Chen Pin Wang

Variation in the drinking trajectories of freshmen college students

F. K. Del Boca, J. Darkes, P. E. Greenbaum, and M. S. Goldman (2004) examined temporal variations in drinking during the freshmen college year and the relationship of several risk factors to these variations. Here, using the same data, the authors investigate whether a single growth curve adequately characterizes the variability in individual drinking trajectories. Latent growth mixture modeling identified 5 drinking trajectory classes: light-stable, light-stable plus high holiday, medium-increasing, highdecreasing, and heavy-stable. In multivariate predictor analyses, gender (i.e., more women) and lower alcohol expectancies distinguished the light-stable class from other trajectories; only expectancies differentiated the high-decreasing from the heavy-stable and medium-increasing classes. These findings allow for improved identification of individuals at risk for developing problematic trajectories and for development of interventions tailored to specific drinker classes.

Residual Diagnostics for Growth Mixture Models: Examining the Impact of a Preventive Intervention on Multiple Trajectories of Aggressive Behavior

Growth mixture modeling has become a prominent tool for studying the heterogeneity of developmental trajectories within a population. In this article we develop graphical diagnostics to detect misspecification in growth mixture models regarding the number of growth classes, growth trajectory means, and covariance structures. For each model misspecification, we propose a different type of empirical Bayes residual to quantify the departure. Our procedure begins by imputing multiple independent sets of growth classes for the sample. Then, from these so-called “pseudoclass” draws, we form diagnostic plots to examine the averaged empirical distributions of residuals in each such class. Our proposals draw on the property that each single set of pseudoclass adjusted residuals is asymptotically normal with known mean and (co)variance when the underlying model is correct. These methods are justified in simulation studies involving two classes of linear growth curves that also differ by their covariance structures. These are then applied to longitudinal data from a randomized field trial that tests whether childrens trajectories of aggressive behavior could be modified during elementary and middle school. Our diagnostics lead to a solution involving a mixture of three growth classes. When comparing the diagnostics obtained from multiple pseudoclasses with those from multiple imputations, we show the computational advantage of the former and obtain a criterion for determining the minimum number of pseudoclass draws.

Patterns of primary care and mortality among patients with schizophrenia or diabetes: a cluster analysis approach to the retrospective study of healthcare utilization

BackgroundPatients with schizophrenia have difficulty managing their medical healthcare needs, possibly resulting in delayed treatment and poor outcomes. We analyzed whether patients reduced primary care use over time, differentially by diagnosis with schizophrenia, diabetes, or both schizophrenia and diabetes. We also assessed whether such patterns of primary care use were a significant predictor of mortality over a 4-year period.MethodsThe Veterans Healthcare Administration (VA) is the largest integrated healthcare system in the United States. Administrative extracts of the VAs all-electronic medical records were studied. Patients over age 50 and diagnosed with schizophrenia in 2002 were age-matched 1:4 to diabetes patients. All patients were followed through 2005. Cluster analysis explored trajectories of primary care use. Proportional hazards regression modelled the impact of these primary care utilization trajectories on survival, controlling for demographic and clinical covariates.ResultsPatients comprised three diagnostic groups: diabetes only (n = 188,332), schizophrenia only (n = 40,109), and schizophrenia with diabetes (Scz-DM, n = 13,025). Cluster analysis revealed four distinct trajectories of primary care use: consistent over time, increasing over time, high and decreasing, low and decreasing. Patients with schizophrenia only were likely to have low-decreasing use (73% schizophrenia-only vs 54% Scz-DM vs 52% diabetes). Increasing use was least common among schizophrenia patients (4% vs 8% Scz-DM vs 7% diabetes) and was associated with improved survival. Low-decreasing primary care, compared to consistent use, was associated with shorter survival controlling for demographics and case-mix. The observational study was limited by reliance on administrative data.ConclusionRegular primary care and high levels of primary care were associated with better survival for patients with chronic illness, whether psychiatric or medical. For schizophrenia patients, with or without comorbid diabetes, primary care offers a survival benefit, suggesting that innovations in treatment retention targeting at-risk groups can offer significant promise of improving outcomes.

Complex comorbidity clusters in OEF/OIF veterans: the polytrauma clinical triad and beyond.

Background:A growing body of research on US Veterans from Afghanistan and Iraq [Operations Enduring and Iraqi Freedom, and Operation New Dawn (OEF/OIF)] has described the polytrauma clinical triad (PCT): traumatic brain injury (TBI), posttraumatic stress disorder (PTSD), and pain. Extant research has not explored comorbidity clusters in this population more broadly, particularly co-occurring chronic diseases. Objectives:The aim of the study was to identify comorbidity clusters among diagnoses of deployment-specific (TBI, PTSD, pain) and chronic (eg, hypertension, diabetes) conditions, and to examine the association of these clusters with health care utilization and adverse outcomes. Research Design:This was a retrospective cohort study. Subjects:The cohort comprised OEF/OIF Veterans who received care in the Veterans Health Administration in fiscal years (FY) 2008–2010. Measures:We identified comorbidity using validated ICD-9-CM code–based algorithms and FY08–09 data, followed by which we applied latent class analysis to identify the most statistically distinct and clinically meaningful patterns of comorbidity. We examined the association of these clusters with process measures/outcomes using logistic regression to correlate medication use, acute health care utilization, and adverse outcomes in FY10. Results:In this cohort (N=191,797), we found 6 comorbidity clusters. Cluster 1: PCT+Chronic Disease (5%); Cluster 2: PCT (9%); Cluster 3: Mental Health+Substance Abuse (24%); Cluster 4: Sleep, Amputation, Chronic Disease (4%); Cluster 5: Pain, Moderate PTSD (6%); and Cluster 6: Relatively Healthy (53%). Subsequent health care utilization patterns and adverse events were consistent with disease patterns. Conclusions:These comorbidity clusters extend beyond the PCT and may be used as a foundation to examine coordination/quality of care and outcomes for OEF/OIF Veterans with different patterns of comorbidity.

Statin use as a moderator of metformin effect on risk for prostate cancer among type 2 diabetic patients.

OBJECTIVE Metformin and statins have shown promise for cancer prevention. This study assessed whether the effect of metformin on prostate cancer (PCa) incidence varied by statin use among type 2 diabetic patients. RESEARCH DESIGN AND METHODS The study cohort consisted of 5,042 type 2 diabetic male patients seen in the Veteran Administration Health Care System who were without prior cancer and were prescribed with metformin or sulfonylurea as the exclusive hypoglycemic medication between fiscal years 1999 and 2005. Cox proportional hazards analyses were conducted to assess the differential hazard ratio (HR) of PCa due to metformin by statin use versus sulfonylurea use, where propensity scores of metformin and statin use were adjusted to account for imbalances in baseline covariates across medication groups. RESULTS Mean follow-up was ∼5 years, and 7.5% had a PCa diagnosis. Statin use modified the effect of metformin on PCa incidence (P < 0.0001). Metformin was associated with a significantly reduced PCa incidence among patients on statins (HR 0.69 [95% CI 0.50–0.92]; 17 cases/533 metformin users vs. 135 cases/2,404 sulfonylureas users) and an increased PCa incidence among patients not on statins (HR 2.15 [1.83–2.52]; 22 cases/175 metformin users vs. 186 cases/1,930 sulfonylureas users). The HR of PCa incidence for those taking metformin and statins versus those taking neither medication was 0.32 (0.25–0.42). CONCLUSIONS Among men with type 2 diabetes, PCa incidence among metformin users varied by their statin use. The potential beneficial influence on PCa by combination use of metformin and statin may be due to synergistic effects.

VHA Corporate Data Warehouse height and weight data: opportunities and challenges for health services research.

Within the Veterans Health Administration (VHA), anthropometric measurements entered into the electronic medical record are stored in local information systems, the national Corporate Data Warehouse (CDW), and in some regional data warehouses. This article describes efforts to examine the quality of weight and height data within the CDW and to compare CDW data with data from warehouses maintained by several of VHAs regional groupings of healthcare facilities (Veterans Integrated Service Networks [VISNs]). We found significantly fewer recorded heights than weights in both the CDW and VISN data sources. In spite of occasional anomalies, the concordance in the number and value of records in the CDW and the VISN warehouses was generally 97% to 99% or greater. Implausible variation in same-day and same-year heights and weights was noted, suggesting measurement or data-entry errors. Our work suggests that the CDW, over time and through validation, has become a generally reliable source of anthropometric data. Researchers should assess the reliability of data contained within any source and apply strategies to minimize the impact of data errors appropriate to their study population.

Influence of frailty-related diagnoses, high-risk prescribing in elderly adults, and primary care use on readmissions in fewer than 30 days for veterans aged 65 and older.

To determine the effect of two variables not previously studied in the readmissions literature (frailty‐related diagnoses and high‐risk medications in the elderly (HRME)) and one understudied variable (volume of primary care visits in the prior year).

Better Glycemic Control Is Associated With Maintenance of Lower-Extremity Function Over Time in Mexican American and European American Older Adults With Diabetes

OBJECTIVE Diabetes is a major cause of functional decline among older adults, but the role of glycemic control remains unclear. This article assesses whether better glycemic control is associated with better maintenance of lower-extremity function over time in older adults with diabetes. RESEARCH DESIGN AND METHODS Participants (n = 119) in the San Antonio Longitudinal Study of Aging, ages 71–85, who met American Diabetes Association diabetes criteria were followed over a 36-month period. Seven measures of A1C (HbA1c) were obtained at 6-month intervals; three measures of lower-extremity function were obtained at 18-month intervals using the Short Physical Performance Battery (SPPB). A two-step analytic approach was used, first, to identify distinct glycemic control classes using latent growth mixture modeling and, second, to examine trajectories of lower-extremity function based on these classes using path analysis. RESULTS Two glycemic control classes were identified: a poorer control class with higher means (all >7%) and higher within-subject variability in HbA1c and a better control class with lower means (all <7%) and lower within-subject variability. The short-term and long-term maintenance of lower-extremity function, assessed by the association between the first and second SPPB measures and the first and third SPPB measures, were both greater in the better control class than in the poorer control class. CONCLUSIONS Among older adults with diabetes, better glycemic control may improve both short-term and long-term maintenance of lower-extremity function.

Choice of Initial Antiepileptic Drug for Older Veterans: Possible Pharmacokinetic Drug Interactions with Existing Medications

OBJECTIVES: To identify clinically meaningful potential drug–drug interactions (PDIs) with antiepileptic drugs (AEDs), the AEDs and co‐administered drugs commonly associated with AED‐PDIs, and characteristics of patients with high likelihood of AED‐PDI exposure.

Temporal trends in new exposure to antiepileptic drug monotherapy and suicide-related behavior

Objective: Because some recent studies suggest increased risk for suicide-related behavior (SRB; ideation, attempts) among those receiving antiepileptic drugs (AEDs), we examined the temporal relationship between new AED exposure and SRB in a cohort of older veterans. Methods: We used national Veterans Health Administration databases to identify veterans aged ≥65 years who received a new AED prescription in 2004–2006. All instances of SRB were identified using ICD-9-CM codes 1 year before and after the AED exposure (index) date. We also identified comorbid conditions and medication associated with SRB in prior research. We used generalized estimating equations with a logit link to examine the association between new AED exposure and SRB during 30-day intervals during the year before and after the index date, controlling for potential confounders. Results: In this cohort of 90,263 older veterans, the likelihood of SRB the month prior to AED exposure was significantly higher than in other time periods even after adjusting for potential confounders. Although there were 87 SRB events (74 individuals) the year before and 106 SRB events (92 individuals) after, approximately 22% (n = 16) of those also had SRB before the index date. Moreover, the rate of SRB after AED start was gradually reduced over time. Conclusions: The temporal pattern of AED exposure and SRB suggests that, in clinical practice, the peak in SRB is prior to exposure. While speculative, the rate of gradual reduction in SRB thereafter suggests that symptoms may prompt AED prescription.