Background:The aim was to examine the association between smoking cessation and prognosis in smoking-related cancer as it is unclear that cessation reduces mortality.Methods:In this retrospective cohort study from 1999 to 2013, we assessed the association between cessation during the first year after diagnosis and all-cause and cancer-specific mortality.Results:Of 2882 lung, 757 upper aero-digestive tract (UAT) and 1733 bladder cancer patients 27%, 29% and 21% of lung, UAT and bladder cancer patients quit smoking. In lung cancer patients that quit, all-cause mortality was significantly lower (HR: 0.82 (0.74-0.92), while cancer-specific mortality (HR: 0.89 (0.76-1.04) and death due to index cancer (HR: 0.90 (0.77-1.05) were non-significantly lower. In UAT cancer, all-cause mortality (HR: 0.81 (0.58-1.14), cancer-specific mortality (HR: 0.84 (0.48-1.45), and death due to index cancer (HR: 0.75 (0.42-1.34) were non-significantly lower. There was no evidence of an association between quitting and mortality in bladder cancer. The HRs were 1.02 (0.81-1.30) for all-cause, 1.23 (0.81-1.86) for cancer specific, and 1.25 (0.71-2.20) for death due to index cancer. These showed a non-significantly lower risk in sensitivity analyses.Conclusions:People with lung and possibly UAT cancer who quit smoking have a lower risk of mortality than people who continue smoking.
\n \n\n \n \nPURPOSE Smoking cessation after a diagnosis of lung, bladder, and upper aerodigestive tract cancer appears to improve survival, and support to quit would improve cessation. The aims of this study were to assess how often general practitioners provide active smoking cessation support for these patients and whether physician behavior is influenced by incentive payments. METHODS Using electronic primary care records from the UK Clinical Practice Research Datalink, 12,393 patients with incident cases of cancer diagnosed between 1999 and 2013 were matched 1 to 1 to patients with incident cases of coronary heart disease (CHD) diagnosed during the same time. We assessed differences in the proportion for whom physicians updated smoking status, advised quitting, and prescribed cessation medications, as well as the proportion of patients who stopped smoking within a year of diagnosis. We further examined whether any differences arose because the physicians were offered incentives to address smoking in patients with CHD and not cancer. RESULTS At diagnosis, 32.0% of patients with cancer and 18.2% of patients with CHD smoked tobacco. Patients with cancer were less likely than patients with CHD to have their general practitioners update smoking status (OR = 0.18; 95% CI, 0.17-0.19), advise quitting (OR = 0.38; 95% CI, 0.36-0.40), or prescribe medication (OR = 0.67; 95% CI, 0.63-0.73), and they were less likely to have stopped smoking (OR = 0.76; 95% CI, 0.69-0.84). One year later 61.7% of patients with cancer and 55.4% with CHD who were smoking at diagnosis were still smoking. Introducing incentive payments was associated with more frequent interventions, but not for patients with CHD specifically. CONCLUSIONS General practitioners were less likely to support smoking cessation in patients with cancer than with CHD, and patients with cancer were less likely to stop smoking. This finding is not due to the difference in incentive payments.
\n \n\n \n \nObjective: To systematically review studies quantifying the associations of long term (clinic), mid-term (home), and short term (ambulatory) variability in blood pressure, independent of mean blood pressure, with cardiovascular disease events and mortality. Data sources: Medline, Embase, Cinahl, and Web of Science, searched to 15 February 2016 for full text articles in English. Eligibility criteria for study selection: Prospective cohort studies or clinical trials in adults, except those in patients receiving haemodialysis, where the condition may directly impact blood pressure variability. Standardised hazard ratios were extracted and, if there was little risk of confounding, combined using random effects meta-analysis in main analyses. Outcomes included all cause and cardiovascular disease mortality and cardiovascular disease events. Measures of variability included standard deviation, coefficient of variation, variation independent of mean, and average real variability, but not night dipping or day-night variation. Results: 41 papers representing 19 observational cohort studies and 17 clinical trial cohorts, comprising 46 separate analyses were identified. Long term variability in blood pressure was studied in 24 papers, mid-term in four, and short-term in 15 (two studied both long term and short term variability). Results from 23 analyses were excluded from main analyses owing to high risks of confounding. Increased long term variability in systolic blood pressure was associated with risk of all cause mortality (hazard ratio 1.15, 95% confidence interval 1.09 to 1.22), cardiovascular disease mortality (1.18, 1.09 to 1.28), cardiovascular disease events (1.18, 1.07 to 1.30), coronary heart disease (1.10, 1.04 to 1.16), and stroke (1.15, 1.04 to 1.27). Increased mid-term and short term variability in daytime systolic blood pressure were also associated with all cause mortality (1.15, 1.06 to 1.26 and 1.10, 1.04 to 1.16, respectively). Conclusions: Long term variability in blood pressure is associated with cardiovascular and mortality outcomes, over and above the effect of mean blood pressure. Associations are similar in magnitude to those of cholesterol measures with cardiovascular disease. Limited data for mid-term and short term variability showed similar associations. Future work should focus on the clinical implications of assessment of variability in blood pressure and avoid the common confounding pitfalls observed to date.
\n \n\n \n \nBACKGROUND: Competing risks occur when populations may experience outcomes that either preclude or alter the probability of experiencing the main study outcome(s). Many standard survival analysis methods do not account for competing risks. We used mortality risk in people with diabetes with and without albuminuria as a case study to investigate the impact\u00a0of competing risks on measures of absolute and relative risk. METHODS: A population with type 2 diabetes was identified in Clinical Practice Research Datalink as part of a historical cohort study. Patients were followed for up to 9\u00a0years. To quantify differences in absolute risk estimates of cardiovascular and cancer, mortality standard (Kaplan-Meier) estimates were compared to competing-risks-adjusted (cumulative incidence competing risk) estimates. To quantify differences in measures of association, regression coefficients for the effect of albuminuria on the relative hazard of each outcome were compared between standard cause-specific hazard (CSH) models (Cox proportional hazards regression) and two competing risk models: the unstratified Lunn-McNeil model, which estimates CSH, and the Fine-Gray model, which estimates subdistribution hazard (SDH). RESULTS: In patients with normoalbuminuria, standard and competing-risks-adjusted estimates for cardiovascular mortality were 11.1% (95% confidence interval (CI) 10.8-11.5%) and 10.2% (95% CI 9.9-10.5%), respectively. For cancer mortality, these figures were 8.0% (95% CI 7.7-8.3%) and 7.2% (95% CI 6.9-7.5%). In patients with albuminuria, standard and competing-risks-adjusted estimates for cardiovascular mortality were 21.8% (95% CI 20.9-22.7%) and 18.5% (95% CI 17.8-19.3%), respectively. For cancer mortality, these figures were 10.7% (95% CI 10.0-11.5%) and 8.6% (8.1-9.2%). For the effect of albuminuria on cardiovascular mortality, regression coefficient values from multivariable standard CSH, competing risks CSH, and competing risks SDH models were 0.557 (95% CI 0.491-0.623), 0.561 (95% CI 0.494-0.628), and 0.456 (95% CI 0.389-0.523), respectively. For the effect of albuminuria on cancer mortality, these values were 0.237 (95% CI 0.148-0.326), 0.244 (95% CI 0.154-0.333), and 0.102 (95% CI 0.012-0.192), respectively. CONCLUSIONS: Studies of absolute risk should use methods that adjust for competing risks to avoid over-stating risk, such as the CICR estimator. Studies of relative risk should consider carefully which measure of association is most appropriate for the research question.
\n \n\n \n \nBackground: Type 2 (T2) diabetes and diabetic nephropathy are risk factors for a range of vascular and neoplastic outcomes. The competing nature of these outcomes means that the use of standard survival analysis techniques (like Kaplan-Meier (KM) curves and Cox proportional hazards (PH) regression) could introduce bias in risk estimates. The literature was reviewed to determine whether authors accounted for competing risks (CRs) when reporting time-to-event analyses in populations with T2 diabetes and nephropathy.\n\nMethods: Medline, EMBASE and CINAHL databases were searched for studies with \u22655 years follow up reporting vascular or neoplastic outcomes in patients with T2 diabetes and nephropathy.\n\nResults: The search returned 3,886 abstracts. Of these, 179 studies were eligible for full-text review, with 29 papers eligible for data extraction. No study accounted for CRs. Analyses liable to incorporate bias through ignoring competing outcomes were present in 21 studies, of which: all studies used Cox-PH regression, 6 studies used KM curves and 2 studies produced cumulative incidence estimates from Cox-PH analysis. The remaining 8 studies did not use time-to-event analyses.\n\nConclusions: Studies investigating cardiovascular or neoplastic outcomes in populations with DN fail to account for CRs in their analyses. Using standard analyses when populations are at increased risk of multiple outcomes is liable to introduce an unknown level of bias in risk estimates. Absolute risk estimates from KM and Cox-PH regression are well known to be susceptible to this, while many have identified relative risk measured from Cox-PH regression as also being susceptible.
\n \n\n \n \nBackground: Type 2 (T2) diabetes and diabetic nephropathy (DN) are risk factors for multiple vascular and cancerous outcomes. The competing nature of these outcomes mean that the use of standard survival analysis techniques can result in bias and overestimation of the risk; particularly in cases where follow-up is long or the competing outcome is common. I reviewed the literature to determine whether authors account for competing risks (CRs) in reporting time-to-event risk measures of outcomes in individuals with T2-DN.\nMethods: Medline, EMBASE and CINAHL databases were searched for trial and cohort studies reporting occurrences of vascular or neoplasm events in T2 diabetic nephropathic populations. Articles were excluded if median follow-up was <5yrs or <1,000 subjects with T2-DN were present at baseline. Articles published <1980 or not available in English were also excluded from the analysis.\nResults: From 3,886 abstracts identified, 179 studies were eligible for full-text review. Of 16 papers currently identified for data extraction: only 1 implemented a true CRs model, 14 used single outcome models or composite end-points and 1 study provided only general incidence statistics. More results will be available.\nConclusions: Preliminary results suggest most studies fail to account for CRs in their analyses. The use of both composite end points and serial single-outcome models can produce bias through either assuming the same hazard for several outcomes or failing to accurately define the population at risk, respectively. Simulation work is currently underway to explore these biases and their potential effect on the risk measures generated.
\n \n\n \n \nPurpose: Overlooking other medical conditions during cancer treatment and follow-up could result in excess morbidity and mortality, thereby undermining gains associated with early detection and improved treatment of cancer. We compared the quality of care for diabetes patients subsequently diagnosed with breast, colorectal, or prostate cancer to matched, diabetic non-cancer controls. Methods: Longitudinal cohort study using primary care records from the Clinical Practice Research Datalink, United Kingdom. Patients with pre-existing diabetes were followed for up to 5\u00a0years after cancer diagnosis, or after an assigned index date (non-cancer controls). Quality of diabetes care was estimated based on Quality and Outcomes Framework indicators. Mixed effects logistic regression analyses were used to compare the unadjusted and adjusted odds of meeting quality measures between cancer patients and controls, overall and stratified by type of cancer. Results: 3382 cancer patients and 11,135 controls contributed 44,507\u00a0person-years of follow-up. In adjusted analyses, cancer patients were less likely to meet five of 14 quality measures, including: total cholesterol \u2264 5\u00a0mmol/L (odds ratio [OR] = 0.82; 95% confidence interval [CI], 0.75\u20130.90); glycosylated hemoglobin \u2264 59\u00a0mmol/mol (adjusted OR = 0.77; 95% CI, 0.70\u20130.85); and albumin creatinine ratio testing (adjusted OR = 0.83; 95% CI, 0.75\u20130.91). However, cancer patients were as likely as their matched controls to meet quality measures for other diabetes services, including retinal screening, foot examination, and dietary review. Conclusions: Although in the short-term, cancer patients were less likely to achieve target thresholds for cholesterol and HbA1c, they continued to receive high-quality diabetes primary care throughout 5\u00a0years post diagnosis. Implications for Cancer Survivors: These findings are important for cancer survivors with pre-existing diabetes because they indicate that high-quality diabetes care is maintained throughout the continuum of cancer diagnosis, treatment, and follow-up.
\n \n\n \n \nPurpose: Preexisting diabetes is associated with increased morbidity and mortality in cancer. We examined the impact of incident cancer on the long-term outcomes of diabetes. Methods: Using the United Kingdom Clinical Practice Research Datalink, we identified three cohorts of diabetes patients subsequently diagnosed with breast, colorectal, or prostate cancer, each matched to diabetic noncancer controls. Patients were required to have survived at least 1\u00a0year after cancer diagnosis (cases) or a matched index date (controls), and were followed up to 10\u00a0years for incident microvascular and macrovascular complications and mortality. Multivariate competing risks regression analyses were used to compare outcomes between cancer patients and controls. Results: Overall, there were 3382 cancer patients and 11,135 controls with 59,431 person-years of follow-up. In adjusted analyses, there were no statistically significant (p\u00a0\u2264\u00a00.05) differences in diabetes complication rates between cancer patients and their controls in any of the three cancer cohorts. Combined, cancer patients were less likely (adjusted hazard ratio [HR] 0.88; 95% CI\u00a0=\u00a00.79\u20130.98) to develop retinopathy. Cancer patients were more likely to die of any cause (including cancer), but prostate cancer patients were less likely to die of causes associated with diabetes (HR 0.61; 95% CI\u00a0=\u00a00.43\u20130.88). Conclusions and implications: There is no evidence that incident cancer had an adverse impact on the long-term outcomes of preexisting diabetes. Implications for Cancer Survivors: These findings are important for cancer survivors with preexisting diabetes because they suggest that substantial improvements in the relative survival of several of the most common types of cancer are not undermined by excess diabetes morbidity and mortality.
\n \n\n \n \nObjective: To estimate numbers affected by a recent change in UK guidelines for statin use in primary prevention of cardiovascular disease. Method: We modelled cholesterol ratio over time using a sample of 45,151 men (\u2265 40 years) and 36,168 women (\u2265 55 years) in 2006, without statin treatment or previous cardiovascular disease, from the Clinical Practice Research Datalink. Using simulation methods, we estimated numbers indicated for new statin treatment, if cholesterol was measured annually and used in the QRISK2 CVD risk calculator, using the previous 20% and newly recommended 10% thresholds. Results: We estimate that 58% of men and 55% of women would be indicated for treatment by five years and 71% of men and 73% of women by ten years using the 20% threshold. Using the proposed threshold of 10%, 84% of men and 90% of women would be indicated for treatment by 5. years and 92% of men and 98% of women by ten years. Conclusion: The proposed change of risk threshold from 20% to 10% would result in the substantial majority of those recommended for cholesterol testing being indicated for statin treatment. Implications depend on the value of statins in those at low to medium risk, and whether there are harms.
\n \n\n \n \nObjectives: To determine how many kidney function tests are done, on whom, how frequently they are performed and how they have changed over time. Design: Retrospective study of all serum creatinine, urine albumin and urine creatinine tests. Setting: Primary and secondary care in Oxfordshire from 1993 to 2013. Participants: Unselected population of 1 220 447 people. Main outcome measures: The total number of creatinine and urinary protein tests ordered from primary and secondary care and the number of tests per year stratified by categories of estimated glomerular filtration rate (EGFR). The frequency of testing in patients having their kidney function monitored. Results: Creatinine requests from primary care increased steadily from 1997 and exceeded 220 000 requests in 2013. Tests corresponding to normal kidney function (EGFR 60/mL/min/1.73 m2) constituted 59% of all kidney function tests in 1993 and accounted for 83% of all tests in 2013. Test corresponding to chronic kidney disease (CKD) stages 3-5 declined after 2007. Reduced kidney function, albuminuria, male gender, diabetes and age were independently associated with more frequent monitoring. For a female patient between 61 and 80 years and with stage 3a CKD, the average number of serum creatinine tests (95% CI) was 3.23/ year (3.19 to 3.26) and for a similar woman with diabetes, the average number of tests was 5.50 (5.44 to 5.56) tests per year. Conclusions: There has been a large increase in the number of kidney function tests over the past two decades. However, we found little evidence that this increase is detecting more CKD. Tests are becoming more frequent in people with and without evidence of renal impairment. Future work using a richer data source could help unravel the underlying reasons for the increased testing and determine how much is necessary and useful.
\n \n\n \n \nBackground: The publication of clinical prediction rules (CPRs) studies has risen significantly. It is unclear if this reflects increasing usage of these tools in clinical practice or how this may vary across clinical areas. Aim: To review clinical guidelines in selected areas and survey GPs in order to explore CPR usefulness in the opinion of experts and use at the point of care. Design and setting: A review of clinical guidelines and survey of UK GPs. Method: Clinical guidelines in eight clinical domains with published CPRs were reviewed for recommendations to use CPRs including primary prevention of cardiovascular disease, transient ischaemic attack (TIA) and stroke, diabetes mellitus, fracture risk assessment in osteoporosis, lower limb fractures, breast cancer, depression, and acute infections in childhood. An online survey of 401 UK GPs was also conducted. Results: Guideline review: Of 7637 records screened by title and/or abstract, 243 clinical guidelines met inclusion criteria. CPRs were most commonly recommended in guidelines regarding primary prevention of cardiovascular disease (67%) and depression (67%). There was little consensus across various clinical guidelines as to which CPR to use preferentially. Survey: Of 401 responders to the GP survey, most were aware of and applied named CPRs in the clinical areas of cardiovascular disease and depression. The commonest reasons for using CPRs were to guide management and conform to local policy requirements. Conclusion: GPs use CPRs to guide management but also to comply with local policy requirements. Future research could focus on which clinical areas clinicians would most benefit from CPRs and promoting the use of robust, externally validated CPRs. \u00a9British Journal of General Practice.
\n \n\n \n \nRisk factors for pancreatic cancer, other than smoking and diabetes, are not well-established, especially for women. In a cohort of 1.3 million middle-aged women, followed for 9.2 million personyears for cancer incidence and 11.5 million person-years for mortality, there were 1,338 incident pancreatic cancer cases and 1,710 deaths from the disease. Using proportional hazards models, we calculated adjusted relative risks (RRs) and 95% confidence intervals (CIs) by smoking, height, body mass index (BMI), alcohol consumption, physical activity and history of diabetes. Pancreatic cancer incidence was greater in current than never smokers (RR 2.39, CI 2.10-2.73), the risk increasing with the number of cigarettes smoked. The incidence of pancreatic cancer also increased with increasing BMI (RR 1.34, CI 1.13-1.57 for BMI \u2265 30 vs. 22.5-25 kg/m 2), and with a history of diabetes (RR 1.58, CI 1.22-2.03, with vs. without such a history). These factors were also associated with increased mortality from pancreatic cancer. Height, alcohol consumption and physical activity showed little or no association with pancreatic cancer risk. \u00a9 2008 Wiley-Liss, Inc.
\n \n\n \n \nTo compare the effect of potentially modifiable lifestyle factors on the incidence of vascular disease in women with and without diabetes. In 1996-2001 over one million middle-aged women in the UK joined a prospective study, providing medical history, lifestyle and socio-demographic information. All participants were followed for hospital admissions and deaths using electronic record-linkage. Adjusted relative risks (RRs) and incidence rates were calculated to compare the incidence of coronary heart disease and stroke in women with and without diabetes and by lifestyle factors. At recruitment 25,915 women (2.1% of 1,242,338) reported current treatment for diabetes. During a mean follow-up of 6.1 years per woman, 21,928 had a first hospital admission or death from coronary heart disease (RR for women with versus without diabetes = 3.30, 95% CI 3.14-3.47) and 7,087 had a first stroke (RR = 2.47, 95% CI 2.24-2.74). Adjusted incidence rates of these conditions in women with diabetes increased with duration of diabetes, obesity, inactivity and smoking. The 5-year adjusted incidence rates for cardiovascular disease were 4.6 (95% CI 4.4-4.9) per 100 women aged 50-69 in non-smokers with diabetes, 5.9 (95% CI 4.6-7.6) in smokers with diabetes not using insulin and 11.0 (95% CI 8.3-14.7) in smokers with diabetes using insulin. Non-smoking women with diabetes who were not overweight or inactive still had threefold increased rate for coronary disease or stroke compared with women without diabetes. Of the modifiable factors examined in middle aged women with diabetes, smoking causes the greatest increase in cardiovascular disease, especially in those with insulin treated diabetes. \u00a9 2008 Springer Science+Business Media B.V.
\n \n\n \n \nBackground Home blood-pressure (BP) monitoring is recommended in guidelines and is increasingly popular with patients and health professionals, but the accuracy of patients' own monitors in real-world use is not known. Aim To assess the accuracy of home BP monitors used by people with hypertension, and to investigate factors affecting accuracy. Design and setting Cross-sectional, observational study in urban and suburban settings in central England. Method Patients (n = 6891) on the hypertension register at seven practices in the West Midlands, England, were surveyed to ascertain whether they owned a BP monitor and wanted it tested. Monitor accuracy was compared with a calibrated reference device at 50 mmHg intervals between 0-280/300 mmHg (static pressure test); a difference from the reference monitor of +/-3 mmHg at any interval was considered a failure. Cuff performance was also assessed. Results were analysed by frequency of use, length of time in service, make and model, monitor validation status, purchase price, and any previous testing. Results In total, 251 (76%, 95% confidence interval [95% CI] = 71 to 80%) of 331 tested devices passed all tests (monitors and cuffs), and 86% (CI] = 82 to 90%) passed the static pressure test; deficiencies were, primarily, because of monitors overestimating BP. A total of 40% of testable monitors were not validated. The pass rate on the static pressure test was greater in validated monitors (96%, 95% CI = 94 to 98%) versus unvalidated monitors (64%, 95% CI = 58 to 69%), those retailing for >\u00a310 (90%, 95% CI = 86 to 94%), those retailing for \u2264\u00a310 (66%, 95% CI = 51 to 80%), those in use for \u22644 years (95%, 95% CI = 91 to 98%), and those in use for >4 years (74%, 95% CI = 67 to 82%). All in all, 12% of cuffs failed. Conclusion Patients' own BP monitor failure rate was similar to that demonstrated in studies performed in professional settings, although cuff failure was more frequent. Clinicians can be confident of the accuracy of patients' own BP monitors if the devices are validated and \u22644 years old.
\n \n\n \n \nBackground People with reduced kidney function have increased cardiovascular disease (CVD) risk. We present a policy model that simulates individuals\u2019 long-term health outcomes and costs to inform strategies to reduce risks of kidney and CVDs in this population. Methods and findings We used a United Kingdom primary healthcare database, the Clinical Practice Research Datalink (CPRD), linked with secondary healthcare and mortality data, to derive an open 2005\u20132013 cohort of adults (\u226518 years of age) with reduced kidney function (\u22652 measures of estimated glomerular filtration rate [eGFR] <90 mL/min/1.73 m2 \u226590 days apart). Data on individuals\u2019 sociodemographic and clinical characteristics at entry and outcomes (first occurrences of stroke, myocardial infarction (MI), and hospitalisation for heart failure; annual kidney disease stages; and cardiovascular and nonvascular deaths) during follow-up were extracted. The cohort was used to estimate risk equations for outcomes and develop a chronic kidney disease\u2013cardiovascular disease (CKD\u2013CVD) health outcomes model, a Markov state transition model simulating individuals\u2019 long-term outcomes, healthcare costs, and quality of life based on their characteristics at entry. Model-simulated cumulative risks of outcomes were compared with respective observed risks using a split-sample approach. To illustrate model value, we assess the benefits of partial (i.e., at 2013 levels) and optimal (i.e., fully compliant with clinical guidelines in 2019) use of cardioprotective medications. The cohort included 1.1 million individuals with reduced kidney function (median follow-up 4.9 years, 45% men, 19% with CVD, and 74% with only mildly decreased eGFR of 60\u201389 mL/min/1.73 m2 at entry). Age, kidney function status, and CVD events were the key determinants of subsequent morbidity and mortality. The model-simulated cumulative disease risks corresponded well to observed risks in participant categories by eGFR level. Without the use of cardioprotective medications, for 60- to 69-year-old individuals with mildly decreased eGFR (60\u201389 mL/min/1.73 m2), the model projected a further 22.1 (95% confidence interval [CI] 21.8\u201322.3) years of life if without previous CVD and 18.6 (18.2\u201318.9) years if with CVD. Cardioprotective medication use at 2013 levels (29%\u201344% of indicated individuals without CVD; 64%\u201376% of those with CVD) was projected to increase their life expectancy by 0.19 (0.14\u20130.23) and 0.90 (0.50\u20131.21) years, respectively. At optimal cardioprotective medication use, the projected health gains in these individuals increased by further 0.33 (0.25\u20130.40) and 0.37 (0.20\u20130.50) years, respectively. Limitations include risk factor measurements from the UK routine primary care database and limited albuminuria measurements. Conclusions The CKD\u2013CVD policy model is a novel resource for projecting long-term health outcomes and assessing treatment strategies in people with reduced kidney function. The model indicates clear survival benefits with cardioprotective treatments in this population and scope for further benefits if use of these treatments is optimised.
\n \n\n \n \nObjective To assess the associations between statins and adverse events in primary prevention of cardiovascular disease and to examine how the associations vary by type and dosage of statins. Design Systematic review and meta-analysis. Data sources Studies were identified from previous systematic reviews and searched in Medline, Embase, and the Cochrane Central Register of Controlled Trials, up to August 2020. Review methods Randomised controlled trials in adults without a history of cardiovascular disease that compared statins with non-statin controls or compared different types or dosages of statins were included. Main outcome measures Primary outcomes were common adverse events: self-reported muscle symptoms, clinically confirmed muscle disorders, liver dysfunction, renal insufficiency, diabetes, and eye conditions. Secondary outcomes included myocardial infarction, stroke, and death from cardiovascular disease as measures of efficacy. Data synthesis A pairwise meta-analysis was conducted to calculate odds ratios and 95% confidence intervals for each outcome between statins and non-statin controls, and the absolute risk difference in the number of events per 10 000 patients treated for a year was estimated. A network meta-analysis was performed to compare the adverse effects of different types of statins. An E max model based meta-analysis was used to examine the dose-response relationships of the adverse effects of each statin. Results 62 trials were included, with 120 456 participants followed up for an average of 3.9 years. Statins were associated with an increased risk of self-reported muscle symptoms (21 trials, odds ratio 1.06 (95% confidence interval 1.01 to 1.13); absolute risk difference 15 (95% confidence interval 1 to 29)), liver dysfunction (21 trials, odds ratio 1.33 (1.12 to 1.58); absolute risk difference 8 (3 to 14)), renal insufficiency (eight trials, odds ratio 1.14 (1.01 to 1.28); absolute risk difference 12 (1 to 24)), and eye conditions (six trials, odds ratio 1.23 (1.04 to 1.47); absolute risk difference 14 (2 to 29)) but were not associated with clinically confirmed muscle disorders or diabetes. The increased risks did not outweigh the reduction in the risk of major cardiovascular events. Atorvastatin, lovastatin, and rosuvastatin were individually associated with some adverse events, but few significant differences were found between types of statins. An E max dose-response relationship was identified for the effect of atorvastatin on liver dysfunction, but the dose-response relationships for the other statins and adverse effects were inconclusive. Conclusions For primary prevention of cardiovascular disease, the risk of adverse events attributable to statins was low and did not outweigh their efficacy in preventing cardiovascular disease, suggesting that the benefit-to-harm balance of statins is generally favourable. Evidence to support tailoring the type or dosage of statins to account for safety concerns before starting treatment was limited.
\n \n\n \n \nBackground: Long-term monitoring is important in chronic condition management. Despite considerable costs of monitoring, there is no or poor evidence on how, what and when to monitor. The aim of this study was to improve understanding, methods, evidence base and practice of clinical monitoring in primary care, focusing on two areas: Chronic kidney disease and chronic heart failure. Objectives: The research questions were as follows: Does the choice of test affect better care while being affordable to the NHS? Can the number of tests used to manage individuals with early-stage kidney disease, and hence the costs, be reduced? Is it possible to monitor heart failure using a simple blood test? Can this be done using a rapid test in a general practitioner consultation? Would changes in the management of these conditions be acceptable to patients and carers? Design: Various study designs were employed, including cohort, feasibility study, Clinical Practice Research Datalink analysis, seven systematic reviews, two qualitative studies, one cost-effectiveness analysis and one cost recommendation. Setting: This study was set in UK primary care. Data sources: Data were collected from study participants and sourced from UK general practice and hospital electronic health records, and worldwide literature. Participants: The participants were NHS patients (Clinical Practice Research Datalink: 4.5 million patients), chronic kidney disease and chronic heart failure patients managed in primary care (including 750 participants in the cohort study) and primary care health professionals. Interventions: The interventions were monitoring with blood and urine tests (for chronic kidney disease) and monitoring with blood tests and weight measurement (for chronic heart failure). Main outcome measures: The main outcomes were the frequency, accuracy, utility, acceptability, costs and cost-effectiveness of monitoring. Results: Chronic kidney disease: Serum creatinine testing has increased steadily since 1997, with most results being normal (83% in 2013). Increases in tests of creatinine and proteinuria correspond to their introduction as indicators in the Quality and Outcomes Framework. The Chronic Kidney Disease Epidemiology Collaboration equation had 2.7% greater accuracy (95% confidence interval 1.6% to 3.8%) than the Modification of Diet in Renal Disease equation for estimating glomerular filtration rate. Estimated annual transition rates to the next chronic kidney disease stage are \u2248 2% for people with normal urine albumin, 3\u20135% for people with microalbuminuria (3\u201330 mg/mmol) and 3\u201312% for people with macroalbuminuria (> 30 mg/mmol). Variability in estimated glomerular filtration rate-creatinine leads to misclassification of chronic kidney disease stage in 12\u201315% of tests in primary care. Glycaemiccontrol and lipid-modifying drugs are associated with a 6% (95% confidence interval 2% to 10%) and 4% (95% confidence interval 0% to 8%) improvement in renal function, respectively. Neither estimated glomerular filtration rate-creatinine nor estimated glomerular filtration rate-Cystatin C have utility in predicting rate of kidney function change. Patients viewed phrases such as \u2018kidney damage\u2019 or \u2018kidney failure\u2019 as frightening, and the term \u2018chronic\u2019 was misinterpreted as serious. Diagnosis of asymptomatic conditions (chronic kidney disease) was difficult to understand, and primary care professionals often did not use \u2018chronic kidney disease\u2019 when managing patients at early stages. General practitioners relied on Clinical Commissioning Group or Quality and Outcomes Framework alerts rather than National Institute for Health and Care Excellence guidance for information. Cost-effectiveness modelling did not demonstrate a tangible benefit of monitoring kidney function to guide preventative treatments, except for individuals with an estimated glomerular filtration rate of 60\u201390 ml/minute/1.73 m2, aged < 70 years and without cardiovascular disease, where monitoring every 3\u20134 years to guide cardiovascular prevention may be cost-effective. Chronic heart failure: Natriuretic peptide-guided treatment could reduce all-cause mortality by 13% and heart failure admission by 20%. Implementing natriuretic peptide-guided treatment is likely to require predefined protocols, stringent natriuretic peptide targets, relative targets and being located in a specialist heart failure setting. Remote monitoring can reduce all-cause mortality and heart failure hospitalisation, and could improve quality of life. Diagnostic accuracy of point-of-care N-terminal prohormone of B-type natriuretic peptide (sensitivity, 0.99; specificity, 0.60) was better than point-of-care B-type natriuretic peptide (sensitivity, 0.95; specificity, 0.57).Within-person variation estimates for B-type natriuretic peptide and weight were as follows: Coefficient of variation, 46% and coefficient of variation, 1.2%, respectively. Point-of-care N-terminal prohormone of B-type natriuretic peptide within-person variability over 12 months was 881 pg/ml (95% confidence interval 380 to 1382 pg/ml), whereas between-person variability was 1972 pg/ml (95% confidence interval 1525 to 2791 pg/ml). For individuals, monitoring provided reassurance; future changes, such as increased testing, would be acceptable. Point-of-care testing in general practice surgeries was perceived positively, reducing waiting time and anxiety. Community heart failure nurses had greater knowledge of National Institute for Health and Care Excellence guidance than general practitioners and practice nurses. Health-care professionals believed that the cost of natriuretic peptide tests in routine monitoring would outweigh potential benefits. The review of cost-effectiveness studies suggests that natriuretic peptide-guided treatment is cost-effective in specialist settings, but with no evidence for its value in primary care settings. Limitations: No randomised controlled trial evidence was generated. The pathways to the benefit of monitoring chronic kidney disease were unclear. Conclusions: It is difficult to ascribe quantifiable benefits to monitoring chronic kidney disease, because monitoring is unlikely to change treatment, especially in chronic kidney disease stages G3 and G4. New approaches to monitoring chronic heart failure, such as point-of-care natriuretic peptide tests in general practice, show promise if high within-test variability can be overcome. Future work: The following future work is recommended: Improve general practitioner\u2013patient communication of early-stage renal function decline, and identify strategies to reduce the variability of natriuretic peptide. Study registration: This study is registered as PROSPERO CRD42015017501, CRD42019134922 and CRD42016046902.
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