Healthcare utilization and monetary costs associated with agitation in UK care home residents with advanced dementia: a prospective cohort study.

OBJECTIVE: Nearly half of care home residents with advanced dementia have clinically significant agitation. Little is known about costs associated with these symptoms toward the end of life. We calculated monetary costs associated with agitation from UK National Health Service, personal social services, and societal perspectives. DESIGN: Prospective cohort study. SETTING: Thirteen nursing homes in London and the southeast of England. PARTICIPANTS: Seventy-nine people with advanced dementia (Functional Assessment Staging Tool grade 6e and above) residing in nursing homes, and thirty-five of their informal carers. MEASUREMENTS: Data collected at study entry and monthly for up to 9 months, extrapolated for expression per annum. Agitation was assessed using the Cohen-Mansfield Agitation Inventory (CMAI). Health and social care costs of residing in care homes, and costs of contacts with health and social care services were calculated from national unit costs; for a societal perspective, costs of providing informal care were estimated using the resource utilization in dementia (RUD)-Lite scale. RESULTS: After adjustment, health and social care costs, and costs of providing informal care varied significantly by level of agitation as death approached, from £23,000 over a 1-year period with no agitation symptoms (CMAI agitation score 0-10) to £45,000 at the most severe level (CMAI agitation score >100). On average, agitation accounted for 30% of health and social care costs. Informal care costs were substantial, constituting 29% of total costs. CONCLUSIONS: With the increasing prevalence of dementia, costs of care will impact on healthcare and social services systems, as well as informal carers. Agitation is a key driver of these costs in people with advanced dementia presenting complex challenges for symptom management, service planners, and providers.

Statin prescribing for prevention of cardiovascular disease amongst people with severe mental illness: Cohort study in UK primary care.

BACKGROUND: Severe mental illness (SMI) is associated with excess cardiovascular disease (CVD) morbidity, but little is known on provision of preventative interventions. We investigated statin initiation for primary CVD prevention in individuals with and without SMI. METHODS: We used primary care data from The Health Improvement Network from 2006 to 2015 for UK patients aged 30-99years with no pre-existing CVD conditions and selected individuals with schizophrenia (n=13,252) or bipolar disorder (n=11,994). In addition, we identified samples of individuals without schizophrenia (n=66,060) and bipolar disorder (n=59,765), but with similar age and gender distribution. Missing data on CVD covariates were estimated using multiple imputation. Statin prescribing differences between individuals with and without SMI were investigated using multivariable Poisson regression models. RESULTS: Initiation of statin prescribing was between 2 and 3 fold higher in people aged 30-59years with SMI than in those without after adjusting for CVD covariates. The rates in those aged 60-74years with SMI were similar or slightly higher relative to those without SMI. The incidence rate ratio (IRR) was 1.15 (95% CI 1.03-1.28) for bipolar disorder and 1.00 (0.91-1.11) for schizophrenia. The rate of statin prescribing was lower (IRR 0.81 (0.66-0.98)) amongst the oldest (aged 75+years) with schizophrenia relative to those without schizophrenia. CONCLUSIONS: Despite higher rates of new statin prescriptions to younger individuals with SMI relative to individuals without SMI, there was evidence of lower rates of statin initiation for older individuals with schizophrenia, and this group may benefit from additional measures to prevent CVD.

Effects of chronic exposure of hydroxychloroquine/chloroquine on the risk of cancer, metastasis, and death: a population-based cohort study on patients with connective tissue diseases.

BACKGROUND: Hydroxychloroquine and chloroquine may reduce the risk of cancer as they inhibit autophagy, in particular, in people with connective tissue diseases. METHODS: The hazard ratios of cancers, metastases, and death were assessed in adults with connective tissue diseases prescribed hydroxychloroquine/chloroquine for at least 1 year in comparison with unexposed individuals with the same underlying conditions. A competing risk survival regression analysis was performed. Data were extracted from the Health Improvement Network UK primary care database. RESULTS: Eight thousand nine hundred and ninety-nine individuals exposed to hydroxychloroquine (98.6%) or chloroquine (1.4%) and 24,118 unexposed individuals were included in the study (median age: 56 [45-66] years, women: 76.8%). When compared to the unexposed group, individuals exposed to hydroxychloroquine/chloroquine were not at lower risk of non-skin cancers (adjusted sub-distribution hazard ratio [sHR]: 1.04 [0.92-1.18], p=0.54), hematological malignancies (adjusted sHR: 1.00 [0.73-1.38], p=0.99), or skin cancers (adjusted sHR: 0.92 [0.78-1.07], p=0.26). The risk of metastasis was not significantly different between the two groups. However, it was significantly lower during the exposure period when compared with the unexposed (adjusted sHR: 0.64 [0.44-0.95] for the overall population and 0.61 [0.38-1.00] for those diagnosed with incident cancers). The risk of death was also significantly lower in those exposed to hydroxychloroquine/chloroquine (adjusted HR: 0.90 [0.81-1.00] in the overall population and 0.78 [0.64-0.96] in those diagnosed with incident cancer). CONCLUSION: Individuals on long-term exposure to hydroxychloroquine/chloroquine are not at lower risk of cancer. However, hydroxychloroquine/chloroquine may lower the risk of metastatic cancer and death.

Statin prescribing for people with severe mental illnesses: a staggered cohort study of 'real-world' impacts.

OBJECTIVES: To estimate the 'real-world effectiveness of statins for primary prevention of cardiovascular disease (CVD) and for lipid modification in people with severe mental illnesses (SMI), including schizophrenia and bipolar disorder. DESIGN: Series of staggered cohorts. We estimated the effect of statin prescribing on CVD outcomes using a multivariable Poisson regression model or linear regression for cholesterol outcomes. SETTING: 587 general practice (GP) surgeries across the UK reporting data to The Health Improvement Network. PARTICIPANTS: All permanently registered GP patients aged 40-84 years between 2002 and 2012 who had a diagnosis of SMI. Exclusion criteria were pre-existing CVD, statin-contraindicating conditions or a statin prescription within the 24 months prior to the study start. EXPOSURE: One or more statin prescriptions during a 24-month 'baseline' period (vs no statin prescription during the same period). MAIN OUTCOME MEASURES: The primary outcome was combined first myocardial infarction and stroke. All-cause mortality and total cholesterol concentration were secondary outcomes. RESULTS: We identified 2944 statin users and 42 886 statin non-users across the staggered cohorts. Statin prescribing was not associated with significant reduction in CVD events (incident rate ratio 0.89; 95% CI 0.68 to 1.15) or all-cause mortality (0.89; 95% CI 0.78 to 1.02). Statin prescribing was, however, associated with statistically significant reductions in total cholesterol of 1.2 mmol/L (95% CI 1.1 to 1.3) for up to 2 years after adjusting for differences in baseline characteristics. On average, total cholesterol decreased from 6.3 to 4.6 in statin users and 5.4 to 5.3 mmol/L in non-users. CONCLUSIONS: We found that statin prescribing to people with SMI in UK primary care was effective for lipid modification but not CVD events. The latter finding may reflect insufficient power to detect a smaller effect size than that observed in randomised controlled trials of statins in people without SMI.

Relative risks of cardiovascular disease in people prescribed olanzapine, risperidone and quetiapine.

Antipsychotics may confer long term benefits and risks, including cardiovascular disease (CVD) risk. Several studies using routine clinical data have reported associations between antipsychotics and CVD but potential confounding factors and unclear classification of drug exposure limits their interpretation. METHOD: We used data from The Health Improvement Network, a large UK primary care database to determine relative risks of (CVD) comparing similar groups of people only prescribed olanzapine versus either risperidone or quetiapine. We included participants over 18 between 1995 and 2011. To assess confounding factors we created propensity scores for being prescribed each antipsychotic. We used propensity score matching and Poisson regression to calculate the CVD incidence rate ratios for olanzapine versus the other two drugs. RESULTS: We identified 18,319 people who received a single antipsychotic during follow-up (n=5090 risperidone, 7797 olanzapine and 4613 quetiapine). In unmatched analyses, the CVD incidence rate ratio (IRR) for olanzapine versus risperidone was 0.63 (0.51-0.77) but the propensity score matched IRR was 0.78 (0.61-1.02). In the unmatched olanzapine versus quetiapine analysis the IRR adjusted for age and sex for olanzapine was 1.52 (1.16-1.98) but the propensity score matched analysis gave an IRR of 1.08 (0.79-1.46). CONCLUSIONS: After propensity score matching, we found no statistical differences in CVD incidence between olanzapine and either risperidone or quetiapine. Analyses which did not account for confounding factors produced very different results. Researchers must address confounding factors when designing observational studies to assess adverse outcomes of drugs, including antipsychotics.

A brief intervention for weight control based on habit-formation theory delivered through primary care: results from a randomised controlled trial.

BACKGROUND: Primary care is the 'first port of call' for weight control advice, creating a need for simple, effective interventions that can be delivered without specialist skills. Ten Top Tips (10TT) is a leaflet based on habit-formation theory that could fill this gap. The aim of the current study was to test the hypothesis that 10TT can achieve significantly greater weight loss over 3 months than 'usual care'. METHODS: A two-arm, individually randomised, controlled trial in primary care. Adults with obesity were identified from 14 primary care providers across England. Patients were randomised to either 10TT or 'usual care' and followed up at 3, 6, 12, 18 and 24 months. The primary outcome was weight loss at 3 months, assessed by a health professional blinded to group allocation. Difference between arms was assessed using a mixed-effect linear model taking into account the health professionals delivering 10TT, and adjusted for baseline weight. Secondary outcomes included body mass index, waist circumference, the number achieving a 5% weight reduction, clinical markers for potential comorbidities, weight loss over 24 months and basic costs. RESULTS: Five-hundred and thirty-seven participants were randomised to 10TT (n=267) or to 'usual care' (n=270). Data were available for 389 (72%) participants at 3 months and for 312 (58%) at 24 months. Participants receiving 10TT lost significantly more weight over 3 months than those receiving usual care (mean difference =-0.87kg; 95% confidence interval: -1.47 to -0.27; P=0.004). At 24 months, the 10TT group had maintained their weight loss, but the 'usual care' group had lost a similar amount. The basic cost of 10TT was low, that is, around £23 ($32) per participant. CONCLUSIONS: The 10TT leaflet delivered through primary care is effective in the short-term and a low-cost option over the longer term. It is the first habit-based intervention to be used in a health service setting and offers a low-intensity alternative to 'usual care'.

Predicting dementia risk in primary care: development and validation of the Dementia Risk Score using routinely collected data.

BACKGROUND: Existing dementia risk scores require collection of additional data from patients, limiting their use in practice. Routinely collected healthcare data have the potential to assess dementia risk without the need to collect further information. Our objective was to develop and validate a 5-year dementia risk score derived from primary healthcare data. METHODS: We used data from general practices in The Health Improvement Network (THIN) database from across the UK, randomly selecting 377 practices for a development cohort and identifying 930,395 patients aged 60-95 years without a recording of dementia, cognitive impairment or memory symptoms at baseline. We developed risk algorithm models for two age groups (60-79 and 80-95 years). An external validation was conducted by validating the model on a separate cohort of 264,224 patients from 95 randomly chosen THIN practices that did not contribute to the development cohort. Our main outcome was 5-year risk of first recorded dementia diagnosis. Potential predictors included sociodemographic, cardiovascular, lifestyle and mental health variables. RESULTS: Dementia incidence was 1.88 (95% CI, 1.83-1.93) and 16.53 (95% CI, 16.15-16.92) per 1000 PYAR for those aged 60-79 (n = 6017) and 80-95 years (n = 7104), respectively. Predictors for those aged 60-79 included age, sex, social deprivation, smoking, BMI, heavy alcohol use, anti-hypertensive drugs, diabetes, stroke/TIA, atrial fibrillation, aspirin, depression. The discrimination and calibration of the risk algorithm were good for the 60-79 years model; D statistic 2.03 (95% CI, 1.95-2.11), C index 0.84 (95% CI, 0.81-0.87), and calibration slope 0.98 (95% CI, 0.93-1.02). The algorithm had a high negative predictive value, but lower positive predictive value at most risk thresholds. Discrimination and calibration were poor for the 80-95 years model. CONCLUSIONS: Routinely collected data predicts 5-year risk of recorded diagnosis of dementia for those aged 60-79, but not those aged 80+. This algorithm can identify higher risk populations for dementia in primary care. The risk score has a high negative predictive value and may be most helpful in 'ruling out' those at very low risk from further testing or intensive preventative activities.

Strategies to improve retention in randomised trials: a Cochrane systematic review and meta-analysis.

OBJECTIVE: To quantify the effect of strategies to improve retention in randomised trials. DESIGN: Systematic review and meta-analysis. DATA SOURCES: Sources searched: MEDLINE, EMBASE, PsycINFO, DARE, CENTRAL, CINAHL, C2-SPECTR, ERIC, PreMEDLINE, Cochrane Methodology Register, Current Controlled Trials metaRegister, WHO trials platform, Society for Clinical Trials (SCT) conference proceedings and a survey of all UK clinical trial research units. REVIEW METHODS: Included trials were randomised evaluations of strategies to improve retention embedded within host randomised trials. The primary outcome was retention of trial participants. Data from trials were pooled using the fixed-effect model. Subgroup analyses were used to explore the heterogeneity and to determine whether there were any differences in effect by the type of strategy. RESULTS: 38 retention trials were identified. Six broad types of strategies were evaluated. Strategies that increased postal questionnaire responses were: adding, that is, giving a monetary incentive (RR 1.18; 95% CI 1.09 to 1.28) and higher valued incentives (RR 1.12; 95% CI 1.04 to 1.22). Offering a monetary incentive, that is, an incentive given on receipt of a completed questionnaire, also increased electronic questionnaire response (RR 1.25; 95% CI 1.14 to 1.38). The evidence for shorter questionnaires (RR 1.04; 95% CI 1.00 to 1.08) and questionnaires relevant to the disease/condition (RR 1.07; 95% CI 1.01 to 1.14) is less clear. On the basis of the results of single trials, the following strategies appeared effective at increasing questionnaire response: recorded delivery of questionnaires (RR 2.08; 95% CI 1.11 to 3.87); a 'package' of postal communication strategies (RR 1.43; 95% CI 1.22 to 1.67) and an open trial design (RR 1.37; 95% CI 1.16 to 1.63). There is no good evidence that the following strategies impact on trial response/retention: adding a non-monetary incentive (RR=1.00; 95% CI 0.98 to 1.02); offering a non-monetary incentive (RR=0.99; 95% CI 0.95 to 1.03); 'enhanced' letters (RR=1.01; 95% CI 0.97 to 1.05); monetary incentives compared with offering prize draw entry (RR=1.04; 95% CI 0.91 to 1.19); priority postal delivery (RR=1.02; 95% CI 0.95 to 1.09); behavioural motivational strategies (RR=1.08; 95% CI 0.93 to 1.24); additional reminders to participants (RR=1.03; 95% CI 0.99 to 1.06) and questionnaire question order (RR=1.00, 0.97 to 1.02). Also based on single trials, these strategies do not appear effective: a telephone survey compared with a monetary incentive plus questionnaire (RR=1.08; 95% CI 0.94 to 1.24); offering a charity donation (RR=1.02, 95% CI 0.78 to 1.32); sending sites reminders (RR=0.96; 95% CI 0.83 to 1.11); sending questionnaires early (RR=1.10; 95% CI 0.96 to 1.26); longer and clearer questionnaires (RR=1.01, 0.95 to 1.07) and participant case management by trial assistants (RR=1.00; 95% CI 0.97 to 1.04). CONCLUSIONS: Most of the trials evaluated questionnaire response rather than ways to improve participants return to site for follow-up. Monetary incentives and offers of monetary incentives increase postal and electronic questionnaire response. Some strategies need further evaluation. Application of these results would depend on trial context and follow-up procedures.

Use of strategies to improve retention in primary care randomised trials: a qualitative study with in-depth interviews.

OBJECTIVE: To explore the strategies used to improve retention in primary care randomised trials. DESIGN: Qualitative in-depth interviews and thematic analysis. PARTICIPANTS: 29 UK primary care chief and principal investigators, trial managers and research nurses. METHODS: In-depth face-to-face interviews. RESULTS: Primary care researchers use incentive and communication strategies to improve retention in trials, but were unsure of their effect. Small monetary incentives were used to increase response to postal questionnaires. Non-monetary incentives were used although there was scepticism about the impact of these on retention. Nurses routinely used telephone communication to encourage participants to return for trial follow-up. Trial managers used first class post, shorter questionnaires and improved questionnaire designs with the aim of improving questionnaire response. Interviewees thought an open trial design could lead to biased results and were negative about using behavioural strategies to improve retention. There was consensus among the interviewees that effective communication and rapport with participants, participant altruism, respect for participant's time, flexibility of trial personnel and appointment schedules and trial information improve retention. Interviewees noted particular challenges with retention in mental health trials and those involving teenagers. CONCLUSIONS: The findings of this qualitative study have allowed us to reflect on research practice around retention and highlight a gap between such practice and current evidence. Interviewees describe acting from experience without evidence from the literature, which supports the use of small monetary incentives to improve the questionnaire response. No such evidence exists for non-monetary incentives or first class post, use of which may need reconsideration. An exploration of barriers and facilitators to retention in other research contexts may be justified.

Modelling the cost-effectiveness of preventing major depression in general practice patients.

BACKGROUND: The prevention of depression is a key public health policy priority. PredictD is the first risk algorithm for the prediction of the onset of major depression. Our aim in this study was to model the cost-effectiveness of PredictD in depression prevention in general practice (GP). METHOD: A decision analytical model was developed to determine the cost-effectiveness of two approaches, each of which was compared to treatment as usual (TAU) over 12 months: (1) the PredictD risk algorithm plus a low-intensity depression prevention programme; and (2) a universal prevention programme in which there was no initial identification of those at risk. The model simulates the incidence of depression and disease progression over 12 months and calculates the net monetary benefit (NMB) from the National Health Service (NHS) perspective. RESULTS: Providing patients with PredictD and a depression prevention programme prevented 15 (17%) cases of depression in a cohort of 1000 patients over 12 months and had the highest probability of being the optimal choice at a willingness to pay (WTP) of £20,000 for a quality-adjusted life year (QALY). Universal prevention was strongly dominated by PredictD plus a depression prevention programme in that universal prevention resulted in less QALYs than PredictD plus prevention for a greater cost. CONCLUSIONS: Using PredictD to identify primary-care patients at high risk of depression and providing them with a low-intensity prevention programme is potentially cost-effective at a WTP of £20,000 per QALY.

Spiritual and religious beliefs as risk factors for the onset of major depression: an international cohort study.

BACKGROUND: Several studies have reported weak associations between religious or spiritual belief and psychological health. However, most have been cross-sectional surveys in the U.S.A., limiting inference about generalizability. An international longitudinal study of incidence of major depression gave us the opportunity to investigate this relationship further. METHOD: Data were collected in a prospective cohort study of adult general practice attendees across seven countries. Participants were followed at 6 and 12 months. Spiritual and religious beliefs were assessed using a standardized questionnaire, and DSM-IV diagnosis of major depression was made using the Composite International Diagnostic Interview (CIDI). Logistic regression was used to estimate incidence rates and odds ratios (ORs), after multiple imputation of missing data. RESULTS: The analyses included 8318 attendees. Of participants reporting a spiritual understanding of life at baseline, 10.5% had an episode of depression in the following year compared to 10.3% of religious participants and 7.0% of the secular group (p<0.001). However, the findings varied significantly across countries, with the difference being significant only in the U.K., where spiritual participants were nearly three times more likely to experience an episode of depression than the secular group [OR 2.73, 95% confidence interval (CI) 1.59­4.68]. The strength of belief also had an effect, with participants with strong belief having twice the risk of participants with weak belief. There was no evidence of religion acting as a buffer to prevent depression after a serious life event. CONCLUSIONS: These results do not support the notion that religious and spiritual life views enhance psychological well-being.

Predicting onset of major depression in general practice attendees in Europe: extending the application of the predictD risk algorithm from 12 to 24 months.

BACKGROUND: PredictD is a risk algorithm that was developed to predict risk of onset of major depression over 12 months in general practice attendees in Europe and validated in a similar population in Chile. It was the first risk algorithm to be developed in the field of mental disorders. Our objective was to extend predictD as an algorithm to detect people at risk of major depression over 24 months. Method Participants were 4190 adult attendees to general practices in the UK, Spain, Slovenia and Portugal, who were not depressed at baseline and were followed up for 24 months. The original predictD risk algorithm for onset of DSM-IV major depression had already been developed in data arising from the first 12 months of follow-up. In this analysis we fitted predictD to the longer period of follow-up, first by examining only the second year (12-24 months) and then the whole period of follow-up (0-24 months). RESULTS: The instrument performed well for prediction of major depression from 12 to 24 months [c-index 0.728, 95% confidence interval (CI) 0.675-0.781], or over the whole 24 months (c-index 0.783, 95% CI 0.757-0.809). CONCLUSIONS: The predictD risk algorithm for major depression is accurate over 24 months, extending it current use of prediction over 12 months. This strengthens its use in prevention efforts in general medical settings.

Computer-based interventions for sexual health promotion: systematic review and meta-analyses.

This systematic review was conducted to determine the effects of self-help interactive computer-based interventions (ICBIs) for sexual health promotion. We searched 40 databases for randomized controlled trials (RCTs) of computer-based interventions, defining 'interactive' as programmes that require contributions from users to produce personally relevant material. We conducted searches and analysed data using Cochrane Collaboration methods. Results of RCTs were pooled using a random-effects model with standardized mean differences for continuous outcomes and odds ratios (ORs) for binary outcomes, with heterogeneity assessed using the I(2) statistic. We identified 15 RCTs of ICBIs (3917 participants). Comparing ICBIs to minimal interventions, there were significant effects on sexual health knowledge (standardized mean difference [SMD] 0.72, 95% confidence interval [CI] 0.27-1.18); safer sex self-efficacy (SMD 0.17, 95% CI 0.05-0.29); safer-sex intentions (SMD 0.16, 95% CI 0.02-0.30); and sexual behaviour (OR 1.75, 95% CI 1.18-2.59). ICBIs had a greater impact on sexual health knowledge than face-to-face interventions did (SMD 0.36, 95% CI 0.13-0.58). ICBIs are effective tools for learning about sexual health, and show promising effects on self-efficacy, intention and sexual behaviour. More data are needed to analyse biological outcomes and cost-effectiveness.

Characteristics of a population-wide sample of smokers recruited proactively for the ESCAPE trial.

OBJECTIVES: To describe the characteristics of a sample of smokers recruited proactively into a smoking cessation trial, and to compare these characteristics with the wider population using data from the General Household Survey (GHS) and National Statistics Omnibus Survey. STUDY DESIGN: Sample recruited for a randomized controlled trial. METHODS: Between August 2007 and October 2008, 123 general practices mailed questionnaires to smokers in the U.K. identified from computer records. Smokers willing to participate in a trial of personalized computer-tailored feedback returned the questionnaires to the research team. The characteristics of the sample were compared with the wider population using data from the GHS and National Statistics Omnibus Survey, and Index of Material Deprivation scores. RESULTS: A response rate of 11.4% (n = 6697) was achieved. The sample was demographically similar to the population sample, with an even distribution of participants from areas of both high and low deprivation. The sample was more dependent than the GHS sample, but less dependent than clinic samples. Distribution by motivation and readiness to quit was similar to population estimates. CONCLUSIONS: Public health strategies targeting the entire population of smokers are needed to counter the low recruitment rates resulting from the traditional reactive methods of recruitment to smoking cessation studies. Using computerized records to identify and contact patients who are smokers is a simple method of recruiting a larger, more representative sample of smokers.

Two-stage method to remove population- and individual-level outliers from longitudinal data in a primary care database.

PURPOSE: In the UK, primary care databases include repeated measurements of health indicators at the individual level. As these databases encompass a large population, some individuals have extreme values, but some values may also be recorded incorrectly. The challenge for researchers is to distinguish between records that are due to incorrect recording and those which represent true but extreme values. This study evaluated different methods to identify outliers. METHODS: Ten percent of practices were selected at random to evaluate the recording of 513,367 height measurements. Population-level outliers were identified using boundaries defined using Health Survey for England data. Individual-level outliers were identified by fitting a random-effects model with subject-specific slopes for height measurements adjusted for age and sex. Any height measurements with a patient-level standardised residual more extreme than ±10 were identified as an outlier and excluded. The model was subsequently refitted twice after removing outliers at each stage. This method was compared with existing methods of removing outliers. RESULTS: Most outliers were identified at the population level using the boundaries defined using Health Survey for England (1550 of 1643). Once these were removed from the database, fitting the random-effects model to the remaining data successfully identified only 75 further outliers. This method was more efficient at identifying true outliers compared with existing methods. CONCLUSIONS: We propose a new, two-stage approach in identifying outliers in longitudinal data and show that it can successfully identify outliers at both population and individual level. Copyright © 2011 John Wiley & Sons, Ltd.

Predicting the onset of major depression in primary care: international validation of a risk prediction algorithm from Spain.

BACKGROUND: The different incidence rates of, and risk factors for, depression in different countries argue for the need to have a specific risk algorithm for each country or a supranational risk algorithm. We aimed to develop and validate a predictD-Spain risk algorithm (PSRA) for the onset of major depression and to compare the performance of the PSRA with the predictD-Europe risk algorithm (PERA) in Spanish primary care. METHOD: A prospective cohort study with evaluations at baseline, 6 and 12 months. We measured 39 known risk factors and used multi-level logistic regression and inverse probability weighting to build the PSRA. In Spain (4574), Chile (2133) and another five European countries (5184), 11 891 non-depressed adult primary care attendees formed our at-risk population. The main outcome was DSM-IV major depression (CIDI). RESULTS: Six variables were patient characteristics or past events (sex, age, sex×age interaction, education, physical child abuse, and lifetime depression) and six were current status [Short Form 12 (SF-12) physical score, SF-12 mental score, dissatisfaction with unpaid work, number of serious problems in very close persons, dissatisfaction with living together at home, and taking medication for stress, anxiety or depression]. The C-index of the PSRA was 0.82 [95% confidence interval (CI) 0.79-0.84]. The Integrated Discrimination Improvement (IDI) was 0.0558 [standard error (s.e.)=0.0071, Zexp=7.88, p<0.0001] mainly due to the increase in sensitivity. Both the IDI and calibration plots showed that the PSRA functioned better than the PERA in Spain. CONCLUSIONS: The PSRA included new variables and afforded an improved performance over the PERA for predicting the onset of major depression in Spain. However, the PERA is still the best option in other European countries.

[Description of oral glucocorticoid prescriptions in general population]. / Description des prescriptions de corticothérapies orales en population générale.

PURPOSE: Very little is known about oral glucocorticoids (GCs) prescriptions in general population. METHODS: Data of UK adult patients registered between January 1989 and December 2008 with general practices contributing to The Health Improvement Network (THIN) database were analyzed. We identified all patients aged 18 years and older who received at least one oral GCs prescription. Short-term treatments (i.e., <3 months) were differentiated from long term (i.e., ≥3 months) ones. Demographical data of patients being prescribed such treatments and reason for prescriptions over the 20 years were described. The annual prevalence of GCs prescriptions was assessed. RESULTS: The study population consisted of 4,518,753 adult patients (26,035,154 person-years of follow-up). Overall, 810,009 oral GCs treatments (220,195,154 person-years of follow-up) were prescribed in 384,897 patients. Over the 20 years, the mean prevalence of oral GCs prescriptions was 0.85% [0.84-0.85], increasing from 0.65% [0.57-0.74] in 1989 to 0.91% [0.90-0.93] in 2008. Short-term therapies (median duration of prescription: 9 days [6-10], median cumulative prednisone equivalent (PE) dosage: 210 mg [150-420]) represented 79.3% of treatments and 11.9% of prevalence whereas it was the opposite for long term prescriptions (median duration of prescription: 215 days [126-490], median cumulative PE dosage: 2000 mg [950-4310]). Women were more prescribed GCs. Median age at first GCs prescription was 56.1 years [39.4-70.4] and 67.4 years [54.0-76.8] for short-term and long-term therapies, respectively. Reasons for prescription were mainly pulmonary diseases. CONCLUSION: About 1% of the UK general population receives GCs therapy in any point of time. This prevalence has constantly increased over the last 20 years.

An international risk prediction algorithm for the onset of generalized anxiety and panic syndromes in general practice attendees: predictA.

BACKGROUND: There are no risk models for the prediction of anxiety that may help in prevention. We aimed to develop a risk algorithm for the onset of generalized anxiety and panic syndromes. METHOD: Family practice attendees were recruited between April 2003 and February 2005 and followed over 24 months in the UK, Spain, Portugal and Slovenia (Europe4 countries) and over 6 months in The Netherlands, Estonia and Chile. Our main outcome was generalized anxiety and panic syndromes as measured by the Patient Health Questionnaire. We entered 38 variables into a risk model using stepwise logistic regression in Europe4 data, corrected for over-fitting and tested it in The Netherlands, Estonia and Chile. RESULTS: There were 4905 attendees in Europe4, 1094 in Estonia, 1221 in The Netherlands and 2825 in Chile. In the algorithm four variables were fixed characteristics (sex, age, lifetime depression screen, family history of psychological difficulties); three current status (Short Form 12 physical health subscale and mental health subscale scores, and unsupported difficulties in paid and/or unpaid work); one concerned country; and one time of follow-up. The overall C-index in Europe4 was 0.752 [95% confidence interval (CI) 0.724-0.780]. The effect size for difference in predicted log odds between developing and not developing anxiety was 0.972 (95% CI 0.837-1.107). The validation of predictA resulted in C-indices of 0.731 (95% CI 0.654-0.809) in Estonia, 0.811 (95% CI 0.736-0.886) in The Netherlands and 0.707 (95% CI 0.671-0.742) in Chile. CONCLUSIONS: PredictA accurately predicts the risk of anxiety syndromes. The algorithm is strikingly similar to the predictD algorithm for major depression, suggesting considerable overlap in the concepts of anxiety and depression.

Development and pilot evaluation of a complex intervention to improve experienced continuity of care in patients with cancer.

High experienced continuity of care in patients with cancer is associated with lower needs for care, better quality of life and better psychological outcomes. We developed and evaluated an intervention to improve experienced continuity. The intervention, consisted of (1) a 17-item patient-completed continuity assessment; (2) feedback to clinical nurse specialists and action to address the needs identified. Multidisciplinary team meetings and oncology outpatient clinics were observed, and patients and staff were interviewed. After qualitative work and reliability testing, the intervention was evaluated in a feasibility trial. Sixty-one patients provided data for analysis. No statistically significant differences were found in patients' experienced continuity between the trial arms, but important trends were seen in measures of needs for care in favour of those receiving the intervention. Feeding back findings from the continuity assessment to clinicians reduced patients' needs for care. Our results indicate that an intervention to target patients' experiences of continuity can reduce their subsequent needs for care. However, overcoming barriers to organisational change and addressing some patients' hesitation to report their continuity difficulties must be considered when implementing such an intervention. A phase III trial targeting patients with inadequate experienced continuity of care is recommended.