Polycystic ovary syndrome (PCOS) is a common heterogeneous endocrine disorder characterized by irregular menses, hyperandrogenism, and polycystic ovaries. The prevalence of PCOS varies depending on which criteria are used to make the diagnosis, but is as high as 15%-20% when the European Society for Human Reproduction and Embryology/American Society for Reproductive Medicine criteria are used. Clinical manifestations include oligomenorrhea or amenorrhea, hirsutism, and frequently infertility. Risk factors for PCOS in adults includes type 1 diabetes, type 2 diabetes, and gestational diabetes. Insulin resistance affects 50%-70% of women with PCOS leading to a number of comorbidities including metabolic syndrome, hypertension, dyslipidemia, glucose intolerance, and diabetes. Studies show that women with PCOS are more likely to have increased coronary artery calcium scores and increased carotid intima-media thickness. Mental health disorders including depression, anxiety, bipolar disorder and binge eating disorder also occur more frequently in women with PCOS. Weight loss improves menstrual irregularities, symptoms of androgen excess, and infertility. Management of clinical manifestations of PCOS includes oral contraceptives for menstrual irregularities and hirsutism. Spironolactone and finasteride are used to treat symptoms of androgen excess. Treatment options for infertility include clomiphene, laparoscopic ovarian drilling, gonadotropins, and assisted reproductive technology. Recent data suggest that letrozole and metformin may play an important role in ovulation induction. Proper diagnosis and management of PCOS is essential to address patient concerns but also to prevent future metabolic, endocrine, psychiatric, and cardiovascular complications.
With the aging of the population, the burden of Alzheimer's disease (AD) is rapidly expanding. More than 5 million people in the US alone are affected with AD and this number is expected to triple by 2050. While men may have a higher risk of mild cognitive impairment (MCI), an intermediate stage between normal aging and dementia, women are disproportionally affected with AD. One explanation is that men may die of competing causes of death earlier in life, so that only the most resilient men may survive to older ages. However, many other factors should also be considered to explain the sex differences. In this review, we discuss the differences observed in men versus women in the incidence and prevalence of MCI and AD, in the structure and function of the brain, and in the sex-specific and gender-specific risk and protective factors for AD. In medical research, sex refers to biological differences such as chromosomal differences (eg, XX versus XY chromosomes), gonadal differences, or hormonal differences. In contrast, gender refers to psychosocial and cultural differences between men and women (eg, access to education and occupation). Both factors play an important role in the development and progression of diseases, including AD. Understanding both sex-and gender-specific risk and protective factors for AD is critical for developing individualized interventions for the prevention and treatment of AD.
Sjogren's syndrome is a chronic systemic autoimmune disease characterized by lymphocytic infiltration of exocrine glands. It can present as an entity by itself, primary Sjogren's syndrome (pSS), or in addition to another autoimmune disease, secondary Sjogren's syndrome (sSS). pSS has a strong female propensity and is more prevalent in Caucasian women, with the mean age of onset usually in the 4th to 5th decade. Clinical presentation varies from mild symptoms, such as classic sicca symptoms of dry eyes and dry mouth, keratoconjunctivitis sicca, and xerostomia, to severe systemic symptoms, involving multiple organ systems. Furthermore, a range of autoantibodies can be present in Sjogren's syndrome (anti-SSA/Ro and anti-SSB/La antibodies, rheumatoid factor, cryoglobulins, antinuclear antibodies), complicating the presentation. The heterogeneity of signs and symptoms has led to the development of multiple classification criteria. However, there is no accepted universal classification criterion for the diagnosis of Sjogren's syndrome. There are a limited number of studies that have been published on the epidemiology of Sjogren's syndrome, and the incidence and prevalence of the disease varies according to the classification criteria used. The data is further confounded by selection bias and misclassification bias, making it difficult for interpretation. The aim of this review is to understand the reported incidence and prevalence on pSS and sSS, the frequency of autoantibodies, and the risk of malignancy, which has been associated with pSS, taking into account the different classification criteria used.
A number of studies have shown poorer survival among cancer patients with comorbidity. Several mechanisms may underlie this finding. In this review we summarize the current literature on the association between patient comorbidity and cancer prognosis. Prognostic factors examined include tumor biology, diagnosis, treatment, clinical quality, and adherence. All English-language articles published during 2002-2012 on the association between comorbidity and survival among patients with colon cancer, breast cancer, and lung cancer were identified from PubMed, MEDLINE and Embase. Titles and abstracts were reviewed to identify eligible studies and their main results were then extracted. Our search yielded more than 2,500 articles related to comorbidity and cancer, but few investigated the prognostic impact of comorbidity as a primary aim. Most studies found that cancer patients with comorbidity had poorer survival than those without comorbidity, with 5-year mortality hazard ratios ranging from 1.1 to 5.8. Few studies examined the influence of specific chronic conditions. In general, comorbidity does not appear to be associated with more aggressive types of cancer or other differences in tumor biology. Presence of specific severe comorbidities or psychiatric disorders were found to be associated with delayed cancer diagnosis in some studies, while chronic diseases requiring regular medical visits were associated with earlier cancer detection in others. Another finding was that patients with comorbidity do not receive standard cancer treatments such as surgery, chemotherapy, and radiation therapy as often as patients without comorbidity, and their chance of completing a course of cancer treatment is lower. Postoperative complications and mortality are higher in patients with comorbidity. It is unclear from the literature whether the apparent undertreatment reflects appropriate consideration of greater toxicity risk, poorer clinical quality, patient preferences, or poor adherence among patients with comorbidity. Despite increasing recognition of the importance of comorbid illnesses among cancer patients, major challenges remain. Both treatment effectiveness and compliance appear compromised among cancer patients with comorbidity. Data on clinical quality is limited.
Missing data are ubiquitous in clinical epidemiological research. Individuals with missing data may differ from those with no missing data in terms of the outcome of interest and prognosis in general. Missing data are often categorized into the following three types: missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR). In clinical epidemiological research, missing data are seldom MCAR. Missing data can constitute considerable challenges in the analyses and interpretation of results and can potentially weaken the validity of results and conclusions. A number of methods have been developed for dealing with missing data. These include complete-case analyses, missing indicator method, single value imputation, and sensitivity analyses incorporating worst-case and best-case scenarios. If applied under the MCAR assumption, some of these methods can provide unbiased but often less precise estimates. Multiple imputation is an alternative method to deal with missing data, which accounts for the uncertainty associated with missing data. Multiple imputation is implemented in most statistical software under the MAR assumption and provides unbiased and valid estimates of associations based on information from the available data. The method affects not only the coefficient estimates for variables with missing data but also the estimates for other variables with no missing data.
Both the use of antidepressant medication during pregnancy and the prevalence of autism spectrum disorder have increased during recent years. A causal link has recently been suggested, but the association may be confounded by the underlying indication for antidepressant use. We investigated the association between maternal use of antidepressant medication in pregnancy and autism, controlling for potential confounding factors. We identified all children born alive in Denmark 1996-2006 (n=668,468) and their parents in the Danish Civil Registration System. We obtained information on the mother's prescriptions filled during pregnancy from the Danish National Prescription Registry, and on diagnoses of autism spectrum disorders in the children and diagnoses of psychiatric disorders in the parents from the Danish Psychiatric Central Register. In a cohort analysis, we estimated hazard ratios of autism spectrum disorders in children exposed to antidepressant medication during pregnancy compared with children who were not exposed, using Cox proportional hazards regression analysis. Furthermore, we estimated the risk for autism spectrum disorder in a sibling design. Children exposed prenatally to antidepressants had an adjusted hazard ratio of 1.5 (95% confidence interval [CI] 1.2-1.9) for autism spectrum disorder compared with unexposed children. Restricting the analysis to children of women with a diagnosis of affective disorder, the adjusted hazard ratio was 1.2 (95% CI 0.7-2.1), and the risk was further reduced when exposed children were compared with their unexposed siblings (adjusted hazard ratio 1.1; 95% CI 0.5-2.3). After controlling for important confounding factors, there was no significant association between prenatal exposure to antidepressant medication and autism spectrum disorders in the offspring.
The Danish health care system provides partial reimbursement of most prescription medications in Denmark. The dispensation of prescription medications is registered in administrative databases. Each time a prescription is redeemed at a pharmacy, an electronic record is generated with information related to the user, prescriber, the pharmacy, and the dispensed drug. The National Health Service gathers this information for administration of the drug reimbursement plan. Recently, this information became the basis for the establishment of a new research database, the Danish National Database of Reimbursed Prescriptions (DNDRP). In this paper, we review the content, coverage, quality, linkage, access, and research possibilities of this new database. The database encompasses the reimbursement records of all reimbursed drugs sold in community pharmacies and hospital-based outpatient pharmacies in Denmark since 2004. On average, approximately 3.5 million users are recorded in the database each year. During the coverage period, the number of annual prescription redemptions increased by 15%. Most dispensed prescriptions are in the categories "alimentary tract and metabolism", "cardiovascular system", "nervous system", and "respiratory system". Individuals are identified by the unique central personal registration (CPR) number assigned to all persons born in or immigrating to Denmark. The new database fully complies with Denmark's Act on Processing of Personal Data, while avoiding additional restrictions imposed on data use at the Danish National Prescription Registry, administered by Statistics Denmark. Most importantly, CPR numbers are reversibly encrypted, which allows re-identification of drug users; furthermore, the data access is possible outside the servers of Statistics Denmark. These features open additional opportunities for international collaboration, validation studies, studies on adverse drug effects requiring review of medical records, studies involving contact to general practitioners, and linkage of prescription data to other clinical and research databases. The DNDRP thus is a valuable data source for pharmacoepidemiological research.
Describing the relationship between socioeconomic inequalities and cancer survival is important but methodologically challenging. We propose guidelines for addressing these challenges and illustrate their implementation on French population-based data. We analyzed 17 cancers. Socioeconomic deprivation was measured by an ecological measure, the European Deprivation Index (EDI). The Excess Mortality Hazard (EMH), ie, the mortality hazard among cancer patients after accounting for other causes of death, was modeled using a flexible parametric model, allowing for nonlinear and/or time-dependent association between the EDI and the EMH. The model included a cluster-specific random effect to deal with the hierarchical structure of the data. We reported the conventional age-standardized net survival (ASNS) and described the changes of the EMH over the time since diagnosis at different levels of deprivation. We illustrated nonlinear and/or time-dependent associations between the EDI and the EMH by plotting the excess hazard ratio according to EDI values at different times after diagnosis. The median excess hazard ratio quantified the general contextual effect. Lip-oral cavity-pharynx cancer in men showed the widest deprivation gap, with 5-year ASNS at 41% and 29% for deprivation quintiles 1 and 5, respectively, and we found a nonlinear association between the EDI and the EMH. The EDI accounted for a substantial part of the general contextual effect on the EMH. The association between the EDI and the EMH was time dependent in stomach and pancreas cancers in men and in cervix cancer. The methodological guidelines proved efficient in describing the way socioeconomic inequalities influence cancer survival. Their use would allow comparisons between different health care systems.
Background: The validity of the registration of patients in stroke-specific registries has seldom been investigated, nor compared with administrative hospital discharge registries. The objective of this study was to examine the validity of the registration of patients in a stroke-specific registry (The Danish Stroke Registry [DSR]) and a hospital discharge registry (The Danish National Patient Registry [DNRP]). Methods: Assuming that all patients with stroke were registered in either the DSR, DNRP or both, we first identified a sample of 75 patients registered with stroke in 2009; 25 patients in the DSR, 25 patients in the DNRP, and 25 patients registered in both data sources. Using the medical record as a gold standard, we then estimated the sensitivity and positive predictive value of a stroke diagnosis in the DSR and the DNRP. Secondly, we reviewed 160 medical records for all potential stroke patients discharged from four major neurologic wards within a 7-day period in 2010, and estimated the sensitivity, specificity, positive predictive value, and negative predictive value of the DSR and the DNRP. Results: Using the first approach, we found a sensitivity of 97% (worst/best case scenario 92%-99%) in the DSR and 79% (worst/best case scenario 73%-84%) in the DNRP. The positive predictive value was 90% (worst/best case scenario 72%-98%) in the DSR and 79% (worst/best case scenario 62%-88%) in the DNRP. Using the second approach, we found a sensitivity of 91% (95% confidence interval [CI] 81%-96%) and 58% (95% CI 46%-69%) in the DSR and DNRP, respectively. The negative predictive value was 91% (95% CI 83%-96%) in the DSR and 72% (95% CI 62%-80%) in the DNRP. The specificity and positive predictive value did not differ among the registries. Conclusion: Our data suggest a higher sensitivity in the DSR than the DNRP for acute stroke diagnoses, whereas the positive predictive value was comparable in the two data sources.
Background: Due to over-the-counter availability, no consensus exists on whether adequate information on nonsteroidal anti-inflammatory drug (NSAID) use can be obtained from prescription registries. Objectives: To examine utilization of aspirin and nonaspirin NSAIDs in Denmark between 1999 and 2012 and to quantify the proportion of total sales that was sold on prescription. Method: Based on nationwide data from the Danish Serum Institute and the Danish National Prescription Registry, we retrieved sales statistics for the Danish primary health care sector to calculate 1-year prevalences of prescription users of aspirin or nonaspirin NSAIDs, and to estimate the corresponding proportions of total sales dispensed on prescription. Results: Both low-dose aspirin and nonaspirin NSAIDs were commonly used in the Danish population between 1999 and 2012, particularly among elderly individuals. The 1-year prevalence of prescribed low-dose aspirin increased throughout the study period, notably among men. Nonaspirin NSAID use was frequent in all age groups above 15 years and showed a female preponderance. Overall, the prevalence of prescribed nonaspirin NSAIDs decreased moderately after 2004, but substantial variation according to NSAID subtype was observed; ibuprofen use increased, use of all newer selective cyclooxygenase-2 inhibitors nearly ceased after 2004, diclofenac use decreased by nearly 50% after 2008, and naproxen use remained stable. As of 2012, the prescribed proportion of individual-level NSAID sales was 92% for low-dose aspirin, 66% for ibuprofen, and 100% for all other NSAIDs. Conclusion: The potential for identifying NSAID use from prescription registries in Denmark is high. Low-dose aspirin and nonaspirin NSAID use varied substantially between 1999 and 2012. Notably, use of cyclooxygenase-2 inhibitors nearly ceased, use of diclofenac decreased markedly, and naproxen use remained unaltered.
Background: PRE2DUP is a modeling method that generates drug use periods (ie, when drug use started and ended) from drug purchases recorded in dispensing-based register data. It is based on the evaluation of personal drug purchasing patterns and considers hospital stays, possible stockpiling of drugs, and package information. Objective: The objective of this study was to investigate person-level agreement between self-reported drug use in the interview and drug use modeled from dispensing data with PRE2DUP method for various drug classes used by older persons. Methods: Self-reported drug use was assessed from the GeMS Study including a random sample of persons aged >= 75 years from the city of Kuopio, Finland, in 2006. Drug purchases recorded in the Prescription register data of these persons were modeled to determine drug use periods with PRE2DUP modeling method. Agreement between self-reported drug use on the interview date and drug use calculated from register-based data was compared in order to find the frequently used drugs and drug classes, which was evaluated by Cohen's kappa. Kappa values 0.61-0.80 were considered to represent good and 0.81-1.00 as very good agreement. Results: Among 569 participants with mean age of 82 years, the agreement between interview and register data was very good for 75% and very good or good for 93% of the studied drugs or drug classes. Good or very good agreement was observed for drugs that are typically used on regular bases, whereas "as needed" drugs represented poorer results. Conclusion: PRE2DUP modeling method validly describes regular drug use among older persons. For most of drug classes investigated, PRE2DUP-modeled register data described drug use as well as interview-based data which are more time-consuming to collect. Further studies should be conducted by comparing it with other methods and in different drug user populations.
Population-based prescription databases in Nordic countries have become a mainstay of epidemiologic research. Denmark has both national and regional population-based prescription databases. Aarhus University Prescription Database collects data on reimbursed medications dispensed at all community pharmacies of the North Denmark Region and the Central Denmark Region. The regions have a combined population of 1.8 million inhabitants, or one-third of the Danish population. Denmark's primary health care sector, which includes general practitioners, specialists, and dentists, generates about 96% of the prescription sales, most of which are reimbursable and are dispensed by the community pharmacies. The Aarhus University Prescription Database combines the region's pharmacy records in a single database, maintained and updated for research purposes. Each dispensation record contains patient-, drug-, and prescriber-related data. Dispensation records retain patients' universal personal identifier, which allows for individual-level linkage to all Danish registries and medical databases. The linked data have many applications in clinical epidemiology, including drug utilization studies, safety monitoring, etiologic research, and validation studies.
Heart failure (HF) is a prevalent chronic disease in older adults that requires extensive self-care to prevent decompensation and hospitalization. Cognitive impairment may impact the ability to perform HF self-care activities. We examined the association between cognitive impairment and adherence to self-care in patients hospitalized for acute HF. Prospective cohort study. A total of 577 patients (mean age = 71 years, 44% female) hospitalized for HF at five medical centers in the United States and Canada. Participants were interviewed for information on self-reported adherence to self-care using the European Heart Failure Self-care Behaviour Scale. We assessed cognitive impairment in three domains (memory, processing speed, and executive function) using standardized measures. Patients' demographic and clinical characteristics were obtained through medical record review. Multivariable linear regression was used to examine the association between cognitive impairment and self-care practices adjusting for demographic and clinical factors. A total of 453 patients (79%) were impaired in at least one cognitive domain. Average adherence to self-care activities among patients with global cognitive impairment did not differ significantly from those without cognitive impairment (30.5 versus 29.6; 45-point scale). However, impaired memory was associated with lower self-care scores (P = 0.006) in multivariable models. Cognitive impairment is highly prevalent among older patients hospitalized for HF. Memory impairment is associated with poorer adherence to self-care practices. Screening for memory impairment in patients with HF may help to identify patients at risk for poor self-care who may benefit from tailored disease management programs.
Introduction: Mesothelioma is a rare malignancy typically associated with exposure to asbestos and poor survival. The purpose of this investigation was to describe mesothelioma patient characteristics, treatment patterns, and overall survival (OS) utilizing the National Cancer Institute's Surveillance, Epidemiology, and End Results-Medicare database. Materials and methods: Patients in this study were diagnosed with malignant mesothelioma of the pleura or peritoneum between January 1, 2005 and December 31, 2009 with follow-up for survival through December 31, 2010. We examined both patient and tumor characteristics at time of diagnosis and subsequent treatment patterns (surgery, radiation, and chemotherapy). Among patients treated with chemotherapy, we determined chemotherapy regimen and OS by line of therapy. Results: Of the 1,625 patients considered eligible for this investigation, the median age at diagnosis was 78 years. Nearly a third of patients (30%) had surgery as part of their treatment and 45% were given chemotherapy. The median OS was 8 months (range 1-69 months). Among chemotherapy patients, the most commonly (67%) prescribed regimen for first-line therapy was cisplatin or carboplatin (Ca/Ci) combined with pemetrexed (Pe). Among those prescribed Ca/Ci + Pe as first-line therapy, retreatment with Ca/Ci + Pe (28%) or treatment with gemcitabine (30%) were the most common second-line therapies. Median OS for those receiving first-line chemotherapy was 7 months, and among those receiving second-line therapy median OS was extended an additional 5 months. Conclusion: Irrespective of surgical resection, mesothelioma patients receiving some form of chemotherapy survived longer than patients who did not, with an additional survival benefit among those patients receiving multimodal treatment.
The prevalence of metastatic bone disease in the US population is not well understood. We sought to estimate the current number of US adults with metastatic bone disease using two large administrative data sets. Prevalence was estimated from a commercially insured cohort (ages 18-64 years, MarketScan database) and from a fee-for-service Medicare cohort (ages ≥65 years, Medicare 5% database) with coverage on December 31, 2008, representing approximately two-thirds of the US population in each age group. We searched for claims-based evidence of metastatic bone disease from January 1, 2004, using a combination of relevant diagnosis and treatment codes. The number of cases in the US adult population was extrapolated from age- and sex-specific prevalence estimated in these cohorts. Results are presented for all cancers combined and separately for primary breast, prostate, and lung cancer. In the commercially insured cohort (mean age = 42.3 years [SD = 13.1]), we identified 9505 patients (0.052%) with metastatic bone disease. Breast cancer was the most common primary tumor type (n = 4041). In the Medicare cohort (mean age = 75.6 years [SD = 7.8]), we identified 6427 (0.495%) patients with metastatic bone disease. Breast (n = 1798) and prostate (n = 1862) cancers were the most common primary tumor types. We estimate that 279,679 (95% confidence interval: 274,579-284,780) US adults alive on December 31, 2008, had evidence of metastatic bone disease in the previous 5 years. Breast, prostate, and lung cancers accounted for 68% of these cases. Our findings suggest that approximately 280,000 US adults were living with metastatic bone disease on December 31, 2008. This likely underestimates the true frequency; not all cases of metastatic bone disease are diagnosed, and some diagnosed cases might lack documentation in claims data.
textabstractCushing’s syndrome is a rare disorder resulting from prolonged exposure to excess glucocorticoids. Early diagnosis and treatment of Cushing’s syndrome is associated with a decrease in morbidity and mortality. Clinical presentation can be highly variable, and establishing the diagnosis can often be difficult. Surgery (resection of the pituitary or ectopic source of adrenocorticotropic hormone, or unilateral or bilateral adrenalectomy) remains the optimal treatment in all forms of Cushing’s syndrome, but may not always lead to remission. Medical therapy (steroidogenesis inhibitors, agents that decrease adrenocorticotropic hormone levels or glucocorticoid receptor antagonists) and pituitary radiotherapy may be needed as an adjunct. A multidisciplinary approach, long-term follow-up, and treatment modalities customized to each individual are essential for optimal control of hypercortisolemia and management of comorbidities.
Routinely recorded health data have evolved from mere by-products of health care delivery or billing into a powerful research tool for studying and improving patient care through clinical epidemiologic research. Big data in the context of epidemiologic research means large interlinkable data sets within a single country or networks of multinational databases. Several Nordic, European, and other multinational collaborations are now well established. Advantages of big data for clinical epidemiology include improved precision of estimates, which is especially important for reassuring ("null") findings; ability to conduct meaningful analyses in subgroup of patients; and rapid detection of safety signals. Big data will also provide new possibilities for research by enabling access to linked information from biobanks, electronic medical records, patient-reported outcome measures, automatic and semiautomatic electronic monitoring devices, and social media. The sheer amount of data, however, does not eliminate and may even amplify systematic error. Therefore, methodologies addressing systematic error, clinical knowledge, and underlying hypotheses are more important than ever to ensure that the signal is discernable behind the noise.
Objective: Missing data is a ubiquitous problem in studies using patient-reported measures, decreasing sample sizes and causing possible bias. In longitudinal studies, special problems relate to attrition and death during follow-up. We describe a methodological approach for the use of multiple imputation (MI) to meet these challenges. Methods: In a cohort of patients treated with percutaneous coronary intervention followed with use of repetitive questionnaires and information from national registers over 3 years, only 417 out of 1,726 patients had complete data on all measure points and covariates. We suggest strategies for use of MI and different methods for dealing with death along with sensitivity analysis of deviations from the assumption of missing at random, all with the use of standard statistical software. The Mental Component Summary from Short Form 12-item survey was used as an example. Conclusion: Ignoring missing data may cause bias of unknown size and direction in longitudinal studies. We have illustrated that MI is a feasible method to try to deal with bias due to missing data in longitudinal studies, including attrition and nonresponse, and should be considered in combination with analysis of sensitivity in longitudinal studies. How to handle dropout due to death is still open for debate.
Background: Statins are widely prescribed for the primary prevention of cardiovascular disease. Guidelines exist for statin prescriptions, but there is little recent analysis concerning prescription trends over time and how these vary with respect to demographic variables. Methods and results: Using The Health Improvement Network primary care database, statin therapy initiation and statin prescription prevalence rates were calculated using data from 7,027,711 individuals across the UK for the years 1995 to 2013, overall and stratified by sex, age group, and socioeconomic deprivation level (Townsend score). Statin therapy initiation rates rose sharply from 1995 (0.51 per 1,000 person-years) up to 2006 (19.83 per 1,000 person-years) and thereafter declined (10.76 per 1,000 person-years in 2013). Males had higher initiation rates than females and individuals aged 60-85 years had higher initiation rates than younger or more elderly age groups. Initiation rates were slightly higher as social deprivation level increased, after accounting for age and sex. Prescription prevalence increased sharply from 1995 (2.36 per 1,000 person-years) to 2013 (128.03 per 1,000 person-years) with males generally having a higher prevalence rate, over time, than females. Prevalence rates over time were generally higher for older age groups but were similar with respect to social deprivation level. Conclusion: The uptake of statins within UK primary care has increased greatly over time with statins being more commonly prescribed to older patients in general and, in recent years, males appear to have been prescribed statins at higher rates than females. After accounting for age and sex, the statin therapy initiation rate increases with the level of social deprivation.
Objective: Polypharmacy is the concomitant use of several drugs by a single person, and it increases the risk of adverse drug-related events in older adults. Little is known about the epidemiology of polypharmacy at the population level. We aimed to measure the prevalence and incidence of polypharmacy and to investigate the associated factors. Methods: A prospective cohort study was conducted using register data with national coverage in Sweden. A total of 1,742,336 individuals aged >= 65 years at baseline (November 1, 2010) were included and followed until death or the end of the study (December 20, 2013). Results: On average, individuals were exposed to 4.6 (SD =4.0) drugs at baseline. The prevalence of polypharmacy (5+ drugs) was 44.0%, and the prevalence of excessive polypharmacy (10+ drugs) was 11.7%. The incidence rate of polypharmacy among individuals without polypharmacy at baseline was 19.9 per 100 person-years, ranging from 16.8% in individuals aged 65-74 years to 33.2% in those aged >= 95 years (adjusted hazard ratio [HR] = 1.49, 95% confidence interval [CI] 1.42- 1.56). The incidence rate of excessive polypharmacy was 8.0 per 100 person-years. Older adults using multi-dose dispensing were at significantly higher risk of developing incident polypharmacy compared with those receiving ordinary prescriptions (HR =1.51, 95% CI 1.47-1.55). When adjusting for confounders, living in nursing home was found to be associated with lower risks of incident polypharmacy and incident excessive polypharmacy (HR =0.79 and HR =0.86, p<0.001, respectively). Conclusion: The prevalence and incidence of polypharmacy are high among older adults in Sweden. Interventions aimed at reducing the prevalence of polypharmacy should also target potential incident polypharmacy users as they are the ones who fuel future polypharmacy.