Initial Validation of a Computerized Adaptive Test for Substance Use Disorder Identification in Adolescents.

PURPOSE: Computerized adaptive tests (CATs) are highly efficient assessment tools that couple low patient and clinician time burden with high diagnostic accuracy. A CAT for substance use disorders (CAT-SUD-E) has been validated in adult populations but has yet to be tested in adolescents. The purpose of this study was to perform initial evaluation of the K-CAT-SUD-E (i.e., Kiddy-CAT-SUD-E) in an adolescent sample compared to a gold-standard diagnostic interview. METHODS: Adolescents (N = 156; aged 11-17) with diverse substance use histories completed the K-CAT-SUD-E electronically and the substance related disorders portion of a clinician-conducted diagnostic interview (K-SADS) via tele-videoconferencing platform. The K-CAT-SUD-E assessed both current and lifetime overall SUD and substance-specific diagnoses for nine substance classes. RESULTS: Using the K-CAT-SUD-E continuous severity score and diagnoses to predict the presence of any K-SADS SUD diagnosis, the classification accuracy ranged from excellent for current SUD (AUC = 0.89, 95% CI = 0.81, 0.95) to outstanding (AUC = 0.93, 95% CI = 0.82, 0.97) for lifetime SUD. Regarding current substance-specific diagnoses, the classification accuracy was excellent for alcohol (AUC = 0.82), cannabis (AUC = 0.83) and nicotine/tobacco (AUC = 0.90). For lifetime substance-specific diagnoses, the classification accuracy ranged from excellent (e.g., opioids, AUC = 0.84) to outstanding (e.g., stimulants, AUC = 0.96). K-CAT-SUD-E median completion time was 4 min 22 s compared to 45 min for the K-SADS. CONCLUSIONS: This study provides initial support for the K-CAT-SUD-E as a feasible accurate diagnostic tool for assessing SUDs in adolescents. Future studies should further validate the K-CAT-SUD-E in a larger sample of adolescents and examine its acceptability, feasibility, and scalability in youth-serving settings.

Radiological risk assessment of the Hunters Point Naval Shipyard (HPNS).

Hunters Point Naval Shipyard in San Francisco, California was deemed a Superfund site by the USEPA in 1989 due to chemical and radiological contamination resulting from U.S. Navy operations from 1939 to 1974. During characterization and remediation efforts, over 50,000 radiological soil samples and 19,000 air samples were collected. This risk assessment, conducted in accordance with federal guidelines, represents the first comprehensive evaluation of past, present, and future health risks associated with radionuclides present at the site. The assessment indicated that before site remediation, most radionuclide soil concentrations were at or near local background concentrations. Had such low remedial goals not been established, significant remediation of surface soils would not have been necessary to protect human health. The pre-remediation lifetime incremental cancer morbidity risks for on-site workers and theoretical on-site residents due to radionuclide contamination were found to be 1.3 × 10-6 and 3.2 × 10-6, respectively. The post-remediation risks to future on-site residents were found to be 6.3 × 10-8 (without durable cover) and 3.7 × 10-8 (with durable cover), while post-remediation risks to on-site workers were found to be 2.6 × 10-8 (without durable cover) and 1.6 × 10-8 (with durable cover). Risk estimates for all scenarios were found to be significantly below the acceptable risk of 3 × 10-4 approved by regulatory agencies. Upwind and downwind air samples collected during remediation indicate that remediation activities never posed a measurable risk to off-site residents. This risk assessment emphasizes the importance of establishing clear and scientifically rigorous soil remedial goals at sites as well as understanding local radionuclide background concentrations.

Preoperative Assessment of Anxiety and Depression Using Computerized Adaptive Screening Tools: A Pilot Prospective Cohort Study.

BACKGROUND: Serious mental health conditions (eg, anxiety and depression) are common in surgical patients, yet likely underassessed due to the time-consuming and cumbersome traditional screening process. A recently developed computerized adaptive mental health assessment tool (computerized adaptive test-mental health [CAT-MH]) allows rapid, precise, and accurate assessment of numerous mental health disorders, including anxiety and depression, without the need for a trained interviewer. The goal of this investigation was to determine the feasibility of administering CAT-MH for anxiety and depression in the preoperative setting and to obtain preliminary evidence of the prevalence of anxiety and depression in preoperative patients. METHODS: In this prospective cohort study, 100 adult patients scheduled for elective surgery were enrolled and asked to complete the CAT-MH in the preoperative clinic. Urgent and emergency surgeries were excluded as were pregnant patients. Primary feasibility outcomes were completion rate and time to completion. Secondary outcomes were prevalence estimates of anxiety and depression. RESULTS: All 100 enrolled patients completed the study. All patients were able to complete the mental health assessment (mean time: 3.6 ± 1.8 minutes standard deviation). Sixteen patients (16%) screened positive for anxiety (severity: mild, n = 7 [7%]; moderate, n = 7 [7%]); severe, n = 2 [2%]); 12 of 16 (75%) did not have a previous diagnosis of anxiety disorder. Twenty-eight (28%) patients screened positive for depression (severity: mild, n = 26 [26%]; moderate and severe, n = 1 each [1%]); 23 of 28 (82%) had no previous diagnosis of depressive disorder. Nineteen patients (19%) met the screening criteria for major depressive disorder; 14 of 19 (74%) of which had no previous diagnosis of major depressive disorder. CONCLUSIONS: The results of this pilot study support the feasibility of using CAT-MH in a preoperative evaluation and indicate that there is a substantial prevalence of undiagnosed anxiety and depression in surgical patients.

Awareness of illness moderates self-assessment of psychotic symptoms.

OBJECTIVE: Self-reports or patient-reported outcome measures are seldom used in psychosis due to concerns about the ability of patients to accurately report their symptomatology, particularly in cases of low awareness of illness. The aim of this study was to assess the effect of insight on the accuracy of self-reported psychotic symptoms using a computerized adaptive testing tool (CAT-Psychosis). METHODS: A secondary analysis of data drawn from the CAT-Psychosis development and validation study was performed. The Brief Psychiatric Rating Scale and the Scale of Unawareness of Mental Disorders were administered by clinicians. Patients completed the self-reported version of the CAT-Psychosis. Patients were median-split regarding their insight level to compare the correlation between the two psychosis severity measures. A subgroup sensitivity analysis was performed only on patients with schizophrenia spectrum disorders. RESULTS: A total of 159 patients with a psychotic disorder who completed both CAT-Psychosis and Scale of Unawareness of Mental Disorders were included. For the whole sample, CAT-Psychosis scores showed convergent validity with Brief Psychiatric Rating Scale ratings (r = 0.517, 95% confidence interval = [0.392, 0.622], p < 0.001). Insight was found to moderate this correlation (ß = -0.511, p = 0.005), yet agreement between both measures remained statistically significant for both high (r = 0.621, 95% confidence interval = [0.476, 0.733], p < 0.001) and low insight patients (r = 0.408, 95% confidence interval = [0.187, 0.589], p < 0.001), while psychosis severity was comparable between these groups (for Brief Psychiatric Rating Scale: U = 3057, z = -0.129, p = 0.897; disorganization: U = 2986.5, z = -0.274, p = 0.784 and for CAT-Psychosis: U = 2800.5, z = -1.022, p = 0.307). Subgroup of patients with schizophrenia spectrum disorders showed very similar results. CONCLUSIONS: Insight moderates the correlation between self-reported and clinician-rated severity of psychosis, yet CAT-Psychosis remains valid in patients with both high and low awareness of illness.

Accounting for Context in Randomized Trials after Assignment.

Many preventive trials randomize individuals to intervention condition which is then delivered in a group setting. Other trials randomize higher levels, say organizations, and then use learning collaboratives comprised of multiple organizations to support improved implementation or sustainment. Other trials randomize or expand existing social networks and use key opinion leaders to deliver interventions through these networks. We use the term contextually driven to refer generally to such trials (traditionally referred to as clustering, where groups are formed either pre-randomization or post-randomization - i.e., a cluster-randomized trial), as these groupings or networks provide fixed or time-varying contexts that matter both theoretically and practically in the delivery of interventions. While such contextually driven trials can provide efficient and effective ways to deliver and evaluate prevention programs, they all require analytical procedures that take appropriate account of non-independence, something not always appreciated. Published analyses of many prevention trials have failed to take this into account. We discuss different types of contextually driven designs and then show that even small amounts of non-independence can inflate actual Type I error rates. This inflation leads to rejecting the null hypotheses too often, and erroneously leading us to conclude that there are significant differences between interventions when they do not exist. We describe a procedure to account for non-independence in the important case of a two-arm trial that randomizes units of individuals or organizations in both arms and then provides the active treatment in one arm through groups formed after assignment. We provide sample code in multiple programming languages to guide the analyst, distinguish diverse contextually driven designs, and summarize implications for multiple audiences.

Between-center variation in high-priority listing status under the new heart allocation policy.

Under the new US heart allocation policy, transplant centers listed significantly more candidates at high priority statuses (Status 1 and 2) with mechanical circulatory support devices than expected. We determined whether the practice change was widespread or concentrated among certain transplant centers. Using data from the Scientific Registry of Transplant Recipients, we used mixed-effect logistic regression to compare the observed listings of adult, heart-alone transplant candidates post-policy (December 2018 to February 2020) to seasonally matched pre-policy cohort (December 2016 to February 2018). US transplant centers (N = 96) listed similar number of candidates in each policy period (4472 vs. 4498) but listed significantly more at high priority status (25.5% vs. 7.0%, p < .001) than expected. Adjusted for candidate characteristics, 91 of 96 (94.8%) centers listed significantly more candidates at high-priority status than expected, with the unexpected increase varying from 4.8% to 50.4% (interquartile range [IQR]: 14.0%-23.3%). Centers in OPOs with highest Status 1A transplant rate pre-policy were significantly more likely to utilize high-priority status under the new policy (OR: 9.73, p = .01). The new heart allocation policy was associated with widespread and significantly variable changes in transplant center practice that may undermine the effectiveness of the new system.

Associating Psychotic Symptoms with Altered Brain Anatomy in Psychotic Disorders Using Multidimensional Item Response Theory Models.

Reduced cortical thickness has been demonstrated in psychotic disorders, but its relationship to clinical symptoms has not been established. We aimed to identify the regions throughout neocortex where clinical psychosis manifestations correlate with cortical thickness. Rather than perform a traditional correlation analysis using total scores on psychiatric rating scales, we applied multidimensional item response theory to identify a profile of psychotic symptoms that was related to a region where cortical thickness was reduced. This analysis was performed using a large population of probands with psychotic disorders (N = 865), their family members (N = 678) and healthy volunteers (N = 347), from the 5-site Bipolar-Schizophrenia Network for Intermediate Phenotypes. Regional cortical thickness from structural magnetic resonance scans was measured using FreeSurfer; individual symptoms were rated using the Positive and Negative Syndrome Scale, Montgomery-Asberg Depression Rating Scale, and Young Mania Rating Scale. A cluster of cortical regions whose thickness was inversely related to severity of psychosis symptoms was identified. The regions turned out to be located contiguously in a large region of heteromodal association cortex including temporal, parietal and frontal lobe regions, suggesting a cluster of contiguous neocortical regions important to psychosis expression. When we tested the relationship between reduced cortical surface area and high psychotic symptoms we found no linked regions describing a related cortical set.

Depression and anxiety symptoms across pregnancy and the postpartum in low-income Black and Latina women.

Underserved women of color experience high rates of perinatal affective disorders, but most research to date on the natural history of these disorders has been conducted on White women. The present study investigated longitudinal changes in anxiety and depression in a sample of perinatal non-Hispanic Black and Latina women. Categorical (yes/no) measures of positive anxiety and depression screens, as well as total symptom scores, were measured longitudinally across the perinatal period in 178 women (115 non-Hispanic Black, 63 Latina) using the CAT-MH™, a computerized adaptive test. Time (up to 4 visits) and race/ethnicity effects were assessed in linear mixed effects models. Rates of positive anxiety screenings were 13.6%, 3.2%, 8.5%, and 0% in Latina women and 2.6%, 4.2%, 6.1%, and 5.8% in non-Hispanic Black women in the 1st, 2nd, and 3rd trimesters, and postpartum, respectively. Rates of positive anxiety screenings overall were highest in the first trimester (OR = 0.20; 95% CI 0.04-0.98), and there was a significant time-by-race/ethnicity interaction for positive anxiety screens (OR = 8.88; 95% CI 1.42-55.51), as positive screens were most frequent in the first trimester and sharply declined for Latina women, while rates were relatively consistent across the perinatal period in non-Hispanic Black women. Rates of positive depression screens did not change over time, but there was a trend (OR = 1.93; 95% CI 0.93-4.03) for a time-by-race/ethnicity interaction in a direction similar to that seen for anxiety. The odds of positive anxiety screens vary by race/ethnicity and trimester, suggesting that anxiety screening and anxiety interventions may be most resourcefully used in the first trimester for Latina women in particular.

Imputing Gene Expression in Uncollected Tissues Within and Beyond GTEx.

Gene expression and its regulation can vary substantially across tissue types. In order to generate knowledge about gene expression in human tissues, the Genotype-Tissue Expression (GTEx) program has collected transcriptome data in a wide variety of tissue types from post-mortem donors. However, many tissue types are difficult to access and are not collected in every GTEx individual. Furthermore, in non-GTEx studies, the accessibility of certain tissue types greatly limits the feasibility and scale of studies of multi-tissue expression. In this work, we developed multi-tissue imputation methods to impute gene expression in uncollected or inaccessible tissues. Via simulation studies, we showed that the proposed methods outperform existing imputation methods in multi-tissue expression imputation and that incorporating imputed expression data can improve power to detect phenotype-expression correlations. By analyzing data from nine selected tissue types in the GTEx pilot project, we demonstrated that harnessing expression quantitative trait loci (eQTLs) and tissue-tissue expression-level correlations can aid imputation of transcriptome data from uncollected GTEx tissues. More importantly, we showed that by using GTEx data as a reference, one can impute expression levels in inaccessible tissues in non-GTEx expression studies.

Validation of the Computerized Adaptive Test for Mental Health in Primary Care.

PURPOSE: The US Preventive Services Task Force recommends screening for depression in the general adult population. Although screening questionnaires for depression and anxiety exist in primary care settings, electronic health tools such as computerized adaptive tests based on item response theory can advance screening practices. This study evaluated the validity of the Computerized Adaptive Test for Mental Health (CAT-MH) for screening for major depressive disorder (MDD) and assessing MDD and anxiety severity among adult primary care patients. METHODS: We approached 402 English-speaking adults for participation from a primary care clinic, of whom 271 adults (71% female, 65% black) participated. Participants completed modules from the CAT-MH (Computerized Adaptive Diagnostic Test for MDD, CAT-Depression Inventory, CAT-Anxiety Inventory); brief paper questionnaires (9-item Patient Health Questionnaire [PHQ-9], 2-item Patient Health Questionnaire [PHQ-2], Generalized Anxiety Disorder 7-item Scale [GAD-7]); and a reference-standard interview, the Structured Clinical Interview for DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition) Diagnoses. RESULTS: On the basis of the interview, 31 participants met criteria for MDD and 29 met criteria for GAD. The diagnostic accuracy of the Computerized Adaptive Diagnostic Test for MDD (area under curve [AUC] = 0.85) was similar to that of the PHQ-9 (AUC = 0.84) and higher than that of the PHQ-2 (AUC = 0.76) for MDD screening. Using the interview as the reference standard, the accuracy of the CAT-Anxiety Inventory (AUC = 0.93) was similar to that of the GAD-7 (AUC = 0.97) for assessing anxiety severity. The patient-preferred screening method was assessment via tablet/computer with audio. CONCLUSIONS: Computerized adaptive testing could be a valid and efficient patient-centered screening strategy for depression and anxiety screening in primary care settings.

Without Wasting a Word: Extreme Improvements in Efficiency and Accuracy Using Computerized Adaptive Testing for Mental Health Disorders (CAT-MH).

PURPOSE OF REVIEW: We review recent literature on the adaptive assessment of complex mental health disorders and provide a detailed comparison of classical test theory and adaptive testing based on multidimensional item response theory. RECENT FINDINGS: Adaptive tests for a wide variety of mental health traits (e.g., depression, anxiety, mania, substance misuse, suicidality) are now available in a cloud-based environment. These tests have been validated in a variety of settings against lengthy structured clinical interviews with excellent results and even higher reliability than fixed-length tests. Applications include screening and assessments in emergency departments, psychiatric and primary care clinics, student health clinics, perinatal medicine clinics, child welfare settings, and the judicial system. The future of mental health measurement will be based on automated screening and assessments. Adaptive tests will provide increased precision of measurement and decreased burden of measurement. Integration into the electronic health record is important and now easily accomplished.

Association of Transplant Center With Survival Benefit Among Adults Undergoing Heart Transplant in the United States.

Importance: In the United States, the number of deceased donor hearts available for transplant is limited. As a proxy for medical urgency, the US heart allocation system ranks heart transplant candidates largely according to the supportive therapy prescribed by transplant centers. Objective: To determine if there is a significant association between transplant center and survival benefit in the US heart allocation system. Design, Setting, and Participants: Observational study of 29 199 adult candidates for heart transplant listed on the national transplant registry from January 2006 through December 2015 with follow-up complete through August 2018. Exposures: Transplant center. Main Outcomes and Measures: The survival benefit associated with heart transplant as defined by the difference between survival after heart transplant and waiting list survival without transplant at 5 years. Each transplant center's mean survival benefit was estimated using a mixed-effects proportional hazards model with transplant as a time-dependent covariate, adjusted for year of transplant, donor quality, ischemic time, and candidate status. Results: Of 29 199 candidates (mean age, 52 years; 26% women) on the transplant waiting list at 113 centers, 19 815 (68%) underwent heart transplant. Among heart transplant recipients, 5389 (27%) died or underwent another transplant operation during the study period. Of the 9384 candidates who did not undergo heart transplant, 5669 (60%) died (2644 while on the waiting list and 3025 after being delisted). Estimated 5-year survival was 77% (interquartile range [IQR], 74% to 80%) among transplant recipients and 33% (IQR, 17% to 51%) among those who did not undergo heart transplant, which is a survival benefit of 44% (IQR, 27% to 59%). Survival benefit ranged from 30% to 55% across centers and 31 centers (27%) had significantly higher survival benefit than the mean and 30 centers (27%) had significantly lower survival benefit than the mean. Compared with low survival benefit centers, high survival benefit centers performed heart transplant for patients with lower estimated expected waiting list survival without transplant (29% at high survival benefit centers vs 39% at low survival benefit centers; survival difference, -10% [95% CI, -12% to -8.1%]), although the adjusted 5-year survival after transplant was not significantly different between high and low survival benefit centers (77.6% vs 77.1%, respectively; survival difference, 0.5% [95% CI, -1.3% to 2.3%]). Overall, for every 10% decrease in estimated transplant candidate waiting list survival at a given center, there was an increase of 6.2% (95% CI, 5.2% to 7.3%) in the 5-year survival benefit associated with heart transplant. Conclusions and Relevance: In this registry-based study of US heart transplant candidates, transplant center was associated with the survival benefit of transplant. Although the adjusted 5-year survival after transplant was not significantly different between high and low survival benefit centers, compared with centers with survival benefit significantly below the mean, centers with survival benefit significantly above the mean performed heart transplant for recipients who had significantly lower estimated expected 5-year waiting list survival without transplant.

A note on marginalization of regression parameters from mixed models of binary outcomes.

This article discusses marginalization of the regression parameters in mixed models for correlated binary outcomes. As is well known, the regression parameters in such models have the "subject-specific" (SS) or conditional interpretation, in contrast to the "population-averaged" (PA) or marginal estimates that represent the unconditional covariate effects. We describe an approach using numerical quadrature to obtain PA estimates from their SS counterparts in models with multiple random effects. Standard errors for the PA estimates are derived using the delta method. We illustrate our proposed method using data from a smoking cessation study in which a binary outcome (smoking, Y/N) was measured longitudinally. We compare our estimates to those obtained using GEE and marginalized multilevel models, and present results from a simulation study.

Are Evidence-based Practices Associated With Effective Prevention of Hospital-acquired Pressure Ulcers in US Academic Medical Centers?

BACKGROUND: In 2008, the Centers for Medicare and Medicaid Services (CMS) established nonpayment policies resulting from costliness of hospital-acquired pressure ulcers (HAPUs) to hospitals. This prompted hospitals to adopt quality improvement (QI) interventions that increase use of evidence-based practices (EBPs) for HAPU prevention. OBJECTIVE: To evaluate the longitudinal impact of CMS policy and QI adoption on HAPU rates. MATERIALS AND METHODS: We characterized longitudinal adoption of 25 QI interventions that support EBPs through hospital leadership, staff, information technology, and performance and improvement. Quarterly counts of HAPU incidence and inpatient characteristics were collected from 55 University HealthSystem Consortium hospitals between 2007 and 2012. Mixed-effects regression models tested the longitudinal association of CMS policy, HAPU coding, and QI on HAPU rates. The models assumed level-2 random intercepts and random effects for CMS policy and EBP implementation to account for between-hospital variability in HAPU incidence. RESULTS: Controlling for all 25 QI interventions, specific updates to EBPs for HAPU prevention had a significant, though modest reduction on HAPU rates (-1.86 cases/quarter; P=0.002) and the effect of CMS nonpayment policy on HAPU prevention was much greater (-11.32 cases/quarter; P<0.001). CONCLUSIONS: HAPU rates were significantly lower after changes in CMS reimbursement. Reductions are associated with hospital-wide implementation of EBPs for HAPU prevention. Given that administrative data were used, it remains unknown whether these improvements were due to changes in coding or improved quality of care.

Distribution of donor lungs in the United States: a case for broader geographic sharing.

OBJECTIVES: To evaluate the association between allocation of donor lungs by geographic sharing type (GST) and lung allocation score (LAS). METHODS: UNOS data included lung transplant recipients between 5/4/05 and 09/30/15 (n = 17 416) grouped by GST of donor lungs: local, regional, or national. Recipients were stratified by LAS <50, 50-75, and >75. Kaplan-Meier analysis was used to assess five-yr survival. RESULTS: The majority of lungs were shared locally (n = 9200; 52.8%) followed by nationally (n = 5356; 30.8%) and regionally (n = 2860; 16.4%). There was a significant difference in the mean LAS at transplant (local: 43.7 ± 15; regional: 49.5 ± 18.8; national 51 ± 19.4; p < 0.001). There was a significant association between GST and LAS (p < 0.001). The majority (n = 7431; 58.2%) of recipients with LAS <50 received local lungs. Recipients with LAS >75 received a majority of their organs from national (n = 881; 45.4%) and regional (n = 414; 21.6%) donors. Although statistically significant (p = 0.024), absolute decline in five-yr survival by GST in the national GST was only 1.1% compared to the local GST. CONCLUSIONS: Nearly half of all lungs in the United States are allocated locally to recipients with an LAS <50. Additional studies should determine if organ sharing over broader geographies would improve waitlist outcomes.

Computerized Adaptive Diagnosis and Testing of Mental Health Disorders.

In this review we explore recent developments in computerized adaptive diagnostic screening and computerized adaptive testing for the presence and severity of mental health disorders such as depression, anxiety, and mania. The statistical methodology is unique in that it is based on multidimensional item response theory (severity) and random forests (diagnosis) instead of traditional mental health measurement based on classical test theory (a simple total score) or unidimensional item response theory. We show that the information contained in large item banks consisting of hundreds of symptom items can be efficiently calibrated using multidimensional item response theory, and the information contained in these large item banks can be precisely extracted using adaptive administration of a small set of items for each individual. In terms of diagnosis, computerized adaptive diagnostic screening can accurately track an hour-long face-to-face clinician diagnostic interview for major depressive disorder (as an example) in less than a minute using an average of four questions with unprecedented high sensitivity and specificity. Directions for future research and applications are discussed.

The experience of depression, anxiety, and mania among perinatal women.

We assessed differential item functioning (DIF) based on computerized adaptive testing (CAT) to examine how perinatal mood disorders differ from adult psychiatric disorders. The CAT-Mental Health (CAT-MH) was administered to 1614 adult psychiatric outpatients and 419 perinatal women with IRB approval. We examined individual item-level differences using logistic regression and overall score differences by scoring the perinatal data using the original bifactor model calibration based on the psychiatric sample data and a new bifactor model calibration based on the perinatal data and computing their correlation. To examine convergent validity, we computed correlations of the CAT-MH with contemporaneously administered Edinburgh Postnatal Depression Scales (EPDS). The rate of major depression in the perinatal sample was 13 %. Rates of anxiety, mania, and suicide risk were 5, 6, and 0.4 %, respectively. One of 66 depression items, one of 69 anxiety items, and 15 of 53 mania items exhibited DIF (i.e., failure to discriminate between high and low levels of the disorder) in the perinatal sample based on the psychiatric sample calibration. Removal of these items resulted in correlations of the original and perinatal calibrations of r = 0.983 for depression, r = 0.986 for anxiety, and r = 0.932 for mania. The 91.3 % of cases were concordantly categorized as either "at-risk" or "low-risk" between the EPDS and the perinatal calibration of the CAT-MH. There was little evidence of DIF for depression and anxiety symptoms in perinatal women. This was not true for mania. Now calibrated for perinatal women, the CAT-MH can be evaluated for longitudinal symptom monitoring.

Environmental and state-level regulatory factors affect the incidence of autism and intellectual disability.

Many factors affect the risks for neurodevelopmental maladies such as autism spectrum disorders (ASD) and intellectual disability (ID). To compare environmental, phenotypic, socioeconomic and state-policy factors in a unified geospatial framework, we analyzed the spatial incidence patterns of ASD and ID using an insurance claims dataset covering nearly one third of the US population. Following epidemiologic evidence, we used the rate of congenital malformations of the reproductive system as a surrogate for environmental exposure of parents to unmeasured developmental risk factors, including toxins. Adjusted for gender, ethnic, socioeconomic, and geopolitical factors, the ASD incidence rates were strongly linked to population-normalized rates of congenital malformations of the reproductive system in males (an increase in ASD incidence by 283% for every percent increase in incidence of malformations, 95% CI: [91%, 576%], p<6×10(-5)). Such congenital malformations were barely significant for ID (94% increase, 95% CI: [1%, 250%], p = 0.0384). Other congenital malformations in males (excluding those affecting the reproductive system) appeared to significantly affect both phenotypes: 31.8% ASD rate increase (CI: [12%, 52%], p<6×10(-5)), and 43% ID rate increase (CI: [23%, 67%], p<6×10(-5)). Furthermore, the state-mandated rigor of diagnosis of ASD by a pediatrician or clinician for consideration in the special education system was predictive of a considerable decrease in ASD and ID incidence rates (98.6%, CI: [28%, 99.99%], p = 0.02475 and 99% CI: [68%, 99.99%], p = 0.00637 respectively). Thus, the observed spatial variability of both ID and ASD rates is associated with environmental and state-level regulatory factors; the magnitude of influence of compound environmental predictors was approximately three times greater than that of state-level incentives. The estimated county-level random effects exhibited marked spatial clustering, strongly indicating existence of as yet unidentified localized factors driving apparent disease incidence. Finally, we found that the rates of ASD and ID at the county level were weakly but significantly correlated (Pearson product-moment correlation 0.0589, p = 0.00101), while for females the correlation was much stronger (0.197, p<2.26×10(-16)).

Multiple imputation for harmonizing longitudinal non-commensurate measures in individual participant data meta-analysis.

There are many advantages to individual participant data meta-analysis for combining data from multiple studies. These advantages include greater power to detect effects, increased sample heterogeneity, and the ability to perform more sophisticated analyses than meta-analyses that rely on published results. However, a fundamental challenge is that it is unlikely that variables of interest are measured the same way in all of the studies to be combined. We propose that this situation can be viewed as a missing data problem in which some outcomes are entirely missing within some trials and use multiple imputation to fill in missing measurements. We apply our method to five longitudinal adolescent depression trials where four studies used one depression measure and the fifth study used a different depression measure. None of the five studies contained both depression measures. We describe a multiple imputation approach for filling in missing depression measures that makes use of external calibration studies in which both depression measures were used. We discuss some practical issues in developing the imputation model including taking into account treatment group and study. We present diagnostics for checking the fit of the imputation model and investigate whether external information is appropriately incorporated into the imputed values.

Antidepressant treatment and suicide attempts and self-inflicted injury in children and adolescents.

PURPOSE: In the 2004, FDA placed a black box warning on antidepressants for risk of suicidal thoughts and behavior in children and adolescents. The purpose of this paper is to examine the risk of suicide attempt and self-inflicted injury in depressed children ages 5-17 treated with antidepressants in two large observational datasets taking account time-varying confounding. METHODS: We analyzed two large US medical claims databases (MarketScan and LifeLink) containing 221,028 youth (ages 5-17) with new episodes of depression, with and without antidepressant treatment during the period of 2004-2009. Subjects were followed for up to 180 days. Marginal structural models were used to adjust for time-dependent confounding. RESULTS: For both datasets, significantly increased risk of suicide attempts and self-inflicted injury were seen during antidepressant treatment episodes in the unadjusted and simple covariate adjusted analyses. Marginal structural models revealed that the majority of the association is produced by dynamic confounding in the treatment selection process; estimated odds ratios were close to 1.0 consistent with the unadjusted and simple covariate adjusted association being a product of chance alone. CONCLUSIONS: Our analysis suggests antidepressant treatment selection is a product of both static and dynamic patient characteristics. Lack of adjustment for treatment selection based on dynamic patient characteristics can lead to the appearance of an association between antidepressant treatment and suicide attempts and self-inflicted injury among youths in unadjusted and simple covariate adjusted analyses. Marginal structural models can be used to adjust for static and dynamic treatment selection processes such as that likely encountered in observational studies of associations between antidepressant treatment selection, suicide and related behaviors in youth.