## Abstract

Inflammatory bowel disease (IBD), which encompasses Crohn's disease and ulcerative colitis, affects approximately nine in 100,000 children and adolescents (Lindberg, Lindquist, Holmquist, & Hildebrand, 2000). It is characterized by chronic, intermittent, and unpredictable inflammation of the gastrointestinal tract resulting in symptoms such as recurrent diarrhea, abdominal pain, fatigue, arthritis, growth delay, delayed puberty, and perianal disease (Drossman & Ringel 2003; Mackner & Crandall, 2006). Depending on presenting symptoms, severity of illness, and individual patient's disease course, treatment can involve multiple medications with varying regimens, infusions, dietary changes, and surgery. Medications used in this population may produce undesirable side effects including weight gain, cushingoid appearance, osteopenia/osteoporosis, pancreatitis, immune suppression, and increased risk of cancer (Mackner, Sisson, & Crandall, 2004). IBD patients are often prescribed immunomodulators such as 6-mercaptopurine (6-MP; or azathioprine, which is cleaved to 6-MP) and/or anti-inflammatory agents such as 5-aminosalicylic acid (5-ASA), which have considerably different dosing schedules. Whereas 6-MP/azathioprine dosing is usually once daily with ∼1–2 pills, 5-ASA dosing is often three times daily with up to ∼4–6 pills each dose. Patients may also experience changes in dosing depending on their response to treatment. Given the complex treatment regimens these patients are often prescribed, it is plausible that this population experiences difficulty adhering to treatment regimens.

In an effort to address the aforementioned limitations in the extant research, this cross-sectional study was designed to examine the relationship between medication adherence and both patient and parent ratings of QOL in pediatric IBD, using data from an ongoing longitudinal study. Additionally, this study provides preliminary data on adherence rates in this population using a multimodal adherence assessment method. This assessment approach was chosen because no one measure has been shown to accurately assess adherence in IBD. It was hypothesized that adherence to medication would predict higher patient- and parent-reported QOL and, conversely, nonadherence would predict lower patient- and parent-reported QOL after statistically controlling demographic and behavioral parameters on QOL.

## Method

### Participants

Inclusion criteria were: (a) diagnosis of Crohn's disease or ulcerative colitis, (b) 13–17 years of age, (c) prescribed 6-MP/azatinoprine and 5-ASA, (d) 6-TGN assay during the previous month, and (e) English fluency; exclusion criteria were: (a) developmental delay, (b) prescribed >1 mg/kg/d corticosteroids, and (c) comorbid chronic illness. Two hundred seventy-one patients were screened for eligibility, and 48 patients met criteria; eight were never reached for recruitment; and four declined participation. A convenience sample of 36 adolescents (22 male, 14 female; M age = 15.69 years, SD = 1.37 years) with IBD and their parents served as participants. Families were recruited from a gastroenterology clinic in a large children's hospital in the northeastern United States. Average income was $120,056 (SD =$61,727.86). The sample was 85% Caucasian, 11% African American, and 4% Hispanic. Demographics of this sample were representative of the clinic population with respect to race, gender, and income.

### Measures

A demographic questionnaire assessing family income, parental age, marital status, parental education, and number of family members in the home was completed by parents.

#### 6-thioguanine Nucleotide (6-TGN) Assay

6-TGN (i.e., 6-MP metabolite) assays measure 6-TGN concentration in blood; this served as a biological proxy measure of adherence to 6-MP/azathioprine. 6-TGN levels have been used in prior research to measure adherence to 6-MP/azathioprine in IBD patients (Belaiche, Desager, Horsmans, & Louis, 2001; Cuffari, Seidman, Latour, & Theoret, 1996). Thiopurine methyltransferase (TPMT), which is an enzyme that catalyzes 6-MP/azathioprine to production of methylated mercaptopurines (6-MMP), was tested for each patient prior to treatment initiation to determine appropriate dosing. Therapeutic 6-TGN levels range from 230 to 400 pmol; values below 230 pmol were considered indicative of nonadherence for this study.

The MAM (Zelikovsky, in press) is a semi-structured interview conducted with patients and parents that quantifies medication adherence. Adherence scores range from 0 to 100%; <80% of medications taken was used as the cutoff for nonadherence in this study. Patients and parents were interviewed together in this study, and percentage of doses taken was used as the measure of adherence to both 6-MP/azathioprine and 5-ASA. The MAM has demonstrated adequate convergent validity (r = −.40, p <.05) and test–retest reliability (r =.89, p <.05; Zelikovsky, 2007).

#### Pill Counts

Pill counts of all medication prescribed to each patient were conducted. Patients and parents reported number of pills remaining in bottles and other containers (e.g., pill boxes) for each medication, prescription instructions, date prescription was filled, and quantity filled. Adherence to both 6-MP/azathioprine and 5-ASA was calculated as percentage of doses removed/doses prescribed × 100.

#### Pediatric Crohn's Disease Activity Index (PCDAI)

The PCDAI (Hyams et al., 1991) is a well-validated assessment of disease activity in pediatric patients with Crohn's disease. The scale is scored 0–100 based on subjective criteria (e.g., pain), objective criteria (e.g., physical exam), laboratory findings, and growth parameters. Scores <15, inactive disease; 15–30, mild to moderate disease; and >30, severe disease activity (Otley et al., 1999). Internal consistency (Cronbach, 1951) was.83 in this sample.

#### Lichtiger Colitis Activity Index (CAI)

The CAI (Lichtiger et al., 1994) is scored 0–21, with higher scores representing more severe disease. It is assessed across eight ulcerative colitis symptoms. Internal consistency was.87 in this sample.

#### Pediatric Quality of Life Inventory (PedsQL 4.0)

The PedsQL 4.0 (Varni, Seid, & Rode, 1999) is a 23-item measure that evaluates children's QOL across four areas of functioning: physical, emotional, social, and school. Items are reverse scored and transformed to a 0–100 scale, with higher scores representing better QOL. The PedsQL 4.0 has both child- and parent-report forms and is used in children ages 2–18 years. Respondents rate how much of a problem each item has been during the past month on an anchored Likert scale. This measure yields a Total QOL score, two summary scores (i.e., Physical Health Summary Score and Psychological Health Summary Score), and three subscale scores (i.e., Emotional, Social, and School Functioning). The PedsQL 4.0 is a reliable (α child =.88, α parent =.90; Varni, Seid, & Kurtin, 2001) and valid measure of QOL. Internal consistency was.92 for Parent Report and.92 for Teen Report in this sample.

#### Children's Depression Inventory (CDI)

The CDI (Kovacs, 1992) is a 27-item self-report measure used to assess the severity of major depression symptomatology in children. Each item on the CDI is a group of three statements that combine to measure the severity of a single depressive symptom on a 0–2 scale. The CDI is a reliable (α from.71 to.89) and valid measure of depressive symptomatology in children (Kovacs, 1992). Internal consistency for this sample was.92.

### Procedure

This study was approved by the hospital Institutional Review Board. All recruitment and data collection was conducted by the principal investigator or a trained master's level research coordinator who were not members of the treatment team. Eligible patients and their parents were recruited via telephone. A thorough description of the study was provided and informed consent was obtained. Patients and parents provided information for pill counts, and the MAM interview was conducted via telephone; participants were told their responses would not be shared with the treatment team. Disease and medication regimen information and 6-TGN data were obtained via medical chart review. Demographic and behavioral measures were mailed to participants. Each patient's gastroenterologist provided information for disease severity assessments in patients’ chart notes, and this data was obtained and recorded by study personnel. Participants were mailed \$25 gift cards for compensation.

### Data Analyses

PCDAI and CAI scores were combined into one variable representing disease severity. The rationale for this was that the majority of the sample demonstrated mild to moderate or better disease severity and both measures yield continuous scores appropriate for correlational analyses. Descriptive statistics (i.e., M, SD, percentages) were conducted on demographic, disease related, and behavioral study variables. Subsequently, independent samples t-test and bivariate correlations were performed to identify potential covariates for primary analyses. Finally, hierarchical multiple regression analyses examining the contribution of adherence to patient QOL were conducted in order to test the primary hypothesis.

## Results

### Preliminary Analyses

Disease related and behavioral descriptive data are presented in Table I. Based on a raw score cutoff of 13 or higher on the CDI (Timbremont, Braet, & Dreessen, 2004), 18.5% of the sample demonstrated clinically elevated levels of depression. Independent samples t-tests and bivariate correlations were conducted to identify potential covariates for the primary regression analyses. Results revealed no significant differences between male and female participants on 5-ASA/6-MP-azathioprine pill count, 5-ASA/6-MP MAM, or 6-TGN measures of adherence (p >.05) or on PedsQL 4.0 Teen or Parent Report (p >.05). Significant correlations between PedsQL 4.0 Parent Report and both CDI depressive symptoms (r = −.75, p <.01) and patient age (r = −.48, p <.05) were observed. There was also a significant correlation between PedsQL 4.0 Teen Report and CDI depressive symptoms (r = −.77, p <.01), 6-TGN adherence (r =.40, p <.05) and 5-ASA MAM adherence (r = −.56, p <.01). Pill count adherence scores for 6-MP and 5-ASA were not significantly correlated with Parent or Teen reported QOL. No significant correlations were observed between measures of adherence and depressive symptomatology, age, or disease severity, and disease severity was not significantly correlated with QOL. Variables significantly correlated (i.e., age and CDI depressive symptoms) with either Parent or Teen Report QOL were entered into the primary regression analyses; variables not significantly correlated with Parent or Teen Report QOL were not entered.

Table I.

Descriptive Data for Disease Related and Behavioral Variables

Variable M Mdn SD Percentage
IBD diagnosis
Crohn's disease    86.1%
Ulcerative colitis    13.9%
CAI score 4.20 5.85
PCDAI score 11.37 10.00 9.83
Inactive disease (<15)    71.0%
Mild to moderate disease (15–30)    22.5%
Severe disease (>30)    6.5%
6-MP
Prescribed daily dose 1.49 1.50 0.74
Pill count adherence 62.62% 64.20% 23.42%
6-TGN level 163.22a 151.00a 107.54
5-ASA
Prescribed daily dose 9.11 9.00 2.76
Pill count adherence 51.56% 51.39% 25.24%
PedsQL 4.0 Parent Report for Teens
Total Score 82.69 86.96 13.48
Physical Health Summary Score 86.23 93.75 12.92
Emotional Functioning Subscale 77.41 75.00 20.40
Social Functioning Subscale 86.67 95.00 15.99
School Functioning Subscale 78.33 85.00 17.87
Psychological Health Summary Score 80.80 88.33 15.56
PedsQL 4.0 Teen Report
Total Score 79.59 79.35 14.32
Physical Health Summary Score 82.75 84.38 13.10
Emotional Functioning Subscale 76.30 85.00 19.34
Social Functioning Subscale 84.26 85.00 16.74
School Functioning Subscale 73.15 80.00 21.40
Psychological Health Summary Score 77.90 81.67 17.02
CDI Total Score 6.70 4.00 7.43
Variable M Mdn SD Percentage
IBD diagnosis
Crohn's disease    86.1%
Ulcerative colitis    13.9%
CAI score 4.20 5.85
PCDAI score 11.37 10.00 9.83
Inactive disease (<15)    71.0%
Mild to moderate disease (15–30)    22.5%
Severe disease (>30)    6.5%
6-MP
Prescribed daily dose 1.49 1.50 0.74
Pill count adherence 62.62% 64.20% 23.42%
6-TGN level 163.22a 151.00a 107.54
5-ASA
Prescribed daily dose 9.11 9.00 2.76
Pill count adherence 51.56% 51.39% 25.24%
PedsQL 4.0 Parent Report for Teens
Total Score 82.69 86.96 13.48
Physical Health Summary Score 86.23 93.75 12.92
Emotional Functioning Subscale 77.41 75.00 20.40
Social Functioning Subscale 86.67 95.00 15.99
School Functioning Subscale 78.33 85.00 17.87
Psychological Health Summary Score 80.80 88.33 15.56
PedsQL 4.0 Teen Report
Total Score 79.59 79.35 14.32
Physical Health Summary Score 82.75 84.38 13.10
Emotional Functioning Subscale 76.30 85.00 19.34
Social Functioning Subscale 84.26 85.00 16.74
School Functioning Subscale 73.15 80.00 21.40
Psychological Health Summary Score 77.90 81.67 17.02
CDI Total Score 6.70 4.00 7.43

a80.56% of sample at sub-therapeutic level.

### Primary Analyses

Two hierarchical multiple regression equations were constructed to test the primary hypothesis. On Step 1 of each equation, age and CDI total score were entered, followed by 6-TGN adherence, 6-MP MAM adherence, and 5-ASA MAM adherence on Step 2. Parent Report Total QOL and Teen Report Total QOL served as the dependent variables for the two regression equations. Results of the first regression revealed that 6-TGN adherence, 6-MP MAM adherence, and 5-ASA MAM adherence contributed nonsignificant variance to Parent Report Total QOL (F change =.76, p >.05). In contrast, the second regression revealed that these three measures of adherence contributed a significant 19% of unique variance to Teen Report Total QOL after statistically controlling the significant variance accounted for by age and CDI depressive symptomatology (F change = 5.06, p <.01; see Table II).

Table II.

Multiple Regression Analyses Examining the Contribution of Adherence to QOL

Analyses Step Variables β t for within step predictors R2 change for step F Change
Primary
Equation 1 (DV = PedsQL 4.0 Parent Report Total Score)
Age −.35 −2.82* .65 21.16**
CDI Total Score −.67 −5.32**
6-TGN Adherence .05 .36 .04 .76
Equation 2 (DV = PedsQL 4.0 Teen Report Total Score)
Age .02 .16 .55 14.18**
CDI Total Score −.75 −5.28**
6-TGN Adherence .22 1.81 .19 5.06*
Exploratory
Equation 3 (DV = PedsQL 4.0 Physical Health Summary Score)
Age −.18 −.91 .14 1.80
CDI Total Score −.29 −1.49
6-TGN Adherence .41 2.27* .30 3.48*
Equation 4 (DV = PedsQL 4.0 Emotional Functioning Subscale Score)
Age .05 .35 .64 20.17**
CDI Total Score −.80 −6.31**
6-TGN Adherence .01 .05 .03 .63
Equation 5 (DV = PedsQL 4.0 Social Functioning Subscale Score)
Age .18 1.25 .54 13.29**
CDI Total Score −.74 −5.14**
6-TGN Adherence .12 1.01 .21 5.43**
Equation 6 (DV = PedsQL 4.0 School Functioning Subscale Score)
Age .06 .41 .48 10.54**
CDI Total Score −.70 −4.58**
6-TGN Adherence .16 1.11 .14 2.42
Equation 7 (DV = PedsQL 4.0 Psychological Health Summary Score)
Age .10 .88 .69 25.20**
CDI Total Score −.84 −7.09**
6-TGN Adherence .11 1.08 .13 4.77*
Analyses Step Variables β t for within step predictors R2 change for step F Change
Primary
Equation 1 (DV = PedsQL 4.0 Parent Report Total Score)
Age −.35 −2.82* .65 21.16**
CDI Total Score −.67 −5.32**
6-TGN Adherence .05 .36 .04 .76
Equation 2 (DV = PedsQL 4.0 Teen Report Total Score)
Age .02 .16 .55 14.18**
CDI Total Score −.75 −5.28**
6-TGN Adherence .22 1.81 .19 5.06*
Exploratory
Equation 3 (DV = PedsQL 4.0 Physical Health Summary Score)
Age −.18 −.91 .14 1.80
CDI Total Score −.29 −1.49
6-TGN Adherence .41 2.27* .30 3.48*
Equation 4 (DV = PedsQL 4.0 Emotional Functioning Subscale Score)
Age .05 .35 .64 20.17**
CDI Total Score −.80 −6.31**
6-TGN Adherence .01 .05 .03 .63
Equation 5 (DV = PedsQL 4.0 Social Functioning Subscale Score)
Age .18 1.25 .54 13.29**
CDI Total Score −.74 −5.14**
6-TGN Adherence .12 1.01 .21 5.43**
Equation 6 (DV = PedsQL 4.0 School Functioning Subscale Score)
Age .06 .41 .48 10.54**
CDI Total Score −.70 −4.58**
6-TGN Adherence .16 1.11 .14 2.42
Equation 7 (DV = PedsQL 4.0 Psychological Health Summary Score)
Age .10 .88 .69 25.20**
CDI Total Score −.84 −7.09**
6-TGN Adherence .11 1.08 .13 4.77*

*p <.05; **p <.01.

### Exploratory Analyses

In order to gain a better understanding of how adherence might be specifically related to different aspects of patient-reported QOL in this population, subsequent regression analyses were performed to examine the relationship between adherence and Teen Report PedsQL 4.0 subscale and summary scores. Regression equations were constructed in the same manner as for the primary analyses. Results revealed nonsignificant contributions of 6-TGN adherence, 6-MP MAM adherence, and 5-ASA MAM adherence to variance in the School and Emotional Functioning subscales (F change = 2.42 and 0.63, respectively, p's >.05). In contrast, 6-TGN adherence significantly predicted variance in the Physical Health Summary Score (t = 2.27, p <.05), and 5-ASA MAM adherence predicted significant variance in the Psychological Health Summary Score (t = −2.97, p <.01). Moreover, within the Psychological Health Summary Score, only the Social Functioning subscale (t = −3.22, p <.01) was significantly predicted by 5-ASA MAM adherence. Finally, 6-MP MAM adherence was a nonsignificant predictor (Table II).

## Discussion

Although adherence and parent-reported QOL were not correlated, results partially supported the primary hypothesis in that 6-MP/azathioprine nonadherence as measured by sub-therapeutic 6-TGN levels was significantly related to poorer patient-reported physical health QOL. This is plausible given that one might expect that nonadherence to result in poorer disease functioning and, consequently, poorer physical health perceptions. Disease severity in this sample was primarily mild to moderate or better, and disease severity was not related to the PedsQL 4.0 Total score. However, compared with other subscales on the PedsQL 4.0 the Physical Health Summary Score might be particularly sensitive to significant nonadherence in this population, which would explain why the measure resulting in the highest estimates of nonadherence in this study (i.e., 6-TGN assays) was the only measure related to physical health QOL. Nevertheless, this issue warrants further investigation.

The inverse relationship between self-report adherence and QOL is supported by a recent study in children with sickle cell disease (Barakat, Lutz, Smith-Whitley, & Ohene-Frempong, 2005), which examined provider and parent estimates of adherence and found that greater adherence was significantly related to poorer overall QOL. The authors speculated that socioeconomic status (SES), volitional nonadherence, and interference in activities due to treatment adherence might have accounted for the inverse relationship. Given the middle to upper middle class SES of our sample, it is unlikely that SES played a role in the current findings. Volitional nonadherence might have influenced these results; however, this was not specifically assessed. Yet, similar to the sickle cell sample, our patients might have experienced disruption in desired activities resulting from dosing schedules involving multiple pills and doses per day. Although speculative, it is plausible that patients perceive adherence to medical regimens as burdensome to some extent, resulting in poorer patient QOL. This is consistent with an inverse relationship between routine burden and QOL reported in asthma patients (Fiese, Wamboldt, & Anbar, 2004).

Another important observation of this study concerns the use of a multimethod adherence assessment approach. Use of this methodology is exploratory at this stage in adherence research, but such an approach has merit. For example, use of this method in the present study highlights the potential variation in adherence measures and might reveal subtle yet salient relationships between adherence and disease outcomes such as QOL that could go unnoticed with unimodal adherence assessment. Clearly, this methodology warrants further utilization to determine which measures and combinations of measures best represents patient adherence and concomitant disease outcomes.

This preliminary study is limited by the modest sample size, which precludes broad generalization. In addition, although the SES of this sample is similar to other recent research in pediatric IBD (Mackner & Crandall, 2005), it might not represent the IBD population in general. However, it is possible that SES of the IBD population is negatively skewed compared with other disease populations, as IBD primarily afflicts Caucasians (CCFA, 2008). Nevertheless, this must be considered when interpreting these findings. Also, the current study did not include electronic monitoring of adherence, which can provide considerable details about adherence behavior (e.g., timing and frequency of presumed consumption) that other measures cannot (Rapoff, 1999). However, this study utilized a multimethod assessment approach comprised of measures that are more likely to be used in actual clinical settings. Finally, 6-TGN levels are limited as adherence indicators as they are subject to pharmacokinetic variation and drug metabolism in patients. Further, TPMT activity and liver functioning tests were not conducted simultaneously with 6-TGN assays to examine potential pharmacokinetic interference. These factors might help explain the high percentage of participants who exhibited subtherapeutic 6-TGN values, though this is speculative given that the extent to which TMPT activity interferes with 6-TGN metabolite measurement has not been empirically examined. Results of 6-TGN values as adherence markers must be taken with considerable caution given that this measure quantifies concentration of only one 6-MP/azathioprine metabolite in blood, and does not quantify actual pill consumption.

Although clinical implications from this preliminary data would be premature, providers and patients might benefit from discussing the potential impact of patients’ treatment regimens on overall functioning. Future replication is needed in larger samples utilizing longitudinal designs to determine directionality and stability of the findings in this study. In addition, multimethod adherence assessment should be examined in future studies to examine the efficacy of particular measures or combination of measures in assessing adherence in this population. Issues pertaining to adherence burden should also be examined in relation to various medications and dosing schedules. Finally, the impact of adherence/nonadherence on disease outcomes should continue to be a focus of research in order to better understand the impact of this disease management behavior on patient well being.

## Acknowledgments

Funding for this study was provided by Procter and Gamble Pharmaceuticals and Prometheus Laboratories. We extend our sincere appreciation to the families who devoted their time to participate in this research and the physicians with whom we collaborated.

Conflicts of interest: None declared.

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