Subjective Cognitive Decline Plus and Longitudinal Assessment and Risk for Cognitive Impairment.

Importance: Subjective cognitive decline (SCD) is recognized to be in the Alzheimer disease (AD) cognitive continuum. The SCD Initiative International Working Group recently proposed SCD-plus (SCD+) features that increase risk for future objective cognitive decline but that have not been assessed in a large community-based setting. Objective: To assess SCD risk for mild cognitive impairment (MCI), AD, and all-cause dementia, using SCD+ criteria among cognitively normal adults. Design, Setting, and Participants: The Framingham Heart Study, a community-based prospective cohort study, assessed SCD between 2005 and 2019, with up to 12 years of follow-up. Participants 60 years and older with normal cognition at analytic baseline were included. Cox proportional hazards (CPH) models were adjusted for baseline age, sex, education, APOE ε4 status, and tertiles of AD polygenic risk score (PRS), excluding the APOE region. Data were analyzed from May 2021 to November 2023. Exposure: SCD was assessed longitudinally using a single question and considered present if endorsed at the last cognitively normal visit. It was treated as a time-varying variable, beginning at the first of consecutive, cognitively normal visits, including the last, at which it was endorsed. Main Outcomes and Measures: Consensus-diagnosed MCI, AD, and all-cause dementia. Results: This study included 3585 participants (mean [SD] baseline age, 68.0 [7.7] years; 1975 female [55.1%]). A total of 1596 participants (44.5%) had SCD, and 770 (21.5%) were carriers of APOE ε4. APOE ε4 and tertiles of AD PRS status did not significantly differ between the SCD and non-SCD groups. MCI, AD, and all-cause dementia were diagnosed in 236 participants (6.6%), 73 participants (2.0%), and 89 participants (2.5%), respectively, during follow-up. On average, SCD preceded MCI by 4.4 years, AD by 6.8 years, and all-cause dementia by 6.9 years. SCD was significantly associated with survival time to MCI (hazard ratio [HR], 1.57; 95% CI, 1.22-2.03; P <.001), AD (HR, 2.98; 95% CI, 1.89-4.70; P <.001), and all-cause dementia (HR, 2.14; 95% CI, 1.44-3.18; P <.001). After adjustment for APOE and AD PRS, the hazards of SCD were largely unchanged. Conclusions and Relevance: Results of this cohort study suggest that in a community setting, SCD reflecting SCD+ features was associated with an increased risk of future MCI, AD, and all-cause dementia with similar hazards estimated in clinic-based settings. SCD may be an independent risk factor for AD and other dementias beyond the risk incurred by APOE ε4 and AD PRS.

Lessons From the Coronavirus Disease Experience: Research Participant and Staff Satisfaction With Remote Cognitive Evaluations.

OBJECTIVE: In New York City in 2020 the pandemic shut down in-person research. Icahn School of Medicine's Alzheimer's Disease Research Center transitioned longitudinal evaluations from in-person to telephone to enhance equity of access. We assessed diverse research participants' and clinical research coordinators' (CRC) satisfaction with remote evaluation and examined sociodemographic, cognitive, and behavioral factors that might impact satisfaction. METHODS: Data collected: 241 participants with Clinical Dementia Rating (CDR) = 0/0.5 (3/2020 to 6/2021). A Telehealth Satisfaction Questionnaire for CRCs and participants was administered at the end of remote evaluations. We compared Telehealth Satisfaction Questionnaire items by CDR and Geriatric Depression Scale. RESULTS: Participants' mean age was 78.4, 61.4% were females, 16.2% were Hispanic, 17.1% Asian, 15.8% were non-Hispanic black, and 72.6% CDR = 0. Participant satisfaction was high [14.1 ± 1.4 (out of 15)] but was lower among those with depression. CRC satisfaction was high [16.9 ± 1.8 (out of 18)] but was lower concerning the ability to explain the test battery and interact with participants with CDR = 0.5. CONCLUSION: Telephone research assessments provide flexibility in a hybrid model. They offer equitable access to research participation for those who do not use computer technology and may promote the retention of diverse elderly research participants.

Effects of Mind-Body Qigong Exercise on Overall Health, Fatigue/Sleep, and Cognition in Older Chinese Immigrants in the US: An Intervention Study with Control.

Background: Culturally relevant exercises may help improve health and address disparities faced by older immigrants due to language and cultural barriers. Few studies have focused on such exercise interventions among older Chinese immigrants at US daycare centers. Methods: We conducted a 10-week nonrandomized controlled trial in older Chinese immigrants in Philadelphia, US. The intervention group practiced Chinese Qigong (Baduanjin) 5 days a week guided by trained research assistants and video instructions. The control group maintained their usual daily activities. We collected self-report assessments on overall health, sleep, and fatigue and implemented two computerized cognitive tests measuring psychomotor vigilance task (PVT) and memory twice, preintervention and postintervention. Repeated measures general linear model (GLM) and paired samples t-tests were used for data analyses. Results: Eighty-eight older adults (Qigong, n = 53; control, n = 35) with an average age of 78.13 (SD = 5.05) were included. Groups showed no significant differences at baseline evaluation. After the 10-week exercise, the intervention group showed significant improvements in overall health (p=0.032), fatigue (p < 0.001), and cognitive functions including memory (p=0.01), response speed (p=0.002), and response time (p=0.012) on the PVT, as well as marginally significant benefits in sleep (p=0.058). Between-group comparisons identified significant group-by-time interactions in health (p=0.024), sleep (p=0.004), fatigue (p=0.004), and memory (p=0.004). Conclusion: We revealed significant positive effects of Qigong in older Chinese immigrants across multiple health domains. Findings highlight the potential of a culturally relevant exercise in addressing health disparities.

Asian Cohort for Alzheimer's Disease (ACAD) pilot study on genetic and non-genetic risk factors for Alzheimer's disease among Asian Americans and Canadians.

INTRODUCTION: Clinical research in Alzheimer's disease (AD) lacks cohort diversity despite being a global health crisis. The Asian Cohort for Alzheimer's Disease (ACAD) was formed to address underrepresentation of Asians in research, and limited understanding of how genetics and non-genetic/lifestyle factors impact this multi-ethnic population. METHODS: The ACAD started fully recruiting in October 2021 with one central coordination site, eight recruitment sites, and two analysis sites. We developed a comprehensive study protocol for outreach and recruitment, an extensive data collection packet, and a centralized data management system, in English, Chinese, Korean, and Vietnamese. RESULTS: ACAD has recruited 606 participants with an additional 900 expressing interest in enrollment since program inception. DISCUSSION: ACAD's traction indicates the feasibility of recruiting Asians for clinical research to enhance understanding of AD risk factors. ACAD will recruit > 5000 participants to identify genetic and non-genetic/lifestyle AD risk factors, establish blood biomarker levels for AD diagnosis, and facilitate clinical trial readiness. HIGHLIGHTS: The Asian Cohort for Alzheimer's Disease (ACAD) promotes awareness of under-investment in clinical research for Asians. We are recruiting Asian Americans and Canadians for novel insights into Alzheimer's disease. We describe culturally appropriate recruitment strategies and data collection protocol. ACAD addresses challenges of recruitment from heterogeneous Asian subcommunities. We aim to implement a successful recruitment program that enrolls across three Asian subcommunities.

Sleep dysfunction mediates the relationship between hypothalamic-insula connectivity and anxiety-depression symptom severity bidirectionally in young adults.

BACKGROUND: The hypothalamus plays a crucial role in regulating sleep-wake cycle and motivated behavior. Sleep disturbance is associated with impairment in cognitive and affective functions. However, how hypothalamic dysfunction may contribute to inter-related sleep, cognitive, and emotional deficits remain unclear. METHODS: We curated the Human Connectome Project dataset and investigated how hypothalamic resting state functional connectivities (rsFC) were associated with sleep dysfunction, as evaluated by the Pittsburgh Sleep Quality Index (PSQI), cognitive performance, and subjective mood states in 687 young adults (342 women). Imaging data were processed with published routines and evaluated with a corrected threshold. We examined the inter-relationship amongst hypothalamic rsFC, PSQI score, and clinical measures with mediation analyses. RESULTS: In whole-brain regressions with age and drinking severity as covariates, men showed higher hypothalamic rsFC with the right insula in correlation with PSQI score. No clusters were identified in women at the same threshold. Both hypothalamic-insula rsFC and PSQI score were significantly correlated with anxiety and depression scores in men. Further, mediation analyses showed that PSQI score mediated the relationship between hypothalamic-insula rsFC and anxiety/depression symptom severity bidirectionally in men. CONCLUSIONS: Sleep dysfunction is associated with negative emotions and hypothalamic rsFC with the right insula, a core structure of the interoceptive circuits. Notably, anxiety-depression symptom severity and altered hypothalamic-insula rsFC are related bidirectionally by poor sleep quality. These findings are specific to men, suggesting potential sex differences in the neural circuits regulating sleep and emotional states that need to be further investigated.

The utility of word list and story recall for identifying older U.S. Chinese immigrants with cognitive impairment.

OBJECTIVE: This study examined the utility of the Chinese-language translations of the word list memory test (Philadelphia Verbal Learning Test) and story memory test (Logical Memory subtest of the Wechsler Memory Scale) for differentiating cognitive diagnosis in older U.S. Chinese immigrants. METHOD: Participants were ≥ 60 years old, with Chinese language proficiency to complete a diagnostic workup at the Mount Sinai's Alzheimer's Disease Research Center. The workup included an evaluation by a geriatric psychiatrist and cognitive testing with a psychometrician. Diagnosis of normal, mild cognitive impairment (MCI), and dementia was made independent of the cognitive tests at consensus led by a dementia expert physician. Multivariable logistic regression models were used to assess the sensitivity of story and word list memory tests for distinguishing between groups. Receiver operating characteristic (ROC area/area under the curve [AUC]) was used to compare the predictive accuracy of the two tests. RESULTS: The sample included 71 participants with normal cognition, 42 with MCI, and 24 with dementia. The MCI group was older and less educated than normal controls but younger and more educated than the dementia group. Delayed recall of both memory tests, but not immediate recall of either test, predicted diagnosis. While composite memory score of word list (AUC = 0.90) predicted diagnosis slightly better than that of stories (AUC = 0.85), the difference was not significant in this small sample (p = .14). CONCLUSIONS: Chinese-language translations of verbal memory tests, in particular delayed recall scores, were equally sensitive for classifying cognitive diagnosis in older U.S. Chinese immigrants. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Evaluating memory testing to distinguish dementia severity among White, Black, and Spanish-speaking individuals in the Uniform Data Set (UDS).

INTRODUCTION: Little work has compared the effectiveness of using multiple types of memory tests alone or in combination to distinguish dementia severity in diverse research cohorts including Black individuals and Spanish speakers. Here we evaluate word list and paragraph recall tests to distinguish cognitively normal, mild cognitively impaired, and those with Alzheimer's disease in diverse cohorts. METHODS: Using Uniform Data Set (UDS) and site-specific supplemental data, logistic regression models and receiver operating characteristic-area under the curve were used to compare paragraph recall versus word list in differentiating among Clinical Dementia Rating (CDR) scale level. RESULTS: Results reveal high discriminability for all groups and no difference between either test in distinguishing between CDR levels. Combining tests improved discriminability for the whole group but did not for Black individuals or Spanish speakers. DISCUSSION: Our findings indicate that using multiple memory tests may not improve differentiation between cognitive impairment levels for diverse cohorts. The burden of added testing may be a barrier for maximizing inclusion of under-represented groups in research.

The use of subjective cognitive complaints for detecting mild cognitive impairment in older adults across cultural and linguistic groups: A comparison of the Cognitive Function Instrument to the Montreal Cognitive Assessment.

INTRODUCTION: This pilot study aims to explore the psychometric properties of the Cognitive Function Instrument (CFI) as a measure of subjective cognitive complaints (SCC) and its performance in distinguishing mild cognitive impairment (MCI) from normal control (NC) compared to an objective cognitive screen (Montreal Cognitive Assessment [MoCA]). METHODS: One hundred ninety-four community-dwelling non-demented older adults with racial/ethnic diversity were included. Unidimensionality and internal consistency of the CFI were examined using factor analysis, Cronbach's alpha, and McDonald's omega. Logistic regression models and receiver operating characteristic (ROC) analysis were used to examine the performance of CFI. RESULTS: The CFI demonstrated adequate internal consistency; however, the fit for a unidimensional model was suboptimal. The CFI distinguished MCI from NC alone or in combination with MoCA. ROC analysis showed comparable performance of the CFI and the MoCA. DISCUSSION: Our findings support the use of CFI as a brief and easy-to-use screen to detect MCI in culturally/linguistically diverse older adults. HIGHLIGHT: What is the key scientific question or problem of central interest of the paper? Subjective cognitive complaints (SCCs) are considered the earliest sign of dementia in older adults. However, it is unclear if SCC are equivalent in different cultures. The Cognitive Function Instrument (CFI) is a 14-item measure of SCC. This study provides pilot data suggesting that CFI is sensitive for detecting mild cognitive impairment in a cohort of older adults with racial/ethnic diversity. Comparing performance, CFI demonstrates comparable sensitivity to the Montreal Cognitive Assessment, an objective cognitive screening test. Overall, SCC may provide a non-invasive, easy-to-use method to flag possible cognitive impairment in both research and clinical settings.

Gray matter volumetric correlates of attention deficit and hyperactivity traits in emerging adolescents.

Previous research has demonstrated reduction in cortical and subcortical, including basal ganglia (BG), gray matter volumes (GMV) in individuals with attention deficit hyperactivity disorder (ADHD), a neurodevelopmental condition that is more prevalent in males than in females. However, the volumetric deficits vary across studies. Whether volumetric reductions are more significant in males than females; to what extent these neural markers are heritable and relate to cognitive dysfunction in ADHD remain unclear. To address these questions, we followed published routines and performed voxel-based morphometry analysis of a data set (n = 11,502; 5,464 girls, 9-10 years) curated from the Adolescent Brain Cognition Development project, a population-based study of typically developing children. Of the sample, 634 and 2,826 were identified as monozygotic twins and dizygotic twins/siblings, respectively. In linear regressions, a cluster in the hypothalamus showed larger GMV, and bilateral caudate and putamen, lateral orbitofrontal and occipital cortex showed smaller GMVs, in correlation with higher ADHD scores in girls and boys combined. When examined separately, boys relative to girls showed more widespread (including BG) and stronger associations between GMV deficits and ADHD scores. ADHD traits and the volumetric correlates demonstrated heritability estimates (a2) between 0.59 and 0.79, replicating prior findings of the genetic basis of ADHD. Further, ADHD traits and the volumetric correlates (except for the hypothalamus) were each negatively and positively correlated with N-back performance. Together, these findings confirm volumetric deficits in children with more prominent ADHD traits. Highly heritable in both girls and boys and potentially more significant in boys than in girls, the structural deficits underlie diminished capacity in working memory and potentially other cognitive deficits in ADHD.

Gray matter volumetric correlates of dimensional impulsivity traits in children: Sex differences and heritability.

Previous research investigated the cerebral volumetric correlates of impulsivity largely in moderate-sized samples and few have examined the distinct correlates of dimensions of impulsivity, sex differences, or heritability of the correlates. Here, we performed voxel-based morphometry analysis of data (n = 11,474; 5,452 girls, 9-10 years) curated from the Adolescent Brain Cognition Development project. In a linear regression with all five UPPS-P subscores as regressors and age in months, total intracranial volume, study site, and scanner model as covariates, higher levels of lack of premeditation, and sensation seeking were correlated with larger cortical and subcortical gray matter volumes (GMVs). In contrast, higher positive urgency was correlated with smaller GMVs in many of the same regions. The dimensional impulsivity traits also involved distinct volumetric correlates, with, for instance, sensation seeking and positive urgency specifically implicating bilateral caudate head/mid-cingulate cortex and bilateral lateral orbitofrontal cortex/left precentral gyrus, respectively. Boys relative to girls scored higher in all impulsivity dimensions. Girls relative to boys showed significantly stronger positive and negative correlations between sensation seeking and insula, putamen, and inferior frontal gyrus (IFG) GMVs and between positive urgency and cingulate cortex, insula, and IFG GMVs, respectively. With a subsample of twins, the dimensional impulsivity traits were weakly to moderately heritable in both girls and boys, and the GMV correlates were highly heritable in girls and boys combined. These findings collectively suggest shared and nonshared as well as sex differences in the cerebral volumetric bases of dimensional impulsivity traits and may facilitate research of externalizing psychopathology in children.

Sex Differences in Depression and Sleep Disturbance as Inter-Related Risk Factors of Diabetes.

Objectives: Previous studies identified depression and sleep disturbance as risk factors for diabetes. Sleep disturbance and depression are known to be inter-related. Further, women relative to men are more prone to depression. Here, we investigated how depression and sleep disturbance may jointly influence the risk of diabetes and the effects of sex on these influences. Methods: Using the data of 21,229 participants from the 2018 National Health Interview Survey, we performed multivariate logistic regression with diabetes diagnosis as the dependent variable, sex, self-reported frequency of weekly depression and nightly sleep duration, and their interactions with sex as independent variables, and age, race, income, body mass index and physical activity as covariates. We employed Bayesian and Akaike Information criteria to identify the best model, evaluated the accuracy of the model in predicting diabetes using receiver operating characteristic analysis, and computed the odds ratios of these risk factors. Results: In the two best models, depression frequency and sleep hours interact with sex in determining the diagnosis of diabetes, with higher depression frequency and nightly duration of sleep longer or shorter than 7 to 8 hours associated with higher likelihood of diabetes. The two models both predicted diabetes at an accuracy (area under the receiver operating characteristic curve) of 0.86. Further, these effects were stronger in men than in women at each depression and sleep level. Conclusions: Depression and sleep inter-relatedly rather than independently contributes to diabetes. Depression and sleep hours associate with diabetes more significantly in men than in women. The current findings indicate a sex-dependent relationship between depression, sleep disturbance and diabetes risk and add to a growing body of evidence linking mental and physical health.

Evaluating the Beijing Version of Montreal Cognitive Assessment for Identification of Cognitive Impairment in Monolingual Chinese American Older Adults.

Objective: This study aims to evaluate the performance of a Chinese version of the Montreal Cognitive Assessment (MoCA) as a screener to detect mild cognitive impairment (MCI) and dementia from normal cognition in the monolingual Chinese-speaking immigrant population. Method: A cohort of 176 Chinese-speaking older adults from the National Alzheimer's Coordinating Center Uniform Data Set is used for analysis. We explore the impact of demographic variables on MoCA performance and calculate the optimal cutoffs for the detection of MCI and dementia from normal cognition with appropriate demographic adjustment. Results: MoCA performance is predicted by age and education independent of clinical diagnoses, but not by sex, years of living in the U.S., or primary Chinese dialect spoken (i.e., Mandarin vs. Cantonese). With adjustment and stratification for education and age, we identify optimal cutoff scores to detect MCI and dementia, respectively, in this population. These optimal cutoff scores are different from the established scores for non-Chinese-speaking populations residing in the U.S. Conclusions: Our findings suggest that the Chinese version of MoCA is a valid screener to detect cognitive decline in older Chinese-speaking immigrants in the U.S. They also highlight the need for population-based cutoff scores with appropriate considerations for demographic variables.

The 32-Item Multilingual Naming Test: Cultural and Linguistic Biases in Monolingual Chinese-Speaking Older Adults.

OBJECTIVES: This study describes the performance of the Multilingual Naming Test (MINT) by Chinese American older adults who are monolingual Chinese speakers. An attempt was also made to identify items that could introduce bias and warrant attention in future investigation. METHODS: The MINT was administered to 67 monolingual Chinese older adults as part of the standard dementia evaluation at the Alzheimer's Disease Research Center (ADRC) at the Icahn School of Medicine at Mount Sinai (ISMMS), New York, USA. A diagnosis of normal cognition (n = 38), mild cognitive impairment (n = 12), and dementia (n = 17) was assigned to all participants at clinical consensus conferences using criterion sheets developed at the ADRC at ISMMS. RESULTS: MINT scores were negatively correlated with age and positively correlated with education, showing sensitivity to demographic factors. One item, butterfly, showed no variations in responses across diagnostic groups. Inclusion of responses from different regions of China changed the answers from "incorrect" to "correct" on 20 items. The last five items, porthole, anvil, mortar, pestle, and axle, yielded a high nonresponse rate, with more than 70% of participants responding with "I don't know." Four items, funnel, witch, seesaw, and wig, were not ordered with respect to item difficulty in the Chinese language. Two items, gauge and witch, were identified as culturally biased for the monolingual group. CONCLUSIONS: Our study highlights the cultural and linguistic differences that might influence the test performance. Future studies are needed to revise the MINT using more universally recognized items of similar word frequency across different cultural and linguistic groups.

Smartphone ownership and usage in Chinese- and English-speaking older adults.

BACKGROUND: Data collection by smartphone is becoming more widespread in healthcare research. Previous studies reported racial/ethnical differences in the use of digital health technology. However, cross-language group comparison (Chinese- and English-speaking older adults) were not performed in these studies. This project will expand to smartphone technology use in diverse older populations with a focus on Chinese American older adults who are monolingual Chinese-speakers. METHOD: The Alzheimer's Disease Research Center (ADRC) at Icahn School of Medicine at Mount Sinai (ISMMS) evaluates diverse older populations using National Alzheimer's Coordinating Center's Uniform Data Set (NACC UDS). The UDS has different language versions, including English and Chinese. The evaluation includes a medical examination, cognitive assessments, and a research blood draw. Smartphone ownership and usage were captured using a local questionnaire developed by our ADRC. The questionnaire, available in English and Chinese, was administered by our ADRC coordinators during the COVID-19 pandemic. Multivariate analysis of variance (MANOVA) was used to examine differences in technology ownership and usages between the two language groups, while controlling for age, gender, education, and cognitive status (measured by Clinical Dementia Rating). RESULT: 33 Chinese- and 117 English-speaking older adults who received a diagnosis of normal cognition or mild cognitive impairment at consensus were included in the data analysis. Results reveal a high prevalence of smartphone ownership in our Chinese- (100%) and English-speaking older participants (86.3%). Participants in both language groups use mobile technology for a wide range of purposes, such as getting news and other information (Chinese=90.9%; English=87.2%), sending/receiving text (Chinese=97.0%; English=96.6%), watching videos/TV shows (Chinese=78.8%; English=69.2%), and taking classes (Chinese=57.5%; English=57.3%). However, Chinese-speaking older adults were less likely than English-speaking older adults to use mobile technology to post their own reviews or comments online (Chinese=9.1%; English=39.3%, p=0.001), download or purchase an app (Chinese=21.2%; English=70.9%, p<0.001), track health/ fitness via apps/website (Chinese=12.1%; English=47.9%, p<0.001) and manage/receive medical care (Chinese=15.2%; English=67.5%, p<0.001). CONCLUSION: Our findings highlight potential barriers to smartphone usage in Chinese American older adults with limited English proficiency. The results have implications for how smartphone technology can be used in clinical practice and aging research.

Adapting Alzheimer Disease and Related Dementias Clinical Research Evaluations in the Age of COVID-19.

In March 2020, the novel coronavirus (COVID-19) became a global pandemic that would cause most in-person visits for clinical studies to be put on pause. Coupled with protective stay at home guidelines, clinical research at the Icahn School of Medicine at Mount Sinai Alzheimer's Disease Research Center (ISMMS ADRC) needed to quickly adapt to remain operational and maintain our cohort of research participants. Data collected by the ISMMS ADRC as well as from other National Institute on Aging (NIA) Alzheimer Disease centers, follows the guidance of the National Alzheimer Coordinating Center (NACC). However, at the start of this pandemic, NACC had no alternative data collection mechanisms that could accommodate these safety guidelines. To stay in touch with our cohort and to ensure continued data collection under different stages of quarantine, the ISMMS ADRC redeployed their work force to continue their observational study via telehealth assessment. On the basis of this experience and that of other centers, NACC was able to create a data collection process to accommodate remote assessment in mid-August. Here we review our experience in filling the gap during this period of isolation and describe the adaptations for clinical research, which informed the national dialog for conducting dementia research in the age of COVID-19 and beyond.

Design Considerations for Mobile Health Applications Targeting Older Adults.

Mobile technologies are becoming ubiquitous in the world, changing the way we communicate and provide patient care and services. Some of the most compelling benefits of mobile technologies are in the areas of disease prevention, health management, and care delivery. For all the advances that are occurring in mobile health, its full potential for older adults is only starting to emerge. Yet, existing mobile health applications have design flaws that may limit usability by older adults. The aim of this paper is to review barriers and identify knowledge gaps where more research is needed to improve the accessibility of mobile health use in aging populations. The same observations might apply to those who are not elderly, including individuals suffering from severe mental or medical illnesses.

Exploiting Rules to Enhance Machine Learning in Extracting Information From Multi-Institutional Prostate Pathology Reports.

PURPOSE: Literature on clinical note mining has highlighted the superiority of machine learning (ML) over hand-crafted rules. Nevertheless, most studies assume the availability of large training sets, which is rarely the case. For this reason, in the clinical setting, rules are still common. We suggest 2 methods to leverage the knowledge encoded in pre-existing rules to inform ML decisions and obtain high performance, even with scarce annotations. METHODS: We collected 501 prostate pathology reports from 6 American hospitals. Reports were split into 2,711 core segments, annotated with 20 attributes describing the histology, grade, extension, and location of tumors. The data set was split by institutions to generate a cross-institutional evaluation setting. We assessed 4 systems, namely a rule-based approach, an ML model, and 2 hybrid systems integrating the previous methods: a Rule as Feature model and a Classifier Confidence model. Several ML algorithms were tested, including logistic regression (LR), support vector machine (SVM), and eXtreme gradient boosting (XGB). RESULTS: When training on data from a single institution, LR lags behind the rules by 3.5% (F1 score: 92.2% v 95.7%). Hybrid models, instead, obtain competitive results, with Classifier Confidence outperforming the rules by +0.5% (96.2%). When a larger amount of data from multiple institutions is used, LR improves by +1.5% over the rules (97.2%), whereas hybrid systems obtain +2.2% for Rule as Feature (97.7%) and +2.6% for Classifier Confidence (98.3%). Replacing LR with SVM or XGB yielded similar performance gains. CONCLUSION: We developed methods to use pre-existing handcrafted rules to inform ML algorithms. These hybrid systems obtain better performance than either rules or ML models alone, even when training data are limited.

Gray matter volumetric correlates of behavioral activation and inhibition system traits in children: An exploratory voxel-based morphometry study of the ABCD project data.

Approach and avoidance represent two fundamental behavioral traits that develop early in life. Previous studies have examined the neural correlates of approach and avoidance traits in adults and adolescents. Here, using the data set of the Adolescent Brain Cognition Development project, we investigated the structural cerebral bases of behavioral activation system (BAS) and behavioral inhibition system (BIS) in children. We employed voxel-based morphometry to examine how gray matter volumes (GMV) related specifically to BAS and BIS traits in 11,542 children (5491 girls, age 9-10 years) with 648 and 2697 identified as monozygotic twins (MZ) and dizygotic twins/siblings (DZ), respectively. After accounting for the BIS score, higher BAS scores (residuals) were positively correlated with the GMV of the ventral striatum (VS), and the correlation was stronger in MZ than in DZ and unrelated children, with a heritability (h2) of 0.8463. Higher BAS scores were negatively correlated with the GMV of bilateral visual, lateral orbitofrontal, temporal, and inferior frontal cortex, as well as the precuneus. Higher BIS (after accounting for BAS) scores were negatively correlated with the GMVs of the ventral caudate and bilateral putamen/pallidum, hypothalamus, and right anterior insula, and the correlation was stronger in MZ than in DZ and unrelated children, with a heritability of 0.8848. A cluster in the VS showed positive and negative correlation with the BAS and BIS scores, respectively. These findings suggest shared and distinct cerebral volumetric bases of the BAS and BIS traits in children. Whereas both traits have a strong genetic basis, the BAS relative to BIS appears to be more amenable to environmental influences. These findings add to the literature of developmental neuroscience and may help identify genetic risk factors of externalizing and internalizing psychopathology.

Incidental breast carcinoma: incidence, management, and outcomes in 4804 bilateral reduction mammoplasties.

INTRODUCTION: Bilateral reduction mammoplasty is one of the most common plastic surgery procedures performed in the U.S. This study examines the incidence, management, and prognosis of incidental breast cancer identified in reduction specimens from a large cohort of reduction mammoplasty patients. METHODS: Breast pathology reports were retrospectively reviewed for evidence of incidental cancers in bilateral reduction mammoplasty specimens from five institutions between 1990 and 2017. RESULTS: A total of 4804 women met the inclusion criteria of this study; incidental cancer was identified in 45 breasts of 39 (0.8%) patients. Six patients (15%) had bilateral cancer. Overall, the maximum diagnosis by breast was 16 invasive cancers and 29 ductal carcinomas in situs. Thirty-three patients had unilateral cancer, 15 (45.5%) of which had high-risk lesions in the contralateral breast. Twenty-one patients underwent mastectomy (12 bilateral and nine unilateral), residual cancer was found in 10 in 25 (40%) therapeutic mastectomies. Seven patients did not undergo mastectomy received breast radiation. The median follow-up was 92 months. No local recurrences were observed in the patients undergoing mastectomy or radiation. Three of 11 (27%) patients who did not undergo mastectomy or radiation developed a local recurrence. The overall survival rate was 87.2% and disease-free survival was 82.1%. CONCLUSIONS: Patients undergoing reduction mammoplasty for macromastia have a small but definite risk of incidental breast cancer. The high rate of bilateral cancer, contralateral high-risk lesions, and residual disease at mastectomy mandates thorough pathologic evaluation and careful follow-up of these patients. Mastectomy or breast radiation is recommended for local control given the high likelihood of local recurrence without either.

Do Neural Information Extraction Algorithms Generalize Across Institutions?

PURPOSE: Natural language processing (NLP) techniques have been adopted to reduce the curation costs of electronic health records. However, studies have questioned whether such techniques can be applied to data from previously unseen institutions. We investigated the performance of a common neural NLP algorithm on data from both known and heldout (ie, institutions whose data were withheld from the training set and only used for testing) hospitals. We also explored how diversity in the training data affects the system's generalization ability. METHODS: We collected 24,881 breast pathology reports from seven hospitals and manually annotated them with nine key attributes that describe types of atypia and cancer. We trained a convolutional neural network (CNN) on annotations from either only one (CNN1), only two (CNN2), or only four (CNN4) hospitals. The trained systems were tested on data from five organizations, including both known and heldout ones. For every setting, we provide the accuracy scores as well as the learning curves that show how much data are necessary to achieve good performance and generalizability. RESULTS: The system achieved a cross-institutional accuracy of 93.87% when trained on reports from only one hospital (CNN1). Performance improved to 95.7% and 96%, respectively, when the system was trained on reports from two (CNN2) and four (CNN4) hospitals. The introduction of diversity during training did not lead to improvements on the known institutions, but it boosted performance on the heldout institutions. When tested on reports from heldout hospitals, CNN4 outperformed CNN1 and CNN2 by 2.13% and 0.3%, respectively. CONCLUSION: Real-world scenarios require that neural NLP approaches scale to data from previously unseen institutions. We show that a common neural NLP algorithm for information extraction can achieve this goal, especially when diverse data are used during training.