Barry D. Dickinson

Drug interactions between oral contraceptives and antibiotics

OBJECTIVE To evaluate the evidence on possible drug interactions between antibiotics and oral contraceptives (OCs) that may lead to OC failure. DATA SOURCES MEDLINE and Lexis/Nexis Medical Library searches for 1966–1999 using the key word “oral contraceptives,” cross‐indexed with the terms “antibiotics,” “adverse effects,” and “pregnancy,” and MEDLINE search using the additional MeSH term “drug interactions.” No language restrictions were used. METHODS OF STUDY SELECTION A total of 167 articles were retrieved for analysis. Another 32 articles were identified by review of the references cited in these publications. Articles were selected based on their ability to provide information on the relationship between antibiotic therapy and OC efficacy in otherwise compliant users (defined as women with unplanned pregnancies who reported compliance with their OC regimen). Additionally, studies that either directly measured the effects of antibiotics on the pharmacokinetics of OC components, or that analyzed the effects of antibiotics on measures of ovulation in OC users were accepted. TABULATION, INTEGRATION, AND RESULTS At least 30 cases have been reported of pregnancies occurring in women taking OCs and antibiotics, particularly rifampin. Approximately 20% of pregnant women reporting to family planning or abortion clinics reported concomitant OC and antibiotic use. Information from adverse event reporting databases generally mirrors the types of information gleaned from these case reports and clinical surveys and accounts for approximately one‐third of reported cases. Retrospective surveys, primarily from dermatology‐based practices, also have reported 24 pregnancies in OC users who concomitantly received therapy with antibiotics, most commonly tetracyclines and penicillins. Apparent OC failure rates in clinical surveys were within the usual range expected for patterns of typical use. In pooled results obtained from relatively small populations, oral antibiotics, with the exception of rifampin, have not significantly affected the pharmacokinetics of ethinyl estradiol, levonorgestrel, and norethindrone or reduced the serum concentrations of gonadotropins. However, individual patients have been identified who experienced significant decreases in the plasma concentration of these components of OCs and who appeared to ovulate. CONCLUSION Rifampin impairs the effectiveness of OCs. Pharmacokinetic studies of other antibiotics have not shown any systematic interaction between antibiotics and OC steroids. However, individual patients do show large decreases in the plasma concentrations of ethinyl estradiol when they take certain other antibiotics, notably tetracycline and penicillin derivatives. Because it is not possible to identify these women in advance, a cautious approach is advised.

Pharmacogenomic knowledge gaps and educational resource needs among physicians in selected specialties

Background The use of pharmacogenomic testing in the clinical setting has the potential to improve the safety and effectiveness of drug therapy, yet studies have revealed that physicians lack knowledge about the topic of pharmacogenomics, and are not prepared to implement it in the clinical setting. This study further explores the pharmacogenomic knowledge deficit and educational resource needs among physicians. Materials and methods Surveys of primary care physicians, cardiologists, and psychiatrists were conducted. Results Few physicians reported familiarity with the topic of pharmacogenomics, but more reported confidence in their knowledge about the influence of genetics on drug therapy. Only a small minority had undergone formal training in pharmacogenomics, and a majority reported being unsure what type of pharmacogenomic tests were appropriate to order for the clinical situation. Respondents indicated that an ideal pharmacogenomic educational resource should be electronic and include such components as how to interpret pharmacogenomic test results, recommendations for prescribing, population subgroups most likely to be affected, and contact information for laboratories offering pharmacogenomic testing. Conclusion Physicians continue to demonstrate pharmacogenomic knowledge gaps, and are unsure about how to use pharmacogenomic testing in clinical practice. Educational resources that are clinically oriented and easily accessible are preferred by physicians, and may best support appropriate clinical implementation of pharmacogenomics.

Genomic-based tools for the risk assessment, management, and prevention of type 2 diabetes.

Type 2 diabetes (T2D) is a common and serious disorder and is a significant risk factor for the development of cardiovascular disease, neuropathy, nephropathy, retinopathy, periodontal disease, and foot ulcers and amputations. The burden of disease associated with T2D has led to an emphasis on early identification of the millions of individuals at high risk so that management and intervention strategies can be effectively implemented before disease progression begins. With increasing knowledge about the genetic basis of T2D, several genomic-based strategies have been tested for their ability to improve risk assessment, management and prevention. Genetic risk scores have been developed with the intent to more accurately identify those at risk for T2D and to potentially improve motivation and adherence to lifestyle modification programs. In addition, evidence is building that oral antihyperglycemic medications are subject to pharmacogenomic variation in a substantial number of patients, suggesting genomics may soon play a role in determining the most effective therapies. T2D is a complex disease that affects individuals differently, and risk prediction and treatment may be challenging for health care providers. Genomic approaches hold promise for their potential to improve risk prediction and tailor management for individual patients and to contribute to better health outcomes for those with T2D.