Scientific
publications

BACKGROUND: Anxiety is common, with significant morbidity, but little is known about presentations and recording of anxiety diagnoses and symptoms in primary care. This study aimed to determine trends in incidence and socio-demographic variation in General Practitioner (GP) recorded diagnoses of anxiety, mixed anxiety/depression, panic and anxiety symptoms. METHODOLOGY/PRINCIPAL FINDINGS: Annual incidence rates of anxiety diagnoses and symptoms were calculated from 361 UK general practices contributing to The Health Improvement Network (THIN) database between 1998 and 2008, adjusted for year of diagnosis, gender, age, and deprivation. Incidence of GP recorded anxiety diagnosis fell from 7.9 to 4.9/1000PYAR from 1998 to 2008, while incidence of anxiety symptoms rose from 3.9 to 5.8/1000PYAR. Incidence of mixed anxiety/depression fell from 4.0 to 2.2/1000PYAR, and incidence of panic disorder fell from 0.9/1000PYAR in 1998 to 0.5/1000PYAR in 2008. All these entries were approximately twice as common in women and more common in deprived areas. GP-recorded anxiety diagnoses, symptoms and mixed anxiety/depression were commonest aged 45-64 years, whilst panic disorder/attacks were more common in those 16-44 years. GPs predominately use broad non-specific codes to record anxiety problems in the UK. CONCLUSIONS/SIGNIFICANCE: GP recording of anxiety diagnoses has fallen whilst recording of anxiety symptoms has increased over time. The incidence of GP recorded diagnoses of anxiety diagnoses was lower than in screened populations in primary care. The reasons for this apparent under-recording and whether it represents under-detection in those being seen, a reluctance to report anxiety to their GP, or a reluctance amongst GPs to label people with anxiety requires investigation.

BACKGROUND: Obesity is associated with an increased risk of psoriasis; however, its potential impact on the risk of psoriatic arthritis (PsA) remains unclear. OBJECTIVES: To evaluate the association between body mass index (BMI) and the risk of PsA among patients with psoriasis from the general population. METHODS: The authors conducted a cohort study using data from The Health Improvement Network, an electronic medical records database representative of the UK general population, collected between 1995 and 2010. The exposure of interest was the first BMI measured after psoriasis diagnosis and endpoints were incident cases of physician-diagnosed PsA. The authors estimated the RR of PsA after adjusting for age, sex, and histories of trauma, smoking and alcohol consumption. RESULTS: Among 75,395 individuals with psoriasis (43% male, mean follow-up of 5 years, and mean age of 52 years), 976 developed PsA (incidence rate, 26.5 per 10,000 person-years). The PsA incidence rates increased with increasing BMI. Compared with psoriasis patients with BMI <25 kg/m(2), the RRs for developing PsA were 1.09 (0.93-1.28) for BMIs from 25.0 to 29.9, 1.22 (1.02-1.47) for BMIs from 30.0 to 34.9 and 1.48 (1.20-1.81) for BMIs ≥35.0. In our secondary analysis among all individuals, regardless of psoriasis (~2 million), the corresponding multivariate RRs tended to be stronger (1.0, 1.17, 1.57, 1.96; p for trend <0.001). CONCLUSIONS: This general population study suggests that obesity is associated with an increased risk of incident PsA and supports the importance of weight reduction among psoriasis patients who often suffer from the metabolic syndrome and obesity.

BACKGROUND: Women taking antidepressant or anti-anxiety medications during early pregnancy have high risks of non-live pregnancy outcomes, although the contribution of the underlying illnesses to these risks remains unclear. We examined the impacts of antenatal depression and anxiety and of commonly prescribed treatments on the risks of non-live pregnancy outcomes. METHODS: We identified all pregnancies and their outcome (live birth, perinatal death, miscarriage or termination) among women aged 15-45 years between 1990 and 2009 from a large primary care database in the United Kingdom. Women were grouped according to whether they had no history of depression and anxiety, a diagnosis of such illness prior to pregnancy, illness during pregnancy and illness during pregnancy with use of medication (stratified by medication type). Multinomial logistic regression models were used to compare risks of non-live outcomes among these groups, adjusting for major socio-demographic and lifestyle characteristics. RESULTS: Among 512,574 pregnancies in 331,414 women, those with antenatal drug exposure showed the greatest increased risks for all non-live pregnancy outcomes, relative to those with no history of depression or anxiety, although women with prior (but not currently medicated) illness also showed modest increased risks. Compared with un-medicated antenatal morbidity, there was weak evidence of an excess risk in women taking tricyclic antidepressants, and stronger evidence for other medications. CONCLUSIONS: Women with depression or anxiety have higher risks of miscarriage, perinatal death and decisions to terminate a pregnancy if prescribed psychotropic medication during early pregnancy than if not. Although underlying disease severity could also play a role, avoiding or reducing use of these drugs during early pregnancy may be advisable.

OBJECTIVES: To assess whether people with learning disability in the UK have poorer access to cancer screening. DESIGN: Four cohort studies comparing people with and without learning disability, within the recommended age ranges for cancer screening in the UK. We used Poisson regression to determine relative incidence rates of cancer screening. SETTING: The Health Improvement Network, a UK primary care database with over 450 General practices. PARTICIPANTS: Individuals with a recorded diagnosis of learning disability including general diagnostic terms, specific syndromes, chromosomal abnormalities and autism in their General Practitioner computerised notes. For each type of cancer screening, a comparison cohort of up to six people without learning disability was selected for each person with a learning disability, using stratified sampling on age within GP practice. MAIN OUTCOME MEASURES: Incidence rate ratios for receiving 1) a cervical smear test, 2) a mammogram, 3) a faecal occult blood test and 4) a prostate specific antigen test. RESULTS: Relative rates of screening for all four cancers were significantly lower for people with learning disability. The adjusted incidence rate ratios (95% confidence intervals) were Cervical smears: Number eligible with learning disability = 6,254; IRR = 0.54 (0.52-0.56). Mammograms: Number eligible with learning disability = 2,956; IRR = 0.76 (0.72-0.81); Prostate Specific Antigen: Number eligible = 3,520; IRR = 0.87 (0.80-0.96) and Faecal Occult Blood Number eligible = 6,566; 0.86 (0.78-0.94). Differences in screening rates were less pronounced in more socially deprived areas. Disparities in cervical screening rates narrowed over time, but were 45% lower in 2008/9, those for breast cancer screening appeared to widen and were 35% lower in 2009. CONCLUSION: Despite recent incentives, people with learning disability in the UK are significantly less likely to receive screening tests for cancer that those without learning disability. Other methods for reducing inequalities in access to cancer screening should be considered.

AIMS: This study characterized UK primary care patients with Type 2 diabetes who initiated insulin treatment, and described the initial insulin regimens used, overall metabolic changes and health-care resource usage. METHODS: A retrospective cohort study was performed using quality-checked patient data from The Health Improvement Network database. Eligible patients who initiated insulin for the first time between 2004 and 2006 were grouped into four cohorts according to the type of insulin regimen initiated. Data on patient characteristics, metabolic and clinical outcomes and health-care resource use were collected at baseline and during 6 months of follow-up. RESULTS: In total, 4045 eligible adults [2269 male, 1776 female; mean age 62.6 ± 13.3 years; mean baseline HbA(1c) 82 ± 22 mmol/mol (9.6% ± 2.0%)] initiated insulin. Approximately half (52.4%) initiated insulin as basal insulin only, 41.6% as premixed only, 4.0% as basal-bolus and 2.1% as prandial insulin only. Among patients with ≥ 180 days follow-up (n=3815), the initial insulin regimen was not changed during follow-up in 75.1% of patients, while 13.7% discontinued, 7.0% switched and 4.7% intensified insulin therapy. The mean change in HbA(1c) was -14 mmol/mol (-1.3%, n=2881), with 17.3% of patients achieving an HbA(1c) of <53 mmol/mol (7%, n=3024). The mean weight change was +0.9 kg (n=2345). CONCLUSIONS: Basal and premixed insulin were the most common types of insulin initiated and in most patients no changes were made to the initial regimen over 6 months. However, few patients achieved glycemic control targets.

PURPOSE: To identify practices common to both the General Practice Research Database and The Health Improvement Network database for purposes of combining the databases for analysis without duplicate records. METHODS: We developed two independent algorithms to identify practices common to the two databases. The first used the total number of patients in the therapy and clinical data sets and the total number of etoricoxib and celecoxib users each year during the study period. The second used the total number of patients stratified by gender and four different categories of birth year. Further checking of potential matched practice pairs identified by the two algorithms was performed by comparing the patient-level medical records by birth year, dates of clinical visits, and diagnosis codes. RESULTS: Three hundred twelve potential matched pairs of practices were found by both algorithms. Fifteen additional potential pairs were matched by only one algorithm: 13 by algorithm 1 (A1) only and 2 by algorithm 2 (A2) only. The examination of the patient-level visit dates and diagnosis codes for the matches revealed that all of the 327 potential pairs of duplicate practices were in fact the same practice in the two databases. CONCLUSIONS: The two algorithms successfully found the practices common to the two different databases without de-identifying the practices. The identification of the common practices allows for combining the two databases without duplicate records to create a larger data set for analysis, with 168 more practices than when using the General Practice Research Database alone, or with 268 more practices than when using The Health Improvement Network alone. Copyright © 2012 John Wiley & Sons, Ltd.

AIMS: To describe patients with Type 2 diabetes mellitus treated with basal insulin, with or without oral antidiabetics in UK primary care, and evaluate insulin treatment patterns and factors explaining changes in therapy. METHODS: Retrospective analysis of patients with Type 2 diabetes within The Health Improvement Network UK primary care database. Patients receiving basal insulin between January and June 2006 were followed until July 2009. RESULTS: Analysis included 3185 patients, mean age 65.6 years [standard deviation (SD) 12.4], 50.9% men, median diabetes duration 9.6 years, median basal insulin use 1.3 years, 86.5% had received oral antidiabetics in the previous 12 months. Mean follow-up was 2.9 years (SD 1.0), 59.8% patients maintained basal insulin throughout follow-up with a mean HbA(1C) of 69 mmol/mol (SD 19; 8.4%, SD 1.7) at baseline and 65 mmol/mol (SD 17; 8.1%, SD 1.6) during follow-up. During follow-up, 6.9% of patients discontinued, 19.3% intensified with and 14.1% switched to prandial or premixed insulin. Patients who intensified (prandial) had a mean HbA(1c) of 77 mmol/mol (SD 18; 9.2%, SD 1.6) before change and a mean HbA(1c) of 71 mmol/mol (SD 21; 8.6%, SD 2.0) at the end of the study. Those switching to premixed insulin had a mean HbA(1c) of 80 mmol/mol (SD 18; 9.5%, SD 1.7) before change and a mean HbA(1c) of 69 mmol/mol (SD 17; 8.5%, SD 1.5) at the end of the study. Increasing HbA(1c) and longer diabetes duration explained intensification and switch. CONCLUSIONS: The majority of patients had HbA(1c) above the 53 mmol/mol (< 7%) target at baseline and post-intensification/switch. The HbA(1c) levels were reduced by intensification/switch suggesting that insulin changes did have some impact. Most patients did not change insulin treatment despite having higher than recommended HbA(1c) levels. Reasons for not changing treatment in face of unsatisfactory clinical outcomes are unclear. Further research is warranted to explore barriers towards therapy change.

AIMS:   In November 2005 the indications for nicotine replacement therapy (NRT) were broadened in the United Kingdom, making all forms available to patients with stable cardiovascular disease (CVD). This study aimed to estimate the effects of this change on prescribing of NRT to CVD patients in England. DESIGN:   Segmented regression analysis of time series of monthly rates of prescribing of NRT. SETTING:   A total of 350 general practices in England included in The Health Improvement Network (THIN), a database of UK electronic primary care records. PARTICIPANTS:   All adult patients with coronary heart disease (CHD) or stroke registered with a THIN practice in England. MEASUREMENTS:   The number of patients per 100,000 with CHD and stroke that received a prescription for NRT each month between January 2002 and June 2009. FINDINGS:   Approximately 1500 per 100,000 smokers with CVD were prescribed NRT per month. Prescribing of NRT to CHD and stroke patients increased until the end of 2005 and subsequently decreased, with no immediate change following the Medicines and Healthcare Regulatory Authority (MHRA) licensing change. CONCLUSIONS:   Broadening the marketing licence in the United Kingdom for nicotine replacement therapy to allow it to be prescribed to patients with CVD did not increase prescribing rates for this group of patients.

BACKGROUND: Recommended pain treatments for osteoarthritis (OA) and chronic low back pain (CLBP) are suboptimal, and limited information is available regarding patterns of pharmacotherapy among patients with these conditions. AIMS: Evaluate patterns of therapy switching, augmentation, and discontinuation after treatment initiation with select pain medications in patients with OA and CLBP. METHODS: Using the U.K. The Health Improvement Network (THIN) database, OA and CLBP patients newly prescribed (index-event) nonselective nonsteroidal anti-inflammatory drugs (NS-NSAIDs), cyclooxygenase-2 inhibitors (Cox-2s), acetaminophen, tramadol and weak or strong opioids were selected. Descriptive statistics, Kaplan-Meier analyses, and COX proportional hazards models were used to evaluate patterns of changes in pharmacotherapy during the 12-month postindex period. RESULTS: Rates of therapy switching, augmentation, and discontinuation, respectively, were significantly different (all P values<0.0001) across the evaluated medication cohorts for both OA and CLBP patients. Discontinuation rates in OA patients were 91.9% (NS-NSAIDs), 86.9% (Cox-2s), 91.4% (acetaminophen), 89.7% (tramadol), 93.2% (weak opioids), and 84.3% (strong opioids); and in CLBP patients were 97.2% (NS-NSAIDs), 94.0% (Cox-2s), 95.0% (acetaminophen), 92.8% (tramadol), 97.0% (weak opioids), and 86.8% (strong opioids). The rates of switching (range 30.0% to 59.6%) and augmentation (range 7.5% to 15.2%) were lower. Estimated probability evaluations suggested that two-thirds of patients who switched, augmented, or discontinued therapy did so within the first couple of months, and a majority did so within 6-months of treatment initiation. CONCLUSIONS: This study demonstrates that therapy switching and discontinuation of select pain medications were common among OA and CLBP patients in the U.K. and may result from inadequate pain relief or undesirable side effects.

BACKGROUND: Smoking is a UK public health threat but GPs can be effective in helping patients to quit; consequently, the Quality and Outcomes Framework (QOF) incentivises the recording of smoking status and delivery of cessation advice in patients' medical records. This study investigates the association between smoking-related QOF targets and such recording, and the factors which influence these clinical activities. METHODS: For 2000 to 2008, using medical records in The Health Improvement Network (THIN) database, the annual proportions of i) patients who had a record of smoking status made in the previous 27 months and ii) current smokers recorded as receiving cessation advice in the previous 15 months were calculated. Then, for all patients at selected points before and after the QOF's implementation, data on gender, age, Townsend score, and smoking-related morbidity were extracted. Multivariate logistic regression was used to investigate individual-level characteristics associated with the recording of smoking status and cessation advice. RESULTS: Rapid increases in recording smoking status and advice occurred around the QOF's introduction in April 2004. Subsequently, compliance to targets has been sustained, although rates of increase have slowed. By 2008 64.5% of patients aged 15+ had smoking status documented in the previous 27 months and 50.5% of current smokers had cessation advice recorded in the last 15 months. Adjusted odds ratios show that, both before and after the introduction of the QOF, those with chronic medical conditions, greater social deprivation and women were more likely to have a recent recording of smoking status or cessation advice. Since the QOF's introduction, the strongest characteristic associated with recording activities was the presence of co-morbidity. An example of this was patients with COPD, who in 2008, were 15.38 (95% CI 13.70-17.27) times and 11.72 (95% CI 10.41-13.21) times more likely to have a record of smoking status and cessation advice, respectively. CONCLUSIONS: Rates of recording smoking status and cessation advice plateaued after large increases during the QOF's introduction; however, recording remains most strongly associated with the presence of chronic disease as specified by the QOF, and suggests that incentivised targets have a direct effect on clinical behaviour.

OBJECTIVE: To investigate whether there is an increased risk of cardiovascular events in people who exhibit iatrogenic Cushing's syndrome during treatment with glucocorticoids. DESIGN: Cohort study. SETTING: 424 UK general practices contributing to The Health Improvement Network database. PARTICIPANTS: People prescribed systemic glucocorticoids and with a diagnosis of iatrogenic Cushing's syndrome (n = 547) and two comparison groups: those prescribed glucocorticoids and with no diagnosis of iatrogenic Cushing's syndrome (n = 3231) and those not prescribed systemic glucocorticoids (n = 3282). MAIN OUTCOME MEASURES: Incidence of cardiovascular events within a year after diagnosis of iatrogenic Cushing's syndrome or after a randomly selected date, and association between iatrogenic Cushing's syndrome and risk of cardiovascular events. RESULTS: 417 cardiovascular events occurred in 341 patients. Taking into account only the first event by patient (coronary heart disease n = 177, heart failure n = 101, ischaemic stroke n = 63), the incidence rates of cardiovascular events per 100 person years at risk were 15.1 (95% confidence interval 11.8 to 18.4) in those prescribed glucocorticoids and with a diagnosis of iatrogenic Cushing's syndrome, 6.4 (5.5 to 7.3) in those prescribed glucocorticoids without a diagnosis of iatrogenic Cushing's syndrome, and 4.1 (3.4 to 4.8) in those not prescribed glucocorticoids. In multivariate analyses adjusted for sex, age, intensity of glucocorticoid use, underlying disease, smoking status, and use of aspirin, diabetes drugs, antihypertensive drugs, lipid lowering drugs, or oral anticoagulant drugs, the relation between iatrogenic Cushing's syndrome and cardiovascular events was strong (adjusted hazard ratios 2.27 (95% confidence interval 1.48 to 3.47) for coronary heart disease, 3.77 (2.41 to 5.90) for heart failure, and 2.23 (0.96 to 5.17) for ischaemic cerebrovascular events). The adjusted hazard ratio for any cardiovascular event was 4.16 (2.98 to 5.82) when the group prescribed glucocorticoids and with iatrogenic Cushing's syndrome was compared with the group not prescribed glucocorticoids. CONCLUSION: People who use glucocorticoids and exhibit iatrogenic Cushing's syndrome should be aggressively targeted for early screening and management of cardiovascular risk factors.

OBJECTIVE: To evaluate the performance of the QStatin scores for predicting the 5-year risk of developing acute renal failure, cataract, liver dysfunction and myopathy in men and women in England and Wales receiving statins. DESIGN: Prospective cohort study to evaluate the performance of four statin risk prediction models. SETTING: 364 practices in the UK contributing to The Health Improvement Network database. PARTICIPANTS: 2.2 million patients aged 35-84 years registered with a general practice surgery between 1 January 2002 and 30 June 2008, with 2037 incident cases of acute renal failure, 25 692 incident cataract cases, 14 756 cases of liver dysfunction and 1209 incident cases of myopathy. MAIN OUTCOME MEASURES: First recorded occurrence of acute renal failure, cataract, moderate or severe liver dysfunction and moderate or severe myopathic events as recorded in general practice records. RESULTS: Results from this independent and external validation of QStatin scores indicate that models predicting the 5-year statin risk of developing acute renal failure, cataracts and myopathy perform well with areas under the receiver operating characteristic curve ranging from 0.73 to 0.87. Calibration plots for the three models also indicated close agreement between observed and predicted risks. Poor performance was observed for the model predicting the 5-year statin risk of developing liver dysfunction with areas under the receiver operating characteristic curve of 0.64 and 0.60 for women and men, respectively. CONCLUSIONS: QStatin scores for predicting the 5-year statin risk of developing acute renal failure, cataract and myopathy appear to be useful models with good discriminative and calibration properties. The model for predicting the 5-year statin risk of developing liver dysfunction appears to have limited ability to identify high-risk individuals and the authors caution against its use.