Browsing by Author "Clark, Jeanne M."

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    Early Response to Preventive Strategies in the Diabetes Prevention Program
    (Springer, Part of Springer Science+Business Media, 2013-12) Maruthur, Nisa M.; Ma, Yong; Delahanty, Linda M.; Nelson, Julie A.; Aroda, Vanita; White, Neil H.; Marrero, David; Brancati, Frederick L.; Clark, Jeanne M.; Diabetes Prevention Program Research Group; Department of Medicine, IU School of Medicine
    BACKGROUND Recommendations for diabetes prevention in patients with prediabetes include lifestyle modification and metformin. However, the significance of early weight loss and glucose measurements when monitoring response to these proven interventions is unknown. OBJECTIVE To quantify the relationship between early measures of weight and glucose and subsequent diabetes in patients undergoing diabetes prevention interventions. DESIGN Analysis of results from a randomized controlled trial in 27 academic medical centers in the United States. PARTICIPANTS/INTERVENTIONS 3,041 adults with hyperglycemia randomized to lifestyle (n = 1,018), metformin (n = 1,036), or placebo (n = 987) with complete follow-up in The Diabetes Prevention Program. MAIN MEASURES Independent variables were weight loss at 6 and 12 months; fasting glucose (FG) at 6 months; hemoglobin A1c (HbA1c) at 6 months; and post-load glucose at 12 months. The main outcome was time to diabetes diagnosis. KEY RESULTS After 6 months, 604 participants developed diabetes in the lifestyle (n = 140), metformin (n = 206), and placebo (n = 258) arms over 2.7 years. In the lifestyle arm, 6-month weight loss predicted decreased diabetes risk in a graded fashion: adjusted HR (95 % CI) 0.65 (0.35–1.22), 0.62 (0.33–1.18), 0.46 (0.24–0.87), 0.34 (0.18–0.64), and 0.15 (0.07–0.30) for 0–<3 %, 3–<5 %, 5–<7 %, 7–<10 %, and ≥10 % weight loss, respectively (reference: weight gain). Attainment of optimal 6-month FG and HbA1c and 12-month post-load glucose predicted >60 % lower diabetes risk across arms. We found a significant interaction between 6-month weight loss and FG in the lifestyle arm (P = 0.038). CONCLUSION Weight and glucose at 6 and 12 months strongly predict lower subsequent diabetes risk with a lifestyle intervention; lower FG predicts lower risk even with substantial weight loss. Early reduction in glycemia is a stronger predictor of future diabetes risk than weight loss for metformin. We offer the first evidence to guide clinicians in making interval management decisions for high-risk patients undertaking measures to prevent diabetes.
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    Hepatic Fat in Participants With and Without Incident Diabetes in the Diabetes Prevention Program Outcome Study
    (The Endocrine Society, 2021) Goldberg, Ronald B.; Tripputi, Mark T.; Boyko, Edward J.; Budoff, Matthew; Chen, Zsu-Zsu; Clark, Jeanne M.; Dabelea, Dana M.; Edelstein, Sharon L.; Gerszten, Robert E.; Horton, Edward; Mather, Kieren J.; Perreault, Leigh; Temprosa, Marinella; Wallia, Amisha; Watson, Karol; Irfan, Zeb; Medicine, School of Medicine
    Context: There is little information about fatty liver in prediabetes as it transitions to early diabetes. Objective: This study is aimed at evaluating the prevalence and determinants of fatty liver in the Diabetes Prevention Program (DPP). Methods: We measured liver fat as liver attenuation (LA) in Hounsfield units (HU) in 1876 participants at ~14 years following randomization into the DPP, which tested the effects of lifestyle or metformin interventions versus standard care to prevent diabetes. LA was compared among intervention groups and in those with versus without diabetes, and associations with baseline and follow-up measurements of anthropometric and metabolic covariates were assessed. Results: There were no differences in liver fat between treatment groups at 14 years of follow-up. Participants with diabetes had lower LA (mean ± SD: 46 ± 16 vs 51 ± 14 HU; P < 0.001) and a greater prevalence of fatty liver (LA < 40 HU) (34% vs 17%; P < 0.001). Severity of metabolic abnormalities at the time of LA evaluation was associated with lower LA categories in a graded manner and more strongly in those with diabetes. Averaged annual fasting insulin (an index of insulin resistance [OR, 95% CI 1.76, 1.41-2.20]) waist circumference (1.63, 1.17-2.26), and triglyceride (1.42, 1.13-1.78), but not glucose, were independently associated with LA < 40 HU prevalence. Conclusion: Fatty liver is common in the early phases of diabetes development. The association of LA with insulin resistance, waist circumference, and triglyceride levels emphasizes the importance of these markers for hepatic steatosis in this population and that assessment of hepatic fat in early diabetes development is warranted.
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    Histologic Findings of Advanced Fibrosis and Cirrhosis in Patients With Nonalcoholic Fatty Liver Disease Who Have Normal Aminotransferase Levels
    (Wolters Kluwer, 2019-10-01) Gawrieh, Samer; Wilson, Laura A.; Cummings, Oscar W.; Clark, Jeanne M.; Loomba, Rohit; Hameed, Bilal; Abdelmalek, Manal F.; Dasarathy, Srinivasan; Neuschwander-Tetri, Brent A.; Kowdley, Kris; Kleiner, David; Doo, Edward; Tonascia, James; Sanyal, Arun; Chalasani, Naga; Network and the NASH Clinical Research; Medicine, School of Medicine
    Background and aims: Patients with nonalcoholic fatty liver disease (NAFLD) and normal aminotransferase levels may have advanced liver histology. We conducted a study to characterize the prevalence of and factors associated with advanced liver histology in patients with histologically characterized NAFLD and normal aminotransferase levels. Methods: We evaluated 534 adults with biopsy-proven NAFLD and ALT and AST < 40 U/L within 3 months of their liver biopsy. Histological phenotypes of primary interest were NASH with stage 2-3 fibrosis (NASH F2-3) and cirrhosis. Using multiple logistic regression models with Akaike’s Information Criteria (AIC), we identified variables associated with these histological phenotypes. We developed and internally validated their clinical prediction models. Results: The prevalence of NASH F2-F3 and cirrhosis were 19% and 7%, respectively. The best multiple regression AIC model for NASH F2-3 consisted of type 2 diabetes, White race, lower LDL, lower platelet count, higher AST/ALT ratio, higher serum triglycerides, and hypertension. The best AIC model for cirrhosis consisted of lower platelet count, lower AST/ALT ratio, higher BMI, and female sex. The area under the receiver operator curves of the prediction models were 0.70 (95% CI: 0.65-0.76) for detecting NASH-F2-3 and 0.85 (95% CI: 0.77-0.92) for detecting cirrhosis. When models were fixed at maximum Youden’s index, their positive and negative predictive values were 35% and 88% for NASH F2-F3 and 30% and 98% for cirrhosis, respectively. Conclusion: Clinically significant histological phenotypes are observed in patients with NAFLD and normal aminotransferase levels. Our models can assist the clinicians in excluding advanced liver histology in NAFLD patients with normal aminotransferase levels.
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    Low and High Birth Weights Are Risk Factors for Nonalcoholic Fatty Liver Disease in Children
    (Elsevier, 2017-08) Newton, Kimberly P.; Feldman, Haruna S.; Chambers, Christina D.; Wilson, Laura; Behling, Cynthia; Clark, Jeanne M.; Molleston, Jean P.; Chalasani, Naga; Sanyal, Arun J.; Fishbein, Mark H.; Lavine, Joel E.; Schwimmer, Jeffrey B.; Medicine, School of Medicine
    OBJECTIVES: To examine the distribution of birth weight in children with nonalcoholic fatty liver disease (NAFLD) compared with the general US population, and to investigate the relationship between birth weight and severity of NAFLD. STUDY DESIGN: A multicenter, cross-sectional study of children with biopsy-proven NAFLD enrolled in the Nonalcoholic Steatohepatitis Clinical Research Network Database. Birth weight was categorized as low birth weight (LBW), normal birth weight (NBW), or high birth weight (HBW) and compared with the birth weight distribution in the general US population. The severity of liver histology was assessed by birth weight category. RESULTS: Children with NAFLD (n = 538) had overrepresentation of both LBW and HBW compared with the general US population (LBW, 9.3%; NBW, 75.8%; HBW, 14.9% vs LBW, 6.1%; NBW, 83.5%; HBW 10.5%; P < .0001). Children with HBW had significantly greater odds of having more severe steatosis (OR, 1.82, 95% CI. 1.15-2.88) and nonalcoholic steatohepatitis (OR, 2.03; 95% CI, 1.21-3.40) compared with children with NBW. In addition, children with NAFLD and LBW had significantly greater odds of having advanced fibrosis (OR, 2.23; 95% CI, 1.08-4.62). CONCLUSION: Birth weight involves maternal and in utero factors that may have long-lasting consequences. Children with both LBW and HBW may be at increased risk for developing NAFLD. Among children with NAFLD, those with LBW or HBW appear to be at increased risk for more severe disease.
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    Validation of the accuracy of the FAST™ score for detecting patients with at-risk nonalcoholic steatohepatitis (NASH) in a North American cohort and comparison to other non-invasive algorithms
    (PLOS, 2022) Woreta, Tinsay A.; Van Natta, Mark L.; Lazo, Mariana; Krishnan, Arunkumar; Neuschwander-Tetri, Brent A.; Loomba, Rohit; Diehl, Anna Mae; Abdelmalek, Manal F.; Chalasani, Naga; Gawrieh, Samer; Dasarathy, Srinivasan; Vuppalanchi, Raj; Siddiqui, Mohammad S.; Kowdley, Kris V.; McCullough, Arthur; Terrault, Norah A.; Behling, Cynthia; Kleiner, David E.; Fishbein, Mark; Hertel, Paula; Wilson, Laura A.; Mitchell, Emily P.; Miriel, Laura A.; Clark, Jeanne M.; Tonascia, James; Sanyal, Arun J.; NASH Clinical Research Network; Medicine, School of Medicine
    Background and aims: Management of patients with NASH who are at elevated risk of progressing to complications of cirrhosis (at-risk NASH) would be enhanced by an accurate, noninvasive diagnostic test. The new FAST™ score, a combination of FibroScan® parameters liver stiffness measurement (LSM) and controlled attenuation parameter (CAP) and aspartate aminotransferase (AST), has shown good diagnostic accuracy for at-risk NASH (area-under-the-Receiver-Operating-Characteristic [AUROC] = 0.80) in European cohorts. We aimed to validate the FAST™ score in a North American cohort and show how its diagnostic accuracy might vary by patient mix. We also compared the diagnostic performance of FAST™ to other non-invasive algorithms for the diagnosis of at-risk NASH. Methods: We studied adults with biopsy-proven non-alcoholic fatty liver disease (NAFLD) from the multicenter NASH Clinical Research Network (CRN) Adult Database 2 (DB2) cohort study. At-risk-NASH was histologically defined as definite NASH with a NAFLD Activity Score (NAS) ≥ 4 with at least 1 point in each category and a fibrosis stage ≥ 2. We used the Echosens® formula for FAST™ from LSM (kPa), CAP (dB/m), and AST (U/L), and the FAST™-based Rule-Out (FAST™ ≤ 0.35, sensitivity = 90%) and Rule-In (FAST™ ≥ 0.67, specificity = 90%) zones. We determined the following diagnostic performance measures: AUROC, sensitivity (Se), specificity (Sp), positive predictive value (PPV), and negative predictive value (NPV); these were calculated for the total sample and by subgroups of patients and by FibroScan® exam features. We also compared the at-risk NASH diagnostic performance of FAST™ to other non-invasive algorithms: NAFLD fibrosis score (NFS), Fibrosis-4 (FIB-4) index, and AST to platelet ratio index (APRI). Results: The NASH CRN population of 585 patients was 62% female, 79% white, 14% Hispanic, and 73% obese; the mean age was 51 years. The mean (SD) AST and ALT were 50 (37) U/L and 66 (45) U/L, respectively. 214 (37%) had at-risk NASH. The AUROC of FAST™ for at-risk NASH in the NASH CRN study population was 0.81 (95% CI: 0.77, 0.84. Using FAST™-based cut-offs, 35% of patients were ruled-out with corresponding NPV = 0.90 and 27% of patients were ruled-in with corresponding PPV = 0.69. The diagnostic accuracy of FAST™ was higher in non-whites vs. whites (AUROC: 0.91 vs 0.78; p = 0.001), and in patients with a normal BMI vs. BMI > 35 kg/m2 (AUROC: 0.94 vs 0.78, p = 0.008). No differences were observed by other patient characteristics or FibroScan® exam features. The FAST™ score had higher diagnostic accuracy than other non-invasive algorithms for the diagnosis of at-risk NASH (AUROC for NFS, FIB-4, and APRI 0.67, 0.73, 0.74, respectively). Conclusion: We validated the FAST™ score for the diagnosis of at-risk NASH in a large, multi-racial population in North America, with a prevalence of at-risk NASH of 37%. Diagnostic performance varies by subgroups of NASH patients defined by race and obesity. FAST™ performed better than other non-invasive algorithms for the diagnosis of at-risk NASH.