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© 2018 S. Karger AG, Basel. Copyright: All rights reserved. Background: Placebo and nocebo effects occur in clinical or laboratory medical contexts after administration of an inert treatment or as part of active treatments and are due to psychobiological mechanisms such as expectancies of the patient. Placebo and nocebo studies have evolved from predominantly methodological research into a far-reaching interdisciplinary field that is unravelling the neurobiological, behavioural and clinical underpinnings of these phenomena in a broad variety of medical conditions. As a consequence, there is an increasing demand from health professionals to develop expert recommendations about evidence-based and ethical use of placebo and nocebo effects for clinical practice. Methods: A survey and interdisciplinary expert meeting by invitation was organized as part of the 1st Society for Interdisciplinary Placebo Studies (SIPS) conference in 2017. Twenty-nine internationally recognized placebo researchers participated. Results: There was consensus that maximizing placebo effects and minimizing nocebo effects should lead to better treatment outcomes with fewer side effects. Experts particularly agreed on the importance of informing patients about placebo and nocebo effects and training health professionals in patient-clinician communication to maximize placebo and minimize nocebo effects. Conclusions: The current paper forms a first step towards developing evidence-based and ethical recommendations about the implications of placebo and nocebo research for medical practice, based on the current state of evidence and the consensus of experts. Future research might focus on how to implement these recommendations, including how to optimize conditions for educating patients about placebo and nocebo effects and providing training for the implementation in clinical practice.
© Springer Science+Business Media Dordrecht 2017. The supposed superiority of randomized over non-randomized studies is used to justify claims about therapeutic effectiveness of medical interventions and also inclusion criteria for many systematic reviews of therapeutic interventions. However, the view that randomized trials provide better evidence has been challenged by philosophers of science. In addition, empirical evidence for average differences between randomized trials and observational studies (which we would expect if one method were superior) has proven difficult to find. This chapter reviews the controversy surrounding the relative merits of randomized trials and observational studies. It is concluded that while (well-conducted) observational can often provide the same level of evidential support as randomized trials, merits of (well-conducted) randomized trials warrant claims about their superiority, especially where results from the two methods are contradictory.
Effects of empathic and positive communication in healthcare consultations: a systematic review and meta-analysis
© 2018, The Royal Society of Medicine. Background: Practitioners who enhance how they express empathy and create positive expectations of benefit could improve patient outcomes. However, the evidence in this area has not been recently synthesised. Objective: To estimate the effects of empathy and expectations interventions for any clinical condition. Design: Systematic review and meta-analysis of randomised trials. Data sources: Six databases from inception to August 2017. Study selection: Randomised trials of empathy or expectations interventions in any clinical setting with patients aged 12 years or older. Review methods: Two reviewers independently screened citations, extracted data, assessed risk of bias and graded quality of evidence using GRADE. Random effects model was used for meta-analysis. Results: We identified 28 eligible (n = 6017). In seven trials, empathic consultations improved pain, anxiety and satisfaction by a small amount (standardised mean difference −0.18 [95% confidence interval −0.32 to −0.03]). Twenty-two trials tested the effects of positive expectations. Eighteen of these (n = 2014) reported psychological outcomes (mostly pain) and showed a modest benefit (standardised mean difference −0.43 [95% confidence interval −0.65 to −0.21]); 11 (n = 1790) reported physical outcomes (including bronchial function/ length of hospital stay) and showed a small benefit (standardised mean difference −0.18 [95% confidence interval −0.32 to −0.05]). Within 11 trials (n = 2706) assessing harms, there was no evidence of adverse effects (odds ratio 1.04; 95% confidence interval 0.67 to 1.63). The risk of bias was low. The main limitations were difficulties in blinding and high heterogeneity for some comparisons. Conclusions: Greater practitioner empathy or communication of positive messages can have small patient benefits for a range of clinical conditions, especially pain. Protocol registration: Cochrane Database of Systematic Reviews (protocol) DOI: 10.1002/14651858.CD011934.pub2.
All forms of Brexit are bad for health, but some are worse than others. This paper builds on our analysis using the WHO health system building blocks framework to assess the likely effects of Brexit on the NHS in the UK. We consider four possible futures: (1) a “No Deal” Brexit under which the UK leaves the EU on 29 March 2019 without any formal agreement on the terms of withdrawal; (2) the Withdrawal Agreement, as negotiated between the UK and EU and awaiting (possible) formal agreement, which provides a transition period until the end of December 2020; (3) if the Northern Ireland Protocol’s ‘Backstop’ comes into effect after the end of that period; and (4) the Political Declaration on the Future Relationship between the UK and the EU. Our analysis shows that a No Deal Brexit is significantly worse for the NHS than a future involving the Withdrawal Agreement, which provides certainty and continuity in legal relations while the Future Relationship is negotiated and put into legal form. The Northern Ireland ‘Backstop’ has variable impact, with continuity in some areas, such as health products, but no continuity in others. The Political Declaration envisages a future relationship which is centred around a free trade agreement, in which wider health-related issues are largely absent. All forms of Brexit, however, involve negative repercussions for the UK’s leadership and governance of health, both in Europe and globally, and significant harmful consequences for the ability of parliament and other stakeholders to scrutinize and oversee governmental actions.
Do doctors in dispensing practices with a financial conflict of interest prescribe more expensive drugs? A cross-sectional analysis of English primary care prescribing data
© Author(s) (or their employer(s)) 2019. Objectives Approximately one in eight practices in primary care in England are 'dispensing practices' with an in-house dispensary providing medication directly to patients. These practices can generate additional income by negotiating lower prices on higher cost drugs, while being reimbursed at a standard rate. They, therefore, have a potential financial conflict of interest around prescribing choices. We aimed to determine whether dispensing practices are more likely to prescribe high-cost options for four commonly prescribed classes of drug where there is no evidence of superiority for high-cost options. Design A list was generated of drugs with high acquisition costs that were no more clinically effective than those with the lowest acquisition costs, for all four classes of drug examined. Data were obtained prescribing of statins, proton pump inhibitors (PPIs), angiotensin receptor blockers (ARBs) and ACE inhibitors (ACEis). Logistic regression was used to calculate ORs for prescribing high-cost options in dispensing practices, adjusting for Index of Multiple Deprivation score, practice list size and the number of doctors at each practice. Setting English primary care. Participants All general practices in England. Main outcome measures Mean cost per dose was calculated separately for dispensing and non-dispensing practices. Dispensing practices can vary in the number of patients they dispense to; we, therefore, additionally compared practices with no dispensing patients, low, medium and high proportions of dispensing patients. Total cost savings were modelled by applying the mean cost per dose from non-dispensing practices to the number of doses prescribed in dispensing practices. Results Dispensing practices were more likely to prescribe high-cost drugs across all classes: statins adjusted OR 1.51 (95% CI 1.49 to 1.53, p<0.0001), PPIs OR 1.11 (95% CI 1.09 to 1.13, p<0.0001), ACEi OR 2.58 (95% CI 2.46 to 2.70, p<0.0001), ARB OR 5.11 (95% CI 5.02 to 5.20, p<0.0001). Mean cost per dose in pence was higher in dispensing practices (statins 7.44 vs 6.27, PPIs 5.57 vs 5.46, ACEi 4.30 vs 4.24, ARB 11.09 vs 8.19). For all drug classes, the more dispensing patients a practice had, the more likely it was to issue a prescription for a high-cost option. Total cost savings in England available from all four classes are £628 875 per month or £7 546 502 per year. Conclusions Doctors in dispensing practices are more likely to prescribe higher cost drugs. This is the largest study ever conducted on dispensing practices, and the first contemporary research suggesting some UK doctors respond to a financial conflict of interest in treatment decisions. The reimbursement system for dispensing practices may generate unintended consequences. Robust routine audit of practices prescribing higher volumes of unnecessarily expensive drugs may help reduce costs.
Development and validation of QDiabetes-2018 risk prediction algorithm to estimate future risk of type 2 diabetes: cohort study
Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions. Objectives To derive and validate updated QDiabetes-2018 prediction algorithms to estimate the 10 year risk of type 2 diabetes in men and women, taking account of potential new risk factors, and to compare their performance with current approaches.Design Prospective open cohort study.Setting Routinely collected data from 1457 general practices in England contributing to the QResearch database: 1094 were used to develop the scores and a separate set of 363 were used to validate the scores.Participants 11.5 million people aged 25-84 and free of diabetes at baseline: 8.87 million in the derivation cohort and 2.63 million in the validation cohort.Methods Cox proportional hazards models were used in the derivation cohort to derive separate risk equations in men and women for evaluation at 10 years. Risk factors considered included those already in QDiabetes (age, ethnicity, deprivation, body mass index, smoking, family history of diabetes in a first degree relative, cardiovascular disease, treated hypertension, and regular use of corticosteroids) and new risk factors: atypical antipsychotics, statins, schizophrenia or bipolar affective disorder, learning disability, gestational diabetes, and polycystic ovary syndrome. Additional models included fasting blood glucose and glycated haemoglobin (HBA1c). Measures of calibration and discrimination were determined in the validation cohort for men and women separately and for individual subgroups by age group, ethnicity, and baseline disease status.Main outcome measure Incident type 2 diabetes recorded on the general practice record.Results In the derivation cohort, 178 314 incident cases of type 2 diabetes were identified during follow-up arising from 42.72 million person years of observation. In the validation cohort, 62 326 incident cases of type 2 diabetes were identified from 14.32 million person years of observation. All new risk factors considered met our model inclusion criteria. Model A included age, ethnicity, deprivation, body mass index, smoking, family history of diabetes in a first degree relative, cardiovascular disease, treated hypertension, and regular use of corticosteroids, and new risk factors: atypical antipsychotics, statins, schizophrenia or bipolar affective disorder, learning disability, and gestational diabetes and polycystic ovary syndrome in women. Model B included the same variables as model A plus fasting blood glucose. Model C included HBA1c instead of fasting blood glucose. All three models had good calibration and high levels of explained variation and discrimination. In women, model B explained 63.3% of the variation in time to diagnosis of type 2 diabetes (R2), the D statistic was 2.69 and the Harrell's C statistic value was 0.89. The corresponding values for men were 58.4%, 2.42, and 0.87. Model B also had the highest sensitivity compared with current recommended practice in the National Health Service based on bands of either fasting blood glucose or HBA1c. However, only 16% of patients had complete data for blood glucose measurements, smoking, and body mass index.Conclusions Three updated QDiabetes risk models to quantify the absolute risk of type 2 diabetes were developed and validated: model A does not require a blood test and can be used to identify patients for fasting blood glucose (model B) or HBA1c (model C) testing. Model B had the best performance for predicting 10 year risk of type 2 diabetes to identify those who need interventions and more intensive follow-up, improving on current approaches. Additional external validation of models B and C in datasets with more completely collected data on blood glucose would be valuable before the models are used in clinical practice.
Development and validation of QMortality risk prediction algorithm to estimate short term risk of death and assess frailty: cohort study
Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions. Objectives To derive and validate a risk prediction equation to estimate the short term risk of death, and to develop a classification method for frailty based on risk of death and risk of unplanned hospital admission.Design Prospective open cohort study.Participants Routinely collected data from 1436 general practices contributing data to QResearch in England between 2012 and 2016. 1079 practices were used to develop the scores and a separate set of 357 practices to validate the scores. 1.47 million patients aged 65-100 years were in the derivation cohort and 0.50 million patients in the validation cohort.Methods Cox proportional hazards models in the derivation cohort were used to derive separate risk equations in men and women for evaluation of the risk of death at one year. Risk factors considered were age, sex, ethnicity, deprivation, smoking status, alcohol intake, body mass index, medical conditions, specific drugs, social factors, and results of recent investigations. Measures of calibration and discrimination were determined in the validation cohort for men and women separately and for each age and ethnic group. The new mortality equation was used in conjunction with the existing QAdmissions equation (which predicts risk of unplanned hospital admission) to classify patients into frailty groups.Main outcome measure The primary outcome was all cause mortality.Results During follow-up 180 132 deaths were identified in the derivation cohort arising from 4.39 million person years of observation. The final model included terms for age, body mass index, Townsend score, ethnic group, smoking status, alcohol intake, unplanned hospital admissions in the past 12 months, atrial fibrillation, antipsychotics, cancer, asthma or chronic obstructive pulmonary disease, living in a care home, congestive heart failure, corticosteroids, cardiovascular disease, dementia, epilepsy, learning disability, leg ulcer, chronic liver disease or pancreatitis, Parkinson's disease, poor mobility, rheumatoid arthritis, chronic kidney disease, type 1 diabetes, type 2 diabetes, venous thromboembolism, anaemia, abnormal liver function test result, high platelet count, visited doctor in the past year with either appetite loss, unexpected weight loss, or breathlessness. The model had good calibration and high levels of explained variation and discrimination. In women, the equation explained 55.6% of the variation in time to death (R2), and had very good discrimination-the D statistic was 2.29, and Harrell's C statistic value was 0.85. The corresponding values for men were 53.1%, 2.18, and 0.84. By combining predicted risks of mortality and unplanned hospital admissions, 2.7% of patients (n=13 665) were classified as severely frail, 9.4% (n=46 770) as moderately frail, 43.1% (n=215 253) as mildly frail, and 44.8% (n=223 790) as fit.Conclusions We have developed new equations to predict the short term risk of death in men and women aged 65 or more, taking account of demographic, social, and clinical variables. The equations had good performance on a separate validation cohort. The QMortality equations can be used in conjunction with the QAdmissions equations, to classify patients into four frailty groups (known as QFrailty categories) to enable patients to be identified for further assessment or interventions.
Risks and benefits of direct oral anticoagulants versus warfarin in a real world setting: cohort study in primary care
Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions. OBJECTIVE: To investigate the associations between direct oral anticoagulants (DOACs) and risks of bleeding, ischaemic stroke, venous thromboembolism, and all cause mortality compared with warfarin.DESIGN: Prospective open cohort study.SETTING: UK general practices contributing to QResearch or Clinical Practice Research Datalink.PARTICIPANTS: 132 231 warfarin, 7744 dabigatran, 37 863 rivaroxaban, and 18 223 apixaban users without anticoagulant prescriptions for 12 months before study entry, subgrouped into 103 270 patients with atrial fibrillation and 92 791 without atrial fibrillation between 2011 and 2016.MAIN OUTCOME MEASURES: Major bleeding leading to hospital admission or death. Specific sites of bleeding and all cause mortality were also studied.RESULTS: In patients with atrial fibrillation, compared with warfarin, apixaban was associated with a decreased risk of major bleeding (adjusted hazard ratio 0.66, 95% confidence interval 0.54 to 0.79) and intracranial bleeding (0.40, 0.25 to 0.64); dabigatran was associated with a decreased risk of intracranial bleeding (0.45, 0.26 to 0.77). An increased risk of all cause mortality was observed in patients taking rivaroxaban (1.19, 1.09 to 1.29) or on lower doses of apixaban (1.27, 1.12 to 1.45). In patients without atrial fibrillation, compared with warfarin, apixaban was associated with a decreased risk of major bleeding (0.60, 0.46 to 0.79), any gastrointestinal bleeding (0.55, 0.37 to 0.83), and upper gastrointestinal bleeding (0.55, 0.36 to 0.83); rivaroxaban was associated with a decreased risk of intracranial bleeding (0.54, 0.35 to 0.82). Increased risk of all cause mortality was observed in patients taking rivaroxaban (1.51, 1.38 to 1.66) and those on lower doses of apixaban (1.34, 1.13 to 1.58).CONCLUSIONS: Overall, apixaban was found to be the safest drug, with reduced risks of major, intracranial, and gastrointestinal bleeding compared with warfarin. Rivaroxaban and low dose apixaban were, however, associated with increased risks of all cause mortality compared with warfarin.
Use of hormone replacement therapy and risk of venous thromboembolism: Nested case-control studies using the QResearch and CPRD databases
© Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to. Objective To assess the association between risk of venous thromboembolism and use of different types of hormone replacement therapy. Design Two nested case-control studies. Setting UK general practices contributing to the QResearch or Clinical Practice Research Datalink (CPRD) databases, and linked to hospital, mortality, and social deprivation data. Participants 80 396 women aged 40-79 with a primary diagnosis of venous thromboembolism between 1998 and 2017, matched by age, general practice, and index date to 391 494 female controls. Main outcome measures Venous thromboembolism recorded on general practice, mortality, or hospital records. Odds ratios were adjusted for demographics, smoking status, alcohol consumption, comorbidities, recent medical events, and other prescribed drugs. Results Overall, 5795 (7.2%) women who had venous thromboembolism and 21 670 (5.5%) controls had been exposed to hormone replacement therapy within 90 days before the index date. Of these two groups, 4915 (85%)and 16 938 (78%) women used oral therapy, respectively, which was associated with a significantly increased risk of venous thromboembolism compared with no exposure (adjusted odds ratio 1.58, 95% confidence interval 1.52 to 1.64), for both oestrogen only preparations (1.40, 1.32 to 1.48) and combined preparations (1.73, 1.65 to 1.81). Estradiolhad a lower risk than conjugated equine oestrogen for oestrogen only preparations (0.85, 0.76 to 0.95) and combined preparations (0.83, 0.76 to 0.91). Compared with no exposure, conjugated equine oestrogen with medroxyprogesterone acetate had the highest risk (2.10, 1.92 to 2.31), and estradiol with dydrogesterone had the lowest risk (1.18, 0.98 to 1.42). Transdermal preparations were not associated with risk of venous thromboembolism, which was consistent for different regimens (overall adjusted odds ratio 0.93, 95% confidence interval 0.87 to 1.01). Conclusions In the present study, transdermal treatment was the safest type of hormone replacement therapy when risk of venous thromboembolism was assessed. Transdermal treatment appears to be underused, with the overwhelming preference still for oral preparations.
Development and validation of risk prediction equations to estimate survival in patients with colorectal cancer: Cohort study
© Published by the BMJ Publishing Group Limited. Objective To develop and externally validate risk prediction equations to estimate absolute and conditional survival in patients with colorectal cancer. Design Cohort study. Setting General practices in England providing data for the QResearch database linked to the national cancer registry. Participants 44 145 patients aged 15-99 with colorectal cancer from 947 practices to derive the equations. The equations were validated in 15 214 patients with colorectal cancer from 305 different QResearch practices and 437 821 patients with colorectal cancer from the national cancer registry. Main outcome measures The primary outcome was all cause mortality and secondary outcome was colorectal cancer mortality. Methods Cause specific hazards models were used to predict risks of colorectal cancer mortality and other cause mortality accounting for competing risks, and these risk estimates were combined to obtain risks of all cause mortality. Separate equations were derived for men and women. Several variables were tested: age, ethnicity, deprivation score, cancer stage, cancer grade, surgery, chemotherapy, radiotherapy, smoking status, alcohol consumption, body mass index, family history of bowel cancer, anaemia, liver function test result, comorbidities, use of statins, use of aspirin, clinical values for anaemia, and platelet count. Measures of calibration and discrimination were determined in both validation cohorts at 1, 5, and 10 years. Results The final models included the following variables in men and women: age, deprivation score, cancer stage, cancer grade, smoking status, colorectal surgery, chemotherapy, family history of bowel cancer, raised platelet count, abnormal liver function, cardiovascular disease, diabetes, chronic renal disease, chronic obstructive pulmonary disease, prescribed aspirin at diagnosis, and prescribed statins at diagnosis. Improved survival in women was associated with younger age, earlier stage of cancer, well or moderately differentiated cancer grade, colorectal cancer surgery (adjusted hazard ratio 0.50), family history of bowel cancer (0.62), and prescriptions for statins (0.77) and aspirin (0.83) at diagnosis, with comparable results for men. The risk equations were well calibrated, with predicted risks closely matching observed risks. Discrimination was good in men and women in both validation cohorts. For example, the five year survival equations on the QResearch validation cohort explained 45.3% of the variation in time to colorectal cancer death for women, the D statistic was 1.86, and Harrell's C statistic was 0.80 (both measures of discrimination, indicating that the scores are able to distinguish between people with different levels of risk). The corresponding results for all cause mortality were 42.6%, 1.77, and 0.79. Conclusions Risk prediction equations were developed and validated to estimate overall and conditional survival of patients with colorectal cancer accounting for an individual's clinical and demographic characteristics. These equations can provide more individualised accurate information for patients with colorectal cancer to inform decision making and follow-up.
Development and validation of QRISK3 risk prediction algorithms to estimate future risk of cardiovascular disease: Prospective cohort study
© Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to. Objectives To develop and validate updated QRISK3 prediction algorithms to estimate the 10 year risk of cardiovascular disease in women and men accounting for potential new risk factors. Design Prospective open cohort study. Setting General practices in England providing data for the QResearch database. Participants 1309 QResearch general practices in England: 981 practices were used to develop the scores and a separate set of 328 practices were used to validate the scores. 7.89 million patients aged 25-84 years were in the derivation cohort and 2.67 million patients in the validation cohort. Patients were free of cardiovascular disease and not prescribed statins at baseline. Methods Cox proportional hazards models in the derivation cohort to derive separate risk equations in men and women for evaluation at 10 years. Risk factors considered included those already in QRISK2 (age, ethnicity, deprivation, systolic blood pressure, body mass index, total cholesterol: high density lipoprotein cholesterol ratio, smoking, family history of coronary heart disease in a first degree relative aged less than 60 years, type 1 diabetes, type 2 diabetes, treated hypertension, rheumatoid arthritis, atrial fibrillation, chronic kidney disease (stage 4 or 5)) and new risk factors (chronic kidney disease (stage 3, 4, or 5), a measure of systolic blood pressure variability (standard deviation of repeated measures), migraine, corticosteroids, systemic lupus erythematosus (SLE), atypical antipsychotics, severe mental illness, and HIV/AIDS). We also considered erectile dysfunction diagnosis or treatment in men. Measures of calibration and discrimination were determined in the validation cohort for men and women separately and for individual subgroups by age group, ethnicity, and baseline disease status. Main outcome measures Incident cardiovascular disease recorded on any of the following three linked data sources: general practice, mortality, or hospital admission records. Results 363 565 incident cases of cardiovascular disease were identified in the derivation cohort during follow-up arising from 50.8 million person years of observation. All new risk factors considered met the model inclusion criteria except for HIV/AIDS, which was not statistically significant. The models had good calibration and high levels of explained variation and discrimination. In women, the algorithm explained 59.6% of the variation in time to diagnosis of cardiovascular disease (R 2, with higher values indicating more variation), and the D statistic was 2.48 and Harrell's C statistic was 0.88 (both measures of discrimination, with higher values indicating better discrimination). The corresponding values for men were 54.8%, 2.26, and 0.86. Overall performance of the updated QRISK3 algorithms was similar to the QRISK2 algorithms. Conclusion Updated QRISK3 risk prediction models were developed and validated. The inclusion of additional clinical variables in QRISK3 (chronic kidney disease, a measure of systolic blood pressure variability (standard deviation of repeated measures), migraine, corticosteroids, SLE, atypical antipsychotics, severe mental illness, and erectile dysfunction) can help enable doctors to identify those at most risk of heart disease and stroke.
Diabetes treatments and risk of heart failure, cardiovascular disease, and all cause mortality: Cohort study in primary care
© BMJ Publishing Group Ltd 2016. Objective: To assess associations between risks of cardiovascular disease, heart failure, and all cause mortality and different diabetes drugs in people with type 2 diabetes, particularly newer agents, including gliptins and thiazolidinediones (glitazones). Design: Open cohort study. Setting: 1243 general practices contributing data to the QResearch database in England. Participants: 469 688 people with type 2 diabetes aged 25-84 years between 1 April 2007 and 31 January 2015. Exposures: Diabetes drugs (glitazones, gliptins, metformin, sulphonylureas, insulin, other) alone and in combination. Main outcom e measure: First recorded diagnoses of cardiovascular disease, heart failure, and all cause mortality recorded on the patients' primary care, mortality, or hospital record. Cox proportional hazards models were used to estimate hazard ratios for diabetes treatments, adjusting for potential confounders. Results: During follow-up, 21 308 patients (4.5%) received prescriptions for glitazones and 32 533 (6.9%) received prescriptions for gliptins. Compared with non-use, gliptins were significantly associated with an 18% decreased risk of all cause mortality, a 14% decreased risk of heart failure, and no significant change in risk of cardiovascular disease; corresponding values for glitazones were significantly decreased risks of 23% for all cause mortality, 26% for heart failure, and 25% for cardiovascular disease. Compared with no current treatment, there were no significant associations between monotherapy with gliptins and risk of any complications. Dual treatment with gliptins and metformin was associated with a decreased risk of all three outcomes (reductions of 38% for heart failure, 33% for cardiovascular disease, and 48% for all cause mortality). Triple treatment with metformin, sulphonylureas, and gliptins was associated with a decreased risk of all three outcomes (reductions of 40% for heart failure, 30% for cardiovascular disease, and 51% for all cause mortality). Compared with no current treatment, monotherapy with glitazone was associated with a 50% decreased risk of heart failure, and dual treatment with glitazones and metformin was associated with a decreased risk of all three outcomes (reductions of 50% for heart failure, 54% for cardiovascular disease, and 45% for all cause mortality); dual treatment with glitazones and sulphonylureas was associated with risk reductions of 35% for heart failure and 25% for cardiovascular disease; triple treatment with metformin, sulphonylureas, and glitazones was associated with decreased risks of all three outcomes (reductions of 46% for heart failure, 41% for cardiovascular disease, and 56% for all cause mortality). Conclusions: There are clinically important differences in risk of cardiovascular disease, heart failure, and all cause mortality between different diabetes drugs alone and in combination. Overall, use of gliptins or glitazones was associated with decreased risks of heart failure, cardiovascular disease, and all cause mortality compared with non-use of these drugs. These results, which do not account for levels of adherence or dosage information and which are subject to confounding by indication, might have implications for prescribing of diabetes drugs.
Discontinuation and restarting in patients on statin treatment: Prospective open cohort study using a primary care database
© 2016 BMJ Publishing Group Ltd. Objectives: To estimate rates of discontinuation and restarting of statins, and to identify patient characteristics associated with either discontinuation or restarting. Design: Prospective open cohort study. Setting: 664 general practices contributing to the Clinical Practice Research Datalink in the United Kingdom. Data extracted in October 2014. Participants: Incident statin users aged 25-84 years identified between January 2002 and September 2013. Patients with statin prescriptions divided into two groups: primary prevention and secondary prevention (those already diagnosed with cardiovascular disease). Patients with statin prescriptions in the 12 months before study entry were excluded. Main outcome measures: Discontinuation of statin treatment (first 90 day gap after the estimated end date of a statin prescription), and restarting statin treatment for those who discontinued (defined as any subsequent prescription between discontinuation and study end). Results: Of 431 023 patients prescribed statins as primary prevention with a median follow-up time of 137 weeks, 47% (n=204 622) discontinued treatment and 72% (n=147 305) of those who discontinued restarted. Of 139 314 patients prescribed statins as secondary prevention with median follow-up time of 182 weeks, 41% (n=57 791) discontinued treatment and 75% (43 211) of those who discontinued restarted. Younger patients (aged ≤50 years), older patients (≥75 years), women, and patients with chronic liver disease were more likely to discontinue statins and less likely to restart. However, patients in ethnic minority groups, current smokers, and patients with type 1 diabetes were more likely to discontinue treatment but then were more likely to restart, whereas patients with hypertension and type 2 diabetes were less likely to discontinue treatment and more likely to restart if they did discontinue. These results were mainly consistent in the primary prevention and secondary prevention groups. Conclusions: Although a large proportion of statin users discontinue, many of them restart. For many patient groups previously considered as "stoppers," the problem of statin treatment "stopping" could be part of the wider issue of poor adherence. Identification of patient groups associated with completely stopping or stop-starting behaviour has positive implications for patients and doctors as well as suggesting areas for future research.
BACKGROUND: A number of treatments can help smokers make a successful quit attempt, but many initially successful quitters relapse over time. Several interventions were proposed to help prevent relapse. OBJECTIVES: To assess whether specific interventions for relapse prevention reduce the proportion of recent quitters who return to smoking. SEARCH STRATEGY: We searched the Cochrane Tobacco Addiction Group trials register in August 2008 for studies mentioning relapse prevention or maintenance in title, abstracts or keywords. SELECTION CRITERIA: Randomized or quasi-randomized controlled trials of relapse prevention interventions with a minimum follow up of six months. We included smokers who quit on their own, or were undergoing enforced abstinence, or who were participating in treatment programmes. We included trials that compared relapse prevention interventions to a no intervention control, or that compared a cessation programme with additional relapse prevention components to a cessation programme alone. DATA COLLECTION AND ANALYSIS: Studies were screened and data extracted by one author and checked by a second. Disagreements were resolved by discussion or referral to a third author. MAIN RESULTS: Fifty-four studies met inclusion criteria, but were heterogeneous in terms of populations and interventions. We considered 36 studies that randomized abstainers separately from studies that randomized participants prior to their quit date.Looking at studies of behavioural interventions which randomised abstainers, we detected no benefit of brief and 'skills-based' relapse prevention methods for women who had quit smoking due to pregnancy, or for smokers undergoing a period of enforced abstinence during hospitalisation or military training. We also failed to detect significant effects of behavioural interventions in trials in unselected groups of smokers who had quit on their own or with a formal programme. Amongst trials randomising smokers prior to their quit date and evaluating the effect of additional relapse prevention components we also found no evidence of benefit of behavioural interventions in any subgroup. Overall, providing training in skills thought to be needed for relapse avoidance did not reduce relapse, but most studies did not use experimental designs best suited to the task, and had limited power to detect expected small differences between interventions. For pharmacological interventions, extended treatment with varenicline significantly reduced relapse in one trial (risk ratio 1.18, 95% confidence interval 1.03 to 1.36). Pooling of five studies of extended treatment with bupropion failed to detect a significant effect (risk ratio 1.17; 95% confidence interval 0.99 to 1.39). Two small trials of oral nicotine replacement treatment (NRT) failed to detect an effect but treatment compliance was low and in two other trials of oral NRT randomizing short-term abstainers there was a significant effect of intervention. AUTHORS' CONCLUSIONS: At the moment there is insufficient evidence to support the use of any specific behavioural intervention for helping smokers who have successfully quit for a short time to avoid relapse. The verdict is strongest for interventions focusing on identifying and resolving tempting situations, as most studies were concerned with these. There is little research available regarding other behavioural approaches. Extended treatment with varenicline may prevent relapse. Extended treatment with bupropion is unlikely to have a clinically important effect. Studies of extended treatment with nicotine replacement are needed.
© 2018 A poor diet is the leading cause of premature morbidity and mortality in England. Nutritional surveillance shows that, on average, people eat too little fruit and vegetables, fibre and oily fish, and too many foods and drinks high in calories, sugar and saturated fat. Although micronutrient deficiencies are rare at the population level, some subgroups may require nutritional supplements. Public health policy seeks to intervene to close the gap between dietary intake and dietary recommendations for good health. Population-level policies include actions to enhance nutritional knowledge, set nutrition standards for food provision and introduce fiscal interventions such as taxation. They can also encourage the food industry to reformulate food and drink products, change the availability or positioning of products, thus changing the default choices, and change the way products are marketed, with a mix of both voluntary and mandatory approaches. Health professionals can play a pivotal role in motivating dietary change at an individual level, particularly for individuals with increased risk, and have an advocacy role in supporting policies to improve population health.