Influence of cardiometabolic medications on abdominal aortic aneurysm growth in the UK Aneurysm Growth Study: metformin and angiotensin-converting enzyme inhibitors associated with slower aneurysm growth.

BACKGROUND: There is a clinical need for treatments that can slow or prevent the growth of an abdominal aortic aneurysm, not only to reduce the need for surgery, but to provide a means to treat those who cannot undergo surgery. METHODS: Analysis of the UK Aneurysm Growth Study (UKAGS) prospective cohort was conducted to test for an association between cardiometabolic medications and the growth of an abdominal aortic aneurysm above 30 mm in diameter, using linear mixed-effect models. RESULTS: A total of 3670 male participants with data available on abdominal aortic aneurysm growth, smoking status, co-morbidities, and medication history were included. The mean age at recruitment was 69.5 years, the median number of surveillance scans was 6, and the mean(s.e.) unadjusted abdominal aortic aneurysm growth rate was 1.75(0.03) mm/year. In a multivariate linear mixed-effect model, smoking (mean(s.e.) +0.305(0.07) mm/year, P = 0.00003) and antiplatelet use (mean(s.e.) +0.235(0.06) mm/year, P = 0.00018) were found to be associated with more rapid abdominal aortic aneurysm growth, whilst metformin was strongly associated with slower abdominal aortic aneurysm growth (mean(s.e.) -0.38(0.1) mm/year, P = 0.00019), as were angiotensin-converting enzyme inhibitors (mean(s.e.) -0.243(0.07) mm/year, P = 0.0004), angiotensin II receptor antagonists (mean(s.e.) -0.253(0.08) mm/year, P = 0.00255), and thiazides/related diuretics (mean(s.e.) -0.307(0.09) mm/year, P = 0.00078). CONCLUSION: The strong association of metformin with slower abdominal aortic aneurysm growth highlights the importance of the ongoing clinical trials assessing the effectiveness of metformin with regard to the prevention of abdominal aortic aneurysm growth and/or rupture. The association of angiotensin-converting enzyme inhibitors, angiotensin II receptor antagonists, and diuretics with slower abdominal aortic aneurysm growth points to the possibility that optimization of cardiovascular risk management as part of abdominal aortic aneurysm surveillance may have the secondary benefit of also reducing abdominal aortic aneurysm growth rates.

Evaluation of Flexible Parametric Relative Survival Approaches for Enforcing Long-Term Constraints When Extrapolating All-Cause Survival.

OBJECTIVES: Parametric models are used to estimate the lifetime benefit of an intervention beyond the range of trial follow-up. Recent recommendations have suggested more flexible survival approaches and the use of external data when extrapolating. Both of these can be realized by using flexible parametric relative survival modeling. The overall aim of this article is to introduce and contrast various approaches for applying constraints on the long-term disease-related (excess) mortality including cure models and evaluate the consequent implications for extrapolation. METHODS: We describe flexible parametric relative survival modeling approaches. We then introduce various options for constraining the long-term excess mortality and compare the performance of each method in simulated data. These methods include fitting a standard flexible parametric relative survival model, enforcing statistical cure, and forcing the long-term excess mortality to converge to a constant. We simulate various scenarios, including where statistical cure is reasonable and where the long-term excess mortality persists. RESULTS: The compared approaches showed similar survival fits within the follow-up period. However, when extrapolating the all-cause survival beyond trial follow-up, there is variation depending on the assumption made about the long-term excess mortality. Altering the time point from which the excess mortality is constrained enables further flexibility. CONCLUSIONS: The various constraints can lead to applying explicit assumptions when extrapolating, which could lead to more plausible survival extrapolations. The inclusion of general population mortality directly into the model-building process, which is possible for all considered approaches, should be adopted more widely in survival extrapolation in health technology assessment.

Perils of Randomized Controlled Trial Survival Extrapolation Assuming Treatment Effect Waning: Why the Distinction Between Marginal and Conditional Estimates Matters.

OBJECTIVES: A long-term, constant, protective treatment effect is a strong assumption when extrapolating survival beyond clinical trial follow-up; hence, sensitivity to treatment effect waning is commonly assessed for economic evaluations. Forcing a hazard ratio (HR) to 1 does not necessarily estimate loss of individual-level treatment effect accurately because of HR selection bias. A simulation study was designed to explore the behavior of marginal HRs under a waning conditional (individual-level) treatment effect and demonstrate bias in forcing a marginal HR to 1 when the estimand is "survival difference with individual-level waning". METHODS: Data were simulated under 4 parameter combinations (varying prognostic strength of heterogeneity and treatment effect). Time-varying marginal HRs were estimated in scenarios where the true conditional HR attenuated to 1. Restricted mean survival time differences, estimated having constrained the marginal HR to 1, were compared with true values to assess bias induced by marginal constraints. RESULTS: Under loss of conditional treatment effect, the marginal HR took a value >1 because of covariate imbalances. Constraining this value to 1 lead to restricted mean survival time difference bias of up to 0.8 years (57% increase). Inflation of effect size estimates also increased with the magnitude of initial protective treatment effect. CONCLUSIONS: Important differences exist between survival extrapolations assuming marginal versus conditional treatment effect waning. When a marginal HR is constrained to 1 to assess efficacy under individual-level treatment effect waning, the survival benefits associated with the new treatment will be overestimated, and incremental cost-effectiveness ratios will be underestimated.

Sex-specific differences in the standard of care for infrarenal abdominal aortic aneurysm repair, and risk of major adverse cardiovascular events and death.

BACKGROUND: This study investigated whether sex-specific differences in preoperative/perioperative standard of care (SOC) account for disparity in outcomes after elective infrarenal abdominal aortic aneurysm repair. METHODS: This was a retrospective cohort study of elective infrarenal abdominal aortic aneurysm repairs (2013-2020) using depersonalized patient-level National Vascular Registry data. SOC was defined for waiting times, preoperative assessment (multidisciplinary/anaesthetic review), cardiovascular risk prevention, and perioperative medication. The primary outcome was major cardiovascular event and/or death (MACED). RESULTS: Some 21 810 patients with an infrarenal abdominal aortic aneurysm were included, 2380 women and 19 430 men. Women less often underwent aneurysm repair within SOC waiting times (51.5 versus 59.3 per cent; P < 0.001), but were equally likely to receive preoperative assessment (72.1 versus 72.5 per cent; P = 0.742). Women were less likely to receive secondary prevention for known cardiac disease (34.9 versus 39.6 per cent; P = 0.015), but more often met overall cardiovascular risk prevention standards (52.1 versus 47.3 per cent; P < 0.001). Women were at greater risk of MACED (open: 12.0 versus 8.9 per cent, P < 0.001; endovascular: 4.9 versus 2.9 per cent, P < 0.001; risk-adjusted OR 1.33, 95 per cent c.i. 1.12 to 1.59). A significant reduction in the odds of MACED was associated with preoperative assessment (OR 0.86, 0.75 to 0.98) and SOC waiting times (OR 0.78, 0.69 to 0.87). There was insufficient evidence to confirm a significant sex-specific difference in the effect of SOC preoperative assessment (women: OR 0.69, 0.50 to 0.97; men: OR 0.89, 0.77 to 1.03; interaction P = 0.170) or SOC waiting times (women: OR 0.84, 0.62 to 1.16; men: OR 0.76, 0.67 to 0.87; interaction P = 0.570) on the risk of MACED. CONCLUSION: SOC waiting times and preoperative assessment were not met for both sexes, which was associated with an increased risk of MACED. Sex-specific differences in SOC attenuated but did not fully account for the increased risk of MACED in women.

Impact of a post-donation hemoglobin testing strategy on efficiency and safety of whole blood donation in England: A modeling study.

BACKGROUND: Deferrals due to low hemoglobin are time-consuming and costly for blood donors and donation services. Furthermore, accepting donations from those with low hemoglobin could represent a significant safety issue. One approach to reduce them is to use hemoglobin concentration alongside donor characteristics to inform personalized inter-donation intervals. STUDY DESIGN AND METHODS: We used data from 17,308 donors to inform a discrete event simulation model comparing personalized inter-donation intervals using "post-donation" testing (i.e., estimating current hemoglobin from that measured by a hematology analyzer at last donation) versus the current approach in England (i.e., pre-donation testing with fixed intervals of 12-weeks for men and 16-weeks for women). We reported the impact on total donations, low hemoglobin deferrals, inappropriate bleeds, and blood service costs. Personalized inter-donation intervals were defined using mixed-effects modeling to estimate hemoglobin trajectories and probability of crossing hemoglobin donation thresholds. RESULTS: The model had generally good internal validation, with predicted events similar to those observed. Over 1 year, a personalized strategy requiring ≥90% probability of being over the hemoglobin threshold, minimized adverse events (low hemoglobin deferrals and inappropriate bleeds) in both sexes and costs in women. Donations per adverse event improved from 3.4 (95% uncertainty interval 2.8, 3.7) under the current strategy to 14.8 (11.6, 19.2) in women, and from 7.1 (6.1, 8.5) to 26.9 (20.8, 42.6) in men. In comparison, a strategy incorporating early returns for those with high certainty of being over the threshold maximized total donations in both men and women, but was less favorable in terms of adverse events, with 8.4 donations per adverse event in women (7.0, 10,1) and 14.8 (12.1, 21.0) in men. DISCUSSION: Personalized inter-donation intervals using post-donation testing combined with modeling of hemoglobin trajectories can help reduce deferrals, inappropriate bleeds, and costs.

Glycosylated haemoglobin and prognosis in 10,536 people with cancer and pre-existing diabetes: a meta-analysis with dose-response analysis.

AIMS: To assess whether glycaemic control is associated with prognosis in people with cancer and pre-existing diabetes. METHODS: In this pre-registered systematic review (PROSPERO: CRD42020223956), PubMed and Web of Science were searched on 25th Nov 2021 for studies investigating associations between glycosylated haemoglobin (HbA1c) and prognosis in people with diabetes and cancer. Summary relative risks (RRs) and 95% Confidence Intervals (CIs) for associations between poorly controlled HbA1c or per 1-unit HbA1c increment and cancer outcomes were estimated using a random-effects meta-analysis. We also investigated the impact of potential small-study effects using the trim-and-fill method and potential sources of heterogeneity using subgroup analyses. RESULTS: Fifteen eligible observational studies, reporting data on 10,536 patients with cancer and pre-existing diabetes, were included. Random-effects meta-analyses indicated that HbA1c ≥ 7% (53 mmol/mol) was associated with increased risks of: all-cause mortality (14 studies; RR: 1.14 [95% CI: 1.03-1.27]; p-value: 0.012), cancer-specific mortality (5; 1.68 [1.13-2.49]; p-value: 0.011) and cancer recurrence (8; 1.68 [1.18-2.38; p-value: 0.004]), with moderate to high heterogeneity. Dose-response meta-analyses indicated that 1-unit increment of HbA1c (%) was associated with increased risks of all-cause mortality (13 studies; 1.04 [1.01-1.08]; p-value: 0.016) and cancer-specific mortality (4; 1.11 [1.04-1.20]; p-value: 0.003). All RRs were attenuated in trim-and-fill analyses. CONCLUSIONS: Our findings suggested that glycaemic control might be a modifiable risk factor for mortality and cancer recurrence in people with cancer and pre-existing diabetes. High-quality studies with a larger sample size are warranted to confirm these findings due to heterogeneity and potential small-study effects. In the interim, it makes clinical sense to recommend continued optimal glycaemic control.

Prediction of Cardiovascular Disease Risk Accounting for Future Initiation of Statin Treatment.

Cardiovascular disease (CVD) risk-prediction models are used to identify high-risk individuals and guide statin initiation. However, these models are usually derived from individuals who might initiate statins during follow-up. We present a simple approach to address statin initiation to predict "statin-naive" CVD risk. We analyzed primary care data (2004-2017) from the UK Clinical Practice Research Datalink for 1,678,727 individuals (aged 40-85 years) without CVD or statin treatment history at study entry. We derived age- and sex-specific prediction models including conventional risk factors and a time-dependent effect of statin initiation constrained to 25% risk reduction (from trial results). We compared predictive performance and measures of public-health impact (e.g., number needed to screen to prevent 1 event) against models ignoring statin initiation. During a median follow-up of 8.9 years, 103,163 individuals developed CVD. In models accounting for (versus ignoring) statin initiation, 10-year CVD risk predictions were slightly higher; predictive performance was moderately improved. However, few individuals were reclassified to a high-risk threshold, resulting in negligible improvements in number needed to screen to prevent 1 event. In conclusion, incorporating statin effects from trial results into risk-prediction models enables statin-naive CVD risk estimation and provides moderate gains in predictive ability but had a limited impact on treatment decision-making under current guidelines in this population.

Optimizing Surveillance and Re-intervention Strategy Following Elective Endovascular Repair of Abdominal Aortic Aneurysms.

BACKGROUND: EVAR for abdominal aortic aneurysm has an initial survival advantage over OR, but more frequent complications increase costs and long-term aneurysm-related mortality. Randomized controlled trials of EVAR versus OR have shown EVAR is not cost-effective over a patient's lifetime. However, in the EVAR-1 trial, postoperative surveillance may have been sub-optimal, as the importance of sac growth as a predictor of graft failure was overlooked. METHODS: Real-world data informed a discrete event simulation model of postoperative outcomes following EVAR. Outcomes observed EVAR-1 were compared with those from 5 alternative postoperative surveillance and re-intervention strategies. Key events, quality-adjusted life years and costs were predicted. The impact of using complication and rupture rates from more recent devices, imaging and re-intervention methods was also explored. RESULTS: Compared with observed EVAR-1 outcomes, modeling full adherence to the EVAR-1 scan protocol reduced abdominal aortic aneurysm (AAA) deaths by 3% and increased elective re-interventions by 44%. European Society re-intervention guidelines provided the most clinically effective strategy, with an 8% reduction in AAA deaths, but a 52% increase in elective re-interventions. The cheapest and most cost-effective strategy used lifetime annual ultrasound in primary care with confirmatory computed tomography if necessary, and reduced AAA-related deaths by 5%. Using contemporary rates for complications and rupture did not alter these conclusions. CONCLUSIONS: All alternative strategies improved clinical benefits compared with the EVAR-1 trial. Further work is needed regarding the cost and accuracy of primary care ultrasound, and the potential impact of these strategies in the comparison with OR.

Evaluating the Cost-Effectiveness of Changes to the Surveillance Intervals in the UK Abdominal Aortic Aneurysm Screening Programme.

OBJECTIVES: To investigate the safety and cost-effectiveness of lengthening the time between surveillance ultrasound scans in the UK Abdominal Aortic Aneurysm (AAA) Screening Programme. METHODS: A discrete event simulation model was used to evaluate the cost-effectiveness of AAA screening for men aged 65, comparing current surveillance intervals to 6 alternative surveillance interval strategies that lengthened the time between surveillance scans for 1 or more AAA size categories. The model considered clinical events and costs incurred over a 30-year time horizon and the cost per quality-adjusted life year (QALY). The model adopted the National Health Service perspective and discounted future costs and benefits at 3.5%. RESULTS: Compared with current practice, alternative surveillance strategies resulted in up to a 4% reduction in the number of elective AAA repairs but with an increase of up to 1.6% in the number of AAA ruptures and AAA-related deaths. Alternative strategies resulted in a small reduction in QALYs compared to current practice but with reduced costs. Two strategies that lengthened surveillance intervals in only very small AAAs (3.0-3.9 cm) provided, at a cost-effectiveness threshold of £20 000 per QALY, the highest positive incremental net benefit. There was negligible chance that current practice is the most cost-effective strategy at any threshold below £40 000 per QALY. CONCLUSIONS: Lengthening surveillance intervals in the UK Abdominal Aortic Aneurysm Screening Programme, especially for small AAA, can marginally reduce the incremental cost per QALY of the program. Nevertheless, whether the cost savings from refining surveillance strategies justifies a change in clinical practice is unclear.

Comparison of four methods to measure haemoglobin concentrations in whole blood donors (COMPARE): A diagnostic accuracy study.

OBJECTIVE: To compare four haemoglobin measurement methods in whole blood donors. BACKGROUND: To safeguard donors, blood services measure haemoglobin concentration in advance of each donation. NHS Blood and Transplant's (NHSBT) customary method have been capillary gravimetry (copper sulphate), followed by venous spectrophotometry (HemoCue) for donors failing gravimetry. However, NHSBT's customary method results in 10% of donors being inappropriately bled (ie, with haemoglobin values below the regulatory threshold). METHODS: We compared the following four methods in 21 840 blood donors (aged ≥18 years) recruited from 10 NHSBT centres in England, with the Sysmex XN-2000 haematology analyser, the reference standard: (1) NHSBT's customary method; (2) "post donation" approach, that is, estimating current haemoglobin concentration from that measured by a haematology analyser at a donor's most recent prior donation; (3) "portable haemoglobinometry" (using capillary HemoCue); (4) non-invasive spectrometry (using MBR Haemospect or Orsense NMB200). We assessed sensitivity; specificity; proportion who would have been inappropriately bled, or rejected from donation ("deferred") incorrectly; and test preference. RESULTS: Compared with the reference standard, the methods ranged in test sensitivity from 17.0% (MBR Haemospect) to 79.0% (portable haemoglobinometry) in men, and from 19.0% (MBR Haemospect) to 82.8% (portable haemoglobinometry) in women. For specificity, the methods ranged from 87.2% (MBR Haemospect) to 99.9% (NHSBT's customary method) in men, and from 74.1% (Orsense NMB200) to 99.8% (NHSBT's customary method) in women. The proportion of donors who would have been inappropriately bled ranged from 2.2% in men for portable haemoglobinometry to 18.9% in women for MBR Haemospect. The proportion of donors who would have been deferred incorrectly with haemoglobin concentration above the minimum threshold ranged from 0.1% in men for NHSBT's customary method to 20.3% in women for OrSense. Most donors preferred non-invasive spectrometry. CONCLUSION: In the largest study reporting head-to-head comparisons of four methods to measure haemoglobin prior to blood donation, our results support replacement of NHSBT's customary method with portable haemoglobinometry.

Safety of Men With Small and Medium Abdominal Aortic Aneurysms Under Surveillance in the NAAASP.

BACKGROUND: Population screening for abdominal aortic aneurysm (AAA) has commenced in several countries, and has been shown to reduce AAA-related mortality by up to 50%. Most men who screen positive have an AAA <5.5 cm in diameter, the referral threshold for treatment, and are entered into an ultrasound surveillance program. This study aimed to determine the risk of ruptured AAA (rAAA) in men under surveillance. METHODS: Men in the National Health Service AAA Screening Programme who initially had a small (3-4.4 cm) or medium (4.5-5.4 cm) AAA were followed up. The screening program's database collected data on ultrasound AAA diameter measurements, dates of referral, and loss to follow-up. Local screening programs recorded adverse outcomes, including rAAA and death. Rupture and mortality rates were calculated by initial and final known AAA diameter. RESULTS: A total of 18 652 men were included (50 103 person-years of surveillance). Thirty-one men had rAAA during surveillance, of whom 29 died. Some 952 men died of other causes during surveillance, mainly cardiovascular complications (26.3%) and cancer (31.2%). The overall mortality rate was 1.96% per annum, similar for men with small and medium AAAs. The rAAA risk was 0.03% per annum (95% CI, 0.02%-0.05%) for men with small AAAs and 0.28% (0.17%-0.44%) for medium AAAs. The rAAA risk for men with AAAs just below the referral threshold (5.0-5.4 cm) was 0.40% (0.22%-0.73%). CONCLUSIONS: The risk of rAAA under surveillance is <0.5% per annum, even just below the present referral threshold of 5.5 cm, and only 0.4% of men under surveillance are estimated to rupture before referral. It can be concluded that men with small and medium screen-detected AAAs are safe provided they are enrolled in an intensive surveillance program, and that there is no evidence that the current referral threshold of 5.5 cm should be changed.

Consumption of Meat, Fish, Dairy Products, and Eggs and Risk of Ischemic Heart Disease.

BACKGROUND: There is uncertainty about the relevance of animal foods to the pathogenesis of ischemic heart disease (IHD). We examined meat, fish, dairy products, and eggs and risk for IHD in the pan-European EPIC cohort (European Prospective Investigation Into Cancer and Nutrition). METHODS: In this prospective study of 409 885 men and women in 9 European countries, diet was assessed with validated questionnaires and calibrated with 24-hour recalls. Lipids and blood pressure were measured in a subsample. During a mean of 12.6 years of follow-up, 7198 participants had a myocardial infarction or died of IHD. The relationships of animal foods with risk were examined with Cox regression with adjustment for other animal foods and relevant covariates. RESULTS: The hazard ratio (HR) for IHD was 1.19 (95% CI, 1.06-1.33) for a 100-g/d increment in intake of red and processed meat, and this remained significant after exclusion of the first 4 years of follow-up (HR, 1.25 [95% CI, 1.09-1.42]). Risk was inversely associated with intakes of yogurt (HR, 0.93 [95% CI, 0.89-0.98] per 100-g/d increment), cheese (HR, 0.92 [95% CI, 0.86-0.98] per 30-g/d increment), and eggs (HR, 0.93 [95% CI, 0.88-0.99] per 20-g/d increment); the associations with yogurt and eggs were attenuated and nonsignificant after exclusion of the first 4 years of follow-up. Risk was not significantly associated with intakes of poultry, fish, or milk. In analyses modeling dietary substitutions, replacement of 100 kcal/d from red and processed meat with 100 kcal/d from fatty fish, yogurt, cheese, or eggs was associated with ≈20% lower risk of IHD. Consumption of red and processed meat was positively associated with serum non-high-density lipoprotein cholesterol concentration and systolic blood pressure, and consumption of cheese was inversely associated with serum non-high-density lipoprotein cholesterol. CONCLUSIONS: Risk for IHD was positively associated with consumption of red and processed meat and inversely associated with consumption of yogurt, cheese, and eggs, although the associations with yogurt and eggs may be influenced by reverse causation bias. It is not clear whether the associations with red and processed meat and cheese reflect causality, but they were consistent with the associations of these foods with plasma non-high-density lipoprotein cholesterol and for red and processed meat with systolic blood pressure, which could mediate such effects.

Impact on survival of modelling increased surgical resection rates in patients with non-small-cell lung cancer and cardiovascular comorbidities: a VICORI study.

BACKGROUND: The impact of cardiovascular disease (CVD) comorbidity on resection rates and survival for patients with early-stage non-small-cell lung cancer (NSCLC) is unclear. We explored if CVD comorbidity explained surgical resection rate variation and the impact on survival if resection rates increased. METHODS: Cancer registry data consisted of English patients diagnosed with NSCLC from 2012 to 2016. Linked hospital records identified CVD comorbidities. We investigated resection rate variation by geographical region using funnel plots; resection and death rates using time-to-event analysis. We modelled an increased propensity for resection in regions with the lowest resection rates and estimated survival change. RESULTS: Among 57,373 patients with Stage 1-3A NSCLC, resection rates varied considerably between regions. Patients with CVD comorbidity had lower resection rates and higher mortality rates. CVD comorbidity explained only 1.9% of the variation in resection rates. For every 100 CVD comorbid patients, increasing resection in regions with the lowest rates from 24 to 44% would result in 16 more patients resected and alive after 1 year and two fewer deaths overall. CONCLUSIONS: Variation in regional resection rate is not explained by CVD comorbidities. Increasing resection in patients with CVD comorbidity to the levels of the highest resecting region would increase 1-year survival.

Lifestyle factors and risk of multimorbidity of cancer and cardiometabolic diseases: a multinational cohort study.

BACKGROUND: Although lifestyle factors have been studied in relation to individual non-communicable diseases (NCDs), their association with development of a subsequent NCD, defined as multimorbidity, has been scarcely investigated. The aim of this study was to investigate associations between five lifestyle factors and incident multimorbidity of cancer and cardiometabolic diseases. METHODS: In this prospective cohort study, 291,778 participants (64% women) from seven European countries, mostly aged 43 to 58 years and free of cancer, cardiovascular disease (CVD), and type 2 diabetes (T2D) at recruitment, were included. Incident multimorbidity of cancer and cardiometabolic diseases was defined as developing subsequently two diseases including first cancer at any site, CVD, and T2D in an individual. Multi-state modelling based on Cox regression was used to compute hazard ratios (HR) and 95% confidence intervals (95% CI) of developing cancer, CVD, or T2D, and subsequent transitions to multimorbidity, in relation to body mass index (BMI), smoking status, alcohol intake, physical activity, adherence to the Mediterranean diet, and their combination as a healthy lifestyle index (HLI) score. Cumulative incidence functions (CIFs) were estimated to compute 10-year absolute risks for transitions from healthy to cancer at any site, CVD (both fatal and non-fatal), or T2D, and to subsequent multimorbidity after each of the three NCDs. RESULTS: During a median follow-up of 11 years, 1910 men and 1334 women developed multimorbidity of cancer and cardiometabolic diseases. A higher HLI, reflecting healthy lifestyles, was strongly inversely associated with multimorbidity, with hazard ratios per 3-unit increment of 0.75 (95% CI, 0.71 to 0.81), 0.84 (0.79 to 0.90), and 0.82 (0.77 to 0.88) after cancer, CVD, and T2D, respectively. After T2D, the 10-year absolute risks of multimorbidity were 40% and 25% for men and women, respectively, with unhealthy lifestyle, and 30% and 18% for men and women with healthy lifestyles. CONCLUSION: Pre-diagnostic healthy lifestyle behaviours were strongly inversely associated with the risk of cancer and cardiometabolic diseases, and with the prognosis of these diseases by reducing risk of multimorbidity.

Mixed-effects models for health care longitudinal data with an informative visiting process: A Monte Carlo simulation study.

Electronic health records are being increasingly used in medical research to answer more relevant and detailed clinical questions; however, they pose new and significant methodological challenges. For instance, observation times are likely correlated with the underlying disease severity: Patients with worse conditions utilise health care more and may have worse biomarker values recorded. Traditional methods for analysing longitudinal data assume independence between observation times and disease severity; yet, with health care data, such assumptions unlikely hold. Through Monte Carlo simulation, we compare different analytical approaches proposed to account for an informative visiting process to assess whether they lead to unbiased results. Furthermore, we formalise a joint model for the observation process and the longitudinal outcome within an extended joint modelling framework. We illustrate our results using data from a pragmatic trial on enhanced care for individuals with chronic kidney disease, and we introduce user-friendly software that can be used to fit the joint model for the observation process and a longitudinal outcome.

Analysis of clinical benefit, harms, and cost-effectiveness of screening women for abdominal aortic aneurysm.

BACKGROUND: A third of deaths in the UK from ruptured abdominal aortic aneurysm (AAA) are in women. In men, national screening programmes reduce deaths from AAA and are cost-effective. The benefits, harms, and cost-effectiveness in offering a similar programme to women have not been formally assessed, and this was the aim of this study. METHODS: We developed a decision model to assess predefined outcomes of death caused by AAA, life years, quality-adjusted life years, costs, and the incremental cost-effectiveness ratio for a population of women invited to AAA screening versus a population who were not invited to screening. A discrete event simulation model was set up for AAA screening, surveillance, and intervention. Relevant women-specific parameters were obtained from sources including systematic literature reviews, national registry or administrative databases, major AAA surgery trials, and UK National Health Service reference costs. FINDINGS: AAA screening for women, as currently offered to UK men (at age 65 years, with an AAA diagnosis at an aortic diameter of ≥3·0 cm, and elective repair considered at ≥5·5cm) gave, over 30 years, an estimated incremental cost-effectiveness ratio of £30 000 (95% CI 12 000-87 000) per quality-adjusted life year gained, with 3900 invitations to screening required to prevent one AAA-related death and an overdiagnosis rate of 33%. A modified option for women (screening at age 70 years, diagnosis at 2·5 cm and repair at 5·0 cm) was estimated to have an incremental cost-effectiveness ratio of £23 000 (9500-71 000) per quality-adjusted life year and 1800 invitations to screening required to prevent one AAA-death, but an overdiagnosis rate of 55%. There was considerable uncertainty in the cost-effectiveness ratio, largely driven by uncertainty about AAA prevalence, the distribution of aortic sizes for women at different ages, and the effect of screening on quality of life. INTERPRETATION: By UK standards, an AAA screening programme for women, designed to be similar to that used to screen men, is unlikely to be cost-effective. Further research on the aortic diameter distribution in women and potential quality of life decrements associated with screening are needed to assess the full benefits and harms of modified options. FUNDING: UK National Institute for Health Research Health Technology Assessment programme.

Risk thresholds for alcohol consumption: combined analysis of individual-participant data for 599 912 current drinkers in 83 prospective studies.

BACKGROUND: Low-risk limits recommended for alcohol consumption vary substantially across different national guidelines. To define thresholds associated with lowest risk for all-cause mortality and cardiovascular disease, we studied individual-participant data from 599 912 current drinkers without previous cardiovascular disease. METHODS: We did a combined analysis of individual-participant data from three large-scale data sources in 19 high-income countries (the Emerging Risk Factors Collaboration, EPIC-CVD, and the UK Biobank). We characterised dose-response associations and calculated hazard ratios (HRs) per 100 g per week of alcohol (12·5 units per week) across 83 prospective studies, adjusting at least for study or centre, age, sex, smoking, and diabetes. To be eligible for the analysis, participants had to have information recorded about their alcohol consumption amount and status (ie, non-drinker vs current drinker), plus age, sex, history of diabetes and smoking status, at least 1 year of follow-up after baseline, and no baseline history of cardiovascular disease. The main analyses focused on current drinkers, whose baseline alcohol consumption was categorised into eight predefined groups according to the amount in grams consumed per week. We assessed alcohol consumption in relation to all-cause mortality, total cardiovascular disease, and several cardiovascular disease subtypes. We corrected HRs for estimated long-term variability in alcohol consumption using 152 640 serial alcohol assessments obtained some years apart (median interval 5·6 years [5th-95th percentile 1·04-13·5]) from 71 011 participants from 37 studies. FINDINGS: In the 599 912 current drinkers included in the analysis, we recorded 40 310 deaths and 39 018 incident cardiovascular disease events during 5·4 million person-years of follow-up. For all-cause mortality, we recorded a positive and curvilinear association with the level of alcohol consumption, with the minimum mortality risk around or below 100 g per week. Alcohol consumption was roughly linearly associated with a higher risk of stroke (HR per 100 g per week higher consumption 1·14, 95% CI, 1·10-1·17), coronary disease excluding myocardial infarction (1·06, 1·00-1·11), heart failure (1·09, 1·03-1·15), fatal hypertensive disease (1·24, 1·15-1·33); and fatal aortic aneurysm (1·15, 1·03-1·28). By contrast, increased alcohol consumption was log-linearly associated with a lower risk of myocardial infarction (HR 0·94, 0·91-0·97). In comparison to those who reported drinking >0-≤100 g per week, those who reported drinking >100-≤200 g per week, >200-≤350 g per week, or >350 g per week had lower life expectancy at age 40 years of approximately 6 months, 1-2 years, or 4-5 years, respectively. INTERPRETATION: In current drinkers of alcohol in high-income countries, the threshold for lowest risk of all-cause mortality was about 100 g/week. For cardiovascular disease subtypes other than myocardial infarction, there were no clear risk thresholds below which lower alcohol consumption stopped being associated with lower disease risk. These data support limits for alcohol consumption that are lower than those recommended in most current guidelines. FUNDING: UK Medical Research Council, British Heart Foundation, National Institute for Health Research, European Union Framework 7, and European Research Council.

Separate and combined associations of obesity and metabolic health with coronary heart disease: a pan-European case-cohort analysis.

Aims: The hypothesis of 'metabolically healthy obesity' implies that, in the absence of metabolic dysfunction, individuals with excess adiposity are not at greater cardiovascular risk. We tested this hypothesis in a large pan-European prospective study. Methods and results: We conducted a case-cohort analysis in the 520 000-person European Prospective Investigation into Cancer and Nutrition study ('EPIC-CVD'). During a median follow-up of 12.2 years, we recorded 7637 incident coronary heart disease (CHD) cases. Using cut-offs recommended by guidelines, we defined obesity and overweight using body mass index (BMI), and metabolic dysfunction ('unhealthy') as ≥ 3 of elevated blood pressure, hypertriglyceridaemia, low HDL-cholesterol, hyperglycaemia, and elevated waist circumference. We calculated hazard ratios (HRs) and 95% confidence intervals (95% CI) within each country using Prentice-weighted Cox proportional hazard regressions, accounting for age, sex, centre, education, smoking, diet, and physical activity. Compared with metabolically healthy normal weight people (reference), HRs were 2.15 (95% CI: 1.79; 2.57) for unhealthy normal weight, 2.33 (1.97; 2.76) for unhealthy overweight, and 2.54 (2.21; 2.92) for unhealthy obese people. Compared with the reference group, HRs were 1.26 (1.14; 1.40) and 1.28 (1.03; 1.58) for metabolically healthy overweight and obese people, respectively. These results were robust to various sensitivity analyses. Conclusion: Irrespective of BMI, metabolically unhealthy individuals had higher CHD risk than their healthy counterparts. Conversely, irrespective of metabolic health, overweight and obese people had higher CHD risk than lean people. These findings challenge the concept of 'metabolically healthy obesity', encouraging population-wide strategies to tackle obesity.

Biases incurred from nonrandom repeat testing of haemoglobin levels in blood donors: Selective testing and its implications.

To help prevent anaemia, it is a requisite for blood donors to undergo a haemoglobin test to ensure levels are not too low before donation. It is therefore important to have an accurate testing device and strategy to ensure donors are not being inappropriately bled. A recent study in blood donors used a selective testing strategy where if a donor's haemoglobin level is below the level required for donation, then another reading is taken and if this occurs again, a third and final reading is used. This strategy can reduce the average number of readings required per donor compared to taking three measurements for all donors. However, the final decision-making measurement will on average be higher than a single measurement. In this paper, a selective testing strategy is compared against other strategies. Individual-level biases are derived for the selective strategy and are shown to depend on how close a donor's true haemoglobin level is to the donation threshold and the magnitude of error in the testing device. A simulation study was conducted using the distribution of haemoglobin levels from a large donor population to investigate the effects different strategies have on population performance. We consider scenarios based on varying the measurement device bias and error, including differential biases that depend on the underlying haemoglobin level. Discriminatory performance is shown to be affected when using the selective testing strategies, especially when measurement error is large and when differential bias is present in the device. We recommend that the average of a number of readings should be used in preference to selective testing strategies if multiple measurements are available.

Landmark Models for Optimizing the Use of Repeated Measurements of Risk Factors in Electronic Health Records to Predict Future Disease Risk.

The benefits of using electronic health records (EHRs) for disease risk screening and personalized health-care decisions are being increasingly recognized. Here we present a computationally feasible statistical approach with which to address the methodological challenges involved in utilizing historical repeat measures of multiple risk factors recorded in EHRs to systematically identify patients at high risk of future disease. The approach is principally based on a 2-stage dynamic landmark model. The first stage estimates current risk factor values from all available historical repeat risk factor measurements via landmark-age-specific multivariate linear mixed-effects models with correlated random intercepts, which account for sporadically recorded repeat measures, unobserved data, and measurement errors. The second stage predicts future disease risk from a sex-stratified Cox proportional hazards model, with estimated current risk factor values from the first stage. We exemplify these methods by developing and validating a dynamic 10-year cardiovascular disease risk prediction model using primary-care EHRs for age, diabetes status, hypertension treatment, smoking status, systolic blood pressure, total cholesterol, and high-density lipoprotein cholesterol in 41,373 persons from 10 primary-care practices in England and Wales contributing to The Health Improvement Network (1997-2016). Using cross-validation, the model was well-calibrated (Brier score = 0.041, 95% confidence interval: 0.039, 0.042) and had good discrimination (C-index = 0.768, 95% confidence interval: 0.759, 0.777).