OBJECTIVE Assess the prevalence of nonalcoholic fatty liver disease (NAFLD) and of liver fibrosis associated with nonalcoholic steatohepatitis in unselected patients with type 2 diabetes mellitus (T2DM). RESEARCH DESIGN AND METHODS A total of 561 patients with T2DM (age: 60 ± 11 years; BMI: 33.4 ± 6.2 kg/m2; and HbA1c: 7.5 ± 1.8%) attending primary care or endocrinology outpatient clinics and unaware of having NAFLD were recruited. At the visit, volunteers were invited to be screened by elastography for steatosis and fibrosis by controlled attenuation parameter (≥274 dB/m) and liver stiffness measurement (LSM; ≥7.0 kPa), respectively. Secondary causes of liver disease were ruled out. Diagnostic panels for prediction of advanced fibrosis, such as AST-to-platelet ratio index (APRI) and Fibrosis-4 (FIB-4) index, were also measured. A liver biopsy was performed if results were suggestive of fibrosis. RESULTS The prevalence of steatosis was 70% and of fibrosis 21% (LSM ≥7.0 kPa). Moderate fibrosis (F2: LSM ≥8.2 kPa) was present in 6% and severe fibrosis or cirrhosis (F3–4: LSM ≥9.7 kPa) in 9%, similar to that estimated by FIB-4 and APRI panels. Noninvasive testing was consistent with liver biopsy results. Elevated AST or ALT ≥40 units/L was present in a minority of patients with steatosis (8% and 13%, respectively) or with liver fibrosis (18% and 28%, respectively). This suggests that AST/ALT alone are insufficient as initial screening. However, performance may be enhanced by imaging (e.g., transient elastography) and plasma diagnostic panels (e.g., FIB-4 and APRI). CONCLUSIONS Moderate-to-advanced fibrosis (F2 or higher), an established risk factor for cirrhosis and overall mortality, affects at least one out of six (15%) patients with T2DM. These results support the American Diabetes Association guidelines to screen for clinically significant fibrosis in patients with T2DM with steatosis or elevated ALT.

Purpose: CYP2D6 bioactivates codeine and tramadol, with intermediate and poor metabolizers (IMs and PMs) expected to have impaired analgesia. This pragmatic proof-of-concept trial tested the effects of CYP2D6-guided opioid prescribing on pain control. Methods: Participants with chronic pain (94% on an opioid) from 7 clinics were enrolled into CYP2D6-guided (n=235) or usual care (n=135) arms using a cluster design. CYP2D6 phenotypes were assigned based on genotype and CYP2D6 inhibitor use, with recommendations for opioid prescribing made in the CYP2D6-guided arm. Pain was assessed at baseline and 3 months using PROMIS ® measures. Results: On stepwise multiple linear regression, the primary outcome of composite pain intensity (composite of current pain and worst and average pain in the past week) among IM/PMs initially prescribed tramadol/codeine (n=45) had greater improvement in the CYP2D6-guided versus usual care arm (−1.01±1.59 versus −0.40±1.20; adj- P =0.016); 24% of CYP2D6-guided versus 0% of usual care participants reported ≥30% (clinically meaningful) reduction in the composite outcome. In contrast, among normal metabolizers prescribed tramadol or codeine at baseline, there was no difference in the change in composite pain intensity at 3 months between CYP2D6-guided (−0.61±1.39) and usual care (−0.54±1.69) groups (adj-P=0.540). Conclusion: These data support the potential benefits of CYP2D6-guided pain management.

Individualization of drug therapy, described as tailoring drug selection and drug dosing to a given patient, has been an objective of physicians and other health-care providers for centuries. An understanding of the pathogenesis of the disease, the mechanism of action of the drug, and exposure-response relationships provides the framework for individualization. There are many approaches to individualization: selecting an antibiotic based on minimum effective concentrations and bacterial sensitivity, population (sparse sample) pharmacokinetics, therapeutic drug monitoring and, more recently, pharmacogenomics. The goal of individualization is to optimize the efficacy of a drug, minimize its toxicity, or both. With the growth of technology and databases, drug-disease-trial models and simulation have become useful for integrating information from many different domains. Physiology-based pharmacokinetic (PBPK) models have provided a mechanistic approach to individualization, and clinical trial designs such as those involving enrichment have also enabled individualization. In the future, "-omics" technologies, vaccines, ex vivo gene therapy, and the so-called "diseases-in-a-dish" will provide additional strategies to achieve individualization.

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