Cardiovascular disease and its impact on longevity and longevity improvement

An increased risk or a history of cardiovascular disease (CVD) is associated with worse survival prospects. Clinical guidelines recommend several treatments for primary and secondary prevention. These guidelines are mainly based on clinical trials and hospital data. Data from routine clinical practice could provide insights in longevity and longevity improvement in the general population as opposed to selected patients. The primary objectives of this research were to investigate how a history of CVD affects longevity in residents of the United Kingdom at retirement age, and to investigate which treatments improve longevity. Medical records from 1987 to 2011 from general practices contributing to The Health Improvement Network (THIN) database were used to develop two specific survival models: to estimate the hazards of all-cause mortality associated with a history of acute myocardial infarction (AMI) and related treatments, and to estimate the hazard of all-cause mortality associated with statins prescribed as primary prevention of CVD. The models were multilevel Cox's proportional hazards regressions that included comorbidities, treatments, lifestyle choices, and socio-demographic factors. The models were specified for ages 60, 65, 70, and 75. More accurate estimates of longevity at these key ages could inform future medical management by clinicians and financial planning for retirement by individuals, actuaries, and the government. This research found that survival prospects after AMI were reduced by less than previous studies have reported. Furthermore, currently recommended treatments for CVD were associated with mixed survival prospects, in which coronary revascularisation and prescription of beta blockers and statins were associated with improved prospects and prescription of ACE inhibitors and aspirin were associated with worsened prospects

How medical advances and health interventions will shape future longevity

Medicine-related research includes numerous studies on the hazards of mortality and what risk factors are associated with these hazards, such as diseases and treatments. These hazards are estimated in a sample of people and summarised over the observed period. From these observations, inferences can be made about the underlying population and consequently inform medical guidelines for intervention. New health interventions are usually based on these estimated hazards obtained from clinical trials. A lengthy lead time would be needed to observe their effect on population longevity. This paper shows how estimated mortality hazards can be translated to hypothetical changes in life expectancies at the individual and population levels. For an individual, the relative hazards are translated into the number of years gained or lost in “effective age”, which is the average chronological age with the same risk profile. This translation from hazard ratio to effective age could be used to explain to individuals the consequences of various diseases and lifestyle choices and as a result persuade clients in life and health insurance to pursue a healthier lifestyle. At the population level, a period life expectancy is a weighted average of component life expectancies associated with the particular risk profiles, with the weights defined by the prevalences of the risk factor of interest and the uptake of the relevant intervention. Splitting the overall life expectancy into these components allows us to estimate hypothetical changes in life expectancy at the population level at different morbidity and uptake scenarios. These calculations are illustrated by two examples of medical interventions and their impact on life expectancy, which are beta blockers in heart attack survivors and blood pressure treatment in hypertensive patients. The second example also illustrates the dangers of applying the results from clinical trials to much wider populations

Statins: figures on the pulse, in: The Actuary (August 2018)

Medical advances are the major drivers in the longevity increase. But how to quantify this relationship? Our research, funded by the Actuarial Research Centre (ARC), uses The Health Improvement Network (THIN) primary care data to develop statistical models of longevity, given a particular chronic medical condition or intervention

Survival prospects after acute myocardial infarction in the UK: a matched cohort study 1987–2011

Objectives: Estimate survival after acute myocardial infarction (AMI) in the general population aged 60 and over, and the effect of recommended treatments. Design: Cohort study in the United Kingdom with routinely collected data between January 1987 and March 2011. Setting: 310 general practices that contributed to The Health Improvement Network (THIN) database. Participants: Four cohorts who reached the age of 60, 65, 70, or 75 years between 1987 and 2011 included 16,744, 43,528, 73,728, and 76,392 participants, respectively. Participants with a history of AMI were matched on sex, year of birth, and general practice to three controls each. Outcome measures: The hazard of all-cause mortality associated with AMI was calculated by a multilevel Cox’s proportional hazards regression, adjusted for sex, year of birth, socioeconomic status, angina, heart failure, other cardiovascular conditions, chronic kidney disease, diabetes, hypertension, hypercholesterolaemia, alcohol consumption, body mass index, smoking status, coronary revascularisation, prescription of beta blockers, ACE inhibitors, calcium-channel blockers, aspirin, or statins, and general practice. Results: Compared to no history of AMI by age 60, 65, 70, or 75, having had one AMI was associated with an adjusted hazard of mortality of 1.80 (95% CI 1.60-2.02), 1.71 (1.59-1.84), 1.50 (1.42-1.59), or 1.45 (1.38-1.53), respectively, and having had multiple AMIs with a hazard of 1.92 (1.60-2.29), 1.87 (1.68-2.07), 1.66 (1.53-1.80), or 1.63 (1.51-1.76), respectively. Survival was better after statins (hazard ratio range across the four cohorts 0.74-0.81), beta blockers (0.79-0.85), or coronary revascularisation (in first five years) (0.72-0.80); unchanged after calcium-channel blockers (1.00-1.07); and worse after aspirin (1.05-1.10) or ACE inhibitors (1.10-1.25). Conclusions: The hazard of death after AMI is less than reported by previous studies, and standard treatments of aspirin or ACE inhibitors prescription may be of little benefit or even cause harm

Survival benefits of statin therapy in primary care: landmark analyses

Statins have been widely prescribed for primary and secondary prevention of cardiovascular disease since clinical trials have demonstrated the survival benefits. However, the threshold of cardiac risk at which to prescribe statins is still controversial, especially at older ages when everyone would be eligible solely due to their age. Our study aim was to dynamically predict the survival benefits associated with statin therapy over the course of 25 years in patients aged 60 residential in England or Wales

The ideal blood pressure: assessment of fixed and variant targets over time in clinical trial and routine clinical practice

Recent evaluation of the research evidence on blood pressure thresholds for intervention by the Scottish Intercollegiate Guidelines Network (SIGN) and the American Heart Association (AHA) led to different updated hypertension guidelines. The question remains what the ideal blood pressure is in hypertensive patients. In clinical trials, blood pressure targets are fixed and blood pressure is treated accordingly during the intervention time, however this is done in a selective group of patients for a relatively short follow-up of less than five years. In routine clinical practice, patients are observed during most of their lifetime and sequential treatment decisions are made in treating blood pressure according to the latest guideline. These data qualities make the assessment of blood pressure targets complex. In this study, various Cox’s proportional hazards regression models were fitted to assess the time-variant effect of blood pressure targets on survival and chronic kidney disease outcomes (main adverse effect of antihypertensive treatment) using US Systolic Blood Pressure Intervention Trial (SPRINT) data and UK The Health Improvement Network (THIN) primary care data. The studied systolic blood pressure targets were <140 mmHg (standard treatment in routine clinical practice in the UK and previously also in the US) and <120 mmHg (intensive treatment). This work was supported by the Institute and Faculty of Actuaries (IFoA) and by the Business and Local Government Data Research Centre [grant ES/L011859/1]

Perinatal outcomes of frequent attendance in midwifery care in the Netherlands: a retrospective cohort study

Background Over the last decade, a trend towards high utilisation of primary maternity care was observed in high-income countries. There is limited research with contradictory results regarding frequent attendance (FA) and perinatal outcomes in midwifery care. Therefore, this study examined possible associations between FA in midwifery care and obstetric interventions and perinatal outcomes. Methods A retrospective cohort study was performed in a medium-sized midwifery-led care practice in an urban region in the Netherlands. Frequent attenders (FAs) were categorised using the Kotelchuck-Index Revised. Regression analyses were executed to examine the relationship between FAs and perinatal outcomes, stratified by antenatal referral to an obstetrician. Main outcomes of interest were Apgar score ≤ 7 and perinatal death, birth weight, mode of delivery, haemorrhage, place of birth, transfer during labour, and a requirement for pain relief. Results The study included 1015 women, 239 (24%) FAs and 776 (76%) non-FAs, 538 (53%) were not referred and 447 (47%) were referred to an obstetrician. In the non-referred group, FA was significantly associated with a requirement for pain relief (OR 1.98, 95% CI 1.24–3.17) and duration of dilatation (OR 1.20, 95% CI 1.04–1.38). In the referred group, FA was significantly associated with induction of labour (OR 1.86, 95% CI 1.17–2.95), ruptured perineum (OR 0.50, 95% CI 0.27–0.95) and episiotomy (OR 0.48, 95% CI 0.24–0.95). In the non-referred and the referred group, FA was not associated with the other obstetric and neonatal outcomes. Due to small numbers, we could not measure possible associations of FA with an Apgar score ≤ 7 and perinatal death. Conclusion In our study, perinatal outcomes differed by FA and antenatal referral to an obstetrician. In the non-referred group, FA was significantly associated with medical pain relief and duration of dilatation. In the referred group, FA was significantly associated with induction of labour, ruptured perineum, and episiotomy. Further research with a larger study population is needed to look for a possible association between FA and primary adverse birth outcomes such as perinatal mortality

Outcomes of blood pressure targets in clinical trial versus primary care setting

Objective: The primary objective was to compare outcomes of different systolic blood pressure (SBP) targets in the US clinical setting and the UK primary care setting. / Methods: Data from the SPRINT randomised control trial and The Health Improvement Network (THIN) primary care database were used to develop survival models for longevity and adverse renal outcome (ARO, main adverse effect) at different SBP targets given treatment in people without diabetes and chronic kidney disease. The hazard of all-cause mortality or ARO associated with SBP targets was calculated by a multilevel Cox’s proportional hazards regression, adjusted for sex, age, race, smoking, BMI, SBP, cardiovascular disease, number of antihypertensive agents at baseline, additional medication after trial entry, their interaction, and clinical site. / Results: Compared to SBP target of ≤120 mmHg, SBP target of ≤140 mmHg was associated with increased hazard of mortality of 1.42 (1.06-1.90) in SPRINT, but with decreased hazard of 0.70 (0.65-0.76) in THIN. Both in SPRINT and THIN, SBP target of ≤140 mmHg was associated with decreased hazard of ARO of 0.32 (0.22-0.46) and 0.87 (0.80-0.95), respectively. Additional antihypertensive agents (3+) were associated with increased hazards of both outcomes, with HRs of 1.71-1.74 in SPRINT and 1.43-2.23 in THIN, yet being on 2 agents had survival benefits in SPRINT (HRs 0.70-0.79). / Conclusions: Lower SBP target was associated with survival benefits in the clinical setting, but with increased hazard of mortality in the primary care setting. In both settings, polypharmacy patients tended to be worse off. An intensive control of SBP may benefit a selected subgroup of patients, but it appears harmful for the broader population