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Figure 1.  Study Flowchart
Study Flowchart

CRC indicates colorectal cancer.

Figure 2.  Individuals Aged 50 to 75 Years Who Were Up to Date With Colorectal Cancer (CRC) Screening
Individuals Aged 50 to 75 Years Who Were Up to Date With Colorectal Cancer (CRC) Screening

mt-sDNA indicates multitarget stool DNA.

Figure 3.  Screening Patterns Among All Individuals Aged 50 to 75 Years Who Were Due for Screening and Newly Screened
Screening Patterns Among All Individuals Aged 50 to 75 Years Who Were Due for Screening and Newly Screened

FIT indicates fecal immunochemical test; FOBT, fecal occult blood test; and mt-sDNA, multitarget stool DNA.

Table 1.  Demographic Characteristicsa
Demographic Characteristicsa
Table 2.  Proportion of Individuals With Average Risk for Colorectal Cancer by Screening Status and Type of Screening, Segmented by Age on August 1, 2011
Proportion of Individuals With Average Risk for Colorectal Cancer by Screening Status and Type of Screening, Segmented by Age on August 1, 2011
1.
Siegel  RL, Miller  KD, Jemal  A.  Cancer statistics, 2020.   CA Cancer J Clin. 2020;70(1):7-30. doi:10.3322/caac.21590PubMedGoogle ScholarCrossref
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Shaukat  A, Mongin  SJ, Geisser  MS,  et al.  Long-term mortality after screening for colorectal cancer.   N Engl J Med. 2013;369(12):1106-1114. doi:10.1056/NEJMoa1300720PubMedGoogle ScholarCrossref
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Zauber  AG, Winawer  SJ, O’Brien  MJ,  et al.  Colonoscopic polypectomy and long-term prevention of colorectal-cancer deaths.   N Engl J Med. 2012;366(8):687-696. doi:10.1056/NEJMoa1100370PubMedGoogle ScholarCrossref
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Meester  RGS, Doubeni  CA, Zauber  AG,  et al.  Public health impact of achieving 80% colorectal cancer screening rates in the United States by 2018.   Cancer. 2015;121(13):2281-2285. doi:10.1002/cncr.29336PubMedGoogle ScholarCrossref
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Siegel  RL, Miller  KD, Goding Sauer  A,  et al.  Colorectal cancer statistics, 2020.   CA Cancer J Clin. 2020;70(3):145-164. doi:10.3322/caac.21601PubMedGoogle ScholarCrossref
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Huguet  N, Angier  H, Rdesinski  R,  et al.  Cervical and colorectal cancer screening prevalence before and after Affordable Care Act Medicaid expansion.   Prev Med. 2019;124:91-97. doi:10.1016/j.ypmed.2019.05.003PubMedGoogle ScholarCrossref
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Wyatt  TE, Pernenkil  V, Akinyemiju  TF.  Trends in breast and colorectal cancer screening among US adults by race, healthcare coverage, and SES before, during, and after the Great Recession.   Prev Med Rep. 2017;7:239-245. doi:10.1016/j.pmedr.2017.04.001PubMedGoogle ScholarCrossref
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Bibbins-Domingo  K, Grossman  DC, Curry  SJ,  et al; US Preventive Services Task Force.  Screening for colorectal cancer: US Preventive Services Task Force recommendation statement.   JAMA. 2016;315(23):2564-2575. doi:10.1001/jama.2016.5989PubMedGoogle Scholar
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Wolf  AMD, Fontham  ETH, Church  TR,  et al.  Colorectal cancer screening for average-risk adults: 2018 guideline update from the American Cancer Society.   CA Cancer J Clin. 2018;68(4):250-281. doi:10.3322/caac.21457PubMedGoogle ScholarCrossref
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Provenzale  D, Ness  RM, Llor  X,  et al.  NCCN guidelines insights: colorectal cancer screening, version 2.2020.   J Natl Compr Canc Netw. 2020;18(10):1312-1320. doi:10.6004/jnccn.2020.0048PubMedGoogle ScholarCrossref
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Rex  DK, Boland  CR, Dominitz  JA,  et al.  Colorectal cancer screening: recommendations for physicians and patients from the US Multi-Society Task Force on Colorectal Cancer.   Am J Gastroenterol. 2017;112(7):1016-1030. doi:10.1038/ajg.2017.174PubMedGoogle ScholarCrossref
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von Elm  E, Altman  DG, Egger  M, Pocock  SJ, Gøtzsche  PC, Vandenbroucke  JP; STROBE Initiative.  The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies.   Prev Med. 2007;45(4):247-251. doi:10.1016/j.ypmed.2007.08.012PubMedGoogle ScholarCrossref
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Cyhaniuk  A, Coombes  ME.  Longitudinal adherence to colorectal cancer screening guidelines.   Am J Manag Care. 2016;22(2):105-111.PubMedGoogle Scholar
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de Moor  JS, Cohen  RA, Shapiro  JA,  et al.  Colorectal cancer screening in the United States: trends from 2008 to 2015 and variation by health insurance coverage.   Prev Med. 2018;112:199-206. doi:10.1016/j.ypmed.2018.05.001PubMedGoogle ScholarCrossref
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Joseph  DA, King  JB, Dowling  NF, Thomas  CC, Richardson  LC.  Vital Signs: colorectal cancer screening test use—United States, 2018.   MMWR Morb Mortal Wkly Rep. 2020;69(10):253-259. doi:10.15585/mmwr.mm6910a1PubMedGoogle ScholarCrossref
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Klabunde  CN, Joseph  DA, King  JB, White  A, Plescia  M; Centers for Disease Control and Prevention (CDC).  Vital Signs: colorectal cancer screening test use—United States, 2012.   MMWR Morb Mortal Wkly Rep. 2013;62(44):881-888.PubMedGoogle Scholar
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Levin  TR, Corley  DA, Jensen  CD,  et al.  Effects of organized colorectal cancer screening on cancer incidence and mortality in a large community-based population.   Gastroenterology. 2018;155(5):1383-1391.e5. doi:10.1053/j.gastro.2018.07.017PubMedGoogle ScholarCrossref
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Adler  A, Geiger  S, Keil  A,  et al.  Improving compliance to colorectal cancer screening using blood and stool based tests in patients refusing screening colonoscopy in Germany.   BMC Gastroenterol. 2014;14(1):183. doi:10.1186/1471-230X-14-183PubMedGoogle ScholarCrossref
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Issa  IA, Noureddine  M.  Colorectal cancer screening: an updated review of the available options.   World J Gastroenterol. 2017;23(28):5086-5096. doi:10.3748/wjg.v23.i28.5086PubMedGoogle ScholarCrossref
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Lieberman  DA, Rex  DK, Winawer  SJ, Giardiello  FM, Johnson  DA, Levin  TR.  Guidelines for colonoscopy surveillance after screening and polypectomy: a consensus update by the US Multi-Society Task Force on Colorectal Cancer.   Gastroenterology. 2012;143(3):844-857. doi:10.1053/j.gastro.2012.06.001PubMedGoogle ScholarCrossref
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    1 Comment for this article
    EXPAND ALL
    Cologuard can improve its outcomes by sharing all test information with every patient who takes the test.
    David Keller, MD, MSEE | Internal Medicine Physician
    In a large 2014 randomized trial, the Cologuard FIT-DNA noninvasive fecal test had a sensitivity of 92% for detection of colon cancer compared to a sensitivity of 74% with standard FIT alone (P=0.002). The specificity of Cologuard was 90% compared with 96% for FIT. [1]. Screening with Cologuard will fail to detect fewer cancers, but will result in more normal (unnecessary) colonoscopies. Considering that the retail price of Cologuard is about $600, compared to $20 for a typical FIT test, is there any way to improve the specificity of Cologuard, without reducing its sensitivity, or possibly improving it?

    The ColoGuard colorectal cancer screening test is composed of 7 different sub-tests, including an assay for occult fecal hemoglobin, 5 assays for DNA changes associated with malignancy, and an assay for normal DNA to standardize the sample. The results of these seven subtests are combined using complex equations to yield a Composite Score ("CS") which can range from 0 to 1000, and is directly related to the likelihood of colon neoplasia.

    If the CS is larger than or equal to 183, the result of the screen is "positive" and the patient is sent for immediate colonoscopy. If the CS is lower than 183 (in the range of 0 through 182) the patient is advised to repeat the Cologuard test in 3 years. The CS requires 10 bits of binary information to convey a unique CS value between 0 and 1000, but the patient and his doctor are only given one bit of information: negative (normal) or positive (abnormal). A patient whose CS is reported as "normal" might have a CS of 182, told not to worry, and to come back and repeat the Cologuard screen in 3 years (this testing interval is not based on  clinical science, but determined by cost considerations that annual testing would be too expensive). A "normal" CS of 182 that would be just 1 point higher, equal to 183, would trigger sending the patient for immediate colonoscopy. This kind of abrupt discontinuity is not often seen in physiology, and is not reassuring.

    Cologuard could improve the accuracy of its receiver operating curve (sensitivity versus specificity) by reporting the actual value of the Composite score, not just a binary result of "positive" or "negative". Then, patients could be risk-stratified by their "normal" CS as follows:

    1) CS = 120 through 182: repeat Cologuard in 1 year (not 3 years)
    2) CS = 60 through 119: repeat Cologuard in 2 years
    3) CS = 0 through 59: repeat Cologuard in 3 years

    The above might increase the cost of screening but allocated testing resources where they are likely to do the most good (i.e. to patients with higher CS's), and there is less discontinuity across the range of normal CS values and their follow-up intervals.

    I proposed this idea in 2016 [2], and have asked Exact Sciences, the distributor of Cologuard, to release the CS (composite score) to all patients who use their product. How many patients with a CS over 170 might have had better outcomes by repeating their Cologuard screen in 1 year rather than waiting 3 years?

    References

    1: Imperiale TF, Ransohoff DF, Itzkowitz SH, et al. Multitarget stool DNA testing for colorectal cancer screening. N Engl J Med 2014;370:1287-97

    2: Keller DL. Patients Have a Right to All Their Medical Test Results. Am J Med. 2016 Oct;129(10):e233-4. doi: 10.1016/j.amjmed.2016.04.033

    CONFLICT OF INTEREST: None Reported
    READ MORE
    Original Investigation
    Oncology
    September 2, 2021

    Utilization of a Colorectal Cancer Screening Test Among Individuals With Average Risk

    Author Affiliations
    • 1Division of Gastroenterology, Duke University, Durham, North Carolina
    • 2IBM Watson Health, Cambridge, Massachusetts
    • 3Exact Sciences Corporation, Madison, Wisconsin
    • 4Division of General Internal Medicine, University of Michigan, Ann Arbor
    • 5Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota
    JAMA Netw Open. 2021;4(9):e2122269. doi:10.1001/jamanetworkopen.2021.22269
    Key Points

    Question  What were the overall and test-specific colorectal cancer screening participation rates in the period before and after the introduction of the multitarget stool DNA assay?

    Findings  In this cohort study of 97 776 individuals with average risk of colorectal cancer with commercial or Medicare supplemental insurance in the United States, adherence to colorectal cancer screening increased between 2011 and 2019. There was an increase in the adoption of the multitarget stool DNA assay and a decrease in fecal occult blood testing.

    Meaning  These findings suggest that overall colorectal cancer screening rates are increasing over time and there are varied patterns of use for specific tests.

    Abstract

    Importance  Colorectal cancer (CRC) screening reduces CRC incidence and mortality. It is important to examine screening patterns over time, including after the introduction of new screening modalities.

    Objective  To compare use of CRC screening tests before and after the availability of the multitarget stool DNA (mt-sDNA) test, given that endorsed options have changed.

    Design, Setting, and Participants  This longitudinal cohort study used administrative claims data to examine CRC screening use in 2 discrete periods: before (August 1, 2011, to July 31, 2014) and after (August 1, 2016, to July 31, 2019) the mt-sDNA test became available. The MarketScan Commercial and Medicare Supplemental databases were queried for individuals aged 45 to 75 years between August 1, 2011, and July 31, 2019, with average risk of CRC and with continuous enrollment in the databases from August 1, 2001, to July 31, 2019.

    Main Outcomes and Measures  The proportion of individuals up to date or not due for CRC screening during each measurement year and the type of screening test used among individuals due for screening. Data were reported overall and among individuals aged 45 to 49 or 50 years and older on August 1, 2011.

    Results  A total of 97 776 individuals with average risk were identified. Individuals had a mean (SD) age of 50.8 (3.5) years, and 54 227 (55.5%) were women. The proportion of individuals with average risk aged 50 to 75 years with commercial or Medicare supplemental insurance who were up to date with CRC screening increased from 50.4% in 2011 (30 605 of 60 770) to 69.7% in 2019 (42 367 of 60 770). Among individuals due for screening and screened, the use of high-sensitivity fecal occult blood test (FOBT) decreased between 2011 (1088 of 6241 eligible individuals [17.7%]) and 2019 (195 of 2943 eligible individuals [6.6%]), and the use of mt-sDNA increased between 2016 (58 of 3014 eligible individuals [1.9%]) and 2019 (418 of 2943 eligible individuals [14.2%]). No consistent trends were observed with fecal immunochemical test (FIT) or screening colonoscopy. Computed tomography colonography, double-contrast barium enema, and flexible sigmoidoscopy were rarely performed.

    Conclusions and Relevance  In this cohort study, the proportion of individuals with average risk who were up to date with CRC screening increased between 2011 and 2019 but remained suboptimal. There were no substantial changes in the use of the colonoscopy or FIT; however, there was an increase in the adoption of mt-sDNA and a decrease in the use of FOBT during the study period.

    Introduction

    Colorectal cancer (CRC) is the second-most common cause of cancer-related death in the United States.1 Encouragingly, CRC incidence and mortality rates in the United States have decreased by 1% to 2% per year between 2007 and 2016, likely attributable to increased participation in screening. However, despite the established benefits of CRC screening,2,3 screening rates in the United States remain below the National Colorectal Cancer Roundtable goal of 80%.4-7

    National organizations, such as the United States Preventive Services Task Force (USPSTF), the National Comprehensive Cancer Network, and Multi-Society Task Force, endorse several test options for CRC screening for individuals with average risk beginning at age 50 years, while the 2018 American Cancer Society (ACS) guidelines have a qualified recommendation that individuals with average risk start CRC screening at age 45 years.8-11 CRC test options include high-sensitivity fecal occult blood test (FOBT), fecal immunochemical test (FIT), multitarget stool DNA assay (mt-sDNA; marketed as Cologuard [Exact Sciences, Madison, WI]), computed tomography (CT) colonography, flexible sigmoidoscopy, or colonoscopy. There is evidence that providing a choice of screening tests improves screening adherence.8,9 The current study used administrative claims data to assess longitudinal trends in overall CRC screening and by-modality CRC screening in the period before and after the introduction of mt-sDNA and availability of its Current Procedural Terminology (CPT) code in 2016.

    Methods
    Study Design and Data Source

    This longitudinal cohort study used the MarketScan Commercial Claims and Encounters (commercial) and Medicare Supplemental and Coordination of Benefits (Medicare) administrative claims databases to examine CRC screening test utilization between August 1, 2011, and August 31, 2019. The commercial database contains the inpatient, outpatient, and outpatient prescription drug experience of employees and their dependents, covered under a variety of geographically dispersed fee-for-service and managed care health plans in the United States. The Medicare database contains the same health care data for retirees with Medicare supplemental insurance paid for by employers. The Medicare database captures both the Medicare-covered portion of payment (represented as Coordination of Benefits amount) and the employer-paid portion and thus reflects the patient’s full interaction with the health care system. All database records are statistically deidentified and certified to be fully compliant with US patient confidentiality requirements set forth in the Health Insurance Portability and Accountability Act of 1996. Because this study used only deidentified patient records and did not involve the collection, use, or transmittal of individually identifiable data, this study was exempted from institutional review board approval and the requirement for informed consent per the Common Rule. This study followed the reporting requirements of the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for observational studies.12 All variables used to define study outcomes were obtained using medical codes such as the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) and ICD-10-CM, the CPT fourth edition, and the Healthcare Common Procedure Coding System (HCPCS).

    Patient Selection and Study Periods

    Because this study used a longitudinal design, the cohort included individuals continuously enrolled in the MarketScan databases throughout the 18-year study period from August 1, 2001, through July 31, 2019. This period was segmented into a screening measurement period (August 1, 2011, through July 31, 2019) and a 10-year prescreening period (August 1, 2001, through July 31, 2011). The screening measurement period was further segmented into the pre–mt-sDNA period (August 1, 2011, through July 31, 2014) and the post–mt-sDNA period (August 1, 2016, through July 31, 2019). Due to the lack of availability of a CPT code for the mt-sDNA test during the period between mt-sDNA approval in 2014 and the adoption of the CPT code for the mt-sDNA test on January 1, 2016, the period from August 1, 2014, and July 31, 2016, was defined as a washout period.

    To be included in the current study, individuals were required to be aged at least 45 years but no older than 67 years on August 1, 2011, which ensured that individuals were 75 years or younger by the end of the screening measurement period on July 31, 2019. In addition, individuals were required to have no evidence of having above average risk of CRC. Individuals were considered to have above average risk if (1) they had at least 1 medical non–rule out claim with ICD-9-CM or ICD-10-CM diagnosis codes for benign or malignant colorectal neoplasms, colorectal polyps, inflammatory bowel disease, or family history of gastrointestinal cancer during the 10-year prescreening period or (2) they had at least 1 medical non–rule out claim with an ICD-9-CM or ICD-10-CM diagnosis code for a high-risk symptom (eg, blood in the stool) during the 3 months immediately preceding the start of the screening measurement period. A rule out claim is for a service typically used to rule out a condition rather than to confirm it.

    Outcomes

    All outcomes are reported by measurement year, which started on August 1 and ended on July 31 of the subsequent calendar year. The proportion of individuals up to date with CRC screening in each measurement year was reported and included (1) individuals not due for screening in the year because they had evidence of prior screening (defined as having a claim with any procedure code [CPT or HCPCS] for colonoscopy in the prior 10 years; FIT or FOBT in the prior year; mt-sDNA test in the prior 3 years; or flexible sigmoidoscopy, CT colonography, or double-contrast barium enema [DCBE] in the prior 5 years) and (2) those due for screening and newly screened (defined as having a claim with a procedure code [CPT or HCPCS] for any CRC screening test) in the year. Evidence of prior CRC screenings was identified using procedure codes indicative of diagnostic or screening procedures, while new CRC screenings were identified using screening procedure codes only. CPT and HCPCS codes used to identify screening procedures are listed in the eTable in the Supplement. Among individuals due for screening and newly screened, the proportion of individuals was reported by test type (ie, screening colonoscopy, FIT, FOBT, mt-sDNA, flexible sigmoidoscopy, CT colonography, or DCBE) during the pre–mt-sDNA period and the post–mt-sDNA period. Among individuals with evidence of multiple screening modalities in a single measurement year, the first test was considered the screening event and used in the proportional analysis.

    Statistical Analysis

    In 2018, the ACS introduced a qualified recommendation that the age of CRC screening initiation decrease from 50 to 45 years. Because the ACS guidelines changed during the study period, the outcomes are reported for individuals aged 50 years or older at the start of the measurement period and separately for those aged 45 to 49 years old at the start of the measurement period (August 1, 2011). Continuous variables are reported in each measurement year as mean and SD, while categorical variables are reported as frequencies. All data analyses were conducted using WPS version 4.1 (World Programming).

    Results

    There were 97 776 individuals who met the defined study criteria (Figure 1). At the start of the measurement period (August 1, 2011), individuals had a mean (SD) age of 50.8 (3.5) years, and 54 227 (55.5%) were women (Table 1). Of these, 60 770 (62.2%) were aged 50 years or older and 37 006 (37.8%) were aged 45 to 49 years on August 1, 2011.

    Among individuals aged 50 years and older, the percentage who were up to date with screening increased each year, from 50.4% (30 605) in the first measurement year (2011-2012) to 69.7% (42 367) in the final measurement year (2018-2019) (Figure 2). Among individuals aged 45 to 49 years, the proportion of individuals up to date with screening in the first year of measurement was low (9542 [25.8%]), but the difference between age groups was nearly eliminated by the last year of measurement (25 041 [67.7%]).

    Among individuals aged 50 years or older due for screening, utilization patterns of specific screening modalities changed between 2011 and 2019 (Figure 3). While the use of FIT and screening colonoscopy remained steady (range for FIT: 1107 of 6241 eligible individuals [17.7%] in 2011-2012 to 680 of 3014 [22.6%] in 2016-2017; range for colonoscopy: 1776 of 2943 [60.3%] in 2018-2019 to 2561 of 3962 [64.6%] in 2013-2014), the use of FOBT declined from 17.4% (1088 of 6241 eligible individuals) in the first measurement year to 6.6% (195 of 2943 eligible individuals) in the final measurement year. After the CPT code for mt-sDNA became available in 2016, the use of this modality increased from 1.9% (58 of 3014 eligible individuals) in the 2016 to 2017 measurement year to 14.2% (418 of 2943 eligible individuals) in the final measurement year (2018-2019). CT colonography, DCBE, and flexible sigmoidoscopy were used by less than 1% of the screened population in any given measurement year.

    When examined among individuals aged 45 to 49 years, the trends in utilization of specific screening modalities reflected in an increase in colonoscopy during the measurement period (Table 2). Colonoscopy use increased from 40.9% (1193 of 2915 eligible individuals) in the first measurement year to 72.2% (1820 of 2521 eligible individuals) in the 2017 to 2018 measurement year. Screening with FIT decreased from 27.4% (799 of 2915 eligible individuals) in the first measurement year to 17.9% (451 of 2521 eligible individuals) in the 2017 to 2018 measurement year, while screening with FOBT decreased from 31.1% (908 of 2915 eligible individuals) in the first measurement year to 6.1% (136 of 2235 eligible individuals) in the 2018 to 2019 measurement year. However, screening with mt-sDNA increased from 1.1% (38 of 3464 individuals) in the 2016 to 2017 measurement year to 10.3% (230 of 2235 eligible individuals) in the final measurement year (2018-2019).

    Discussion

    In this longitudinal cohort study, the proportion of individuals with average risk and commercial or Medicare supplemental insurance who were up to date with CRC screening increased from 2011 to 2019 (41% to 69%) but remained below the 80% goal set by the National Colorectal Cancer Roundtable.4 Uptake of mt-sDNA, the newest guideline-endorsed option for average-risk CRC screening, increased from 1.9% in 2016 to 14.2% in 2019, while the use of FOBT declined. No consistent trends for FIT or screening colonoscopy were observed.

    During at least the past decade, there have been many population-level and public health interventions that have increased awareness and uptake of CRC screening in the United States. In addition, changes in CRC screening guidelines, such as the 2018 ACS guidelines containing a qualified recommendation that individuals with average risk start CRC screening at age 45 years, have brought media attention to the importance of being up to date with CRC screening. At the same time, increased insurance coverage provided by the Patient Protection and Affordable Care Act has further increased awareness and accessibility of CRC screening.

    Although there remains progress to be made before reaching the 80% screening rate goal set by the National Colorectal Cancer Roundtable, the results of this analysis and other studies highlight the effectiveness these population-level interventions have had on increasing CRC screening uptake in the United States. Estimates of adherence to CRC screening guidelines during the period covered in this study (ie, 2011-2019) generally range from 57% to 69% and depend on population, metrics, and study design.13-16 The most recent Morbidity and Mortality Weekly Report on CRC screening adherence reported that 63% of individuals aged 50 to 64 years and 79% of individuals aged 65 to 75 years were up to date with CRC screening in the 2018 Behavioral Risk Factor Surveillance System (BRFSS) survey.15 This was a roughly 3% increase in both age cohorts from the 2012 BRFSS survey.16 Analysis of the 2015 National Health Interview Survey16 found that among individuals aged 50 to 64 years, the age-adjusted rate of adherence to CRC screening guidelines among individuals with traditional or high-deductible employer-sponsored private insurance was 62%.

    The availability of new, noninvasive screening modalities, like mt-sDNA, provides yet another strategy for increasing CRC screening. Prior studies have shown that the availability of noninvasive screening tests, such as FIT, have increased CRC screening compliance compared with only offering colonoscopy.17,18 Offering individuals a choice of options with different test attributes may better align with their preferences. For example, colonoscopy has the highest detection of cancer and adenomas and can identify and remove colorectal neoplasia during a single examination; however, it requires bowel cleansing, sedation, and time away from work and usual activities and is associated with the risk of complications, such as bowel perforation.15,19

    It is worth noting that the present study showed that the introduction of mt-sDNA corresponded to a reduction in uptake of other noninvasive screening tests, such as FOBT, from 2016 to 2019. In the long term, whether the introduction of new CRC screening tests leads to further shifting among existing screening modalities or an overall increase in CRC screening is yet to be determined. The extent to which the expansion of CRC screening modalities contributes to the 80% goal of CRC screening and to the early identification and prevention of CRC should be explored in future studies.

    Limitations

    The primary limitation of this study is that all up-to-date screening intervals are assigned based on the assumption that individuals are not in a high-risk category for CRC; therefore, we may be overestimating the percentage of individuals with up-to-date screening. In particular, we may be overestimating the up-to-date period among individuals who had colorectal neoplasia (adenoma) diagnosed during the measurement period; individuals who had a colonoscopy with polyp removal in the prescreening period were excluded from the analysis. As claims data do not contain test results, we were not able to adjust the screening period based on polyp findings and assigned a 10-year up-to-date screening period for all individuals screened by colonoscopy, as this would be the most common screening interval.20

    Other limitations of this study include those inherent in any analysis using administrative claims. First, this study was limited to only those individuals with commercial health coverage or private Medicare supplemental coverage. Also, the longitudinal study design required continuous insurance plan enrollment during the 10-year prescreening period and the 8-year CRC screening measurement period. Individuals who died, started receiving long-term disability, or lost their health insurance would have been excluded from the analysis. As insurance coverage has been strongly associated with screening access,15 the results of this analysis may overstate CRC screening rates for individuals with other insurance or without health insurance coverage. Second, the potential for misclassification of covariates or study outcomes may be present given that individuals were identified through administrative claims data rather than medical records. As with any claims databases, the MarketScan Research Databases rely on administrative claims data for clinical detail. These data are subject to data coding limitations and data entry errors.

    Conclusions

    In this study, the proportion of individuals up to date with CRC screening increased between 2011 and 2019, but uptake remained suboptimal. There were no substantial changes in the use of the most common screening modalities (ie, colonoscopy and FIT); however, a decrease in FOBT use and an increase in the adoption of mt-sDNA tests were observed during the study period.

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    Article Information

    Accepted for Publication: June 20, 2021.

    Published: September 2, 2021. doi:10.1001/jamanetworkopen.2021.22269

    Open Access: This is an open access article distributed under the terms of the CC-BY-NC-ND License. © 2021 Fisher DA et al. JAMA Network Open.

    Corresponding Author: Nicole Princic, MS, IBM Watson Health, 75 Binney St, Cambridge, MA 02142 (nprincic@us.ibm.com).

    Author Contributions: Ms Princic had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

    Concept and design: Miller-Wilson, Wilson, Fendrick, Limburg.

    Acquisition, analysis, or interpretation of data: Fisher, Princic, Wilson, Limburg.

    Drafting of the manuscript: Miller-Wilson, Wilson, Fendrick, Limburg.

    Critical revision of the manuscript for important intellectual content: Fisher, Princic, Miller-Wilson, Wilson, Limburg.

    Obtained funding: Miller-Wilson.

    Administrative, technical, or material support: Princic, Miller-Wilson, Wilson, Limburg.

    Supervision: Wilson, Fendrick, Limburg.

    Conflict of Interest Disclosures: Dr Fisher reported receiving personal fees from Exact Sciences during the conduct of the study; receiving grants from Exact Sciences; and serving on the advisory board of Guardant Health outside the submitted work. Ms Princic reported being employed by IBM Watson Health, which was paid by Exact Sciences to conduct this research. Dr Miller-Wilson reported being an employee of Exact Sciences during the conduct of the study. Ms Wilson reported being employed by IBM Watson Health, which received funding from Exact Sciences Corporation to conduct this analysis. Dr Fendrick reported serving as a consultant for AbbVie, Amgen, Bayer, Centivo, the Community Oncology Association, Covered California, EmblemHealth, Exact Sciences, Freedman Health, GRAIL, Harvard University, Health and Wellness Innovations, Health at Scale Technologies, HealthCorum, Hygieia, MedZed, Merck, Mercer, Montana Health Cooperative, Pair Team, Penguin Pay, Phathom Pharmaceuticals, Risalto, Risk International, Sempre Health, the State of Minnesota, the US Department of Defense, Virginia Center for Health Innovation, Wellth, Wildflower Health, YaleNew Haven Health System, and Zansors; holding equity interest in Health and Wellness Innovations, Health at Scale Technologies, Pair Team, Sempre Health, Wellth, and Zansors; receiving research funding from the Agency for Healthcare Research and Quality, Boehringer-Ingelheim, the Gary and Mary West Health Policy Center, Arnold Ventures, National Pharmaceutical Council, the Patient-Centered Outcomes Research Institute, PhRMA, Robert Wood Johnson Foundation, and the State of Michigan/Centers of Medicare & Medicaid Services; serving as coeditor for The American Journal of Managed Care; being a member of the Medicare Evidence Development & Coverage Advisory Committee; and being a partner in V-BID Health outside the submitted work. Dr Limburg reported receiving royalties from Exact Sciences to their institution during the conduct of the study and outside the submitted work and serving as chief medical officer for screening at Exact Sciences through a contracted services agreement with Mayo Clinic; Dr. Limburg and Mayo Clinic have contractual rights to receive royalties through this agreement.

    Funding/Support: This study was funded by Exact Sciences Corporation.

    Role of the Funder/Sponsor: The role of the sponsor was the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

    Meeting Presentation: This research was presented in part at the virtual American College of Gastroenterology 2020 Annual Scientific Meeting; October 23-28, 2020.

    Additional Contributions: Programming services were provided by Cyndi Ritz Wallen, BS (IBM Watson Health). Medical writing services were provided by Jessamine Winer-Jones, PhD (IBM Watson Health). These services were paid for by Exact Sciences Corporation.

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