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My research investigates approaches for deriving and validating prediction models when multiple sources of evidence are available. Particularly, we propose methods to aggregate previously published prediction models and associations with new data, methods to combine multiple datasets, methods to quantify heterogeneity and interpret external validity.


van Doorn S, Debray TPA, Kaasenbrood F, Hoes AW, Rutten FH, Moons KGM, Geersing GJ. Predictive performance of the CHA2DS2-VASc rule in atrial fibrillation: a systematic review and meta-analysis. J Thromb Haemost 0 (pp. ).

Efthimiou O, Mavridis D, Debray TP, Samara M, Belger M, Siontis GC, Leucht S, Salanti G, on behalf of GetReal Work Package 4. Combining randomized and non-randomized evidence in network meta-analysis. Stat Med 36 (pp. 1210-1226).

Debray TPA, Damen JAAG, Snell, KIE, Ensor J, Hooft L, Reitsma JB, Riley RD, Moons KGM. A guide to systematic review and meta-analysis of prediction model performance. BMJ 356 (pp. i6460).

Hummel N, Debray TPA, Didden E-M, Efthimiou O, Egger M, Fletcher C, Moons KG, Reitsma JB, Ruffieux Y, Salanti G, van Valkenhoef G, on behalf of WP4. Methodological guidance, recommendations and illustrative case studies for (network) meta-analysis and modelling to predict real-world effectiveness using individual participant and/or aggregate data. 0 (pp. ).

Rietbergen C, Debray TPA, Klugkist I, Janssen KJM, Moons KG. Use and reporting of Bayesian methods for primary data analysis in epidemiological research: a systematic review. J Clin Epidemiol 0 (pp. ).


Vergouwe Y, Nieboer D, Oostenbrink R, Debray TPA, Murray G, Kattan M, Koffijberg H, Moons KGM, Steyerberg EW. A closed testing procedure to select an appropriate method for updating prediction models. Stat Med 0 (pp. ).

Panayidou K, Gsteiger S, Egger M, Kilcher G, Carreras M, Efthimiou O, Debray TP, Trelle S, Hummel N, on behalf of the GetReal methods review group. GetReal in mathematical modelling: a review of studies predicting drug effectiveness in the real world. Res Synth Methods 7 (pp. 264-77).

Debray TP, Schuit E, Efthimiou O, Reitsma JB, Ioannidis JP, Salanti G, Moons KG, on behalf of GetReal Workpackage 4. An overview of methods for network meta-analysis using individual participant data: when do benefits arise?. Stat Methods Med Res 0 (pp. ).

Riley RD, Ensor J, Snell KI, Debray TP, Altman DG, Moons KG, Collins GS. External validation of clinical prediction models using big datasets from e-health records or IPD meta-analysis: opportunities and challenges. BMJ 353 (pp. i3140).

Damen JA, Hooft L, Schuit E, Debray TP, Collins GS, Tzoulaki I, et al. Prediction models for cardiovascular disease risk in the general population: systematic review. BMJ 353 (pp. i2416).

Groenwold RH, Moons KG, Pajouheshnia R, Altman DG, Collins GS, Debray TP, et al. Explicit inclusion of treatment in prognostic modeling was recommended in observational and randomized settings. J Clin Epidemiol 78 (pp. 90-100).

Efthimiou O, Debray TP, van Valkenhoef G, Trelle S, Panayidou K, Moons KG, Reitsma JB, Shang A, Salanti G, on behalf of the GetReal methods review group. GetReal in network meta-analysis: a review of the methodology. Res Synth Methods 7 (pp. 236-63).

Snell KI, Hua H, Debray TP, Ensor J, Look MP, Moons KG, Riley RD. Multivariate meta-analysis of individual participant data helped externally validate the performance and implementation of a prediction model. J Clin Epidemiol 69 (pp. 40-50).


Ayele HT, Mourik MS, Debray TP, Bonten MJ. Isoniazid Prophylactic Therapy for the Prevention of Tuberculosis in HIV Infected Adults: A Systematic Review and Meta-Analysis of Randomized Trials. PLoS One 10 (pp. e0142290).

Debray TP, Riley RD, Rovers MM, Reitsma JB, Moons KG, on behalf of the Cochrane IPD Meta-analysis Methods group. Individual participant data (IPD) meta-analyses of diagnostic and prognostic modeling studies: guidance on their use. PLoS Med 12 (pp. e1001886).

Debray TP, Moons KG, van Valkenhoef G, Efthimiou O, Hummel N, Groenwold RH, Reitsma JB, on behalf of the GetReal methods review group. Get real in individual participant data (IPD) meta-analysis: a review of the methodology. Res Synth Methods 6 (pp. 293-309).

Riley RD, Ahmed I, Debray TP, Willis BH, Noordzij JP, Higgins JP, Deeks JJ. Summarising and validating test accuracy results across multiple studies for use in clinical practice. Stat Med 34 (pp. 2081-103).

Debray TP, Jolani S, Koffijberg H, van Buuren S, Moons KG. Imputation of systematically missing predictors in an individual participant data meta-analysis: a generalized approach using MICE. Stat Med 34 (pp. 1841-63).

Nell S, Kist JW, Debray TP, de Keizer B, van Oostenbrugge TJ, Borel Rinkes IH, Valk GD, Vriens MR. Qualitative elastography can replace thyroid nodule fine-needle aspiration in patients with soft thyroid nodules. A systematic review and meta-analysis. Eur J Radiol 84 (pp. 652-61).

Debray TP, Vergouwe Y, Koffijberg H, Nieboer D, Steyerberg EW, Moons KG. A new framework to enhance the interpretation of external validation studies of clinical prediction models. J Clin Epidemiol 68 (pp. 279-89).


Debray TP, Koffijberg H, Nieboer D, Vergouwe Y, Steyerberg EW, Moons KG. Meta-analysis and aggregation of multiple published prediction models. Stat Med 33 (pp. 2341-62).

Ahmed I, Debray TP, Moons KG, Riley RD. Developing and validating risk prediction models in an individual participant data meta-analysis. BMC Med Res Methodol 14 (pp. 3).


Onland W, Debray TP, Laughon MM, Miedema M, Cools F, Askie LM, et al. Clinical prediction models for bronchopulmonary dysplasia: a systematic review and external validation study. BMC Pediatr 13 (pp. 207).

Abo-Zaid G, Guo B, Deeks JJ, Debray TP, Steyerberg EW, Moons KG, Riley RD. Individual participant data meta-analyses should not ignore clustering. J Clin Epidemiol 66 (pp. 865-873).

Debray TP, Moons KG, Abo-Zaid GM, Koffijberg H, Riley RD. Individual participant data meta-analysis for a binary outcome: one-stage or two-stage?. PLoS One 8 (pp. e60650).

Debray TP, Moons KG, Ahmed I, Koffijberg H, Riley RD. A framework for developing, implementing, and evaluating clinical prediction models in an individual participant data meta-analysis. Stat Med 32 (pp. 3158-80).


Debray TP, Koffijberg H, Lu D, Vergouwe Y, Steyerberg EW, Moons KG. Incorporating published univariable associations in diagnostic and prognostic modeling. BMC Med Res Methodol 12 (pp. 121).

Debray TPA, Koffijberg H, Vergouwe Y, Moons KGM, Steyerberg EW. Aggregating published prediction models with individual patient data: a comparison of different approaches. Stat Med 31 (pp. 2697-712).

Janssen KJ, Siccama I, Vergouwe Y, Koffijberg H, Debray TP, Keijzer M, Grobbee DE, Moons KG. Development and validation of clinical prediction models: marginal differences between logistic regression, penalized maximum likelihood estimation, and genetic programming. J Clin Epidemiol 65 (pp. 404-12).



Debray TPA. Meta-analysis of clinical prediction models. PhD thesis (2013). Julius Center for Health Sciences and Primary Care. Utrecht University , Utrecht, The Netherlands. [Full Text]

Debray TPA. Classification in Imbalanced Datasets. MSc thesis (2009). Department of Knowledge Engineering. Maastricht University , Maastricht, The Netherlands. [Full Text]