Retention of American Indian and Alaska Native participants in the National Alzheimer's Coordinating Center Uniform Data Set.

INTRODUCTION: The number of American Indian and Alaska Native (AI/AN) elders is expected to double by 2060. Thus it is imperative to retain AI/AN participants in longitudinal research studies to identify novel risk factors and potential targets for intervention for Alzheimer's disease and related dementias in these communities. METHODS: The National Alzheimer's Coordinating Center houses uniformly collected longitudinal data from the network of National Institute on Aging (NIA)-funded Alzheimer's Disease Research Centers (ADRCs). We used logistic regression to quantify participant retention at 43 ADRCs, comparing self-identified AI/AN participants to non-Hispanic White (NHW) participants, adjusting for potential confounding factors including baseline diagnosis, age, sex, education, and smoking. RESULTS: The odds of AI/AN participant retention at the first follow-up visit were significantly lower than those for NHW participants (adjusted odds ratio [aOR]: 0.599; 95%: 0.46-0.78; p < 0.001). DISCUSSION: These results suggest the need for improved strategies to retain AI/AN participants, perhaps including improved researcher-community relationships and community engagement and education. HIGHLIGHTS: American Indian and Alaska Native (AI/AN) research participants were retained to the first follow-up appointment at lower rates than non-Hispanic White (NHW) participants. AI/AN participants are retained at lower rates than NHW participants for long-term follow-up. The majority of AI/AN participants were not retained to the second follow-up visit.

Post-disclosure distress among racial and ethnic groups in a preclinical AD trial.

INTRODUCTION: Trialists need a thorough understanding of whether reactions to Alzheimer's disease (AD) biomarker information differ among racial and ethnic groups in preclinical AD trials. METHODS: We used data from the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease Study to analyze cognitively unimpaired participants' responses on the Impact of Event Scale (IES) 24 to 72 hours after amyloid disclosure. We fit a linear regression model to test whether mean IES scores differed among participants from specific racial and ethnic groups. We considered potential effect modification by amyloid status. RESULTS: Reactions to disclosure did not significantly differ among participant groups based on self-reported race and ethnicity. Although the results were not significant when stratified by amyloid status, all racial and ethnic groups except for participants self-reporting Hispanic/Latino ethnicity were observed to have higher mean IES in the elevated amyloid group. DISCUSSION: These results support continued use of current disclosure methods in preclinical AD trials.

Chlorhexidine and Mupirocin for Clearance of Methicillin-Resistant Staphylococcus aureus Colonization After Hospital Discharge: A Secondary Analysis of the Changing Lives by Eradicating Antibiotic Resistance Trial.

BACKGROUND: The CLEAR Trial demonstrated that a multisite body decolonization regimen reduced post-discharge infection and hospitalization in methicillin-resistant Staphylococcus aureus (MRSA) carriers. Here, we describe decolonization efficacy. METHODS: We performed a large, multicenter, randomized clinical trial of MRSA decolonization among adult patients after hospital discharge with MRSA infection or colonization. Participants were randomized 1:1 to either MRSA prevention education or education plus decolonization with topical chlorhexidine, oral chlorhexidine, and nasal mupirocin. Participants were swabbed in the nares, throat, axilla/groin, and wound (if applicable) at baseline and 1, 3, 6, and 9 months after randomization. The primary outcomes of this study are follow-up colonization differences between groups. RESULTS: Among 2121 participants, 1058 were randomized to decolonization. By 1 month, MRSA colonization was lower in the decolonization group compared with the education-only group (odds ration [OR] = 0.44; 95% confidence interval [CI], .36-.54; P ≤ .001). A similar magnitude of reduction was seen in the nares (OR = 0.34; 95% CI, .27-.42; P < .001), throat (OR = 0.55; 95% CI, .42-.73; P < .001), and axilla/groin (OR = 0.57; 95% CI, .43-.75; P < .001). These differences persisted through month 9 except at the wound site, which had a relatively small sample size. Higher regimen adherence was associated with lower MRSA colonization (P ≤ .01). CONCLUSIONS: In a randomized, clinical trial, a repeated post-discharge decolonization regimen for MRSA carriers reduced MRSA colonization overall and at multiple body sites. Higher treatment adherence was associated with greater reductions in MRSA colonization.

Maternal insulin resistance in pregnancy is associated with fetal fat deposition: findings from a longitudinal study.

BACKGROUND: Newborns exhibit substantial variation in fat mass accretion over gestation. These individual differences in newborn adiposity extend into infancy and childhood and relate to subsequent risk of obesity and metabolic dysregulation. Maternal glucose homeostasis in pregnancy has been proposed as an underlying mechanism; however, the timing in gestation when maternal glucose regulation influences the progression of fetal fat deposition remain unclear. OBJECTIVE: This study aimed to investigate the cross-sectional and longitudinal association of maternal insulin resistance in early, mid, and late pregnancy with fetal fat deposition in uncomplicated pregnancies. We hypothesized that maternal insulin resistance at early, mid, and late gestation is positively associated with fetal fat deposition, and that the magnitude of the association is greater for the mid and late gestation measures than for the early gestation measure. STUDY DESIGN: In a longitudinal study of 137 low-risk pregnancies, a fasting maternal blood sample was obtained and fetal ultrasonography was performed at ≈ 12, 20, and 30 weeks' gestation. Maternal insulin resistance was quantified using the homeostasis model assessment of insulin resistance (fasting insulin×fasting glucose/405). Estimated fetal adiposity was calculated by integrating measurements of cross-sectional arm and thigh percentage fat area and anterior abdominal wall thickness. The associations between maternal homeostasis model assessment of insulin resistance and estimated fetal adiposity and estimated fetal weight were determined by multiple linear regression adjusted for potential confounding factors including maternal age, parity, race and ethnicity, prepregnancy body mass index, gestational weight gain per week, fetal sex, and gestational age at assessments. RESULTS: Maternal homeostasis model assessment of insulin resistance at ≈ 12, 20, and 30 weeks was 2.79±1.79 (±standard deviation), 2.78±1.54, and 3.76±2.30, respectively. Homeostasis model assessment of insulin resistance at 20 weeks was positively associated with estimated fetal adiposity at 20 weeks (r=0.261; P=.005). Homeostasis model assessment of insulin resistance at 20 weeks (r=0.215; P=.011) and 30 weeks (r=0.285; P=.001) were also positively associated with estimated fetal adiposity at 30 weeks. These relationships remained significant after adjustment for confounding factors. There was no significant correlation between homeostasis model assessment of insulin resistance and estimated fetal weight at 20 and 30 weeks' gestation. CONCLUSION: In low-risk pregnancies, maternal insulin resistance at mid and late but not early pregnancy is significantly associated with fetal adiposity but not with fetal weight. Maternal insulin resistance in mid-gestation could provide a basis for risk identification and interventions that target child adiposity.

Frameworks for estimating causal effects in observational settings: comparing confounder adjustment and instrumental variables.

To estimate causal effects, analysts performing observational studies in health settings utilize several strategies to mitigate bias due to confounding by indication. There are two broad classes of approaches for these purposes: use of confounders and instrumental variables (IVs). Because such approaches are largely characterized by untestable assumptions, analysts must operate under an indefinite paradigm that these methods will work imperfectly. In this tutorial, we formalize a set of general principles and heuristics for estimating causal effects in the two approaches when the assumptions are potentially violated. This crucially requires reframing the process of observational studies as hypothesizing potential scenarios where the estimates from one approach are less inconsistent than the other. While most of our discussion of methodology centers around the linear setting, we touch upon complexities in non-linear settings and flexible procedures such as target minimum loss-based estimation and double machine learning. To demonstrate the application of our principles, we investigate the use of donepezil off-label for mild cognitive impairment. We compare and contrast results from confounder and IV methods, traditional and flexible, within our analysis and to a similar observational study and clinical trial.

Decolonization to Reduce Postdischarge Infection Risk among MRSA Carriers.

BACKGROUND: Hospitalized patients who are colonized with methicillin-resistant Staphylococcus aureus (MRSA) are at high risk for infection after discharge. METHODS: We conducted a multicenter, randomized, controlled trial of postdischarge hygiene education, as compared with education plus decolonization, in patients colonized with MRSA (carriers). Decolonization involved chlorhexidine mouthwash, baths or showers with chlorhexidine, and nasal mupirocin for 5 days twice per month for 6 months. Participants were followed for 1 year. The primary outcome was MRSA infection as defined according to Centers for Disease Control and Prevention (CDC) criteria. Secondary outcomes included MRSA infection determined on the basis of clinical judgment, infection from any cause, and infection-related hospitalization. All analyses were performed with the use of proportional-hazards models in the per-protocol population (all participants who underwent randomization, met the inclusion criteria, and survived beyond the recruitment hospitalization) and as-treated population (participants stratified according to adherence). RESULTS: In the per-protocol population, MRSA infection occurred in 98 of 1063 participants (9.2%) in the education group and in 67 of 1058 (6.3%) in the decolonization group; 84.8% of the MRSA infections led to hospitalization. Infection from any cause occurred in 23.7% of the participants in the education group and 19.6% of those in the decolonization group; 85.8% of the infections led to hospitalization. The hazard of MRSA infection was significantly lower in the decolonization group than in the education group (hazard ratio, 0.70; 95% confidence interval [CI], 0.52 to 0.96; P=0.03; number needed to treat to prevent one infection, 30; 95% CI, 18 to 230); this lower hazard led to a lower risk of hospitalization due to MRSA infection (hazard ratio, 0.71; 95% CI, 0.51 to 0.99). The decolonization group had lower likelihoods of clinically judged infection from any cause (hazard ratio, 0.83; 95% CI, 0.70 to 0.99) and infection-related hospitalization (hazard ratio, 0.76; 95% CI, 0.62 to 0.93); treatment effects for secondary outcomes should be interpreted with caution owing to a lack of prespecified adjustment for multiple comparisons. In as-treated analyses, participants in the decolonization group who adhered fully to the regimen had 44% fewer MRSA infections than the education group (hazard ratio, 0.56; 95% CI, 0.36 to 0.86) and had 40% fewer infections from any cause (hazard ratio, 0.60; 95% CI, 0.46 to 0.78). Side effects (all mild) occurred in 4.2% of the participants. CONCLUSIONS: Postdischarge MRSA decolonization with chlorhexidine and mupirocin led to a 30% lower risk of MRSA infection than education alone. (Funded by the AHRQ Healthcare-Associated Infections Program and others; ClinicalTrials.gov number, NCT01209234 .).

Dyadic Enrollment in a Phase 3 Mild Cognitive Impairment Clinical Trial.

BACKGROUND: Dyadic enrollment of a participant and study partner is required in mild cognitive impairment (MCI) clinical trials, despite participants being functionally independent. Research examining how the study partner requirement impacts MCI trials remains limited. METHODS: Using the Alzheimer's Disease Cooperative Study donepezil and vitamin E MCI trial data, we quantified the proportions of enrolled spouse, adult child, and other dyads. We used multinomial regression to identify which baseline participant characteristics (age, sex, race and ethnicity, apolipoprotein E ε4 status, education, residence type) were associated with dyad type. RESULTS: Among 769 randomized dyads, 73% were spousal, 14% adult child, and 13% other dyads. Adjusting for multiple comparisons, underrepresented racial and ethnic background (eg, comparing Hispanic to non-Hispanic White participants: adult child vs. spouse odds ratio = 5.86; 95% confidence interval: 2.09, 16.5; other vs. spouse odds ratio = 4.95; 95% confidence interval: 1.83, 13.4), female sex, age, nonhouse residence, and apolipoprotein E ε4 noncarriage were each associated with a higher odds of having an adult child, as well as an other, study partner at enrollment. DISCUSSION: Increasing participation among nonspousal dyads may facilitate more inclusive and representative MCI trial samples.

Censoring-robust time-dependent receiver operating characteristic curve estimators.

Time-dependent receiver operating characteristic curves are often used to evaluate the classification performance of continuous measures when considering time-to-event data. When one is interested in evaluating the predictive performance of multiple covariates, it is common to use the Cox proportional hazards model to obtain risk scores; however, previous work has shown that when the model is mis-specified, the estimand corresponding to the partial likelihood estimator depends on the censoring distribution. In this manuscript, we show that when the risk score model is mis-specified, the AUC will also depend on the censoring distribution, leading to either over- or under-estimation of the risk score's predictive performance. We propose the use of censoring-robust estimators to remove the dependence on the censoring distribution and provide empirical results supporting the use of censoring-robust risk scores.

Robust estimation in the nested case-control design under a misspecified covariate functional form.

The Cox proportional hazards model is typically used to analyze time-to-event data. If the event of interest is rare and covariates are difficult or expensive to collect, the nested case-control (NCC) design provides consistent estimates at reduced costs with minimal impact on precision if the model is specified correctly. If our scientific goal is to conduct inference regarding an association of interest, it is essential that we specify the model a priori to avoid multiple testing bias. We cannot, however, be certain that all assumptions will be satisfied so it is important to consider robustness of the NCC design under model misspecification. In this manuscript, we show that in finite sample settings where the functional form of a covariate of interest is misspecified, the estimates resulting from the partial likelihood estimator under the NCC design depend on the number of controls sampled at each event time. To account for this dependency, we propose an estimator that recovers the results obtained using using the full cohort, where full covariate information is available for all study participants. We present the utility of our estimator using simulation studies and show the theoretical properties. We end by applying our estimator to motivating data from the Alzheimer's Disease Neuroimaging Initiative.

Direct Mail Recruitment to a Potential Participant Registry.

Recruitment registries are novel tools to accelerate Alzheimer disease research accrual. Optimal methods to populate such registries remain largely unstudied. We sent postcards with 3 unique taglines (Alzheimer's Prevention Research, brain health research, general research) to 100,000 local residents aged 50 years and older to assess the effectiveness of recruiting to an online recruitment registry by mail. The postcard campaign recruited 273 new registry enrollees (0.27% overall response rate). Neither the response rate nor the demographic characteristics of recruited participants differed by the postcard tagline. These results suggest that direct mail may not be the most cost-effective approach to recruit participants to online registries.

Using Direct-to-Consumer Genetic Testing Results to Accelerate Alzheimer Disease Clinical Trial Recruitment.

INTRODUCTION: The apolipoprotein E (APOE) gene is the strongest known genetic risk factor for sporadic Alzheimer disease (AD). APOE can be used as an enrichment strategy or inclusion criterion for AD prevention trials. Personal genomics companies market direct-to-consumer (DTC) genetic tests, including APOE. We assessed DTC APOE testing usage among enrollees of the University of California Irvine Consent-to-Contact Registry, an online recruitment registry, and attitudes toward using this information in clinical trial recruitment. METHODS: We emailed links to an electronic survey to registry enrollees age 50 years or older. We assessed participants' use of DTC services, willingness to learn APOE status, and willingness to share genetic information. Logistic regression models assessed relationships between DTC testing usage and demographic characteristics, and with willingness to share results to assist trial recruitment. RESULTS: Among 1312 responders (57% response rate), few (7%) had used DTC testing for APOE. Non-Hispanic Asian enrollees were 93% less likely to have used DTC testing, compared with non-Hispanic Whites [95% confidence interval: (0.01, 0.67)]. Willingness to share APOE information for study recruitment was >90% for both users and nonusers. CONCLUSIONS: Matching participants to trials on the basis of DTC APOE information may be an effective way to streamline AD prevention trial recruitment.

RITS: a toolbox for assessing complex interventions via interrupted time series models.

BACKGROUND: Various interacting and interdependent components comprise complex interventions. These components create difficulty in assessing the true impact of interventions designed to improve patient-centered outcomes. Interrupted time series (ITS) designs borrow from case-crossover designs and serve as quasi-experimental methodology able to retrospectively assess the impact of an intervention while accounting for temporal correlation. While ITS designs are aptly situated for studying the impacts of large-scale public health policies, existing ITS software implement rigid ITS methodology that often assume the pre- and post-intervention phases are fully differentiated (by a known change-point or set of time points) and do not allow for changes in both the mean functions and correlation structure. RESULTS: This article describes the Robust Interrupted Time Series (RITS) toolbox, a stand-alone user-friendly application researchers can use to implement flexible ITS models that estimate the lagged effect of an intervention on an outcome, level and trend changes, and post-intervention changes in the correlation structure, for single and multiple ITS. The RITS toolbox incorporates a formal test for the existence of a change in the outcome and estimates a change-point over a set of possible change-points defined by the researcher. In settings with multiple ITS, RITS provides a global over-all units change-point and allows for unit-specific changes in the mean functions and correlation structures. CONCLUSIONS: The RITS toolbox is the first piece of software that allows researchers to use flexible ITS models that test for the existence of a change-point, estimate the change-point (if estimation is desired), and allow for changes in both the mean functions and correlation structures at the change point. RITS does not require any knowledge of a statistical (or otherwise) programming language, is freely available to the community, and may be downloaded and used on a local machine to ensure data protection.

On the design of early-phase Alzheimer's disease clinical trials with cerebrospinal fluid tau outcomes.

BACKGROUND/AIMS: The focus of Alzheimer's disease studies has shifted to earlier disease stages, including mild cognitive impairment. Biomarker inclusion criteria are often incorporated into mild cognitive impairment clinical trials to identify individuals with "prodromal Alzheimer's disease" to ensure appropriate drug targets and enrich for participants likely to develop Alzheimer's disease dementia. The use of these eligibility criteria may affect study power. METHODS: We investigated outcome variability and study power in the setting of proof-of-concept prodromal Alzheimer's disease trials that incorporate cerebrospinal fluid levels of total tau (t-tau) and phosphorylated (p-tau) as primary outcomes and how differing biomarker inclusion criteria affect power. We used data from the Alzheimer's Disease Neuroimaging Initiative to model trial scenarios and to estimate the variance and within-subject correlation of total and phosphorylated tau. These estimates were then used to investigate the differences in study power for trials considering these two surrogate outcomes. RESULTS: Patient characteristics were similar for all eligibility criteria. The lowest outcome variance and highest within-subject correlation were obtained when phosphorylated tau was used as an eligibility criterion, compared to amyloid beta or total tau, regardless of whether total tau or phosphorylated tau were used as primary outcomes. Power increased when eligibility criteria were broadened to allow for enrollment of subjects with either low amyloid beta or high phosphorylated tau. CONCLUSION: Specific biomarker inclusion criteria may impact statistical power in trials using total tau or phosphorylated tau as the primary outcome. In concert with other important considerations such as treatment target and population of clinical interest, these results may have implications to the integrity and efficiency of prodromal Alzheimer's disease trial designs.

Evidence for disordered acid-base handling in calcium stone-forming patients.

In stone formers (SFs) with idiopathic hypercalciuria, urine pH governs the mineral phase of stones. Calcium phosphate (CaP) SFs have higher urine pH than calcium oxalate (CaOx) SFs. Normal women have higher urine pH than men on fixed diets, accompanied by greater absorption of food alkali. Female CaP and male CaOx SFs have similar urine pH as same sex normal individuals, but male CaP and female CaOx SFs may have abnormal acid-base handling. We studied 25 normal individuals (13 men and 12 women), 17 CaOx SFs (11 men and 6 women), and 15 CaP SFs (8 men and 7 women) on fixed diets. Urine and blood samples were collected under fasting and fed conditions. Female CaOx SFs had lower urine pH and lower alkali absorption, fed, compared with normal women; their urine NH4 was higher and urine citrate excretion lower than in normal women, consistent with their higher net acid excretion. Male CaOx SFs had higher urine citrate excretion and higher serum ultrafilterable citrate levels than normal men. Both male and female CaP SFs had higher urine pH fasting than same sex normal individuals, but only men were higher in the fed period, and there were no differences from normal in gut alkali absorption. CaP SFs of both sexes had higher urine NH4 and lower urine citrate than same sex normal individuals. The lower urine pH of female CaOx SFs seems related to decreased gut alkali absorption, while the higher pH of CaP SFs, accompanied by higher urine NH4 and lower urine citrate, suggests a proximal tubule disorder.

A stratified generalized additive model and permutation test for temporal heterogeneity of smoothed bivariate spatial effects.

Generalized additive models (GAMs) with bivariate smoothers are frequently used to map geographic disease risks in epidemiology studies. A challenge in identifying health disparities has been the lack of intuitive and computationally feasible methods to assess whether the pattern of spatial effects varies over time. In this research, we accommodate time-stratified smoothers into the GAM framework to estimate time-specific spatial risk patterns while borrowing information from confounding effects across time. A backfitting algorithm for model estimation is proposed along with a permutation testing framework for assessing temporal heterogeneity of geospatial risk patterns across two or more time points. Simulation studies show that our proposed permuted mean squared difference (PMSD) test performs well with respect to type I error and power in various settings when compared with existing methods. The proposed model and PMSD test are used geospatial risk patterns of patent ductus arteriosus (PDA) in the state of Massachusetts over 2003-2009. We show that there is variation over time in spatial patterns of PDA risk, adjusting for other known risk factors, suggesting the presence of potential time-varying and space-related risk factors other than the adjusted ones.

Variance estimation for the Kappa statistic in the presence of clustered data and heterogeneous observations.

We present a methodology motivated by a controlled trial designed to validate SPOT GRADE, a novel surgical bleeding severity scale. Briefly, the study was designed to quantify inter- and intra-surgeon agreement for characterizing the severity of surgical bleeds via a Kappa statistic. Multiple surgeons were presented with a randomized sequence of controlled bleeding videos and asked to apply the rating system to characterize each wound. Each video was shown multiple times to quantify intra-surgeon reliability, creating clustered data. In addition, videos within the same category may have had different classification probabilities due to changes in blood flow rates and wound sizes. In this work, we propose a new variance estimator for the Kappa statistic, for use in clustered data as well as heterogeneity among items within the same classification category. We then apply this methodology to data from the SPOT GRADE trial.

The RhoJ-BAD signaling network: An Achilles' heel for BRAF mutant melanomas.

Genes and pathways that allow cells to cope with oncogene-induced stress represent selective cancer therapeutic targets that remain largely undiscovered. In this study, we identify a RhoJ signaling pathway that is a selective therapeutic target for BRAF mutant cells. RhoJ deletion in BRAF mutant melanocytes modulates the expression of the pro-apoptotic protein BAD as well as genes involved in cellular metabolism, impairing nevus formation, cellular transformation, and metastasis. Short-term treatment of nascent melanoma tumors with PAK inhibitors that block RhoJ signaling halts the growth of BRAF mutant melanoma tumors in vivo and induces apoptosis in melanoma cells in vitro via a BAD-dependent mechanism. As up to 50% of BRAF mutant human melanomas express high levels of RhoJ, these studies nominate the RhoJ-BAD signaling network as a therapeutic vulnerability for fledgling BRAF mutant human tumors.

Prospective, multicenter, randomized, controlled trial evaluating the performance of a novel combination powder vs hemostatic matrix in cardiothoracic operations.

AIM: This trial compared the hemostatic performance of a novel combination powder (CP) to a control hemostatic matrix (HM) in cardiothoracic operations. METHODS: Patients meeting eligibility criteria were enrolled after providing informed consent. Subjects were randomized intraoperatively to receive CP (HEMOBLAST Bellows; Biom'up, France) or HM (FLOSEAL Hemostatic Matrix; Baxter Healthcare Corporation, Hayward, CA). Bleeding was assessed using a clinically validated, quantitative bleeding severity scale. The primary endpoint was total time to hemostasis (TTTH), from the start of device preparation, as an indicator of when a surgeon asks for a surgical hemostat until hemostasis was achieved. TTTH at 3 minutes was utilized for the primary analysis, while TTTH at 5 minutes was considered as a secondary endpoint. RESULTS: A total of 105 subjects were enrolled across four institutions. The primary efficacy endpoint for the superiority of CP relative to HM for success at achieving hemostasis within 3 minutes was met, with 64.2% of the CP group achieving hemostasis compared with 9.6% of the HM group, a difference of 54.54% (37.4%-71.6%; P < .001 for superiority). The secondary efficacy endpoint was also met, with 92.5% of the CP group achieving hemostasis at 5 minutes versus 44.2% in the HM group, a difference of 48.2% (31.1%-65.4%; P < .001 for noninferiority). There were no device-related adverse events. CONCLUSIONS: In this multicenter, randomized, controlled trial, comparison of CP to HM revealed CP superiority and noninferiority for TTTH at 3 and 5 minutes, respectively.

A Preliminary Study of Clinical Trial Enrollment Decisions Among People With Mild Cognitive Impairment and Their Study Partners.

OBJECTIVE: All Alzheimer disease (AD) clinical trials, including those enrolling patients with mild cognitive impairment (MCI), require dyadic participation. The purpose of this study was to elucidate how people with MCI and their study partners decide whether to enroll in clinical trials. METHODS: This was a mixed methods interview study. We interviewed patient participants with a consensus research diagnosis of MCI and their study partners. Interviews examined how dyads decide whether to enroll in a clinical trial and whether AD biomarker testing affects willingness to enroll. RESULTS: Though most MCI patients and study partners would decide in partnership whether to enroll in a clinical trial, agreement was lower among nonspousal, compared with spousal, dyads. Deterrents to enrollment included concerns about patient safety and inconvenience, especially for study partners. Motivators to enrollment included altruism, the desire to contribute to research, hope for patient benefit, and the desire to learn more about the patient's condition. When asked open-ended questions about motivators to enroll in trials, few patients cited access to biomarker testing specifically, though most expressed a desire to undergo biomarker testing when asked directly. CONCLUSION: Spousal and nonspousal MCI dyads may approach clinical trial decisions differently. Future research should investigate how AD biomarker testing affects participants' willingness to enroll in trials.

Assessing health care interventions via an interrupted time series model: Study power and design considerations.

The delivery and assessment of quality health care is complex with many interacting and interdependent components. In terms of research design and statistical analysis, this complexity and interdependency makes it difficult to assess the true impact of interventions designed to improve patient health care outcomes. Interrupted time series (ITS) is a quasi-experimental design developed for inferring the effectiveness of a health policy intervention while accounting for temporal dependence within a single system or unit. Current standardized ITS methods do not simultaneously analyze data for several units nor are there methods to test for the existence of a change point and to assess statistical power for study planning purposes in this context. To address this limitation, we propose the "Robust Multiple ITS" (R-MITS) model, appropriate for multiunit ITS data, that allows for inference regarding the estimation of a global change point across units in the presence of a potentially lagged (or anticipatory) treatment effect. Under the R-MITS model, one can formally test for the existence of a change point and estimate the time delay between the formal intervention implementation and the over-all-unit intervention effect. We conducted empirical simulation studies to assess the type one error rate of the testing procedure, power for detecting specified change-point alternatives, and accuracy of the proposed estimating methodology. R-MITS is illustrated by analyzing patient satisfaction data from a hospital that implemented and evaluated a new care delivery model in multiple units.