Supplementary Data
Details on the statistical analysis
All statistical analysis were performed using the software packages STATA 10.0
(StataCorp. 2007) and R 2.6.2 (R Development Core Team, 2008). All continuous variables were
expressed by their mean and corresponding standard deviations. Categorical variables were
evaluated by frequencies and proportions. For presence of concomitant intestinal stenoses based
on fistulas as diagnostic predictor, sensitivity, specitivity, positive predictive value (PPV), negative
predictive value (NPV), and corresponding binomial 95% confidence intervals (95% CI) according
to Wilson were calculated. In addition, we used (bivariate) logistic regression analysis to measure
the strength of the association between stenosis and fistula presented as odds ratio (OR) and
corresponding 95% CI according to Wald. In addition, we built a multivariate logistic regression
model to predict the presence or absence of stenosis considering the following potential clinical
and health-related predictors: fistula, gender, age (in years), disease duration (in years), smoking
behaviour, body mass index (BMI), and therapy with infliximab and immunosuppressive agents.
To account for the possibility of non-linear relationships between stenosis and continuous
covariates such as age, age at disease onset, disease duration, and BMI, we applied fractional
polynomials to build multivariate logistic regression models. We used the multivariable fractional
polynomials (MFP) algorithm developed by Sauerbrei and Royston
18-20
, which combines the
selection of the functional forms of each continuous covariate using fractional polynomials of first
and second degree with the selection of all (continuous and non-continuous) covariates via
backward elimination. We set the selection level for the fractional polynomials to 0.05 using closed
test procedure and set the nominal p-value for the potential predictors to 0.01 to prevent the risk of
overfitting. In order to judge the ability of the multivariate logistic regression model to discriminate
between patients with and without stenosis, we converted the linear predictor of the logistic
regression model to the estimated probability of having stenosis. Then, each patient can be
classified as having stenosis if their estimated probability exceeds a chosen value (“cutting point”)
Jürgens M et al. Fistulas as predictor of stricturing Crohn’s disease
2
or as not having stenosis. The lower the chosen cutting point, the higher the sensitivity and the
lower the specificity will be. The sensitivity and specificity of all possible cutting points can be
graphically represented as the receiver operating characteristic (ROC) curve by plotting the
sensitivity on 1 minus specificity. In addition, we calculated the area under the ROC curve (AUC)
as a measure of overall discriminatory power of the multivariate logistic regression model. Further,
the fit of the final multivariate logistic regression model was judged by an intense graphically based
residual analysis 21.
To quantify the impact of the genotypes, we created contingency tables to describe the
association between the presence or absence of stenosis and the different NOD2/CARD15 and
IL23R genotypes. We used Fisher’s exact test to analyze the association between the presence of
stenosis and each genotype. Overall, we tested 14 genotypes: 10 IL23R gene variants, the three
main NOD2 mutations, and the presence or absence of any NOD2 mutation. To adjust for multiple
testing, we used the method proposed by Benjamini and Hochberg to control the false discovery
rate
22
. To assess the additional genotype influence on the ability to discriminate between patients
with and without stenosis, we used only the statistically significant compound genotypes variables
and entered them in the developed multivariate logistic regression model. The results were plotted
as an ROC curve and the AUC was calculated.
Jürgens M et al. Fistulas as predictor of stricturing Crohn’s disease
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Supplemental Table 1. Demographic characteristics of the patient population of the retrospective
and prospective study.
Retrospective data analysis
Prospective data analysis
n=333
n=42
Female
172 (51.7%)
20 (47.6%)
Male
161 (48.3%)
22 (52.4%)
Mean ± SD
40.9 ±12.7
38.5 ± 12.3
Range
15 – 75
20 – 65
(years)
28.0 ± 11.9
29.3 ± 12.1
Mean ± SD
6 – 71
15 – 65
(years)
12.2 ± 8.6
15.1 ± 10.4
Mean ± SD
0.5 – 44
0 – 41
Mean ± SD
23.1 ± 4.0
23.7 ± 3.7
Range
15.6 - 39.4
17.0 - 31.9
Gender (%)
Age (years)
Age at diagnosis
Range
Disease duration
Range
BMI (kg/m2)
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Supplemental Table 2. Fistula distribution and concomitant stenosis stratified for the anatomic
region of fistula formation for both the retrospective and the prospective study. Considering that
some patients had concomitantly fistulas in several anatomic regions, the total number of fistulas
was higher than the number of patients.
Retrospective analysis
Prospective analysis
Combined analysis
(retrospective and
prospective study)
Fistulas
Conco-
Fistulas
Conco-
Fistulas
Conco-
mitant
mitant
mitant
stenoses
stenoses
stenoses
Perianal
n=49
67.4%
n=20
75.0%
n=69
69.6%
Entero-
n=78
94.9%
n=19
94.7%
n=97
94.8%
n=6
66.7%
n=2
100.0%
n=8
75.0%
n=10
80.0%
n=1
100.0%
n=11
81.8%
n=18
94.4%
n=2
100.0%
n=20
95.0%
n=161*
84.5%
n=44*
86.4%
n=205*
84.9%
enteral
Enterovaginal
Enterovesical
Enterocutaneous
Total
*Analyzed were 161 fistulas in 145 different patients in the retrospective study and 44 fistulas in 42
patients in the prospective study.
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Supplemental Table 3. In patients with fistulas and stenosis, fistulas were stratified for
“symptomatic” and “asymptomatic” fistulas and the time of the diagnosis of fistula compared to the
date of diagnosis of stenosis. This table contains n=120 patients (n=48 with “symptomatic” fistulas,
n=72 with “asymptomatic” fistulas) out of the group of 125 patients with fistulas and stenosis for
which exact time information on the diagnosis of fistulas and stenosis was available.
“Symptomatic”
“Asymptomatic”
fistulas
fistulas
(perianal, entero-
(entero-enteral)
cutaneous, entero-
n=72
p-value
vesical, enterovaginal)
n=48
Diagnosis of fistulas prior to
12 / 48
3 / 72
diagnosis of stenosis
(25.0%)
(4.2%)
Diagnosis of fistulas at time of
24 / 48
58 / 72
diagnosis of stenosis
(50.0%)
(80.6%)
Diagnosis of fistulas after the
12 / 48
11 / 72
diagnosis of stenosis
(25.0%)
(15.2%)
0.0012
0.0006
0.2375
Jürgens M et al. Fistulas as predictor of stricturing Crohn’s disease
Supplemental Table 4. Disease localization
7
6
of the patients of the retrospective study. This
analysis includes all patients of the retrospective study with complete information on their disease
localization based on endoscopic and radiological methods (n=86 patients without fistulas and
stenosis; n=19 with fistulas and without stenosis; n=125 with fistulas and stenosis).
Disease localization
(1)
(2)
(3)
p-value
p-value
p-value
No
Fistulas,
Fistulas
(1) vs.
(1) vs.
(2) vs.
fistulas,
no
and
(2)
(3)
(3)
no
stenosis
stenosis
n=86
n=19
n=125
L1
16 / 86
1 / 19
19 / 125
0.2986
0.5373
0.4373
Terminal ileum
(18.6%)
(5.2%)
(15.2%)
L2
14 / 86
9 / 19
12 / 125
0.0058
0.2003
0.0002
Colon
(16.3%)
(47.4%)
(9.6%)
L3
52 / 86
9 / 19
92 / 125
0.3156
0.0510
0.0299
Ileocolon
(60.5%)
(47.4%)
(73.6%)
L4
4 / 86
0 / 19
2 / 125
1.0000
0.2967
0.4865
Upper GI
(4.7%)
(0.0%)
(1.6%)
stenosis
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Supplemental Table 5. Immunosuppressive and immunomodulatory treatment in the study
population. The data are presented for n=231 CD patients of the retrospective study which had
complete information on their medical treatment available. *In this subgroup, information on
immunosuppressive therapy was available only in 18 patients, data on immunomodulatory agents
were available in 19 patients.
(1)
(2)
(3)
p-value
p-value
p-value
No
Fistulas,
Fistulas
(1) vs.
(1) vs.
(2) vs.
fistulas,
No
and
(2)
(3)
(3)
no
stenosis
stenosis
n=87
n=19*
n=125
agents (Aza, 6-MP
61 / 87
17 / 18*
118
0.0374
<0.0001
1.0000
or MTX)
(70.1%)
(94.4%)
(94.4%)
(infliximab,
22 / 87
10 / 19*
60
0.0271
0.0010
0.8072
adalimumab or
(25.3%)
(52.6%)
(48.0%)
stenosis
Immunosuppressive
Anti-TNF agents
certolizumab)
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Supplemental Table 6. Distribution of CD-associated NOD2/CARD15 genotypes in stricturing and
non-stricturing CD
Genotype (%)
NOD2 SNP
-/-
+/-
+/+
p-value
(Fisher's exact
test)
1007fs
Stenosis-
93 (35.1)
17 (34.7)
0 (0.0)
172 (64.9)
32 (65.3)
19 (100)
86 (31.3)
23 (43.4)
1 (20.0)
189 (68.7)
30 (56.6)
4 (80.0)
103 (33.9)
7 (25.0)
0 (0.0)
201 (66.1)
21 (75.0)
1 (100)
64 (33.2)
43 (43.0)
3* (7.5)
129 (66.8)
57 (57.0)
37**(92.5)
0.0018
(n=110)
Stenosis+
(n=223)
R702W
Stenosis-
0.19
(n=110)
Stenosis+
(n=223)
G908R
Stenosis-
0.60
(n=110)
Stenosis+
(n=223)
NOD2/CARD15
Stenosis(n=110)
Stenosis+
(n=223)
0.00097
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*This number represents 1 patient homozygous for one of the 3 CD-associated NOD2 variants and
2 compound heterozygous patients.
** This number represents 24 patients homozygous for one of the 3 CD-associated NOD2 variants
and 13 compound heterozygous patients. The distribution of each genotype regarding the
presence of stenosis (+: stenosis present; -: stenosis absent) is given in brackets.
-/-: wild-type; +/-: heterozygous; +/+: homozygous for the minor allele.
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Supplemental Table 7. Distribution of CD-associated IL23R genotypes dependent on the
presence of stenosis in the patients analyzed in the retrospective study. The distribution of each
genotype regarding the presence of stenosis (+: stenosis present; -: stenosis absent) is given in
brackets. -/-: wild-type; +/-: heterozygous; +/+: homozygous for the minor allele.
Genotype (%)
IL23R SNP
-/-
+/-
+/+
p-value
(Fisher's
exact test)
rs1004819
Stenosis-
46 (34.6)
47 (29.7)
15 (41.7)
87 (65.4)
111 (70.3)
21 (58.3)
43 (33.1)
58 (34.7)
7 (23.3)
87 (66.9)
109 (65.3)
23 (76.7)
42 (33.1)
52 (32.7)
14 (34.2)
85 (66.9)
107 (67.3)
27 (65.8)
53 (36.5)
41 (28.1)
14 (38.9)
92 (63.5)
105 (71.9)
22 (61.1)
0.34
(n=108)
Stenosis+
(n=219)
rs7517847
Stenosis-
0.50
(n=108)
Stenosis+
(n=219)
rs10489629
Stenosis-
0.99
(n=108)
Stenosis+
(n=219)
rs2201841
Stenosis(n=108)
Stenosis+
(n=219)
0.22
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rs11465804
Stenosis-
99 (31.8)
9 (56.2)
0 (0.0)
212 (68.2)
7 (43.8)
0 (0.0)
97 (31.6)
11 (55.0)
0 (0.0)
210 (68.4)
9 (45.0)
0 (0.0)
57 (32.9)
43 (33.6)
8 (30.8)
116 (67.1)
85 (66.4)
18 (69.2)
55 (37.2)
39 (27.5)
14 (37.8)
93 (62.8)
103 (72.5)
23 (62.2)
45 (33.6)
47 (30.7)
16 (40.0)
89 (66.4)
106 (69.3)
24 (60.0)
27 (32.1)
54 (32.9)
27 (34.2)
0.056
(n=108)
Stenosis+
(n=219)
rs11209026/
R381Q
Stenosis-
0.047
(n=108)
Stenosis+
(n=219)
rs1343151
Stenosis-
1.00
(n=108)
Stenosis+
(n=219)
rs10889677
Stenosis-
0.17
(n=108)
Stenosis+
(n=219)
rs11209032
Stenosis-
0.50
(n=108)
Stenosis+
(n=219)
rs1495965
Stenosis-
0.98
Jürgens M et al. Fistulas as predictor of stricturing Crohn’s disease
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(n=108)
Stenosis+
(n=219)
57 (67.9)
110 (67.1)
52 (65.8)