Search

Background: Joinpoint regression analysis is usually applied to study varying trends over time in order to identify the time point(s) in which the trend significantly changes. We illustrate three epidemiological investigations in which this methodology was applied with time-on-study as time-scale. Methods: Data were retrieved from the healthcare utilization databases of Lombardy Region (Italy). We investigated the trend of the: (1) mortality rate among centenarians hospitalized for hip fracture (2004-2011); (2) proportion of persistent patients after the initial prescription of antihypertensive drugs during the first year of treatment according to gender (2005); (3) prescription rate of statins in the year before and after the hospital admission among patients hospitalized for a transient ischemic attack (2008-2009). Results: The following results were obtained: (1) a joinpoint was identified in the fourth month, showing an increased risk of death during the three months after hip fracture hospitalization; (2) the proportion of patients still under antihypertensive treatment falls until the fifth month, remaining stable afterwards; there was evidence that the prevalence of patients who discontinued the treatment was significantly higher among women than men; (3) during the year after the transient ischemic attack episode, monthly rate of available statins was double than the previous year with a significant decrease in the first four months. Conclusions: The joinpoint regression analysis can be a useful tool in epidemiologic framework when a temporal trend is the objective of the investigation since it allows to make inference by means of a quantitative method rather than a qualitative evaluation.

Real-world evidence can provide answers on healthcare utilization and appropriateness, post-marketing drugs safety and comparative effectiveness, and cost-effectiveness profiles of healthcare pathways. Healthcare utilization databases, possibly integrated with drug and disease registries, electronic medical records, survey and cohort data (i.e. real-world data), allow to trace healthcare ‘footprints’ left from beneficiaries of National Health Service. Beaver is a research platform available on demand to Italian regions which we developed for computing indicators of healthcare utilization and clinical outcomes, as well as for generating evidence on effectiveness and cost-effectiveness profile. Two distinct solutions may be adopted. One, the so-called Beaver Light front-end allows to automatically compute health indicators of adherence to official guidelines. Two, the so-called Beaver Full front-end involves an eight-step procedure entirely driven by the study protocol. In order to fulfil the directives recently issued by the European Parliament and Council and the Italian Authority for the protection of individual data, the platform resides in each region’s infrastructure, so limiting the free movement of electronic health data. Indeed, regional authorities should be responsible for data safety and for allowing data accessibility. The use of standardized and validated algorithms enables to obtain regional estimates that, being obtained by employing regional platforms containing data extracted with standardized procedure, may be compared and possibly summarized by using common meta-analytic techniques. In conclusion, the Beaver regional platform is a promising tool which may contribute to stimulate healthcare research in Italy.

BACKGROUND. Statins, are to date the most effective drugs for the treatment of hypercholesterolemia, and their important protective role in the prevention of cardiovascular (CV) morbidity and mortality is well-established [1]. Since people aged between 60 and 79 years were well represented in many trials, this applies also to elderly patients [2]. However, it does not apply to patients aged 80 years or older, because (i) none or few octogenarians have been included in outcome-based trials and (ii) evidence on the protective effects of statins among them is limited to only few observational studies with inconsistent results [3,4]. This represents an important limitation because the increasing life expectancy makes octogenarians the fastest growing subgroup of the population and, furthermore, this highly advanced aged subgroup accounts for a considerable portion of the overall CV events, hospitalizations and deaths [5]. AIM. To assess whether in individuals aged 80 years or older adherence to statins is accompanied by a reduced risk of all-cause mortality and major cardiovascular events. METHODS. A nested case–control study was carried out including a cohort of patients aged 80 years or older, who were under treatment with statins between 2008 and 2009, using the administrative databases of Lombardy region (Italy). Cases were the cohort members who experienced death or hospitalization for stroke, myocardial infarction or heart failure from the initial prescription until 2012. Up to five controls were randomly selected for each case. Logistic regression was fitted to estimate the odds ratio (OR), and its 95% confidence interval (CI), for the considered outcomes in relation to the adherence to therapy with statins, measured by the proportion of days covered (PDC). Four categories of adherence were employed (i.e., <25%, 25-49%, 50-74%, >=75%), using the lowest one (<25%) as reference. Two younger patient cohorts aged 60 to 69 years and 70 to 79 years were taken for compa