Jeffrey L. Mahon

A Randomized Study Comparing a Patient-Directed Hypertension Management Strategy With Usual Office-Based Care

This study aimed to compare the efficacy of a patient-directed management strategy with office-based management in maintaining blood pressure control in patients with chronic stable hypertension using a randomized trial of two months duration. The subjects had chronic stable essential hypertension without secondary causes or unstable cardiovascular disease and were selected through the offices of 11 family physicians and a tertiary care hypertension research unit. Patients were randomly assigned (2:1 ratio) to either a patient-directed management strategy using home blood pressure monitoring to adjust drug therapy if readings consistently exceeded defined limits, or office-based management through physician visits. The primary endpoint was the change from baseline in mean arterial pressure as determined by automatic ambulatory blood pressure monitoring. Secondary endpoints were changes in compliance, quality of life, and health care resource use. Ninety-one potential subjects were screened and 31 were randomized. Subjects in the patient-directed management group employed the drug adjustment protocols appropriately without complications. A significant difference in change in mean blood pressure was observed, favoring the patient-directed management (-0.95 mm Hg and +1.90 mm Hg, respectively, for patient-directed management and office-based management, P = .039). Compliance rates and quality of life scores were not significantly different between groups. Physician visits were more frequent in the patient-directed management group (1.05 v 0.20 visits/8 weeks, respectively, for patient-directed management and office-based management groups, P = .045). A patient-directed hypertensive management strategy may be feasible for patients with chronic stable hypertension. Such a strategy may improve blood pressure control compared with usual office-based care. However, physician visits may be increased using this strategy, at least in the short term.

The TrialNet Natural History Study of the Development of Type 1 Diabetes: objectives, design, and initial results

Objectives:  TrialNet’s goal to test preventions for type 1 diabetes has created an opportunity to gain new insights into the natural history of pre‐type 1 diabetes. The TrialNet Natural History Study (NHS) will assess the predictive value of existing and novel risk markers for type 1 diabetes and will find subjects for prevention trials.

Natural Course of Remission in IDDM During 1st yr After Diagnosis

Objective –To describe the natural course of clinical remission in insulin-dependent diabetes mellitus (IDDM) when insulin dose is minimized without loss of target glycemia and to identify factors that predict clinical remission. Research Design and Methods –Ninety-five patients, who were placebo-treated control subjects in the Canadian-European multicenter randomized trial of cyclosporin A in recent-onset IDDM, were studied. Results –The mean insulin dose decreased during the first months after diagnosis, with a nadir at 3 mo, when 27% of the patients did not require insulin to maintain target glycemia. At 1 yr, 10% of patients still did not need insulin. Patients not receiving insulin who had glycosylated hemoglobin within the normal range were called remitters. Mean basal and glucagon-stimulated C-peptide values were significantly (P < 0.025) higher in remitters than nonremitters at the start of the study. Therefore, all patients were divided into those with values above the mean stimulated C-peptide (0.4 nM) and those with values below the mean at entry. The probability of entering a remission with a stimulated C-peptide > 0.4 nM was 10 times as high (P < 0.05) as for those with a stimulated C-peptide below this level. Surprisingly, the beginning and end of the remission were associated with neither major changes in C-peptide levels nor islet cell antibody and insulin-antibody titer. A more rapid loss of stimulated C-peptide occurred in patients who lacked HLA-DR3 and -DR4 (P < 0.05 at mo 9). Conclusions –This study shows a higher spontaneous clinical remission rate than expected during the 1st yr after diagnosis. Preserved beta-cell function at entry predicts a greater chance of entering a remission, and a more rapid loss of beta-cell function was seen in patients without HLA-DR3 and -DR4.

Randomised study of n of 1 trials versus standard practice

Abstract Objective: To compare outcomes between groups of patients with irreversible chronic airflow limitation given theophylline by n of 1 trials or standard practice. Design: Randomised controlled study of n of 1 trials versus standard practice. Setting: Tertiary care centre outpatient department. Subjects: 31 patients with irreversible chronic airflow limitation who were unsure that theophylline was helpful after an open trial. Interventions: n Of 1 trials (single patient randomised multiple crossover comparisons of theophylline against placebo) followed published guidelines. For standard practice patients theophylline was stopped and resumed if their dyspnoea worsened; if their dyspnoea then improved theophylline was continued. For both groups a decision to continue or stop the drug was made within three months of randomisation. Main outcome measures: Exercise capacity as measured by six minute walking distance, quality of life as measured by the chronic respiratory disease questionnaire at baseline and six months after randomisation, and proportions of patients taking theophylline at six months. Results: 26 patients completed follow up. 47% fewer n of 1 trial patients than standard practice patients were taking theophylline at six months (5/14 versus 10/12; 95% confidence interval of difference 14% to 80%) without differences in exercise capacity or quality of life. Conclusions: n Of 1 trials led to less theophylline use without adverse effects on exercise capacity or quality of life in patients with irreversible chronic airflow limitation. These data directly support the presence of a clinically important bias towards unnecessary treatment during open prescription of theophylline for irreversible chronic airflow limitation. Confirmation in a larger study and similar studies for other problems appropriate for n of 1 trials are needed before widespread use of n of 1 trials can be advocated in routine clinical practice. Key messages Several common clinical problems suit n of 1 tri- als, including prescription of theophylline for irre- versible chronic airflow limitation, yet they are rarely used Among patients with chronic airflow limitation randomised to receive theophylline by an n of 1 trial or standard practice 47% fewer n of 1 trial patients were taking theophylline after six months without difference in exercise capacity or quality of life There seems to be a clinically important bias towards unnecessary treatment in standard prac- tice in this setting; n of 1 trials may limit this bias

The effects of valsartan and captopril on reducing microalbuminuria in patients with type 2 diabetes mellitus: a placebo-controlled trial

Abstract This multicenter, randomized, double-blind, placebo- and captopril-controlled, parallel-group trial evaluated the efficacy and safety of valsartan 80 and 160 mg in patients with incipient diabetic nephropathy. Patients were randomized to receive either valsartan 80 mg or 160 mg once daily, captopril 25 mg 3 times daily, or placebo. The study comprised 122 normotensive and treated hypertensive patients with type 2 diabetes mellitus and microalbuminuria (mean age, 56 years; 90% white). Treatment lasted 52 weeks. Efficacy variables included albumin excretion rate (AER), progression to clinical proteinuria, and glomerular filtration rate. In both the valsartan 80-mg (n = 31) and 160-mg (n = 31) groups and in the captopril group ( n=29), a decrease in AER from baseline was observed at end point, compared with an increase in the placebo group (n = 31). The positive effect of valsartan 80 mg versus placebo on AER was statistically significant (95% confidence interval [CI] for end point/baseline ratio: 0.365 to 0.966); the 95% CI for valsartan 160 mg versus placebo was 0.407 to 1.043. No significant differences in AER occurred in the comparisons of valsartan 80 mg and valsartan 160 mg versus captopril. The percentage of patients with trial drug—related adverse experiences was highest in the captopril group (34.5%). The corresponding values for the groups receiving valsartan 80 mg, valsartan 160 mg, and placebo were 9.7%, 22.6%, and 13.8%, respectively. Results of this study suggest that treatment with valsartan slows the progressive rise of AER in normotensive and treated hypertensive patients with type 2 diabetes mellitus with comparable efficacy and superior tolerability to captropril.

Surveying Physicians To Determine the Minimal Important Difference: Implications for Sample-Size Calculation

The minimal important difference (MID) is the smallest benefit of treatment that would result in clinicians recommending it to their patients. The MID is necessary to calculate sample size for randomized clinical trials, but its chosen value is often arbitrary. This study set out to determine the practicability of surveying physicians to elicit the MID for clinical trial sample-size calculation. Using a mail survey, we elicited the MID of different physician specialties (family medicine, internal medicine, vascular surgery) for using propranolol to slow abdominal aortic aneurysm (AAA) growth assuming that propranolol was efficacious in this condition. We used different outcome measures (growth rate or proportion of patients requiring surgery) and different methods of data presentation for the proportion of patients requiring surgery (absolute risk reduction or number needed to treat). The MID varied significantly by physician specialty, experience with AAA and propranolol, and the method used to elicit the MID. Consequently, sample-size calculations using these various MIDs varied from 116 to 3015. Future attempts to elicit the MID need to consider carefully who is surveyed, how data are presented, and how opinions are elicited.

N-of-1 (Single-Patient) Trials for Statin-Related Myalgia

Context Differentiating statin-related myalgia from myalgia due to other causes can be difficult and largely relies on subjective responses to open-label cessation or reinstitution of therapy. Contribution In this proof-of-concept study, patients previously reporting symptoms while receiving statins had several pairs of double-blind statin or placebo challenges (n-of-1 trials). None of the patients had a statistically significant difference in myalgia or other pain measures during statin therapy compared with placebo, and most resumed statin therapy after reviewing their results. Implication N-of-1 trials are a feasible and potentially useful tool to examine myalgia during statin rechallenge in selected patients. The Editors Statin-related myopathy is an umbrella term that includes patients with myalgia (muscle symptoms without creatine kinase [CK] elevation), myositis (muscle symptoms with CK elevation), and rhabdomyolysis (1). Although older randomized clinical trials have shown the incidence of muscle symptoms with clinically significant CK elevations to be low (1% to 5%) (2, 3), recent trials have reported the incidence of statin-related muscle symptoms regardless of CK levels to be as high as 15% to 20% (4, 5). Thus, statin-related myopathy is common and is an important problem because it may lead to patients discontinuing a therapy that has been shown to improve cardiovascular outcomes. The diagnosis of statin-related myalgia in most patients is not optimum because there is no highly specific diagnostic test. Creatine kinase levels are usually normal or only slightly increased (6). Moreover, myalgia and changes in CK levels can often occur for other reasons, including physical exertion and fibromyalgia (7). Muscle biopsies are invasive and may not be congruent with symptoms or CK elevations (8, 9). Thus, the diagnosis of statin-related myalgia is primarily dependent on patients and physicians impressions of causality during open-label statin therapy. This approach can lead to false conclusions that statins cause myalgia because of inherent biases in unblinded, beforeafter therapeutic trials (10). N-of-1 trials (single-patient, randomized, multiple crossover, blinded comparisons of an active treatment vs. placebo) are the most effective way to limit these biases in individual patients because each patient serves as his or her own control (11). These trials have been used to optimize management for many chronic problems, including those associated with pain (12), but they have not been used for statin-related myalgia. We therefore conducted a proof-of-concept study to assess the feasibility and potential value of n-of-1 trials in patients with statin-related myalgia. We hypothesized that such trials would yield objective proof in some patients that their symptoms were (or were not) statin-related. We also assessed patients willingness to resume statin therapy after completion of their respective trials. Methods Design Overview Design of the n-of-1 trials was consistent with previously published guidelines (13). Each trial lasted up to 33 weeks and comprised a maximum of 3 statin and placebo treatment pairs assigned in random order (Figure 1). Because we only included patients who had previously developed myalgia within 3 weeks of open-label statin use (see Setting and Participants), we used 3-week treatment periods (statin or placebo) to allow for adequate time for myalgia to develop. For each patient, the specific statin and daily dose that had previously been associated with the development of myalgia were used in the respective n-of-1 trial. Figure 1. Study design. The study duration was 33 wk. After the baseline assessment at time 0, patients had 3 pairs of active drug (3 wk) and placebo (3 wk) exposures. Randomly assigned treatment pairs comprised 2 treatment periods (active therapy or placebo) separated by a 3-wk washout period. Treatment pairs were also separated by washout periods. A complete n-of-1 trial comprised 3 treatment pairs. Clinic visits occurred at baseline and at the end of each treatment period (solid arrows). Baseline scores for the visual analogue scales and Brief Pain Inventories were collected at time 0. Patients then completed these questionnaires at days 7, 14, and 21 in each treatment period. Treatment periods were separated by 3-week washout intervals to minimize carryover effects (13, 14). The duration was substantially longer than the washout of 100 hours measured for the statins (rosuvastatin and atorvastatin) with the longest half-lives (15 to 20 hours) (15) because some patients may report slower resolution of symptoms than predicted by pharmacokinetics (16). If patients developed symptoms, they were offered the option of discontinuing a treatment period early and crossing over to the other treatment period after a washout period. The trial could be stopped and the treatment assignment unblinded at any point if the patient was convinced that a clear difference had emerged between treatment periods. The order of the statin or placebo was randomly allocated within pairs according to a computer-generated list held by the hospital pharmacist, who had no contact with patients. Randomization was done by using the Web site www.randomizer.org, which generates a set of random numbers. A total of 30 sets of random numbers (numerals 1 [arbitrarily designated as placebo] or 2 [designated as active]) were generated for a total of 10 patients. We then used 3 of these sets per patient. Blinding was maintained by use of identical-looking dispensing bottles and capsules in which statin or placebo pills were compounded by the hospital pharmacy. Physicians and all other study personnel were blinded to the drug sequence. Setting and Participants We recruited patients aged 18 years or older through advertisements and from endocrinology clinics at a tertiary referral center. Patients were included if they had a history of hypercholesterolemia requiring statin therapy according to the Canadian Dyslipidemia Guidelines (17) and statin-related myalgia (as defined by the American College of Cardiology [1]) without clinically significant CK elevations (<3 times the upper limit of normal or <3 times the baseline value) occurring within 3 weeks of starting open-label statin therapy. We only included patients who could not tolerate statin therapy. Despite having previously tried and discontinued statin therapy for myalgia, all patients were willing to retry their prior statin. We excluded patients with a history of rhabdomyolysis, metabolic or inflammatory myopathy, or neuropathy and those who could not comply with the added demands of an n-of-1 trial. The study was approved by the Western University Research Ethics Board, and all participants provided informed consent. Outcomes and Follow-up The baseline visit included a history and physical examination; measurement of serum CK, aspartate aminotransferase, alanine aminotransferase, and creatinine levels; and a set of questionnaires that assessed symptoms of possible myalgia. We also recorded the most recent fasting low-density lipoprotein cholesterol (LDL-C) level that the patient had while not receiving a statin in the past year. We assessed patients for myalgia by using 2 self-completed visual analogue scales (VASs) and the Brief Pain Inventory (BPI) Short Form (18, 19). One VAS focused on myalgia (VAS myalgia score), and the second assessed a specific symptom identified by the patient as being the most troublesome during prior statin therapy (symptom-specific VAS score). The stem question for the myalgia VAS was, How severe is your muscle pain today? The patient-specific symptoms included generalized muscle pain, pain in a particular muscle group, muscle weakness, or muscle cramping. The stem question for the symptom-specific VAS was, How severe was your [X] today? in which X was replaced with the patients specific symptom. For both VAS questions, the patient responded by making a mark between 0 mm (no symptoms) and 100 mm (maximum intensity for the symptom in question) on a horizontal line. The BPI is a self-completed, validated measure of clinical pain (20). The pain severity score (PSS) (mean score of questions 3 to 6 of the BPI) and the pain interference score (PIS) (mean score of questions 9A to 9G of the BPI) were calculated (19). The PSS and PIS have scores ranging from 0 to 10, with higher scores indicating worse pain severity and pain interference, respectively. Patients completed the myalgia VAS, symptom-specific VAS, and BPI at baseline before commencing the n-of-1 trial. During each 3-week period (statin or placebo), each questionnaire was completed at the end of each week (that is, days 7, 14, and 21) (Figure 1). Because longer duration of exposure to statin should theoretically result in greater symptoms, we suspected that symptom intensity would be greatest on the last day of each completed week. A patient completing 3 full treatment pairs in an n-of-1 trial provided a total of 18 follow-up questionnaire sets (myalgia VAS, symptom-specific VAS, and BPI). If a patient found symptoms to be intolerable and wished to move to a washout period early, they were instructed to complete their questionnaires when they terminated the treatment period. At the follow-up study visits (weeks 3, 9, 15, 21, 27, and 33), we used pill counts to assess adherence; drew blood for CK, aspartate aminotransferase, alanine aminotransferase, and creatinine levels; recorded adverse events; and collected the questionnaires. Follow-up visits could be moved to earlier points if the treatment periods were terminated early. To maintain blinding, we did not measure serum LDL-C levels during the n-of-1 trials. At the conclusion of each n-of-1 trial, unblinded results of the VAS myalgia score, symptom-specific VAS score, PSS, and PIS were reviewed with the patient by the n-of-1 trial physician. The decision whether to resume a statin was based on this discussion. When

Zinc Transporter-8 Autoantibodies Improve Prediction of Type 1 Diabetes in Relatives Positive for the Standard Biochemical Autoantibodies

OBJECTIVE We assessed diabetes risk associated with zinc transporter-8 antibodies (ZnT8A), islet cell antibodies (ICA), and HLA type and age in relatives of people with type 1 diabetes with the standard biochemical autoantibodies (BAA) to insulin (IAA), GAD65 (GAD65A), and/or insulinoma-associated protein 2 antigen (IA-2A). RESEARCH DESIGN AND METHODS For this analysis, 2,256 relatives positive for at least one BAA, of whom 142 developed diabetes, were tested for ZnT8A, ICA, and HLA genotype followed by biannual oral glucose tolerance tests. ZnT8A were also tested in 911 randomly chosen antibody-negative relatives. RESULTS ZnT8A were associated with the other BAA (548 of 2,256 [24.3%] BAA+ vs. 8 of 911 [0.8%] BAA−, P < 0.001) and BAA number (177 of 1,683 [10.5%] single-, 221 of 384 [57.6%] double-, and 150 of 189 [79.4%] triple-BAA positivity, P < 0.001). The 4-year diabetes risk was higher in single BAA+ relatives with ZnT8A than ZnT8A− relatives (31 vs. 7%, P < 0.001). In multivariable analysis, age ≤20 years (hazard ratio 2.13, P = 0.03), IA-2A (2.15, P = 0.005), IAA (1.73, P = 0.01), ICA (2.37, P = 0.002), and ZnT8A (1.87, P = 0.03) independently predicted diabetes, whereas HLA type (high and moderate vs. low risk) and GAD65A did not (P = 0.81 and 0.86, respectively). CONCLUSIONS In relatives with one standard BAA, ZnT8A identified a subset at higher diabetes risk. ZnT8A predicted diabetes independently of ICA, the standard BAA, age, and HLA type. ZnT8A should be included in type 1 diabetes prediction and prevention studies.

Increasing the Accuracy of Oral Glucose Tolerance Testing and Extending Its Application to Individuals With Normal Glucose Tolerance for the Prediction of Type 1 Diabetes: The Diabetes Prevention Trial-Type 1

OBJECTIVE—We assessed the extent to which both standard and alternative indexes from 2-h oral glucose tolerance testing predict type 1 diabetes and whether oral glucose tolerance tests (OGTTs) predict type 1 diabetes in individuals with normal glucose tolerance. RESEARCH DESIGN AND METHODS—The prediction of type 1 diabetes from baseline OGTTs was studied in 704 Diabetes Prevention Trial-Type 1 participants (islet-cell autoantibody [ICA]-positive relatives of type 1 diabetic patients). The maximum follow-up was 7.4 years. Analyses utilized receiver-operator curves (ROCs), proportional hazards models, and survival curves. RESULTS—ROC areas under the curve (ROCAUCs) for both the AUC glucose (0.73 ± 0.02) and an OGTT prediction index (0.78 ± 0.02) were higher (P < 0.001) than those for the fasting (0.53 ± 0.02) and 2-h glucose (0.66 ± 0.02). ROCAUCs for the 60- and 90-min glucose (0.71 ± 0.02 and 0.72 ± 0.02, respectively) were also higher (P < 0.01) than those for the fasting and 2-h glucose. Among individuals with normal glucose tolerance, OGTTs were highly predictive, with 4th versus 1st quartile hazard ratios for the 2-h glucose, AUC glucose, and OGTT prediction index ranging from 3.77 to 5.30 (P < 0.001 for all). CONCLUSIONS—Certain alternative OGTT indexes appear to better predict type 1 diabetes than standard OGTT indexes in ICA-positive relatives of type 1 diabetic patients. Moreover, even among those with normal glucose tolerance, OGTTs are strongly predictive. This suggests that subtle metabolic abnormalities are present several years before the diagnosis of type 1 diabetes.

The Prediction of Type 1 Diabetes by Multiple Autoantibody Levels and Their Incorporation Into an Autoantibody Risk Score in Relatives of Type 1 Diabetic Patients

OBJECTIVE We assessed whether a risk score that incorporates levels of multiple islet autoantibodies could enhance the prediction of type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS TrialNet Natural History Study participants (n = 784) were tested for three autoantibodies (GADA, IA-2A, and mIAA) at their initial screening. Samples from those positive for at least one autoantibody were subsequently tested for ICA and ZnT8A. An autoantibody risk score (ABRS) was developed from a proportional hazards model that combined autoantibody levels from each autoantibody along with their designations of positivity and negativity. RESULTS The ABRS was strongly predictive of T1D (hazard ratio [with 95% CI] 2.72 [2.23–3.31], P < 0.001). Receiver operating characteristic curve areas (with 95% CI) for the ABRS revealed good predictability (0.84 [0.78–0.90] at 2 years, 0.81 [0.74–0.89] at 3 years, P < 0.001 for both). The composite of levels from the five autoantibodies was predictive of T1D before and after an adjustment for the positivity or negativity of autoantibodies (P < 0.001). The findings were almost identical when ICA was excluded from the risk score model. The combination of the ABRS and the previously validated Diabetes Prevention Trial–Type 1 Risk Score (DPTRS) predicted T1D more accurately (0.93 [0.88–0.98] at 2 years, 0.91 [0.83–0.99] at 3 years) than either the DPTRS or the ABRS alone (P ≤ 0.01 for all comparisons). CONCLUSIONS These findings show the importance of considering autoantibody levels in assessing the risk of T1D. Moreover, levels of multiple autoantibodies can be incorporated into an ABRS that accurately predicts T1D.