Observational Study Open Access
Copyright ©The Author(s) 2018. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. May 14, 2018; 24(18): 2036-2046
Published online May 14, 2018. doi: 10.3748/wjg.v24.i18.2036
Thiopurines are negatively associated with anthropometric parameters in pediatric Crohn’s disease
Neera Gupta, Division of Gastroenterology and Nutrition, Department of Pediatrics, Weill Cornell Medicine, New York, NY 10021, United States
Robert H Lustig, Division of Endocrinology, Department of Pediatrics, University of California, San Francisco, San Francisco, CA 94158, United States
Cewin Chao, Department of Nutrition and Food Services, University of California, San Francisco, San Francisco, CA 94143, United States
Eric Vittinghoff, Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA 94158, United States
Howard Andrews, Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY 10032, United States
Cheng-Shiun Leu, Department of Biostatistics, Columbia University Medical Center, New York, NY 10032, United States
ORCID number: Neera Gupta (0000-0002-9571-3913); Robert H Lustig (0000-0001-6983-2639); Cewin Chao (0000-0002-5711-926X); Eric Vittinghoff (0000-0001-8535-0920); Howard Andrews (0000-0002-7726-0551); Cheng-Shiun Leu (0000-0002-0301-8316).
Author contributions: Gupta N initial concept, secured funding; Gupta N, Lustig RH, Vittinghoff E and Leu CS study design; Gupta N data collection; Lustig RH bone age interpretation; Chao C anthropometric measurements; Gupta N and Leu CS data management; Gupta N, Vittinghoff E and Leu CS statistical analyses; Gupta N, Lustig RH, Chao C, Vittinghoff E, Andrews H and Leu CS data interpretation; Gupta N initial manuscript preparation; Gupta N, Lustig RH, Chao C, Vittinghoff E, Andrews H and Leu CS manuscript editing and revising; Gupta N finalized submission.
Supported by National Institutes of Health, No. DK077734 (NG); Children’s Digestive Health and Nutrition Foundation (now known as North American Society for Pediatric Gastroenterology, Hepatology, and Nutrition Foundation)/Crohn’s and Colitis Foundation of America (now known as Crohn’s and Colitis Foundation) Award for New Investigators, No. CDHNF-06-002 (NG); Crohn’s and Colitis Foundation of America (now known as Crohn’s and Colitis Foundation) Career Development Award, No. Award ID 1743 (NG); University of California San Francisco Department of Pediatrics Pediatric Clinical Research Center Clinical Research Pilot Funding Award (NG), and National Institutes of Health/National Center for Research Resources University of California San Francisco-Clinical and Translational Science Institute, No. UL1 RR024131.
Institutional review board statement: We obtained Institutional Review Board Approval for the study protocol.
Conflict-of-interest statement: Robert H Lustig wrote two trade books on metabolic health, but not related to the issues of this paper. The other authors have no conflicts of interest relevant to this article to disclose.
STROBE statement: The guidelines of the STROBE Statement have been adopted.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Correspondence to: Neera Gupta, MD, MAS, Associate Professor, Division of Gastroenterology and Nutrition, Department of Pediatrics, Weill Cornell Medicine, 505 East 70th Street, Helmsley Tower, 3rd Floor, New York, NY 10021, United States. neg9020@med.cornell.edu
Telephone: +1-646-9623869 Fax: +1-646-9620246
Received: February 3, 2018
Peer-review started: February 3, 2018
First decision: February 20, 2018
Revised: April 12, 2018
Accepted: April 26, 2018
Article in press: April 26, 2018
Published online: May 14, 2018

Abstract
AIM

To determine the distribution of anthropometric parameter (AP)-z-scores and characterize associations between medications/serum biomarkers and AP-z-scores in pediatric Crohn’s disease (CD).

METHODS

CD patients [< chronological age (CA) 21 years] were enrolled in a cross-sectional study. Descriptive statistics were generated for participants’ demographic characteristics and key variables of interest. Paired t-tests were used to compare AP-z-scores calculated based on CA (CA z-scores) and bone age (BA) (BA z-scores) for interpretation of AP’s. Linear regression was utilized to examine associations between medications and serum biomarkers with AP-z-scores calculated based on CA (n = 82) and BA (n = 49). We reported regression coefficients as well as their corresponding p-values and 95% confidence intervals.

RESULTS

Mean CA at the time of the study visit was 15.3 ± 3.5 (SD; range = 4.8-20.7) years. Mean triceps skinfold (P = 0.039), subscapular skinfold (P = 0.002) and mid-arm circumference (MAC) (P = 0.001) BA z-scores were higher than corresponding CA z-scores. Medications were positively associated with subscapular skinfold [adalimumab (P = 0.018) and methotrexate (P = 0.027)] and BMI CA z-scores [adalimumab (P = 0.029)]. Azathioprine/6-mercaptopurine were negatively associated with MAC (P = 0.045), subscapular skinfold (P = 0.014), weight (P = 0.002) and BMI (P = 0.013) CA z-scores. ESR, CRP, and WBC count were negatively associated, while albumin and IGF-1 BA z-scores were positively associated, with specific AP z-scores (P < 0.05). Mean height CA z-scores were higher in females, not males, treated with infliximab (P = 0.038). Hemoglobin (P = 0.018) was positively associated, while platelets (P = 0.005), ESR (P = 0.003) and CRP (P = 0.039) were negatively associated with height CA z-scores in males, not females.

CONCLUSION

Our results suggest poor efficacy of thiopurines and a possible sex difference in statural growth response to infliximab in pediatric CD. Prospective longitudinal studies are required.

Key Words: Inflammatory bowel disease, Azathioprine/6-mercaptopurine, Biologics, Nutrition

Core tip: Azathioprine/6-mercaptopurine were negatively associated with specific anthropometric parameters, suggesting a possible negative effect vs poor efficacy of thiopurines in pediatric Crohn’s disease (CD). Infliximab was positively associated with standardized height in females only, suggesting a possible sex difference in response to infliximab from the standpoint of statural growth in pediatric CD. Specific serum biomarkers were associated with standardized height in males only, supporting that inflammation has a more detrimental effect on statural growth in males with pediatric CD.



INTRODUCTION

Several studies document alterations in anthropometric parameters in pediatric Crohn’s disease (CD) such as lean mass deficits[1-5], reductions in fat free mass[6,7] , fat mass deficits[3,5,7], low body mass index (BMI)[1-3,5-8], high BMI[7,8], and low height[1-3,5,9,10]. Similar to impaired statural growth (height velocity), a dynamic marker of disease status, body composition deficits may reflect poorly controlled disease despite the absence of overt clinical intestinal symptoms.

Delayed bone age (BA) is common in pediatric CD[10-16]. BA assessed by left hand X-ray is regarded as a valid measure of skeletal maturity[13-14,17-19]. Determination of BA allows clinically meaningful interpretation of growth in the context of skeletal maturity in pediatric CD[11]. Mean height, weight and BMI z-scores calculated based on BA (BA z-scores) are higher than corresponding z-scores calculated based on chronological age (CA) (CA z-scores) in pediatric CD[11].

The impact of accounting for BA in the interpretation of body composition is unclear. Accurate interpretation of body composition is important since it reflects nutritional[4] and disease status. Not only is nutritional status an important determinant of pubertal development and growth velocity[20], it is a prognostic factor for disease course[21-28]. Several factors affect nutritional status, including inflammation, medications, nutrient intake, and hormones[4,29,30]. The association between medications and serum inflammatory and hormonal biomarkers with anthropometric measurements is not well delineated in pediatric CD, particularly after adjusting for maturational status (BA).

Nutritional status is an important factor to consider when making therapeutic decisions given its association with poor outcomes[21-28]. Yet, the impact of treatments on anthropometric measurements is poorly defined and has not received sufficient attention[31]. While there are well-documented sex differences in risk for statural growth impairment[9-10,14,21,32-35], sex differences in nutritional status require further study. Data regarding the relationship between medications and serum biomarkers with anthropometric parameters by sex, an important biological variable, are lacking.

Here we assessed body composition by skinfold measurements in pediatric CD. Our aims were to (1) determine the distribution of anthropometric parameters based on CA (CA z-scores) and BA (BA z-scores); and (2) characterize the associations between medications and serum biomarkers with anthropometric parameter z-scores in pediatric CD.

MATERIALS AND METHODS

Pediatric CD patients < CA 21 years enrolled in this cross-sectional study at University of California, San Francisco (UCSF) between January 2007 and July 2009 as previously described[10-11,36]. We excluded patients who received growth hormone ever or corticosteroids within 2 mo prior to study participation since more recent use would suppress the somatotropic axis and interfere with accurate assessment of insulin-like growth factor-1 (IGF-1) levels. Eighty-two patients completed the study.

Mid-arm circumference measurements and skinfold thickness measurements were collected to the nearest 0.1 mm from the non-dominant side of the body in triplicate and averaged. A measuring tape was used for mid-arm circumference measurements and Lange skinfold calipers were used for skinfold thickness measurements. The mid-arm circumference measurement was obtained at the mid-point between the olecranon process and acromion. The triceps skinfold measurement was obtained at the mid-point of the upper arm, halfway between the acromion and the olecranon. The subscapular skinfold was measured at a 45° angle just below the inferior angle of the scapula. One of two registered dietitians obtained the measurements. Both were trained using standardized NHANES methodologies with established inter-rater reliability[37]. Weight and height were measured using a digital scale (Scale-Tronix, White Plains, NY, United States) to the nearest 0.1 kg and stadiometer (Proscale, Accurate Technology, Inc., Cincinnati, OH, United States) to the nearest 0.1 cm, respectively. Body mass index (BMI) was calculated as the weight in kg divided by the square of the height in meters. Self-Tanner staging was performed[38]. Left hand x-rays obtained for BA were blindly interpreted by RL using the standards of Greulich and Pyle[17].

Medications of interest included adalimumab, 5-aminosalicylates, antibiotics, azathioprine/6-mercaptopurine (thiopurines), infliximab, and methotrexate.

We classified disease location as esophagus or stomach; small bowel, no colon; small bowel and colon; colon, no small bowel; perianal.

A lab draw was performed to measure serum IGF-1, insulin-like growth factor binding protein 3 (IGFBP-3), testosterone, estradiol, luteinizing hormone (LH), follicle stimulating hormone (FSH), albumin, alkaline phosphatase, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), hemoglobin, platelets, and white blood cell (WBC) count. Tubes for serum hormone levels and routine clinical labs were processed by Esoterix Endocrinology (Calabasas Hills, CA, United States) and UCSF clinical lab, respectively. Clinical information was collected.

Statistical analysis

We calculated CA z-scores for IGF-1, IGFBP-3, estradiol, testosterone, FSH, LH, mid-arm circumference, triceps skinfold, subscapular skinfold, weight, height, and BMI using reference values based in part on CA. Because pubertal growth acceleration correlates more closely with BA than CA[39], we also calculated BA z-scores for all 17 females ≤ CA 15 and 32 males ≤ CA 17 years, as epiphyses close at BA 15 in females and 17 years in males. We excluded all females > CA 15 and males > CA 17 years from BA analyses because sufficient reference data on variability of BA beyond these CA thresholds are not available. We transformed mid-arm circumference, triceps skinfold, subscapular skinfold, weight, height, and BMI measurements to z-scores[40-45]. Means and standard deviations (SDs) provided by Esoterix Endocrinology were used to calculate IGF-1 and IGFBP-3 z-scores. The mean and the upper and lower bounds of the normal ranges (specific to sex, age, and Tanner stage), accounting for asymmetry about the mean if present, were used to compute SDs for gonadotropins and sex hormones. Low and high z-scores are defined as z-scores < -2.0 and > 2.0, respectively.

Descriptive statistics were generated for participants’ demographic characteristics and key variables of interest. Paired t-tests were used to compare CA z-scores and BA z-scores for interpretation of anthropometric parameters. We employed linear regression to assess the associations between predictors (medications and serum biomarkers) and outcomes (anthropometric parameter CA z-scores and BA z-scores). For outcomes based on CA z-scores (n = 82), we also conducted analyses including CA at study visit, sex, CRP, albumin, ESR, and hemoglobin in the model to adjust for potential confounding. We conducted additional analyses adjusting for disease activity indices, disease duration, stricturing disease and penetrating disease in these models. We analyzed height CA z-scores separately by sex because of well-established sex differences in risk for statural growth impairment[9-10,14,21,32-35]. We reported regression coefficients as well as their corresponding p-values and 95% confidence intervals (CI); P-values < 0.05 were considered as statistically significant. Data were analyzed using IBM SPSS Statistics 23.

Ethical considerations

We obtained Institutional Review Board Approval for the study protocol. Informed consent/assent were obtained from parents/patients.

RESULTS
Participant characteristics

82 patients completed the study; 35 (43%) were female[10]. Mean CA at the time of the study visit was 15.3 ± 3.5 (SD; range = 4.8-20.7) years[10]. Mean CA at the time of inflammatory bowel disease (IBD) diagnosis was 12.1 ± 3.8 (0.5-17.9) years. Mean time since IBD diagnosis was 3.4 ± 2.8 (0.01-12.0) years. Race/ethnicity, Tanner stage, disease location, and medications are summarized in Table 1. History of corticosteroid use did not differ by sex[10].

Table 1 Demographics, Tanner stage, disease location, and medications.
Itemn (%)
Race
Asian12 (14.6)
East Asian6
South Asian6
Black/African American1 (1.2)
Other4 (4.9)
White65 (79.3)
Ethnicity
Hispanic or Latino7 (8.5)
Not Hispanic or Latino75 (91.5)
Tanner stage
18 (9.8)
215 (18.3)
316 (19.5)
424 (29.3)
519 (23.2)
Disease location
Esophagus or stomach9 (11)
Small bowel, no colon12 (14.6)
Colon, no small bowel17 (20.7)
Small bowel and colon53 (64.6)
Perianal disease49 (59.8)
Medication
Adalimumab4 (4.9)
5-Aminosalicylates50 (61.0)
Antibiotics14 (17.1)
Azathioprine/6-Mercaptopurine44 (53.7)
Infliximab20 (24.4)
Methotrexate7 (8.5)
Steroids ever55 (67.1)
Monotherapy vs combination therapy

Of the 44 patients on azathioprine/6-mercaptopurine, 33 (75%) were on thiopurine monotherapy, 10 (23%) were on combination therapy with infliximab and 1 (2%) was on combination therapy with adalimumab.

Of the 7 patients on methotrexate, 3 (43%) were on monotherapy, 2 (28.5%) were on combination therapy with infliximab and 2 (28.5%) were on combination therapy with adalimumab.

Of the 20 patients on infliximab, 8 (40%) were on monotherapy, 10 (50%) were on combination therapy with thiopurines and 2 (10%) were on combination therapy with methotrexate.

Of the 4 patients on adalimumab, 1 (25%) was on monotherapy, 1 (25%) was on combination therapy with thiopurines, 2 (50%) were on combination therapy with methotrexate.

Anthropometric parameters

Anthropometric parameters are summarized in Table 2.

Table 2 Summary of anthropometric parameters.
Variable (n)Mean ± SDRangePercent with z-scores > 2 (%)Percent with z-scores < -2 (%)
Mid-arm circumference-CA-z-score n = 82-0.64 ± 1.39-5.03 to 2.88217
Mid-arm circumference-BA-z-score n = 49-0.54 ± 1.30-2.86 to 2.50216
Subscapular skinfold-CA-z-score n = 810.59 ± 0.83-1.56 to 2.3130
Subscapular skinfold-BA-z-score n = 480.64 ± 0.87-1.17 to 2.2740
Triceps-CA-z-score n = 811.02 ± 0.74-0.88 to 2.79110
Triceps-BA-z-score n = 491.10 ± 0.72-1.17 to 2.4780
Height-CA-z-score n = 82-0.30 ± 1.02-2.74 to 2.3416
Height-BA-z-score n = 490.17 ± 1.12-3.29 to 2.5342
Weight CA-z-score n = 82-0.17 ± 1.10-3.49 to 2.2045
Weight BA-z-score n = 490.11 ± 0.91-2.52 to 1.9702
BMI-CA-z-score n = 82-0.07 ± 1.04-2.78 to 2.1744
BMI BA-z-score n = 490.05 ± 0.86-2.58 to 2.0922
Bone age vs chronological age for the interpretation of anthropometric parameters

For the 49 patients qualifying for BA analyses, mean BA (12.2 ± 2.9 years) was significantly lower than mean CA (13.1 ± 2.6 years) (P < 0.0001)[10]. Mid-arm circumference (0.35 units, 95%CI: 0.14-0.55; P = 0.001), subscapular skinfold (0.10 units, 95%CI: 0.04-0.16; P = 0.002), and triceps skinfold (0.05 units, 95%CI: 0.003-0.11; P = 0.039) BA z-scores were systematically higher than corresponding CA z-scores.

Medications, serum biomarkers, and anthropometric parameters

Tables 3 and 4 show the unadjusted and adjusted associations, respectively, between medication treatment, serum biomarkers and anthropometric parameter CA z-scores (height CA z-scores presented separately) that achieved statistical significance. Infliximab was not statistically significantly associated with mid-arm circumference, triceps skinfold, subscapular skinfold, weight or BMI CA z-scores (data not shown). Results did not change when disease activity indices, disease duration, stricturing disease or penetrating disease were included in the adjusted models.

Table 3 Significant associations between medications/serum biomarkers and anthropometric parameters [z-scores based on chronological age (n = 82)] - unadjusted analyses.
VariableMid-arm circumference CA-z-scoresSubscapular skinfold CA-z-scoresWeight CA-z-scoresBMI CA-z-scores
Adalimumab0.901 (0.08, 1.72)2 0.03331.09 (0.05, 2.13) 0.04
Azathioprine-0.65 (-1.25, -0.05) 0.033-0.5 (-0.85, -0.14) 0.006-0.7 (-1.16, -0.23) 0.004-0.56 (-1.004, -0.12) 0.014
Methotrexate0.75 (0.06, 1.43) 0.032
ESR-0.024 (-0.05, -0.002) 0.036-0.03 (-0.05, -0.02) 0.0003-0.02 (-0.04, -0.006) 0.009
Hemoglobin0.19 (0.04, 0.34) 0.015
Table 4 Significant associations between medications/serum biomarkers and anthropometric parameters [z-scores based on chronological age (n = 82)] - adjusted analyses.
VariableMid-arm circumference CA-z-scoresSubscapular skinfold CA-z-scoresWeight CA-z-scoresBMI CA-z-scores
Adalimumab1.021 (0.18, 1.86)2 0.01831.17 (0.13, 2.21) 0.029
Azathioprine-0.64 (-1.26, -0.02) 0.045-0.47 (-0.83, -0.10) 0.014-0.73 (-1.17, -0.29) 0.002-0.58 (-1.03, -0.12) 0.013
Methotrexate0.81 (0.10, 1.53) 0.027
ESR-0.03 (-0.05, -0.01) 0.01-0.03 (-0.05, -0.004) 0.024

Table 5 shows the unadjusted associations between serum biomarkers and anthropometric parameter BA z-scores (height BA z-scores presented separately). Medication treatments were not statistically significantly associated with anthropometric parameter BA z-scores.

Table 5 Significant associations between serum biomarkers and anthropometric parameters [z-scores based on bone age (n = 49)] - unadjusted analyses.
VariableMid-arm circumference BA-z-scoresSubscapular skinfoldBA-z-scoresTriceps skinfoldBA-z-scoresWeightBA-z-scoresBMIBA-z-scores
WBC-0.191 (-0.36, -0.02)2 0.0293-0.12 (-0.24, -0.01) 0.04-0.16 (-0.28, -0.04) 0.008
ESR-0.03 (-0.04, -0.01) 0.003-0.02 (-0.03, -0.001) 0.037
CRP-0.03 (-0.07, -0.0001) 0.049-0.06 (-0.10, -0.02) 0.008
Albumin0.73 (0.28, 1.18) 0.002
IGF-1 BA-z-scores0.2 (0.01, 0.38) 0.039

Table 6 shows the unadjusted associations between medications, serum biomarkers and height CA z-scores by sex.

Table 6 Significant associations between medications/serum biomarkers and height z-scores by sex (based on chronological age (female n = 35; male n = 47)) - unadjusted analyses.
VariableHeight CA z-scoresPoint estimate195%CIP value
InfliximabFemales0.650.04, 1.250.038
CRPMales-0.04-0.079, -0.0020.039
ESRMales-0.03-0.051, -0.0110.003
HemoglobinMales0.230.04, 0.420.018
PlateletsMales-0.004-0.006, -0.0010.005

Table 7 shows the unadjusted association between serum biomarkers and height BA z-scores. Medications were not statistically significantly associated with height BA z-scores.

Table 7 Significant associations between serum biomarkers and height z-scores [based on bone age (n = 49)] - unadjusted analyses.
VariableHeight BA-z-scoresPoint estimate195%CIP value
AlbuminMales and females0.80.22, 1.360.008
CRPMales and females-0.06-0.11, -0.0060.03
ESRMales and females-0.02-0.05, -0.0030.029
IGF-1 BA-z-scoresMales and females0.260.03, 0.480.025
DISCUSSION

In our prospective, cross-sectional study, azathioprine/6-mercaptopurine were negatively associated with lean tissue mass (mid-arm circumference CA z-scores) and fat store (subscapular CA z-scores) measurements, and weight CA z-scores and BMI CA z-scores in pediatric CD. We previously reported thiopurine treatment was associated with lower standardized BA results[11]. From a mechanistic perspective, it is unlikely these associations represents a direct negative impact of thiopurines on skeletal maturation or anthropometric parameters. When examining the association between azathioprine/6-mercaptopurine and BA z-scores for these specific anthropometric parameters, the direction of the association remained negative between thiopurines and subscapular skinfold BA z-scores (though did not achieve statistical significance due to smaller sample size (n = 49 for BA analyses vs n = 82 for CA analyses). This continued negative association between thiopurines and subscapular skinfold BA z-scores in combination with our previously reported finding of a negative association between thiopurines and standardized BA results[11] calls into question the efficacy of thiopurines for treating pediatric CD. Our findings highlight the importance of considering BA in the interpretation of anthropometric parameters because its inclusion clarifies the relationship between medications and these outcomes.

Previously published data on the impact of thiopurines on anthropometry for comparison to our findings are limited, but also raise concerns about the efficacy of these medications. Csontos et al[31] reported no statistically significant difference in the change in fat free mass index, skeletal muscle index, or body fat mass index in adult IBD patients on vs not on azathioprine during initiation of biologic therapy. In newly diagnosed CD children randomized to treatment with 6-mercaptopurine plus steroids vs placebo plus steroids, Markowitz et al[46] did not detect a difference in statural growth.

Regarding a possible negative impact of utilizing thiopurines, in a pediatric IBD cohort, Hyams et al[47] reported thiopurine exposure is an important preceding event for the development of malignancy or hemophagocytic lymphohistiocytosis. Our data identify another negative signal associated with thiopurines, given the constellation of findings of statistically significant negative associations between azathioprine/6-mercaptopurine and mid-arm circumference, subscapular skinfold, weight and BMI CA z-scores and persistent negative association with subscapular skinfold BA z-scores (though did not achieve statistical significance due to smaller sample size available for BA analyses), in combination with our previously reported finding of a statistically significant association with lower standardized BA results[11]. Prospective longitudinal study is required to examine the longitudinal pattern of these associations and to investigate whether these findings represents a lack of efficacy of thiopurines (given that anthropometric parameters and skeletal maturation reflect nutritional status/disease status) vs a direct negative impact of thiopurines in pediatric CD. Patients with lower body composition z-scores and lower standardized BA results were not selectively placed on thiopurines vs another medication such as methotrexate, infliximab, or adalimumab as these measurements were obtained at the time of the study.

Adalimumab and methotrexate were positively associated (statistically significant) with measurements of fat mass [subscapular CA z-scores (adalimumab/methotrexate)] and BMI CA z-scores (adalimumab). While these medications were not statistically significantly associated with these outcome BA z-scores due to a smaller sample size available for BA analyses, the direction of these associations (positive) remained unchanged and the effect sizes were similar to only mildly decreased compared with the statistically significant positive associations between these medications and these outcome CA z-scores, supporting a positive association between adalimumab and methotrexate with these anthropometric parameter BA z-scores.

Similar to our finding of a positive association between the anti-tumor necrosis factor alpha (TNF-α) agent, adalimumab, and BMI, Diamanti et al[48] reported that weight and BMI improved in children treated with infliximab, but not with mesalazine and azathioprine. Wiese et al[49] reported a significant increase in BMI with infliximab treatment in adult CD.

In a pediatric CD study, investigators reported specific medications were associated with greater increases in race- and sex-specific z-scores for both lean mass (infliximab) and fat mass (infliximab, glucocorticoid, and methotrexate) relative to height[50]. Similarly, we identified a positive association between methotrexate and subscapular skinfold CA z-scores. In a CD patient cohort, age 5-25 years, Sentongo et al[14] reported triceps skinfold z-scores, also a measure of adiposity, were significantly correlated with corticosteroid exposure. Our findings do not reveal a statistically significant association between history of corticosteroid therapy and current anthropometric parameters.

Csontos et al[31] reported baseline BMI increased significantly during initiation of adalimumab/infliximab therapy in adult IBD, in agreement with our identified positive association between adalimumab and BMI. They found fat free mass index also increased. They found no significant differences between the effects of adalimumab and infliximab on body composition, whereas we identified significant associations between body composition and adalimumab only, not infliximab. Notably, fat free mass index and skeletal muscle mass index significantly improved only in males. Subramaniam et al[51] reported infliximab was associated with significant gains in muscle volume that correlated with male sex in adult CD[51]. Supporting these sex differences in response to infliximab, in a mouse model of pulmonary inflammation in which TNF-α was over expressed in mouse lungs, lower body and muscle mass were evident only in males[52].

Our study does not reveal a sex difference in the association between medications and body composition, but does identify a statistically significant positive association between infliximab and height CA z-scores in females only. A positive relationship between infliximab and height BA z-scores was also identified in females only, but did not reach statistical significance, likely due to the smaller sample size available for BA analyses (n = 17 females for BA analyses vs n = 35 females for CA analyses). The combination of findings described here between infliximab and height z-scores (based on CA and BA) supports a possible sex difference in response to infliximab from the standpoint of statural growth. Taken together, these findings of sex differences in response to infliximab add to the growing body of literature indicating that there may be sex differences in the molecular pathways affecting statural growth and body composition in CD. Our findings in combination with the existing literature raise an intriguing question: does TNF-α play an important role in compromising body composition in CD males but statural growth in females, and if so, why? Tang et al[52] speculated that estrogen has protective effects against the actions of TNF-α. Ordas et al[53] reported that clearance of monoclonal antibodies is higher in men. Ternant et al[54] theorized that the central volume of distribution may be higher in men because for a given body weight, plasma volume is lower in women.

We found hemoglobin was positively associated, while platelets, ESR, and CRP were negatively associated, with height CA z-scores in males only, supporting our previously reported findings of a greater detrimental effect of inflammation on statural growth in males[10]. Several investigators have documented that growth impairment is more frequent in males[9,10,14,21,32-35]. Perhaps the molecular pathways that lead to growth impairment in males are different than in females, and less responsive to currently used medications, such as infliximab. As expected, albumin and IGF-1 BA z-scores were positively associated, while ESR and CRP were negatively associated with height BA z-scores. In contrast, no treatment (5-aminosalicylate, corticosteroids, immunomodulators, infliximab, nutritional therapy, surgical resection) was associated with height, weight or BMI at maximal follow up in a pediatric CD cohort in Northern France[21].

The relationships between medications and anthropometric parameters may reflect efficacy of medications, side effects of medications, or confounding by indication. Since body composition measurements were obtained as part of a study protocol and not standard of care, it is unlikely these relationships reflect confounding by indication since these body composition measurements were not available to the care provider. Our results suggest methotrexate, infliximab and adalimumab are more effective than thiopurines for treating pediatric CD.

As expected, body composition BA z-scores were systematically higher than corresponding body composition CA z-scores. Patients did not exhibit severe deficiencies in fat stores, as reflected by standardized subscapular and triceps skinfold measurements. Depending on the measurement obtained, 3% to 11% had subscapular or triceps skinfold measurement CA z-scores or BA z-scores > 2.0, reflecting excess fat stores. In contrast, 16%-17% had deficiencies in lean mass tissue as reflected by mid-arm circumference z-score measurements < -2.0 and only 2% with mid-arm circumference z-score measurements > 2.0. We identified a negative association between thiopurines and mid-arm circumference CA z-scores. The published literature surrounding the relationship between medications and lean mass tissue is conflicting[31,50-51]. More studies are needed to identify the most effective treatments for improving lean mass tissue in pediatric CD.

Correlations between inflammatory markers/disease activity indices and anthropometric parameters have been reported by other investigators[5,14,50,55,56], similar to our findings. Enhancing our understanding of the specific inflammatory cytokines involved in molecular pathways affecting body composition and growth is critical for optimizing treatment.

Limitations

The etiology of compromised nutritional status/disease status is multifactorial. The cross-sectional study design does not permit longitudinal assessment of changes in anthropometric parameters with respect to medication treatment and serum biomarkers to be determined. Within-subjects characterization of the influence of disease activity and hormone levels on changes in anthropometric parameters may clarify the effects of long-term inflammation on nutritional status/disease status. Nevertheless, our results suggest a mechanistic relationship between medications, inflammation and anthropometric status/disease status, as well as a difference by sex. Prospective longitudinal study, collecting additional markers of disease activity/disease status such as fecal calprotectin, cross-sectional imaging and endoscopic assessment, is required as a next step to further investigate these intriguing findings and would allow further risk stratification which will improve patient counseling, guide expectations, and facilitate an individualized treatment approach. Future studies should examine the impact of monotherapy vs combination therapy (including duration of treatment and drug levels) on anthropometric status/disease status.

Summary and Conclusions

Complex processes regulate body composition and growth in pediatric CD. We examined the relationship between medication treatments and serum inflammatory and hormonal biomarkers with anthropometric parameters in a well-characterized pediatric CD cohort. Our findings reinforce the importance of accounting for BA when interpreting anthropometric parameters in pediatric CD. The main findings of our study raise intriguing questions.

Thiopurines were negatively associated with specific anthropometric parameters. Do thiopurines have a negative effect on nutritional status/disease status? Alternatively, is the efficacy of thiopurines suboptimal? This interesting finding may have significant implications for pediatric CD treatment and requires further investigation in a prospective longitudinal study to determine if thiopurines should continue to be utilized as a treatment for pediatric CD.

Infliximab was positively associated with standardized height in females only. Is there a sex difference in response to infliximab from the standpoint of statural growth? Specific serum biomarkers were associated with standardized height in males only, supporting the hypothesis that inflammation has a more detrimental effect on statural growth in males. The combination of these findings lends further support to the theory that sex differences in the molecular pathways driving statural growth impairment in pediatric CD exist and should be delineated in a prospective longitudinal study utilizing height velocity BA z-scores as the primary outcome. An improved understanding of this sex difference in response to treatment would be a huge step towards enhancing risk prediction and individualized treatment.

The studies presented herein contribute to a better understanding of the relationship between medications and serum inflammatory and hormonal biomarkers with anthropometric parameters in pediatric CD. These findings serve as a foundation on which to build future studies with the goal of identifying patients at highest risk for poor outcomes, enhancing treatment algorithms, and ultimately developing individual treatment approaches based on risk stratification. The present study may provide a basis for mechanistic studies in many pediatric chronic inflammatory conditions.

ARTICLE HIGHLIGHTS
Research background

Similar to impaired statural growth (height velocity), a dynamic marker of disease status, body composition deficits may reflect poorly controlled disease despite the absence of overt clinical intestinal symptoms. Delayed bone age (BA) is common in pediatric Crohn’s disease (CD). Determination of BA allows clinically meaningful interpretation of growth in the context of skeletal maturity in pediatric CD. The impact of accounting for BA in the interpretation of body composition is unclear. Accurate interpretation of body composition is important since it reflects nutritional and disease status. Not only is nutritional status an important determinant of pubertal development and growth velocity, it is a prognostic factor for disease course. The association between medications and serum inflammatory and hormonal biomarkers with anthropometric measurements is not well delineated in pediatric CD, particularly after adjusting for maturational status (BA).

Research motivation

Nutritional status is an important factor to consider when making therapeutic decisions given its association with poor outcomes. Yet, the impact of treatments on anthropometric measurements is poorly defined and has not received sufficient attention.

Research objectives

Our aims were to determine the distribution of anthropometric parameters based on CA (CA z-scores) and BA (BA z-scores) and characterize the associations between medications and serum biomarkers with anthropometric parameter z-scores in pediatric CD.

Research methods

CD patients [< chronological age (CA) 21 years] were prospectively enrolled in a cross-sectional study. Descriptive statistics were generated for participants’ demographic characteristics and key variables of interest. Paired t-tests were used to compare anthropometric parameter z-scores calculated based on CA (CA z-scores) and BA (BA z-scores) for interpretation of anthropometric parameters. Linear regression was utilized to examine associations between medications and serum biomarkers with anthropometric parameter z-scores calculated based on CA (n = 82) and BA (n = 49). We reported regression coefficients as well as their corresponding p-values and 95% confidence intervals.

Research results

Mean CA at the time of the study visit was 15.3 ± 3.5 (standard deviation; range = 4.8-20.7) years. Mean triceps skinfold, subscapular skinfold and mid-arm circumference (MAC) BA z-scores were higher than corresponding CA z-scores. Medications were positively associated with subscapular skinfold (adalimumab and methotrexate) and BMI (adalimumab) CA z-scores. Azathioprine/6-mercaptopurine were negatively associated with MAC, subscapular skinfold, weight and BMI CA z-scores . ESR, CRP, and WBC count were negatively associated, while albumin and IGF-1 BA z-scores were positively associated with specific AP z-scores. Mean height CA z-scores were higher in females, not males, treated with infliximab. Hemoglobin was positively associated, while platelets, ESR and CRP were negatively associated with height CA z-scores in males, not females.

Research conclusions

Our findings reinforce the importance of accounting for BA when interpreting anthropometric parameters in pediatric CD. The main findings of our study raise intriguing questions. Thiopurines were negatively associated with specific anthropometric parameters. Do thiopurines have a negative effect on nutritional status/disease status? Alternatively, is the efficacy of thiopurines suboptimal? Infliximab was positively associated with standardized height in females only. Is there a sex difference in response to infliximab from the standpoint of statural growth? Specific serum biomarkers were associated with standardized height in males only, supporting the hypothesis that inflammation has a more detrimental effect on statural growth in males. Our results suggest a mechanistic relationship between medications, inflammation and anthropometric status/disease status, as well as a difference by sex. The studies presented herein contribute to a better understanding of the relationship between medications and serum inflammatory and hormonal biomarkers with anthropometric parameters in pediatric CD. Prospective longitudinal study is required as a next step to further investigate these intriguing findings and would allow further risk stratification which will improve patient counseling, guide expectations, and facilitate an individualized treatment approach.

Research perspectives

These findings serve as a foundation on which to build future studies with the goal of identifying patients at highest risk for poor outcomes, enhancing treatment algorithms, and ultimately developing individual treatment approaches based on risk stratification. The present study may provide a basis for mechanistic studies in many pediatric chronic inflammatory conditions.

ACKNOWLEDGMENTS

We thank the patients for participating in this study. We thank Dr. Keith C Mages, Clinical Medical Librarian at the Samuel J Wood Library, Weill Cornell Medicine, for library services.

Footnotes

Manuscript source: Unsolicited manuscript

Specialty type: Gastroenterology and hepatology

Country of origin: United States

Peer-review report classification

Grade A (Excellent): A

Grade B (Very good): 0

Grade C (Good): C

Grade D (Fair): D

Grade E (Poor): 0

P- Reviewer: Gazouli M, Nielsen OH, Vasudevan A S- Editor: Ma YJ L- Editor: A E- Editor: Huang Y

References
1.  Burnham JM, Shults J, Semeao E, Foster B, Zemel BS, Stallings VA, Leonard MB. Whole body BMC in pediatric Crohn disease: independent effects of altered growth, maturation, and body composition. J Bone Miner Res. 2004;19:1961-1968.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 124]  [Cited by in F6Publishing: 104]  [Article Influence: 5.2]  [Reference Citation Analysis (0)]
2.  Burnham JM, Shults J, Semeao E, Foster BJ, Zemel BS, Stallings VA, Leonard MB. Body-composition alterations consistent with cachexia in children and young adults with Crohn disease. Am J Clin Nutr. 2005;82:413-420.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 107]  [Cited by in F6Publishing: 108]  [Article Influence: 5.7]  [Reference Citation Analysis (0)]
3.  Boot AM, Bouquet J, Krenning EP, de Muinck Keizer-Schrama SM. Bone mineral density and nutritional status in children with chronic inflammatory bowel disease. Gut. 1998;42:188-194.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 155]  [Cited by in F6Publishing: 160]  [Article Influence: 6.2]  [Reference Citation Analysis (0)]
4.  Jahnsen J, Falch JA, Mowinckel P, Aadland E. Body composition in patients with inflammatory bowel disease: a population-based study. Am J Gastroenterol. 2003;98:1556-1562.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 111]  [Cited by in F6Publishing: 109]  [Article Influence: 5.2]  [Reference Citation Analysis (0)]
5.  Thayu M, Shults J, Burnham JM, Zemel BS, Baldassano RN, Leonard MB. Gender differences in body composition deficits at diagnosis in children and adolescents with Crohn’s disease. Inflamm Bowel Dis. 2007;13:1121-1128.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 59]  [Cited by in F6Publishing: 49]  [Article Influence: 2.9]  [Reference Citation Analysis (0)]
6.  Sylvester FA, Leopold S, Lincoln M, Hyams JS, Griffiths AM, Lerer T. A two-year longitudinal study of persistent lean tissue deficits in children with Crohn’s disease. Clin Gastroenterol Hepatol. 2009;7:452-455.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 58]  [Cited by in F6Publishing: 62]  [Article Influence: 4.1]  [Reference Citation Analysis (0)]
7.  Sousa Guerreiro C, Cravo M, Costa AR, Miranda A, Tavares L, Moura-Santos P, MarquesVidal P, Nobre Leitão C. A comprehensive approach to evaluate nutritional status in Crohn’s patients in the era of biologic therapy: a case-control study. Am J Gastroenterol. 2007;102:2551-2556.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 68]  [Cited by in F6Publishing: 64]  [Article Influence: 3.8]  [Reference Citation Analysis (0)]
8.  Kugathasan S, Nebel J, Skelton JA, Markowitz J, Keljo D, Rosh J, LeLeiko N, Mack D, Griffiths A, Bousvaros A. Body mass index in children with newly diagnosed inflammatory bowel disease: observations from two multicenter North American inception cohorts. J Pediatr. 2007;151:523-527.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 77]  [Cited by in F6Publishing: 78]  [Article Influence: 4.6]  [Reference Citation Analysis (0)]
9.  Gupta N, Bostrom AG, Kirschner BS, Ferry GD, Winter HS, Baldassano RN, Gold BD, Abramson O, Smith T, Cohen SA. Gender differences in presentation and course of disease in pediatric patients with Crohn disease. Pediatrics. 2007;120:e1418-e1425.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 82]  [Cited by in F6Publishing: 86]  [Article Influence: 5.1]  [Reference Citation Analysis (0)]
10.  Gupta N, Lustig RH, Kohn MA, McCracken M, Vittinghoff E. Sex differences in statural growth impairment in Crohn’s disease: role of IGF-1. Inflamm Bowel Dis. 2011;17:2318-2325.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 39]  [Cited by in F6Publishing: 36]  [Article Influence: 2.8]  [Reference Citation Analysis (0)]
11.  Gupta N, Lustig RH, Kohn MA, Vittinghoff E. Determination of bone age in pediatric patients with Crohn’s disease should become part of routine care. Inflamm Bowel Dis. 2013;19:61-65.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 17]  [Cited by in F6Publishing: 16]  [Article Influence: 1.5]  [Reference Citation Analysis (0)]
12.  Motil KJ, Grand RJ, Davis-Kraft L, Ferlic LL, Smith EO. Growth failure in children with inflammatory bowel disease: a prospective study. Gastroenterology. 1993;105:681-691.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 207]  [Cited by in F6Publishing: 211]  [Article Influence: 6.8]  [Reference Citation Analysis (0)]
13.  Hill RJ, Brookes DS, Lewindon PJ, Withers GD, Ee LC, Connor FL, Cleghorn GJ, Davies PS. Bone health in children with inflammatory bowel disease: adjusting for bone age. J Pediatr Gastroenterol Nutr. 2009;48:538-543.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 22]  [Cited by in F6Publishing: 20]  [Article Influence: 1.3]  [Reference Citation Analysis (0)]
14.  Sentongo TA, Semeao EJ, Piccoli DA, Stallings VA, Zemel BS. Growth, body composition, and nutritional status in children and adolescents with Crohn’s disease. J Pediatr Gastroenterol Nutr. 2000;31:33-40.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 114]  [Cited by in F6Publishing: 116]  [Article Influence: 4.8]  [Reference Citation Analysis (0)]
15.  McCaffery TD, Nasr K, Lawrence AM, Kirsner JB. Severe growth retardation in children with inflammatory bowel disease. Pediatrics. 1970;45:386-393.  [PubMed]  [DOI]  [Cited in This Article: ]
16.  Savage MO, Beattie RM, Camacho-Hübner C, Walker-Smith JA, Sanderson IR. Growth in Crohn’s disease. Acta Paediatr Suppl. 1999;88:89-92.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 48]  [Cited by in F6Publishing: 52]  [Article Influence: 2.1]  [Reference Citation Analysis (0)]
17.  Greulich WW, Pyle SI.  Radiographic Atlas of Skeletal Development of the Hand and Wrist, 2nd ed. Stanford, CA: Stanford University Press 1959; .  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 2]  [Cited by in F6Publishing: 2]  [Article Influence: 0.2]  [Reference Citation Analysis (0)]
18.  Jones G, Ma D. Skeletal age deviation assessed by the Tanner-Whitehouse 2 method is associated with bone mass and fracture risk in children. Bone. 2005;36:352-357.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 25]  [Cited by in F6Publishing: 26]  [Article Influence: 1.4]  [Reference Citation Analysis (0)]
19.  Johnson W, Stovitz SD, Choh AC, Czerwinski SA, Towne B, Demerath EW. Patterns of linear growth and skeletal maturation from birth to 18 years of age in overweight young adults. Int J Obes (Lond). 2012;36:535-541.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 57]  [Cited by in F6Publishing: 60]  [Article Influence: 4.6]  [Reference Citation Analysis (0)]
20.  Forbes A, Escher J, Hébuterne X, Kłęk S, Krznaric Z, Schneider S, Shamir R, Stardelova K, Wierdsma N, Wiskin AE. ESPEN guideline: Clinical nutrition in inflammatory bowel disease. Clin Nutr. 2017;36:321-347.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 342]  [Cited by in F6Publishing: 375]  [Article Influence: 46.9]  [Reference Citation Analysis (0)]
21.  Vasseur F, Gower-Rousseau C, Vernier-Massouille G, Dupas JL, Merle V, Merlin B, Lerebours E, Savoye G, Salomez JL, Cortot A. Nutritional status and growth in pediatric Crohn’s disease: a population-based study. Am J Gastroenterol. 2010;105:1893-1900.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 97]  [Cited by in F6Publishing: 101]  [Article Influence: 7.2]  [Reference Citation Analysis (0)]
22.  Ananthakrishnan AN, McGinley EL. Infection-related hospitalizations are associated with increased mortality in patients with inflammatory bowel diseases. J Crohns Colitis. 2013;7:107-112.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 124]  [Cited by in F6Publishing: 135]  [Article Influence: 12.3]  [Reference Citation Analysis (0)]
23.  Nguyen GC, Munsell M, Harris ML. Nationwide prevalence and prognostic significance of clinically diagnosable protein-calorie malnutrition in hospitalized inflammatory bowel disease patients. Inflamm Bowel Dis. 2008;14:1105-1111.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 126]  [Cited by in F6Publishing: 113]  [Article Influence: 7.1]  [Reference Citation Analysis (2)]
24.  Ananthakrishnan AN, McGinley EL, Binion DG, Saeian K. A novel risk score to stratify severity of Crohn’s disease hospitalizations. Am J Gastroenterol. 2010;105:1799-1807.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 43]  [Cited by in F6Publishing: 39]  [Article Influence: 2.8]  [Reference Citation Analysis (0)]
25.  Gajendran M, Umapathy C, Loganathan P, Hashash JG, Koutroubakis IE, Binion DG. Analysis of Hospital-Based Emergency Department Visits for Inflammatory Bowel Disease in the USA. Dig Dis Sci. 2016;61:389-399.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 44]  [Cited by in F6Publishing: 33]  [Article Influence: 4.1]  [Reference Citation Analysis (0)]
26.  Wallaert JB, De Martino RR, Marsicovetere PS, Goodney PP, Finlayson SR, Murray JJ, Holubar SD. Venous thromboembolism after surgery for inflammatory bowel disease: are there modifiable risk factors? Data from ACS NSQIP. Dis Colon Rectum. 2012;55:1138-1144.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 100]  [Cited by in F6Publishing: 117]  [Article Influence: 9.8]  [Reference Citation Analysis (0)]
27.  Nguyen DL, Parekh N, Bechtold ML, Jamal MM. National Trends and In-Hospital Outcomes of Adult Patients With Inflammatory Bowel Disease Receiving Parenteral Nutrition Support. JPEN J Parenter Enteral Nutr. 2016;40:412-416.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 9]  [Cited by in F6Publishing: 10]  [Article Influence: 1.0]  [Reference Citation Analysis (0)]
28.  Addolorato G, Capristo E, Stefanini GF, Gasbarrini G. Inflammatory bowel disease: a study of the association between anxiety and depression, physical morbidity, and nutritional status. Scand J Gastroenterol. 1997;32:1013-1021.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 160]  [Cited by in F6Publishing: 168]  [Article Influence: 6.2]  [Reference Citation Analysis (0)]
29.  Forbes GB. Perspectives on body composition. Curr Opin Clin Nutr Metab Care. 2002;5:25-30.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 10]  [Cited by in F6Publishing: 11]  [Article Influence: 0.5]  [Reference Citation Analysis (0)]
30.  Thangarajah D, Hyde MJ, Konteti VK, Santhakumaran S, Frost G, Fell JM. Systematic review: Body composition in children with inflammatory bowel disease. Aliment Pharmacol Ther. 2015;42:142-157.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 38]  [Cited by in F6Publishing: 25]  [Article Influence: 2.8]  [Reference Citation Analysis (0)]
31.  Csontos ÁA, Molnár A, Piri Z, Katona B, Dakó S, Pálfi E, Miheller P. The Effect of anti-TNFα Induction Therapy on the Nutritional Status and Dietary Intake in Inflammatory Bowel Disease. J Gastrointestin Liver Dis. 2016;25:49-56.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 4]  [Cited by in F6Publishing: 8]  [Article Influence: 1.1]  [Reference Citation Analysis (0)]
32.  Gupta N. Summary of “Growth and nutritional status in pediatric Crohn’s disease” with a focus on sex differences in statural growth impairment. J Pediatr Gastroenterol Nutr. 2011;53:227-228.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 5]  [Cited by in F6Publishing: 6]  [Article Influence: 0.5]  [Reference Citation Analysis (0)]
33.  Griffiths AM, Nguyen P, Smith C, MacMillan JH, Sherman PM. Growth and clinical course of children with Crohn’s disease. Gut. 1993;34:939-943.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 178]  [Cited by in F6Publishing: 189]  [Article Influence: 6.1]  [Reference Citation Analysis (0)]
34.  Pigneur B, Seksik P, Viola S, Viala J, Beaugerie L, Girardet JP, Ruemmele FM, Cosnes J. Natural history of Crohn’s disease: comparison between childhood- and adult-onset disease. Inflamm Bowel Dis. 2010;16:953-961.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 181]  [Cited by in F6Publishing: 183]  [Article Influence: 13.1]  [Reference Citation Analysis (0)]
35.  Mason A, Malik S, McMillan M, McNeilly JD, Bishop J, McGrogan P, Russell RK, Ahmed SF. A prospective longitudinal study of growth and pubertal progress in adolescents with inflammatory bowel disease. Horm Res Paediatr. 2015;83:45-54.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 25]  [Cited by in F6Publishing: 24]  [Article Influence: 2.7]  [Reference Citation Analysis (0)]
36.  Gupta N, Lustig RH, Kohn MA, Vittinghoff E. Menarche in pediatric patients with Crohn’s disease. Dig Dis Sci. 2012;57:2975-2981.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 18]  [Cited by in F6Publishing: 16]  [Article Influence: 1.3]  [Reference Citation Analysis (0)]
37.  Centers for Disease Control and Prevention. National Health and Nutrition Examination Survey (NHANES) Anthropometry Manual.  Available from: https://www.cdc.gov/nchs/data/nhanes/nhanes_11_12/Anthropometry_Procedures_Manual.pdf.  [PubMed]  [DOI]  [Cited in This Article: ]
38.  Morris NM, Udry JR. Validation of a self-administered instrument to assess stage of adolescent development. J Youth Adolesc. 1980;9:271-280.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 681]  [Cited by in F6Publishing: 709]  [Article Influence: 64.5]  [Reference Citation Analysis (0)]
39.  Smith DW. Growth and its disorders: basics and standards, approach and classifications, growth deficiency disorders, growth excess disorders, obesity. Major Probl Clin Pediatr. 1977;15:1-155.  [PubMed]  [DOI]  [Cited in This Article: ]
40.  McDowell MA, Fryar CD, Ogden CL, Flegal KM. Anthropometric reference data for children and adults: United States, 2003–2006. Natl Health Stat Report. 2008;10:1-48.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 68]  [Cited by in F6Publishing: 57]  [Article Influence: 6.3]  [Reference Citation Analysis (0)]
41.  McDowell MA, Fryar CD, Hirsch R, Ogden CL. Anthropometric reference data for children and adults: U.S. population, 1999-2002. Adv Data. 2005;361:1-5.  [PubMed]  [DOI]  [Cited in This Article: ]
42.  Frisancho AR. New norms of upper limb fat and muscle areas for assessment of nutritional status. Am J Clin Nutr. 1981;34:2540-2545.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1116]  [Cited by in F6Publishing: 1045]  [Article Influence: 24.3]  [Reference Citation Analysis (0)]
43.  Tanner JM, Whitehouse RH. Revised standards for triceps and subscapular skinfolds in British children. Arch Dis Child. 1975;50:142-145.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 284]  [Cited by in F6Publishing: 298]  [Article Influence: 6.1]  [Reference Citation Analysis (0)]
44.  Davies PS, Day JM, Cole TJ. Converting Tanner-Whitehouse reference tricep and subscapular skinfold measurements to standard deviation scores. Eur J Clin Nutr. 1993;47:559-566.  [PubMed]  [DOI]  [Cited in This Article: ]
45.  Centers for Disease Control and Prevention. CDC Growth Charts: Percentile Data Files with LMS Values.  Available from: https://www.cdc.gov/growthcharts/percentile_data_files.htm.  [PubMed]  [DOI]  [Cited in This Article: ]
46.  Markowitz J, Grancher K, Kohn N, Lesser M, Daum F. A multicenter trial of 6-mercaptopurine and prednisone in children with newly diagnosed Crohn’s disease. Gastroenterology. 2000;119:895-902.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 562]  [Cited by in F6Publishing: 590]  [Article Influence: 24.6]  [Reference Citation Analysis (0)]
47.  Hyams JS, Dubinsky MC, Baldassano RN, Colletti RB, Cucchiara S, Escher J, Faubion W, Fell J, Gold BD, Griffiths A. Infliximab Is Not Associated With Increased Risk of Malignancy or Hemophagocytic Lymphohistiocytosis in Pediatric Patients With Inflammatory Bowel Disease. Gastroenterology. 2017;152:1901-1914.e3.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 141]  [Cited by in F6Publishing: 152]  [Article Influence: 21.7]  [Reference Citation Analysis (0)]
48.  Diamanti A, Basso MS, Gambarara M, Papadatou B, Bracci F, Noto C, Castro M. Positive impact of blocking tumor necrosis factor alpha on the nutritional status in pediatric Crohn’s disease patients. Int J Colorectal Dis. 2009;24:19-25.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 26]  [Cited by in F6Publishing: 27]  [Article Influence: 1.8]  [Reference Citation Analysis (0)]
49.  Wiese D, Lashner B, Seidner D. Measurement of nutrition status in Crohn’s disease patients receiving infliximab therapy. Nutr Clin Pract. 2008;23:551-556.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 29]  [Cited by in F6Publishing: 29]  [Article Influence: 1.8]  [Reference Citation Analysis (0)]
50.  Thayu M, Denson LA, Shults J, Zemel BS, Burnham JM, Baldassano RN, Howard KM, Ryan A, Leonard MB. Determinants of changes in linear growth and body composition in incident pediatric Crohn’s disease. Gastroenterology. 2010;139:430-438.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 87]  [Cited by in F6Publishing: 91]  [Article Influence: 6.5]  [Reference Citation Analysis (0)]
51.  Subramaniam K, Fallon K, Ruut T, Lane D, McKay R, Shadbolt B, Ang S, Cook M, Platten J, Pavli P. Infliximab reverses inflammatory muscle wasting (sarcopenia) in Crohn’s disease. Aliment Pharmacol Ther. 2015;41:419-428.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 82]  [Cited by in F6Publishing: 73]  [Article Influence: 8.1]  [Reference Citation Analysis (0)]
52.  Tang K, Murano G, Wagner H, Nogueira L, Wagner PD, Tang A, Dalton ND, Gu Y, Peterson KL, Breen EC. Impaired exercise capacity and skeletal muscle function in a mouse model of pulmonary inflammation. J Appl Physiol (1985). 2013;114:1340-1350.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 15]  [Cited by in F6Publishing: 16]  [Article Influence: 1.5]  [Reference Citation Analysis (0)]
53.  Ordás I, Mould DR, Feagan BG, Sandborn WJ. Anti-TNF monoclonal antibodies in inflammatory bowel disease: pharmacokinetics-based dosing paradigms. Clin Pharmacol Ther. 2012;91:635-646.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 353]  [Cited by in F6Publishing: 357]  [Article Influence: 29.8]  [Reference Citation Analysis (0)]
54.  Ternant D, Aubourg A, Magdelaine-Beuzelin C, Degenne D, Watier H, Picon L, Paintaud G. Infliximab pharmacokinetics in inflammatory bowel disease patients. Ther Drug Monit. 2008;30:523-529.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 138]  [Cited by in F6Publishing: 150]  [Article Influence: 9.4]  [Reference Citation Analysis (0)]
55.  Schneider SM, Al-Jaouni R, Filippi J, Wiroth JB, Zeanandin G, Arab K, Hébuterne X. Sarcopenia is prevalent in patients with Crohn’s disease in clinical remission. Inflamm Bowel Dis. 2008;14:1562-1568.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 95]  [Cited by in F6Publishing: 102]  [Article Influence: 6.4]  [Reference Citation Analysis (0)]
56.  Reimund JM, Arondel Y, Escalin G, Finck G, Baumann R, Duclos B. Immune activation and nutritional status in adult Crohn’s disease patients. Dig Liver Dis. 2005;37:424-431.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 35]  [Cited by in F6Publishing: 36]  [Article Influence: 1.9]  [Reference Citation Analysis (0)]