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bioRxiv2018

Validation of known risk factors associated with carpal tunnel syndrome: A retrospective nationwide 11-year population-based cohort study in South Korea

Key PointsO_ST_ABSQuestionC_ST_ABSWhat is the relationship between the previously known risk factors and occurrence of carpal tunnel syndrome (CTS)?\n\nFindingsIn this retrospective population-based cohort study that included 512,942 participants sampled from the Korean National Health Insurance System database, we determined the following known risk factors were related to the occurrence of CTS: the age of 40s, female, being overweight, diabetes, rheumatoid arthritis, gout, and Raynauds syndrome. However, ESRD, hypothyroidism and smoking were not correlated with CTS occurrence.\n\nImplicationsWe identified the age of 40s, female, overweight, diabetes, rheumatoid arthritis, gout, and Raynauds syndrome as risk factors for the occurrence of CTS.\n\nAbstractO_ST_ABSImportanceC_ST_ABSThere have been few large-scale studies that have included a risk factor analysis for CTS. No prior study has investigated and validated the relationship between the occurrence of CTS and known risk factors using nationwide health care database.\n\nObjectiveTo confirm the actual risk factors for CTS out of various known risk factors\n\nDesignWe conducted this study using a retrospective cohort model based on the combined two databases of the Korean National Health Insurance System; the national periodic health screening program database from 2002-2003 and health insurance database of reimbursement claims from 2003 through 2013.\n\nSettingA population-based retrospective cohort study.\n\nParticipantsFirst, we randomly sampled 514,795 patients who represented 10% of the 5,147,950 people who took part in periodic health screenings in 2002-2003. Existing CTS patients were excluded from this group. Therefore, this study finally included 512,942 participants and followed up their medical records from 2003-2013.\n\nMain Outcomes and MeasuresDesired outcomes were the incidence rate of CTS in patients with various risk factors and the hazard ratios of risk factors affecting the diseases occurrence.\n\nResultsThe incidence of CTS was highest in patients in the age of 40s, in the moderate obesity group, in females, and in patients with diabetes mellitus (DM). The hazard ratio analysis revealed that the following risk factors were strongly related to the occurrence of CTS: age of 40s, female, obesity, DM, rheumatoid arthritis, gout, and Raynauds syndrome. However, ESRD, hypothyroidism and smoking were not correlated with CTS occurrence.\n\nConclusions and RelevanceIn our large-scale cohort study, risk factors such as being in ones 40s, obesity, being female, suffering from DM, and rheumatoid arthritis were reaffirmed as those of CTS occurrence.

epidemiology↗

bioRxiv2018

Risk factors associated with Parkinson’s disease: An 11-year population-based South Korean study

ObjectiveTo validate various known risk factors of Parkinsonism and to establish basic information to formulate public health policy by using a 10-year follow-up cohort model.\n\nMethodsThis population based nation-wide study was performed using the National Health Insurance Database of reimbursement claims of the Health Insurance Review and Assessment Service of South Korea data on regular health check-ups in 2003 and 2004, with 10 years follow-up.\n\nResultsWe identified 7,746 patients with Parkinsonism. Old age, hypertension, diabetes, depression, anxiety, taking statin medication, high body mass index, non-smoking, non-alcohol drinking, and low socioeconomic status were each associated with an increase in the risk of Parkinsonism (fully adjusted Cox proportional hazards model: hazard ratio (HR) 1.259, 95% confidence interval (CI) 1.194-1.328 for hypertension, HR 1.255, 95% CI 1.186-1.329 for diabetes, HR 1.554, 95% CI 1.664-1.965 for depression, HR 1.808, 95% CI 1.462-1.652 for anxiety, and HR 1.157, 95% CI 1.072-1.250 for taking statin medication).\n\nConclusionsIn our study, old age, depression, anxiety, and a non-smoker status were found to be risk factors of Parkinsonism, in agreement with previous studies. However, sex, hypertension, diabetes, taking statin medication, non-drinking of Alcohol, and lower socioeconomic status have not been described as risk factors in previous studies and need further verification in future studies.

epidemiology↗

bioRxiv2018

Data mining and classification of polycystic ovaries in pelvic ultrasound reports

ObjectivesTo develop and evaluate the performance of a rules-based classifier and a gradient boosted tree model for automatic feature extraction and classification of polycystic ovary morphology (PCOM) in pelvic ultrasounds\n\nMethodsPelvic ultrasound reports from patients at Boston Medical Center between October 1, 2003 and December 12, 2016 were included for analysis, which resulted in 39,093 ultrasound reports from 25,535 unique women. Following the 2003 Rotterdam Consensus Criteria for polycystic ovary syndrome, 2000 randomly selected ultrasounds were manually labeled for PCOM status as present, absent, or unidentifiable. Half of the labeled data was used as a training set, and the other half was used as a test set.\n\nResultsOn the test set of 1000 random US reports, the accuracy of rules-based classifier (RBC) was 97.6% (95% CI: 96.5%, 98.5%) and 96.1% (94.7%, 97.2%) for the gradient boosted tree model (GBT). Both models were more adept at identifying non-PCOM ultrasounds than either unidentifiable or PCOM ultrasounds. The two classifiers estimated prevalence of PCOM within our populations ultrasounds to be about 44%, unidentifiable 32%, and PCOM 24%.\n\nConclusionsAlthough accuracy measured on the test set and inter-rater agreement between the two classifiers (Cohens Kappa = 0.988) was high, a major limitation of our approach is that it uses the ultrasound report text as a proxy and does not directly count follicles from the ultrasound images themselves.

epidemiology↗

bioRxiv2018

Estimating sleep parameters using an accelerometer without sleep diary

Wrist worn raw-data accelerometers are used increasingly in large scale population research. We examined whether sleep parameters can be estimated from these data in the absence of sleep diaries. Our heuristic algorithm uses the variance in estimated z-axis angle and makes basic assumptions about sleep interruptions. Detected sleep period time window (SPT-window), was compared against sleep diary in 3752 participants (range=60-82years) and polysomnography in sleep clinic patients (N=28) and in healthy good sleepers (N=22). The SPT-window derived from the algorithm was 10.9 and 2.9 minutes longer compared with sleep diary in men and women, respectively. Mean C-statistic to detect the SPT-window compared to polysomnography was 0.86 and 0.83 in clinic-based and healthy sleepers, respectively. We demonstrated the accuracy of our algorithm to detect the SPT-window. The value of this algorithm lies in studies such as UK Biobank where a sleep diary was not used.

epidemiology↗

bioRxiv2018

Use of an individual-based model of pneumococcal carriage for planning a randomized trial of a vaccine

For encapsulated bacteria such as Streptococcus pneumoniae, asymptomatic carriage is more common and longer in duration than disease, and hence is often a more convenient endpoint for clinical trials of vaccines against these bacteria. However, using a carriage endpoint entails specific challenges. Carriage is almost always measured as prevalence, whereas the vaccine may act by reducing incidence or duration. Thus, to determine sample size requirements, its impact on prevalence must first be estimated. The relationship between incidence and prevalence (or duration and prevalence) is convex, saturating at 100% prevalence. For this reason, the proportional effect of a vaccine on prevalence is typically less than its proportional effect on incidence or duration. This relationship is further complicated in the presence of multiple pathogen strains. In addition, host immunity to carriage accumulates rapidly with frequent exposures in early years of life, creating potentially complex interactions with the vaccines effect. We conducted a simulation study to predict the impact of an inactivated whole cell pneumococcal vaccine--believed to reduce carriage duration--on carriage prevalence in different age groups and trial settings. We used an individual-based model of pneumococcal carriage that incorporates relevant immunological processes, both vaccine-induced and naturally acquired. Our simulations showed that for a wide range of vaccine efficacies, sampling time and age at vaccination are important determinants of sample size. There is a window of favorable sampling times during which the required sample size is relatively low, and this window is prolonged with a younger age at vaccination, and in a trial setting with lower transmission intensity. These results illustrate the ability of simulation studies to inform the planning of vaccine trials with carriage endpoints, and the methods we present here can be applied to trials evaluating other pneumococcal vaccine candidates or comparing alternative dosing schedules for the existing conjugate vaccines.\n\nAuthor SummaryStreptococcus pneumoniae, a bacterium carried in the nasopharynx of many healthy people, is also a leading cause of bacterial pneumonia, sepsis, and ear infections in children aged five years and younger. Vaccines targeting select strains of S. pneumoniae have been effective, and the development of new vaccines, particularly those that target all strains, can further lower disease burden. For clinical trials of these vaccines, the number of study participants needed depends on the expected effect of the vaccine on a conveniently measured outcome: asymptomatic carriage. The most economical way to test a vaccine for its effect on carriage is by measuring prevalence at a specific time, and comparing vaccinated to unvaccinated participants. The relationship between incidence (or duration) and prevalence is complex, and changes with time as children develop natural immunity. We explored this relationship using a mathematical model. Given a vaccine efficacy, our computer simulations predict that fewer study participants are needed if they are vaccinated at a younger age, taken from a population with intermediate levels of transmission, and sampled for carriage at a certain time window: 9 to 18 months after vaccination. Our study illustrates how simulation studies can help plan more efficient vaccine trials.

epidemiology↗

bioRxiv2018

Choices in Vaccine Trial Design for Epidemics of Emerging Infections

The 2014-2016 Ebola epidemic highlighted the lack of consensus on the design of trials for investigational vaccine products in an emergency setting. With the advent of the ring vaccination strategy, it also underscored that the range of design options is evolving according to scientific need and creativity. Ideally, principles and protocols will be drawn up in advance, facilitating expediency and trust, for rapid deployment early in an epidemic. Here, we attempt a summary of the scientific, ethical and feasibility considerations relevant to different trial designs. We focus on four elements of design choices which, in our view, are most fundamental to designing an experimental vaccine trial and for which the most distinctive issues arise in the setting of an emerging infectious disease for which no proven vaccines exist: 1) randomization unit, 2) trial population, 3) comparator intervention and 4) trial implementation. Likewise, we focus on three of several ethical considerations in clinical research, namely the trials social and scientific value, its risk-benefit profile and its participant selection. A catalogue of possible designs to guide trial design choices is offered, along with a systematic evaluation of the benefits and drawbacks of each in given contexts.

epidemiology↗

bioRxiv2018

Estimation of age-specific susceptibility to influenza in the Netherlands and its relation to loss of CD8+ T-cell memory

The magnitude of influenza epidemics is largely determined by the number of susceptible individuals at the start of the influenza season. Susceptibility, in turn, is influenced by antigenic drift. The evolution of influenzas B-cell epitopes has been charted thoroughly, and only recently evidence for T-cell driven evolution is accumulating. We investigate the relation between susceptibility to influenza, and antigenic drift at CD8+ T-cell epitopes over a 45-year timespan. We estimate age-specific susceptibility with data reported by general practitioners, using a disease-transmission model in a Bayesian framework. We find large variation in susceptibility, both between seasons and age classes. Although it is often assumed that antigenic drift drives the variation in susceptibility, we do not find evidence for a relation between drift and susceptibility in our data. This suggests that other factors determining the variation in susceptibility play a dominating role, or that complex influenza-infection histories obscure any direct effects.\n\nPreface to this bioR{chi}iv pre-printWe are currently in the process of making this manuscript ready for re-submission, and are resolving some issues brought forward by our referees. Most importantly, we aim to better incorporate the co-circulation of the various influenza A and B subtypes during the different seasons, both in the estimation of susceptibility and antigenic drift.

epidemiology↗

bioRxiv2018

Education can Reduce Health Disparities Related to Genetic Risk of Obesity: Evidence from a British Reform

This paper investigates whether genetic makeup moderates the effects of education on health. Low statistical power and endogenous measures of environment have been obstacles to the credible estimation of such gene-by-environment interactions. We overcome these obstacles by combining a natural experiment that generated variation in secondary education with polygenic scores for a quarter million individuals. The additional schooling affected body size, lung function, and blood pressure in middle age. The improvements in body size and lung function were larger for individuals with high genetic predisposition to obesity. As a result, education reduced the gap in unhealthy body size between those with high and low genetic risk of obesity from 20 to 6 percentage points.

epidemiology↗

bioRxiv2018

The upstrap

Bootstrap [2] is a landmark method for quantifying variability. It uses sampling with replacement with a sample size equal to that of the original data. We propose the upstrap, which samples with replacement either more or fewer samples than the original sample size. We illustrate the upstrap by solving a hard, but common, sample size calculation problem.

epidemiology↗

bioRxiv2018

Segmenting accelerometer data from daily life with unsupervised machine learning

PurposeAccelerometers are increasingly used to obtain valuable descriptors of physical activity for health research. The cut-points approach to segment accelerometer data is widely used in physical activity research but requires resource expensive calibration studies and does not make it easy to explore the information that can be gained for a variety of raw data metrics. To address these limitations, we present a data-driven approach for segmenting and clustering the accelerometer data using unsupervised machine learning.\n\nMethodsThe data used came from five hundred fourteen-year-old participants from the Millennium cohort study who wore an accelerometer (GENEActiv) on their wrist on one weekday and one weekend day. A Hidden Semi-Markov Model (HSMM), configured to identify a maximum of ten behavioral states from five second averaged acceleration with and without addition of x, y, and z-angles, was used for segmenting and clustering of the data. A cut-points approach was used as comparison.\n\nResultsTime spent in behavioral states with or without angle metrics constituted eight and five principal components to reach 95% explained variance, respectively; in comparison four components were identified with the cut-points approach. In the HSMM with acceleration and angle as input, the distributions for acceleration in the states showed similar groupings as the cut-points categories, while more variety was seen in the distribution of angles.\n\nConclusionOur unsupervised classification approach learns a construct of human behavior based on the data it observes, without the need for resource expensive calibration studies, has the ability to combine multiple data metrics, and offers a higher dimensional description of physical behavior. States are interpretable from the distributions of observations and by their duration.

epidemiology↗

bioRxiv2018

Epigenome-wide association study of placental DNA methylation and maternal exposure to night shift work in the Rhode Island Child Health Study

ObjectivesCircadian disruption from environmental and occupational exposures can potentially impact health, including offspring health, through epigenetic alterations. Night shift workers experience circadian disruption, but little is known about how this exposure could influence the epigenome of the placenta, which is situated at the maternal-fetal interface. To investigate whether night shift work is associated with variations in DNA methylation patterns of placental tissue, we conducted an epigenome-wide association study (EWAS) of night shift work.\n\nMethodsCpG specific methylation genome-wide of placental tissue (measured with the Illumina 450K array) from participants (n=237) in the Rhode Island Child Health Study (RICHS) who did (n=53) and did not (n=184) report working the night shift was compared using robust linear modeling, adjusting for maternal age, pre-pregnancy smoking, infant sex, maternal adversity, and putative cell mixture.\n\nResultsNight shift work was associated with differential methylation in placental tissue, including CpG sites in the genes NAV1, SMPD1, TAPBP, CLEC16A, DIP2C, FAM172A, and PLEKHG6 (Bonferroni-adjusted p<0.05). CpG sites within NAV1, MXRA8, GABRG1, PRDM16, WNT5A, and FOXG1 exhibited the most hypomethylation, while CpG sites within TDO2, ADAMTSL3, DLX2, and SERPINA1 exhibited the most hypermethylation (BH q<0.10). PER1 was the only core circadian gene demonstrating differential methylation. Functional analysis indicated GO-terms associated with cell-cell adhesion.\n\nConclusionsNight shift work was associated with differential methylation of the placenta, which may have implications for fetal health and development. Additionally, neuron navigator 1 (NAV1) may play a role in the development of the human circadian system.\n\nWhat is already known about this subject?Night shift work and circadian disruption may play a role in the development and progression of many diseases. However, little is known about how circadian disruption impacts human fetal health and development.\n\nWhat are the new findings?Working the night shift is associated with altered placental methylation patterns, and particularly, neuron navigator 1 (NAV1) may play a role in the development of the human circadian system.\n\nHow might this impact on policy or clinical practice in the foreseeable future?Night shift work prior to or during pregnancy may alter the placental epigenome, which has implications for fetal health. Further studies are needed to evaluate night shift work as a possible risk factor for gestational diabetes and to evaluate the impact of circadian disruption on fetal health and development.

epidemiology↗

bioRxiv2018

A new paradigm for personalized cancer screening

A series of distinct histologic lesions precedes the onset of malignancy in many common cancers, yet early detection remains a major challenge. Many patients still experience late (stage IV) diagnoses and thus poor prognosis and limited options for therapeutic intervention. For cancers with known biomarkers of premalignant progression, optimized patient-specific screening protocols would minimize the risk of undetected progression to advanced stage disease. Here, we propose simple, cost-effective mathematical and statistical approaches to forecasting disease progression that could guide the personalization of optimal screening times for high-risk patients.

epidemiology↗

bioRxiv2018

The clinician impact and financial cost to the NHS of litigation over pregabalin: an economic impact analysis

ObjectivesFollowing litigation over pregabalins second-use medical patent for neuropathic pain NHS England were required by the court to instruct GPs to prescribe the branded form (Lyrica) for pain. Pfizers patent was found invalid in 2015; a ruling subject to ongoing appeals. If the Supreme Court appeal in February 2018 is unsuccessful, the NHS can reclaim excess prescribing costs. We set out to describe the variation in prescribing of pregabalin as branded Lyrica, geographically and over time; to determine how clinicians responded to the NHS England instruction to GPs; and to model excess costs to the NHS attributable to the legal judgments.\n\nSettingEnglish primary care\n\nParticipantsEnglish general practices\n\nPrimary and secondary outcome measuresVariation in prescribing of branded Lyrica across the country before and after the NHS England instruction, by practice and by Clinical Commissioning Group (CCG); excess prescribing costs.\n\nResultsThe proportion of pregabalin prescribed as Lyrica increased, from 0.3% over six months before the NHS England instruction (September 2014-February 2015) to 25.7% afterwards (April - September 2015). Although 70% of pregabalin is estimated to be for neuropathic pain, only 11.6% of practices prescribed Lyrica at this level; the median proportion prescribed as Lyrica was 8.8% (IQR 1.1-41.9%). If pregabalin had come entirely off patent in September 2015, and Pfizer had not appealed, we estimate the NHS would have spent {pound}502m less on pregabalin to July 2017.\n\nConclusionNHS England instructions to GPs regarding branded prescription of pregabalin were widely ignored, and have created much debate around clinical independence in prescribing. Protecting revenue from \"skinny labels\" will pose a challenge. If Pfizers final appeal on the patent is unsuccessful the NHS can seek reimbursement of excess pregabalin prescribing costs, potentially {pound}502m.

epidemiology↗

bioRxiv2018

Phylogenetic factorization of mammalian viruses complements trait-based analyses and guides surveillance efforts

Predicting which novel microorganisms may spill over from animals to humans has become a major priority in infectious disease biology. However, there are few tools to help assess the zoonotic potential of the enormous number of potential pathogens, the majority of which are undiscovered or unclassified and may be unlikely to infect or cause disease in humans. We adapt a new biological machine learning technique - phylofactorization - to partition viruses into clades based on their non-human host range and whether or not there exist evidence they have infected humans. Our cladistic analyses identify clades of viruses with common within-clade patterns - unusually high or low propensity for spillover. Phylofactorization by spillover yields many clades of viruses containing few to no representatives that have spilled over to humans, including the families Papillomaviridae and Herpesviridae, and the genus Parvovirus. Removal of these non-zoonotic clades from previous trait-based analyses changed the relative significance of traits determining spillover due to strong associations of traits with non-zoonotic clades. Phylofactorization by host breadth yielded clades with unusually high host breadth, including the family Togaviridae. We identify putative life-history traits differentiating clades host breadth and propensities for zoonosis, and discuss how these results can prioritize sequencing-based surveillance of emerging infectious diseases.

epidemiology↗

bioRxiv2018

The strong grip of childhood conditions in older Europeans

Among older Europeans grip strength has been found to be marked by a disadvantaged adulthood. Across the Channel, among older Britons gait speed as another measure of physical function has been found to be marked by disadvantaged childhood. Using the Survey of Health, Ageing, and Retirement in Europe (2004-2013), we studied whether childhood poverty led to Europeans aged 50 to 104 years having a weaker grip. We then drew their trajectories of repeatedly measured grip strength to discern a steeper decline among the childhood poor. Retrospective childhood poverty some four to nine decades in the past was treated as a latent construct following the above literature; attrition during repeated measurements is handled using inverse proportional to attrition weighting. The data showed the childhood poor to have a weaker grip for half a century in later life. However, they do not show a steeper decline. Most important, by contributing to levels of grip strength in later life, adult condition holds the potential to shape the strong and long arm of childhood condition. The results are another impetus to eliminate childhood poverty to ensure healthy ageing Europeans.

epidemiology↗

bioRxiv2018

Does a poor childhood associate with higher and steeper inflammation trajectories in the English Longitudinal Study of Ageing?

Inflammation has been implicated in many diseases in later life of older Britons. Moreover, health outcomes in later life have also been markedly affected by childhood poverty. But no study has established whether childhood poverty has the effect of upregulating inflammation throughout later life. Using the English Longitudinal Study of Ageing (2004 - 2013) life history information and longitudinal observations of C-reactive protein and fibrinogen as inflammatory biomarkers, we studied the association between childhood condition and trajectories of inflammation for people aged 50 to 97 years. Retrospective childhood poverty some four to eight decades in the past was treated as a latent construct; attrition in longitudinal observations is addressed using inverse proportional to attrition weighting. The analytis revealed significantly higher levels of both biomarkers throughout later life among those with a poor childhood, though there is no evidence of a steeper inflammation trajectory among them. We discussed possible epigenetic changes underlying this strong and long arm of childhood condition. The results suggest that eliminating child poverty can prove to be a wise investment with the prospect of a lifelong reward.

epidemiology↗

bioRxiv2018

Ability of known susceptibility SNPs to predict colorectal cancer risk for persons with and without a family history

BackgroundA number of single nucleotide polymorphisms (SNPs), which are common inherited genetic variants, have been identified that are associated with risk of colorectal cancer. The aim of this study was to determine the ability of these SNPs to estimate colorectal cancer (CRC) risk for persons with and without a family history of CRC, and the screening implications.\n\nMethodsWe estimated the association with CRC of a 45 SNP-based risk using 1,181 cases and 999 controls, and its correlation (r) with CRC risk predicted from detailed family history. We estimated the predicted change in the distribution across predefined risk categories, and implications for recommended age to commence screening, from adding SNP-based risk to family history.\n\nResultsThe inter-quintile risk ratio for colorectal cancer risk of the SNP-based risk was 2.46 (95% CI 1.91 - 3.11). SNP-based and family history-based risks were not correlated (r = 0.02). For persons with no first-degree relatives with CRC, recommended screening would commence 2 years earlier for women (4 years for men) in the highest quintile of SNP-based risk, and 12 years later for women (7 years for men) in the lowest quintile. For persons with two first-degree relatives with CRC, recommended screening would commence 15 years earlier for men and women in the highest quintile, and 8 years earlier for men and women in the lowest quintile.\n\nConclusionsRisk reclassification by 45 SNPs could inform targeted screening for CRC prevention, particularly in clinical genetics settings when mutations in high-risk genes cannot be identified.

epidemiology↗

bioRxiv2018

Citius, Fortius? Cohort, inflammation and trajectories of gait speed and grip strength in older Britons

Although the cost of long term care of physical disabilities is considerable, little is known about individual trajectories of physical function (measured by gait speed and grip strength) that preceded the process of disablement. Moreover, studies on trajectories of health function have often ignored cohort composition, precluding evidence of secular improvement. And few have explored the role of chronic inflammation on older peoples physical function trajectories. Using the English Longitudinal Study of Ageing 2004-2013 we derived trajectories of gait speed and grip strength of Britons aged [≥] 50 years and investigated the effect of inflammation. Then we drew trajectories for different cohorts to seek evidence of secular improvement. We uncovered a complex gradient of improvement in trajectories of physical function that depends on sex and maximum versus normal capacity. In conclusion, accounting for the cohort composition of older people can materially modify the future cost of long term care.

epidemiology↗