Journal of Pediatric Gastroenterology & Nutrition:
Original Articles: Hepatology and Nutrition
Evaluation of Stool Collections to Measure Efficacy of PERT in Subjects With Exocrine Pancreatic Insufficiency
Caras, Steve*; Boyd, David*; Zipfel, Lisa*; Sander-Struckmeier, Suntje†
*Abbott Products Inc, Marietta, GA
†Abbott Products GmbH, Hannover, Germany.
Address correspondence and reprint requests to Suntje Sander-Struckmeier, Abbott Products GmbH, Hans-Böckler-Allee 20, 30173 Hannover, Germany (e-mail: firstname.lastname@example.org).
Received 4 November, 2010
Accepted 7 June, 2011
This work was funded by Abbott Products Inc, Marietta, GA.
ClinicalTrials.gov number: NCT00690820.
S.C., D.B., and L.Z. were employees of Abbott, Marietta, GA, at the time of this analysis and writing of the manuscript. S.S.S. is an employee of Abbott, Hannover, Germany.
Objective: The standard measure of pancreatic enzyme replacement therapy (PERT) efficacy in treating exocrine pancreatic insufficiency (EPI) is the coefficient of fat absorption (CFA). CFA measurement involves 72-hour stool collection, which presents a logistical challenge because, although the test may be performed on an outpatient basis in clinical practice, hospitalization is needed if assurance of complete collection and 100% compliance is required, for example, in controlled situations such as clinical trials. Our aim was to investigate sparse stool sample collection as an alternative to complete 72-hour collection for measurement of stool fat in subjects with EPI.
Subjects and Methods: Prospective data analysis from a previously published, double-blind, randomized, placebo-controlled, 2-period crossover trial in subjects ages 7 to 11 years with EPI caused by cystic fibrosis. Percentage fat (PF) data from sparse stool samples were compared with 72-hour CFA values as a dichotomous variable (<80%, ≥80%), with evaluation of sensitivity, specificity, and positive predictive value. Area under the curve values were obtained from receiver operating characteristic plots of sensitivity versus 1–specificity.
Results: Twelve subjects provided samples for this analysis. Multiple-sample PF values ≤30% were greatly predictive for CFA values ≥80%, as shown by positive predictive value, sensitivity, and specificity values ≥0.89, with high accuracy (AUCs ≥0.93).
Conclusions: Sparse stool sampling for PF analysis appears to be a valid, practical alternative to 72-hour CFA determination and has potential as a screening tool in clinical practice to identify both suboptimal dosing in subjects with EPI receiving PERT and substantial fat malabsorption in subjects not receiving PERT.
Exocrine pancreatic insufficiency (EPI) is a lack of pancreatic digestive enzymes, which causes maldigestion that in turn leads to malabsorption, and is often associated with diseases such as cystic fibrosis (CF) and chronic pancreatitis (1). Left untreated, EPI causes steatorrhea, abdominal distension and discomfort, and malnutrition (1,2). Pancreatic enzyme replacement therapy (PERT) has been in clinical use for many years and is essential for the treatment of EPI. The aim of PERT is to achieve normal digestion, thus reducing malabsorption and maintaining adequate nutrition (1).
The efficacy and safety of PERT for the treatment of EPI in adult and pediatric subjects has been shown in randomized placebo-controlled trials (3–8) and in open-label studies (8–11). The key measure of PERT efficacy in all but 1 (10) of these studies was the coefficient of fat absorption (CFA) (12), which is considered the criterion standard for the diagnosis of fat maldigestion (13) and an indirect test of pancreatic function (14). The CFA is calculated from fat intake and stool fat output data collected during a 72-hour period. The 72-hour CFA test is expensive (15), not well tolerated by subjects or laboratory personnel (14), and presents a logistical challenge in clinical studies because hospitalization is required to ensure complete stool collection and a complete record of dietary fat intake (13). In addition, subjects with EPI often experience diarrhea, making accurate and complete stool collection difficult, particularly in young children (13). Although the CFA is a useful tool if carried out correctly, these drawbacks make the CFA a challenging test with high potential for errors and impractical in the clinical setting. Despite these difficulties, it should be noted that the CFA test is routinely performed on an outpatient basis in clinical practice outside the clinical trial setting.
There is considerable interest in developing easier to perform, accurate tests of fat malabsorption and pancreatic function for use in routine clinical practice and clinical trials. Fat malabsorption is frequently measured by assessing stool fat content, which is often determined using the method of Van de Kamer (15–17). Alternative methods of measuring fat malabsorption based on the fat content of stool samples include the steatocrit (15,18,19) and acid steatocrit (15,20–23) fecal fat estimation methods and microscopic examination of stool for fat globules (24,25). Tests that measure other parameters as a marker for EPI include the 14C-triolein (26) and the 13C-mixed triglyceride (27) breath tests, determination of pancreas-specific enzymes (eg, fecal elastase-1) (28), and measurement of serum enzymes (eg, immunoreactive trypsinogen) (14). The use of nonabsorbable lipid markers such as dysprosium chloride (29) and fecal lauric/behenic acid (13) has also been investigated. It should be noted that not all of the aforementioned methods require stool samples for analysis. Data from some of these studies were encouraging for the use of these tests as diagnostic markers for detecting the presence/absence of EPI.
In addition to developing novel techniques for establishing the extent of EPI, there is a need to investigate new stool sampling methods as an alternative to the 72-hour stool collection required to calculate the CFA (12), which is impractical in routine clinical practice. We aimed to investigate the suitability and clinical utility of collecting sparse stool samples for fat determination as an alternative to complete 72-hour collection and measurement of CFA in subjects with EPI caused by CF. To investigate this premise, data were analyzed from a double-blind, randomized, placebo-controlled, 2-period crossover trial of enteric-coated pancrelipase (pancreatin) delayed-release 12,000-lipase unit capsules (CREON; Abbott, Marietta, GA) in subjects ages 7 to 11 years with EPI caused by CF (6) performed at 10 centers across the United States between June 13, 2008 and December 1, 2008. Stool samples collected were analyzed for fat as a percentage of dry weight (percentage fat [PF]) using 4 different sampling methods and were then compared with 72-hour CFA data also collected.
SUBJECTS AND METHODS
Approval of the study was given by the institutional review board/independent ethics committee at each site. The study design for the clinical trial is shown in Figure 1. Briefly, subjects were randomized to 1 of 2 treatment sequences for a period of 5 days: pancrelipase then placebo, or placebo then pancrelipase, with a washout interval of 3 to 14 days between their usual PERT.
Subjects ages 7 to 11 years who had a confirmed diagnosis of CF and EPI were enrolled in the study. Full inclusion/exclusion criteria were described elsewhere (6). Although the primary endpoint was CFA, informed consent was also given to permit the measurement of PF in individual bowel movements for the analysis reported here.
The subjects received 12,000-lipase unit pancrelipase delayed-release capsules. The correct number of capsules to be consumed was calculated to provide a target dose of 4000 lipase units/gram of dietary fat intake according to the upper limit of the recommendation of CF consensus statements (30–32). Each subject received an individualized, prospectively designed diet to maintain normal nutrition, containing at least 40% of energy derived from fat.
Subjects were administered 2 doses of blue food dye (250 mg of FD and C Blue #2 indigo carmine) 72 hours apart to mark the beginning and end of the stool collections, which were performed during both crossover periods. Stool collection began after passage of the first blue-stained bowel movement and ended with passage of the second marker. Bowel movements were collected individually to facilitate determination of the PF in each sample.
Determination of CFA
For the calculation of CFA, 50% of each homogenized bowel movement collected in a treatment period was combined for each subject to allow determination of total stool fat excretion by the titrimetric method of Van de Kamer (16). For each treatment period, the CFA was calculated from the known fat intake and the fat excreted in the combined stool samples collected, according to the following equation:
Equation (Uncited)Image Tools
Total daily fat intake was determined from each subject's dietary intake, which was recorded in dietary diaries in the stool collection periods.
Determination of PF and Sampling Methods
Individual stool samples were analyzed for fat content by removing a 5-g aliquot from the remaining 50% of each homogenized bowel movement. Therefore, PF sampling did not affect the CFA determination. In these samples, stool fat was determined by nuclear magnetic resonance (NMR) methods and the PF was calculated based on the dry weight of each bowel movement (33).
PF values for each subject were derived using 4 different sparse-sample methods (3 multiple-sample methods and 1 single-sample method): mean PF from the first bowel movement on each day; mean PF from the last bowel movement on each day; mean PF from 3 randomly selected bowel movements, each on a different day; and PF from a single random sample selected irrespective of day (Fig. 2).
The strategy for the data analysis reported here is summarized in Figure 2. The PF values were compared with CFA as a dichotomous variable using a CFA cutoff value of 80% because a CFA value <80% is generally considered to indicate the presence of substantial fat malabsorption (34). In addition, analyses were performed to evaluate the correlation between PF and CFA as a continuous variable based on 3 groups of samples: pancrelipase, placebo, and both combined.
The comparison of PF with CFA as a dichotomous variable (CFA <80% vs CFA ≥80%) included evaluation of sensitivity, specificity, and positive predictive value (PPV). Area under the curve (AUC) values (1 = 100% accuracy) were obtained from receiver operating characteristic (ROC) curves of sensitivity versus 1–specificity. The area under an ROC curve measures the ability of the test to differentiate between subjects with a specific condition and subjects without that condition. The closer the area is to 1.0, the better the test in identifying specificity (true positives) and sensitivity (true negatives) (35–37).
Separate Pearson and Spearman correlation analyses were performed to evaluate the association between PF and CFA as a continuous variable in the pancrelipase, placebo, and combined groups. Scatterplots were generated to determine whether a linear relation between PF and CFA existed.
The sample size for this exploratory analysis was based on the number of subjects enrolled in the clinical study who had sparse stool measurements. No sample size calculations were done for this specific analysis.
A total of 17 subjects were randomized in the clinical study (8 received placebo then pancrelipase, 9 received pancrelipase then placebo) (6). One subject (pancrelipase then placebo sequence) withdrew consent in the first treatment period; 16 subjects completed the study. The median age (range) was 8.0 (7–11) years, 12 (70.6%) were boys, and the mean daily lipase dose was 4472 U/g fat consumed (6).
Twelve subjects from 8 of the 10 centers provided samples for this analysis (10 in both treatment periods and 2 in only 1 period); the median age was 9.0 years, all subjects were of white race, and 9 (75.0%) were boys.
Comparison of PF With CFA as a Dichotomous Variable
The PPVs, sensitivity, and specificity for the comparison of PF values obtained using each of the 4 sparse stool sampling methods with the CFA as a dichotomous variable are shown in Table 1. For the 3 multiple-sample methods, PF values ≤30% were greatly predictive for CFA values ≥80%, as shown by PPV, sensitivity, and specificity values ≥0.89. ROC curves of sensitivity versus 1–specificity showed high accuracy (AUCs ≥0.93) for the multiple-sample methods (Fig. 3A–C). PPV and sensitivity values of 0.88 and 0.78, respectively, were lower at the 30% PF threshold for the single-sample method (Table 1) compared with the multiple-sample methods; an AUC of 0.91 in the ROC plot indicated slightly lower accuracy (Fig. 3D).
Comparison of PF With CFA as a Continuous Variable
Correlations of PF measurements derived from the 4 sparse stool sampling methods with CFA as a continuous variable are summarized in Table 2 and Figure 4. The scatterplots with confidence ellipses for the population mean show a negative linear or inverse relation between PF and CFA across all of the sampling methods, with higher variability in the combined-treatment groups (Fig. 4B, D, F, and H) than in the pancrelipase-only group (Fig. 4A, C, E, and G). Correlations between PF and CFA as a continuous variable were strong for the first and last bowel movement sampling methods, with statistically significant Pearson and Spearman values >0.81 for the pancrelipase and combined-treatment groups (P < 0.001; Table 2; Fig. 4A–D). Similar PF and CFA correlation results were obtained for the multiple random sampling method (Fig. 4E and F), although the Spearman correlation (−0.79; P = 0.002) was lower for the pancrelipase samples compared with the combined-treatment samples (Table 2). Correlations were generally lower for the single random bowel movement sampling method (Fig. 4G and H); however, they were statistically significant (P < 0.001) for the combined-treatment samples. PF and CFA correlations were generally not statistically significant for placebo samples (scatterplots not shown); however, Pearson P values for the last bowel movement sampling method (P = 0.04) and the random sampling method (P = 0.05) were significant (0.05 significance level).
The results of this analysis suggest that sparse stool sampling to measure PF may be a suitable alternative method to 72-hour stool collection and CFA calculation to determine whether CFA values are likely to be ≥80% in subjects with EPI. This sparse sampling method is a more convenient stool collection schedule than the 72-hour complete stool collection required for CFA determination and could be more readily applied in routine clinical practice and clinical trials, although assessment of this method in the routine clinical setting is required for confirmation.
In this sparse stool sampling analysis, PF values derived from the multiple-sample methods showed a significant predictive capability for CFA when compared with CFA as a dichotomous variable. PF values below a 30% threshold were greatly predictive for CFA values ≥80%, as shown by high PPV, sensitivity, and specificity values, with high accuracy. There were no relevant differences between the 3 multiple-sample methods tested, which were better than the single-sample method.
When PF values from the multiple-sampling methods were compared with CFA as a continuous variable, stronger correlations were observed for stool samples obtained during the pancrelipase treatment period compared with those collected during placebo treatment; however, when all of the samples were used without regard to treatment (combined group), the results were similar to those observed with the pancrelipase-only samples, despite the higher variability introduced by the placebo group. Although the single-sample method produced a statistically significant correlation in the combined-treatment group, correlations were generally weaker than with the multiple-sample methods. The weaker correlations in the placebo group for all of the sampling methods are most likely caused by the lack of homogeneity and greater variability in CFA values in this group. Ideally, the control group for this analysis would have been normal, healthy subjects. A larger sample also may reduce variability, yielding a more consistent relation between PF and CFA.
Two methods of stool fat determination were used in the present study. The Van de Kamer method (16) was applied to assess fat in stool samples from the 72-hour collection, the results of which were then used to calculate the CFA. The method used to determine PF in the sparse stool samples was the recently introduced 1H-NMR method (33), a rapid, convenient, accurate, and user-safe quantitation procedure. The choice of fat determination method was based on the type of data output generated by each technique. The Van de Kamer method is a wet chemistry technique that provides fat measurements in terms of grams of fat and is ideally suited to provide grams of fat data for input into the CFA calculation. The NMR method provides fat measurements in terms of percentage of dry weight and is therefore applicable to the sparse stool PF assessments. Other methods could be used to assess PF of sparse stool samples; however, the aim of the present study was not to compare methods of stool fat determination but to investigate different stool sampling methods.
In subjects receiving PERT for the treatment of EPI, assessment of the adequacy of treatment in the general clinical setting may be based on symptom severity; however, this may not accurately reflect control of fat malabsorption, particularly because subjects often experience diarrhea in addition to steatorrhea. A reliable and accurate method to assess easily the adequacy of PERT is therefore desired. Many tests of fat malabsorption have been proposed and investigated in the literature and some may be used as diagnostic tools for EPI (13–15,23,25–29). All of these methods have limitations that preclude their use in routine clinical practice for establishing the degree of EPI, and the 72-hour CFA technique remains the criterion standard despite the obvious logistical drawbacks (13). The sparse stool sampling method investigated in the present study requires collection of multiple stool samples; although this may not be acceptable or possible for all clinical centers, the stool collection schedules investigated here are likely to be more desirable and feasible for most clinical practices than collecting every bowel movement during a 72-hour period. The sparse stool samples could then be sent to an internal or external testing facility for PF analysis by NMR or an alternative, validated method. The multiple-sample methods are recommended over the single-sample method given their greater predictive capability and stronger correlations between PF and CFA. Based on this analysis, even if multiple sampling is required, in clinical practice only 3 samples (1 sample per day) would be sufficient.
Because this data analysis was based on only 12 subjects, it is exploratory rather than confirmatory and needs further validation. In addition, the choice of a CFA cutoff value of 80% for substantial fat malabsorption may limit the applicability of these results, because it could be argued that in subjects with EPI receiving PERT, the target CFA should be >90% (38); however, this may be difficult to achieve in subjects with CF. Although the population studied in this analysis was a population of subjects with CF, this method could be applicable to other conditions associated with EPI, for example, chronic pancreatitis, although further validation would be required in specific populations.
In conclusion, provided that sparse stool sampling is feasible in clinical practice, we propose that this sparse stool sampling method be used to identify suboptimal dosing in subjects with EPI caused by CF treated with PERT, and may have the potential to identify substantial fat malabsorption in subjects not receiving PERT. Once substantial fat malabsorption or suboptimal PERT has been identified using this convenient sparse stool sampling method, more detailed investigations could be carried out as required. This method is more convenient and less complicated than the 72-hour CFA method, because it does not require hospitalization, ingestion of food dye, and dietary monitoring, as required for CFA determination. Therefore, if subjects are able to provide assurance and documentation of adequate fat intake to allow interpretability of the results, this method has potential for use as a screening tool in routine clinical practice and clinical trials. Because the analysis we report was performed on only a small sample from a clinical trial setting, a larger study is warranted to investigate these sparse sampling methods in a real-world environment.
Medical writing support was provided by Stephen Gregson, PhD, of Envision Scientific Solutions, Horsham, UK, and funded by Abbott.
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