The Demographic Analyses of Undiagnosed and Misdiagnosed Cancer Cases via Autopsy Data

Cancer is one of the most common causes of death. Recent increases in undiagnosed and misdiagnosed cancer cases at autopsies suggests that the presence of cancer is more prevalent in the general population than previously thought. Such cases may be different in certain populations with regard to key demographic characteristics (age, race, gender, etc.). Therefore, this study aimed to identify trends in these undiagnosed cases of different cancer types. The data suggest that cancers of the lung, gastrointestinal tract, and prostate gland were frequently undiagnosed/misdiagnosed, while cancers of the breast and brain are rarely missed. The data also show that the presence of undetected prostate cancer is likely not different, to a significant degree, in younger versus older age groups. This indicates that cancer possibly manifests early in human life but remains undetected for several decades. However, further research is required to confirm this hypothesis. The data suggests that the prevalence of undetected cancer is highest in African-Americans compared to other races/ethnicities such as European and Asian. With regard to gender, the prevalence of undetected cancer appears to be higher in men than women. To conclusively validate these findings, further research is needed including concurrent and prospective analyses on live cases.

Reference Range of Complete Blood Count in Healthy Term Newborns 1 Week after Birth

BACKGROUND: Determination of the complete blood count (CBC) and reticulocyte reference range helps diagnose a disease related to changes in erythrocyte indices, white blood count, platelets, and reticulocytes, especially in newborns. AIM: The aim study is to establish a reference range for CBC and reticulocyte in healthy term newborns 1 week after birth. MATERIAL AND METHODS: The study method is prospective analyses of CBC and reticulocyte in term newborns within 1 week after birth. Inclusion criteria are term newborn (gestational age 37–42 weeks) with good tone, breathing, or crying immediately, do not have resuscitation, and the birth weight is ≥2500 g. RESULTS: Two hundred and seventy-seven term newborns met the inclusion criteria. There were 145 (52.35%) male infants and 132 (47.65%) female infants. The reference range of newborns for hemoglobin (Hb) at P2.5–P97.5, P3–P97, P5–P95, and mean ± 2 standard deviation (SD) was 11.70–19.60 g/dL, 11.90–19.57 g/dL, 12.20–19.20 g/dL, and 11.35–19.63 g/dL, respectively. In addition, reference range of male newborns for Hb at P2.5–P97.5, P3–P97, P5–P95, and mean ± 2SD was 12.20–20.14 g/dL, 12.28–19.91 g/dL, 12.63–19.38 g/dL, and 11.47–20.15 g/dL, respectively. The reference range of female newborns for Hb at P2.5–P97.5, P3–P97, P5–P95, and mean ± 2 SD was 11.37–19.20 g/dL, 11.50–19.20 g/dL, 11.80–19.20 g/dL, and 11.37–18.93 g/dL, respectively. CONCLUSION: The reference range of CBC and reticulocyte for healthy term newborns, male newborns, and female newborns in this study can be used as a benchmark.

R|S Atlas: Identifying existing cohort study data resources to accelerate epidemiological research on the influence of religion and spirituality on human health

ObjectiveMany studies have documented significant associations between religion and spirituality (R/S) and health, but relatively few prospective analyses exist that can support causal inferences. To date, there has been no systematic analysis of R/S survey items collected in US cohort studies. We conducted a systematic content analysis of all surveys ever fielded in 20 diverse US cohort studies funded by the National Institutes of Health (NIH) to identify all R/S-related items collected from each cohort’s baseline survey through 2014.DesignAn R|S Ontology was developed from our systematic content analysis to categorise all R/S survey items identified into key conceptual categories. A systematic literature review was completed for each R/S item to identify any cohort publications involving these items through 2018.ResultsOur content analysis identified 319 R/S survey items, reflecting 213 unique R/S constructs and 50 R|S Ontology categories. 193 of the 319 extant R/S survey items had been analysed in at least one published paper. Using these data, we created the R|S Atlas (https://atlas.mgh.harvard.edu/), a publicly available, online relational database that allows investigators to identify R/S survey items that have been collected by US cohorts, and to further refine searches by other key data available in cohorts that may be necessary for a given study (eg, race/ethnicity, availability of DNA or geocoded data).ConclusionsR|S Atlas not only allows researchers to identify available sources of R/S data in cohort studies but will also assist in identifying novel research questions that have yet to be explored within the context of US cohort studies.

646Coffee, Brain Volume and Risk of Dementia and Stroke

Background Coffee is a highly popular beverage worldwide, containing caffeine which is a central nervous system stimulant. The aim was to examine whether habitual coffee consumption is associated with differences in brain volumes or the risk odds of dementia or stroke. Methods Prospective analyses of habitual coffee consumption were conducted in 398,646 participants (age 37-73 years) within the UK Biobank, including 17,702 participants with volumetric MRI information. We examined associations between coffee consumption and brain volume using covariate adjusted linear regression, and with odds of dementia and stroke using logistic regression. All participants were free of dementia and stroke at baseline. We obtained 4,333 incident dementia and 6,181 incident stroke cases. Results There were inverse linear associations between coffee consumption and total brain (β per cup -1·42, p = 1·4x10-8), grey matter (-0·92, p = 5·2x10-10), white matter (-0·50, p = 0·002) and hippocampal volumes (-0·01, p = 0·009), but no evidence to support associations with white matter hyperintensity volume (-0·01, p = 0·72). After full covariate adjustment, consumption of > 6 cups/day of coffee was associated with 53% higher odds of dementia compared to consumption of 1-2 cups/day (OR 1.53, 95% CI 1.28, 1.83), with less evidence for an association with stroke (OR 1.17, 95% CI 1.00, 1.37, p = 0.055). Conclusions High coffee consumption was associated with smaller total brain volumes and increased odds of dementia. Key messages The findings suggest caution at higher levels of coffee consumption, however further studies are required to establish causality, and to explore the clinical relevance of brain volume changes.

1484Selection bias in COVID-19 research: Prospective analyses of two UK cohort studies

Background Non-random sampling could bias estimates of association in observational studies but the extent to which this occurs in studies of SARS-CoV-2 infection/COVID-19 severity is not well established. Methods Using ALSPAC and UK Biobank we investigated pre-pandemic predictors of selection (i.e. having data on SARS-CoV-2 infection and COVID-19 severity from self-report and/or health record linkage). We conducted empirical analyses and simulations to explore the potential presence, direction and magnitude of bias due to selection when estimating the association of BMI with SARS-CoV-2 infection and COVID-19 severity. Results A broad range of characteristics related to selection in both cohorts, sometimes in opposite directions. We found bias in all simulated scenarios, mostly of small magnitude. Both the direction and magnitude of bias was influenced by the presence of an effect of BMI on SARS-CoV-2 infection and COVID-19 severity and the control group definition used (e.g. assuming no effect of BMI on SARS-CoV-2 infection our main simulation showed bias equivalent to an estimated odds ratio of 0.99 when using non-infected controls but 1.16 when using controls combining non-infected and non-assessed). Conclusions Despite small amounts of bias in most scenarios, a control group definition including those non-assessed (e.g. non-tested) can induce more bias. In large samples such as UK Biobank the statistical power means incorrect conclusions could be made. Key messages Observational studies estimating associations of factors with SARS-CoV-2 or COVID-19 may be biased due to non-random selection into the analytic sample.

Attribution Errors by People and Intelligent Machines

Objective To explore the ramifications of attribution errors (AEs), initially in the context of vehicle collisions and then to extend this understanding into the broader and diverse realms of all forms of human–machine interaction. Background This work focuses upon a particular topic that John Senders was examining at the time of his death. He was using the lens of attribution, and its associated errors, to seek to further understand and explore dyadic forms of driver collision. Method We evaluated the utility of the set of Senders’ final observations on conjoint AE in two-vehicle collisions. We extended this evaluation to errors of attribution generally, as applicable to all human–human, human–technology, and prospectively technology–technology interactions. Results As with Senders and his many other contributions, we find evident value in this perspective on how humans react to each other and how they react to emerging forms of technology, such as autonomous systems. We illustrate this value through contemporary examples and prospective analyses. Applications The comprehension and mitigation of AEs can help improve all interactions between people, between intelligent machines and between humans and the machines they work with.

The Demand–Control Model as a Predictor of Depressive Symptoms—Interaction and Differential Subscale Effects: Prospective Analyses of 2212 German Employees

Testing assumptions of the widely used demand–control (DC) model in occupational psychosocial epidemiology, we investigated (a) interaction, i.e., whether the combined effect of low job control and high psychological demands on depressive symptoms was stronger than the sum of their single effects (i.e., superadditivity) and (b) whether subscales of psychological demands and job control had similar associations with depressive symptoms. Logistic longitudinal regression analyses of the 5-year cohort of the German Study of Mental Health at Work (S-MGA) 2011/12–2017 of 2212 employees were conducted. The observed combined effect of low job control and high psychological demands on depressive symptoms did not indicate interaction (RERI = −0.26, 95% CI = −0.91; 0.40). When dichotomizing subscales at the median, differential effects of subscales were not found. When dividing subscales into categories based on value ranges, differential effects for job control subscales (namely, decision authority and skill discretion) were found (p = 0.04). This study does not support all assumptions of the DC model: (1) it corroborates previous studies not finding an interaction of psychological demands and job control; and (2) signs of differential subscale effects were found regarding job control. Too few prospective studies have been carried out regarding differential subscale effects.