Performance improvements of stool-based screening tests

Best Practice & Research Clinical Gastroenterology 24 (2010) 479–492

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Best Practice & Research Clinical Gastroenterology

9

Performance improvements of stool-based screening tests Leonie van Dam, Research Fellow a,1, Ernst J. Kuipers, Professor, Head of Department a, b, 2, Monique E. van Leerdam, Gastroenterologist a, * a b

Department of Gastroenterology and Hepatology, Erasmus MC, University Medical Centre Rotterdam, Netherlands Department of Internal Medicine, Erasmus MC, University Medical Centre Rotterdam, Netherlands

Keywords: Colorectal cancer Screening Performance Faecal immunochemical test Guaiac-based faecal occult blood test Faecal DNA test FOBT FIT Adenomas

Stool testing is a widely accepted, non-invasive, technique for colorectal cancer (CRC) screening. Guaiac-based faecal occult blood test (gFOBT) screening has been proven to decrease CRC-related mortality; however gFOBT is hampered by a low sensitivity. Faecal immunochemical tests (FITs) have several advantages over gFOBT. First of all, FIT has a better sensitivity and higher uptake. Furthermore, the quantitative variant of the FIT allows choices on cut-off level for test-positivity according to colonoscopy resources available, personal risk profile, and/or intended detection rate in the screened population. Stool-based DNA (sDNA) tests aiming at the detection of specific DNA alterations may improve detection of CRC and adenomas compared to gFOBT screening, but large-scale population based studies are lacking. This review focuses on factors influencing test performance of those three stool based screening tests. Ó 2010 Elsevier Ltd. All rights reserved.

Introduction Stool testing is a widely accepted, non-invasive, home-based technique for colorectal cancer (CRC) screening [1–3]. Faecal occult blood test (FOBT) screening primarily aims at early detection * Corresponding author at: Department of Gastroenterology and Hepatology, Room HS-510, Erasmus MC, University Medical Centre Rotterdam, Dr. Molewaterplein 40, 3015 GD Rotterdam, The Netherlands. Tel.: þ31 (0)10 7031693; fax: þ31 (0)10 7034682. E-mail addresses: [email protected] (L. van Dam), [email protected] (E.J. Kuipers), m.vanleerdam@ erasmusmc.nl (M.E. van Leerdam). 1 Department of Gastroenterology and Hepatology, Room Ca-413, Erasmus MC, University Medical Centre Rotterdam, ’s-Gravendijkwal 230, 3015 CE Rotterdam, The Netherlands. Tel.: þ31 (0)10 7032983; fax: þ31 (0)10 7034682. 2 Department of Gastroenterology and Hepatology, Room Ba-391, Erasmus MC, University Medical Centre Rotterdam, ’s-Gravendijkwal 230, 3015 CE Rotterdam, The Netherlands. Tel.: þ31 (0)10 7034681; fax: þ31 (0)10 7034682. 1521-6918/$ – see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.bpg.2010.03.009

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of CRC [2]. Traditionally, the guaiac-based FOBT (gFOBT), reacting to the presence of haem, has been used for screening stool samples for the presence of occult blood. More recently, the faecal immunochemical test (FIT), reacting to the presence of globin, has gained an increasing interest due to higher sensitivity and improved detection rate of advanced neoplasia [4–9]. Despite these improvements, sensitivity of FOBTs remains relatively low for CRC and precursor lesions (advanced adenomas) [10]. Stool DNA (sDNA) tests have been developed, with a possible superior sensitivity compared to the gFOBT and FIT for detecting CRC as well as advanced adenomas [11]. However, in the absence of evidence with respect to multiple aspects of sDNA testing and at much higher test costs, they are not used on a large-scale yet. Performance of the gFOBT, FIT and sDNA test depends on program-related as well as test-related factors. Program-related factors include screening interval and program compliance (the willingness to attend successive screening rounds). This review focuses on the influence of test-related factors determining the performance of the different stool tests.

Guaiac-based faecal occult blood test Performance determinants The most common and traditionally used gFOBTs are the guaiac-impregnated Hemoccult II and the more sensitive Hemoccult II SENSA [10,12]. GFOBTs detect the presence of haem in the faecal sample; however gFOBTs do not specifically detect human haem. When guaiac (present on the test cards) is exposed to hydroperoxidase, haem catalyses its oxygenation which results in a perceptible blue colour change. Performance of gFOBT is limited, as it can also detect haem from upper gastrointestinal bleedings in the faeces causing false-positive test results [13]. When haem is released from globin in the stomach, only a small percentage of haem is absorbed in the small intestine. Therefore, in case of an upper gastrointestinal bleeding, the majority of haem passes into the colon and thereby into the faecal sample. Test performance of the gFOBT depends on several factors related to the tested subject, the method of faecal collection, the test itself and test analysis. With regard to the subject related factors, both dietary factors (e.g. consumption of red meat because of haem presence, several fresh fruits and vegetables given peroxidase activity) and medication (e.g. nonsteroidal anti-inflammatory drugs (NSAIDs)) have been suggested to increase the risk of false-positive test results. Vitamin C may cause false-negative results given its capacity to block the hydroperoxidase reaction [2]. Potential interference of plant peroxidases can be avoided since they break down with time, so if the faeces on the gFOBT are dried for at least 48 hours before test analysis, dietary restrictions with regard to peroxidase-rich fruits and vegetables are unnecessary [14]. A meta-analysis concluded that modest dietary restrictions do not to influence uptake of the test and that there is little evidence for dietary restriction to influence positivity rates of Hemoccult or Hemoccult II [15]. However, strict dietary and medication restrictions may influence test uptake. The evidence on the effect of vitamin C use on test performance was inconclusive [15]. The use of aspirin or NSAIDs does not seem to increase false-positivity of the Hemoccult II and Hemoccult II SENSA [16,17]. Thus, physicians do not need to advise participants to restrict their diet and/or medication prior to gFOBT, although usually advised otherwise by test manufacturers. Performance of both the gFOBT and FIT test can also be influenced by the composition of faecal samples and the sample volume [18]. Performance is also dependent on the method of faecal collection. In the US, the gFOBT is sometimes performed as a digital test in the office, while traditionally two stool samples from three consecutive bowel movements are collected at home. Research has demonstrated that the sensitivity of in-office sampling is so low [19], that its use is discouraged in national guidelines [2]. Furthermore, there are test-related factors influencing test performance. Sensitivity and specificity of a single gFOBT have been shown to vary considerably between test variants [20,21]. In one study, sensitivity and specificity of a single test for detecting CRC were 37.1% and 97.7% respectively with unhydrated Hemoccult II testing and 79.4% and 87.7% with analysis by Hemoccult II Sensa [20]. Another

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important determinant of test performance is whether rehydration (adding water to the stool specimen before processing) is applied or not. Rehydration of Hemoccult II has been shown to improve test sensitivity for CRC [22,23], but reduce specificity [23]. In line with these results, another study found rehydration to increase the positivity rate, but decrease the positive predictive value (PPV) [21]. As rehydration also decreases test readability, it is nowadays no longer recommended [2,24,25]. The level of moisture also influences performance, with a decrease in positive rate with increasing moisture content [26]. Furthermore, the threshold chosen (cut-off) for a positive test is an important determinant of test performance. In several large-scale screening studies, gFOBT was considered positive if a colour change was detected in at least one sample [23,27]. A study comparing testing of two and three stool samples from consecutive days by gFOBT found that sensitivity for CRC significantly increased by testing three samples [28]. The two stool sample setting for gFOBT was accompanied by a lower false-positive rate compared to the three sample setting, but this difference was not significant. The number of positive slides per gFOBT has been shown to be significantly associated with the predictive value for both advanced neoplasia and CRC [22,29,30]. In the UK, the approach has been adopted of only referring individuals with 5 or 6 positive gFOBT slides directly for colonoscopy, with a retest for those with 1–4 positive slides [31,32]. In the second round of the UK pilot, seven percent of those with 1–4 positive slides on the first test failed to complete screening [32]. The PPV for CRC (based on the number of individuals attending) was 5% for 1–4 and 18% for 5 or 6 positive slides, for neoplasia (cancer and adenomas) respectively 34% and 42%. In 43 of 3105 individuals with 1–4 positive slides a CRC was detected, and in 274 individuals neoplasia (cancer and adenomas). So this approach can keep the false-positive rate to a minimum [31], but at the cost of a lower detection rate. This approach may be adopted in case of limited colonoscopy capacity. Performance of gFOBT also depends on the accuracy of test result interpretation [33,34]. One study showed that considerable variations in the interpretation of gFOBT occur [34], while another study demonstrated that training improves the accuracy of interpretation [33]. Guidelines recommend several procedures to minimise variability and error associated with visual test reading, as for example a blinded quality check each day for each analyst and double entry of test results [18]. Performance In a recent review, test positivity in average-risk individuals undergoing one-time testing was found to range from 1%–20% for non-rehydrated and 5–8% for rehydrated Hemoccult II [35]. For Hemoccult II SENSA, positivity varied from 5–15%. Sensitivity ranged from 13–37% for non-rehydrated, 50–86% for rehydrated Hemoccult II and 72–79% for Hemoccult II SENSA. Test performance for studies among asymptomatic persons in which all individuals had undergone colonoscopy is described in Table 1 [36,37]. GFOBT has been shown to reduce CRC mortality by on average 16% [38]. Conclusion Guaiac-based FOBT screening is the only CRC screening method which has in prospective studies been proven to reduce CRC mortality [38]. However, the test has limited sensitivity for CRC and even lower for advanced adenoma. Faecal immunochemical test Performance determinants FITs have several advantages over gFOBT among which the higher sensitivity and easier stool collection method [4–8,39,40]. FIT usually aims at the detection of human globin by means of specific antibodies using enzyme-linked immunosorbent assay (ELISA) [41], although they may also aim at for example the detection of the haemo-/haptoglobin complex [42,43]. Globin present in blood from the proximal gastrointestinal tract is gradually digested during its passage through the intestine, making FIT rather specific for bleeding from the distal gastrointestinal tract [18]. FIT allows for the detection of

Author/year

N

Allison, 2007 [5]

Hemoccult Hemoccult Hemoccult Hemoccult Hemoccult Hemoccult

II II II II II II

FIT Nakama, 1999 [6]

Monohaem

Cheng, 2002 [7] Levi, 2007 [8]d Morikawa, 2005 [9] Allison, 2007 [5]

OC-Hemodia OC-Hemodia Magstream FlexSure OBT

First generation stool DNA Imperiale, 2004 [3] PreGen-Plus Ahlquist, 2008 [4] PreGen-Plus SDT-2

(rehydrated) (non-rehydrated) (non-rehydrated) (non-rehydrated) SENSA SENSA

Cut-off

Samples

Positive

Sensitivity

Specificity for colorectal cancer

Colorectal cancer

Advanced adenoma 24%a 14%a 11%

5799

Not applicable (NA) NA NA NA NA NA

32 32 32 32 32 3c

8% 20% 11% NR NR 10%

50% 25% 13% 11%b 21%b 64%

41%

94% (no neoplasia) 79%a 95% 98%b 97%b 91%

4611

NA

NA NA 20 mg Hb/L 0.3 mg Hb/g

1 2 3 3 3 1 3c

NR NR NR 9% 19% 6% 3%

56% 84% 89% 88% 67% 66% 82%

30% 51% 55% 48% 56% 27% 30%

97%a 96%a 94%a 91% 83% 95% 97%

NA NA NA

1 1 1

18% NR NR

52% 20%b 40%b

15%

94% 96%b NR

2885 505 4404 3764

7411 1000 21805 5356 4404 2497 217

References [1] Lieberman DA, Weiss DG. One-time screening for colorectal cancer with combined fecal occult-blood testing and examination of the distal colon. N Engl J Med 2001 Aug 23;345(8):555–60. [2] Sung JJ, Chan FK, Leung WK, et al. Screening for colorectal cancer in Chinese: comparison of fecal occult blood test, flexible sigmoidoscopy, and colonoscopy. Gastroenterology 2003 Mar;124 (3):608–14. [3] Imperiale TF, Ransohoff DF, Itzkowitz SH, et al. Fecal DNA versus fecal occult blood for colorectal-cancer screening in an average-risk population. N Engl J Med 2004 Dec 23;351(26):2704–14. [4] Ahlquist DA, Sargent DJ, Loprinzi CL, et al. Stool DNA and occult blood testing for screen detection of colorectal neoplasia. Ann Intern Med 2008 Oct 7;149(7):441–50, W81. [5] Allison JE, Sakoda LC, Levin TR, et al. Screening for colorectal neoplasms with new fecal occult blood tests: update on performance characteristics. J Natl Cancer Inst 2007 Oct 3;99(19):1462–70. [6] Nakama H, Yamamoto M, Kamijo N, et al. Colonoscopic evaluation of immunochemical fecal occult blood test for detection of colorectal neoplasia. Hepatogastroenterology 1999 Jan;46 (25):228–31. [7] Cheng TI, Wong JM, Hong CF, et al. Colorectal cancer screening in asymptomaic adults: comparison of colonoscopy, sigmoidoscopy and fecal occult blood tests. J Formos Med Assoc 2002 Oct;101(10):685–90. [8] Levi Z, Rozen P, Hazazi R, et al. A quantitative immunochemical fecal occult blood test for colorectal neoplasia. Ann Intern Med 2007 Feb 20;146(4):244–55. [9] Morikawa T, Kato J, Yamaji Y, et al. A comparison of the immunochemical fecal occult blood test and total colonoscopy in the asymptomatic population. Gastroenterology 2005 Aug;129 (2):422–8. a Advanced adenoma including colorectal cancer (CRC). b For screen-relevant neoplasia (defined as curable-stage cancer, high-grade dysplasia, or adenomas > 1 cm). c Combination test Hemoccult SENSA and FlexSure OBT. d Study also included symptomatic patients.

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Standard gFOBT Lieberman, 2001 [1] Sung, 2003 [2] Imperiale, 2004 [3] Ahlquist, 2008 [4]

Brand

482

Table 1 Studies on guaiac based FOBT (gFOBT), faecal immunochemical test (FIT) and stool DNA test performance: a single screening round in asymptomatic individuals, with all individuals followed-up by colonoscopy or with sigmoidoscopy for negative screenees.

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blood at lower concentrations than gFOBT [18]. Furthermore, no dietary restrictions are required given the fact that the FIT specifically detects human haemoglobin and no peroxidase activity is involved, thereby improving specificity. Medication restrictions also seem to be unnecessary. A recent study suggested that NSAID or aspirin use increased the sensitivity of FIT without a decrease in specificity [44], but the study was limited by the low number of NSAID users [41]. Performance of the FIT is mainly determined by factors related to sample collection, the test itself and factors related to test analysis. Differences in performance have been described between the routine sampling method and sampling at digital rectal exam (DRE). Three Japanese studies concluded that stool samples collected during regular screening perform better than of those obtained at DRE [45–47]. Specificity of routine stool sampling was higher (97%) than at DRE (80%), with no significant differences in sensitivity (respectively 80% vs. 86%) [47]. Both quantitative and qualitative FITs have been developed. Qualitative tests require a visual interpretation of test results as positive or negative [48]. Quantitative FITs are analysed automatically, providing a value for the amount of haemoglobin found in the stool sample. Qualitative FIT Qualitative FITs, that often use immunochromatographic technology, allow for simple, office-based analysis. Recently it has been demonstrated that there are large differences in diagnostic performance between different test variants of the qualitative FIT, as is also the case for gFOBT [8,49]. A study assessing the cause of these differences found that the distribution of faecal haemoglobin concentrations strongly varies across tests [48]. The cut-off level (the amount of haemoglobin above which the test is considered positive) of the qualitative tests was determined by comparing the faecal haemoglobin levels found by a quantitative FIT to the test results of the qualitative FITs. The observed pattern suggests that the strongly different positivity rates reflect different cut-off levels of tests with otherwise very high inter-test agreement. Definition of cut-offs is therefore a critical issue in the application of qualitative tests. Since qualitative FITs provide dichotomous test results, the cut-off level for detecting haemoglobin in the stool has to be predefined by the manufacturer. As for gFOBT, interobserver variations in interpretation of test results may influence performance. Measures for ascertaining quality control as recommended for gFOBT [18] may therefore also be important for qualitative FIT screening. Quantitative FIT Quantitative FITs have important advantages over qualitative FITs by using automated analysis, thereby removing interobserver variation in interpretation of test results, improving reproducibility and allowing for high-throughput testing [42]. There are currently many FIT kits marketed, with different antigen target stability and sampling methods [41]. Differences between quantitative FITs have been described. One study found a superior performance of FIT aiming at the detection of haemoglobin compared to a FIT aiming at the haemo-/haptoglobin complex, with a higher sensitivity for advanced adenomas at the same level of specificity [42]. Others found a similar sensitivity for CRC, but the haemo-/haptoglobin test to have a significantly higher sensitivity for adenoma, accompanied by a lower specificity [43]. An important advantage of the quantitative FIT is that the quantitative nature allows for selection of the optimal cut-off level above which the FIT is considered positive and individuals are referred for colonoscopy. Influence of applying different cut-offs on test performance will be discussed in more detail later on. As haemoglobin can degrade during transportation to the laboratory, some FITs use a haemoglobinstabilising buffer [41]. Despite the use of a buffer, a recent study suggests that performance of the quantitative FIT decreases (increased false-negativity) with prolonged time intervals between stool sampling and arrival of the sample at the laboratory [50]. Another study with a qualitative FIT did not observe a significant trend in performance between samples analysed within two days, between 2-7 days or after more than seven days of arrival in the laboratory [8]. It has been demonstrated that the refrigerated OC-sensor FIT remains stable for 21 days [51]. Performance of the FIT also depends on the number of samples. Two studies found that a two consecutive day FIT had a superior sensitivity for CRC compared to a one day FIT, with a similar

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specificity [52,53]. A three day FIT further increased sensitivity, but at the cost of specificity. Two studies comparing highest cut-off value of 1, 2 or 3 FIT samples both found an increase in sensitivity and decrease in specificity using more samples [54,55]. A recent study found that a two day FIT which is considered positive if the mean of two samples’ log-transformed haemoglobin content exceeds the cut-off value may have superior performance to both a one sample FIT, a two sample FIT of which at least one sample is positive and a two sample FIT of which both samples are positive [56]. Another recent study comparing a one and two day FIT (one, at least one or both samples positive) at different cut-off levels did not identify a clear superiority of one of the screening strategies [57]. Three costeffectiveness analyses found a favourable cost-effectiveness of the two day FIT to both the one and three day FIT [28,58,59]. Currently, the optimal number of stool samples has not been established yet [2] and randomised trials are therefore warranted. Test performance of the quantitative FIT for different cut-offs The chosen cut-off level is most important. Several studies found that the amount of faecal haemoglobin detected by FIT correlated with disease severity [54,60–62]. The amount of faecal haemoglobin was found to be lowest for those without neoplasia, higher for those with advanced adenomas and highest for those with CRC. By varying the amount of haemoglobin above which the test is considered to be positive, performance can be optimised (Table 2). This cut-off level, and thus the positivity rate, can be varied according to the colonoscopy resources available, personal risk profile and/or intended detection rate in the screened population [63]. In general, FIT sensitivity and positivity rate decrease by increasing the cut-off, whereas test specificity and PPV increase. Since the amount of haemoglobin is highest for those with CRC and lower for those with advanced adenomas, differences in chosen cut-off will most likely affect the detection rate of advanced adenomas more than that of CRC [5,57]. Several studies have investigated the effect of altering the cut-off level on test performance [5,43,51,54,56,57,61,63–70]. A cut-off value of 75 ng/mL was found to provide most optimal test characteristics in several recent studies based on an adequate positivity rate and an acceptable tradeoff between detection rate and numbers needed to scope [54,63,69]. Others have for example identified a cut-off level of 100 ng/ml [51] or 150 ng/ml [68] as optimal. The optimal cut-off level may vary between different populations, among other things due to differences in CRC prevalence [71]. A local pilot prior to implementation is advisable to determine an optimal cut-off level that is manageable from a clinical, logistical and financial perspective [18]. Performance There are five studies on FIT performance in which a colonoscopy was performed for all asymptomatic subjects. The resulting FIT sensitivities and specificities are reported in Table 1. Performance of FIT has further been described in a systematic review including studies up to 2006 [72]. This review identified nine fair or good quality studies on FIT performance. Sensitivity and specificity varied between FITs, with sensitivity ranging between 61%–91% for CRC and 27–67% for large adenomas, and specificity ranging between 91–98% [72]. GFOBT vs. FIT One of the first studies directly comparing gFOBT (Hemoccult II SENSA) and FIT (HemeSelectTwo) found a higher sensitivity (79% and 69% respectively), but lower specificity (87% and 94% respectively) for gFOBT [20]. Many other studies comparing gFOBT and FIT have been conducted since [4,5,8,28,39,40,63,73–80]. A systematic review reported that FITs overall had a higher sensitivity for CRC (FIT 61–91% vs. gFOBT 25–38%) and advanced neoplasia (FIT 27–67% vs. gFOBT 16– 31%) than the nonrehydrated Hemoccult II although specificity appeared to be lower (FIT 91–98% vs. gFOBT 98–99%) [72]. Recently, two trials have compared gFOBT and FIT in a randomised populationbased setting [7,40]. Both trials demonstrated a superior detection rate with similar number needed to scope (NNScope) of the one-sample FIT at a cut-off of 100 ng/ml (OC-Sensor) compared to

gFOBT FIT

Cut-off Positivity rate

PPV

ng/ml

n

% (95%CI)

Adv neoplasia CRC Adv neoplasia CRC Adv neoplasia % (95%CI) % (95%CI) n n % (95%CI)

CRC % (95%CI)

Adv neoplasia n % (95%CI)

CRC n % (95%CI)

Adv neoplasia CRC n n

50 75 100 125 150 175 200

65 241 170 143 128 120 107 103

2.8 8.1 5.7 4.8 4.1 4.0 3.6 3.5

45 42 49 53 57 60 63 62

97.6 92.9 95.0 95.8 96.3 96.6 97.0 97.1

28 95 80 73 70 69 64 61

6 16 14 14 13 13 12 12

84 31* 37* 41* 43* 43* 46* 49*

(2.2–3.6) (7.2–9.1)* (4.9–6.6)* (4.1–5.6)* (3.4–4.9)* (3.4–4.8)* (3.0–4.3)* (2.9–4.2)*

(33–58) (36–49) (42–57) (45–61) (48–65) (51–69) (53–72)* (52–71)*

NNscope

10 7 9 10 11 11 12 12

(4–20) (4–11) (5–14) (6–17) (6–17) (7–19) (7–20) (7–20)

2.2 2.4 2.0 1.9 1.8 1.7 1.6* 1.6*

Specificity

10.3 14.1 11.6 9.8 9.5 8.8 8.5 8.2

98.5 95.5 97.2 97.8 98.2 98.4 98.7 98.8

(97.9–99.0) (94.5–96.3)* (96.5–97.7)* (97.2–98.2)* (97.7–98.6) (98.0–98.7) (98.3–99.0) (98.4–99.0)

Detection rate

(94.8–98.9) (88.8–95.5)* (91.8–97.0)* (93.2–97.5) (93.8–97.8) (94.2–98.0) (95.0–98.3) (95.0–98.4)

1.2 3.2 2.7 2.5 2.3 2.3 2.2 2.1

(0.8–1.7) (2.6–3.9)* (2.2–3.3)* (2.0–3.1)* (1.9–3.0)* (2.8–2.9)* (1.7–2.7)* (1.6–2.6)*

NNscreen

0.3 0.5 0.5 0.5 0.4 0.4 0.4 0.4

(0.1–0.6) (0.3–0.9) (0.3–0.9) (0.3–0.8) (0.3–0.8) (0.3–0.8) (0.3–0.8) (0.3–0.8)

392 186 213 213 229 229 248 248

*p < 0.05 compared to gFOBT; Advanced neoplasia: adenoma  10 mm, villous component ( 25% villous) or high-grade dysplasia; CRC. FIT: immunochemical faecal occult blood test; gFOBT: guaiac-based faecal occult blood test; Adv neoplasia: advanced neoplasia; PPV: positive predictive value; CRC: colorectal cancer; NNscope: number needed to scope to detect one screenee with an advanced neoplasia; NNscope: number needed to screen to detect one screenee with an advanced neoplasia; TC: Total Colonoscopy. Table reproduced with permission of the authors and the Br J Cancer.

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Table 2 Table from Hol et al [63]: Test characteristics of gFOBT and FIT at different cut-off levels.

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unrehydrated Hemoccult II [40,63]. Positivity rate for gFOBT and FIT (at a cut-off of 100 ng/mL) were respectively 3% and 5%, with a NNScope for cancer of respectively 10.3 and 9.8 [63]. Both studies found specificity to be lower for the FIT at all cut-off values compared to gFOBT [40,63]. Importantly, in both studies uptake of FIT was significantly higher compared to gFOBT screening with a participation rate of 47–49% for gFOBT and 60–62% for FIT screening [7,40]. This is in line with the results of a study comparing a 3-day wooden spatula with food and dietary restrictions (Hemoccult SENSA), a 3-day spatula (FlexSure OBT) and a 2-day brush (InSure) which found that the participation rate was highest in the InSure group, whereby simplification of sampling was found to have contributed 30% to the total increase in participation [81]. A French study also demonstrated FIT to detect more CRC and advanced neoplasia, with a similar PPV [39]. Two other studies found a comparable detection rate and PPV for gFOBT and FIT [74,75]. Comparative performance of gFOBT and FIT depends on the number of samples and threshold chosen for the quantitative FIT [77]. So, results of direct comparisons vary between studies but overall, the FIT demonstrates a superior sensitivity [4,6,8,72,78] often accompanied by a somewhat lower specificity[4,6,8,72] although other studies report a higher specificity for FIT [76,77]. It has been suggested that a gFOBT screening program could be combined with a FIT for those with a positive gFOBT. This approach has been investigated in a few studies [4,28,82,83]. All studies found that testing gFOBT positives with FIT may decrease the number of false-positives compared to gFOBT screening alone (by an increased specificity or an improved identification of individuals at high risk for significant neoplasia) [4,28,82,83], however two studies also demonstrated that this was accompanied by a further decrease in sensitivity [4,83]. By reducing false-positives, the two-tier approach thereby reduces the number of colonoscopies required, which may limit screening costs, but also considerably affects the diagnostic yield and thus the impact of screening. Conclusion FIT outperforms gFOBT based on a higher sensitivity and detection rate, although results differ between studies. Quantitative FIT screening is the most promising FIT technique since the cut-off value can be changed in order to optimise sensitivity and specificity of the test. A two-day FIT is possibly favoured over a one-day FIT, but further research is necessary. A two-tier approach of testing those positive for gFOBT by FIT may increase specificity and be therefore advantageous in settings with limited endoscopy capacity or financial recourses available. However, the decrease in sensitivity by this approach warrants further research and careful consideration. Stool based DNA tests Performance determinants SDNA tests detect specific mutations (known alterations in the adenoma-carcinoma sequence), in cellular DNA excreted in stool, that are associated with CRC development. Adenoma and carcinoma cells with DNA mutations are continuously shed into the large bowel and passed into the faeces [2]. Human DNA can be differentiated from faecal bacterial DNA since human DNA is stable in stool [2]. Only 0.01% of stool DNA is of human origin, the rest comes from sources such as the microflora and diet [84]. DNA mutations can be detected by sDNA tests using PCR methodologies [10] (for example the more recently applied, highly sensitive, BEAMing [85] or digital melt curve analysis (DMC) [86]). SDNA tests require the collection of only a single stool sample per round and no diet or medication restrictions [11]. However, currently the commercially available sDNA test requires the collection of an entire stool specimen instead of a small sample and patients need to have access to a working freezer [2]. Performance of sDNA tests depends on the chosen panorama of markers, stool processing and preservation, DNA extraction from the faecal sample and method of analysis. SDNA tests are generally subdivided into first and second generation tests [10,11,41], with important differences in the utilised panel of markers. A sDNA test usually aims at the detection of multiple gene mutations, since there is not one single mutation present in all advanced adenoma or CRC cells [2].

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The assay of markers utilised by the sDNA test must yield an acceptable sensitivity [87]. Many first generation tests used the multimarker panel PreGen-Plus [36,88–91]. This test consists of a multimarker panel that aims at the detection of 21 point mutations in the K-ras, APC, P53 genes; a probe for BAT-26 (marker for microsatellite instability); and a marker of DNA integrity analysis [2]. In the past five years, research has focussed on improving marker panels by identifying new markers. In this respect, the gene hypermethylation pathway has gained major interest, since it seems a much more common pathway than previously assumed [41]. Several markers aiming at hypermethylated genes have been developed. Hypermethylation of the vimentin gene was found to be present in 43% of CRC patients and only 10% of controls [92]. Subsequently, using vimentin methylation as a single marker was found to be associated with a 73% sensitivity for CRC and a 87% specificity [93]. Since a new version of the long DNA assay provided a 65% sensitivity and 93% specificity, both markers were combined which resulted in a 83% sensitivity for CRC and 82% specificity [94]. Cancer detection was independent of CRC location or stage. Recently, methylation of the SFRP2 gene (involved in the wnt signalling pathway) has been an important target for sDNA tests, either as a single marker or combined [95–100]. Furthermore, many other methylated gene targets have been studied, with sometimes promising results [92,101–107]. The currently used panels of DNA markers seem to detect the majority, but not all CRC [2]. Stool sample processing and preservation are other determinants of sDNA test performance and therefore targets for improvement [2]. Hereby, preservation of DNA in stool without degradation during sample handling is an important target. A stabilising buffer has been developed to improve sDNA preservation [87]. Furthermore, freezing of stool samples after collection or transporting the samples to the laboratory as soon as possible maintains DNA stability [87]. Another determinant of sDNA test performance is the capacity of the chosen mutation detection method to distinguish mutant DNA from wild type DNA, since human stool DNA is highly heterogeneous [87]. The chosen method must have sufficient analytical sensitivity to detect as little as 1% mutant DNA [87]. Therefore techniques have been developed to allow for better extraction of DNA from the stool [108]. BEAMing [85] and DMC [86] are recently developed, highly sensitive methods of analysis that may add to the detection of low-abundance mutations. Since many issues limiting performance of first generation tests have been overcome, performance improvements from now on can be merely achieved by optimising choice of markers and method of analysis [41]. Although this seems promising, there are several reasons for the currently limited application of sDNA tests. First of all, optimisation of new marker panels and assay platforms is advised prior to widespread implementation of next-generation stool DNA testing [11]. Secondly, high throughput systems are required for analysing large numbers of samples with high precision [11]. There are uncertainties about the cost-effectiveness of sDNA tests, which should be assessed critically before implementation [11]. The ideal number of stool samples and screening interval are other issues to be addressed [10]. A last issue is the implication of positive sDNA test results without identifiable colonic abnormality [2]. SDNA tests may possibly also detect supracolonic cancers (e.g. oropharynx, oesophagus, stomach, pancreas, gallbladder) given the fact that these cells may survive into the faeces [11,84]. This has to be studied systematically [2] and there should be guidance for diagnostic evaluation of positive test results and clinical decision making [11]. When solving this issues, true population-based studies are required to accurately establish sDNA test performance in average risk-subjects, since this has only been evaluated by two studies so far [36,89].

Performance Of the two studies performed among average-risk subjects, one study found the positivity of the sDNA in average-risk subjects to be 18%, accompanied by a sensitivity of 52% for CRC and 15% for advanced adenomas [36]. Specificity was 94%. The second study found a sensitivity for CRC of 20%, with a 96% specificity [89]. In other, usually small-scale, studies with often mainly symptomatic subjects, sensitivity for CRC ranged between 62–97% for first-generation sDNA tests, accompanied by specificities of 93–100%. [41] Sensitivity of second generation sDNA tests in small scale studies with symptomatic subjects generally ranges from 42–96%, with specificities usually between 77–100% [41].

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FOBT vs. sDNA The continuous shedding of cells with DNA mutations into the large bowel may favour sDNA testing to both gFOBT and FIT since adenomas and CRC are believed to bleed intermittently into the colon. A part of CRCs will therefore likely be missed by FOBT testing [2], as both FOBTs aim at the detection of blood components that will thus not be present in every faecal sample. Furthermore, since sDNA tests may also detect gene mutations in cells shed from adenomas, they are possibly more effective for CRC prevention than gFOBT or FIT [11]. Few studies have directly compared FOBT and sDNA test performance [36,89]. One study among average-risk subjects concluded that faecal DNA (PreGenPlus) detected more advanced colorectal neoplasias than unrehydrated Hemoccult II, without a reduction in specificity [36]. Another study found no improvement in the detection of significant neoplasm for PreGenPlus over Hemoccult SENSA [89]. Another sDNA test (SDT-2), only performed in a small subset, detected significantly more neoplasm than both Hemoccult II and Hemoccult SENSA. This was however accompanied by a higher false-positivity rate. A combination of sDNA (aiming at APC, BAT-26 and Long DNA) and a standard gFOBT was found to highly increase sensitivity for cancer (93% for the combination vs. 51% for gFOBT and 65% for sDNA), but decrease specificity (89% combination, 98% gFOBT, 91% sDNA) [109].

Conclusion Although sDNA tests have potential given their generally high specificity and an equal or superior sensitivity to gFOBT, further studies on test performance in average-risk populations are necessary as well as comparisons to FIT screening. Summary In the Western World, many countries have adopted a CRC screening program, often based on FOBT screening. gFOBT screening has proven to decrease CRC related mortality, however, FITs have several advantages over gFOBT. First of all, FIT has a better sensitivity and higher uptake compared to gFOBT. Furthermore, the quantitative FIT enables choosing a cut-off level according to the desired detection rate in the population and colonoscopy resources available. The second generation sDNA shows a high sensitivity and specificity, however population based studies are lacking.

Practice points  gFOBT is the only screening test which has in a prospective setting been proven to reduce CRC mortality.  FIT generally shows increased sensitivity and detection rate compared to gFOBT.  Quantitative FITs have several advantages over qualitative FITs.  sDNA testing is promising, but further research is warranted, among which studies in large average risk population settings.

Research agenda  Randomised studies comparing performance of different numbers of FIT samples.  Further studies determining sensitivity and specificity of sDNA tests in average risk populations.  A direct comparison of sDNA with FIT.

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