Estimating Additive Interaction in Two-Stage Individual Participant Data Meta-Analysis.

Individual participant data (IPD) meta-analysis provides important opportunities to study interaction and effect modification for which individual studies often lack power. While previous meta-analyses have commonly focused on multiplicative interaction, additive interaction holds greater relevance for public health and may in certain contexts better reflect biological interaction. Methodological literature on interaction in IPD meta-analysis does not cover additive interaction for models including binary or time-to-event outcomes. We aimed to describe how the Relative Excess Risk due to Interaction (RERI) and other measures of additive interaction or effect modification can be validly estimated within two-stage IPD meta-analysis. First, we explain why direct pooling of study-level RERI estimates may lead to invalid results. Next, we propose a three-step procedure to estimate additive interaction: 1) estimate effects of both exposures and their product term on the outcome within each individual study; 2) pool study-specific estimates using multivariate meta-analysis; 3) estimate an overall RERI and 95% confidence interval based on the pooled effect estimates. We illustrate this procedure by investigating interaction between depression and smoking and risk of smoking-related cancers using data from the PSYchosocial factors and Cancer (PSY-CA) consortium. We discuss implications of this procedure, including the application in meta-analysis based on published data.

CLUSTERS OF PARENTAL SOCIOECONOMIC STATUS IN EARLY CHILDHOOD AND INHERITED RISK FOR CEREBROVASCULAR DISEASE UNTIL MID-LIFE - NORTHERN FINLAND BIRTH COHORT 1966.

BACKGROUND AND AIMS: The incidence of cerebrovascular disease (CVD) is rising among young adults (<55 years). The risk for CVD starts to form in early childhood and is comprised of genetic and environmental risk factors. The aim of this study is to investigate the relationship between early family socioeconomic status (SES), inherited risk, and CVD until midlife. METHODS: In the Northern Finland Birth Cohort 1966 of 12,058 children, individuals were followed from gestational period up to 54 years. We used previously published early family SES clusters, based on latent class analysis of a wide set of prenatally collected variables. We investigated inherited risk with polygenic risk score (PRS) and parental CVDs during follow-up. The associations of the five distinct clusters, inherited risk, and consequent risk for various types of CVDs until middle age were analysed with Cox regression. All analyses were conducted first in the whole sample and then stratified by sex as is recommended in cardiovascular studies. RESULTS: During the follow-up of 586,943 person-years, 512 CVDs occurred. No clear association between SES clusters and CVD were found. Higher PRS associated with any CVD (HR per 1 SD increase 1.15; 95%CI 1.02-1.31), and ischemic CVD (HR 1.21; 1.05-1.40). We found no combined associations of early family SES and inherited risk for CVD. CONCLUSIONS: Inherited risk was associated with the risk for CVD in mid-life in Finnish population. We found no clear connection with early family SES and CVD. Being born to a specific SES group did not increase the effect of inherited risk.

The association of sociodemographic factors with total and item-level semantic fluency metrics.

OBJECTIVE: We aimed to estimate the association of age, education, and sex/gender with semantic fluency performance as measured by the standard total number of words as well as novel item-level metrics and to descriptively compare associations across cohorts with different recruitment strategies and sample compositions. METHOD: Cross-sectional data from 2,391 individuals from three cohorts were used: Washington Heights/Inwood Columbia Aging Project, a community-based cohort; Second Manifestations of ARTerial disease-Magnetic Resonance, a clinic-based cohort; and African American Alzheimer's Disease Genetics Study, a volunteer-based cohort. Total number of correct words and six item-level semantic fluency metrics were included as main outcomes: average cluster size, number of cluster switches, lexical/Zipf frequency, age of acquisition, and lexical decision response time. General linear models were run separately in each cohort to model the association between sociodemographic variables and semantic fluency metrics. RESULTS: Across cohorts, older age was associated with a lower total score and fewer cluster switches. Higher level of education was associated with naming more words, performing more cluster switches, and naming words with a longer lexical decision response time, lower frequency of occurrence, or later age of acquisition. Being female compared to male was associated with naming fewer words, smaller cluster sizes, naming words with a longer lexical decision response time, and lower age of acquisition. The effects varied in strength but were in a similar direction across cohorts. CONCLUSIONS: Item-level semantic fluency metrics-similar to the standard total score-are sensitive to the effects of age, education, and sex/gender. The results suggest geographical, cultural, and cross-linguistic generalizability of these sociodemographic effects on semantic fluency performance. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Prescribed Drug Use and Aneurysmal Subarachnoid Hemorrhage Incidence: A Drug-Wide Association Study.

BACKGROUND AND OBJECTIVES: Current benefits of invasive intracranial aneurysm treatment to prevent aneurysmal subarachnoid hemorrhage (aSAH) rarely outweigh treatment risks. Most intracranial aneurysms thus remain untreated. Commonly prescribed drugs reducing aSAH incidence may provide leads for drug repurposing. We performed a drug-wide association study (DWAS) to systematically investigate the association between commonly prescribed drugs and aSAH incidence. METHODS: We defined all aSAH cases between 2000 and 2020 using International Classification of Diseases codes from the Secure Anonymised Information Linkage databank. Each case was matched with 9 controls based on age, sex, and year of database entry. We investigated commonly prescribed drugs (>2% in study population) and defined 3 exposure windows relative to the most recent prescription before index date (i.e., occurrence of aSAH): current (within 3 months), recent (3-12 months), and past (>12 months). A logistic regression model was fitted to compare drug use across these exposure windows vs never use, controlling for age, sex, known aSAH risk factors, and health care utilization. The family-wise error rate was kept at p < 0.05 through Bonferroni correction. RESULTS: We investigated exposure to 205 commonly prescribed drugs between 4,879 aSAH cases (mean age 61.4, 61.2% women) and 43,911 matched controls. We found similar trends for lisinopril and amlodipine, with a decreased aSAH risk for current use (lisinopril odds ratio [OR] 0.63, 95% CI 0.44-0.90, amlodipine OR 0.82, 95% CI 0.65-1.04) and an increased aSAH risk for recent use (lisinopril OR 1.30, 95% CI 0.61-2.78, amlodipine OR 1.61, 95% CI 1.04-2.48). A decreased aSAH risk in current use was also found for simvastatin (OR 0.78, 95% CI 0.64-0.96), metformin (OR 0.58, 95% CI 0.43-0.78), and tamsulosin (OR 0.55, 95% CI 0.32-0.93). By contrast, an increased aSAH risk was found for current use of warfarin (OR 1.35, 95% CI 1.02-1.79), venlafaxine (OR 1.67, 95% CI 1.01-2.75), prochlorperazine (OR 2.15, 95% CI 1.45-3.18), and co-codamol (OR 1.31, 95% CI 1.10-1.56). DISCUSSION: We identified several drugs associated with aSAH, of which 5 drugs (lisinopril and possibly amlodipine, simvastatin, metformin, and tamsulosin) showed a decreased aSAH risk. Future research should build on these signals to further assess the effectiveness of these drugs in reducing aSAH incidence. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that some commonly prescribed drugs are associated with subsequent development of aSAH.

Prediction of aneurysmal subarachnoid hemorrhage in comparison with other stroke types using routine care data.

Aneurysmal subarachnoid hemorrhage (aSAH) can be prevented by early detection and treatment of intracranial aneurysms in high-risk individuals. We investigated whether individuals at high risk of aSAH in the general population can be identified by developing an aSAH prediction model with electronic health records (EHR) data. To assess the aSAH model's relative performance, we additionally developed prediction models for acute ischemic stroke (AIS) and intracerebral hemorrhage (ICH) and compared the discriminative performance of the models. We included individuals aged ≥35 years without history of stroke from a Dutch routine care database (years 2007-2020) and defined outcomes aSAH, AIS and ICH using International Classification of Diseases (ICD) codes. Potential predictors included sociodemographic data, diagnoses, medications, and blood measurements. We cross-validated a Cox proportional hazards model with an elastic net penalty on derivation cohorts and reported the c-statistic and 10-year calibration on validation cohorts. We examined 1,040,855 individuals (mean age 54.6 years, 50.9% women) for a total of 10,173,170 person-years (median 11 years). 17,465 stroke events occurred during follow-up: 723 aSAH, 14,659 AIS, and 2,083 ICH. The aSAH model's c-statistic was 0.61 (95%CI 0.57-0.65), which was lower than the c-statistic of the AIS (0.77, 95%CI 0.77-0.78) and ICH models (0.77, 95%CI 0.75-0.78). All models were well-calibrated. The aSAH model identified 19 predictors, of which the 10 strongest included age, female sex, population density, socioeconomic status, oral contraceptive use, gastroenterological complaints, obstructive airway medication, epilepsy, childbirth complications, and smoking. Discriminative performance of the aSAH prediction model was moderate, while it was good for the AIS and ICH models. We conclude that it is currently not feasible to accurately identify individuals at increased risk for aSAH using EHR data.

The mediating role of health behaviors in the association between depression, anxiety and cancer incidence: an individual participant data meta-analysis.

BACKGROUND: Although behavioral mechanisms in the association among depression, anxiety, and cancer are plausible, few studies have empirically studied mediation by health behaviors. We aimed to examine the mediating role of several health behaviors in the associations among depression, anxiety, and the incidence of various cancer types (overall, breast, prostate, lung, colorectal, smoking-related, and alcohol-related cancers). METHODS: Two-stage individual participant data meta-analyses were performed based on 18 cohorts within the Psychosocial Factors and Cancer Incidence consortium that had a measure of depression or anxiety (N = 319 613, cancer incidence = 25 803). Health behaviors included smoking, physical inactivity, alcohol use, body mass index (BMI), sedentary behavior, and sleep duration and quality. In stage one, path-specific regression estimates were obtained in each cohort. In stage two, cohort-specific estimates were pooled using random-effects multivariate meta-analysis, and natural indirect effects (i.e. mediating effects) were calculated as hazard ratios (HRs). RESULTS: Smoking (HRs range 1.04-1.10) and physical inactivity (HRs range 1.01-1.02) significantly mediated the associations among depression, anxiety, and lung cancer. Smoking was also a mediator for smoking-related cancers (HRs range 1.03-1.06). There was mediation by health behaviors, especially smoking, physical inactivity, alcohol use, and a higher BMI, in the associations among depression, anxiety, and overall cancer or other types of cancer, but effects were small (HRs generally below 1.01). CONCLUSIONS: Smoking constitutes a mediating pathway linking depression and anxiety to lung cancer and smoking-related cancers. Our findings underline the importance of smoking cessation interventions for persons with depression or anxiety.

Imaging of intracranial arterial disease: a comparison between MRI and unenhanced CT.

Background and purpose: Arterial calcifications on unenhanced CT scans and vessel wall lesions on MRI are often used interchangeably to portray intracranial arterial disease. However, the extent of pathology depicted with each technique is unclear. We investigated the presence and distribution of these two imaging findings in patients with a history of cerebrovascular disease. Materials and methods: We analyzed CT and MRI data from 78 patients admitted for stroke or TIA at our institution. Vessel wall lesions were assessed on 7 T MRI sequences, while arterial calcifications were assessed on CT scans. The number of vessel wall lesions, severity of intracranial internal carotid artery (iICA) calcifications, and overall presence and distribution of the two imaging findings were visually assessed in the intracranial arteries. Results: At least one vessel wall lesion or arterial calcification was assessed in 69 (88%) patients. Only the iICA and vertebral arteries (VA) showed a substantial number of both calcifications and vessel wall lesions. The other vessels showed almost exclusively vessel wall lesions. The number of vessel wall lesions was associated with the severity of iICA calcification (p = 0.013). Conclusions: The number of vessel wall lesions increases with the severity of iICA calcifications. Nonetheless, the distribution of vessel wall lesions on MRI and arterial calcifications on CT shows remarkable differences. These findings support the need for a combined approach to examine intracranial arterial disease.

Depressive Symptoms and Plasma Markers of Alzheimer's Disease and Neurodegeneration: A Coordinated Meta-Analysis of 8 Cohort Studies.

BACKGROUND: Depressive symptoms are associated with an increased risk of Alzheimer's disease (AD). There has been a recent emergence in plasma biomarkers for AD pathophysiology, such as amyloid-beta (Aß) and phosphorylated tau (p-tau), as well as for axonal damage (neurofilament light, NfL) and astrocytic activation (glial fibrillary acidic protein, GFAP). Hypothesizing that depressive symptoms may occur along the AD process, we investigated associations between plasma biomarkers of AD with depressive symptoms in individuals without dementia. METHODS: A two-stage meta-analysis was performed on 2 clinic-based and 6 population-based cohorts (N = 7210) as part of the Netherlands Consortium of Dementia Cohorts. Plasma markers (Aß42/40, p-tau181, NfL, and GFAP) were measured using Single Molecular Array (Simoa; Quanterix) assays. Depressive symptoms were measured with validated questionnaires. We estimated the cross-sectional association of each standardized plasma marker (determinants) with standardized depressive symptoms (outcome) using linear regressions, correcting for age, sex, education, and APOE ε4 allele presence, as well as subgrouping by sex and APOE ε4 allele. Effect estimates were entered into a random-effects meta-analysis. RESULTS: Mean age of participants was 71 years. The prevalence of clinically relevant depressive symptoms ranged from 1% to 22%. None of the plasma markers were associated with depressive symptoms in the meta-analyses. However, NfL was associated with depressive symptoms only in APOE ε4 carriers (ß 0.11; 95% CI: 0.05-0.17). CONCLUSIONS: Late-life depressive symptoms did not show an association to plasma biomarkers of AD pathology. However, in APOE ε4 allele carriers, a more profound role of neurodegeneration was suggested with depressive symptoms.

Sex differences in modifiable risk factors for stroke incidence and recurrence: the UCC-SMART study.

BACKGROUND AND PURPOSE: Risk factors for stroke differ between women and men in general populations. However, little is known about sex differences in secondary prevention. We investigated if sex interacted with modifiable risk factors for stroke in a large arterial disease cohort. METHODS: Within the prospective UCC-SMART study, 13,898 patients (35% women) with atherosclerotic disease or high-risk factor profile were followed up to 23 years for stroke incidence or recurrence. Hypertension, smoking, diabetes, overweight, dyslipidemia, high alcohol use, and physical inactivity were studied as risk factors. Association between these factors and ischemic and hemorrhagic stroke incidence or recurrence was studied in women and men using Cox proportional hazard models and Poisson regression models. Women-to-men relative hazard ratios (RHR) and rate differences (RD) were estimated for each risk factor. Left-truncated age was used as timescale. RESULTS: The age-adjusted stroke incidence rate was lower in women than men (3.9 vs 4.4 per 1000 person-years), as was the age-adjusted stroke recurrence rate (10.0 vs 11.7). Hypertension and smoking were associated with stroke risk in both sexes. HDL cholesterol was associated with lower stroke incidence in women but not in men (RHR 0.49; CI 0.27-0.88; and RD 1.39; CI - 1.31 to 4.10). Overweight was associated with a lower stroke recurrence in women but not in men (RHR 0.42; CI 0.23-0.80; and RD 9.05; CI 2.78-15.32). CONCLUSIONS: In high-risk population, sex modifies the association of HDL cholesterol on stroke incidence, and the association of overweight on stroke recurrence. Our findings highlight the importance of sex-specific secondary prevention.

Plasma Markers of Alzheimer's Disease Pathology, Neuronal Injury, and Astrocytic Activation and MRI Load of Vascular Pathology and Neurodegeneration: The SMART-MR Study.

BACKGROUND: Two of the main causes for dementia are Alzheimer's disease (AD) and vascular pathology, with most patients showing mixed pathology. Plasma biomarkers for Alzheimer's disease-related pathology have recently emerged, including Aß (amyloid-beta), p-tau (phosphorylated tau), NfL (neurofilament light), and GFAP (glial fibrillary acidic protein). There is a current gap in the literature regarding whether there is an association between these plasma biomarkers with vascular pathology and neurodegeneration. METHODS AND RESULTS: Cross-sectional data from 594 individuals (mean [SD] age: 64 [8] years; 17% female) were included from the SMART-MR (Second Manifestations of Arterial Disease-Magnetic Resonance) study, a prospective cohort study of individuals with a history of arterial disease. Plasma markers were assessed using single molecular array assays (Quanterix). Magnetic resonance imaging markers included white matter hyperintensity volume, presence of infarcts (yes/no), total brain volume, and hippocampal volume assessed on 1.5T magnetic resonance imaging. Linear regressions were performed for each standardized plasma marker with white matter hyperintensity volume, total brain volume, and hippocampal volume as separate outcomes, correcting for age, sex, education, and intracranial volume. Logistic regressions were performed for the presence of lacunar and cortical infarcts. Higher p-tau181 was associated with larger white matter hyperintensity volume (b per SD increase=0.16 [95% CI, 0.06-0.26], P=0.015). Higher NfL (b=-5.63, [95% CI, -8.95 to -2.31], P=0.015) was associated with lower total brain volume and the presence of infarcts (odds ratio [OR], 1.42 [95% CI, 1.13-1.78], P=0.039). Higher GFAP levels were associated with cortical infarcts (OR, 1.45 [95% CI, 1.09-1.92], P=0.010). CONCLUSIONS: Plasma biomarkers that have been associated with tau pathology, axonal injury, and astrocytic activation are related to magnetic resonance imagingmarkers of vascular pathology and neurodegeneration in patients with manifest arterial disease.

RISK FACTORS FOR MEDIAL AND INTIMAL INTRACRANIAL INTERNAL CAROTID ARTERY CALCIFICATION IN MEN AND WOMEN WITH CARDIOVASCULAR DISEASE. THE UCC-SMART STUDY.

INTRODUCTION: Calcifications of the intracranial internal carotid artery (iICA) can lead to an increased risk for stroke. Two types of iICA calcification are known: those affecting the tunica intima or the tunica media. In extracranial arteries, risk factors and calcification patterns are different in women and men, but little is known regarding the iICA. In this study we aimed to identify sex-specific risk profiles and medications associated to intimal and medial iICA calcification in patients with cardiovascular disease (CVD). METHODS: Participants of the UCC-SMART cohort undergoing a non-contrast head CT within six months from the study inclusion were considered (n=475). Intimal or medial iICA calcification pattern was assessed using a previously histology-validated method. Sex-stratified associations between calcification pattern and cardiovascular risk factors, laboratory parameters, and medication use were calculated using Poisson regression analysis with robust standard errors. RESULTS: 204 women and 271 men (age range 24-79 years) were included. 45.4% of men and 34.8% of women showed intimal iICA calcification, while 28.4% of men and 24.0% of women showed medial iICA calcification. Minimal or no iICA calcification was observed in 26.2% of men and in 41,2% of women (reference group). Older age was associated with both calcification patterns in women and men. In women, use of vitamin K antagonists and lipid lowering drugs were associated to medial calcification, while systolic blood pressure and glucose levels were associated to intimal calcification. In men, current smoking was associated to intimal calcification. CONCLUSIONS: Women and men with CVD show differences in risk profiles and medication use associated to intimal and medial iCA calcification.

Psychosocial factors, health behaviors and risk of cancer incidence: Testing interaction and effect modification in an individual participant data meta-analysis.

Depression, anxiety and other psychosocial factors are hypothesized to be involved in cancer development. We examined whether psychosocial factors interact with or modify the effects of health behaviors, such as smoking and alcohol use, in relation to cancer incidence. Two-stage individual participant data meta-analyses were performed based on 22 cohorts of the PSYchosocial factors and CAncer (PSY-CA) study. We examined nine psychosocial factors (depression diagnosis, depression symptoms, anxiety diagnosis, anxiety symptoms, perceived social support, loss events, general distress, neuroticism, relationship status), seven health behaviors/behavior-related factors (smoking, alcohol use, physical activity, body mass index, sedentary behavior, sleep quality, sleep duration) and seven cancer outcomes (overall cancer, smoking-related, alcohol-related, breast, lung, prostate, colorectal). Effects of the psychosocial factor, health behavior and their product term on cancer incidence were estimated using Cox regression. We pooled cohort-specific estimates using multivariate random-effects meta-analyses. Additive and multiplicative interaction/effect modification was examined. This study involved 437,827 participants, 36,961 incident cancer diagnoses, and 4,749,481 person years of follow-up. Out of 744 combinations of psychosocial factors, health behaviors, and cancer outcomes, we found no evidence of interaction. Effect modification was found for some combinations, but there were no clear patterns for any particular factors or outcomes involved. In this first large study to systematically examine potential interaction and effect modification, we found no evidence for psychosocial factors to interact with or modify health behaviors in relation to cancer incidence. The behavioral risk profile for cancer incidence is similar in people with and without psychosocial stress.

Microvascular Dysfunction and Whole-Brain White Matter Connectivity: The Maastricht Study.

BACKGROUND: Microvascular dysfunction is involved in the development of various cerebral disorders. It may contribute to these disorders by disrupting white matter tracts and altering brain connectivity, but evidence is scarce. We investigated the association between multiple biomarkers of microvascular function and whole-brain white matter connectivity. METHODS AND RESULTS: Cross-sectional data from The Maastricht Study, a Dutch population-based cohort (n=4326; age, 59.4±8.6 years; 49.7% women). Measures of microvascular function included urinary albumin excretion, central retinal arteriolar and venular calibers, composite scores of flicker light-induced retinal arteriolar and venular dilation, and plasma biomarkers of endothelial dysfunction (intercellular adhesion molecule-1, vascular cell adhesion molecule-1, E-selectin, and von Willebrand factor). White matter connectivity was calculated from 3T diffusion magnetic resonance imaging to quantify the number (average node degree) and organization (characteristic path length, global efficiency, clustering coefficient, and local efficiency) of white matter connections. A higher plasma biomarkers of endothelial dysfunction composite score was associated with a longer characteristic path length (ß per SD, 0.066 [95% CI, 0.017-0.114]) after adjustment for sociodemographic, lifestyle, and cardiovascular factors but not with any of the other white matter connectivity measures. After multiple comparison correction, this association was nonsignificant. None of the other microvascular function measures were associated with any of the connectivity measures. CONCLUSIONS: These findings suggest that microvascular dysfunction as measured by indirect markers is not associated with whole-brain white matter connectivity.

Association of amyloid-beta with depression or depressive symptoms in older adults without dementia: a systematic review and meta-analysis.

Several lines of evidence have indicated that depression might be a prodromal symptom of Alzheimer's disease (AD). This systematic review and meta-analysis investigated the cross-sectional association between amyloid-beta, one of the key pathologies defining AD, and depression or depressive symptoms in older adults without dementia. A systematic search in PubMed yielded 689 peer-reviewed articles. After full-text screening, nine CSF studies, 11 PET studies, and five plasma studies were included. No association between amyloid-beta and depression or depressive symptoms were found using cerebrospinal fluid (CSF) (0.15; 95% CI: -0.08; 0.37), positron emission topography (PET) (Cohen's d: 0.09; 95% CI: -0.05; 0.24), or plasma (-0.01; 95% CI: -0.23; 0.22). However, subgroup analyses revealed an association in plasma studies of individuals with cognitive impairment. A trend of an association was found in the studies using CSF and PET. This systematic review and meta-analysis suggested that depressive symptoms may be part of the prodromal stage of dementia.

Effect of Physical Exercise on MRI-Assessed Brain Perfusion in Chemotherapy-Treated Breast Cancer Patients: A Randomized Controlled Trial.

BACKGROUND: Exercise is a promising intervention to alleviate cognitive problems in breast cancer patients, but studies on mechanisms underlying these effects are lacking. PURPOSE: Investigating whether an exercise intervention can affect cerebral blood flow (CBF) in cognitively impaired breast cancer patients and to determine if CBF changes relate to memory function. STUDY TYPE: Prospective. POPULATION: A total of 181 chemotherapy-treated stage I-III breast cancer patients with cognitive problems and relatively low physical activity levels (≤150 minutes moderate to vigorous physical activity per week), divided into an exercise (N = 91) or control group (N = 90). FIELD STRENGTH/SEQUENCE: Two-dimensional echo planar pseudo-continuous arterial spin labeling CBF sequence at 3 T. ASSESSMENT: The 6-month long intervention consisted of (supervised) aerobic and strength training, 4 × 1 hour/week. Measurements at baseline (2-4 years post-diagnosis) and after 6 months included gray matter CBF in the whole brain, hippocampus, anterior cingulate cortex, and posterior cingulate cortex. Physical fitness and memory function were also assessed. Subgroup analyses were performed in patients with high fatigue levels at baseline. STATISTICAL TESTS: Multiple regression analyses with a two-sided alpha of 0.05 for all analyses. RESULTS: There was a significant improvement in physical fitness (VO2peak in mL/minute/kg) in the intervention group (N = 53) compared to controls (N = 51, ß = 1.47 mL/minute/kg, 95% CI: 0.44-2.50). However, no intervention effects on CBF were found (eg, whole brain: P = 0.565). Highly fatigued patients showed larger but insignificant treatment effects on CBF (eg, whole brain: P = 0.098). Additionally, irrespective of group, a change in physical fitness was positively associated with changes in CBF (eg, whole brain: ß = 0.75, 95% CI: 0.07-1.43). There was no significant relation between CBF changes and changes in memory performance. DATA CONCLUSION: The exercise intervention did not affect CBF of cognitively affected breast cancer patients. A change in physical fitness was associated with changes in CBF, but changes in CBF were not associated with memory functioning. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 5.

Performance of a diagnostic model for the presence of unruptured intracranial aneurysms in the general population.

INTRODUCTION: The prevalence of unruptured intracranial aneurysms (UIAs) in the general population is 3%. Aneurysmal subarachnoid hemorrhage (aSAH) can be prevented by screening for UIAs followed by monitoring and, if needed, preventive neurosurgical or endovascular treatment of identified UIAs. Therefore, we developed a diagnostic model for presence of UIAs in the general population to help identify persons at high risk of having UIAs. METHODS: Between 2005-2015, participants from the population-based Rotterdam Study underwent brain magnetic resonance imaging at 1.5 Tesla, on which presence of incidental UIAs was evaluated. We developed a multivariable logistic regression model using candidate diagnostic markers that were selected based on the literature, including sex, age, hypertension, smoking, hypercholesterolemia, diabetes, alcohol, and their interactions. We corrected for overfitting using bootstrapping. Model performance was assessed with discrimination, calibration, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). RESULTS: 5835 persons were included (55.0% women, mean age 64.9 ± 10.9 years) with a 2.2% UIA prevalence. Sex, age, hypertension, smoking, diabetes, and interactions of sex with age, hypertension, and smoking were independent diagnostic markers. The resulting model had a c-statistic of 0.65 (95% confidence interval [CI] 0.60 - 0.68) and 56% sensitivity, 52% specificity, 98% PPV, and 3% NPV for UIA presence at a cut-off value of 4%. Because of interactions with sex, additional models for men and women separately were developed. The model for men had a c-statistic of 0.70 (95% CI 0.62 - 0.78) with age, hypertension, and smoking as diagnostic markers and comparable additional performance values as for the full model. The model for women had a c-statistic of 0.58 (95% CI 0.52 - 0.63) with smoking as the only diagnostic marker. CONCLUSION: Our diagnostic model had insufficient performance to help identify persons at high risk of having UIAs in the general population. Rather, it provides insight in risk factors contributing to UIA risk and shows that these may be in part sex-specific.

Bear in mind: the role of personal background in semantic animal fluency - The SMART-MR study.

Objectives: Semantic fluency is a prominent neuropsychological task, typically administered within the category 'animals'. With the increasing development of novel item-level metrics of semantic fluency, a concern around the validity of item-level analyses could be that personal background factors (e.g., hobbies like birdwatching or fishing) may disproportionally influence performance. We analyzed animal fluency performance at the item level and investigated the prevalence of individuals with abundant knowledge in specific classes of animals (e.g., birds, fish, insects) and the relationship of such knowledge with personal background factors and other cognitive tasks (episodic memory and executive functioning). Method: Participants included 736 Dutch middle-aged to older adults from the SMART-MR cohort (mean age 58 ± 9.4 years, 18% women). Individuals were asked to name as many animals as possible for 2 min. Number of people with abundant animal class knowledge was calculated for the ability to recall a series of minimum ≥5 and up to ≥15 animals within a specific class with at most one interruption by an animal from another class. Subsequent analyses to investigate relationships of abundant class knowledge with sociodemographic characteristics (t-tests and chi-square tests) and cognitive performance (linear regressions) were performed for a cut-off of ≥10 animals within a specific class (90th percentile), with a sensitivity analysis for ≥7 animals (67th percentile). Results: A total of 416 (56.2%) participants recalled a series of ≥5 animals from a specific class, 245 (33.3%) participants recalled ≥7, 78 (10.6%) participants recalled ≥10, and 8 (1.1%) participants recalled ≥15. Those who recalled a series of at least 10 animals within a class were older, more often men, and more often retired than those who did not. Moreover, they had a higher total score on animal fluency, letter fluency (i.e., executive functioning), and episodic memory tasks compared to those who did not. Discussion: Our results suggest that the benefit of abundant animal class knowledge gained by personal background does not disproportionally influence animal fluency performance as individuals with such knowledge also performed better on other cognitive tasks unrelated to abundant knowledge of animal classes.

Dementia prediction in the general population using clinically accessible variables: a proof-of-concept study using machine learning. The AGES-Reykjavik study.

BACKGROUND: Early identification of dementia is crucial for prompt intervention for high-risk individuals in the general population. External validation studies on prognostic models for dementia have highlighted the need for updated models. The use of machine learning in dementia prediction is in its infancy and may improve predictive performance. The current study aimed to explore the difference in performance of machine learning algorithms compared to traditional statistical techniques, such as logistic and Cox regression, for prediction of all-cause dementia. Our secondary aim was to assess the feasibility of only using clinically accessible predictors rather than MRI predictors. METHODS: Data are from 4,793 participants in the population-based AGES-Reykjavik Study without dementia or mild cognitive impairment at baseline (mean age: 76 years, % female: 59%). Cognitive, biometric, and MRI assessments (total: 59 variables) were collected at baseline, with follow-up of incident dementia diagnoses for a maximum of 12 years. Machine learning algorithms included elastic net regression, random forest, support vector machine, and elastic net Cox regression. Traditional statistical methods for comparison were logistic and Cox regression. Model 1 was fit using all variables and model 2 was after feature selection using the Boruta package. A third model explored performance when leaving out neuroimaging markers (clinically accessible model). Ten-fold cross-validation, repeated ten times, was implemented during training. Upsampling was used to account for imbalanced data. Tuning parameters were optimized for recalibration automatically using the caret package in R. RESULTS: 19% of participants developed all-cause dementia. Machine learning algorithms were comparable in performance to logistic regression in all three models. However, a slight added performance was observed in the elastic net Cox regression in the third model (c = 0.78, 95% CI: 0.78-0.78) compared to the traditional Cox regression (c = 0.75, 95% CI: 0.74-0.77). CONCLUSIONS: Supervised machine learning only showed added benefit when using survival techniques. Removing MRI markers did not significantly worsen our model's performance. Further, we presented the use of a nomogram using machine learning methods, showing transportability for the use of machine learning models in clinical practice. External validation is needed to assess the use of this model in other populations. Identifying high-risk individuals will amplify prevention efforts and selection for clinical trials.

Depression, anxiety, and the risk of cancer: An individual participant data meta-analysis.

BACKGROUND: Depression and anxiety have long been hypothesized to be related to an increased cancer risk. Despite the great amount of research that has been conducted, findings are inconclusive. To provide a stronger basis for addressing the associations between depression, anxiety, and the incidence of various cancer types (overall, breast, lung, prostate, colorectal, alcohol-related, and smoking-related cancers), individual participant data (IPD) meta-analyses were performed within the Psychosocial Factors and Cancer Incidence (PSY-CA) consortium. METHODS: The PSY-CA consortium includes data from 18 cohorts with measures of depression or anxiety (up to N = 319,613; cancer incidences, 25,803; person-years of follow-up, 3,254,714). Both symptoms and a diagnosis of depression and anxiety were examined as predictors of future cancer risk. Two-stage IPD meta-analyses were run, first by using Cox regression models in each cohort (stage 1), and then by aggregating the results in random-effects meta-analyses (stage 2). RESULTS: No associations were found between depression or anxiety and overall, breast, prostate, colorectal, and alcohol-related cancers. Depression and anxiety (symptoms and diagnoses) were associated with the incidence of lung cancer and smoking-related cancers (hazard ratios [HRs], 1.06-1.60). However, these associations were substantially attenuated when additionally adjusting for known risk factors including smoking, alcohol use, and body mass index (HRs, 1.04-1.23). CONCLUSIONS: Depression and anxiety are not related to increased risk for most cancer outcomes, except for lung and smoking-related cancers. This study shows that key covariates are likely to explain the relationship between depression, anxiety, and lung and smoking-related cancers. PREREGISTRATION NUMBER: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=157677.