Estimated Mean Sojourn Time Associated with Hemoccult SENSA for Detection of Proximal and Distal Colorectal Cancer

Abstract

Background

Sojourn time is the length of the preclinical screen-detectable phase, a period when a test can detect asymptomatic disease. Mean sojourn time (MST) is an important factor in determining appropriate screening intervals. Available estimates of MST for colorectal cancer (CRC) are imprecise and are associated with the older Hemoccult II test. This paper presents MST estimates associated with the newer Hemoccult SENSA test and describes differences in MST by the location of cancer in the colorectum and age at the time of screening.

Methods

MST was estimated from a cohort of 42,079 patients who underwent Hemoccult SENSA between January 1, 1997 and December 31, 2010. The precision of MST estimates was improved by incorporating information from a meta-analysis of the sensitivity of Hemoccult SENSA into the analytic model.

Results

Estimated MST for cancers in the proximal and distal colorectum, with 95% credible intervals in years, were: 3.86 (1.55, 6.91) and 3.35 (2.11, 4.93) among 45–54 year olds; 3.78 (2.18, 5.77) and 2.24 (1.48, 3.17) among 55–64 year olds; and 2.70 (1.41, 4.31) and 2.10 (1.34, 3.04) among 65–74 year olds.

Conclusions

MST associated with Hemoccult SENSA was longer for CRC in the proximal versus distal colon. We found no evidence that MST increases with age, and some evidence that it may decrease.

Impact

These results add new information about the natural history of colorectal cancer, and information about the performance of Hemoccult SENSA.

The effectiveness of screening tests depends on test sensitivity, sojourn time, and treatment effectiveness. While much is known about the accuracy of colorectal cancer (CRC) screening tests(1) and treatment effectiveness(2, 3), relatively little is known about its mean sojourn time (MST). Sojourn time is the duration of the preclinical disease state that begins when asymptomatic colorectal cancer can be detected by a screening test and ends with clinical detection, that is, when a patient presents with symptoms.

Cohort studies that follow individuals after a negative screening test can be used to jointly estimate test sensitivity and mean sojourn time (MST). Several studies have estimated sensitivity and MST for Hemoccult II, an older FOBT (4–9). Unlike accuracy studies, which are cross-sectional and require a reference standard assessment for all participants, cohort studies rely on follow-up data combined with additional model assumptions to estimate sojourn time. Prior studies that jointly estimated MST and sensitivity were based on the Hemoccult II test, and resulting MST estimates were imprecise.

We provide updated estimates of MST associated with Hemoccult SENSA(10), the current standard for high-sensitivity guaiac-based FOBT, and investigate differences in MST by the location of cancer in the colorectum and age at the time of screening. We jointly model sensitivity and MST using data from a cohort of individuals, incorporating information from a meta-analysis of the sensitivity of Hemoccult SENSA to improve the precision of estimates.

METHODS

Meta-analysis of FOBT accuracy studies

We searched Web of Science(11) and Academic Search Complete(12) to identify articles describing the accuracy of Hemoccult SENSA, using combinations of the following terms: “Hemoccult”, “colorectal”, “sensitivity”, “screening”, “FOBT”, and “SENSA”. Because test accuracy balances sensitivity and specificity resulting in correlation between these measures, articles were included in analyses if they focused on a population at average risk for CRC and described the number of true positive outcomes (TP, positive test among individuals with CRC); false positive outcomes (FP, positive test among individuals without CRC); false negative outcomes (FN, negative test among individuals with CRC); and true negative outcomes (TN, negative test among individuals without CRC). When articles reported findings from overlapping cohorts, only the most recent study was included. From each article, we recorded first author, year of publication, study period, description of population, study design, reference standard used to determine CRC status, and test outcomes (TP, FP, FN and TN). We calculated sensitivity and specificity using: sensitivity=TP/(TP+FN), specificity=TN/(FP+TN).

Statistical analysis

We found that sensitivity and specificity were essentially uncorrelated across studies: sensitivity varied widely while specificity was nearly constant. Thus, we summarized sensitivity and specificity separately(13) and our analyses focus on sensitivity. We combined information across studies using a random effects model(14) to allow for between-study heterogeneity in sensitivity. Analyses used MetaAnalyst software(15), and estimates are reported with a 95% confidence intervals (CI).

Joint estimation of sensitivity and MST

Analyses use data from a retrospective cohort of individuals 45–74 years old who had at least one Hemoccult SENSA FOBT between January 1, 1997 and December 31, 2010 while members of Group Health Cooperative, a large health care system in Washington State. During this period, Hemoccult SENSA was used for all FOBT at Group Health. However, overall CRC screening guidelines changed over the study period. In 1997, the screening guideline for average-risk members was FOBT (using Hemoccult SENSA) every 2 years plus flexible sigmoidoscopy every 10 years. Guidelines added colonoscopy as a screening modality in 2001, when Medicare began coverage for screening colonoscopy(16, 17). In 2004, guidelines were modified to recommend shorter FOBT screening intervals, with FOBT every 1 to 2 years. In 2006, FOBT screening intervals were shortened again to every year. Throughout the study period, all patients with a positive FOBT were recommended for referral to colonoscopy.

Individuals enter the cohort at the time of their first known (index) FOBT. We excluded individuals with less than six months of follow-up, unless they were diagnosed with CRC within six months of their index FOBT. We also excluded individuals who had lower endoscopy (flexible sigmoidoscopy or colonoscopy) prior to their FOBT, because this reduces the risk of developing CRC(18). We excluded individuals with a total bowel resection or any diagnosis of cancer other than non-melanoma skin cancer prior to their index FOBT because these individuals are ineligible for routine CRC screening. CRC diagnoses were identified using Surveillance, Epidemiology, and End Results (SEER) data(19). The location of CRC was coded as proximal (located in the cecum, ascending, or transverse colon) or distal (located in the descending or sigmoid colon, or the rectum). We excluded one CRC with an unspecified location.

Individuals with a positive index FOBT contributed information about screen-detected CRC, defined as CRC diagnosed within six months after a positive index FOBT. We treated 17 CRCs diagnosed more than six months after a positive index FOBT as false positive tests (13 were diagnosed more than a year after screening).

Individuals with a negative index FOBT contributed information about symptom-detected CRC and were followed until the first occurrence of one of five endpoints: 1) symptom-detected CRC; 2) next CRC test (FOBT, flexible sigmoidoscopy, colonoscopy, or barium enema); 3) death or disenrollment from the health plan; 4) end of screening eligibility because of colonic resection or diagnosis with any non-colorectal cancer other than non-melanoma skin cancer; or 5) end of study period. Symptom-detected CRC is an observed event whereas other endpoints are censoring events. We assume that CRC is symptom-detected if the diagnosis is made without evidence of a prior FOBT (excluding the index test), flexible sigmoidoscopy, or barium enema. This assumes that FOBT, flexible sigmoidoscopy, and barium enema were used for screening. We make the simplifying assumption that all colonoscopy during this period was diagnostic (used to evaluate symptoms), an assumption we explore in sensitivity analyses. Thus, we included CRC diagnosed within six months of the first colonoscopy as symptom-detected. Six individuals with CRC diagnosed more than 6 months after a colonoscopy could not be categorized as interval cancers; their follow-up time was censored at the time of their first colonoscopy.

Statistical model

We use information from screen-detected cancers and symptom-detected cancers that arise during follow-up after a negative FOBT to estimate sensitivity and MST for three strata based on age (in years) at the time of the index FOBT: 45–54, 55–64 and 65–74. Within each strata, let n denote the number of people who had an index FOBT at age T and let S denote the sensitivity of FOBT to detect preclinical CRC when present. Among these n individuals, c_P proximal CRCs are screen-detected and c_D distal CRCs are screen-detected. We assume that (c_P, c_D, n-c_P-c_D) follows a Multinomial distribution. Let L indicate the location of cancer with L=P for proximal CRC and L=D for distal CRC. The probability of detecting CRC in location L at the time of screening at age T is given by S×P(λ_L, J_L, T), where P(λ_L, J_L, T), the probability of preclinical CRC at the age T, is a function of the location-specific incidence rate of preclinical CRC (J_L) and the location-specific incidence rate of clinical CRC (λ_L).

We estimate P(λ_L, J_L,, T) using a time-homogeneous Markov model (20) that describes transitions through 3 disease states: disease free, preclinical disease and clinical disease. Transition time between these states is modeled with an exponential distribution (e.g., time from preclinical to clinical CRC has probability density function f(s)=λ_Lexp(−λ_Ls) so that MST is equal to 1/λ_L)(4–6, 8, 9, 21). Among asymptomatic individuals, the probability of being in the preclinical state at age T is equal to the probability of transitioning into the preclinical disease state by age T divided by the probability of either remaining in the disease-free state or transitioning into the preclinical state by age T:

$$P({\lambda }_L,J_L,T)=\frac{J_L(e^{-{\lambda }_{L}T}-e^{-J_{L}T})/(J_L-{\lambda }_L)}{e^{-J_{L}T}+J_L(e^{-{\lambda }_{L}T}-e^{-J_{L}T})/(J_L-{\lambda }_L)}$$ (1)

We treat unobservable preclinical CRC incidence rates J_P and J_D as known constants approximated by the observed clinical incidence from 1975–1979 SEER data(5, 6) (19, 21, 22), using this time period because it precedes the diffusion of CRC screening and so reflects incidence in an unscreened population. We assumed that preclinical disease incidence rates were constant within age strata, setting J_P equal to 1.08, 3.08 and 7.92 per 10000, for ages, 45–54, 55–64, and 65–74, and setting J_D equal to 2.95, 7.96 and 15.6 per 10 000 for ages, 45–54, 55–64, and 65–74.

We approximate the age at screening, T, with the strata midpoint (e.g. we use T=50 for 45–54 year old individuals). This approximation is needed to calculate equation (1). This assumption had no impact on estimates because within each age strata and for plausible values of λ and J, P(λ, J, T) depends on λ, but varies little with T. This can be seen by re-expressing equation (1) as P(λ_L, J_L, T) =1−(J_L − λ_L)/(J_L exp[(J_L − λ_L)T]−λ_L). Developing preclinical disease is rare, but once preclinical disease has developed clinical disease is not rare. Therefore, for both proximal and distal locations, the overall preclinical disease incidence, J_L, is much smaller than clinical disease incidence among individuals with preclinical disease, λ_L so equation (1) is dominated by (J_L − λ_L)/λ_L.

Let t indicate follow-up time. The index FOBT occurs at time t=0. During the t-th follow-up year, (t−1, t] years since the negative index FOBT, we observe x_Pt symptom-detected proximal CRCs and x_Dt symptom-detected distal CRCs among y_t person-years at risk. Individuals are at risk in the t-th follow-up year if they were followed at least t years or were diagnosed with CRC during the t-th follow-up year. For t=1,2,…,k, we assume that (x_Pt, x_Dt, y_t − x_Pt − x_Dt) follows a Multinomial distribution. The probability of symptom-detected CRC in location L is equal to I(t, S, J_L, λ_L, c_L)/y_t, where the expected number of symptom-detected CRCs in the t-th follow-up year is given by:

$$\begin{array}{l}I(t,S,J_L,{\lambda }_L,c_L)=y_t{J}_L\underset{0}{\overset{t-0.5}{\int }}f(s)ds+\frac{c_L(1-S)}{S}\left[1-\underset{0}{\overset{t-0.5}{\int }}f(s)ds\right]\\ =y_t{J}_L[1-exp(-{\lambda }_L(t-0.5))]+\frac{c_L(1-S)}{S}exp(-{\lambda }_L(t-0.5))\end{array}$$

Symptom-detected cancers are a mixture of preclinical cancers present but missed at the time of the index screening (false negative tests) and new cancers that developed after the index screening (true negative tests). We assume that individuals with symptom-detected CRC in the t-th follow-up year entered the clinical disease state at the midpoint of the t-th follow-up year. The expected number of symptom-detected CRCs in follow-up year t that were missed by screening is the product of the expected number of preclinical CRCs missed by screening (c_L(1−S)/S) and the probability that their sojourn time is greater than or equal to t−0.5, assuming that these individuals entered the preclinical disease state before or at the time of the index screening test. The expected number of newly developed CRCs that are symptom-detected in follow-up year t is the product of the expected number of new preclinical cancers (y_tJ_L) and the probability that their sojourn time is less than or equal to t−0.5, assuming that these individuals entered the preclinical disease state after the time of the index screening test.

For each age strata, the joint likelihood is given by the product, L₁L₂. L₁ is associated with screen-detected CRC:

$$L_1=\left(\frac{n!}{c_P!c_D!(n-c_p-c_D)!}\right){\left(S\times P({\lambda }_P,J_P,T)\right)}^{c_P}{\left(S\times P({\lambda }_D,J_D,T)\right)}^{c_D}{\left(1-S\times P({\lambda }_D,J_D,T)-S\times P({\lambda }_D,J_D,T)\right)}^{(n-c_P-c_D)}$$

L₂ is associated with symptom-detected CRC during follow-up:

$$L_2=\prod _{t=1}^k\left\{\left(\frac{y_t!}{x_{Pt}!x_{Dt}!(y_t-x_{Pt}-x_{Dt})!}\right)\times {\left(\frac{I(t,S,J_P,{\lambda }_{P,}{c}_P)}{y_t}\right)}^{x_{Pt}}\times {\left(\frac{I(t,S,J_D,{\lambda }_D,c_D))}{y_t}\right)}^{x_{Dt}}\times {\left(1-\frac{I(t,S,J_P,{\lambda }_P,c_P)}{y_t}-\frac{I(t,S,J_D,{\lambda }_D,c_D))}{y_t}\right)}^{y_t-x_{Pt}-x_{Dt}}\right\}$$

We use a Bayesian model, specifying prior distributions for 1/λ_P, 1/λ_D and S. We assume S has a Normal prior based on our meta-analysis of FOBT sensitivity. Because we lacked information about MST, we assumed a Uniform(0.05, 10) prior distribution for MST associated with both proximal (1/λ_P) and distal (1/λ_D) CRC.

We jointly estimated MST and sensitivity using Gibbs sampling, implemented using WinBUGs software (23). We assessed convergence using the method of Gelman and Rubin (24), based on five chains started at widely dispersed points in the sample space. Our estimates are based on simulated draws that showed evidence for convergence, with Gelman and Rubin statistics greater than 0.99. We report estimated mean sensitivity and sojourn times with 95% credible intervals (CrI) (25). The bounds of 95% CrI are estimated by the 25^th and 75^th percentiles of the simulated posterior samples. The 95% CrI is an interval with a 95% probability of containing the true parameter value. We used pairwise comparisons to test for differences in MST by age strata and CRC location and present estimated mean differences with posterior probabilities that these differences are greater than zero to indicate statistical significance (25).

We carried out several sensitivity analyses to explore the impact of model assumptions. We estimated a model that allowed the incidence rate of preclinical cancer, J, to increase over the follow-up period, based on linear interpolation of J at ages 50, 60, and 70. We estimated models stratified by the year of index FOBT, using strata based on changes to guideline recommendations: 1997–1999, 2000–2002, 2003–2005 and 2006–2010. We also estimated models that treated the 17 patients with CRC detected more than six months after a positive index FOBT as true positive test results. Finally, we estimated a model that speicified a Uniform (0.001,0.999) prior distribution for S.

RESULTS

Meta-analysis of FOBT accuracy studies

Thirty studies met our criteria for review. We excluded 25 studies because of insufficient data to calculate sensitivity and specificity (n=17), their sample represented a population at high risk for CRC (n=3), their study sample overlapped with another included study (n=3), or no primary data were reported (e.g., simulation studies, n=2). Our meta-analysis included five studies that estimated both the sensitivity and specificity of Hemoccult SENSA in an average risk population (Table 1, Figure 1)(26–31). The estimated overall sensitivity was 0.748 (95% CI: 0.630, 0.839), which corresponds to a Normal prior distribution for S with mean 0.748 and standard deviation 0.05, truncated to range from 0.001 to 0.999.

Table 1.

Characteristics of Studies for Average Risk Populations

Study (year)	Study Period	Population	Study Design	Gold Standard	TP*	FN	FP	TN	Sensitivity	Specificity
Allison (2007) (26)	4/1997–10/1999	Patients aged 50–80 years old at average risk for colorectal cancer	Prospective	Colonoscopy for test positive, Flex Sig for test negative, plus 2-year follow-up	9	5	575	5210	64.3%	90.1%
Allison (1996) (23)	10/1990–10/1991	People at least 50 years old with an average risk of colorectal cancer	Prospective	Flex Sig for Hemoccult II SENSA positive, 2-year follow-up	27	7	1046	6824	79.4%	86.7%
Ahlquist (2008) (27)	2001–2007	Asymptomatic persons age 50–80 years at average risk for colorectal cancer	Cross-sectional	Colonoscopy for all participants	12	7	144	3601	63.2%	96.2%
Rennert (2001) (25)	1992–1997	Asymptomatic patients in Israel, age 50–74	Prospective	Full colonoscopy or sigmoidoscopy plus double contrast barium enema for test positive with follow-up with mean time 34.1 months	58	10	977	21148	85.3%	95.6%
Rozen (1997) (24)	Not Stated	97% consecutive asymptomatic persons and 3% symptomatic patients evaluated for abdominal complaints	Cross-sectional	Colonoscopy for test positive, otherwise flexible sigmoidoscopy	3	2	32	366	60.0%	92.0%

^*TP: true positive tests; FP: false positive tests; FN: false negative tests; TN: true negative test

Figure 1.

Jointly estimated sensitivity and MST

Our cohort included 42,079 individuals. Overall rates of a positive FOBT were 6% to 7%, approximately half of the patients in our sample were women, and the average age at index screening was about 56 years (Table 2). Among subjects with a negative index FOBT, the average follow-up time was about 3 years (Table 3). The length of follow-up decreased over time, consistent with decreases in recommended screening intervals and a shorter time to the end of the follow-up period. Over time, the percentage of individuals censored because of colonoscopy increased from 6.7% to 10.7%; with similar trends across age strata. While the reasons for censoring shifted away from FOBT and toward colonoscopy, patterns of censoring were similar across age strata (data not shown).

Table 2.

Characteristics of the Cohort

	Year of index FOBT test
	1997–1999 (n=13,556)	2000–2002 (n=10,209)	2003–2005 (n=7,879)	2006–2010 (n=10,435)
Positive FOBT, %	6.7	6.3	7.3	7.0
Female, %	53.5	55.3	55.1	54.3
Age, years
Mean (SD)	57.7 (7.8)	56.1 (7.1)	55.3 (6.5)	56.2 (6.4)
45–54, %	43.4	53.1	56.0	48.8
55–64, %	33.5	31.5	32.8	38.5
65–74, %	23.1	15.4	11.2	12.7

Table 3. Follow-up Information for Individuals with a Negative FOBT.

Individuals with less than one year of follow-up contributed information only if diagnosed with CRC within one year of a negative FOBT.

	Year of index FOBT test
	1997–1999 (n=12,647)	2000–2002 (n=9,562)	2003–2005 (n=7,304)	2006–2010 (n=9,708)
Follow-up time, year
Mean (SD)	3.4 (2.7)	3.2 (2.3)	2.9 (1.7)	1.6 (1.0)
<1, %	10.5	11.8	12.3	32.5
1 – <2, %	25.7	24.7	25.1	40.6
2 – <3, %	23.4	23.3	23.8	16.8
3 – <4, %	13.0	12.5	14.6	6.8
4+, %	27.4	27.7	24.2	3.3
Reason end follow-up, %
CRC diagnosis	0.2	0.1	0.1	0.1
FOBT, Flexible Sigmoidoscopy, or Barium Enema	66.8	60.2	53.6	29.8
Colonoscopy	6.7	11.1	17.8	10.7
Non-CRC cancer or resection	2.8	2.1	1.8	0.9
Disenrollment	20.5	21.7	18.8	9.7
Death	1.2	0.9	0.6	0.2
End of follow-up	1.8	3.9	7.3	48.6

We identified 93 screen-detected cancers (29 proximal and 64 distal (13 rectum)) and 52 symptom-detected cancers (32 proximal and 20 distal (4 rectum)). Estimated sensitivity was stable across age strata (Table 4). MST was longer in the proximal than distal colon (Tables 4 and 5). MST was shorter in older age strata, especially for cancer in the distal colorectum (Table 4 and 5).

Table 4.

Estimated Sensitivity and MST, with 95% Credible Intervals

Index age	Sensitivity	Mean Sojourn Time (MST)
		Proximal Colon	Distal Colorectum
45–54	0.87 (0.80, 0.94)	3.86 (1.55, 6.91)	3.35 (2.11, 4.93)
55–64	0.87 (0.80, 0.93)	3.78 (2.18, 5.77)	2.24 (1.48, 3.17)
65–74	0.82 (0.75, 0.90)	2.70 (1.41, 4.31)	2.10 (1.34, 3.04)

Table 5.

Comparison of Mean Sojourn Time (MST) by Site and Age Group.

	Average MST Difference	95% Credible Interval	Posterior Probability1
Proximal vs. Distal Colorectum
Index age 45–54	0.51	(−2.33, 3.85)	0.61
Index age 55–64	1.54	(−0.31, 3.66)	0.95
Index age 65–74	0.60	(−1.03, 2.40)	0.75
Index Age 55–64 vs. 45–54 years
Proximal colon	−0.09	(−3.52, 2.99)	0.49
Distal colorectum	−1.11	(−2.89, 0.44)	0.08
Index Age 65–74 vs. 45–54 years
Proximal colon	−1.16	(−4.47, 1.66)	0.23
Distal colorectum	−1.25	(−3.01, 0.31)	0.06
Index age 65–74 vs. 55–64 years
Proximal colon	−1.08	(−3.44, 1.16)	0.18
Distal colorectum	−0.14	(−1.34, 1.08)	0.41

¹The estimated posterior probability that the difference is greater than zero.

Sensitivity analysis resulted in similar findings. Analyses stratified by year of index FOBT showed no evidence of systematic changes in MST over time. MST estimates based on a model with a Uniform (0.001, 0.999) prior distribution for S were similar to analyses presented, but with greater variability. Our results were unaffected by assumptions about patients with CRC detected more than six months after a positive index FOBT.

DISCUSSION

Our study is the first to jointly estimate the sensitivity and MST based on the newer, highly sensitive guaiac-based Hemoccult SENSA test, and is the first to estimate MST by both location in the colorectum and age at the time of screening.

We found that MST associated with Hemoccult SENSA was longer for CRC in the proximal versus distal colon. This finding is consistent with the current knowledge of biological differences in left and right sided colorectal cancer (32–34). It is well-established that there are multiple pathways to CRC, and the frequency of carcinomas arising from these different pathways varies by anatomic location (35). The most common pathway, termed the conventional adenoma-carcinoma pathway, results in carcinomas that tend to exhibit chromosomal instability (CIN) but lack microsatellite instability (MSI).(36) A separate pathway, the “serrated pathway”, is associated with carcinomas characterized by a CpG island methylator phenotype (CIMP), microsatellite instability (MSI), and often BRAF-mutation (37–39). The serrated pathway is much more common in the proximal colon than in the distal colon and rectum, as evidenced by the distribution of CIMP-positive carcinomas, with 30–32% of proximal colon cancers being CIMP-positive, compared to 3–5% of distal colon and rectal carcinomas (40, 41). There is also evidence that cancer exhibiting molecular markers associated with the serrated pathway, specifically MSI(42, 43) and CIMP(44, 45), are associated with better prognosis than cancers without these molecular markers. Therefore, estimated differences in mean sojourn time for cancers in the proximal and distal colon may reflect differences in pathways leading to cancer. Despite the uncertainty about the time to progression for cancers in the serrated pathway, this may be evidence for a less aggressive disease with longer mean sojourn time.

We found no evidence that MST increased with age, and some evidence that it may decrease. This may reflect other age-related differences in the characteristics of colorectal cancers.

Our models differed somewhat from earlier approaches. We extended the model proposed by Prevost and colleagues(6) to investigate differences in MST by location, using a multinomial distribution to simultaneously describe the occurrence of proximal and distal CRC. We incorporated information from a meta-analysis of the sensitivity of Hemoccult SENSA to increase the precision of our estimates. The resulting Normal prior distribution for sensitivity improved precision, but did not drive our findings.

Because both Hemoccult SENSA and Hemoccult II are guaiac-based tests that detect bleeding, we expected that our results would be similar to earlier findings for Hemoccult II. Our MST estimates (ranging from 2.7 to 3.9 years) were longer than previous estimates. The first study to jointly estimate MST and sensitivity estimated a 2.1 year MST (standard error (SE)=0.18)(4). A subsequent study(5) estimated sensitivity and MST for cancers in the proximal colon, distal colon, and rectum, and found that the sensitivity was similar for all three locations; MSTs varied with location, though estimates were imprecise: estimated MST was 3.5 years (95% CI: 1.6, 11.3) for the proximal colon, 6.4 years (95% CI: 3.9, 14.8) for the distal colon, and 2.6 years (95% CI: 1.2, 11.2) for the rectum. A third study estimated a 2.6-year MST(8).

We found some evidence that MST decreased with age. Previous studies have generally found an increase in MST with age. The first study to examine age differences in MST found that the sensitivity of Hemoccult II decreased with age while MST increased with age, though 95% credible intervals associated with these MST estimates were more than 10 years wide(6). A additional analysis of these data reported estimated MST of 3.4 years for 50-year-olds and 5.8 years for 60-year-olds, though the precision of estimates was not reported(7).

We made several simplifying assumptions when building our models. Sensitivity analysis demonstrated that our results were robust to many assumptions. In particular, while primary analyses restricted the variability of FOBT sensitivity across age groups, analyses that allowed sensitivity to vary across age groups, using a Uniform prior distribution, produced similar findings. The influence of some assumptions was untested. We assumed that FOBT sensitivity was the same for proximal and distal CRC. This is consistent with earlier estimates from joint estimation of MST and sensitivity(5). Additional support for this assumption comes from a 1992 study of individuals with newly diagnosed CRC that found that the sensitivity of Hemoccult II did not vary for proximal and distal CRC(46). Further support comes from a study which found that the distribution of cancer across locations in the colorectum was similar for an FOBT-screened group (n=100) and an unscreened group (n=1390) (47).

Our data has two important limitations. First, we were unable to distinguish between screening and diagnostic tests. We assumed that FOBT, flexible sigmoidoscopy, and barium enema were used to screen for CRC, and censored individuals at the time of additional tests. Some of these tests may have been performed in response to symptoms. Resulting misclassification of symptom-detected cancers as screen detected (censored at the time of the exam) would bias our results toward longer MST. We also assumed that all colonoscopy was diagnostic, though the uptake of screening colonoscopy increased over the study period(48–50). Misclassifying cancer detected by screening colonoscopy as symptom-detected would bias our results toward shorter MST. Results from models stratified by year of index FOBT did not demonstrate the shortening of MST over time that would be expected with increased screening colonoscopy. Older age groups may also appear to have shorter MST if older individuals were more likely to undergo screening colonoscopy. We did not find evidence of differential rates of colonoscopy across age groups.

Another limitation is the potential for informative censoring. Our estimates are based on differences between the expected and observed numbers of symptom-detected CRC during the follow-up period. Individuals were removed from the risk set when they were re-tested for CRC, regardless of whether this was for screening or symptom evaluation. If this censoring mechanism differentially removes individuals at higher risk of CRC, then remaining individuals are at lower risk than the overall population, resulting in higher estimates of sensitivity (fewer missed cancers that later become symptomatic) and longer estimates of MST (fewer new cancers that become symptomatic). Estimated age differences could be biased if there was differential censoring of individuals at greater risk for CRC and the degree of differential censoring varied across age strata. We cannot rule out differential selection into screening across age strata, even though we found no evidence for differential censoring.

Finally, while we found evidence of longer MST for proximal CRC, this could reflect differences in the detection accuracy for proximal and distal cancers. If symptomatic proximal cancers are more frequently missed (for example, because they arise from flat or sessile polyps)(51), this could delay diagnosis and create the appearance that proximal CRC has a longer sojourn time.

Our MST estimates provide support for annual CRC screening with Hemoccult SENSA. Further studies that more fully explore differences in MST by gender, race, and risk factors such as family history could provide additional information to guide personalized screening regimens.