Opportunities and Challenges in Moving From Current Guidelines to Personalized Colorectal Cancer Screening
2018; Elsevier BV; Volume: 156; Issue: 4 Linguagem: Inglês
10.1053/j.gastro.2018.12.012
ISSN1528-0012
AutoresDouglas J. Robertson, Uri Ladabaum,
Tópico(s)Gastric Cancer Management and Outcomes
ResumoColorectal cancer (CRC) remains the second most common cause of cancer death in the United States.1Siegel R.L. Miller K.D. Jemal A. Cancer statistics, 2019.CA Cancer J Clin. 2019; 69: 7-34Crossref PubMed Scopus (16045) Google Scholar However, CRC incidence and mortality have been decreasing over the past 4 decades, and screening has contributed substantially to these gains.2Welch H.G. Robertson D.J. Colorectal cancer on the decline—why screening can't explain it all.N Engl J Med. 2016; 374: 1605-1607Crossref PubMed Scopus (145) Google Scholar, 3Siegel R.L. Fedewa S.A. Anderson W.F. et al.Colorectal cancer incidence patterns in the United States, 1974–2013.J Natl Cancer Inst. 2017; : 109Google Scholar, 4Edwards B.K. Ward E. Kohler B.A. et al.Annual report to the nation on the status of cancer, 1975–2006, featuring colorectal cancer trends and impact of interventions (risk factors, screening, and treatment) to reduce future rates.Cancer. 2010; 116: 544-573Crossref PubMed Scopus (1586) Google Scholar Screening aims to identify disease in asymptomatic individuals at an early stage, in the hope of improving outcomes. CRC lends itself very well to screening, as early-stage CRC has a highly favorable prognosis relative to more advanced disease. Also, the transition from normal mucosa through preneoplastic disease (ie, polyps) to CRC is estimated to be a decade or more.5Kuntz K.M. Lansdorp-Vogelaar I. Rutter C.M. et al.A systematic comparison of microsimulation models of colorectal cancer: the role of assumptions about adenoma progression.Med Decis Making. 2011; 31: 530-539Crossref PubMed Scopus (84) Google Scholar Therefore, finding and removing preneoplastic lesions can reduce CRC incidence. Screening is widely employed in the United States, largely in an opportunistic fashion. While there is no national CRC screening policy or program, there are multiple guidelines endorsing CRC screening.6Rex D.K. Johnson D.A. Anderson J.C. et al.American College of Gastroenterology guidelines for colorectal cancer screening 2009 [corrected].Am J Gastroenterol. 2009; 104: 739-750Crossref PubMed Scopus (1199) Google Scholar, 7Rex D.K. Boland C.R. Dominitz J.A. et al.Colorectal cancer screening: recommendations for physicians and patients from the US Multi-Society Task Force on Colorectal Cancer.Gastroenterology. 2017; 153: 307-323Abstract Full Text Full Text PDF PubMed Scopus (460) Google Scholar, 8Qaseem A. Denberg T.D. Hopkins Jr., R.H. et al.Screening for colorectal cancer: a guidance statement from the American College of Physicians.Ann Intern Med. 2012; 156: 378-386Crossref PubMed Scopus (267) Google Scholar, 9Bibbins-Domingo K. Grossman D.C. et al.US Preventive Services Task ForceScreening for Colorectal Cancer: US Preventive Services Task Force Recommendation Statement.JAMA. 2016; 315: 2564-2575Crossref PubMed Scopus (1382) Google Scholar, 10Wolf A.M.D. Fontham E.T.H. Church T.R. et al.Colorectal cancer screening for average-risk adults: 2018 guideline update from the American Cancer Society.CA Cancer J Clin. 2018; 68: 250-281Crossref PubMed Scopus (1152) Google Scholar Most guidelines, in average-risk populations, recommend initiating CRC screening at age 50 years with one of the available methods. While there is some variation in recommendations by age and race, factors beyond these are not currently used to tailor individual recommendations. This review addresses current CRC epidemiology, screening practice, and guidelines in the United States, and considers how individual risk factors might be used to personalize CRC screening. We first summarize the burden of CRC and current screening efforts. Next, we examine current guidelines for variation regarding the approach to age, sex, and race, and we explain how decision analytic modeling has informed recent guidelines. We then review factors beyond demographic characteristics (eg, smoking, obesity) that affect CRC risk and provide potential opportunities for personalized screening, including the development of risk-prediction models that include biomarkers. Finally, we consider future directions for research and practice, including the opportunities and challenges related to implementing personalized CRC screening. The American Cancer Society (ACS) provides annual cancer statistics for the United States.1Siegel R.L. Miller K.D. Jemal A. Cancer statistics, 2019.CA Cancer J Clin. 2019; 69: 7-34Crossref PubMed Scopus (16045) Google Scholar These statistics are drawn from a number of sources. For example, mortality data are abstracted from the National Center for Health Statistics, and cancer incidence data from the National Cancer Institute's Surveillance, Epidemiology and End Results (SEER) Program. The most recent ACS report estimates that there will be 145,600 new CRC cases and 51,020 CRC-related deaths in the United States this year.1Siegel R.L. Miller K.D. Jemal A. Cancer statistics, 2019.CA Cancer J Clin. 2019; 69: 7-34Crossref PubMed Scopus (16045) Google Scholar CRC remains the third most common cause of cancer and cancer death for both sexes, trailing only lung and prostate cancer in men and lung and breast cancer in women. Age standardized CRC incidence and mortality trends in the United States are improving (Figure 1). From 1975 through 2015, overall CRC mortality fell from 28.1/100,000 to 14/100,000.11Fast Stats: An interactive tool for access to SEER cancer statistics: Surveillance Research Program, National Cancer Institute.Google Scholar Like cancer statistics, data on screening are also drawn from various sources. Based on 2015 National Health Interview Survey data, 62% of US adults reported undergoing a CRC screening test endorsed by the US Preventative Services Task Force (USPSTF).12White A. Thompson T.D. White M.C. et al.Cancer screening test use—United States, 2015.MMWR Morb Mortal Wkly Rep. 2017; 66: 201-206Crossref PubMed Scopus (368) Google Scholar The National Committee for Quality Assurance reports on multiple Healthcare Effectiveness Data and Information Set measures, including screening test use from commercial health plans and the Centers for Medicare and Medicaid Services.13Healthcare Effectiveness Data and Information Set (HEDIS). National Committee for Quality Assurance.https://www.ncqa.org/hedis/measures/colorectal-cancer-screening/. Accessed September 7, 2018.Google Scholar The 2016 report demonstrates that CRC screening rates are higher in Centers for Medicare and Medicaid Services populations (67%–70%) than in commercial plans (58%–62%), but remain significantly short of the 80% target set by the National Colorectal Cancer Roundtable to be achieved by 2018.14Meester R.G. Doubeni C.A. Zauber A.G. et al.Public health impact of achieving 80% colorectal cancer screening rates in the United States by 2018.Cancer. 2015; 121: 2281-2285Crossref PubMed Scopus (163) Google Scholar The United States does not have a single CRC screening program or policy. Rather, there exist several guidelines6Rex D.K. Johnson D.A. Anderson J.C. et al.American College of Gastroenterology guidelines for colorectal cancer screening 2009 [corrected].Am J Gastroenterol. 2009; 104: 739-750Crossref PubMed Scopus (1199) Google Scholar, 7Rex D.K. Boland C.R. Dominitz J.A. et al.Colorectal cancer screening: recommendations for physicians and patients from the US Multi-Society Task Force on Colorectal Cancer.Gastroenterology. 2017; 153: 307-323Abstract Full Text Full Text PDF PubMed Scopus (460) Google Scholar, 8Qaseem A. Denberg T.D. Hopkins Jr., R.H. et al.Screening for colorectal cancer: a guidance statement from the American College of Physicians.Ann Intern Med. 2012; 156: 378-386Crossref PubMed Scopus (267) Google Scholar, 9Bibbins-Domingo K. Grossman D.C. et al.US Preventive Services Task ForceScreening for Colorectal Cancer: US Preventive Services Task Force Recommendation Statement.JAMA. 2016; 315: 2564-2575Crossref PubMed Scopus (1382) Google Scholar, 10Wolf A.M.D. Fontham E.T.H. Church T.R. et al.Colorectal cancer screening for average-risk adults: 2018 guideline update from the American Cancer Society.CA Cancer J Clin. 2018; 68: 250-281Crossref PubMed Scopus (1152) Google Scholar from national bodies (ie, the USPSTF) and other societies (eg, US Multi-Society Task Force and the ACS). Table 1 summarizes the key recommendations of the major guidelines, including starting and stopping ages and the endorsed screening tests.Table 1Summary of Current US Colorectal Cancer Screening GuidelinesGuidelineYearStarting age, yStopping age, ySexRaceEndorsed screening testsPreferred screening testACS10Wolf A.M.D. Fontham E.T.H. Church T.R. et al.Colorectal cancer screening for average-risk adults: 2018 guideline update from the American Cancer Society.CA Cancer J Clin. 2018; 68: 250-281Crossref PubMed Scopus (1152) Google Scholar201845 (qualified)50 (strong)"Discourage over age 85"No tailoring—FIT, high-sensitivity FOBT, mtDNA, colonoscopy, CTC, FSNoneUS Multi-Society Task Force7Rex D.K. Boland C.R. Dominitz J.A. et al.Colorectal cancer screening: recommendations for physicians and patients from the US Multi-Society Task Force on Colorectal Cancer.Gastroenterology. 2017; 153: 307-323Abstract Full Text Full Text PDF PubMed Scopus (460) Google Scholar201750"Potentially beneficial up to age 86"No tailoringAfrican American start age 45 yFIT, colonoscopy, CTC, mtDNA, FS, capsule colonoscopyTier 1Colonoscopy, FITUSPSTF9Bibbins-Domingo K. Grossman D.C. et al.US Preventive Services Task ForceScreening for Colorectal Cancer: US Preventive Services Task Force Recommendation Statement.JAMA. 2016; 315: 2564-2575Crossref PubMed Scopus (1382) Google Scholar201650Through 75 (grade A)76–85 (Individualized)No tailoring—FIT, high-sensitivity FOBT, mtDNA, Colonoscopy, CTC, FS, FS, and FITNoneAmerican College of Physicians8Qaseem A. Denberg T.D. Hopkins Jr., R.H. et al.Screening for colorectal cancer: a guidance statement from the American College of Physicians.Ann Intern Med. 2012; 156: 378-386Crossref PubMed Scopus (267) Google Scholar201250Adults >75No tailoringAfrican American start age 40 yFIT, FOBT, mtDNA, colonoscopy, CTC, FS"Stool-based test, flexible sigmoidoscopy, or optical colonoscopy"American College of Gastroenterology6Rex D.K. Johnson D.A. Anderson J.C. et al.American College of Gastroenterology guidelines for colorectal cancer screening 2009 [corrected].Am J Gastroenterol. 2009; 104: 739-750Crossref PubMed Scopus (1199) Google Scholar201050Not explicitNo tailoringAfrican American start age 45 yFIT, high-sensitivity FOBT, mtDNA, colonoscopy, CTC, FSColonoscopyFOBT, fecal occult blood test; FS, flexible sigmoidoscopy; mtDNA, multi-target DNA. Open table in a new tab FOBT, fecal occult blood test; FS, flexible sigmoidoscopy; mtDNA, multi-target DNA. It has generally been recommended to start CRC screening at age 50 years in average-risk adults. The most recent ACS guidelines10Wolf A.M.D. Fontham E.T.H. Church T.R. et al.Colorectal cancer screening for average-risk adults: 2018 guideline update from the American Cancer Society.CA Cancer J Clin. 2018; 68: 250-281Crossref PubMed Scopus (1152) Google Scholar include a qualified recommendation to start at age 45 years in all average-risk individuals. Most guidelines recommend screening through age 75 years. Guidelines note that decisions about screening beyond that age need to be individualized and based on factors including overall health and screening history. Several guidelines recommend against9Bibbins-Domingo K. Grossman D.C. et al.US Preventive Services Task ForceScreening for Colorectal Cancer: US Preventive Services Task Force Recommendation Statement.JAMA. 2016; 315: 2564-2575Crossref PubMed Scopus (1382) Google Scholar or discourage10Wolf A.M.D. Fontham E.T.H. Church T.R. et al.Colorectal cancer screening for average-risk adults: 2018 guideline update from the American Cancer Society.CA Cancer J Clin. 2018; 68: 250-281Crossref PubMed Scopus (1152) Google Scholar screening after age 85 years. Although age-specific CRC risks are higher in men than women, no guideline specifically recommends a tailored approach based on sex (eg, adjusting the starting age or type of test used). Some guidelines endorse earlier screening in African Americans, based on factors such as a higher overall CRC risk, which we will review. The US Multi-Society Task Force recommends starting screening in African Americans at age 45 years7Rex D.K. Boland C.R. Dominitz J.A. et al.Colorectal cancer screening: recommendations for physicians and patients from the US Multi-Society Task Force on Colorectal Cancer.Gastroenterology. 2017; 153: 307-323Abstract Full Text Full Text PDF PubMed Scopus (460) Google Scholar and the American College of Physicians recommends at 40 years.8Qaseem A. Denberg T.D. Hopkins Jr., R.H. et al.Screening for colorectal cancer: a guidance statement from the American College of Physicians.Ann Intern Med. 2012; 156: 378-386Crossref PubMed Scopus (267) Google Scholar The guidelines generally agree on the recommended tests. All include stool-based tests (fecal immunochemical test [FIT], guaiac-based fecal occult blood test, and the multi-target stool DNA test), and structural examinations (colonoscopy, flexible sigmoidoscopy, computed tomography colonography [CTC]). Although the most recent iterations of the USPSTF and ACS guidelines do not rank tests by preference, the US Multi-Society Task Force guideline ranks colonoscopy and FIT in tier 1, and the American College of Gastroenterology guideline expresses preference for colonoscopy. It is not feasible to perform long-term comparative CRC screening trials of all possible strategies and population subgroups. Decision analytic models can supplement experimental and observational data by making projections based on available information. Models can be used to address key questions, such as comparative effectiveness,15Knudsen A.B. Zauber A.G. Rutter C.M. et al.Estimation of benefits, burden, and harms of colorectal cancer screening strategies: modeling study for the US Preventive Services Task Force.Jama. 2016; 315: 2595-2609Crossref PubMed Scopus (362) Google Scholar, 16Meester R.G.S. Peterse E.F.P. Knudsen A.B. et al.Optimizing colorectal cancer screening by race and sex: microsimulation analysis II to inform the American Cancer Society colorectal cancer screening guideline.Cancer. 2018; 124: 2974-2985Crossref PubMed Scopus (61) Google Scholar, 17Peterse E.F.P. Meester R.G.S. Siegel R.L. et al.The impact of the rising colorectal cancer incidence in young adults on the optimal age to start screening: microsimulation analysis I to inform the American Cancer Society colorectal cancer screening guideline.Cancer. 2018; 124: 2964-2973Crossref PubMed Scopus (151) Google Scholar, 18Ladabaum U. Song K. 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Wandell M. et al.Colorectal cancer screening with blood-based biomarkers: cost-effectiveness of methylated septin 9 DNA versus current strategies.Cancer Epidemiol Biomarkers Prev. 2013; 22: 1567-1576Crossref PubMed Scopus (69) Google Scholar or hybrid screening strategies,21Dinh T. Ladabaum U. Alperin P. et al.Health benefits and cost-effectiveness of a hybrid screening strategy for colorectal cancer.Clin Gastroenterol Hepatol. 2013; 11: 1158-1166Abstract Full Text Full Text PDF PubMed Scopus (39) Google Scholar, 22Ladabaum U. Alvarez-Osorio L. Rosch T. et al.Cost-effectiveness of colorectal cancer screening in Germany: current endoscopic and fecal testing strategies versus plasma methylated Septin 9 DNA.Endosc Int Open. 2014; 2: e96-e104Crossref PubMed Google Scholar implications for payers,23Ladabaum U. Mannalithara A. Brill J.V. et al.Contrasting effectiveness and cost-effectiveness of colorectal cancer screening under commercial insurance vs Medicare.Am J Gastroenterol. 2018; 113: 1836-1847Crossref PubMed Scopus (15) Google Scholar and population-wide impact.18Ladabaum U. Song K. Projected national impact of colorectal cancer screening on clinical and economic outcomes and health services demand.Gastroenterology. 2005; 129: 1151-1162Abstract Full Text Full Text PDF PubMed Scopus (135) Google Scholar In cost-effectiveness analysis, strategies can be compared on the basis of the incremental cost per life-year gained (LYG).24Neumann P.J. Cohen J.T. Weinstein M.C. Updating cost-effectiveness—the curious resilience of the $50,000-per-QALY threshold.N Engl J Med. 2014; 371: 796-797Crossref PubMed Scopus (1655) Google Scholar When cost is not considered, an alternative measure of burden can be considered, such as colonoscopies required, as we will illustrate. Decision analytic models are useful to inform policy about populations, but are generally not designed to be applied to individuals. Models from the National Cancer Institute's Cancer Intervention and Surveillance Modeling Network25Zauber A, Knudsen A, Rutter CM, et al. Evaluating the Benefits and Harms of Colorectal Cancer Screening Strategies: A Collaborative Modeling Approach. AHRQ Publication No. 14-05203-EF-2 2015.Google Scholar consortium informed the recent USPSTF guidelines9Bibbins-Domingo K. Grossman D.C. et al.US Preventive Services Task ForceScreening for Colorectal Cancer: US Preventive Services Task Force Recommendation Statement.JAMA. 2016; 315: 2564-2575Crossref PubMed Scopus (1382) Google Scholar (Microsimulation Screening Analysis [MISCAN] for Colorectal Cancer, Simulation Model of Colorectal Cancer, and Colorectal Cancer Simulated Population Model for Incidence and Natural History), and the recent ACS guidelines10Wolf A.M.D. Fontham E.T.H. Church T.R. et al.Colorectal cancer screening for average-risk adults: 2018 guideline update from the American Cancer Society.CA Cancer J Clin. 2018; 68: 250-281Crossref PubMed Scopus (1152) Google Scholar (MISCAN and Simulation Model of Colorectal Cancer). The 3 Cancer Intervention and Surveillance Modeling Network CRC models simulate the occurrence and growth of adenomas in individuals in a population, and their possible evolution into preclinical and clinical CRC.25Zauber A, Knudsen A, Rutter CM, et al. Evaluating the Benefits and Harms of Colorectal Cancer Screening Strategies: A Collaborative Modeling Approach. AHRQ Publication No. 14-05203-EF-2 2015.Google Scholar Screening is superimposed on natural history. Fundamental assumptions about adenoma and CRC behavior contribute to differences in the models' predictions.25Zauber A, Knudsen A, Rutter CM, et al. Evaluating the Benefits and Harms of Colorectal Cancer Screening Strategies: A Collaborative Modeling Approach. AHRQ Publication No. 14-05203-EF-2 2015.Google Scholar Until the ACS modeling described here, the models were calibrated to CRC epidemiology from decades ago, before widespread screening could have affected CRC incidence and mortality. The USPSTF requested modeling from Cancer Intervention and Surveillance Modeling Network to inform its 2016 recommendations.9Bibbins-Domingo K. Grossman D.C. et al.US Preventive Services Task ForceScreening for Colorectal Cancer: US Preventive Services Task Force Recommendation Statement.JAMA. 2016; 315: 2564-2575Crossref PubMed Scopus (1382) Google Scholar Because the USPSTF does not consider cost, the number of colonoscopies required by a given strategy was used as the measure of screening burden, and strategies were compared on the basis of the incremental number of colonoscopies per LYG (defined as the efficiency ratio [ER]).15Knudsen A.B. Zauber A.G. Rutter C.M. et al.Estimation of benefits, burden, and harms of colorectal cancer screening strategies: modeling study for the US Preventive Services Task Force.Jama. 2016; 315: 2595-2609Crossref PubMed Scopus (362) Google Scholar There is no consensus on what is an acceptable ER. Thus, the choice of a benchmark strategy—the initial stake in the ground—was a key decision. Multiple screening tests performed at various intervals, starting at age 45 years or 50 years or 55 years, and ending at age 75 years or 80 years or 85 years were evaluated. Within each test class (eg, fecal tests), the LYG and the colonoscopy burden were plotted, creating an efficiency frontier, which is the curve connecting the strategies that provide the largest incremental increase in LYG per additional colonoscopy performed. Model-recommended strategies were determined as follows: 1) a colonoscopy benchmark strategy was selected based on the ERs of alternative colonoscopy strategies; 2) in each class, strategies not on the efficiency frontier (or close to it), or with ERs larger than the benchmark, were eliminated; 3) strategies recommendable by at least 2 of the 3 models (maximum of one test per test class) were included in the final set. The 4 model recommendable strategies from ages 50 through 75 years were colonoscopy every 10 years, annual FIT, sigmoidoscopy every 10 years with annual FIT, and CTC every 5 years.15Knudsen A.B. Zauber A.G. Rutter C.M. et al.Estimation of benefits, burden, and harms of colorectal cancer screening strategies: modeling study for the US Preventive Services Task Force.Jama. 2016; 315: 2595-2609Crossref PubMed Scopus (362) Google Scholar It is important to note that even though strategies beginning at age 45 years were predominant on the efficiency frontiers, the USPSTF requested that the final analyses include only strategies beginning at age 50 years.9Bibbins-Domingo K. Grossman D.C. et al.US Preventive Services Task ForceScreening for Colorectal Cancer: US Preventive Services Task Force Recommendation Statement.JAMA. 2016; 315: 2564-2575Crossref PubMed Scopus (1382) Google Scholar, 15Knudsen A.B. Zauber A.G. Rutter C.M. et al.Estimation of benefits, burden, and harms of colorectal cancer screening strategies: modeling study for the US Preventive Services Task Force.Jama. 2016; 315: 2595-2609Crossref PubMed Scopus (362) Google Scholar This decision was based on the relatively small LYG in comparison to the required colonoscopies when starting at age 45 years vs 50 years, the fact that 2 but not 3 models agreed on the acceptability of starting at age 45 years, and the limited empirical data for lowering the screening age. The final USPSTF recommendations included strategies (guaiac-based fecal occult blood test yearly, FIT DNA every 1 or 3 years, sigmoidoscopy every 5 years) that were not on the strictly defined list of model-recommendable strategies, and all recommended strategies were endorsed as a grade A recommendation without any ranking.9Bibbins-Domingo K. Grossman D.C. et al.US Preventive Services Task ForceScreening for Colorectal Cancer: US Preventive Services Task Force Recommendation Statement.JAMA. 2016; 315: 2564-2575Crossref PubMed Scopus (1382) Google Scholar The final judgment considered the totality of the evidence, with modeling supplementing clinical data. The ACS requested that the MISCAN model re-evaluate the optimal age to start screening10Wolf A.M.D. Fontham E.T.H. Church T.R. et al.Colorectal cancer screening for average-risk adults: 2018 guideline update from the American Cancer Society.CA Cancer J Clin. 2018; 68: 250-281Crossref PubMed Scopus (1152) Google Scholar in light of emerging evidence that CRC risk has increased in persons under 50 years of age.3Siegel R.L. Fedewa S.A. Anderson W.F. et al.Colorectal cancer incidence patterns in the United States, 1974–2013.J Natl Cancer Inst. 2017; : 109Google Scholar The ACS also does not consider cost when making its recommendations. The principal outcome was LYG, and the burden was colonoscopies required. For the overall population analysis, MISCAN was recalibrated to recent data on CRC risk.17Peterse E.F.P. Meester R.G.S. Siegel R.L. et al.The impact of the rising colorectal cancer incidence in young adults on the optimal age to start screening: microsimulation analysis I to inform the American Cancer Society colorectal cancer screening guideline.Cancer. 2018; 124: 2964-2973Crossref PubMed Scopus (151) Google Scholar A contemporary cohort of 40-year-olds was assumed to have a 1.59-fold higher risk3Siegel R.L. Fedewa S.A. Anderson W.F. et al.Colorectal cancer incidence patterns in the United States, 1974–2013.J Natl Cancer Inst. 2017; : 109Google Scholar than the cohorts modeled for the USPSTF in 2016. Additional analyses stratified by sex and race (African American or white) were performed in both MISCAN and Simulation Model of Colorectal Cancer, assuming past or higher current CRC risk levels.16Meester R.G.S. Peterse E.F.P. Knudsen A.B. et al.Optimizing colorectal cancer screening by race and sex: microsimulation analysis II to inform the American Cancer Society colorectal cancer screening guideline.Cancer. 2018; 124: 2974-2985Crossref PubMed Scopus (61) Google Scholar In a process similar to the one used for the USPSTF analyses, colonoscopy every 10 years from age 45 to 75 years emerged as the benchmark. The other model-recommendable strategies, all from age 45 to 75 years, were FIT yearly, sigmoidoscopy every 5 years, and CTC every 5 years.17Peterse E.F.P. Meester R.G.S. Siegel R.L. et al.The impact of the rising colorectal cancer incidence in young adults on the optimal age to start screening: microsimulation analysis I to inform the American Cancer Society colorectal cancer screening guideline.Cancer. 2018; 124: 2964-2973Crossref PubMed Scopus (151) Google Scholar In analyses by sex and race, the conclusions depended on whether the original or elevated CRC risk was assumed.16Meester R.G.S. Peterse E.F.P. Knudsen A.B. et al.Optimizing colorectal cancer screening by race and sex: microsimulation analysis II to inform the American Cancer Society colorectal cancer screening guideline.Cancer. 2018; 124: 2974-2985Crossref PubMed Scopus (61) Google Scholar Both models recommended beginning screening at age 45 years in African-American and white women and men when elevated CRC risk was assumed. However, when the original CRC risk was assumed, both models recommended beginning at age 45 years in African-American women and men, but they disagreed about the starting age in white women and men (45 in Simulation Model of Colorectal Cancer vs 50 in MISCAN). The modeling results informed the ACS recommendation to begin screening at age 45 years in both sexes and without distinction by race,10Wolf A.M.D. Fontham E.T.H. Church T.R. et al.Colorectal cancer screening for average-risk adults: 2018 guideline update from the American Cancer Society.CA Cancer J Clin. 2018; 68: 250-281Crossref PubMed Scopus (1152) Google Scholar in the context of data that demonstrate increasing CRC risk as a birth-cohort effect.3Siegel R.L. Fedewa S.A. Anderson W.F. et al.Colorectal cancer incidence patterns in the United States, 1974–2013.J Natl Cancer Inst. 2017; : 109Google Scholar It is important to appreciate that the modeling for the ACS explicitly allowed for a colonoscopy benchmark strategy that begins at age 45 years, whereas the USPSTF specifically requested that the final analyses include only strategies beginning at age 50 years. Modeling might inform more nuanced screening guidelines for subpopulations. This is illustrated by studies focusing on persons with diabetes,26Dinh T.A. Alperin P. Walter L.C. et al.Impact of comorbidity on colorectal cancer screening cost-effectiveness study in diabetic populations.J Gen Intern Med. 2012; 27: 730-738Crossref PubMed Scopus (13) Google Scholar a family history of CRC,27Naber S.K. Kuntz K.M. Henrikson N.B. et al.Cost effectiveness of age-specific screening intervals for people with family histories of colorectal cancer.Gastroenterology. 2018; 154: 105-116.e20Abstract Full Text Full Text PDF PubMed Scopus (23) Google Scholar high-risk patients in a regional screening program,28Ladabaum U. Ferrandez A. Lanas A. Cost-effectiveness of colorectal cancer screening in high-risk Spanish patients: use of a validated model to inform public policy.Cancer Epidemiol Biomarkers Prev. 2010; 19: 2765-2776Crossref PubMed Scopus (24) Google Scholar patients with cystic fibrosis,29Gini A. Zauber A.G. Cenin D.R. et al.Cost effectiveness of screening individuals with cystic fibrosis for colorectal cancer.Gastroenterology. 2018; 154: 556-567.e18Abstract Full Text Full Text PDF PubMed Scopus (20) Google Scholar and elderly persons with a spectrum of comorbidities.30van Hees F. Saini S.D. Lansdorp-Vogelaar I. et al.Personalizing colonoscopy screening for elderly individuals based on screening history, cancer risk, and comorbidity status could increase cost effectiveness.Gastroenterology. 2015; 149: 1425-1437Abstract Full Text Full Text PDF PubMed Scopus (62) Google Scholar Several demographic (age, sex, race) and other factors (eg, smoking, body mass index [BMI]) are associated with CRC risk and could potentially be used to tailor screening beyond the recommendations in current guidelines. Age is one of the strongest predictors of CRC risk. CRC incidence increases markedly after age 50 years. SEER data for 2015 demonstrate an age-adjusted CRC incidence increase from approximately 13/100,000 at ages 20–49 years to 208/100,000 at ages 75 and older (Figure 2A).31US Cancer Statistics Working Group. US Cancer Statistics Data Visualizations Tool, based on November
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