Prospective assessment of patient-reported outcomes and estradiol and drug concentrations in patients experiencing toxicity from adjuvant aromatase inhibitors.

PURPOSE: Aromatase inhibitors (AI), which decrease circulating estradiol concentrations in post-menopausal women, are associated with toxicities that limit adherence. Approximately one-third of patients will tolerate a different AI after not tolerating the first. We report the effect of crossover from exemestane to letrozole or vice versa on patient-reported outcomes (PROs) and whether the success of crossover is due to lack of estrogen suppression. METHODS: Post-menopausal women enrolled on a prospective trial initiating AI therapy for early-stage breast cancer were randomized to exemestane or letrozole. Those that discontinued for intolerance were offered protocol-directed crossover to the other AI after a washout period. Changes in PROs, including pain [Visual Analog Scale (VAS)] and functional status [Health Assessment Questionnaire (HAQ)], were compared after 3 months on the first versus the second AI. Estradiol and drug concentrations were measured. RESULTS: Eighty-three patients participated in the crossover protocol, of whom 91.3% reported improvement in symptoms prior to starting the second AI. Functional status worsened less after 3 months with the second AI (HAQ mean change AI #1: 0.2 [SD 0.41] vs. AI #2: -0.05 [SD 0.36]; p = 0.001); change in pain scores was similar between the first and second AI (VAS mean change AI #1: 0.8 [SD 2.7] vs. AI #2: -0.2 [SD 2.8]; p = 0.19). No statistical differences in estradiol or drug concentrations were found between those that continued or discontinued AI after crossover. CONCLUSIONS: Although all AIs act via the same mechanism, a subset of patients intolerant to one AI report improved PROs with a different one. The mechanism of this tolerance remains unknown, but does not appear to be due to non-adherence to, or insufficient estrogen suppression by, the second AI.

In vivo assessment of the metabolic activity of CYP2D6 diplotypes and alleles.

AIMS: A prospectively enrolled patient cohort was used to assess whether the prediction of CYP2D6 phenotype activity from genotype data could be improved by reclassification of diplotypes or alleles. METHODS: Three hundred and fifty-five patients receiving tamoxifen 20 mg were genotyped for CYP2D6 and tamoxifen metabolite concentrations were measured. The endoxifen : N-desmethly-tamoxifen metabolic ratio, as a surrogate of CYP2D6 activity, was compared across four diplotypes (EM/IM, EM/PM, IM/IM, IM/PM) that are typically collapsed into an intermediate metabolizer (IM) phenotype. The relative metabolic activity of each allele type (UM, EM, IM, and PM) and each EM and IM allele was estimated for comparison with the activity scores typically assigned, 2, 1, 0.5 and 0, respectively. RESULTS: Each of the four IM diplotypes have distinct CYP2D6 activity from each other and from the EM and PM phenotype groups (each P < 0.05). Setting the activity of an EM allele at 1.0, the relative activities of a UM, IM and PM allele were 0.85, 0.67 and 0.52, respectively. The activity of the EM alleles were statistically different (P < 0.0001), with the CYP2D6*2 allele (scaled activity = 0.63) closer in activity to an IM than an EM allele. The activity of the IM alleles were also statistically different (P = 0.014). CONCLUSION: The current systems for translating CYP2D6 genotype into phenotype are not optimally calibrated, particularly in regards to IM diplotypes and the *2 allele. Additional research is needed to improve the prediction of CYP2D6 activity from genetic data for individualized dosing of CYP2D6 dependent drugs.

Literature based drug interaction prediction with clinical assessment using electronic medical records: novel myopathy associated drug interactions.

Drug-drug interactions (DDIs) are a common cause of adverse drug events. In this paper, we combined a literature discovery approach with analysis of a large electronic medical record database method to predict and evaluate novel DDIs. We predicted an initial set of 13197 potential DDIs based on substrates and inhibitors of cytochrome P450 (CYP) metabolism enzymes identified from published in vitro pharmacology experiments. Using a clinical repository of over 800,000 patients, we narrowed this theoretical set of DDIs to 3670 drug pairs actually taken by patients. Finally, we sought to identify novel combinations that synergistically increased the risk of myopathy. Five pairs were identified with their p-values less than 1E-06: loratadine and simvastatin (relative risk or RR = 1.69); loratadine and alprazolam (RR = 1.86); loratadine and duloxetine (RR = 1.94); loratadine and ropinirole (RR = 3.21); and promethazine and tegaserod (RR = 3.00). When taken together, each drug pair showed a significantly increased risk of myopathy when compared to the expected additive myopathy risk from taking either of the drugs alone. Based on additional literature data on in vitro drug metabolism and inhibition potency, loratadine and simvastatin and tegaserod and promethazine were predicted to have a strong DDI through the CYP3A4 and CYP2D6 enzymes, respectively. This new translational biomedical informatics approach supports not only detection of new clinically significant DDI signals, but also evaluation of their potential molecular mechanisms.

Assessment of vascular effects of tamoxifen and its metabolites on the rat perfused hindquarter vascular bed.

Tamoxifen has been suggested to produce beneficial cardiovascular effects, although the mechanisms for these effects are not fully known. Moreover, although tamoxifen metabolites may exhibit 30-100 times higher potency than the parent drug, no previous study has compared the effects produced by tamoxifen and its metabolites on vascular function. Here, we assessed the vascular responses to acetylcholine and sodium nitroprusside on perfused hindquarter vascular bed of rats treated with tamoxifen or its main metabolites (N-desmethyl-tamoxifen, 4-hydroxy-tamoxifen, and endoxifen) for 2 weeks. Plasma and whole-blood thiobarbituric acid reactive substances (TBARS) concentrations were determined using a fluorometric method. Plasma nitrite and NOx (nitrite + nitrate) concentrations were determined using an ozone-based chemiluminescence assay and Griess reaction, respectively. Treatment with tamoxifen reduced the responses to acetylcholine (pD(2) = 2.2 +/- 0.06 and 1.9 +/- 0.05 after vehicle and tamoxifen, respectively; P < 0.05), while its metabolites improved these responses (pD(2) = 2.5 +/- 0.04 after N-desmethyl-tamoxifen, 2.5 +/- 0.03 after 4-hydroxy-tamoxifen, and 2.6 +/- 0.08 after endoxifen; P < 0.01). Tamoxifen and its metabolites showed no effect on endothelial-independent responses to sodium nitroprusside (P > 0.05). While tamoxifen treatment resulted in significantly higher plasma and whole blood lipid peroxide levels (37% and 62%, respectively; both P < 0.05), its metabolites significantly decreased lipid peroxide levels (by approximately 50%; P < 0.05). While treatment with tamoxifen decreased the concentrations of markers of nitric oxide formation by approximately 50% (P < 0.05), tamoxifen metabolites had no effect on these parameters (P > 0.05). These results suggest that while tamoxifen produces detrimental effects, its metabolites produce counteracting beneficial effects on the vascular system and on nitric oxide/reactive oxygen species formation.

Pharmacokinetics of ibutilide in patients with heart failure due to left ventricular systolic dysfunction.

STUDY OBJECTIVE: To assess whether the increased risk of ibutilide-induced torsade de pointes in patients with heart failure may be due to increased ibutilide exposure, we sought to determine if the pharmacokinetics of ibutilide are altered in patients with heart failure due to left ventricular systolic dysfunction. DESIGN: Multicenter, prospective pharmacokinetic study. SETTING: Four academic medical centers in the United States. PATIENTS: Sixteen adult patients with atrial fibrillation or atrial flutter requiring conversion to normal sinus rhythm: six patients who had New York Heart Association (NYHA) class II or III heart failure due to left ventricular dysfunction (mean +/- SD left ventricular ejection fraction [LVEF] 30 +/- 9%); 10 patients who did not have left ventricular dysfunction (mean +/- SD LVEF 54 +/- 5% in six of these 10 patients) served as controls. INTERVENTION: All patients received a single dose of ibutilide 1.0 mg administered intravenously over 10 minutes. Blood samples were obtained through an indwelling catheter in the contralateral arm before ibutilide administration, at the end of the infusion, and at 5, 15, 30, 45 minutes and 1, 1.5, 2, 3, 4, 6, 8, 10, 12, 24, and 48 hours after the infusion. MEASUREMENTS AND MAIN RESULTS: Serum ibutilide concentrations were determined by using high-performance liquid chromatography and mass spectrometry. No significant differences were noted between the heart failure and normal left ventricular function groups in the following parameters: maximum serum ibutilide concentration (median [interquartile range] 3.8 [2.3-5.7] vs 5.8 [3.1-14.4] microg/L, p=0.31), area under the serum concentration-time curve from time zero extrapolated to infinity (mean +/- SD 11.0 +/- 9.4 vs 13.2 +/- 10.6 microg*hr/L, p=0.88), steady-state volume of distribution (1380 +/- 334 vs 1390 +/- 964 L, p=0.99), systemic clearance (129 +/- 60 vs 125 +/- 81 L/hr, p=0.92), or half-life (12.5 +/- 10.7 vs 12.4 +/- 8.6 hrs, p=0.99). CONCLUSION: The pharmacokinetics of ibutilide do not appear to be altered in patients with NYHA class II or III heart failure due to left ventricular systolic dysfunction. Therefore, the increased risk of ibutilide-induced torsade de pointes in patients with heart failure does not appear to be due to increased ibutilide exposure.

A mixture model approach in gene-gene and gene-environmental interactions for binary phenotypes.

In translational research, a genetic association study of a binary outcome has a twofold aim: test whether genetic/environmental variables or their combinations are associated with a clinical phenotype, and determine how those combinations are grouped to predict the phenotype (i.e., which combinations have a similarly distributed phenotype, and which ones have differently distributed phenotypes). The second part of this aim has high clinical appeal, because it can directly facilitate clinical decisions. Although traditional logistic regression can detect gene-gene or gene-environmental interaction effects on binary phenotypes, they cannot decisively determine how genotype combinations are grouped to predict the phenotype. Our proposed mixture model approach is valuable in this context. It concurrently detects main and interaction effects of genetic and environmental variables through a likelihood ratio test (LRT) and conducts phenotype cluster analysis based on genetic and environmental variable combinations. The theoretical distribution of the proposed mixture model's likelihood ratio test is robust not only to small sample size but also to unequal sample size in various genotype and environmental subgroups. Hypothesis testing through a likelihood ratio test results in a fast algorithm for p-value calculations. Extensive simulation studies demonstrate that mixture model, overall test in logistic regression, and Monte Carlo based logic regression constantly possess the best power to detect multi-way gene/environmental combinations. The mixture model approach has the highest recovery probability to recover the true partition in the simulation studies. Its applications are exemplified in interim data analyses for two cancer studies.