Implementation, evaluation and application of multiple imputation for missing data in longitudinal electronic health record research

Longitudinal electronic health records are a valuable resource for research because they contain information on many patients over long follow-up periods. Missing data commonly occur in these data because it was collected for clinical and not research purposes. Analysing data with missing values can potentially bias estimates and standard errors resulting in invalid inferences. Multiple imputation, commonly used in research to impute missing values, is increasingly regarded as the standard method for handling missing data in medical research because of its practicality and flexibility under the assumption the data is missing at random (MAR). Until now, few imputation approaches are sufficiently flexible to account for the longitudinal and dynamic structure of electronic health records. However, the two-fold fully conditional specification (FCS) algorithm was proposed to impute missing values in longitudinal data, but this methods was not currently validated in the complex setting of longitudinal electronic health records. I propose to adapt, evaluate and implement the two-fold FCS algorithm to impute missing data from large primary care database. To achieve this, first I investigate the extent and patterns of missing data in a longitudinal clinical database for health indicators associated with cardiovascular disease risk to determine if the MAR assumption is plausible. Additionally, I develop methods to identify and remove outliers, which can potentially bias imputations, from data with repeated measurements before imputation. Next, I adapt and develop the two-fold FCS multiple imputation algorithm to impute missing values in longitudinal clinical data for health indicators associated with cardiovascular disease risk and I validate the two-fold FCS algorithm to assess bias and precision through challenging simulation studies. I develop a new software programme which implements this adapted version of the two-fold FCS algorithm to impute missing values in longitudinal data. Finally, I apply the two-fold FCS algorithm in THIN to (i) model cardiovascular disease risk and (ii) understand factors associated with greater total cholesterol reduction in patients with type II diabete

Concentration and localization of zinc during seed development and germination in wheat

In a field experiment, the effect of foliar Zn applications on the concentration of Zn in seeds of a bread wheat cultivar (Triticum aestivum L. cv. Balatilla) was studied during different stages of seed development. In addition, a staining method using dithizone (DTZ: diphenyl thiocarbazone) was applied to (1) study the localization of Zn in seeds, (2) follow the remobilization of Zn during germination, and (3) develop a rapid visual Zn screening method for seed and flour samples. In all seed development stages, foliar Zn treatments were effective in increasing seed Zn concentration. The highest Zn concentration in the seeds was found in the first stage of seed development (around the early milk stage); after this, seed Zn concentration gradually decreased until maturity. When reacting with Zn, DTZ forms a redcolored complex. The DTZ staining of seed samples revealed that Zn is predominantly located in the embryo and aleurone parts of the seeds. After 36 h of germination, the coleoptile and roots that emerged from seeds showed very intensive red color formation and had Zn concentrations up to 200 mg kg1, indicating a substantial remobilization of Zn from seed pools into the developing roots (radicle) and coleoptile. The DTZ staining method seems to be useful in ranking flour samples for their Zn concentrations. There was a close relationship between the seed Zn concentrations and spectral absorbance of the methanol extracts of the flour samples stained with DTZ. The results suggest that (1) accumulation of Zn in seeds is particularly high during early seed development, (2) Zn is concentrated in the embryo and aleurone parts, and (3) the DTZ staining method can be used as a rapid, semiquantitative method to estimate Zn concentrations of flour and seed samples and to screen genotypes for their Zn concentrations in seeds

Prevalence of Cardiovascular Disease in Patients With Potentially Curable Malignancies: A National Registry Dataset Analysis.

BACKGROUND: Although a common challenge for patients and clinicians, there is little population-level evidence on the prevalence of cardiovascular disease (CVD) in individuals diagnosed with potentially curable cancer. OBJECTIVES: We investigated CVD rates in patients with common potentially curable malignancies and evaluated the associations between patient and disease characteristics and CVD prevalence. METHODS: The study included cancer registry patients diagnosed in England with stage I to III breast cancer, stage I to III colon or rectal cancer, stage I to III prostate cancer, stage I to IIIA non-small-cell lung cancer, stage I to IV diffuse large B-cell lymphoma, and stage I to IV Hodgkin lymphoma from 2013 to 2018. Linked hospital records and national CVD databases were used to identify CVD. The rates of CVD were investigated according to tumor type, and associations between patient and disease characteristics and CVD prevalence were determined. RESULTS: Among the 634,240 patients included, 102,834 (16.2%) had prior CVD. Men, older patients, and those living in deprived areas had higher CVD rates. Prevalence was highest for non-small-cell lung cancer (36.1%) and lowest for breast cancer (7.7%). After adjustment for age, sex, the income domain of the Index of Multiple Deprivation, and Charlson comorbidity index, CVD remained higher in other tumor types compared to breast cancer patients. CONCLUSIONS: There is a significant overlap between cancer and CVD burden. It is essential to consider CVD when evaluating national and international treatment patterns and cancer outcomes

Prevalence of Cardiovascular Disease in Patients With Potentially Curable Malignancies: A National Registry Dataset Analysis

Background: Although a common challenge for patients and clinicians, there is little population-level evidence on the prevalence of cardiovascular disease (CVD) in individuals diagnosed with potentially curable cancer. Objectives: We investigated CVD rates in patients with common potentially curable malignancies and evaluated the associations between patient and disease characteristics and CVD prevalence. Methods: The study included cancer registry patients diagnosed in England with stage I to III breast cancer, stage I to III colon or rectal cancer, stage I to III prostate cancer, stage I to IIIA non-small-cell lung cancer, stage I to IV diffuse large B-cell lymphoma, and stage I to IV Hodgkin lymphoma from 2013 to 2018. Linked hospital records and national CVD databases were used to identify CVD. The rates of CVD were investigated according to tumor type, and associations between patient and disease characteristics and CVD prevalence were determined. Results: Among the 634,240 patients included, 102,834 (16.2%) had prior CVD. Men, older patients, and those living in deprived areas had higher CVD rates. Prevalence was highest for non-small-cell lung cancer (36.1%) and lowest for breast cancer (7.7%). After adjustment for age, sex, the income domain of the Index of Multiple Deprivation, and Charlson comorbidity index, CVD remained higher in other tumor types compared to breast cancer patients. Conclusions: There is a significant overlap between cancer and CVD burden. It is essential to consider CVD when evaluating national and international treatment patterns and cancer outcomes

Does pattern mixture modelling reduce bias due to informative attrition compared to fitting a mixed effects model to the available cases or data imputed using multiple imputation?: a simulation study

BACKGROUND: Informative attrition occurs when the reason participants drop out from a study is associated with the study outcome. Analysing data with informative attrition can bias longitudinal study inferences. Approaches exist to reduce bias when analysing longitudinal data with monotone missingness (once participants drop out they do not return). However, findings may differ when using these approaches to analyse longitudinal data with nonmonotone missingness. METHODS: Different approaches to reduce bias due to informative attrition in non-monotone longitudinal data were compared. To achieve this aim, we simulated data from a Whitehall II cohort epidemiological study, which used the slope coefficients from a linear mixed effects model to investigate the association between smoking status at baseline and subsequent decline in cognition scores. Participants with lower cognitive scores were thought to be more likely to drop out. By using a simulation study, a range of scenarios using distributions of variables which exist in real data were compared. Informative attrition that would introduce a known bias to the simulated data was specified and the estimates from a mixed effects model with random intercept and slopes when fitted to: available cases; data imputed using multiple imputation (MI); imputed data adjusted using pattern mixture modelling (PMM) were compared. The twofold fully conditional specification MI approach, previously validated for non-monotone longitudinal data under ignorable missing data assumption, was used. However, MI may not reduce bias because informative attrition is non-ignorable missing. Therefore, PMM was applied to reduce the bias, usually unknown, by adjusting the values imputed with MI by a fixed value equal to the introduced bias. RESULTS: With highly correlated repeated outcome measures, the slope coefficients from a mixed effects model were found to have least bias when fitted to available cases. However, for moderately correlated outcome measurements, the slope coefficients from fitting a mixed effects model to data adjusted using PMM were least biased but still underestimated the true coefficients. CONCLUSIONS: PMM may potentially reduce bias in studies analysing longitudinal data with suspected informative attrition and moderately correlated repeated outcome measurements. Including additional auxiliary variables in the imputation model may also reduce any remaining bias

Geographical Variation in Underlying Social Deprivation, Cardiovascular and Other Comorbidities in Patients with Potentially Curable Cancers in England: Results from a National Registry Dataset Analysis

Aims: To describe the prevalence of cardiovascular disease (CVD), multiple comorbidities and social deprivation in patients with a potentially curable cancer in 20 English Cancer Alliances. Materials and methods: This National Registry Dataset Analysis used national cancer registry data and CVD databases to describe rates of CVD, comorbidities and social deprivation in patients diagnosed with a potentially curable malignancy (stage I–III breast cancer, stage I–III colon cancer, stage I–III rectal cancer, stage I–III prostate cancer, stage I–IIIA non-small cell lung cancer, stage I–IV diffuse large B-cell lymphoma, stage I–IV Hodgkin lymphoma) between 2013 and 2018. Outcome measures included observation of CVD prevalence, other comorbidities (evaluated by the Charlson Comorbidity Index) and deprivation (using the Index of Multiple Deprivation) according to tumour site and allocation to Cancer Alliance. Patients were allocated to CVD prevalence tertiles (minimum: 66.6th percentile). Results: In total, 634 240 patients with a potentially curable malignancy were eligible. The total CVD prevalence for all cancer sites varied between 13.4% (CVD n = 2058; 95% confidence interval 12.8, 13.9) and 19.6% (CVD n = 7818; 95% confidence interval 19.2, 20.0) between Cancer Alliances. CVD prevalence showed regional variation both for male (16–26%) and female patients (8–16%) towards higher CVD prevalence in northern Cancer Alliances. Similar variation was observed for social deprivation, with the proportion of cancer patients being identified as most deprived varying between 3.3% and 32.2%, depending on Cancer Alliance. The variation between Cancer Alliance for total comorbidities was much smaller. Conclusion: Social deprivation, CVD and other comorbidities in patients with a potentially curable malignancy in England show significant regional variations, which may partly contribute to differences observed in treatments and outcomes

Veterinarski obilazak mliječnih farmi s povećanim brojem somatskih stanica i bakterija iznad zakonom dozvoljenih vrijednosti

The EU Directives 92/46 and 92/47 (D.P.R. 54/97 under national legislation) fix the agreed levels of somatic cell counts and total bacterial counts allowed in milk. Over a one year period, a total of 165farms which did not comply with one or more such legal requirements were visited and monitored. This was in order to check and, where necessary, correct the hygienic and sanitary management of the farm. A comparison of the bulk tank milk somatic cell count (BTMSCC) before and after the veterinary visit, shows improvements in all the farms which were tested. In a relatively short time, visited dairy farms with a somatic cell content between 401.000 and 500.000 cells/ml managed to comply with the parameters set down by law, achieving a mean of 304.000 cells/ml. However, those farms with a somatic cell counts between 501.000 and 800.000 cells/ml required further technical action. In fact, despite considerable improvements (mean somatic cell count decreasing from 638.000 cells/ml to 403.000 cells/ml), it was not possible to meet the required levels so rapidly. On these farms, a second veterinary visit was needed as well as more specific milk sampling for bacteriological assay and therapeutic guidelines in order to meet the specified requirements.Smjernicama 92/46. i 92/47. (D.P.R. 54/97). Europska unija je utvrdila maksimalno dozvoljene vrijednosti ukupnog broja bakterija i somatskih stanica u mlijeku. Unutar godine dana posjećeno je 165 farmi koje nisu zadovoljavale svim uvjetima. Posjet je obavljen s ciljem da se snimi postojeća situacija, i, ukoliko je neophodno, da se provedu adekvatne korekcije u higijenskom i sanitarnom vođenju farmi. Usporedbom broja somatskih stanica (BTMSCC) u dobavnim tankovima za mlijeko, prije i poslije veterinarske posjete, uočena su poboljšanja na svim ispitanim farmama. Ispitane mliječne farme s brojem somatskih stanica između 401000 i 500.000 stanica/mL u relativno kratkom vremenu uspjele su smanjiti taj broj na prosječnih 304.000 stanica/mL, što udovoljava propisanim vrijednostima. Međutim, na farmama s brojem somatskih stanica između 501.000 i 800.000 Stanica/mL potrebno je provesti dodatne tehničke mjere. Usprkos značajnom poboljšanju (prosječni broj somatskih stanica smanjene je sa 638.000 stanica/mL na 403.000 stanica/mL), nisu dobivene vrijednosti unutar zakonski propisanih. Ovim farmama bio je potreban dodatni veterinarski posjet kao i specifično bakteriološko ispitivanje te terapeutski naputci s ciljem da se postigne usuglašenost sa specifičnim zahtjevima

Standardization of Preclinical PET/CT Imaging to Improve Quantitative Accuracy, Precision, and Reproducibility: A Multicenter Study

Preclinical PET/CT is a well-established noninvasive imaging tool for studying disease development/progression and the development of novel radiotracers and pharmaceuticals for clinical applications. Despite this pivotal role, standardization of preclinical PET/CT protocols, including CT absorbed dose guidelines, is essentially nonexistent. This study (1) quantitatively assesses the variability of current preclinical PET/CT acquisition and reconstruction protocols routinely used across multiple centers and scanners; and (2) proposes acquisition and reconstruction PET/CT protocols for standardization of multicenter data, optimized for routine scanning in the preclinical PET/CT laboratory. Methods: Five different commercial preclinical PET/CT scanners in Europe and the United States were enrolled. Seven different PET/CT phantoms were used for evaluating biases on default/general scanner protocols, followed by developing standardized protocols. PET, CT, and absorbed dose biases were assessed. Results: Site default CT protocols were the following: greatest extracted Hounsfield units (HU) were 133 HU for water and −967 HU for air; significant differences in all tissue equivalent material (TEM) groups were measured. The average CT absorbed doses for mouse and rat were 72 mGy and 40 mGy, respectively. Standardized CT protocol were the following: greatest extracted HU were −77 HU for water and −990 HU for air; TEM precision improved with a reduction in variability for each tissue group. The average CT absorbed dose for mouse and rat decreased to 37 mGy and 24 mGy, respectively. Site default PET protocols were the following: uniformity was substandard in one scanner, recovery coefficients (RCs) were either over- or underestimated (maximum of 43%), standard uptake values (SUVs) were biased by a maximum of 44%. Standardized PET protocols were the following: scanner with substandard uniformity improved by 36%, RC variability decreased by 13% points, and SUV accuracy improved to 10%. Conclusion: Data revealed important quantitative biases in preclinical PET/CT and absorbed doses with default protocols. Standardized protocols showed improvements in measured PET/CT accuracy and precision with reduced CT absorbed dose across sites. Adhering to standardized protocols generates reproducible and consistent preclinical imaging datasets, thus augmenting translation of research findings to the clinic

Data Resource Profile: The Virtual Cardio-Oncology Research Initiative (VICORI) linking national English cancer registration and cardiovascular audits

Background: Cancer and cardiovascular disease (CVD) are the most common causes of morbidity and mortality worldwide. Improvements in treatment strategies for both CVD and cancer have resulted in significant improvements in survival and, as a result, there is an increasing population of patients who now live with both conditions.1–3 It is well known that cancer and its treatment increase the risk of CVD.4–6 Yet a detailed understanding of the underlying relationship between these two conditions and their respective treatments, including both positive and negative modulation of risk, is lacking. This is partly because few cohorts have been large enough to conduct detailed investigations. To address this, the Virtual Cardio-Oncology Research Initiative (VICORI) has linked national cardiac and cancer registries to create a resource of a larger scale and with longer follow-up than typical investigator-led studies

A timeband framework for modelling real-time systems

Complex real-time systems must integrate physical processes with digital control, human operation and organisational structures. New scientific foundations are required for specifying, designing and implementing these systems. One key challenge is to cope with the wide range of time scales and dynamics inherent in such systems. To exploit the unique properties of time, with the aim of producing more dependable computer-based systems, it is desirable to explicitly identify distinct time bands in which the system is situated. Such a framework enables the temporal properties and associated dynamic behaviour of existing systems to be described and the requirements for new or modified systems to be specified. A system model based on a finite set of distinct time bands is motivated and developed in this paper