Description of the updated nutrition calculation of the Oxford WebQ questionnaire and comparison with the previous version among 207,144 participants in UK Biobank.

PURPOSE: The Oxford WebQ is a web-based 24-h dietary assessment method which has been used in UK Biobank and other large prospective studies. The food composition table used to calculate nutrient intakes has recently been replaced with the UK Nutrient Databank, which has food composition data closer in time to when participants completed the questionnaire, and new dietary variables were incorporated. Here we describe the updated version of the Oxford WebQ questionnaire nutrient calculation, and compare nutrient intakes with the previous version used. METHODS: 207,144 UK Biobank participants completed ≥ 1 Oxford WebQs, and means and standard deviations of nutrient intakes were averaged for all completed 24-h dietary assessments. Spearman correlations and weighted kappa statistics were used to compare the re-classification and agreement of nutrient intakes between the two versions. RESULTS: 35 new nutrients were incorporated in the updated version. Compared to the previous version, most nutrients were very similar in the updated version except for a few nutrients which showed a difference of > 10%: lower with the new version for trans-fat (- 20%), and vitamin C (- 15%), but higher for retinol (+ 42%), vitamin D (+ 26%) and vitamin E (+ 20%). Most participants were in the same (> 60%) or adjacent (> 90%) quintile of intake for the two versions. Except for trans-fat (r = 0.58, κ = 0.42), very high correlations were found between the nutrients calculated using the two versions (r > 0.79 and κ > 0.60). CONCLUSION: Small absolute differences in nutrient intakes were observed between the two versions, and the ranking of individuals was minimally affected, except for trans-fat

Investigating Alaskan Methane and Carbon Dioxide Fluxes Using Measurements from the CARVE Tower

Northern high-latitude carbon sources and sinks, including those resulting from degrading permafrost, are thought to be sensitive to the rapidly warming climate. Because the near-surface atmosphere integrates surface fluxes over large ( ∼ 500–1000 km) scales, atmospheric monitoring of carbon dioxide (CO2) and methane (CH4) mole fractions in the daytime mixed layer is a promising method for detecting change in the carbon cycle throughout boreal Alaska. Here we use CO2 and CH4 measurements from a NOAA tower 17 km north of Fairbanks, AK, established as part of NASA\u27s Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE), to investigate regional fluxes of CO2 and CH4 for 2012–2014. CARVE was designed to use aircraft and surface observations to better understand and quantify the sensitivity of Alaskan carbon fluxes to climate variability. We use high-resolution meteorological fields from the Polar Weather Research and Forecasting (WRF) model coupled with the Stochastic Time-Inverted Lagrangian Transport model (hereafter, WRF-STILT), along with the Polar Vegetation Photosynthesis and Respiration Model (PolarVPRM), to investigate fluxes of CO2 in boreal Alaska using the tower observations, which are sensitive to large areas of central Alaska. We show that simulated PolarVPRM–WRF-STILT CO2 mole fractions show remarkably good agreement with tower observations, suggesting that the WRF-STILT model represents the meteorology of the region quite well, and that the PolarVPRM flux magnitudes and spatial distribution are generally consistent with CO2 mole fractions observed at the CARVE tower. One exception to this good agreement is that during the fall of all 3 years, PolarVPRM cannot reproduce the observed CO2 respiration. Using the WRF-STILT model, we find that average CH4 fluxes in boreal Alaska are somewhat lower than flux estimates by Chang et al. (2014) over all of Alaska for May–September 2012; we also find that enhancements appear to persist during some wintertime periods, augmenting those observed during the summer and fall. The possibility of significant fall and winter CO2 and CH4 fluxes underscores the need for year-round in situ observations to quantify changes in boreal Alaskan annual carbon balance

Examination of potential novel biochemical factors in relation to prostate cancer incidence and mortality in UK Biobank

Background: Although prostate cancer is a leading cause of cancer death, its aetiology is not well understood. We aimed to identify novel biochemical factors for prostate cancer incidence and mortality in UK Biobank. Methods: A range of cardiovascular, bone, joint, diabetes, renal and liver-related biomarkers were measured in baseline blood samples collected from up to 211,754 men at recruitment and in a subsample 5 years later. Participants were followed-up via linkage to health administrative datasets to identify prostate cancer cases. Hazard ratios (HRs) and 95% confidence intervals were calculated using multivariable-adjusted Cox regression corrected for regression dilution bias. Multiple testing was accounted for by using a false discovery rate controlling procedure. Results: After an average follow-up of 6.9 years, 5763 prostate cancer cases and 331 prostate cancer deaths were ascertained. Prostate cancer incidence was positively associated with circulating vitamin D, urea and phosphate concentrations and inversely associated with glucose, total protein and aspartate aminotransferase. Phosphate and cystatin-C were the only biomarkers positively and inversely, respectively, associated with risk in analyses excluding the first 4 years of follow-up. There was little evidence of associations with prostate cancer death. Conclusion: We found novel associations of several biomarkers with prostate cancer incidence. Future research will examine associations by tumour characteristics.</p

Long-term efficacy and tolerability of TNFα inhibitors in the treatment of non-infectious ocular inflammation:an 8-year prospective surveillance study

BACKGROUND/AIM: To report the efficacy and tolerability of antitumour necrosis factor-alpha therapy (TNF inhibitors [TNFi]) in the management of non-infectious ocular inflammation, including uveitis and scleritis, in adult patients over an 8-year period. MATERIALS AND METHODS: This is a prospective cohort study of infliximab and adalimumab in the treatment of non-infectious ocular inflammatory disease. 43 of 85 adult patients on TNFi (34 infliximab, 9 adalimumab) for ≥1 year with non-infectious uveitis or scleritis were followed from 2006 to 2014. Clinical assessments, medication, adverse events and history of steroid rescues were collected at 6 monthly intervals. General quality of life (Short Form Health Survey (SF-36)) and visual quality of life (Vision-related quality of life Core Measure (VCM1)) were assessed annually. Outcome measures included rate of sustained remission, rate of relapse, systemic corticosteroid reduction, adverse events, and VCM1 and SF-36 scores. RESULTS: The median time on infliximab was 3.2 years (IQR 4.3) and on adalimumab was 2.4 years (IQR 1.8). Sustained remission was induced in 39 patients (91%) (0.5 per patient year) after a median of 1.2 years on a TNFi. 22 (51%) experienced one relapse, and 5 (12%) had two relapses. 23 (54%) had at least one adverse event; serious adverse events necessitating hospitalisation or cessation of medication occurred in four (9%) patients. 10 patients (23%) switched from the initiation of TNFi, at 1.7 years after starting, to another TNFi or another class of biologic therapy. CONCLUSION: TNFi treatment is associated with long-term drug-induced remission of ocular inflammation, visual stability and corticosteroid reduction. Adverse events were common and no new safety signals occurred. Relapse of inflammation occurs in half of the treated population

Healthcare in England was affected by the COVID-19 pandemic across the pancreatic cancer pathway: A cohort study using OpenSAFELY-TPP

Background: Healthcare across all sectors, in the UK and globally, was negatively affected by the COVID-19 pandemic. We analysed healthcare services delivered to people with pancreatic cancer from January 2015 to March 2023 to investigate the effect of the COVID-19 pandemic. Methods: With the approval of NHS England, and drawing from a nationally representative OpenSAFELY-TPP dataset of 24 million patients (over 40% of the English population), we undertook a cohort study of people diagnosed with pancreatic cancer. We queried electronic healthcare records for information on the provision of healthcare services across the pancreatic cancer pathway. To estimate the effect of the COVID-19 pandemic, we predicted the rates of healthcare services if the pandemic had not happened. We used generalised linear models and the pre-pandemic data from January 2015 to February 2020 to predict rates in March 2020 to March 2023. The 95% confidence intervals of the predicted values were used to estimate the significance of the difference between the predicted and observed rates. Results: The rate of pancreatic cancer and diabetes diagnoses in the cohort was not affected by the pandemic. There were 26,840 people diagnosed with pancreatic cancer from January 2015 to March 2023. The mean age at diagnosis was 72 (±11 SD), 48% of people were female, 95% were of White ethnicity, and 40% were diagnosed with diabetes. We found a reduction in surgical resections by 25-28% during the pandemic. In addition, 20%, 10%, and 4% fewer people received body mass index, glycated haemoglobin, and liver function tests, respectively, before they were diagnosed with pancreatic cancer. There was no impact of the pandemic on the number of people making contact with primary care, but the number of contacts increased on average by 1-2 per person amongst those who made contact. Reporting of jaundice decreased by 28%, but recovered within 12 months into the pandemic. Emergency department visits, hospital admissions, and deaths were not affected. Conclusions: The pandemic affected healthcare in England across the pancreatic cancer pathway. Positive lessons could be learnt from the services that were resilient and those that recovered quickly. The reductions in healthcare experienced by people with cancer have the potential to lead to worse outcomes. Current efforts should focus on addressing the unmet needs of people with cancer. Funding: This work was jointly funded by the Wellcome Trust (222097/Z/20/Z); MRC (MR/V015757/1, MC_PC-20059, MR/W016729/1); NIHR (NIHR135559, COV-LT2-0073), and Health Data Research UK (HDRUK2021.000, 2021.0157). This work was funded by Medical Research Council (MRC) grant reference MR/W021390/1 as part of the postdoctoral fellowship awarded to AL and undertaken at the Bennett Institute, University of Oxford. The views expressed are those of the authors and not necessarily those of the NIHR, NHS England, UK Health Security Agency (UKHSA), or the Department of Health and Social Care. Funders had no role in the study design, collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the article for publication

A National Audit of Pancreatic Enzyme Prescribing in Pancreatic Cancer from 2015 to 2023 in England Using OpenSAFELY-TPP

Objectives: Cancer treatments were variably disrupted during the coronavirus disease 2019 (COVID-19) pandemic. UK guidelines recommend pancreatic enzyme replacement therapy (PERT) to all people with unresectable pancreatic cancer. The aim was to investigate the impact of the COVID-19 pandemic on PERT prescribing to people with unresectable pancreatic cancer and to investigate the national and regional rates from January 2015 to January 2023. Data Sources: With the approval of NHS England, we conducted this study using 24 million electronic health records of people within the OpenSAFELY-TPP research platform. There were 22,860 people diagnosed with pancreatic cancer in the study cohort. We visualized the trends over time and modeled the effect of the COVID-19 pandemic with the interrupted time-series analysis. Conclusion: In contrast to many other treatments, prescribing of PERT was not affected during the pandemic. Overall, since 2015, the rates increased steadily over time by 1% every year. The national rates ranged from 41% in 2015 to 48% in early 2023. There was substantial regional variation, with the highest rates of 50% to 60% in West Midlands. Implications for Nursing Practice: In pancreatic cancer, if PERT is prescribed, it is usually initiated in hospitals by clinical nurse specialists and continued after discharge by primary care practitioners. At just under 50% in early 2023, the rates were still below the recommended 100% standard. More research is needed to understand barriers to prescribing of PERT and geographic variation to improve quality of care. Prior work relied on manual audits. With OpenSAFELY, we developed an automated audit that allows for regular updates (https://doi.org/10.53764/rpt.a0b1b51c7a)

Comparative effectiveness of BNT162b2 versus mRNA-1273 covid-19 vaccine boosting in England: matched cohort study in OpenSAFELY-TPP

Objective To compare the effectiveness of the BNT162b2 mRNA (Pfizer-BioNTech) and mRNA-1273 (Moderna) covid-19 vaccines during the booster programme in England. Design Matched cohort study, emulating a comparative effectiveness trial. Setting Linked primary care, hospital, and covid-19 surveillance records available within the OpenSAFELY-TPP research platform, covering a period when the SARS-CoV-2 delta and omicron variants were dominant. Participants 3 237 918 adults who received a booster dose of either vaccine between 29 October 2021 and 25 February 2022 as part of the national booster programme in England and who received a primary course of BNT162b2 or ChAdOx1. Intervention Vaccination with either BNT162b2 or mRNA-1273 as a booster vaccine dose. Main outcome measures Recorded SARS-CoV-2 positive test, covid-19 related hospital admission, covid-19 related death, and non-covid-19 related death at 20 weeks after receipt of the booster dose. Results 1 618 959 people were matched in each vaccine group, contributing a total 64 546 391 person weeks of follow-up. The 20 week risks per 1000 for a positive SARS-CoV-2 test were 164.2 (95% confidence interval 163.3 to 165.1) for BNT162b2 and 159.9 (159.0 to 160.8) for mRNA-1273; the hazard ratio comparing mRNA-1273 with BNT162b2 was 0.95 (95% confidence interval 0.95 to 0.96). The 20 week risks per 1000 for hospital admission with covid-19 were 0.75 (0.71 to 0.79) for BNT162b2 and 0.65 (0.61 to 0.69) for mRNA-1273; the hazard ratio was 0.89 (0.82 to 0.95). Covid-19 related deaths were rare: the 20 week risks per 1000 were 0.028 (0.021 to 0.037) for BNT162b2 and 0.024 (0.018 to 0.033) for mRNA-1273; hazard ratio 0.83 (0.58 to 1.19). Comparative effectiveness was generally similar within subgroups defined by the primary course vaccine brand, age, previous SARS-CoV-2 infection, and clinical vulnerability. Relative benefit was similar when vaccines were compared separately in the delta and omicron variant eras. Conclusions This matched observational study of adults estimated a modest benefit of booster vaccination with mRNA-1273 compared with BNT162b2 in preventing positive SARS-CoV-2 tests and hospital admission with covid-19 20 weeks after vaccination, during a period of delta followed by omicron variant dominance

CTDAS-Lagrange v1.0:a high-resolution data assimilation system for regional carbon dioxide observations

We have implemented a regional carbon dioxide data assimilation system based on the CarbonTracker Data Assimilation Shell (CTDAS) and a high-resolution Lagrangian transport model, the Stochastic Time-Inverted Lagrangian Transport model driven by the Weather Forecast and Research meteorological fields (WRF-STILT). With this system, named CTDAS-Lagrange, we simultaneously optimize terrestrial biosphere fluxes and four parameters that adjust the lateral boundary conditions (BCs) against CO2 observations from the NOAA ESRL North America tall tower and aircraft programmable flask packages (PFPs) sampling program. Least-squares optimization is performed with a time-stepping ensemble Kalman smoother, over a time window of 10 days and assimilating sequentially a time series of observations. Because the WRF-STILT footprints are pre-computed, it is computationally efficient to run the CTDAS-Lagrange system.To estimate the uncertainties in the optimized fluxes from the system, we performed sensitivity tests with various a priori biosphere fluxes (SiBCASA, SiB3, CT2013B) and BCs (optimized mole fraction fields from CT2013B and CTE2014, and an empirical dataset derived from aircraft observations), as well as with a variety of choices on the ways that fluxes are adjusted (additive or multiplicative), covariance length scales, biosphere flux covariances, BC parameter uncertainties, and model-data mismatches. In pseudo-data experiments, we show that in our implementation the additive flux adjustment method is more flexible in optimizing net ecosystem exchange (NEE) than the multiplicative flux adjustment method, and our sensitivity tests with real observations show that the CTDAS-Lagrange system has the ability to correct for the potential biases in the lateral BCs and to resolve large biases in the prior biosphere fluxes.Using real observations, we have derived a range of estimates for the optimized carbon fluxes from a series of sensitivity tests, which places the North American carbon sink for the year 2010 in a range from -0.92 to -1.26 PgC yr( -1). This is comparable to the TM5-based estimates of CarbonTracker (version CT2016, -0.91 +/- 1.10 PgC yr (-1)) and CarbonTracker Europe (version CTE,2016, -0.91 +/- 0.31 PgC yr(-1)). We conclude that CTDAS-Lagrange can offer a versatile and computationally attractive alternative to these global systems for regional estimates of carbon fluxes, which can take advantage of high-resolution Lagrangian footprints that are increasingly easy to obtain

CTDAS-Lagrange v1.0 : A high-resolution data assimilation system for regional carbon dioxide observations

We have implemented a regional carbon dioxide data assimilation system based on the CarbonTracker Data Assimilation Shell (CTDAS) and a high-resolution Lagrangian transport model, the Stochastic Time-Inverted Lagrangian Transport model driven by the Weather Forecast and Research meteorological fields (WRF-STILT). With this system, named CTDAS-Lagrange, we simultaneously optimize terrestrial biosphere fluxes and four parameters that adjust the lateral boundary conditions (BCs) against CO2 observations from the NOAA ESRL North America tall tower and aircraft programmable flask packages (PFPs) sampling program. Least-squares optimization is performed with a time-stepping ensemble Kalman smoother, over a time window of 10 days and assimilating sequentially a time series of observations. Because the WRF-STILT footprints are pre-computed, it is computationally efficient to run the CTDAS-Lagrange system. To estimate the uncertainties in the optimized fluxes from the system, we performed sensitivity tests with various a priori biosphere fluxes (SiBCASA, SiB3, CT2013B) and BCs (optimized mole fraction fields from CT2013B and CTE2014, and an empirical dataset derived from aircraft observations), as well as with a variety of choices on the ways that fluxes are adjusted (additive or multiplicative), covariance length scales, biosphere flux covariances, BC parameter uncertainties, and model-data mismatches. In pseudo-data experiments, we show that in our implementation the additive flux adjustment method is more flexible in optimizing net ecosystem exchange (NEE) than the multiplicative flux adjustment method, and our sensitivity tests with real observations show that the CTDAS-Lagrange system has the ability to correct for the potential biases in the lateral BCs and to resolve large biases in the prior biosphere fluxes. Using real observations, we have derived a range of estimates for the optimized carbon fluxes from a series of sensitivity tests, which places the North American carbon sink for the year 2010 in a range from -0.92 to -1.26PgCyr-1. This is comparable to the TM5-based estimates of CarbonTracker (version CT2016, -0.91±1.10PgCyr-1) and CarbonTracker Europe (version CTE2016, -0.91±0.31PgCyr-1). We conclude that CTDAS-Lagrange can offer a versatile and computationally attractive alternative to these global systems for regional estimates of carbon fluxes, which can take advantage of high-resolution Lagrangian footprints that are increasingly easy to obtain.</p