Assessment of the End Point Adjudication Process on the Results of the Platelet-Oriented Inhibition in New TIA and Minor Ischemic Stroke (POINT) Trial: A Secondary Analysis.

Importance: Debate continues about the value of event adjudication in clinical trials and whether independent centralized assessments improve reliability and validity of study results in masked randomized trials compared with local, investigator-assessed end points. Objective: To assess the results of the adjudicated end point process in the Platelet-Oriented Inhibition in New TIA and Minor Ischemic Stroke (POINT) trial by comparing end points assessed by local site investigators with centrally adjudicated end points. Design, Setting, and Participants: This is an ad hoc secondary analysis of a randomized, double-blind clinical trial comparing safety and effectiveness of clopidogrel bisulphate plus aspirin vs placebo plus aspirin. Patients received either 600 mg of clopidogrel bisulphate on day 1, then 75 mg per day through day 90 plus 50 to 325 mg of aspirin per day, or the same range of dosages of placebo plus aspirin. Investigators reported all potential end points; independent masked adjudicators were randomly assigned to review using definitions specified in the study protocol. This was a multicenter study; 269 international sites in 10 countries enrolled from May 28, 2010, to December 19, 2017. The study enrolled 4881 patients 18 years or older with transient ischemic attack or minor acute ischemic stroke within 12 hours of symptom onset and followed for 90 days from randomization; last follow-up was completed in March 2018. Main Outcomes and Measures: Independent adjudicators external to the study and masked to study treatment assignment adjudicated 467 primary and secondary effectiveness outcomes and major and minor bleeding events, including the primary composite end point, which was the risk of a composite of major ischemic events at 90 days, defined as ischemic stroke, myocardial infarction, or death from an ischemic vascular event. The primary safety end point was major hemorrhage. All components of the primary and safety outcomes were adjudicated. Results: In this secondary analysis of an international randomized clinical trial, a total of 269 sites worldwide randomized 4881 patients (median age, 65.0 years; interquartile range, 55-74 years); 55.0% were male. The primary results have been published previously. The hazard ratios for clopidogrel plus aspirin vs placebo plus aspirin for the primary composite end point were 0.75 (95% CI, 0.59-0.95) for adjudicator-assessed events and 0.76 (95% CI, 0.60-0.95) for investigator-assessed events. Agreement between adjudicator and investigator assessments was 90.7%. The hazard ratios for clopidogrel plus aspirin vs placebo plus aspirin for the primary safety end point were 2.32 (95% CI, 1.10-4.87) for adjudicator-assessed events and 2.58 (95% CI, 1.19-5.58) for investigator-assessed events, with an agreement rate of 77.5%. Conclusions and Relevance: Independent end point adjudication did not substantially alter estimates of the primary treatment effectiveness in the POINT trial. Trial Registration: ClinicalTrials.gov identifier: NCT00991029.

The asymptotic maximal procedure for subject randomization in clinical trials.

The maximal procedure is a restricted randomization method that maximizes the number of feasible allocation sequences under the constraints of the maximum tolerated imbalance and the allocation sequence length. It assigns an equal probability to all feasible sequences. However, its implementation is not easy due to the lack of the Markovian property of the conditional allocation probabilities. In this paper, we propose the asymptotic maximal procedure, which replaces the sequence-length-dependent conditional allocation probabilities with their asymptotic values. The new randomization procedure is compared with the original maximal procedure and few other randomization procedures with the maximum tolerated imbalance via simulations and is found to be a practical choice for future clinical trials.

When Should ED Physicians Use an HIE? Predicting Presence of Patient Data in an HIE.

OBJECTIVES: Health information exchanges (HIEs) make possible the construction of databases to characterize patients as multisystem users (MSUs), those visiting emergency departments (EDs) of more than one hospital system within a region during a 1-year period. HIE data can inform an algorithm highlighting patients for whom information is more likely to be present in the HIE, leading to a higher yield HIE experience for ED clinicians and incentivizing their adoption of HIE. Our objective was to describe patient characteristics that determine which ED patients are likely to be MSUs and therefore have information in an HIE, thereby improving the efficacy of HIE use and increasing ED clinician perception of HIE benefit. METHODS: Data were extracted from a regional HIE involving four hospital systems (11 EDs) in the Charleston, South Carolina area. We used univariate and multivariable regression analyses to develop a predictive model for MSU status. RESULTS: Factors associated with MSUs included younger age groups, dual-payer insurance status, living in counties that are more rural, and one of at least six specific diagnoses: mental disorders; symptoms, signs, and ill-defined conditions; complications of pregnancy, childbirth, and puerperium; diseases of the musculoskeletal system; injury and poisoning; and diseases of the blood and blood-forming organs. For patients with multiple ED visits during 1 year, 43.8% of MSUs had ≥4 visits, compared with 18.0% of non-MSUs (P < 0.0001). CONCLUSIONS: This predictive model accurately identified patients cared for at multiple hospital systems and can be used to increase the likelihood that time spent logging on to the HIE will be a value-added effort for emergency physicians.

Managing competing demands in the implementation of response-adaptive randomization in a large multicenter phase III acute stroke trial.

It is well known that competing demands exist between the control of important covariate imbalance and protection of treatment allocation randomness in confirmative clinical trials. When implementing a response-adaptive randomization algorithm in confirmative clinical trials designed under a frequentist framework, additional competing demands emerge between the shift of the treatment allocation ratio and the preservation of the power. Based on a large multicenter phase III stroke trial, we present a patient randomization scheme that manages these competing demands by applying a newly developed minimal sufficient balancing design for baseline covariates and a cap on the treatment allocation ratio shift in order to protect the allocation randomness and the power. Statistical properties of this randomization plan are studied by computer simulation. Trial operation characteristics, such as patient enrollment rate and primary outcome response delay, are also incorporated into the randomization plan.

Flexible analytical methods for adding a treatment arm mid-study to an ongoing clinical trial.

It is not uncommon to have experimental drugs under different stages of development for a given disease area. Methods are proposed for use when another treatment arm is to be added mid-study to an ongoing clinical trial. Monte Carlo simulation was used to compare potential analytical approaches for pairwise comparisons through a difference in means in independent normal populations including (1) a linear model adjusting for the design change (stage effect), (2) pooling data across the stages, or (3) the use of an adaptive combination test. In the presence of intra-stage correlation (or a non-ignorable fixed stage effect), simply pooling the data will result in a loss of power and will inflate the type I error rate. The linear model approach is more powerful, but the adaptive methods allow for flexibility (re-estimating sample size). The flexibility to add a treatment arm to an ongoing trial may result in cost savings as treatments that become ready for testing can be added to ongoing studies.

Impact of safety monitoring on error probabilities of binary efficacy outcome analyses in large phase III group sequential trials.

In phase III clinical trials, some adverse events may not be rare or unexpected and can be considered as a primary measure for safety, particularly in trials of life-threatening conditions, such as stroke or traumatic brain injury. In some clinical areas, efficacy endpoints may be highly correlated with safety endpoints, yet the interim efficacy analyses under group sequential designs usually do not consider safety measures formally in the analyses. Furthermore, safety is often statistically monitored more frequently than efficacy measures. Because early termination of a trial in this situation can be triggered by either efficacy or safety, the impact of safety monitoring on the error probabilities of efficacy analyses may be nontrivial if the original design does not take the multiplicity effect into account. We estimate the actual error probabilities for a bivariate binary efficacy-safety response in large confirmatory group sequential trials. The estimated probabilities are verified by Monte Carlo simulation. Our findings suggest that type I error for efficacy analyses decreases as efficacy-safety correlation or between-group difference in the safety event rate increases. In addition, although power for efficacy is robust to misspecification of the efficacy-safety correlation, it decreases dramatically as between-group difference in the safety event rate increases.

Quantifying the cost in power of ignoring continuous covariate imbalances in clinical trial randomization.

Motivated by potentially serious imbalances of continuous baseline covariates in clinical trials, we investigated the cost in statistical power of ignoring the balance of these covariates in treatment allocation design for a logistic regression model. Based on data from a clinical trial of acute ischemic stroke treatment, computer simulations were used to create scenarios varying from the best possible baseline covariate balance to the worst possible imbalance, with multiple balance levels between the two extremes. The likelihood of each scenario occurring under simple randomization was evaluated. The power of the main effect test for treatment was examined. Our simulation results show that the worst possible imbalance is highly unlikely, but it can still occur under simple random allocation. Also, power loss could be nontrivial if balancing distributions of important continuous covariates were ignored even if adjustment is made in the analysis for important covariates. This situation, although unlikely, is more serious for trials with a small sample size and for covariates with large influence on primary outcome. These results suggest that attempts should be made to balance known prognostic continuous covariates at the design phase of a clinical trial even when adjustment is planned for these covariates at the analysis.

Two pharmacy interventions to improve refill persistence for chronic disease medications: a randomized, controlled trial.

BACKGROUND: Despite the proven effectiveness of many medications for chronic diseases, many patients do not refill their prescriptions in the required timeframe. OBJECTIVE: Compare the effectiveness of 3 pharmacist strategies to decrease time to refill of prescriptions for common chronic diseases. RESEARCH DESIGN/SUBJECTS: A randomized, controlled clinical trial with patients as the unit of randomization. Nine pharmacies within a medium-sized grocery store chain in South Carolina were included, representing urban, suburban, and rural areas and patients from a variety of socioeconomic backgrounds. Patients (n = 3048) overdue for refills for selected medications were randomized into 1 of 3 treatment arms: (1) pharmacist contact with the patient via telephone, (2) pharmacist contact with the patient's prescribing physician via facsimile, and (3) usual care. MEASURES: The primary outcome was the number of days from their recommended refill date until the patient filled a prescription for any medication relevant to his/her chronic disease. Prescription refill data were obtained routinely from the pharmacy district office's centralized database. Patient disposition codes were obtained by pharmacy employees. An intent-to-treat approach was used for all analyses. RESULTS: There were no significant differences by treatment arm in the study outcomes. CONCLUSIONS: Neither of the interventions is more effective than usual care at improving persistence of prescription refills for chronic diseases in overdue patients.