In 2004, approximately 34% of children in the United States were overweight or obese (1,2). Overweight and obesity are among the most important public health concerns of our time, with the prevalence of these conditions increasing dramatically during the past several decades worldwide (3–5). As a result, a rising incidence of associated comorbidities has negatively affected the health of children and young adults globally (6,7). In addition, overweight may negatively affect the natural history of other conditions through its effects on multiple organ systems. Hepatitis C virus (HCV) infection is 1 of the most common chronic liver diseases, affecting approximately 170 million people worldwide (8,9). Overweight and obesity have been associated with greater degrees of steatosis and fibrosis in HCV-infected adults (9–13); however, the precise role of overweight in the progression of pediatric chronic HCV liver disease remains to be established.
In the United States, approximately 0.2% of 6- to 12-year-olds and 0.4% of 13- to 19-year-olds, or approximately 174,000 children, are anti-HCV positive (14). Extrapolation from adult data, in which 75% of HCV antibody-positive subjects are HCV RNA positive, leads to an estimate of 130,500 chronically infected children in the United States. Although treatment of HCV has improved in recent years, a significant portion of individuals (up to 40% to 50% of pediatric patients carrying HCV genotype 1 or 4) still fail to respond to therapy for unclear reasons (15,16). A number of determinants associated with diminished response to therapy have been identified. Some of these determinants include older age, longer duration of infection, African American race, infection with HCV genotype 1 or 4, high serum HCV RNA, advanced fibrosis, presence of steatosis and insulin resistance, and possibly overweight (17–20). Of these, only overweight is potentially modifiable.
The role of overweight in antiviral treatment response for HCV has been previously evaluated in adults (21–23), but the data have been confounded by the frequent use of standard adult doses of antiviral medications that are not adjusted for weight (21–23). Few published reports have evaluated the effect of body mass index (BMI) on the response to HCV treatment using weight-based dosing. Among these, Tarantino et al (24) noted a higher mean BMI in nonresponders as compared to responders, but in multivariate analysis, BMI was not independently associated with response to therapy. Gheorghe et al (25) also evaluated weight-based dosing and found that overweight was not associated with diminished response to therapy. They concluded that the negative impact of increasing weight on virological response can be overcome by dosing pegylated interferon (PEG IFN) and ribavirin according to body weight. Whether higher BMI is independently associated with lower response to HCV treatment and whether this can be overcome by adjustment of medication dose remain to be definitively established.
Children offer a unique opportunity to evaluate the independent effects of overweight in the setting of chronic HCV infection. Children and young adults infected with HCV tend to have lower degrees of fibrosis, minimal comorbidities, and shorter duration of infection when compared with older adults. In addition, the universal use of weight-based dosing in pediatric medicine precludes confounding due to relative underdosing. The question of whether overweight or obesity decreases response to HCV therapy in youth has relevance for the HCV-infected population at large. Therefore, we performed a 2-part retrospective investigation to evaluate the role of BMI in HCV progression and response to therapy in young people.
PATIENTS AND METHODS
Patient Population
All of the patients with HCV infection evaluated at Children's Hospital Boston between June 1, 1993 and June 1, 2007 were considered possible study subjects. All of the participants had a history of established HCV infection confirmed by HCV RNA testing.
Subjects in the first part of the study (STUDY 1) were selected to evaluate whether increased BMI is associated with more advanced steatosis or fibrosis in chronic HCV infection. Patients who underwent a liver biopsy during the study period and who were 20 years of age or younger at the time of biopsy were included. Patients with missing height or weight information and patients who had liver disorders in addition to HCV were excluded. A total of 102 subjects met inclusion criteria for STUDY 1. Ninety-three percent of subjects were non-Hispanic caucasians. Fifty-one percent of patients were boys. Routes of HCV acquisition were perinatal (42%), via transfusion (41%), from illegal substance abuse (2%), or unknown (15%). Median age was 14.8 years with a range of 4.6 to 19.8 years. Four subjects carried genotype 2, 7 subjects carried genotype 3, and 1 carried genotype 4; the rest carried genotype 1.
The second part of the study (STUDY 2) consisted of subjects who were selected to determine the association between BMI and response to HCV therapy. Subjects were included if they underwent treatment for HCV infection during the study period and if they were 20 years of age or younger at completion of their treatment. Dosages of medications used were as follows: IFN, 3 MU/m2 to a maximum of 5 MU/m2 subcutaneously 3 times per week; or PEG IFN-α 2a, 180 μg/1.73 m2 to a maximum of 180 μg subcutaneously once per week, with or without oral ribavirin (15 mg · kg−1 · day−1). Subjects with missing weight or height at the start or end of therapy and patients with liver disorders in addition to hepatitis C were excluded. Sixty-two patients met inclusion and exclusion criteria for STUDY 2. Compliance with treatment was assessed by patient and family interviews at each visit. Routes of HCV acquisition were perinatal (47%), via transfusion (47%), or unknown (15%). Four patients acquired the infection by substance abuse, and these were excluded because of concerns with HCV treatment compliance. The final group consisted of 58 subjects, and all had higher than 90% compliance rates. The majority (95%) was non-Hispanic caucasian. The median age of subjects in STUDY 2 was 13.0 years, with a range between 5.9 and 19.2 years, among which 51% were boys. Hepatitis C virus RNA levels before therapy ranged from 2654 IU/mL to 7,866,000 IU/mL, with a mean of 1,158,611 IU/mL.
Patient Characteristics and Laboratory Determinations
For STUDY 1, patients' demographic characteristics included sex, age, and race or ethnicity. Method of HCV contraction, infection duration, and HCV genotype were assessed. HCV infection was confirmed by qualitative and quantitative measurements of HCV RNA using reverse-transcription polymerase chain reaction. All of the liver biopsies were evaluated by a single pathologist, who was blinded to response to therapy and BMI. Fibrosis was scored using the METAVIR scoring system (26). Steatosis was categorized as none, mild, moderate, and severe. Anthropometrical data, including patients' weight and height, were measured at the time of biopsy. In addition, available weights and height 1 year (±3 months) before biopsy were reviewed. For STUDY 2, demographic characteristics and laboratory determinations were the same as in STUDY 1 with the exception of liver histology data, which was not collected. In STUDY 2, anthropometrical data, including patients' weight and height, were measured at the start and at the end of antiviral therapy. Available weights and heights 1 year (±3 months) before initiation of treatment were reviewed.
Calculations
BMI was calculated as weight (kg) divided by height squared (m2). BMI percentile for age and sex as well as z scores were obtained from Centers for Disease Control and Prevention–smoothed percentile curves of the National Health and Nutrition Examination Survey data. For the purposes of this investigation, overweight was defined as BMI higher than the 85th percentile for equivalent age and sex. Infection duration was estimated based on subjects' medical history. For subjects with vertically acquired HCV infection, age was used as duration. In STUDY 2, change in BMI z score was calculated from the difference in BMI z score at the start and at the end of therapy.
Statistical Analysis
Descriptive statistics for continuous variables were expressed as either means with standard deviations (SDs) or medians with ranges. For descriptive purposes and for identification of potential confounding factors in STUDY 1, an initial univariate analysis was performed on the simple associations between steatosis and fibrosis categories with age at the time of liver biopsy, sex, and infection duration. Stability of BMI was assessed by evaluating the correlation between BMI z scores at the time of biopsy and available BMI z scores from 1 year prior. To evaluate the association between BMI and steatosis as well as fibrosis, a general linear model was constructed in which BMI z scores were regressed on steatosis and fibrosis categories. Age at the time of liver biopsy, sex, race or ethnicity, history of alcohol or illegal substance use, infection duration, and HCV genotype were also considered in the model. Because of the sparseness of their distributions, METAVIR fibrosis scores 3 and 4 were collapsed into a single category and steatosis was dichotomized as absent or present.
In STUDY 2, subjects were classified into sustained virologic responders (SVRs) or nonresponders (no SVR). On the basis of standard definitions, patients were considered SVR if they had undetectable HCV RNA levels 24 weeks following the end of HCV treatment and nonresponders if their HCV RNA was detectable at that time. Univariate analysis was performed comparing SVRs and nonresponders with regards to sex, age at the start of therapy, infection duration, HCV genotype, frequency of overweight, and therapy regimen. Stability of BMI was assessed by evaluating the correlation between baseline BMI z score and available BMI z scores from 1 year prior. A multivariate model was then created using logistic regression to evaluate the effect of baseline BMI z score and possible confounding factors on response to therapy. Change in BMI z score was included in the model to account for the possibility that this variable could be independently associated with the outcome. Possible confounding variables were evaluated, and the final model was chosen in consideration of relevant confounders. JMP Statistical Software (SAS Institute, Cary, NC) was used for all of the statistical analyses.
RESULTS
STUDY 1: Association of BMI With Disease Stage
Steatosis was distributed as follows: none (73.5%), mild (21.5%), moderate (5%), and severe (0%). Steatosis categories were collapsed into absent (73.5%) or present (26.5%). Fibrosis was distributed as follows: METAVIR 0 (8.8%), 1 (52%), 2 (15.7%), 3 (20.6%), and 4 (2.9%). Fibrosis stages 3 and 4 were collapsed into METAVIR 3 to 4 (23.5%). Mean age and mean infection duration by steatosis and fibrosis categories are given in Table 1. No statistically significant differences in age or infection duration by steatosis and fibrosis levels were noted (P > 0.32). Sex distribution was similar among patients with and without steatosis (
;)
TABLE 1: Mean age and mean infection duration by steatosis and fibrosis categories (STUDY 1)
= 0.31, P = 0.58) as well as across the different fibrosis categories (
= 3.8, P = 0.29). Among the 31 subjects with available BMI z scores 1 year before biopsy, a strong correlation was noted between that measure and BMI z score at the time of biopsy (r = 0.83, P < 0.0001), illustrating the stability of BMI.
Overweight Is Associated With Progression of Chronic HCV Infection in Young People
In univariate analysis within STUDY 1, the presence of steatosis was statistically associated with higher mean (±SE) BMI percentiles (72nd ± 5.8 vs 58th ± 3.5; (F(1,101) = 4.2, P = 0.04) corresponding to mean BMI z scores of 0.79 versus 0.17 (Fig. 1). Variables including age, sex, infection duration, and fibrosis were considered in a multivariate model as possible confounders, but the results were unchanged (data not shown). Exclusion of subjects with genotype 3 did not alter the results. Among the 7 subjects with genotype 3, mean BMI for subjects with steatosis was the 75th percentile (mean BMI z score = 0.92), whereas for those without steatosis it was the 44th percentile (mean BMI z score = −0.26), although this was not statistically significant, possibly secondary to the small sample size (P = 0.36). Mean (±SE) BMI percentiles across the 4 categories of fibrosis were relatively constant (METAVIR 0 = 61st ± 10.3, METAVIR 1 = 57th ± 4.2, METAVIR 2 = 70th ± 7.7, METAVIR 3–4 = 67th ± 6.3), and not statistically different (F(3,98) = 1.1, P = 0.36) (Fig. 2). In a similar analysis, fibrosis score was then dichotomized as “low” (METAVIR 0–1) or “high” (METAVIR 2–4), and subjects were classified based on their BMI z scores as either “overweight” or “lean” (using the cutoff point of BMI z score higher than 1, which corresponds to higher than the 85th percentile for age and sex). Although not statistically significant (χ2 = 1.32, P = 0.25), compared to lean subjects, overweight patients included a higher percentage of individuals with “high” fibrosis (47% vs 35%).
FIGURE 1: Body mass index percentile scores by steatosis category. The presence of steatosis was significantly associated with greater mean (±SE) BMI percentile scores (72nd ± 5.8 vs 58th ± 3.5) F(1,101) = 4.2, P = 0.04. Diamonds represent 95% confidence intervals around the mean. Box plots represent subject-to-subject variation (box ends represent 25th–75th percentiles).
FIGURE 2: Body mass index (BMI) percentile scores by fibrosis stage. Mean (±SE) BMI percentile scores across the 4 categories of fibrosis were relatively constant (METAVIR 0 = 61st ± 10.3, METAVIR 1 = 57th ± 4.2, METAVIR 2 = 70th ± 7.7, METAVIR 3–4 = 67th ± 6.3), and not statistically different (F[3,98] = 1.1, P = 0.36). Diamonds represent 95% confidence intervals around the mean. Box plots represent subject-to-subject variation (box ends represent 25th–75th percentiles).
STUDY 2: Association of BMI With Response to Therapy
There were 32 SVRs and 26 nonresponders to antiviral therapy. Demographic characteristics by response category are summarized in Table 2. When comparing SVRs with nonresponders, there were no statistically significant differences in sex, age, or infection duration. Not surprisingly, all but 1 nonresponder harbored HCV genotype 1, and sustained responders harbored genotypes 2, 3, and 4 in addition to 1. Forty-five percent of patients were treated with PEG IFN and ribavirin, 22% with standard IFN and ribavirin, whereas the remainder received either standard IFN (14%) or PEG IFN alone (19%). Although a larger percentage of responders than nonresponders had been treated with the combination of PEG IFN and ribavirin (53% vs 35%), there were no statistically significant differences between the 2 comparison groups with regard to regimen received (testing the frequency of use of PEG IFN or ribavirin vs other treatment by response to therapy, (
TABLE 2: Demographic characteristics by response to therapy (STUDY 2)
= 1.99, P = 0.16). There were 27 subjects with available BMI z score 1 year before treatment. Among these, a strong correlation was also noted between baseline BMI z score and BMI z score from 1 year prior (r = 0.975, P < 0.0001).
Diminished Response to Antiviral Therapy With Increased BMI in HCV Infection
There was a greater percentage of overweight subjects among nonresponders (42%) compared to responders (19%), which was statistically significant (
= 3.84, P = 0.05). In addition, nonresponders to treatment had a higher mean (±SE) BMI percentile (70th ± 7.4) when compared to responders (50th ± 6.5) (P = 0.04) (Fig. 3). Thus, there was a univariate association between baseline BMI and response to therapy.
FIGURE 3: Body mass index (BMI) percentile scores by response to therapy. Mean (±SE) BMI percentile scores were higher for hepatitis C virus (HCV) treatment nonresponders (NR) than for sustained virologic responders (SVR) (70th ± 7.4 vs 50th ± 6.5, P = 0.04, respectively).
Association Between Higher Baseline BMI and Response to Therapy Is Not Explained by Confounders
To explore the possibility of confounding by other variables, a multivariable model was constructed. A logistic regression model in STUDY 2 evaluated SVR (yes or no) as the dependent variable and BMI z score, change in BMI z score during the course of therapy, HCV genotype (1 vs other), and use of ribavirin as independent variables. Change in BMI z score during therapy was initially included as a potentially relevant variable, given the fluctuations in weight that patients treated for HCV infection often experience. Inclusion of this variable was noted to be necessary because of the phenomenon of cooperative suppression, by which both higher baseline BMI z score and increase in BMI z score during therapy were negatively associated with the outcome (SVR), but inversely associated with each other. HCV genotype was included in the model because it is 1 of the most important determinants of response to therapy. The possibility of confounding by treatment modality was explored. The use of standard versus PEG IFN did not have a statistically significant impact on response to therapy (data not shown); however, use of ribavirin with any form of IFN was associated with a greater likelihood of response (
= 3.8, P = 0.05). There was no actual bias in this study, given that treatment was not chosen based on subjects' BMIs. Interestingly, we found a greater BMI z score among subjects that used ribavirin versus those that did not and this was at the borderline of significance. Mean BMI z score for subjects who were not treated with ribavirin was −0.1, whereas mean BMI z score for those who were treated with ribavirin was 0.6, P = 0.048. To evaluate the independent effects of treatment modality from BMI, use of ribavirin was included in the multivariate model.
In the final model we found that increasing baseline BMI z score was independently associated with lower odds of response to therapy (Table 3). From this model, it was calculated that 1 SD (1 z score unit) increase in baseline BMI z score is associated with a 12% decrease in the probability of SVR (Fig. 4).
TABLE 3: Logistic regression results (STUDY 2)
FIGURE 4: Logistic response curve for the independent effect of baseline body mass index (BMI) z score on sustained virologic response. Increasing baseline BMI z score was independently associated with lower odds of response to therapy. One unit increase in baseline BMI z score is associated with 12% decrease in response to therapy.
DISCUSSION
It is now clear that HCV has a number of unique metabolic effects on the host that, in turn, render the infected person more vulnerable to adverse health outcomes. These effects, including hepatic steatosis, insulin resistance, and lipid changes, seem to be additionally aggravated by the presence of overweight and obesity. Compounding matters, there is evidence that steatosis and insulin resistance also adversely affect the success of antiviral therapy for HCV (24,27–29). The proposed mechanisms linking obesity to diminished response to HCV therapy include decreased IFN bioavailability, altered cytokine function, and insulin resistance (8). However, definitive conclusions about the independent contribution of increased BMI to HCV progression and response to therapy have not been reached.
In this investigation, we selected a pediatric cohort to ensure the use of weight-based dosing in antiviral regimens and to minimize comorbidities and potential confounders. Two groups with unique inclusion and exclusion criteria were selected to address the primary questions of interest: (1) what is the role of overweight in progression of HCV liver disease? and (2) what is the effect of overweight on response to antiviral therapy?
In STUDY 1, we found that overweight is associated with the development of steatosis in HCV infection. This finding could not be accounted for by varying age or infection duration among our subjects. Although the role of race or ethnicity could not be formally evaluated in our study, having a relatively uniform cohort precludes possible confounding based on racial differences. Although statistical significance was not demonstrated, there was a trend toward more extensive fibrosis among those who were overweight. A retrospective investigation by Giannattasio et al (30) evaluated 64 children from Naples, Italy, undergoing liver biopsy. Their study population carried mostly HCV genotype 1, and the distribution of steatosis was similar to that in our investigation, namely, 25% of children with either mild or moderate steatosis and 75% without steatosis. Giannattasio et al did not find an association between BMI and steatosis in their cohort. The reason for the discrepancy in this regard with our results is unclear but may be explained by geographic and environmental differences. Interestingly, Giannattasio found an association between steatosis and greater fibrosis.
A more recent prospective multicenter trial, the Pegylated Interferon ± Ribavarin for Children with Hepatitis C (PEDS-C) trial, demonstrated results more consistent with our findings. This trial investigated a total of 121 children from 11 US centers (31). They found that 32% of their subjects had minimal and 9% had mild steatosis, and severe steatosis was not observed. There was a statistically significant correlation between presence of steatosis and overweight in accordance with our data. Similarly, they did not find a statistically significant correlation between fibrosis and BMI. However, when categorizing subjects as lean versus overweight they found significantly greater fibrosis in overweight children. In our investigation, we observed a trend toward greater fibrosis in overweight children but this did not achieve statistical significance. We believe that a stronger association between increasing BMI and fibrosis in our cohort would likely have been manifest with longer-term follow-up. In addition, it is also possible that newer methods that assess fibrosis in a more comprehensive manner, such as elastography, could yield more informative results. Nevertheless, in light of the evidence supporting a positive correlation between steatosis and fibrosis (10,12,32), it seems clear that overweight poses a risk of progression to steatosis and possibly future fibrosis in youth chronically infected with HCV.
In STUDY 2, we noted a univariate association between overweight and higher BMI percentile with nonresponse to HCV therapy. A statistically higher percentage of therapy nonresponders were overweight when compared to responders, and nonresponders had higher baseline mean BMI percentiles for equivalent age and sex. When evaluating additional variables, we observed that the use of ribavirin was associated with improved SVR, whereas genotype 1 or 4 were associated with diminished SVR. Increasing BMI z score during the course of therapy was also associated with diminished response to therapy, although this was not statistically significant. More important, a higher baseline BMI z score was independently associated with diminished response in multivariate analysis. In other words, the association noted in univariate analysis became stronger when accounting for important potential confounders. On the basis of the multivariate model, 1 unit increase in baseline BMI z score was associated with a 12% decrease in the probability of SVR. These results could not be explained by differences in infection duration, genotype, treatment used, or any of the other variables analyzed. It is noteworthy that in both STUDY 1 and STUDY 2, BMI proved to be stable because there was a strong and statistically significant correlation in BMI within a 1-year period. Stability of BMI for longer periods of time has also been previously demonstrated in both children and adults (33,34).
Although weight-based dosing was used in this study, the upper limits set on dosages are a potential limitation. However, review of BMI levels demonstrated that there were no morbidly obese patients in our cohort and there were no statistically significant differences in raw BMI values between the 2 comparison groups. Thus, it is unlikely that our findings could be explained by relative underdosing of overweight patients. Another potential limitation of this investigation is its retrospective nature. As a consequence, more than 1 treatment modality was included in this investigation. However, there was no selection bias, because treatment was not chosen based on subjects' BMI values. In addition, careful evaluation of treatment modality revealed that this was not a confounder in the association between BMI and response to therapy. Use of ribavirin was associated with improved response, but subjects who received ribavirin had higher mean BMI z scores and still had lower percentages of eradication of the virus, which does not support confounding by treatment. Through multivariate analyses, the independent effects of treatment and BMI were simultaneously evaluated in the final model and are reported in Table 3. Because of the retrospective nature of this investigation, there were no sample size calculations obtained a priori. Nevertheless, it is unlikely that a larger sample size would have significantly altered our results. Post-hoc calculations of frequency of overweight among patients with significant fibrosis suggest that approximately 560 subjects (280 subjects in the “high fibrosis” and 280 subjects in the “low fibrosis” groups) would be needed to statistically detect a 12% difference (47% vs 35%) at a power of 80%, based on a 2-tailed test with an alpha level of 0.05. The clinical significance of this difference in fibrosis is unclear, but it is possible that different methods of assessing fibrosis would be more appropriate and may lead to more meaningful results. On the basis of our results, controlling overweight before therapy should improve the probability of eradication of HCV infection. Despite the apparent protective effect of even very low BMIs from our results, at this point we would not recommend weight reduction below a BMI of the 50th percentile for age and sex. Prospective studies may provide a more accurate assessment of the actual effect of change in BMI before initiation of treatment on response to therapy through the evaluation of individual fluctuations in BMI. We postulate that such prospective studies may reveal stronger effects than those noted here, given the evidence available with regards to the effects of even moderate weight loss on abnormal liver enzymes or metabolic risk factors and other conditions (35,36).
CONCLUSIONS
In summary, our study suggests that overweight adversely affects the progression of chronic HCV liver disease by way of steatosis and demonstrates an association between overweight before therapy with diminished response to antiviral therapy using weight-based dosing in a cohort with minimal confounding variables. We believe our results are generalizable to the HCV-infected population at large, including children and adults. Prospective studies to evaluate the effect of weight control on response to HCV therapy will be critical in an attempt to halt the progression and improve the odds of sustained clearance of an otherwise progressive disease of young people.
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