CRC screening in the United States from 5 models and reported that the strategies of colonoscopy, sigmoidoscopy with or without FOBT (Hemoccult II), and FOBT alone all provided screening strategies that were less than $50,000 per life-year gained compared with no screening. However, no screening test strategy was consistently the most effective CRC strategy when they were compared with each other across the 5 models. To improve this situation the Institute of Medicine (IOM) convened a conference in 2004 to assess CRC screening CEAs. Representatives from each of the 5 models originally reviewed by Pignone and colleagues were asked to present at the January 2004 IOM conference and provide costs and LYG for 5 screening strategies (colonoscopy, sigmoidoscopy, sigmoidoscopy plus FOBT, FOBT alone, and a test similar to barium enema) under their original assumptions and again with standardized input assumptions concerning test characteristics, adherence to screening (100%), follow-up, and surveillance as well as for test costs and treatment costs. With standardized inputs, the models still varied in the absolute levels of costs and LYG, but the relative ordering of strategies with respect to cost-effectiveness results was comparable. Given a willingness to pay of $20,000 or $50,000 per life-year saved, the preferred strategy was annual FOBT. However, sigmoidoscopy plus annual FOBT was the preferred strategy in 4 of 5 models, for a willingness to pay of $100,000 per life-year saved.

Microsimulation modeling to inform health policy

Although randomized controlled trials are the preferred method for establishing effectiveness of (screening) interventions, they are expensive, require long follow-up, and can include only a few comparison tests. Therefore, well-validated microsimulation models may be used to estimate the required resources and expected benefits from different screening policies and inform decision making. There are 3 CRC microsimulation models in the National Cancer Institute’s Cancer Intervention and Surveillance Modeling Network (CISNET). The models are based on clinical incidence data before the introduction of screening (1975–1979) Surveillance, Epidemiology, and End Results [SEER] data and on the size distribution of adenomas in colonoscopy and autopsy studies. They have been validated against the long-term reductions in incidence and mortality of CRC with annual FOBT reported in the randomized controlled trial of the Minnesota Colon Cancer Control Study and show good concordance with the trial results. Transparency of the models is provided through standardized profiles of the structure of each model, and underlying model parameters and assumptions are available at http://cisnet.cancer.gov/profiles/ .

In this article, the results from one of the CISNET models (MISCAN: Mic rosimulation Sc reening An alysis, from Erasmus University Medical Center and Memorial–Sloan-Kettering Cancer Center) are used to provide CEA of the screening tests recommended by the 3 guideline groups. The results are from the CEA for CMS on CTC and a recent analysis of the different strategies relative to CTC. The primary analysis for this work was for a cohort of those 65 years of age. In this article the results of the secondary analysis for a cohort of those 50 years of age are used.

The MISCAN model simulates the life histories of a large population from birth to death in 2 situations: the natural history of the adenoma-carcinoma sequence and the effect of the screening intervention to detect and remove adenomas or CRC. As each simulated individual ages, there is a chance that an adenomatous polyp (a benign precursor lesion that may lead to CRC) may develop. One or more adenomas can occur in any individual and each can develop into preclinical CRC. The risk of developing an adenoma may depend on age, sex, genetic, and other propensity factors. Adenomas can grow and eventually some of them can become malignant, transforming to stage I preclinical cancer. A preclinical cancer (ie, not detected) has a chance of progressing through the stages (from stages I to IV) and may be detected by symptoms at any stage. The authors assume that adenomas are asymptomatic and can be detected only by a screening test ( Fig. 1 ).

Natural history of CRC as modeled by MISCAN model. Screening provides the opportunity to intervene in the natural history of the adenoma-carcinoma sequence. Screening can either remove a precancerous lesion (ie, adenoma), thus moving a person to the “no lesion” state, or provide early cancer detection, which makes an undiagnosed cancer clinically detected at a potentially earlier stage of disease when it is more amenable to treatment.

The effectiveness of each screening test is modeled through the ability of each test to detect lesions (ie, adenomas, preclinical cancer). Once screening is introduced, a simulated person who has developed an underlying adenoma or preclinical cancer has a chance of having it detected during a screening episode depending on the sensitivity of the test for that lesion. For screened persons without an underlying lesion we apply the false-positive rate (1–specificity) to determine whether or not that person will undergo an unnecessary follow-up examination. Hyperplastic polyps are not modeled explicitly but are reflected in the specificity of the test. Furthermore, a percentage of individuals with false-negative test results (ie, adenoma or preclinical cancer present but not detected) are referred to colonoscopy because of the detection of a hyperplastic polyp.

Comparative effectiveness research to compare CRC screening tests

In comparing screening tests, both the risk and benefits of screening for each particular test are considered. Risks are commonly represented by the costs and benefits by life-years gained (LYG). Incidence or mortality reduction obtained with screening can also be used to represent benefits. Comparative effectiveness research is the conduct and synthesis of research comparing the benefits and harms of various interventions and strategies for preventing, diagnosing, treating, and monitoring health conditions in real-world settings. The purpose is to improve health outcomes by developing and disseminating evidence-based information to patients, clinicians, and other decision makers about which interventions are most effective for which patients under specific circumstances.

In this article the cost-effectiveness of the recommended CRC screening tests is discussed, and in particular the relationship of colonoscopy to other tests for screening in the average risk population. FOBT (Hemoccult II, Hemoccult SENSA, FIT), flexible sigmoidoscopy alone with and without biopsy, flexible sigmoidoscopy with annual Hemoccult II and with annual Hemoccult SENSA, and colonoscopy are included. Because the CMS has not approved either CTC or stool DNA testing for CRC screening, there are no Medicare reimbursement rates for these tests. Our previous results of CEAs that we carried out for CMS in relationship to CT colonoscopy to assess a potential reimbursement level are summarized. Stool DNA testing is not included in this CEA. The capsule endoscopy is not discussed because there is insufficient evidence for effectiveness and it has not been included in any screening guidelines to date.

CEA of CRC screening tests has been conducted with varying cost structures and assumptions and has produced varying conclusions. In 2002, Pignone and colleagues provided a systematic review of CEA for CRC screening in the United States from 5 models and reported that the strategies of colonoscopy, sigmoidoscopy with or without FOBT (Hemoccult II), and FOBT alone all provided screening strategies that were less than $50,000 per life-year gained compared with no screening. However, no screening test strategy was consistently the most effective CRC strategy when they were compared with each other across the 5 models. To improve this situation the Institute of Medicine (IOM) convened a conference in 2004 to assess CRC screening CEAs. Representatives from each of the 5 models originally reviewed by Pignone and colleagues were asked to present at the January 2004 IOM conference and provide costs and LYG for 5 screening strategies (colonoscopy, sigmoidoscopy, sigmoidoscopy plus FOBT, FOBT alone, and a test similar to barium enema) under their original assumptions and again with standardized input assumptions concerning test characteristics, adherence to screening (100%), follow-up, and surveillance as well as for test costs and treatment costs. With standardized inputs, the models still varied in the absolute levels of costs and LYG, but the relative ordering of strategies with respect to cost-effectiveness results was comparable. Given a willingness to pay of $20,000 or $50,000 per life-year saved, the preferred strategy was annual FOBT. However, sigmoidoscopy plus annual FOBT was the preferred strategy in 4 of 5 models, for a willingness to pay of $100,000 per life-year saved.

Microsimulation modeling to inform health policy

Although randomized controlled trials are the preferred method for establishing effectiveness of (screening) interventions, they are expensive, require long follow-up, and can include only a few comparison tests. Therefore, well-validated microsimulation models may be used to estimate the required resources and expected benefits from different screening policies and inform decision making. There are 3 CRC microsimulation models in the National Cancer Institute’s Cancer Intervention and Surveillance Modeling Network (CISNET). The models are based on clinical incidence data before the introduction of screening (1975–1979) Surveillance, Epidemiology, and End Results [SEER] data and on the size distribution of adenomas in colonoscopy and autopsy studies. They have been validated against the long-term reductions in incidence and mortality of CRC with annual FOBT reported in the randomized controlled trial of the Minnesota Colon Cancer Control Study and show good concordance with the trial results. Transparency of the models is provided through standardized profiles of the structure of each model, and underlying model parameters and assumptions are available at http://cisnet.cancer.gov/profiles/ .

In this article, the results from one of the CISNET models (MISCAN: Mic rosimulation Sc reening An alysis, from Erasmus University Medical Center and Memorial–Sloan-Kettering Cancer Center) are used to provide CEA of the screening tests recommended by the 3 guideline groups. The results are from the CEA for CMS on CTC and a recent analysis of the different strategies relative to CTC. The primary analysis for this work was for a cohort of those 65 years of age. In this article the results of the secondary analysis for a cohort of those 50 years of age are used.

The MISCAN model simulates the life histories of a large population from birth to death in 2 situations: the natural history of the adenoma-carcinoma sequence and the effect of the screening intervention to detect and remove adenomas or CRC. As each simulated individual ages, there is a chance that an adenomatous polyp (a benign precursor lesion that may lead to CRC) may develop. One or more adenomas can occur in any individual and each can develop into preclinical CRC. The risk of developing an adenoma may depend on age, sex, genetic, and other propensity factors. Adenomas can grow and eventually some of them can become malignant, transforming to stage I preclinical cancer. A preclinical cancer (ie, not detected) has a chance of progressing through the stages (from stages I to IV) and may be detected by symptoms at any stage. The authors assume that adenomas are asymptomatic and can be detected only by a screening test ( Fig. 1 ).

Natural history of CRC as modeled by MISCAN model. Screening provides the opportunity to intervene in the natural history of the adenoma-carcinoma sequence. Screening can either remove a precancerous lesion (ie, adenoma), thus moving a person to the “no lesion” state, or provide early cancer detection, which makes an undiagnosed cancer clinically detected at a potentially earlier stage of disease when it is more amenable to treatment.

The effectiveness of each screening test is modeled through the ability of each test to detect lesions (ie, adenomas, preclinical cancer). Once screening is introduced, a simulated person who has developed an underlying adenoma or preclinical cancer has a chance of having it detected during a screening episode depending on the sensitivity of the test for that lesion. For screened persons without an underlying lesion we apply the false-positive rate (1–specificity) to determine whether or not that person will undergo an unnecessary follow-up examination. Hyperplastic polyps are not modeled explicitly but are reflected in the specificity of the test. Furthermore, a percentage of individuals with false-negative test results (ie, adenoma or preclinical cancer present but not detected) are referred to colonoscopy because of the detection of a hyperplastic polyp.

Study population

We used the natural history model to estimate the distribution of underlying disease in terms of the presence, location, size, and type (adenoma vs preclinical cancer) of lesions. We conducted an analysis of the effect of different screening strategies among a cohort of 50-year-old individuals in the US population in 2005 who have never been screened as our base case.

Test strategies

A test strategy includes the initial screening test as well as follow-up diagnosis of a positive test, diagnosis, and treatment of CRC and recurrent cancer, surveillance colonoscopy for those with adenomas, and treatment of any complications from screening. We compared the strategies of screening with FOBT every year, flexible sigmoidoscopy every 5 years, combinations of annual FOBT and sigmoidoscopy (every 5 years), and colonoscopy every 10 years. Although double-contrast barium enema was included in the 2002 screening recommendations for the USPSTF, it was not included in the 2008 USPSTF recommendations and is not considered in this analysis. We evaluated 3 FOBTs (Hemoccult II, Hemoccult SENSA, and FIT) and 2 strategies for sigmoidoscopy (with and without biopsy and also with and without FOBT), and 2 representations for CTC for a total of 14 screening strategies plus no screening.

We assumed that all individuals begin CRC screening at age 50 years as recommended by all 3 screening guidelines and end at age 80 years. A patient with a positive screening test is referred for colonoscopy. If adenomas are detected on colonoscopy then the individual begins surveillance with colonoscopy per the 2006 guidelines from the joint publication of the US Multi-Society Task Force and the American Cancer Society. The cohort was followed for their lifetimes to a maximum of age 100 years. The LYG per strategy were derived relative to no screening.

CRC screening test characteristics

The sensitivity and specificity of the FOBTs were based on a literature review and were consistent with those from the 2008 review of the evidence on CRC screening tests for the USPSTF. There are multiple FITs with varying cut points for positivity, number of slides, number of days tested, and preparations reported in the literature. Consequently FIT sensitivity and specificity criteria vary widely. The OC-Sensor FIT has recently been used in clinical trials in Holland and Northern California at Kaiser Permanente (TR Levin, personal communication, 2010). Sensitivities for colonoscopy were based on a meta-analysis ; we assumed the same sensitivities for sigmoidoscopy within the reach of the endoscope. We assumed that 5% of subjects have more than one colonoscopy to visualize the entire colon and that the cecum is ultimately reached in 98% of subjects. For sigmoidoscopy, we assumed that 80% of examinations reach the junction of the sigmoid and descending colon and 40% reach the beginning of the splenic flexure. The test characteristics were consistent with the evidence review used in the USPSTF recommendations. The test characteristics for CTC were based on 2 clinical trials: Department of Defense (DoD) and the National CT Colonography Trial (ACRIN 6664).

Table 2 contains an overview of test characteristics used in our analyses. Test parameters are given by person for the fecal tests and by lesion for colonoscopy, flexible sigmoidoscopy, and CTC. The sensitivities stated in Table 2 are based on sensitivities of the test at one point in time. However, the LYG and the costs for each test strategy are based on repeated screening.

Costs

Cost reimbursements for the components of screening vary by type of insurance plans, and copayments. In this article we present as an example the derivation of costs of a screening strategy based on Medicare reimbursement (without copayments) for each of the recommended screening tests and use these costs in conjunction with the MISCAN microsimulation model for the LYG with screening for each test. We recognize that costs vary in practice but use Medicare reimbursement without copayments as one standardized measure for costs.

Payer’s Perspective

The base case CEA was from the payer’s (CMS) perspective with costs stated as those that Medicare pays and based on Medicare payments of 2007 for procedures and tests associated with CRC screening, complications of screening, and treatment. These payments reflect approximately 80% of the allowable charge, including the facility charges (as applicable) and physician services charges. (Thus the beneficiary’s copay is not reflected in the analysis.) We also conducted an analysis from a modified societal perspective by including direct costs borne by beneficiaries as well as estimated patient time costs, but excluding costs caused by lost productivity caused by early death or disability.

The screening test costs are provided in Table 3 . Screening-related costs are based on the set of current procedural terminology (CPT) codes relevant to CRC screening in conjunction with the points of service for the procedures: (1) in the Ambulatory Surgery Center (ASC) setting, we include the Medicare ASC facility payment and the payment for physician professional services; (2) in the Outpatient Prospective Payment System (OPPS) setting, we include the Medicare OPPS facility payment and the payment for physician services; and (3) in the office setting, we include the payment to the physician that covers both the professional services and the facility costs of the physician’s office. The total costs per CPT code are weighted by the frequencies for points of service. Then the total costs per screening procedure are based on the total costs per CPT code that are part of the procedure and weighted by the frequencies of the CPT codes. Payments for a procedure across these settings are represented as an average of the 3 settings weighted by the frequency of which each setting is used for the procedure in 2007. We do not include the cost of a separate office visit for any of the screening strategies as we assume that all recommendations or arrangements for screening would already be associated with a previously scheduled office visit. Payer cost for Hemoccult II, Hemoccult SENSA, and fecal immunochemical testing does not include additional charges for points of service because these costs are related only to the clinical laboratory fee schedule ( http://www.cms.hhs.gov/ClinicalLabFeeSched/ ).

Table 3

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