Stochastic curtailment tests for phase II trial with time-to-event outcome using the concept of relative time in the case of non-proportional hazards.

As part of the drug development process, interim analysis is frequently used to design efficient phase II clinical trials. A stochastic curtailment framework is often deployed wherein a decision to continue or curtail the trial is taken at each interim look based on the likelihood of observing a positive or negative treatment effect if the trial were to continue to its anticipated end. Thus, curtailment can take place due to evidence of early efficacy or futility. Traditionally, in the case of time-to-event endpoints, interim monitoring is conducted in a two-arm clinical trial using the log-rank test, often with the assumption of proportional hazards. However, when this is violated, the log-rank test may not be appropriate, resulting in loss of power and subsequently inaccurate sample sizes. In this paper, we propose stochastic curtailment methods for two-arm phase II trial with the flexibility to allow non-proportional hazards. The proposed methods are built utilizing the concept of relative time assuming that the survival times in the two treatment arms follow two different Weibull distributions. Three methods - conditional power, predictive power and Bayesian predictive probability - are discussed along with corresponding sample size calculations. The monitoring strategy is discussed with a real-life example.

Sample size reestimation and Bayesian predictive probability for single-arm clinical trials with a time-to-event endpoint using Weibull distribution with unknown shape parameter.

This manuscript consists of two topics. Firstly, we explore the utility of internal pilot study (IPS) approach for reestimating sample size at an interim stage when a reliable estimate of the nuisance shape parameter of the Weibull distribution for modeling survival data is unavailable during the planning phase of a study. Although IPS approach can help rescue the study power, it is noted that the adjusted sample size can be as much as twice the initially planned sample size, which may put substantial practical constraints to continue the study. Secondly, we discuss Bayesian predictive probability for conducting interim analyses to obtain preliminary evidence of efficacy or futility of an experimental treatment warranting early termination of a clinical trial. In the context of single-arm clinical trials with time-to-event endpoints following Weibull distribution, we present the calculation of the Bayesian predictive probability when the shape parameter of the Weibull distribution is unknown. Based on the data accumulated at the interim, we propose two approaches which rely on the posterior mode or the entire posterior distribution of the shape parameter. To account for uncertainty in the shape parameter, it is recommended to incorporate its entire posterior distribution in our calculation.

Using Cognitive Behavioral Therapy for Insomnia in People with Type 2 Diabetes, Pilot RCT Part I: Sleep and Concomitant Symptom.

OBJECTIVE/BACKGROUND: The primary aim of this study was to examine the effect of Cognitive Behavioral Therapy for Insomnia (CBT-I) on the severity of insomnia in people with Type 2 diabetes (T2D) compared to a health education (HE) control group. The secondary aim was to explore the effect of CBT-I on other sleep outcomes and concomitant symptoms. PARTICIPANTS: Twenty-eight participants with T2D were randomly assigned to CBT-I (n = 14) or HE (n = 14). METHODS: Validated assessments were used at baseline and post intervention to assess sleep outcomes and concomitant symptoms. In addition, actigraph and sleep diaries were used to measure sleep parameters. Independent sample t tests and Mann-Whitney U tests were utilized to measure between-group differences in the mean change scores. RESULTS: Participants in the CBT-I group showed higher improvements in the following mean change scores compared to the HE group: insomnia symptoms (d = 1.78; p < .001), sleep quality (d = 1.53; p =.001), sleep self-efficacy (d = 1.67; p < .001). Both actigraph and sleep diary showed improvements in sleep latency and sleep efficiency in the CBT-I group as compared to the HE group. In addition, participants in the CBT-I group showed greater improvement in the mean change scores of depression symptoms (d = 1.49; p = .002) and anxiety symptoms (d = 0.88; p = .04) compared to the HE group. CONCLUSION: This study identified a clinically meaningful effect of CBT-I on sleep outcomes and concomitant symptoms in people with T2D and insomnia symptoms. Further work is needed to investigate the long-term effects of CBT-I in people with T2D and insomnia symptoms.

Some design considerations incorporating early futility for single-arm clinical trials with time-to-event primary endpoints using Weibull distribution.

Sample size calculation is an essential component of the planning phase of a clinical trial. In the context of single-arm clinical trials with time-to-event (TTE) endpoints, only a few options with limited design features are available. Motivated from ethical or practical considerations, two-stage designs are implemented for single-arm studies to obtain early evidence of futility. A major drawback of such designs is that early stopping may only occur at the conclusion of the first stage, even if lack of efficacy becomes apparent at any other time point over the course of the clinical trial. In this manuscript, we attempt to fill some existing gaps in the literature related to single-arm clinical trials with TTE endpoints. We propose a parametric maximum likelihood estimate-based test whose variance component accounts for the expected proportion of loss to follow-up and different accrual patterns (early, late, or uniform accrual). For the proposed method, we present three stochastic curtailment methods (conditional power, predictive power, Bayesian predictive probability) which can be employed for efficacy or futility testing purposes. Finally, we discuss the implementation of group sequential designs for obtaining an early evidence of efficacy or futility at pre-planned timings of interim analyses. Through extensive simulations, it is shown that our proposed method performs well for designing these studies with moderate to large sample sizes. Some examples are presented to demonstrate various aspects of the stochastic curtailment and repeated significance testing methods presented in this manuscript.

Sample size calculation for two-arm trials with time-to-event endpoint for nonproportional hazards using the concept of Relative Time when inference is built on comparing Weibull distributions.

Sample size calculations for two-arm clinical trials with a time-to-event endpoint have traditionally used the assumption of proportional hazards (PH) or the assumption of exponentially distributed survival times. Available software provides methods for sample size calculation using a nonparametric logrank test, Schoenfeld's formula for Cox PH model, or parametric calculations specific to the exponential distribution. In cases where the PH assumption is not valid, the first-choice method is to compute sample size assuming a piecewise linear survival curve (Lakatos approach) for both the control and treatment arms with judiciously chosen cut-points. Recent advances in literature have used the assumption of Weibull distributed times for single-arm trials, and, newer methods have emerged that allow sample size calculations for two-arm trials using the assumption of proportional time (PT) while considering non-PH. These methods, however, always assume an instantaneous effect of treatment relative to control requiring that the effect size be defined by a single number whose magnitude is preserved throughout the trial duration. Here, we consider the scenarios where the hypothesized benefit of treatment relative to control may not be constant giving rise to the notion of Relative Time (RT). By assuming that survival times for control and treatment arm come from two different Weibull distributions with different location and shape parameters, we develop the methodology for sample size calculation for specific cases of both non-PH and non-PT. Simulations are conducted to assess the operation characteristics of the proposed method and a practical example is discussed.

Accurate Medication Adherence Measurement Using Administrative Data for Frequently Hospitalized Patients.

Background: Pharmacy administrative claims data remain an accessible and efficient source to measure medication adherence for frequently hospitalized patient populations that are systematically excluded from the landmark drug trials. Published pharmacotherapy studies use medication possession ratio (MPR) and proportion of days covered (PDC) to calculate medication adherence and usually fail to incorporate hospitalization and prescription overlap/gap from claims data. To make the cacophony of adherence measures clearer, this study created a refined hospital-adjusted algorithm to capture pharmacotherapy adherence among patients with end-stage renal disease (ESRD). Methods: The United States Renal Data System (USRDS) registry of ESRD was used to determine prescription-filling patterns of those receiving new prescriptions for oral P2Y12 inhibitors (P2Y12-I) between 2011 and 2015. P2Y12-I-naïve patients were followed until death, kidney transplantation, discontinuing medications, or loss to follow-up. After flagging/censoring key variables, the algorithm adjusted for hospital length of stay (LOS) and medication overlap. Hospital-adjusted medication adherence (HA-PDC) was calculated and compared with traditional MPR and PDC methods. Analyses were performed with SAS software. Results: Hospitalization occurred for 78% of the cohort (N = 46 514). The median LOS was 12 (interquartile range [IQR] = 2-34) days. MPR and PDC were 61% (IQR = 29%-94%) and 59% (IQR = 31%-93%), respectively. After applying adjustments for overlapping coverage days and hospital stays independently, HA-PDC adherence values changed in 41% and 52.7% of the cohort, respectively. When adjustments for overlap and hospital stay were made concurrently, HA-PDC adherence values changed in 68% of the cohort by 5.8% (HA-PDC median = 0.68, IQR = 0.31-0.93). HA-PDC declined over time (3M-6M-9M-12M). Nearly 48% of the cohort had a ≥30 days refill gap in the first 3 months, and this increased over time (P < .0001). Conclusions: Refill gaps should be investigated carefully to capture accurate pharmacotherapy adherence. HA-PDC measures increased adherence substantially when adjustments for hospital stay and medication refill overlaps are made. Furthermore, if hospitalizations were ignored for medications that are included in Medicare quality measures, such as Medicare STAR program, the apparent reduction in adherence might be associated with lower quality and health plan reimbursement.

The effects of cognitive behavioral therapy for insomnia in people with type 2 diabetes mellitus, pilot RCT part II: diabetes health outcomes.

BACKGROUND: Previous studies have shown the negative impact of sleep disturbances, specifically insomnia symptoms, on glucose metabolism for people with type 2 diabetes (T2D). People with insomnia symptoms are at risk of poor glycemic control and suboptimal diabetes self-care behavior (DSCB). Investigating the impact of a safe and effective intervention for individuals with T2D and insomnia symptoms on diabetes' health outcomes is needed. Therefore, the aim of this exploratory study is to examine the effects of Cognitive Behavioral Therapy for Insomnia (CBT-I) on glycemic control, DSCB, and fatigue. METHODS: Twenty-eight participants with T2D and insomnia symptoms, after passing an eligibility criteria at a medical research center, were randomly assigned to CBT-I (n = 14) or Health Education (HE; n = 14). The CBT-I and HE groups received 6 weekly one-hour sessions. This Randomized Controlled Trial (RCT) used a non-inferiority framework to test the effectiveness of CBT-I. Validated assessments were administered at baseline and post-intervention to assess glycemic control, DSCB, and fatigue. A Wilcoxon signed-rank test was utilized to compare within-group changes from baseline to post-intervention. A Mann-Whitney test was utilized to measure the between-group differences. Linear regression was used to assess the association between the blood glucose level and the number of days in the CBT-I group. RESULTS: The recruitment duration was from October 2018 to May 2019. A total of 13 participants completed the interventions in each group and are included in the final analysis. No adverse events, because of being a part of this RCT, were reported. CBT-I participants showed significantly greater improvement in glycemic control, DSCB, and fatigue. There was a significant association between the number of days in the CBT-I intervention with the blood glucose level before bedtime (B = -0.56, p = .009) and after awakening in the morning (B = -0.57, p = .007). CONCLUSIONS: This study demonstrated a clinically meaningful effect of CBT-I on glycemic control in people with T2D and insomnia symptoms. Also, CBT-I positively impacted daytime functioning, including DSCB and fatigue. Future research is needed to investigate the long-term effects of CBT-I on laboratory tests of glycemic control and to understand the underlying mechanisms of any improvements. TRIAL REGISTRATION: Clinical Trials Registry ( NCT03713996 ). Retrospectively registered on 22 October 2018.

Shorter length of hospital stay for hip fracture in those with dementia and without a known diagnosis of osteoporosis in the USA.

BACKGROUND: About 50% of all hospitalized fragility fracture cases in older Americans are hip fractures. Approximately 3/4 of fracture-related costs in the USA are attributable to hip fractures, and these are mostly covered by Medicare. Hip fracture patients with dementia, including Alzheimer's disease, have worse health outcomes including longer hospital length of stay (LOS) and charges. LOS and hospital charges for dementia patients are usually higher than for those without dementia. Research describing LOS and acute care charges for hip fractures has mostly focused on these outcomes in trauma patients without a known pre-admission diagnosis of osteoporosis (OP). Lack of documented diagnosis put patients at risk of not having an appropriate treatment plan for OP. Whether having a diagnosis of OP would have an effect on hospital outcomes in dementia patients has not been explored. We aim to investigate whether having a diagnosis of OP, dementia, or both has an effect on LOS and hospital charges. In addition, we also report prevalence of common comorbidities in the study population and their effects on hospital outcomes. METHODS: We conducted a cross-sectional analysis of claims data (2012-2013) for 2175 Medicare beneficiaries (≥65 years) in the USA. RESULTS: Compared to those without OP or dementia, patients with demenia only had a shorter LOS (by 5%; P = .04). Median LOS was 6 days (interquartile range [IQR]: 5-7), and the median hospital charges were $45,100 (IQR: 31,500 - 65,600). In general, White patients had a shorter LOS (by 7%), and those with CHF and ischemic heart disease (IHD) had longer LOS (by 7 and 4%, respectively). Hospital charges were 6% lower for women, and 16% lower for White patients. CONCLUSION: This is the first study evaluating LOS in dementia in the context of hip fracture which also disagrees with previous reporting about longer LOS in dementia patients. Patients with CHF and IHD remains at high risk for longer LOS regardless of their diagnosis of dementia or OP.

Trends for and Clinical Factors Associated with Choice of Oral P2Y12 Inhibitors for Patients on Chronic Dialysis.

BACKGROUND: Trends and clinical factors associated with prescribing choices for oral P2Y12 inhibitors (P2Y12-I) remain unknown for patients on chronic dialysis, i.e., with end-stage renal disease (ESRD). METHODS: From 2011-2014 U.S. Renal Data System registry, we identified 36,542 ESRD patients who received new prescriptions for P2Y12-I (median age 64.0 years and 54% males). Of the cohort, 93% were receiving hemodialysis and 7% on peritoneal dialysis. We analyzed trends and investigated clinical factors associated with specific P2Y12-I prescribed. RESULTS: Clopidogrel was prescribed for 95%, prasugrel for 3%, and ticagrelor for 2%. Clopidogrel was favored for those ≥75 years (18% of cohort). Compared to Caucasians, African Americans (36% of cohort) and Hispanics (19% of cohort) were less likely to receive prasugrel and ticagrelor (P<0.05). Patients receiving hemodialysis versus peritoneal dialysis were less likely to receive prasugrel over clopidogrel, adjusted odds ratio (aOR) 0.67 (0.55-0.82). Each additional year of dialysis decreased the odds of receiving prasugrel over clopidogrel, aOR 0.91 (0.85-0.98). History of atrial fibrillation reduced the odds of receiving ticagrelor or prasugrel over clopidogrel, aOR 0.69 (0.54-0.89) and 0.73 (0.60-0.89), respectively. Concomitant oral anticoagulant use was not associated with choice of P2Y12-I. Occurrence of non-ST segment elevation myocardial infarction or percutaneous coronary intervention within the 6-month period prior to the index date favored ticagrelor over prasugrel, aOR 1.31 (1.06-1.62) and 1.29 (1.01-1.66), respectively. However, prescribing trends favoring ticagrelor over prasugrel were not observed for deployment of drug-eluting, or multiple coronary stents. CONCLUSION: Between 2011 and 2014, clopidogrel remained the most common P2Y12-I whereas ticagrelor and prasugrel remained underutilized in ESRD patients. Prescribing practices for these drugs were based upon clinically approved indication for their use in the general population as well as perceived complexity of an ESRD patient including demographics, dialysis-related factors and comorbidities. Comparative effectiveness studies involving ESRD patients are needed to prove that ticagrelor and prasugrel are just as safe and effective as clopidogrel before clinicians can make informed decisions for choice of P2Y12-I in this patient population.

Association Between Gestational Diabetes and Incident Maternal CKD: The Coronary Artery Risk Development in Young Adults (CARDIA) Study.

BACKGROUND: Gestational diabetes mellitus (GDM) is associated with increased risk for diabetes mellitus, metabolic syndrome, and cardiovascular disease. We evaluated whether GDM is associated with incident chronic kidney disease (CKD), controlling for prepregnancy risk factors for both conditions. STUDY DESIGN: Prospective cohort. SETTING & PARTICIPANTS: Of 2,747 women (aged 18-30 years) enrolled in the Coronary Artery Risk Development in Young Adults (CARDIA) Study in 1985 to 86, we studied 820 who were nulliparous at enrollment, delivered at least 1 pregnancy longer than 20 weeks' gestation, and had kidney function measurements during 25 years of follow-up. PREDICTOR: GDM was self-reported by women for each pregnancy. OUTCOMES: CKD was defined as the development of estimated glomerular filtration rate (eGFR)<60mL/min/1.73m2 or urine albumin-creatinine ratio ≥ 25mg/g at any one CARDIA examination in years 10, 15, 20, or 25. MEASUREMENTS: HRs for developing CKD were estimated for women who developed GDM versus women without GDM using complementary log-log models, adjusting for prepregnancy age, systolic blood pressure, dyslipidemia, body mass index, smoking, education, eGFR, fasting glucose concentration, physical activity level (all measured at the CARDIA examination before the first pregnancy), race, and family history of diabetes. We explored for an interaction between race and GDM. RESULTS: During a mean follow-up of 20.8 years, 105 of 820 (12.8%) women developed CKD, predominantly increased urine albumin excretion (98 albuminuria only, 4 decreased eGFR only, and 3 both). There was evidence of a GDM-race interaction on CKD risk (P=0.06). Among black women, the adjusted HR for CKD was 1.96 (95% CI, 1.04-3.67) in GDM compared with those without GDM. Among white women, the HR was 0.65 (95% CI, 0.23-1.83). LIMITATIONS: Albuminuria was assessed by single untimed measurements of urine albumin and creatinine. CONCLUSIONS: GDM is associated with the subsequent development of albuminuria among black women in CARDIA.

A clinical trial design using the concept of proportional time using the generalized gamma ratio distribution.

Traditional methods of sample size and power calculations in clinical trials with a time-to-event end point are based on the logrank test (and its variations), Cox proportional hazards (PH) assumption, or comparison of means of 2 exponential distributions. Of these, sample size calculation based on PH assumption is likely the most common and allows adjusting for the effect of one or more covariates. However, when designing a trial, there are situations when the assumption of PH may not be appropriate. Additionally, when it is known that there is a rapid decline in the survival curve for a control group, such as from previously conducted observational studies, a design based on the PH assumption may confer only a minor statistical improvement for the treatment group that is neither clinically nor practically meaningful. For such scenarios, a clinical trial design that focuses on improvement in patient longevity is proposed, based on the concept of proportional time using the generalized gamma ratio distribution. Simulations are conducted to evaluate the performance of the proportional time method and to identify the situations in which such a design will be beneficial as compared to the standard design using a PH assumption, piecewise exponential hazards assumption, and specific cases of a cure rate model. A practical example in which hemorrhagic stroke patients are randomized to 1 of 2 arms in a putative clinical trial demonstrates the usefulness of this approach by drastically reducing the number of patients needed for study enrollment.

Effectiveness comparison of cardio-selective to non-selective ß-blockers and their association with mortality and morbidity in end-stage renal disease: a retrospective cohort study.

BACKGROUND: Within-class comparative effectiveness studies of ß-blockers have not been performed in the chronic dialysis setting. With widespread cardiac disease in these patients and potential mechanistic differences within the class, we examined whether mortality and morbidity outcomes varied between cardio-selective and non-selective ß-blockers. METHODS: Retrospective observational study of within class ß-blocker exposure among a national cohort of new chronic dialysis patients (N = 52,922) with hypertension and dual eligibility (Medicare-Medicaid). New ß-blocker users were classified according to their exclusive use of one of the subclasses. Outcomes were all-cause mortality (ACM) and cardiovascular morbidity and mortality (CVMM). The associations of cardio-selective and non-selective agents on outcomes were adjusted for baseline characteristics using Cox proportional hazards. RESULTS: There were 4938 new ß-blocker users included in the ACM model and 4537 in the CVMM model: 77 % on cardio-selective ß-blockers. Exposure to cardio-selective and non-selective agents during the follow-up period was comparable, as measured by proportion of days covered (0.56 vs. 0.53 in the ACM model; 0.56 vs 0.54 in the CVMM model). Use of cardio-selective ß-blockers was associated with lower risk for mortality (AHR = 0.84; 99 % CI = 0.72-0.97, p = 0.0026) and lower risk for CVMM events (AHR = 0.86; 99 % CI = 0.75-0.99, p = 0.0042). CONCLUSION: Among new ß-blockers users on chronic dialysis, cardio-selective agents were associated with a statistically significant 16 % reduction in mortality and 14 % in cardiovascular morbidity and mortality relative to non-selective ß-blocker users. A randomized clinical trial would be appropriate to more definitively answer whether cardio-selective ß-blockers are superior to non-selective ß-blockers in the setting of chronic dialysis.

Comparative Effectiveness of Renin-Angiotensin System Antagonists in Maintenance Dialysis Patients.

BACKGROUND/AIMS: Whether angiotensin converting enzyme inhibitors (ACE) and angiotensin receptor blockers (ARB) are differentially associated with reductions in cardiovascular events and mortality in patients receiving maintenance dialysis is uncertain. We compared outcomes between ACE and ARB users among hypertensive, maintenance dialysis patients. METHODS: National retrospective cohort study of hypertensive, Medicare-Medicaid eligible patients initiating chronic dialysis between 1/1/2000 to 12/31/2005. The exposure of interest was new use of either an ACEI or ARB. Outcomes were all-cause mortality (ACM) and combined cardiovascular hospitalization or death (CV-endpoint). Cox proportion hazards models were used to compare the effect of ACEI vs ARB use on ACM and, separately, CV-endpoint. RESULTS: ACM models were based on 3,555 ACEI and 1,442 ARB new users, while CV-endpoint models included 3,289 ACEI and 1,346 ARB new users. After statistical adjustments, ACEI users had higher hazard ratios for ACM (AHR = 1.22, 99% CI 1.05-1.42) and CV-endpoint (AHR = 1.12, 99% CI 0.99-1.27). CONCLUSIONS: Patients initiating maintenance dialysis who received an ACEI faced an increased risk for mortality and a trend towards an increased risk for CV-endpoints when compared to patients who received an ARB. Validation of these results in a rigorous clinical trial is warranted.

Association of multiple ischemic strokes with mortality in incident hemodialysis patients: an application of multistate model to determine transition probabilities in a retrospective observational cohort.

BACKGROUND: Little is known about the effect of multiple, or subsequent, ischemic strokes in patients receiving hemodialysis. METHODS: We undertook a retrospective cohort study of incident hemodialysis patients with Medicare coverage who had experienced a first ischemic stroke. Factors associated with either a subsequent ischemic stroke or death following a first new stroke were modeled. A multistate model with Cox proportional hazards was used to predict transition probabilities from first ischemic stroke to either subsequent stroke or to death, and the demographic and clinical factors associated with the respective transition probabilities were determined. Effect of a subsequent ischemic stroke on survival was quantified. RESULTS: Overall, 12,054 individuals (mean age 69.7 years, 41.3 % male, 53.0 % Caucasian and 34.0 % African-American) experienced a first new ischemic stroke. Female sex was associated with an increased risk of having a subsequent ischemic stroke (adjusted hazard ratio 1.37, 95 % confidence intervals 1.20 - 1.56, P < 0.0001); African-Americans, as compared to Caucasians, had lower likelihood of dying after a first new ischemic stroke (0.81, 0.77 - 0.85, P < 0.0001). A subsequent stroke trended towards having a higher likelihood of transitioning to death compared to a first new ischemic stroke on dialysis (1.72, 0.96 - 3.09, P = 0.071). When a subsequent ischemic stroke occurs at 24 months, probability of survival dropped >15 %, in absolute terms, from 0.254 to 0.096, with substantial drops observed at subsequent time points such that the probability of survival was more than halved. CONCLUSIONS: Likelihood of subsequent ischemic stroke and of survival in hemodialysis patients appears to vary by sex and race: females are more likely than males to experience a subsequent ischemic stroke, and Caucasians are more likely than African-Americans to die after a first new ischemic stroke. The risk of a transitioning to a subsequent stroke (after having had a first) increases until about 1 year, then decreases. Subsequent strokes are associated with decreased probability of survival, an effect which increases as time since first stroke elapses. This information may be of assistance to clinicians when counseling hemodialysis patients about the implications of recurrent ischemic stroke.

Ambulatory Status Protects against Venous Thromboembolism in Acute Mild Ischemic Stroke Patients.

INTRODUCTION: Ischemic stroke patients are at high risk (up to 18%) for venous thromboembolism. We conducted a retrospective cross-sectional study to understand the predictors of acute postmild ischemic stroke patient's ambulatory status and its relationship with venous thromboembolism, hospital length of stay, and in-hospital mortality. METHODS: We identified 522 patients between February 2006 and May 2014 and collected data about patient demographics, admission NIHSS (National Institutes of Health Stroke Scale), venous thromboembolism prophylaxis, ambulatory status, diagnosis of venous thromboembolism, and hospital outcomes (length of stay, mortality). Chi-square test, t-test and Wilcoxon rank-sum test, and binary logistic regression were used for statistical analysis as appropriate. RESULTS: A total of 61 (11.7%), 48 (9.2%), and 23 (4.4%) mild ischemic stroke patients developed venous thromboembolism, deep venous thrombosis, and pulmonary embolism, respectively. During hospitalization, 281 (53.8%) patients were ambulatory. Independent predictors of in-hospital ambulation were being married (OR 1.64, 95% CI 1.10-2.49), being nonreligious (OR 2.19, 95% CI 1.34-3.62), admission NIHSS (per unit decrease in NIHSS; OR 1.62, 95% CI 1.39-1.91), and nonuse of mechanical venous thromboembolism prophylaxis (OR 1.62, 95% CI 1.02-2.61). After adjusting for confounders, ambulatory patients had lower rates of venous thromboembolism (OR .47, 95% CI .25-.89), deep venous thrombosis (OR .36, 95% CI .17-.73), prolonged length of hospital stay (OR .24, 95% CI .16-.37), and mortality (OR .43, 95% CI .21-.84). CONCLUSIONS: Our findings suggest that for hospitalized acute mild ischemic stroke patients, ambulatory status is an independent predictor of venous thromboembolism (specifically deep venous thrombosis), hospital length of stay, and in-hospital mortality.

Relationship between calcium channel blocker class and mortality in dialysis.

BACKGROUND AND OBJECTIVE: The comparative effectiveness of dihydropyridine (DHP) and non-DHP calcium channel blockers (CCBs) in maintenance dialysis patients has not been well-studied. METHODS: A retrospective cohort of hypertensive patients initiating dialysis was created. New CCB initiators, defined as individual who had no evidence of CCB use in the first 90 days of dialysis but who were initiated by day 180, were followed from their first day of medication exposure until event or censoring; events consisted of all-cause mortality (ACM) and a combined endpoint of cardiovascular morbidity or mortality (CVMM). Cox proportional hazards models were used to determine adjusted hazard ratios (AHRs) comparing the effect of DHPs vs. non-DHPs. RESULTS: There were 2900 and 2704 new initiators of CCBs in the ACM and CVMM models, respectively. Adjusted for other factors, use of DHPs, compared to non-DHPs, was associated with an AHR of 0.77 (99% confidence intervals, 0.64 - 0.93, P = 0.0004) for ACM and 0.86 (0.72 - 1.02, P = 0.024) for CVMM. Results were similar when individuals who initiated therapy at any point after the cohort inception were included, with AHRs of 0.60 (0.53 - 0.69, P < 0.0001) and 0.77 (0.67 - 0.89, P < 0.0001) for ACM and CVMM, respectively. Further, elimination of individuals with chronic atrial fibrillation resulted in AHRs of 0.71 and 0.70 for ACM and CVVM, respectively. CONCLUSION: DHPs, as compared to non-DHPs, were associated with reduced hazard of death or cardiovascular morbidity and mortality; potential mechanisms of action require further study.

Antihypertensive medication exposure and cardiovascular outcomes in hemodialysis patients.

BACKGROUND/AIMS: Our understanding of the effectiveness of cardioprotective medications in maintenance dialysis patients is based upon drug exposures assessed at a single point in time. We employed a novel, time-dependent approach to modeling medication use over time to examine outcomes in a large national cohort. METHODS: We linked Medicaid prescription claims with United States Renal Data System registry data and Medicare claims for 52,922 hypertensive maintenance dialysis patients. All-cause mortality and a combined cardiovascular disease (CVD)-endpoint were modeled as functions of exposure to cardioprotective antihypertensive medications (renin angiotensin system antagonists, ß-adrenergic blockers, and calcium channel blockers) measured with three time-dependent covariates (weekly exposure status, proportion of prior weeks with exposure, and number of switches in exposure status) and with propensity adjustment. RESULTS: Current cardioprotective medication exposure status as compared to not exposed was associated with lower adjusted hazard ratios (AHRs) for mortality, though the magnitude depended upon the proportion of prior weeks with medication (duration) and the number of switches between active and non-active use (switches) (AHR range 0.54-0.90). Combined CVD-endpoints depended upon the proportion of weeks on medication: AHR = 1.18 for 10% and AHR = 0.90 for 90% of weeks. Combined CVD-endpoint was also lower for patients with fewer switches. CONCLUSIONS: Effectiveness depends not only on having a drug available but is tempered by duration and stability of use, likely reflecting variation in clinical stability and patient behavior.

Stroke and the "stroke belt" in dialysis: contribution of patient characteristics to ischemic stroke rate and its geographic variation.

Geographic variation in stroke rates is well established in the general population, with higher rates in the South than in other areas of the United States. ESRD is a potent risk factor for stroke, but whether regional variations in stroke risk exist among dialysis patients is unknown. Medicare claims from 2000 to 2005 were used to ascertain ischemic stroke events in a large cohort of 265,685 incident dialysis patients. A Poisson generalized linear mixed model was generated to determine factors associated with stroke and to ascertain state-by-state geographic variability in stroke rates by generating observed-to-expected (O/E) adjusted rate ratios for stroke. Older age, female sex, African American race and Hispanic ethnicity, unemployed status, diabetes, hypertension, history of stroke, and permanent atrial fibrillation were positively associated with ischemic stroke, whereas body mass index >30 kg/m(2) was inversely associated with stroke (P<0.001 for each). After full multivariable adjustment, the three states with O/E rate ratios >1.0 were all in the South: North Carolina, Mississippi, and Oklahoma. Regional efforts to increase primary prevention in the "stroke belt" or to better educate dialysis patients on the signs of stroke so that they may promptly seek care may improve stroke care and outcomes in dialysis patients.

Group sequential design for time-to-event outcome with non-proportional hazards using the concept of relative time utilizing two different Weibull distributions.

A group sequential design allows investigators to sequentially monitor efficacy and safety as part of interim testing in phase III trials. Literature is well developed in the case of continuous and binary outcomes, however, in case of trials with a time-to-event outcome, popular methods of sample size calculation often assume proportional hazards. In situations where the proportional hazards assumption is inappropriate as indicated by historical data, these popular methods are very restrictive. In this paper, a novel simulation-based group sequential design is proposed for a two-arm randomized phase III clinical trial with a survival endpoint for the non-proportional hazards scenario. By assuming that the survival times for each treatment arm follow two different Weibull distributions, the proposed method utilizes the concept of Relative Time to calculate the efficacy and safety boundaries at selected interim testing points. The test statistic used to generate these boundaries is asymptotically normal, allowing p-value calculation at each boundary. Many design features specific to time-to-event data can be incorporated with ease. Additionally, the proposed method allows the flexibility of having the accelerated failure time model and the proportional hazards model as constrained special cases. Real life applications are discussed demonstrating the practicality of the proposed method.

P2Y12 Inhibitors Refill Gap Predicts Death in Medicare Beneficiaries on Chronic Dialysis.

Introduction: Oral P2Y12 inhibitors (P2Y12-I) are commonly used antiplatelet drugs in patients with end-stage kidney disease (ESKD) on chronic dialysis. Although gaps in prescription refills are quite common in patients with ESKD, it remains unclear whether P2Y12-I prescription refill patterns are associated with adverse clinical outcomes. Methods: We used the United States Renal Data System (USRDS) registry for patients with ESKD to capture new P2Y12-I prescriptions from 2011 to 2015. The primary exposure was prescription refill patterns and the primary outcome was all-cause death. Results: Among the 31,243 patients with new P2Y12-I prescription, median age was 64 years; 54% were male; and 39% were Caucasian, 37% African American, and 18% Hispanic. We observed 3 P2Y12-I refill patterns as follows: continuous users (45.1%), noncontinuous users (3.6%), and users with ≥30 days refill gap (51.4%). Prescription refill pattern with ≥30 days refill gap (vs. continuous use) was associated with all-cause death (adjusted hazard ratio [HR]: 1.18; 95% confidence interval [CI]: 1.13-1.23). Age and race were the most important risk factors associated with prescription refill pattern. African Americans (vs. Caucasians) were more likely to demonstrate ≥30 days refill gap, (adjusted odds ratio [OR]: 1.43; 95% CI: 1.36-1.51). In addition, younger patients (vs. older) were more likely to demonstrate ≥30 day refill gap (adjusted OR/decade: 0.9; 95% CI: 0.89-0.92). Conclusion: Nonadherence to P2Y12-I prescriptions is quite common, and disproportionately affects minorities. Younger individuals with ESKD are independently associated with a higher risk of death. The odds of having a refill gap are decreasing for older patients who are more compliant than younger patients. Future studies should investigate whether phenotyping subgroups of patients with ESKD based on prescription refill patterns can help in improving adverse clinical outcomes.