External validation, update and development of prediction models for pre-eclampsia using an Individual Participant Data (IPD) meta-analysis: the International Prediction of Pregnancy Complication Network (IPPIC pre-eclampsia) protocol.

Background: Pre-eclampsia, a condition with raised blood pressure and proteinuria is associated with an increased risk of maternal and offspring mortality and morbidity. Early identification of mothers at risk is needed to target management. Methods/design: We aim to systematically review the existing literature to identify prediction models for pre-eclampsia. We have established the International Prediction of Pregnancy Complication Network (IPPIC), made up of 72 researchers from 21 countries who have carried out relevant primary studies or have access to existing registry databases, and collectively possess data from more than two million patients. We will use the individual participant data (IPD) from these studies to externally validate these existing prediction models and summarise model performance across studies using random-effects meta-analysis for any, late (after 34 weeks) and early (before 34 weeks) onset pre-eclampsia. If none of the models perform well, we will recalibrate (update), or develop and validate new prediction models using the IPD. We will assess the differential accuracy of the models in various settings and subgroups according to the risk status. We will also validate or develop prediction models based on clinical characteristics only; clinical and biochemical markers; clinical and ultrasound parameters; and clinical, biochemical and ultrasound tests. Discussion: Numerous systematic reviews with aggregate data meta-analysis have evaluated various risk factors separately or in combination for predicting pre-eclampsia, but these are affected by many limitations. Our large-scale collaborative IPD approach encourages consensus towards well developed, and validated prognostic models, rather than a number of competing non-validated ones. The large sample size from our IPD will also allow development and validation of multivariable prediction model for the relatively rare outcome of early onset pre-eclampsia. Trial registration: The project was registered on Prospero on the 27 November 2015 with ID: CRD42015029349

Coping strategies of women with postpartum depression symptoms in rural Ethiopia: a cross-sectional community study

Background: Most women with postpartum depression (PPD) in low- and middle-income countries remain undiagnosed and untreated, despite evidence for adverse effects on the woman and her child. The aim of this study was to identify the coping strategies used by women with PPD symptoms in rural Ethiopia to inform the development of socio-culturally appropriate interventions. Methods: A population-based, cross-sectional study was conducted in a predominantly rural district in southern Ethiopia. All women with live infants between one and 12 months post-partum (n = 3147) were screened for depression symptoms using the validated Patient Health Questionnaire, 9 item version (PHQ-9). Those scoring five or more, ‘high PPD symptoms’, (n = 385) were included in this study. The Brief Coping with Problems Experienced (COPE-28) scale was used to assess coping strategies. Construct validity of the brief COPE was evaluated using confirmatory factor analysis. Results: Confirmatory factor analysis of the brief COPE scale supported the previously hypothesized three dimensions of coping (problem-focused, emotion-focused, and dysfunctional). Emotion-focused coping was the most commonly employed coping strategy by women with PPD symptoms. Urban residence was associated positively with all three dimensions of coping. Women who had attended formal education and who attributed their symptoms to a physical cause were more likely to use both problem-focused and emotion-focused coping strategies. Women with better subjective wealth and those who perceived that their husband drank too much alcohol were more likely to use emotion-focused coping. Dysfunctional coping strategies were reported by women who had a poor relationship with their husbands. Conclusions: As in high-income countries, women with PPD symptoms were most likely to use emotion-focused and dysfunctional coping strategies. Poverty and the low level of awareness of depression as an illness may additionally impede problem-solving attempts to cope. Prospective studies are needed to understand the prognostic significance of coping styles in this setting and to inform psychosocial intervention development

Systematic review of prognostic models for recurrent venous thromboembolism (VTE) post-treatment of first unprovoked VTE.

OBJECTIVES: To review studies developing or validating a prognostic model for individual venous thromboembolism (VTE) recurrence risk following cessation of therapy for a first unprovoked VTE. Prediction of recurrence risk is crucial to informing patient prognosis and treatment decisions. The review aims to determine whether reliable prognostic models exist and, if not, what further research is needed within the field. DESIGN: Bibliographic databases (including MEDLINE, EMBASE and the Cochrane Library) were searched using index terms relating to the clinical field and prognosis. Screening of titles, abstracts and subsequently full texts was conducted by 2 reviewers independently using predefined criteria. Quality assessment and critical appraisal of included full texts was based on an early version of the PROBAST (Prediction study Risk Of Bias Assessment Tool) for risk of bias and applicability in prognostic model studies. SETTING: Studies in any setting were included. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome for the review was the predictive accuracy of identified prognostic models in relation to VTE recurrence risk. RESULTS: 3 unique prognostic models were identified including the HERDOO2 score, Vienna prediction model and DASH score. Quality assessment highlighted the Vienna, and DASH models were developed with generally strong methodology, but the HERDOO2 model had many methodological concerns. Further, all models were considered at least at moderate risk of bias, primarily due to the need for further external validation before use in practice. CONCLUSIONS: Although the Vienna model shows the most promise (based on strong development methodology, applicability and having some external validation), none of the models can be considered ready for use until further, external and robust validation is performed in new data. Any new models should consider the inclusion of predictors found to be consistently important in existing models (sex, site of index event, D-dimer), and take heed of several methodological issues identified through this review. PROSPERO REGISTRATION NUMBER: CRD42013003494

Multivariate meta-analysis of individual participant data helped externally validate the performance and implementation of a prediction model

OBJECTIVES: Our aim was to improve meta-analysis methods for summarizing a prediction model's performance when individual participant data are available from multiple studies for external validation. STUDY DESIGN AND SETTING: We suggest multivariate meta-analysis for jointly synthesizing calibration and discrimination performance, while accounting for their correlation. The approach estimates a prediction model's average performance, the heterogeneity in performance across populations, and the probability of "good" performance in new populations. This allows different implementation strategies (e.g., recalibration) to be compared. Application is made to a diagnostic model for deep vein thrombosis (DVT) and a prognostic model for breast cancer mortality. RESULTS: In both examples, multivariate meta-analysis reveals that calibration performance is excellent on average but highly heterogeneous across populations unless the model's intercept (baseline hazard) is recalibrated. For the cancer model, the probability of "good" performance (defined by C statistic ≥0.7 and calibration slope between 0.9 and 1.1) in a new population was 0.67 with recalibration but 0.22 without recalibration. For the DVT model, even with recalibration, there was only a 0.03 probability of "good" performance. CONCLUSION: Multivariate meta-analysis can be used to externally validate a prediction model's calibration and discrimination performance across multiple populations and to evaluate different implementation strategies