Shortening the Alzheimer's disease assessment scale cognitive subscale

BACKGROUND

A short yet reliable cognitive measure is needed that separates treatment and placebo for treatment trials for Alzheimer's disease. Hence, we aimed to shorten the Alzheimer's Disease Assessment Scale Cognitive Subscale (ADAS-Cog) and test its use as an efficacy measure.

METHODS

Secondary data analysis of participant-level data from five pivotal clinical trials of donepezil compared with placebo for Alzheimer's disease (N = 2,198). Across all five trials, cognition was appraised using the original 11-item ADAS-Cog. Statistical analysis consisted of sample characterization, item response theory (IRT) to identify an ADAS-Cog short version, and mixed models for repeated-measures analysis to examine the effect sizes of ADAS-Cog change on the original and short versions in the placebo versus donepezil groups.

RESULTS

Based on IRT, a short ADAS-Cog was developed with seven items and two response options. The original and short ADAS-Cog correlated at baseline and at weeks 12 and 24 at 0.7. Effect sizes based on mixed modeling showed that the short and original ADAS-Cog separated placebo and donepezil comparably (ADAS-Cog original ES = 0.33, 95% CI = 0.29, 0.40, ADAS-Cog short ES = 0.25, 95% CI =0.23, 0.34).

CONCLUSIONS

IRT identified a short ADAS-cog version that separated donepezil and placebo, suggesting its clinical potential for assessment and treatment monitoring.

Single trajectory treatment response for predominant negative symptoms: Post-hoc analysis of a clinical trial with cariprazine and risperidone

Examining the heterogeneity of negative symptoms of schizophrenia contributes to the identification of available treatment targets. Generally, prior evidence classified three to four symptom treatment response trajectory groups over the course of positive symptoms, yet, no evidence exists regarding the heterogeneity of medium-term response to predominant negative symptoms. The current post-hoc analysis aims to identify the heterogeneity in negative symptom treatment response trajectories among patients with predominant negative symptoms who received either cariprazine or risperidone for 26 weeks. Treatment response was analyzed based on the: the Positive and Negative Syndrome Scale Factor Score for Negative Symptoms (PANSS-FSNS), and the Clinical Global Impression Severity (CGIS) and Improvement (CGII) scales. To identify subgroups of patients with a similar course of treatment response, group-based trajectory modelling was utilized. Results demonstrated that in comparison with competing models, a single trajectory best described the treatment response of patients with predominant negative symptoms. The results indicate that patients with predominant negative symptoms with over ten years of schizophrenia respond rapidly to adequate treatment and follow a course of steady improvement.

Is cognition integral to psychopathology? A population-based cohort study

BACKGROUND

Lower cognitive functioning has been documented across psychiatric disorders and hypothesized to be a core deficit of mental disorders. Situating psychopathology and cognition as part of a unitary construct is therefore important to understanding the etiology of psychiatric disorders. The current study aims to test competing structural models of psychopathology and cognition in a large national cohort of adolescents.

METHODS

The analytic sample consisted of 1189 participants aged 16-17 years, screened by the Israeli Draft Board. Psychopathology was assessed using a modified version of the Brief Symptom Inventory, and cognition was assessed based on four standardized test scores ((1) mathematical reasoning, concentration, and concept manipulation; (2) visual-spatial problem-solving skills and nonverbal abstract reasoning; (3) verbal understanding; (4) categorization and verbal abstraction). Confirmatory factor analysis was implemented to compare competing structural models of psychopathology with and without cognition. Sensitivity analyses examined the models in different subpopulations.

RESULTS

Confirmatory factor analysis indicated a better model fit of psychopathological symptoms without cognition (RMSEA = 0.037; TLI = 0.991; CFI = 0.992) than with cognition (RMSEA = 0.04-0.042; TLI = 0.987-0.988; CFI = 0.988-0.989). Sensitivity analyses supported the robustness of these results with a single exception. Among participants with low cognitive abilities (N = 139), models that integrated psychopathological symptoms with cognition had a better fit compared to models of psychopathology without cognition.

CONCLUSIONS

The current study suggests that cognition and psychopathology are, generally, independent constructs. However, within low cognitive abilities, cognition was integral to the structure of psychopathology. Our results point toward an increased vulnerability to psychopathology in individuals with low cognitive abilities and may provide valuable information for clinicians.

Maternal rheumatoid arthritis and risk of autism in the offspring

BACKGROUND

Maternal Rheumatoid Arthritis (RA) is suggested to increase the risk of Autism Spectrum Disorder (ASD) in the offspring, mainly through inflammation/autoimmunity, but the association is unclear. A prospective population-based cohort study was implemented to examine the association between maternal RA and offspring ASD.

METHODS

We included all children born alive in Sweden from 1995 to 2015, followed up through 2017. Diagnoses of ASD and RA were clinically ascertained from National Patient Register. We quantified the association by hazard ratios (HR) and two-sided 95% confidence intervals (CI), from Cox regression after detailed adjustment for potential confounders. We examined RA serostatus, etiological subgroups and the timing of exposure. To closer examine the underlying mechanism for the association, we included a negative control group for RA, arthralgia, with similar symptomology as RA but free from inflammation/autoimmunity.

RESULTS

Of 3629 children born to mothers with RA, 70 (1.94%) were diagnosed with ASD, compared to 28 892 (1.92%) of 1 503 908 children born to mothers without RA. Maternal RA before delivery was associated with an increased risk of offspring ASD (HR = 1.43, 95% CI 1.11-1.84), especially for seronegative RA (HR = 1.61, 95% CI 1.12-2.30). No similar association was observed for paternal RA, maternal sisters with RA, or RA diagnosed after delivery. Maternal arthralgia displayed as high risks for offspring ASD as did maternal RA (HR = 1.41, 95% CI 1.24-1.60).

CONCLUSIONS

In Sweden, maternal RA before delivery was associated with an increased risk of offspring ASD. The comparable association between maternal arthralgia and ASD risk suggests other pathways of risk than autoimmunity/inflammation, acting jointly or independently of RA.

Adult Attention-Deficit/Hyperactivity Disorder and the Risk of Dementia

Importance

Evidence that adult attention-deficit/hyperactivity disorder (ADHD) is associated with an increased risk of dementia is scarce and inconsistent, and potential sources of bias are untested.

Objective

To examine the association between adult ADHD and the risk of dementia.

Design, Setting, and Participants

This prospective national cohort study consisted of 109 218 members of a nonprofit Israeli health maintenance organization born between 1933 and 1952 who entered the cohort on January 1, 2003, without an ADHD or dementia diagnosis and were followed up to February 28, 2020. Participants were aged 51 to 70 years in 2003. Statistical analysis was conducted from December 2022 to August 2023.

Exposure

Adult ADHD was a time-varying covariate, classified as present from the age of the first diagnosis (using the International Classification of Diseases, Ninth Revision, and the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision); otherwise, absent.

Main Outcome and Measures

Cox regression models were fitted to quantify the association between adult ADHD and the risk of incident dementia with hazard ratios (HRs) and their 95% CIs unadjusted and in the primary analysis, using inverse probability weights, adjusted for 18 sources of potential confounding. In 14 complementary analyses, subgroup and sensitivity analyses were implemented.

Results

At the beginning of the follow-up, the sample of 109 218 participants had a mean (SD) age of 57.7 (5.5) years, 56 474 participants (51.7%) were female, and 52 744 (48.3%) were male. During follow-up, 730 participants (0.7%) received a diagnosis of adult ADHD, and 7726 (7.1%) received a diagnosis of dementia. Dementia occurred among 96 of 730 participants (13.2%) with adult ADHD and 7630 of 108 488 participants (7.0%) without adult ADHD. In the primary analysis, compared with the absence of adult ADHD, the presence of adult ADHD was statistically significantly (P < .001) associated with an increased dementia risk (unadjusted HR, 3.62 [95% CI, 2.92-4.49; P < .001]; adjusted HR, 2.77 [95% CI, 2.11-3.63; P < .001]). Twelve of the 14 complementary analyses did not attenuate the conclusions based on the results of the primary analysis. There was, however, no clear increase in the risk of dementia associated with adult ADHD among those who received psychostimulant medication, and evidence of reverse causation was mild.

Conclusions and Relevance

In this cohort study of individuals born between 1933 and 1952 and followed up in old age, adult ADHD was associated with an increased risk of dementia. Policy makers, caregivers, patients, and clinicians may wish to monitor reliably for ADHD in old age.

Increased incident rates of antidepressant use during the COVID-19 pandemic: interrupted time-series analysis of a nationally representative sample

BACKGROUND

The COVID-19 pandemic has been associated with increased levels of depression and anxiety with implications for the use of antidepressant medications.

METHODS

The incident rate of antidepressant fills before and during the COVID-19 pandemic were compared using interrupted time-series analysis followed by comprehensive sensitivity analyses on data derived from electronic medical records from a large health management organization providing nationwide services to 14% of the Israeli population. The dataset covered the period from 1 January 2013 to 1 February 2021, with 1 March 2020 onwards defined as the period of the COVID-19 pandemic. Forecasting analysis was implemented to test the effect of the vaccine roll-out and easing of social restrictions on antidepressant use.

RESULTS

The sample consisted of 852 233 persons with a total antidepressant incident fill count of 139 535.4 (total cumulative rate per 100 000 = 16 372.91, 95% CI 16 287.19-16 459.01). We calculated the proportion of antidepressant prescription fills for the COVID-19 period, and the counterfactual proportion for the same period, assuming COVID-19 had not occurred. The difference in these proportions was significant [Cohen's h = 10-3 (0.16), 95% CI 10-3 ( - 0.71 to 1.03)]. The pandemic was associated with a significant increase in the slope of the incident rate of antidepressant fills (slope change = 0.01, 95% CI 0.00-0.03; p = 0.04) and a monthly increase of 2% compared to the counterfactual (the estimated rate assuming no pandemic occurred). The increased rate was more pronounced in women, and was not modified by lockdown on/off periods, socioeconomic or SARS-CoV-2 status. The rate of observed antidepressant fills was similar to that forecasted under the assumption of ongoing COVID-19 distress.

CONCLUSION

These findings underscore the toll of the pandemic on mental health and inform mental health policy and service delivery during and after implementing COVID-19 attenuation strategies.

Attempted suicide rates before and during the COVID-19 pandemic: interrupted time series analysis of a nationally representative sample

BACKGROUND

To characterize the association between the protracted biopsychosocial coronavirus disease 2019 (COVID-19) pandemic exposures and incident suicide attempt rates.

METHODS

Data were from a nationally representative cohort based on electronic health records from January 2013 to February 2021 (N = 852 233), with an interrupted time series study design. For the primary analysis, the effect of COVID-19 pandemic on incident suicide attempts warranting in-patient hospital treatment was quantified by fitting a Poisson regression and modeling the relative risk (RR) and the corresponding 95% confidence intervals (CIs). Scenarios were forecast to predict attempted suicide rates at 10 months after social mitigation strategies. Fourteen sensitivity analyses were performed to test the robustness of the results.

RESULTS

Despite the increasing trend in the unexposed interval, the interval exposed to the COVID-19 pandemic was statistically significant (p < 0.001) associated with a reduced RR of incident attempted suicide (RR = 0.63, 95% CI 0.52-0.78). Consistent with the primary analysis, sensitivity analysis of sociodemographic groups and methodological factors were statistically significant (p < 0.05). No effect modification was identified for COVID-19 lockdown intervals or COVID-19 illness status. All three forecast scenarios at 10 months projected a suicide attempt rate increase from 12.49 (7.42-21.01) to 21.38 (12.71-35.99).

CONCLUSIONS

The interval exposed to the protracted mass social trauma of the COVID-19 pandemic was associated with a lower suicide attempt rate compared to the unexposed interval. However, this trend is likely to reverse 10 months after lifting social mitigation policies, underscoring the need for enhanced implementation of public health policy for suicide prevention.

Rates of Spontaneous Abortion in Israel Before and During the COVID-19 Pandemic

This cross-sectional study uses electronic health record data to compare monthly incidence rates of spontaneous abortion in Israel before and during the COVID-19 pandemic.

Somatic comorbidities of mental disorders in pregnancy

BACKGROUND

Mental and physical health conditions are frequently comorbid. Despite the widespread physiological and behavioral changes during pregnancy, the pattern of comorbidities among women in pregnancy is not well studied. This study aimed to systematically examine the associations between mental and somatic disorders before and during pregnancy.

METHOD

The study used data from mothers of a nationally representative birth cohort of children born in Israel (1997-2008). We compared the risk of all major somatic disorders (International Classification of Diseases, Ninth Revision) in pregnant women with and without a mental disorder. All analyses were adjusted for maternal age, child's birth year, family socioeconomic status, and the total number of maternal encounters with health services around pregnancy period.

RESULTS

The analytical sample included 77,030 mother-child dyads, with 30,083 unique mothers. The mean age at child's birth was 29.8 years. Prevalence of diagnosis of mental disorder around pregnancy in our sample was 4.4%. Comorbidity between mental and somatic disorders was two times higher than the comorbidity between pairs of different somatic disorders. Of the 17 somatic disorder categories, seven were positively associated with mental health disorders. The highly prevalent comorbidities associated with mental disorders in pregnancy included e.g. musculoskeletal (OR = 1.30; 95% CI = 1.20-1.42) and digestive system diseases (OR = 1.23; 95% CI = 1.13-1.34).

CONCLUSIONS

We observed that associations between maternal diagnoses and mental health stand out from the general pattern of comorbidity between nonmental health diseases. The study results confirm the need for screening for mental disorders during pregnancy and for potential comorbid conditions associated with mental disorders.

Linkage of Young Mania Rating Scale to Clinical Global Impression Scale to Enhance Utility in Clinical Practice and Research Trials

INTRODUCTION

The Young Mania Rating Scale (YMRS) is the gold standard to assess manic symptoms of bipolar disorder, yet the clinical meaning of scores is unknown. To clinically understand and interpret YMRS scores, we examined linkages between the total and change scores of YMRS with the Clinical Global Impression (CGI) ratings.

METHODS

Individual participant data (N=2,988) from eight randomized, double-blind, placebo-controlled trials were included. Data were collected at baseline and subsequent visits. Spearman's correlation coefficients ρ were computed, and equipercentile linking was implemented.

RESULTS

A YMRS score of 6 points corresponded approximately to 'borderline mentally ill,' 12 points to 'mildly ill,' 20 points to 'moderately ill,' 30 points to 'markedly ill,' 40 points to 'severely ill,' and 52 points to 'among the most extremely ill' patients on the CGI-S. A reduction of CGI-S by one point as well as 'minimally improved' on the CGI-I corresponded approximately to an absolute decrease of 4 to 8 YMRS points or a 21% to 29% reduction of YMRS baseline score whereas a reduction of CGI-S by two points and 'much improved' on the CGI-I corresponded to an absolute decrease of 10 to 15 points or a 42% to 53% reduction of YMRS baseline score.

DISCUSSION

The current study findings offer clinicians meaningful cutoff values to interpret YMRS scores. Moreover, these values contribute to the definition of treatment targets, response, remission, and entry criteria in mania trials.

Habituation of Fear-Israeli-Jewish Population during Protracted Belligerence

The identification of demographic factors of vulnerability and resilience in communities facing belligerent conflicts is increasingly relevant today. This representative study aims to examine the effect of protracted violence on the level of fear of the overall Israeli-Jewish population, and the role of the conflict on the connection between socio-economic factors and fears. Sixty-six representative samples were identified and surveyed from 2001 to 2019 (n = 37,190) that occurred during (n = 14,362) and between (n = 22,828) seven conflicts and non-conflict periods. Results show that during military conflicts, civilians declared less fears of physical injury comparing routine time; a slow trend of decline in the level of fears over time was observed; during routine periods, fear was associated with female-gender and with the lowest income level group. Ultra-orthodox and Religious respondents had significantly less fear than the secular and traditional respondents. During military conflicts, the results changed significantly, mainly for the lowest income group, women and ultra-orthodox.

Effect size quantification for interrupted time series analysis: implementation in R and analysis for Covid-19 research

Background

Interrupted time series (ITS) analysis is a time series regression model that aims to evaluate the effect of an intervention on an outcome of interest. ITS analysis is a quasi-experimental study design instrumental in situations where natural experiments occur, gaining popularity, particularly due to the Covid-19 pandemic. However, challenges, including the lack of a control group, have impeded the quantification of the effect size in ITS. The current paper proposes a method and develops a user-friendly R package to quantify the effect size of an ITS regression model for continuous and count outcomes, with or without seasonal adjustment.

Results

The effect size presented in this work, together with its corresponding 95% confidence interval (CI) and P-value, is based on the ITS model-based fitted values and the predicted counterfactual (the exposed period had the intervention not occurred) values. A user-friendly R package to fit an ITS and estimate the effect size was developed and accompanies this paper. To illustrate, we implemented a nation population-based ITS study from January 2001 to May 2021 covering the all-cause mortality of Israel (n = 9,350 thousand) to quantify the effect size of Covid-19 exposure on mortality rates. In the period unexposed to the Covid-19 pandemic, the mortality rate decreased over time and was expected to continue decreasing had Covid-19 not occurred. In contrast, the period exposed to the Covid-19 pandemic was associated with an increased all-cause mortality rate (relative risk = 1.11, 95% CI = 1.04, 1.18, P < 0.001).

Conclusion

For the first time, the effect size in ITS: was quantified, can be estimated by end-users with an R package we developed, and was demonstrated with data showing an increase in mortality following the Covid-19 pandemic. ITS effect size reporting can assist public health policy makers in assessing the magnitude of the entire intervention effect using a single, readily understood measure.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12982-022-00118-7.

Opioid Exposure and the Risk of Dementia: A National Cohort Study

OBJECTIVES

To examine the association between prescription opioid use and the risk of dementia in old-age, since existing studies of the association are few, and the evidence is inconsistent.

DESIGN

Prospective national cohort study (N = 91,307, aged 60 years and over), without a dementia diagnosis for ten years, followed-up for incident dementia from January 2013 to October 2017.

MEASUREMENTS

Opioid exposure was based on opioid purchases classified from Anatomical Therapeutic Chemical Classification system codes (N02A), and classified as exposed if the purchase period covered at least 60 days within a 120-day interval; otherwise, unexposed.

SETTING

Healthcare maintenance organization in Israel.

RESULTS

During follow-up, 2,849 (3.1%) persons were opioid exposed (mean age 73.94 ± 6.71 years), and 5,298 (5.8 %) persons developed dementia (mean age 78.07 ± 6.54 years). Cox regression models were fitted to quantify the risk of incident dementia with Hazard Ratios (HR) and their associated 95% Confidence Intervals (CI). The opioid exposed group aged 75+ to 80 years were at an increased risk of incident dementia (Adjusted HR = 1.39, 95% CI = 1.01, 1.92, Z-statistic = 2.02, p <0.05) compared to the unexposed. The point-precision estimates were generally similar to the primary analysis across fourteen sensitivity analyses.

CONCLUSION

Policymakers, caregivers, patients, and clinicians may wish to consider that opioid exposure aged 75-80 is linked with an increased dementia risk to balance the potential benefits and adverse side effects of opioid use in old age.

Serum folate deficiency and the risks of dementia and all-cause mortality: a national study of old age

BACKGROUND

The association between serum folate deficiency and the risk of dementia in old age is unclear, perhaps owing to small sample sizes, the competing risk of mortality or reverse causation.

OBJECTIVE

To examine the associations between serum folate deficiency and the risks of incident dementia and all-cause mortality in a large national sample of older adults.

METHODS

A prospective cohort aged 60-75 years (n=27 188) without pre-existing dementia for at least 10 years, was tested for serum concentrations of folate and followed up for dementia or all-cause mortality. Serum folate deficiency was classified as present (<4.4 ng/mL), otherwise absent. HRs and 95% CIs from competing risks Cox models were fitted to quantify the associations between serum folate deficiency and the risks of dementia and all-cause mortality. To examine reverse causation, the analysis was stratified by duration of follow-up.

FINDINGS

The presence compared with the absence of serum folate deficiency was associated with higher risks of dementia (HR=1.68; 95% CI 1.32 to 2.13; p<0.001) and all-cause mortality (HR=2.98; 95% CI 2.52 to 3.52; p<0.001). Evidence for reverse causation were moderate for dementia and mild for all-cause mortality.

CONCLUSIONS

Serum concentrations of folate may function as a biomarker used to identify those at risk of dementia and mortality; however, reverse causation is likely. Further research is needed to examine the role of serum folate deficiency in dementia aetiology.

CLINICAL IMPLICATIONS

Serum folate deficiency in older adults requires monitoring and treatment for preventative measures and/or as part of implemented therapeutic strategies.

The number needed to treat adjusted for explanatory variables in regression and survival analysis: Theory and application

The number needed to treat (NNT) is an efficacy index commonly used in randomized clinical trials. The NNT is the average number of treated patients for each undesirable patient outcome, for example, death, prevented by the treatment. We introduce a systematic theoretically-based framework to model and estimate the conditional and the harmonic mean NNT in the presence of explanatory variables, in various models with dichotomous and nondichotomous outcomes. The conditional NNT is illustrated in a series of four primary examples; logistic regression, linear regression, Kaplan-Meier estimation, and Cox regression models. Also, we establish and prove mathematically the exact relationship between the conditional and the harmonic mean NNT in the presence of explanatory variables. We introduce four different methods to calculate asymptotically-correct confidence intervals for both indices. Finally, we implemented a simulation study to provide numerical demonstrations of the aforementioned theoretical results and the four examples. Numerical analysis showed that the parametric estimators of the NNT with nonparametric bootstrap-based confidence intervals outperformed other examined combinations in most settings. An R package and a web application have been developed and made available online to calculate the conditional and the harmonic mean NNTs with their corresponding confidence intervals.

Early- and subsequent- response of cognitive functioning in Alzheimer's disease: Individual-participant data from five pivotal randomized clinical trials of donepezil

The association between early improvement and subsequent change in cognition is unexamined in antidementia clinical trials. We aimed to examine the consequences of early-response to antidementia medication in Alzheimer's disease. Participant-level data were analyzed from five pivotal clinical trials of donepezil for Alzheimer's disease lasting up to 24 weeks (N = 1917). Early-response was based on Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog) change scores under minus four from baseline to week six, otherwise classified non-response; then subgrouped by donepezil or placebo. The primary analysis tested the group differences in ADAS-Cog change from baseline for the interval after week six up to 24, based on a three-level mixed-effects model repeated measures (MMRM) model. Four models of increasing complexity were tested, and the most parsimonious model was examined in the primary analysis. The remaining models were tested in sensitivity analysis. In the analytic sample, 32.09% (N = 396/1234) of donepezil and 24.01% (N = 164/683) of placebo participants were classified as early responders, and 67.91% donepezil (N = 838/1234), 75.99% (N = 519/683) placebo participants were not. MMRM identified a statistically significant (P < 0.05) responder group effect. Marginal means (MM) demonstrated more improvement for the early responders (donepezil: MM = -4.13, 95% CI = -5.93, -2.32; placebo MM = 1.81, 95% CI = -4.12, 0.50), compared to non-early responders (donepezil MM = 0.05, 95% CI = -1.40, 1.51; placebo MM = 2.59, 95% CI = 0.99, 4.19). Results replicated in sensitivity analysis. Our results inform clinicians regarding the extent and consequences of early improvement in cognitive functioning and potentially contribute to treatment monitoring and the design of clinical trials for Alzheimer's disease.

Cognitive impairment networks in Alzheimer's disease: Analysis of three double-blind randomized, placebo-controlled, clinical trials of donepezil

Psychometric network analysis is an alternative theoretically-driven analytic approach that has the potential to conceptualize cognitive impairment in Alzheimer's disease differently than was previously assumed and consequently detect unknown treatment effects. Based on individual participant data, extracted from three double-blind, randomized placebo-controlled clinical trials, psychometric networks were computed on observed Alzheimer's Disease Assessment Scale Cognitive Subscale scores at baseline (N=1,554) and on predicted change scores at 24 weeks of follow-up for participants who received donepezil (N=797) or placebo (N=484). A novel conceptualization of cognitive impairment in Alzheimer's disease was displayed through the baseline network, that had 90% (n=27) positive statistically significant (p<0.05) associations, and a most central aspect of ideational praxis. Following 24 weeks, treatment effects emerged via the differences between the change score networks. The donepezil network had more statistically significant (p<0.05) positive associations and a higher global strength (n=15; S=1.22; p=0.03), than the placebo network (n=8; S=0.57). This suggests that for those who were treated with donepezil compared with placebo, cognition is a more unified construct. The main aspects of change in cognitive impairment were comprehension of spoken language for the donepezil network and spoken language ability for the placebo network. Comprehension of spoken language apears to be most sensitive to psychopharmaceutical interventions and should therefore be closely monitored. Overall, our psychometric network analysis presents a new conceptualization of cognitive impairment in Alzheimer's disease, points to previously unknown treatment effects and highlights well-defined aspects of cognitive impairment  that may translate into future treatment targets.

Gender differences in quality of life and the course of schizophrenia: national study

BACKGROUND

Evidence from various sources suggests that females with schizophrenia tend to report lower quality of life than males with schizophrenia despite having a less severe course of the disorder. However, studies have not examined this directly.

AIMS

To examine gender differences in the association between quality of life and the risk of subsequent psychiatric hospital admissions in a national sample with schizophrenia.

METHOD

The sample consisted of 989 (60.90%) males and 635 (39.10%) females with an ICD-10 diagnosis of schizophrenia. Quality of life was assessed and scored using the Manchester Short Assessment of Quality of Life. The course of schizophrenia was assessed from the number of psychiatric hospital admissions. Participants completed the quality of life assessment and were then followed up for 18-months for subsequent psychiatric admissions. Hazard ratios (HR) from Cox proportional hazards regression models were estimated unadjusted and adjusted for covariates (age at schizophrenia onset and birth year). Analyses were computed for males and females separately, as well as for the entire cohort.

RESULTS

A subsample of 93 males and 55 females was admitted to a psychiatric hospital during follow-up. Higher quality of life scores were significantly (P < 0.05) associated with a reduced risk of subsequent admissions among males (unadjusted: HR = 0.96, 95% CI 0.93-0.99; adjusted HR = 0.96, 95% CI 0.93-0.99) but not among females (unadjusted: HR = 0.97, 95% CI 0.93-1.02; adjusted HR = 0.97, 95% CI 0.93-1.02).

CONCLUSIONS

Quality of life in schizophrenia is a gender-specific construct and should be considered as such in clinical practice and future research.

Biopsychosocial Exposure to the Covid-19 Pandemic and the Relative Risk of Schizophrenia: Interrupted Time-Series Analysis of a Nationally Representative Sample

Background

Studies of COVID-19 pandemic biopsychosocial exposure and schizophrenia risk showed contradictory results, were undertaken early in the pandemic, and did not consider lockdowns or COVID-19 infection. Hence, we examined the association between COVID-19 biopsychosocial exposure and incident schizophrenia.

Methods

An interrupted time-series study design was implemented based on Israeli electronic health records from 2013 to 2021 with national coverage. The period coinciding with the COVID-19 pandemic biopsychosocial exposures from March 2020 to February 2021 was classified as exposed, otherwise unexposed. The effect of the COVID-19 pandemic on incident schizophrenia was quantified by fitting a Poisson regression and modeling the relative risk (RR) and corresponding 95% confidence intervals (CI). Three scenarios were projected from the third lockdown to 10 months to forecast incident schizophrenia rates and their associated 95% prediction intervals (PI).

Results

The total population (N = 736,356) yielded 4,310 cases of incident schizophrenia over time. The primary analysis showed that the period exposed to the COVID-19 pandemic was associated with a reduced RR (RR = 0.81, 95% CI = 0.73, 0.91, p < 0.001). This conclusion was supported in 12 sensitivity analyses, including scrutinizing lockdowns and COVID-19 infection status. Two of three forecast scenarios projected an incident increase (6.74, 95% PI = 5.80, 7.84; 7.40, 95% PI = 6.36, 8.60).

Conclusions

The reduced risk of schizophrenia during the pandemic suggests no immediate triggering of new onsets either by the virus or the pandemic-induced psychosocial adversities. Once restrictions are lifted, the increased projected presentations have implications for clinicians and healthcare policy.

Capturing adolescents in need of psychiatric care with psychopathological symptoms: A population-based cohort study

BACKGROUND

The current study aims to overcome past methodological limitations and capture adolescents in need of psychiatric care with psychopathological symptoms in a cohort with unrestricted access to mental health professionals.

METHODS

The study source population consisted of a random sample of adolescents aged 16-17 years (N=1,369) assessed by the Israeli Draft Board. An adapted version of the Brief Symptom Inventory was used to identify clinically relevant psychopathological symptoms with scores categorized as severe if they were in the top 10th percentile of symptoms, otherwise not severe. An independent interview with a subsequent referral to a mental health professional was used to categorize adolescents in need of psychiatric care. To examine the association between severe psychopathological symptoms and the need for psychiatric care, logistic regression models were fitted unadjusted and adjusted for age, sex, and intellectual assessment scores. Adjusted classification measures were estimated to examine the utility of severe psychopathological symptoms for clinical prediction of need for psychiatric care.

RESULTS

Information on 1,283 adolescents was available in the final analytic sample. Logistic regression modeling showed a statistically significant (p<0.001) association between self-reported severe psychopathological symptoms and the need for psychiatric care (OR adjusted: 4.38; 95% CI: 3.55-5.40). Severe psychopathological symptoms had a classification accuracy of 83% (CI: 81%-85%).

CONCLUSIONS

Severe psychopathological symptoms, although accounting for a fair proportion of treatment seeking, would perhaps be better useful for classification purposes alongside other variables rather than in isolation.

Guidelines to understand and compute the number needed to treat

OBJECTIVE

We aim to explain the unadjusted, adjusted and marginal number needed to treat (NNT) and provide software for clinicians to compute them.

METHODS

The NNT is an efficacy index that is commonly used in randomised clinical trials. The NNT is the average number of patients needed to treat to obtain one successful outcome (ie, response) due to treatment. We developed the nntcalc R package for desktop use and extended it to a user-friendly web application. We provided users with a user-friendly step-by-step guide. The application calculates the NNT for various models with and without explanatory variables. The implemented models for the adjusted NNT are linear regression and analysis of variance (ANOVA), logistic regression, Kaplan-Meier and Cox regression. If no explanatory variables are available, one can compute the unadjusted Laupacis et al's NNT, Kraemer and Kupfer's NNT and the Furukawa and Leucht's NNT. All NNT estimators are computed with their associated appropriate 95% confidence intervals. All calculations are in R and are replicable.

RESULTS

The application provides the user with an easy-to-use web application to compute the NNT in different settings and models. We illustrate the use of the application from examples in schizophrenia research based on the Positive and Negative Syndrome Scale. The application is available from https://nntcalc.iem.technion.ac.il. The output is given in a journal compatible text format, which users can copy and paste or download in a comma-separated values format.

CONCLUSION

This application will help researchers and clinicians assess the efficacy of treatment and consequently improve the quality and accuracy of decisions.

Optimal interpregnancy interval in autism spectrum disorder: A multi-national study of a modifiable risk factor

It is biologically plausible that risk of autism spectrum disorder (ASD) is elevated by both short and long interpregnancy intervals (IPI). We conducted a retrospective cohort study of singleton, non-nulliparous live births, 1998-2007 in Denmark, Finland, and Sweden (N = 925,523 births). Optimal IPI was defined as the IPI at which minimum risk was observed. Generalized additive models were used to estimate relative risks (RR) of ASD and 95% Confidence Intervals (CI). Population impact fractions (PIF) for ASD were estimated under scenarios for shifts in the IPI distribution. We observed that the association between ASD (N = 9302) and IPI was U-shaped for all countries. ASD risk was lowest (optimal IPI) at 35 months for all countries combined, and at 30, 33, and 39 months in Denmark, Finland, and Sweden, respectively. Fully adjusted RRs at IPIs of 6, 12, and 60 months were 1.41 (95% CI: 1.08, 1.85), 1.26 (95% CI: 1.02, 1.56), and 1.24 (95% CI: 0.98, 1.58) compared to an IPI of 35 months. Under the most conservative scenario PIFs ranged from 5% (95% CI: 1%-8%) in Denmark to 9% (95% CI: 6%-12%) in Sweden. The minimum ASD risk followed IPIs of 30-39 months across three countries. These results reflect both direct IPI effects and other, closely related social and biological pathways. If our results reflect biologically causal effects, increasing optimal IPIs and reducing their indications, such as unintended pregnancy and delayed age at first pregnancy has the potential to prevent a salient proportion of ASD cases. LAY SUMMARY: Waiting 35 months to conceive again after giving birth resulted in the least risk of autism. Shorter and longer intervals resulted in risks that were up to 50% and 85% higher, respectively. About 5% to 9% of autism cases might be avoided by optimizing birth spacing.

Linking the Clinical Dementia Rating Scale-Sum of Boxes, the Clinician's Interview-Based Impression Plus Caregiver Input, and the Clinical Global Impression Scale: Evidence based on Individual Participant Data from Five Randomized Clinical Trials of Donepezil

BACKGROUND

In patients with Alzheimer's disease, global assessment scales, such as the Clinical Dementia Rating-Sum of Boxes (CDR-SB), the Clinician's Interview-Based Impression Plus Caregiver Input (CIBI plus), and the Clinical Global Impression (CGI) are commonly used.

OBJECTIVE

To clinically understand and interpret the associations between these scales, we examined the linkages for the total and change scores of CDR-SB, CIBI plus, and CGI.

METHODS

Individual participant data (N = 2,198) from five pivotal randomized placebo-controlled trials of donepezil were included. Data were collected at baseline and scheduled visits for up to 6 months. Spearman's correlation coefficients ρ were examined between corresponding total and change scores of simultaneous CDR-SB, CIBI plus, and CGI ratings. To link between the simultaneous ratings, equipercentile linking was used.

RESULTS

We found strong evidence that the Spearman's correlation coefficients between the CDR-SB and CGI, and CDR-SB and CIBI plus total scores were at least adequately correlated (ρ= 0.50 to 0.71, with p < 0.01). The correlation coefficients between the change scores of CDR-SB and CGI were deemed adequate for weeks 6 to 24 (ρ= 0.44 to 0.65); the remaining correlations were smaller in magnitude (ρ= 0.09 to 0.35). Overall, the linkages were in-line with expectations, e.g., CDR-SB range score of 3-4 (= very mild dementia) was linked to a CGI score of 3 (= mildly ill), and an increase of CDR-SB of 1 was linked to a change of 5 (= minimal worsening) in both CGI and CIBI plus.

CONCLUSION

The study findings can be useful for clinicians wishing to compare scores of different scales across patients. They can also help researchers understand results of studies using different scales and can facilitate meta-analyses, to increase statistical power.

Ethnic group and social support contribution to posttraumatic growth after sudden spousal loss among Jewish, Muslim, and Druze widows in Israel

This study aimed to examine the contribution of ethnic group status and social support to posttraumatic growth (PTG) among widows after sudden spousal loss. Participants included 184 widows from three ethnic groups: 59 (32.3%) Jewish, 58 (31.7%) Muslim, and 66 (36%) Druze. Information was gathered via a demographic questionnaire, PTG Inventory, and Multidimensional Scale of Perceived Social Support. Analysis of covariance was used to test ethnic group status differences in social support, controlling for demographic variables. Hierarchical linear models were used to assess groups differences in the study outcome variables. The results showed that the PTG total score was higher for Jewish widows than for Muslim and Druze widows, with a null difference between the latter two, and social support contributed to increased PTG among Jewish widows more than among Muslim and Druze widows, with no significant association between social support and PTG among Druze widows. The highest PTG levels were observed among widows from modern individualistic cultural backgrounds, compared with traditional collectivist, cultural backgrounds after sudden spousal death. The social support system may be a pathway to enhance PTG among widows in traditional collectivist societies.

Linking the Mini-Mental State Examination, the Alzheimer's Disease Assessment Scale-Cognitive Subscale and the Severe Impairment Battery: evidence from individual participant data from five randomised clinical trials of donepezil

BACKGROUND

The Mini-Mental State Examination (MMSE), the Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog) and the Severe Impairment Battery (SIB) are widely used rating scales to assess cognition in Alzheimer's disease.

OBJECTIVE

To understand the correspondence between these rating scales, we aimed to examine the linkage of MMSE with the ADAS-Cog and SIB total and change scores.

METHODS

We used individual-level data on participants with Alzheimer's disease (n=2925) from five pivotal clinical trials of donepezil. Data were collected at baseline and scheduled visits for up to 6 months. We used equipercentile linking to identify the correspondence between simultaneous measurements of MMSE with ADAS-Cog, and SIB total and change ratings.

FINDINGS

Spearman's correlation coefficients were of strong magnitude between the MMSE total score and the ADAS-Cog (rs from -0.82 to -0.87; p<0.05) and SIB total scores (rs from 0.70 to 0.75; p<0.05). Weaker correlations between the change scores were observed between the MMSE change score and the ADAS-Cog (week 1: r=-0.11, p=0.18; rs thereafter: -0.28 to -0.45; p<0.05) and SIB change scores (rs from 0.31 to 0.44; p<0.05). Linking suggested that the MMSE total scores were sensitive to moderate and severe cognitive impairment levels. Despite weak to moderate correlations for the change scores, moderate change levels linked well, indicating ceiling and floor effects.

CONCLUSIONS

The current results can be used in meta-analyses, data harmonisation and may contribute to increasing statistical power when pooling data from multiple sources.

CLINICAL IMPLICATIONS

The current study results help clinicians to understand these cognitive rating scale scores.

Maternal health around pregnancy and autism risk: a diagnosis-wide, population-based study

BACKGROUND

Many studies have reported an increased risk of autism spectrum disorder (ASD) associated with some maternal diagnoses in pregnancy. However, such associations have not been studied systematically, accounting for comorbidity between maternal disorders. Therefore our aim was to comprehensively test the associations between maternal diagnoses around pregnancy and ASD risk in offspring.

METHODS

This exploratory case-cohort study included children born in Israel from 1997 to 2008, and followed up until 2015. We used information on all ICD-9 codes received by their mothers during pregnancy and the preceding year. ASD risk associated with each of those conditions was calculated using Cox proportional hazards regression, adjusted for the confounders (birth year, maternal age, socioeconomic status and number of ICD-9 diagnoses during the exposure period).

RESULTS

The analytic sample consisted of 80 187 individuals (1132 cases, 79 055 controls), with 822 unique ICD-9 codes recorded in their mothers. After extensive quality control, 22 maternal diagnoses were nominally significantly associated with offspring ASD, with 16 of those surviving subsequent filtering steps (permutation testing, multiple testing correction, multiple regression). Among those, we recorded an increased risk of ASD associated with metabolic [e.g. hypertension; HR = 2.74 (1.92-3.90), p = 2.43 × 10-8], genitourinary [e.g. non-inflammatory disorders of cervix; HR = 1.88 (1.38-2.57), p = 7.06 × 10-5] and psychiatric [depressive disorder; HR = 2.11 (1.32-3.35), p = 1.70 × 10-3] diagnoses. Meanwhile, mothers of children with ASD were less likely to attend prenatal care appointment [HR = 0.62 (0.54-0.71), p = 1.80 × 10-11].

CONCLUSIONS

Sixteen maternal diagnoses were associated with ASD in the offspring, after rigorous filtering of potential false-positive associations. Replication in other cohorts and further research to understand the mechanisms underlying the observed associations with ASD are warranted.

How can we estimate QALYs based on PHQ-9 scores? Equipercentile linking analysis of PHQ-9 and EQ-5D

BACKGROUND

Quality-adjusted life years (QALYs) are widely used to measure the impact of various diseases on both the quality and quantity of life and in their economic valuations. It will be clinically important and informative if we can estimate QALYs based on measurements of depression severity.

OBJECTIVE

To construct a conversion table from the Patient Health Questionnaire-9 (PHQ-9), the most frequently used depression scale in recent years, to the Euro-Qol Five Dimensions Three Levels (EQ-5D-3L), one of the most commonly used instruments to assess QALYs.

METHODS

We obtained individual participant data of randomised controlled trials of internet cognitive-behavioural therapy which had administered depression severity scales and the EQ-5D-3L at baseline and at end of treatment. Scores from depression scales were all converted into the PHQ-9 according to the validated algorithms. We used equipercentile linking to establish correspondences between the PHQ-9 and the EQ-5D-3L.

FINDINGS

Individual-level data from five trials (total N=2457) were available. Subthreshold depression (PHQ-9 scores between 5 and 10) corresponded with EQ-5D-3L index values of 0.9-0.8, mild major depression (10-15) with 0.8-0.7, moderate depression (15-20) with 0.7-0.5 and severe depression (20 or higher) with 0.6-0.0. A five-point improvement in PHQ-9 corresponded approximately with an increase in EQ-5D-3L score by 0.03 and a ten-point improvement by approximately 0.25.

CONCLUSIONS AND CLINICAL IMPLICATIONS

The conversion table between the PHQ-9 and the EQ-5D-3L scores will enable fine-grained assessment of burden of depression at its various levels of severity and of impacts of its various treatments.

Quantifying the heterogeneity of cognitive functioning in Alzheimer's disease to extend the placebo-treatment dichotomy: Latent class analysis of individual-participant data from five pivotal randomized clinical trials of donepezil

BACKGROUND

The extent and profiles of heterogeneity in cognitive functioning among participants in clinical trials of antidementia medication are unknown. We aimed to quantify and identify profiles of heterogeneity of cognition in Alzheimer's disease.

METHODS

Individual-level participant data were analyzed from five pivotal clinical trials of donepezil for Alzheimer's disease (N = 2,919). Based on Alzheimer's Disease Assessment Scale-Cognitive Subscale total scores from baseline up to week 12, a latent class model was used to identify heterogeneous groups. A logistic regression model was used to examine factors associated with group membership. Sensitivity analysis was conducted, restricted to the donepezil, and then the placebo arm.

RESULTS

The latent class model identified three classes labeled as low scorers (i.e., least cognitive impairment; N = 1,666, 76.04%), improvers (N = 27, 1.23%), and high scorers (N = 498, 22.73%). Logistic modeling showed that donepezil compared to placebo was significantly (p < 0.05) positively associated with membership in the improvers class (OR = 6.88, 95% CI = 2.03, 42.95), and negatively with high scorers (OR = 0.79, 95% CI = 0.64, 0.98). Sensitivity analysis restricted to the placebo, then donepezil arms replicated similar heterogeneity patterns.

CONCLUSIONS

Our results inform clinicians regarding the extent of heterogeneity in cognitive functioning during treatment and contribute to trial design considerations.

Early predictors of mental health in mid-adulthood

AIM

Substantial research has focused on the examination of factors that contribute to the development of psychiatric problems. However, much less is known about factors early in life that may protect from poor mental health outcomes in midlife. This study aimed to identify the extent to which a set of key perinatal demographic variables and adolescent academic performance were associated with good mental health in mid-adulthood.

METHODS

In a sample of 525 individuals (aged 34-44, 55.4% male) born and raised in Jerusalem, Israel (STREAM study) we attempted to differentiate those who did and did not report psychiatric symptoms in mid-adulthood. Using χ² and regression analysis, we explored birth factors (year of birth, sex, birth weight, and number of older siblings, data on parental immigration and socioeconomic status), academic achievement in eighth grade and contemporaneous measures of lifestyle factors, personality traits, and perceived resilience.

RESULTS

Participants with good mental health were more often male (P = .005) and had better academic performance already at adolescence than participants who reported psychiatric symptoms in midlife (P < .001). They reported fewer physical complaints (P = .008), were less likely to smoke (P = .001) and considered themselves to be more "resilient" (P < .001).

CONCLUSIONS

The results showed that better academic performance in adolescence may be associated with better stress-coping strategies, resulting in fewer psychiatric complaints, more perceived resilience, and less stress-related behaviours in mid-adulthood. Future studies confirming this hypothesis could inform public mental health interventions.

Gray's model of personality and aggregate level factor analysis

Previous research shows that correlations tend to increase in magnitude when individuals are aggregated across groups. This suggests that uncorrelated constellations of personality variables (such as the primary scales of Extraversion and Neuroticism) may display much higher correlations in aggregate factor analysis. We hypothesize and report that individual level factor analysis can be explained in terms of Giant Three (or Big Five) descriptions of personality, whereas aggregate level factor analysis can be explained in terms of Gray's physiological based model. Although alternative interpretations exist, aggregate level factor analysis may correctly identify the basis of an individual's personality as a result of better reliability of measures due to aggregation. We discuss the implications of this form of analysis in terms of construct validity, personality theory, and its applicability in general. Copyright © 2003 John Wiley & Sons, Ltd.

How to Compare Psychometric Factor and Network Models

In memory of Dr. Dennis John McFarland, who passed away recently, our objective is to continue his efforts to compare psychometric networks and latent variable models statistically. We do so by providing a commentary on his latest work, which he encouraged us to write, shortly before his death. We first discuss the statistical procedure McFarland used, which involved structural equation modeling (SEM) in standard SEM software. Next, we evaluate the penta-factor model of intelligence. We conclude that (1) standard SEM software is not suitable for the comparison of psychometric networks with latent variable models, and (2) the penta-factor model of intelligence is only of limited value, as it is nonidentified. We conclude with a reanalysis of the Wechlser Adult Intelligence Scale data McFarland discussed and illustrate how network and latent variable models can be compared using the recently developed R package Psychonetrics. Of substantive theoretical interest, the results support a network interpretation of general intelligence. A novel empirical finding is that networks of intelligence replicate over standardization samples.

Identification of newborns at risk for autism using electronic medical records and machine learning

BACKGROUND

Current approaches for early identification of individuals at high risk for autism spectrum disorder (ASD) in the general population are limited, and most ASD patients are not identified until after the age of 4. This is despite substantial evidence suggesting that early diagnosis and intervention improves developmental course and outcome. The aim of the current study was to test the ability of machine learning (ML) models applied to electronic medical records (EMRs) to predict ASD early in life, in a general population sample.

METHODS

We used EMR data from a single Israeli Health Maintenance Organization, including EMR information for parents of 1,397 ASD children (ICD-9/10) and 94,741 non-ASD children born between January 1st, 1997 and December 31st, 2008. Routinely available parental sociodemographic information, parental medical histories, and prescribed medications data were used to generate features to train various ML algorithms, including multivariate logistic regression, artificial neural networks, and random forest. Prediction performance was evaluated with 10-fold cross-validation by computing the area under the receiver operating characteristic curve (AUC; C-statistic), sensitivity, specificity, accuracy, false positive rate, and precision (positive predictive value [PPV]).

RESULTS

All ML models tested had similar performance. The average performance across all models had C-statistic of 0.709, sensitivity of 29.93%, specificity of 98.18%, accuracy of 95.62%, false positive rate of 1.81%, and PPV of 43.35% for predicting ASD in this dataset.

CONCLUSIONS

We conclude that ML algorithms combined with EMR capture early life ASD risk as well as reveal previously unknown features to be associated with ASD-risk. Such approaches may be able to enhance the ability for accurate and efficient early detection of ASD in large populations of children.

Systematic analysis of the number needed to treat

The number needed to treat is often used to measure the efficacy of a binary outcome in randomized clinical trials. There are three different available measures of the number needed to treat. Two of these measures, Furukawa and Leucht’s and Kraemer and Kupfer’s, focus on converting Cohen’s δ index into the number needed to treat, while Laupacis et al.’s measure deals primarily with the number needed to treat’s estimation rather than with a reformulation. Mathematical and numerical analysis of numbers needed to treat and their estimators was conducted. Three novel number needed to treat estimators were introduced to supplement the numbers needed to treat introduced by Laupacis, Furukawa and Leucht, and Kraemer and Kupfer. The analysis showed that Laupacis et al.’s number needed to treat is intrinsically different from Kraemer and Kupfer’s number needed to treat, and that Furukawa and Leucht’s estimator is appropriate to use only for normally distributed outcomes with equal standard deviations. Based on the numerical analysis, the novel numbers needed to treat outperformed the existing ones under correct model specifications. Asymptotic analysis was used to test three different types of confidence intervals to supplement the numbers needed to treat. An R-package to calculate these numbers needed to treat and their confidence intervals has been developed and made available for users online.

Association of Genetic and Environmental Factors With Autism in a 5-Country Cohort

IMPORTANCE

The origins and development of autism spectrum disorder (ASD) remain unresolved. No individual-level study has provided estimates of additive genetic, maternal, and environmental effects in ASD across several countries.

OBJECTIVE

To estimate the additive genetic, maternal, and environmental effects in ASD.

DESIGN, SETTING, AND PARTICIPANTS

Population-based, multinational cohort study including full birth cohorts of children from Denmark, Finland, Sweden, Israel, and Western Australia born between January 1, 1998, and December 31, 2011, and followed up to age 16 years. Data were analyzed from September 23, 2016 through February 4, 2018.

MAIN OUTCOMES AND MEASURES

Across 5 countries, models were fitted to estimate variance components describing the total variance in risk for ASD occurrence owing to additive genetics, maternal, and shared and nonshared environmental effects.

RESULTS

The analytic sample included 2 001 631 individuals, of whom 1 027 546 (51.3%) were male. Among the entire sample, 22 156 were diagnosed with ASD. The median (95% CI) ASD heritability was 80.8% (73.2%-85.5%) for country-specific point estimates, ranging from 50.9% (25.1%-75.6%) (Finland) to 86.8% (69.8%-100.0%) (Israel). For the Nordic countries combined, heritability estimates ranged from 81.2% (73.9%-85.3%) to 82.7% (79.1%-86.0%). Maternal effect was estimated to range from 0.4% to 1.6%. Estimates of genetic, maternal, and environmental effects for autistic disorder were similar with ASD.

CONCLUSIONS AND RELEVANCE

Based on population data from 5 countries, the heritability of ASD was estimated to be approximately 80%, indicating that the variation in ASD occurrence in the population is mostly owing to inherited genetic influences, with no support for contribution from maternal effects. The results suggest possible modest differences in the sources of ASD risk between countries.

Recurrence Risk of Autism in Siblings and Cousins: A Multinational, Population-Based Study

OBJECTIVE

Familial recurrence risk is an important population-level measure of the combined genetic and shared familial liability of autism spectrum disorder (ASD). Objectives were to estimate ASD recurrence risk among siblings and cousins by varying degree of relatedness and by sex.

METHOD

This is a population-based cohort study of livebirths from 1998 to 2007 in California, Denmark, Finland, Israel, Sweden and Western Australia followed through 2011 to 2015. Subjects were monitored for an ASD diagnosis in their older siblings or cousins (exposure) and for their ASD diagnosis (outcome). The relative recurrence risk was estimated for different sibling and cousin pairs, for each site separately and combined, and by sex.

RESULTS

During follow-up, 29,998 cases of ASD were observed among the 2,551,918 births used to estimate recurrence in ASD and 33,769 cases of childhood autism (CA) were observed among the 6,110,942 births used to estimate CA recurrence. Compared with the risk in unaffected families, there was an 8.4-fold increase in the risk of ASD following an older sibling with ASD and a 17.4-fold increase in the risk of CA following an older sibling with CA. A 2-fold increase in the risk for cousin recurrence was observed for the 2 disorders. There also was a significant difference in sibling ASD recurrence risk by sex.

CONCLUSION

The present estimates of relative recurrence risks for ASD and CA will assist clinicians and families in understanding autism risk in the context of other families in their population. The observed variation by sex underlines the need to deepen the understanding of factors influencing ASD familial risk.

Exposure to Genocide and the Risk of Dementia

Competing hypotheses stating that past genocide exposure reduces (owing to resilience) versus increases (owing to vulnerabilities) the risk of dementia are yet to receive empirical support. This study tested these competing hypotheses. Registry data were extracted on 51,752 Israeli residents without dementia from September 2002 to January 2012; individuals were born between 1901 and 1945, alive on January 2012, and followed-up for the risk of dementia between January 2013 and October 2017. Groups were classified as exposed to the European Holocaust, based on government recognition, or unexposed. Hazard ratios (HRs) from Cox regression models were used to quantify the risk of dementia between the groups, adjusting for demographic and diagnostic covariates; additionally, 12 sensitivity analyses were computed. In total 10,780 participants (20.8%) were exposed to the Holocaust and 5,584 (10.8%) were diagnosed with dementia during follow-up. Dementia rates were 16.5% in the Holocaust-exposed group and 9.3% in the unexposed group. In the primary analysis, the estimated unadjusted HR of dementia for the exposed compared to the unexposed group was 1.77, 95% CI [1.67, 1.87], and the adjusted HR was 1.21, 95% CI [1.15, 1.28]. Sensitivity analyses significantly replicated the primary results with similar point estimates, adjusted HRs = 1.18-1.28, all ps < .001; all HRs had a small effect size. The current study results are consistent with the hypothesis that exposure to the extreme adversities of genocide heightens vulnerability to the risk of dementia in later life.

The role of substance use and adult sexual assault severity in the course of schizophrenia: An epidemiological catchment study of sexual assault victims

BACKGROUND

Childhood trauma increases the risk of schizophrenia, yet the role of adult sexual assault in the course of schizophrenia is unknown. This study aims to examine the associations between substance use and sexual assault severity characteristics with the course of schizophrenia among adult sexual assault victims using an epidemiologic study design.

METHODS

Sexual assault data on all individuals received from 2000 to 2010 (N = 2147) at the Center for Care of Sexual Assault Victims at Wolfson Medical Center, the largest medical center for sexual assault victims in the country, were merged with the Israel National Psychiatric Case Registry, that consisted of lifetime psychiatric hospitalizations of schizophrenia (birth to 6 years post-assault). The associations between substance use and adult sexual assault severity characteristics with hospitalizations were quantified using recurrent events Cox modeling.

RESULTS

Schizophrenia with sexual assault survivors occurred in 117 persons. Cox modeling showed that recurrent psychiatric hospitalizations were associated with younger age, sexual assault at older age, previous diagnosis of psychosis, and drug use shortly before or during the assault. Other assault characteristics (number of assailants, means of subdual, penetration type, perpetrator violence, physical injury of the victim) and immediacy of seeking help had a null association with the course of psychiatric hospitalization. These results replicated in two sensitivity analyses.

CONCLUSIONS

Substance use among victims of sexual assault was associated with an exacerbated course of schizophrenia, pointing to a possibly modifiable risk factor that should be targeted in prevention, assessment, treatment formulation and implementation.

Efficient two-step multivariate random effects meta-analysis of individual participant data for longitudinal clinical trials using mixed effects models

BACKGROUND

Mixed effects models have been widely applied in clinical trials that involve longitudinal repeated measurements, which possibly contain missing outcome data. In meta-analysis of individual participant data (IPD) based on these longitudinal studies, joint synthesis of the regression coefficient parameters can improve efficiency, especially for explorations of effect modifiers that are useful to predict the response or lack of response to particular treatments.

METHODS

In this article, we provide a valid and efficient two-step method for IPD meta-analyses using the mixed effects models that adequately addresses the between-studies heterogeneity using random effects models. The two-step method overcomes the practical difficulties of computations and modellings of the heterogeneity in the one-step method, and enables valid inference without loss of efficiency. We also show the two-step method can effectively circumvent the modellings of the between-studies heterogeneity of the variance-covariance parameters and provide valid and efficient estimators for the regression coefficient parameters, which are the primary objects of interests in the longitudinal studies. In addition, these methods can be easily implemented using standard statistical packages, and enable synthesis of IPD from different sources (e.g., from different platforms of clinical trial data sharing systems).

RESULTS

To assess the proposed method, we conducted simulation studies and also applied the method to an IPD meta-analysis of clinical trials for new generation antidepressants. Through the numerical studies, the validity and efficiency of the proposed method were demonstrated.

CONCLUSIONS

The two-step approach is an effective method for IPD meta-analyses of longitudinal clinical trials using mixed effects models. It can also effectively circumvent the modellings of the between-studies heterogeneity of the variance-covariance parameters, and enable efficient inferences for the regression coefficient parameters.

Association of Autism Spectrum Disorder With Prenatal Exposure to Medication Affecting Neurotransmitter Systems

IMPORTANCE

Prenatal exposure to certain medications has been hypothesized to influence the risk of autism spectrum disorders (ASD). However, the underlying effects on the neurotransmitter systems have not been comprehensively assessed.

OBJECTIVE

To investigate the association of early-life interference with different neurotransmitter systems by prenatal medication exposure on the risk of ASD in offspring.

DESIGN, SETTING, AND PARTICIPANTS

This case-control study included children born from January 1, 1997, through December 31, 2007, and followed up for ASD until January 26, 2015, within a single Israeli health maintenance organization. Using publicly available data, 55 groups of medications affecting neurotransmitter systems and prescribed to pregnant women in this sample were identified. Children prenatally exposed to medications were compared with nonexposed children. Data were analyzed from March 1, 2017, through June 20, 2018.

MAIN OUTCOME AND MEASURES

Hazard ratios (HRs) and 95% CIs of ASD risk associated with exposure to medication groups using Cox proportional hazards regression, adjusted for the relevant confounders (eg, birth year, maternal age, maternal history of psychiatric and neurologic disorders, or maternal number of all medical diagnoses 1 year before pregnancy).

RESULTS

The analytic sample consisted of 96 249 individuals (1405 cases; 94 844 controls; mean [SD] age at the end of follow-up, 11.6 [3.1] years; 48.8% female), including 1405 with ASD and 94 844 controls. Of 34 groups of medications, 5 showed nominally statistically significant association with ASD in fully adjusted models. Evidence of confounding effects of the number of maternal diagnoses on the association between offspring exposure to medication and ASD was found. Adjusting for this factor, lower estimates of ASD risk among children exposed to cannabinoid receptor agonists (HR, 0.72; 95% CI, 0.55-0.95; P = .02), muscarinic receptor 2 agonists (HR, 0.49; 95% CI, 0.24-0.98; P = .04), opioid receptor κ and ε agonists (HR, 0.67; 95% CI, 0.45-0.99; P = .045), or α2C-adrenergic receptor agonists (HR, 0.43; 95% CI, 0.19-0.96; P = .04) were observed. Exposure to antagonists of neuronal nicotinic acetylcholine receptor α was associated with higher estimates of ASD risk (HR, 12.94; 95% CI, 1.35-124.25; P = .03).

CONCLUSIONS AND RELEVANCE

Most of the medications affecting neurotransmitter systems in this sample had no association with the estimates of ASD risk. Replication and/or validation using experimental techniques are required.

Association of maternal exposure to terror attacks during pregnancy and the risk of schizophrenia in the offspring: A population-based study

This study tested the hypothesis that maternal exposure to terror attacks during pregnancy is associated with the risk of schizophrenia in the offspring. A population-based study was conducted of Israeli children born between 1975 and 1995 and that were registered in the Ministry of Interior and followed up in the Ministry of Health from birth to 2015 for the risk of schizophrenia (N = 201,048). The association between maternal exposure to terror attacks during pregnancy and the risk of schizophrenia in the offspring was quantified with relative risks (RR) and their 95% confidence intervals (CI) fitting Cox regression models unadjusted and adjusted for confounders. Sensitivity analyses were performed to test the robustness of the results. The RR of schizophrenia in offspring of mothers exposed to terror attacks during pregnancy compared to offspring of mothers not exposed during pregnancy were estimated unadjusted (RR = 2.51, 95% CI, 1.33, 4.74) and adjusted (RR = 2.53, 95% CI, 1.63, 3.91). In the sensitivity analyses adjusted RRs were estimated using a sibling-based study design (2.85, 95% CI: 1.31-6.21) and propensity matching (2.45, 95% CI: 1.58-3.81). Maternal exposure to terror attacks during pregnancy was associated with an increased risk of schizophrenia in the offspring, possibly indicating a critical period of neurodevelopment that is sensitive to the stress of terror attacks and affected by epigenetic modifications.

Infertility treatments during pregnancy and the risk of autism spectrum disorder in the offspring

We aimed to examine the effects of infertility treatments on the risk of Autism Spectrum Disorder (ASD). Data were from a representative national registry on 110,093 male live births in Israel (born: 1999-2008; and ASD: 975, 0.9%). Infertility treatments included In Vitro Fertilization (IVF), and five hormone treatments. Relative risk (RR) was estimated with multivariable logistic models. Results showed that IVF treatment compared with spontaneous conception was not statistically significantly associated with the risk of ASD. Only progesterone hormone treatment was associated with a statistically significant (p < .05) increased risk of ASD (RR = 1.51, 95% CI 1.22, 1.86) compared to the group with no progesterone treatment. In conclusion, progesterone exposure during the critical period of fetal life elevated the risk of ASD, possibly reflecting epigenetic modification.

Psychiatric symptoms and related dysfunction in a general population sample

Background

Along with the key clinical features of major psychiatric disorders such as psychosis, mania, and depression, these disorders are also associated with cognitive, social, and functional deficits. A growing body of evidence suggests that these disorders exist at the extreme end of a continuum of symptoms rather than as binary entities, so it is plausible that the associated cognitive, social, and functional deficits assume a similar pattern. Consistent with this approach, we sought to determine whether adults in the general population with psychiatric symptoms also demonstrate milder forms of the cognitive, social, and functional deficits that are often associated with the psychiatric disorders.

Methods

Using data from the Study of Resilience and Environmental Adversity in Midlife Health (STREAM), which includes survey responses of 811 individuals, we compared early academic achievement and self-reported social and functional outcomes between respondents who reported psychotic symptoms, manic symptoms, depressive symptoms, or no psychiatric symptoms (controls).

Results

Adults with psychotic symptoms had significantly poorer early academic performance (p = .04) and social and functional outcomes (self-reported marital status, p = .021, income, p = .001, and health, p < .001) than controls. Adults with depressive symptoms had significantly lower early academic performance and income and poorer health than controls (p's = 0.033, 0.037, 0.013 respectively), and adults with manic symptoms also reported significantly lower rates of marriage than controls (p = .006).

Conclusions

The results are consistent with the continuum view of the etiology of psychiatric disorders in which psychiatric disorders are dimensional and experienced in varying degrees of severity across the general and clinical population. Importantly, the results highlight the potential impact of psychiatric symptomatology on functional outcomes in the population.

Age of onset and quality of life among males and females with schizophrenia: A national study

Background:

Age of onset is considered central to understanding the course of schizophrenia, yet little is known regarding its association with quality of life in general, and specifically among males and females.

Aims:

To examine the association between the age of schizophrenia onset and quality of life, in general, and among males and females, using data from a national sample and competing statistical models.

Methods:

Participants with a diagnosis of schizophrenia (N = 1624) completed the Manchester Short Assessment of Quality of Life (MSA-QoL) and were rated on a parallel measure by their professional caregivers (N = 578). Multiple regression analysis models were computed for self-appraised quality of life, and mixed models with random intercepts were used for caregivers. Six competing models were tested for parsimony for each rating source. Three models without adjustment and three models adjusted for confounding variables. Sensitivity analyses were conducted for males and females separately.

Results:

Age of onset was statistically significantly (P <.05) negatively associated with self-appraised and caregiver-appraised quality of life on aggregate and among females. Among males, a significant (P <.01) quadratic effect of onset age on self-appraised quality of life demonstrated a negative association up to onset age of 36.67 years, after which the association was positive.

Conclusions

An earlier age of onset is associated with a better quality of life in schizophrenia which is tentatively explained by social decline. Specific trends in psychiatric symptom severity may account for this association among females while social advantages may account for the particular results found among males.

Paternal use of antidepressants and offspring outcomes in Sweden: nationwide prospective cohort study

OBJECTIVE

To examine the association between paternal antidepressant use at conception and offspring preterm birth, malformations, autism spectrum disorder, and intellectual disability.

DESIGN

Observational prospective cohort study with regression methods, and negative control comparison.

SETTING

Sweden nationwide.

PARTICIPANTS

170 508 children conceived from 29 July 2005 and born in 2006-07, followed up to 2014 at age 8-9 years. This cohort included 3983 children born to fathers receiving antidepressant treatment during the conception period (that is, from four weeks before conception to four weeks after), a control group of 164 492 children not exposed to paternal antidepressant use, and a negative control comparison group of 2033 children born to fathers who did not use antidepressants during the conception period but began antidepressant treatment later during the pregnancy period (that is, from four weeks after conception to childbirth).

MAIN OUTCOME MEASURE

Offspring preterm birth, malformation diagnosed at birth, diagnosis of autism spectrum disorder, and diagnosis of intellectual disability.

RESULTS

Paternal antidepressant use during conception was not associated with preterm birth (adjusted odds ratio 0.91 (95% confidence interval 0.79 to 1.04)) or malformations (1.06 (0.90 to 1.26)) using logistic regression, compared with offspring born to unexposed fathers. No association was seen between antidepressant use during conception and autism (adjusted hazard ratio 1.13 (0.84 to 1.53)) or intellectual disability (0.82 (0.51 to 1.31)) using Cox regression. In children whose fathers initiated antidepressant treatment during pregnancy, results were similar for all outcomes apart from intellectual disability, which had an increased adjusted hazard ratio (1.66 (1.06 to 2.59)). Compared with the 2033 children whose fathers initiated antidepressant treatment during pregnancy, the 3983 children exposed to paternal use of antidepressants at conception had no differences in preterm birth, malformation, and autism, but a reduced risk of intellectual disability (adjusted hazard ratio 0.49 (0.26 to 0.93)).

CONCLUSION

Paternal intake of antidepressants during the period around conception is safe with respect to the risk of the four major adverse outcomes in offspring-preterm birth, malformation, autism, or intellectual disability.