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Objectives: Observational cohort studies are used to evaluate the effectiveness of screening mammography in women offered screening. Because screening mammography has no effect on causes of death other than breast cancer (BC), cohort studies should show reductions in the risk of BC death substantially greater than possible reductions in the risk of all-cause death. We assessed the risk of BC deaths and of all-cause (or of nonBC) deaths associated with screening mammography attendance reported in cohort studies., Study Design and Setting: Cohort studies published from 2002 to 2022 on women invited to screening mammography were searched in PubMed, Web of Sciences, Scopus, and in review articles. Random effect meta-analyses were performed using relative risks (RRs) of death between women who attended screening compared to women who did not attend screening., Results: Eighteen cohort studies were identified, nine that reported RRs of BC deaths only, five that reported RRs of all-cause deaths only, and four that reported RRs for both BC deaths and all-cause deaths. The latter four cohort studies reported 12-76 times more all-cause deaths than BC deaths. The random-effect summary of RR for BC mortality in screening attendees vs nonattendees was 0.55 (95% CI: 0.50-0.60) in 13 cohort studies. The summary of RR for all-cause mortality was 0.54 (0.50-0.58) in 10 cohort studies. In the four cohort studies that evaluated both outcomes, the summary of RRs were 0.63 (0.43-0.83) for BC mortality and of 0.54 (0.44-0.64) for all-cause mortality., Conclusion: The similar relative reductions in breast- and all-cause (or nonBC) mortality indicates that screening mammography attendance is an indicator of characteristics associated with a lower risk of dying from any cause, including from BC, which observational studies have falsely interpreted as a screening effect., Competing Interests: Declaration of competing interest There are no competing interests for any authors., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background and Aims: Proper prescription and high adherence to intensive lipid lowering drugs (LLD) in patients with coronary heart disease (CHD) are crucial and strongly recommended. The aim of this study is to investigate long-term treatment patterns and adherence to LLD following hospitalization for a CHD event., Methods: Patients admitted to two Norwegian hospitals with a CHD event from 2011 to 2014 (N = 1094) attended clinical examination and completed a questionnaire, median 16 months later. Clinical data were linked to pharmacy dispensing data from 2010 to 2020. The proportions using high-intensity statin therapy (atorvastatin 40/80 mg or rosuvastatin 20/40 mg) and non-statin LLD after the CHD event were assessed. Adherence was evaluated by proportion of days covered (PDC) and gaps in treatment., Results: Median age at hospitalization was 63 (IQR 12) years, 21 % were female. Altogether, 1054 patients (96 %) were discharged with a statin prescription, while treatment was dispensed in 85 % within the following 90 days. During median 8 (SD 2.5) years follow-up, the proportion using high-intensity statin therapy ranged 62-68 %, whereas the use of ezetimibe increased from 4 to 26 %. PDC <0.8 was found in 22 % of statin users and 26 % of ezetimibe users. The proportions with a treatment gap exceeding 180 days were 22 % for statins and 28 % for ezetimibe. Smoking at hospitalization and negative affectivity were significantly associated with reduced statin adherence, regardless of adherence measure., Conclusions: In this long-term follow-up of patients with CHD, less than 70 % used high-intensity statin therapy with only small changes over time, and only 25 % used additional treatment with ezetimibe. We identified factors associated with reduced statin adherence that may be target for interventions., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:IE and CB are affiliated with Oslo Economics and have completed consultancy assignments outside the submitted work for several public and private institutions in recent years. HS is affiliated with Steno Diabetes Center Aarhus and has received consultancy fees from Novartis, Arla Foods AMBA, Bristol-Myers Squibb, Pfizer and Neumirna outside the submitted work. EH, ES and TD reports no conflicts of interest. SH has received lecture fees from Sanofi, Novartis, and Pfizer outside the submitted work. JM received lecture fees from Sanofi, Novartis, Boehringer Ingelheim, and Bayer outside the submitted work., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Serving whey protein before a meal in order to lower postprandial blood glucose concentrations is known as a premeal. The underlying mechanisms are only partly understood but may involve stimulation of glucagon-like peptide-1 (GLP-1), glucose-dependent insulinotropic polypeptide (GIP), and insulin secretion together with a slower gastric emptying rate., Objectives: The objective of this systematic review and meta-analysis was to review all randomized clinical trials investigating premeals with whey protein in comparison with a nonactive comparator (control) that evaluated plasma glucose, GLP-1, GIP, insulin, and/or gastric emptying rate. Secondary aims included subgroup analyses on the timing and dose of the premeal together with the metabolic state of the participants [lean, obese, and type 2 diabetes mellitus (T2DM)]., Methods: We searched EMBASE, CENTRAL, PUBMED, and clinicaltrials.gov and found 16 randomized crossover trials with a total of 244 individuals. The last search was performed on 9 August, 2022., Results: Whey protein premeals lowered peak glucose concentration by -1.4 mmol/L [-1.9 mmol/L; -0.9 mmol/L], and the area under the curve for glucose was -0.9 standard deviation (SD) [-1.2 SD; -0.6 SD] compared with controls (high certainty). In association with these findings, whey protein premeals elevated GLP-1 (low certainty) and peak insulin (high certainty) concentrations and slowed gastric emptying rate (high certainty) compared with controls. Subgroup analyses showed a more pronounced and prolonged glucose-lowering effect in individuals with T2DM compared with participants without T2DM. The available evidence did not elucidate the role of GIP. The protein dose used varied between 4 and 55 g, and meta-regression analysis showed that the protein dose correlated with the glucose-lowering effects., Conclusions: In conclusion, whey protein premeals lower postprandial blood glucose, reduce gastric emptying rate, and increase peak insulin. In addition, whey protein premeals may elevate plasma concentrations of GLP-1. Whey protein premeals may possess clinical potential, but the long-term effects await future clinical trials., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: Observational studies on corona virus disease 2019 (COVID-19) vaccines compare event rates in vaccinated and unvaccinated person time using Poisson or Cox regression. In Cox regression, the chosen time scale needs to account for the time-varying incidence of severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) infection and COVID-19 vaccination.We aimed to quantify bias in person-time based methods, with and without adjustment for calendar time, using simulations and empirical data analysis., Methods: We simulated 500,000 individuals who were followed for 365 days, and a point exposure resembling COVID-19 vaccination (cumulative incidence 80%). We generated an effectiveness outcome, emulating the incidence of severe acute respiratory syndrome corona virus 2 infection in Denmark during 2021 (risk 10%), and a safety outcome with seasonal variation (myocarditis, risk 1/5,000). Incidence rate ratios (IRRs) were set to 0.1 for effectiveness and 5.0 for safety outcomes. IRRs and hazard ratios (HRs) were estimated using Poisson and Cox regression with a time under observation scale, and a calendar time scale. Bias was defined as estimated IRR or HR-true IRR. Further, we obtained estimates for both outcomes using data from the Danish health registries., Results: Unadjusted IRRs (bias effectivenes +0.16; bias safety -2.09) and HRs estimated using a time-under-observation scale (+0.28;-2.15) were biased. Adjustment for calendar time reduced bias in Cox (+0.03; +0.33) and Poisson regression (0.00; -0.28). Cox regression using a calendar time scale was least biased (0.00, +0.12). When analyzing empirical data, adjusted Poisson and Cox regression using a calendar time scale yielded estimates in accordance with existing evidence., Conclusion: Lack of adjustment for the time-varying incidence of COVID-19 related outcomes may severely bias estimates., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: Identification of patients at high risk of treatment-resistant schizophrenia at the time of schizophrenia diagnosis would be of great clinical benefit in minimising the delay to clozapine treatment in patients unlikely to respond to non-clozapine antipsychotics. However, little is known about predictors of treatment resistance in this patient population. We used a treatment-based proxy for treatment-resistant schizophrenia to identify candidate predictors of treatment resistance at first hospital contact with a schizophrenia diagnosis., Methods: In this population-based cohort study, we obtained Danish national registry data for all adult patients (≥18 years) with incident schizophrenia diagnosed between Jan 1, 1996, and Dec 31, 2006, and followed up until Dec 31, 2010. Our main proxy definition of treatment-resistant schizophrenia was the earliest instance of either clozapine initiation or hospital admission for schizophrenia after having had two periods of different antipsychotic monotherapy. We did multivariable Cox proportional hazards regression analysis to estimate the association between baseline candidate predictors and treatment resistance., Findings: 8624 patients fulfilled the criteria for inclusion. In multivariable complete-case analyses, 1703 (21%) of 8044 patients fulfilled the main proxy definition of treatment-resistant schizophrenia during a median follow-up of 9·1 years (IQR 6·3-11·9). Younger age (hazard ratio 0·96 [95% CI 0·95-0·97]), living in a less urban area (provincial 1·38 [1·23-1·56], rural 1·44 [1·25-1·65]), primary education level (0·88 [0·79-0·98]), more than 30 bed-days in psychiatric hospital in the year before first schizophrenia diagnosis (1·54 [1·35-1·75]), inpatient at first schizophrenia diagnosis (2·07 [1·87-2·29]), paranoid subtype (1·24 [1·13-1·37]), comorbid personality disorder (1·24 [1·11-1·39]), psychotropic drug use (antipsychotics 1·51 [1·35-1·69], antidepressants 1·15 [1·03-1·29], and benzodiazepines 1·22 [1·10-1·37]), and previous suicide attempt (1·21 [1·07-1·39]) were all significantly associated with treatment-resistant schizophrenia., Interpretation: Our study identifies several candidate predictors that could potentially be included in future prediction models for treatment-resistant schizophrenia. Notably, established risk factors for schizophrenia did not predict treatment resistance, suggesting that treatment-resistant disease might be a distinct subtype of schizophrenia and not merely a more severe form., Funding: European Community's Seventh Framework Programme., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

The prevalence of diabetes has increased worldwide. We have undertaken an epidemiological analysis of drug-treated diabetes in a well defined community. We present estimates of prevalence, incidence, and mortality of patients with such diabetes during 1993-, based on data for all 470000 people living in the county of Fyn, Denmark. Although prevalence increased (odds ratio: female, 1.026 [95% CI 1.020-1.032]; male, 1.041 [1.036-1.047]), mortality in those treated declined (rate ratio: female, 0.976 [95%CI 0.952-1.001]; male, 0.966 [0.943-0.990]). We did not identify a clear trend for incidence. Future research into the causes of rising diabetes prevalence should take this fall in mortality into account to avoid incorrect conclusions about the relation between western lifestyle and the growing number of diabetics.