Predicting the onset of anxiety syndromes at 12 months in primary care attendees. The PredictA-Spain study

Background: There are no risk algorithms for the onset of anxiety syndromes at 12 months in primary care. We aimed to develop and validate internally a risk algorithm to predict the onset of anxiety syndromes at 12 months. Methods: A prospective cohort study with evaluations at baseline, 6 and 12 months. We measured 39 known risk factors and used multilevel logistic regression and inverse probability weighting to build the risk algorithm. Our main outcome was generalized anxiety, panic and other non-specific anxiety syndromes as measured by the Primary Care Evaluation of Mental Disorders, Patient Health Questionnaire (PRIME-MD-PHQ). We recruited 3,564 adult primary care attendees without anxiety syndromes from 174 family physicians and 32 health centers in 6 Spanish provinces. Results: The cumulative 12-month incidence of anxiety syndromes was 12.2%. The predictA-Spain risk algorithm included the following predictors of anxiety syndromes: province; sex (female); younger age; taking medicines for anxiety, depression or stress; worse physical and mental quality of life (SF-12); dissatisfaction with paid and unpaid work; perception of financial strain; and the interactions sex*age, sex*perception of financial strain, and age*dissatisfaction with paid work. The C-index was 0.80 (95% confidence interval = 0.78–0.83) and the Hedges' g = 1.17 (95% confidence interval = 1.04–1.29). The Copas shrinkage factor was 0.98 and calibration plots showed an accurate goodness of fit. Conclusions: The predictA-Spain risk algorithm is valid to predict anxiety syndromes at 12 months. Although external validation is required, the predictA-Spain is available for use as a predictive tool in the prevention of anxiety syndromes in primary care.This study was supported by the Spanish Ministry of Health (grant FIS references: PI041980, PI041771, PI042450 and PI06/1442) and the Andalusian Council of Health (grant references: 05/403 and 06/278); as well as the Spanish Network of Primary Care Research ‘redIAPP’ (RD06/0018), the ‘Aragón group’ (RD06/0018/0020), the ‘Baleares group’ (RD07/0018/0033), and the ‘SAMSERAP group’ (RD06/0018/0039)

Predicting the onset and persistence of episodes of depression in primary health care. The predictD-Spain study: Methodology

Background: The effects of putative risk factors on the onset and/or persistence of depression remain unclear. We aim to develop comprehensive models to predict the onset and persistence of episodes of depression in primary care. Here we explain the general methodology of the predictD-Spain study and evaluate the reliability of the questionnaires used. Methods: This is a prospective cohort study. A systematic random sample of general practice attendees aged 18 to 75 has been recruited in seven Spanish provinces. Depression is being measured with the CIDI at baseline, and at 6, 12, 24 and 36 months. A set of individual, environmental, genetic, professional and organizational risk factors are to be assessed at each follow-up point. In a separate reliability study, a proportional random sample of 401 participants completed the test-retest (251 researcher-administered and 150 self-administered) between October 2005 and February 2006. We have also checked 118,398 items for data entry from a random sample of 480 patients stratified by province. Results: All items and questionnaires had good test-retest reliability for both methods of administration, except for the use of recreational drugs over the previous six months. Cronbach's alphas were good and their factorial analyses coherent for the three scales evaluated (social support from family and friends, dissatisfaction with paid work, and dissatisfaction with unpaid work). There were 191 (0.16%) data entry errors. Conclusion: The items and questionnaires were reliable and data quality control was excellent. When we eventually obtain our risk index for the onset and persistence of depression, we will be able to determine the individual risk of each patient evaluated in primary health care.The research in Spain was funded by grants from the Spanish Ministry of Health (grant FIS references: PI04/1980, PI0/41771, PI04/2450, and PI06/1442), Andalusian Council of Health (grant references: 05/403, 06/278 and 08/0194), and the Spanish Ministry of Education and Science (grant reference SAF 2006/07192). The Malaga sample, as part of the predictD-International study, was also funded by a grant from The European Commission (reference QL4-CT2002-00683)

Predicting the onset of hazardous alcohol drinking in primary care: development and validation of a simple risk algorithm.

Little is known about the risk of progressing to hazardous alcohol use in abstinent or low-risk drinkers. To develop and validate a simple brief risk algorithm for the onset of hazardous alcohol drinking (HAD) over 12 months for use in primary care. Prospective cohort study in 32 health centres from six Spanish provinces, with evaluations at baseline, 6 months, and 12 months. Forty-one risk factors were measured and multilevel logistic regression and inverse probability weighting were used to build the risk algorithm. The outcome was new occurrence of HAD during the study, as measured by the AUDIT. From the lists of 174 GPs, 3954 adult abstinent or low-risk drinkers were recruited. The 'predictAL-10' risk algorithm included just nine variables (10 questions): province, sex, age, cigarette consumption, perception of financial strain, having ever received treatment for an alcohol problem, childhood sexual abuse, AUDIT-C, and interaction AUDIT-C*Age. The c-index was 0.886 (95% CI = 0.854 to 0.918). The optimal cutoff had a sensitivity of 0.83 and specificity of 0.80. Excluding childhood sexual abuse from the model (the 'predictAL-9'), the c-index was 0.880 (95% CI = 0.847 to 0.913), sensitivity 0.79, and specificity 0.81. There was no statistically significant difference between the c-indexes of predictAL-10 and predictAL-9. The predictAL-10/9 is a simple and internally valid risk algorithm to predict the onset of hazardous alcohol drinking over 12 months in primary care attendees; it is a brief tool that is potentially useful for primary prevention of hazardous alcohol drinking

Examples of predicted probabilities of anxiety at baseline.

<p>(*)The possible range of the SF-12 is 0–100. High scores indicate good health/well-being. Mean (Standard Deviation) Short Form 12 (SF-12) mental and physical subscale scores for Spain are 47.1 (12.4) and 43.8 (11.4), respectively <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0106370#pone.0106370-Belln3" target="_blank">[39]</a>.</p><p>Examples of predicted probabilities of anxiety at baseline.</p

Predicted probability cut-points to predict anxiety syndromes at 12 months and their associated validity.

<p>LR+ Likelihood ratio of the positive test; LR- Likelihood ratio of the negative test.</p><p>*Cutpoint where Youden's J statistic (J  =  Sensitivity + Specificity -1) was greater.</p><p>Predicted probability cut-points to predict anxiety syndromes at 12 months and their associated validity.</p

Area under the ROC curve for the models with/without interactions.

<p>Footnote toFigure 5: <i>predictA: model without interactions predictA3: model with 3 interactions</i>.</p

Comparison of the base model with the models including each of the interactions tested.

#<p>The model sex*province did not converge.</p><p>Comparison of the base model with the models including each of the interactions tested.</p

Demographic characteristics of participants without anxiety at baseline (population at risk).

<p>Demographic characteristics of participants without anxiety at baseline (population at risk).</p

Incidence of anxiety by age and sex.

<p>Incidence of anxiety by age and sex.</p