Dr Laure Wynants (L.)

Collins, G. S., Moons, K. G. M., Dhiman, P., Riley, R. D., Beam, A. L., Van Calster, B., Ghassemi, M., Liu, X., Reitsma, J. B., van Smeden, M., Boulesteix, A. L., Camaradou, J. C., Celi, L. A., Denaxas, S., Denniston, A. K., Glocker, B., Golub, R. M., Harvey, H., Heinze, G., ... Logullo, P. (2024). TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods. BMJ, 385, Article 078378. https://doi.org/10.1136/bmj-2023-078378

de Kok, J. W. T. M., van Bussel, B. C. T., Schnabel, R., van Herpt, T. T. W., Driessen, R. G. H., Meijs, D. A. M., Goossens, J. A., Mertens, H. J. M. M., van Kuijk, S. M. J., Wynants, L., van der Horst, I. C. C., & van Rosmalen, F. (2024). Table 0; documenting the steps to go from clinical database to research dataset. Journal of Clinical Epidemiology, 170, Article 111342. Advance online publication. https://doi.org/10.1016/j.jclinepi.2024.111342

Heremans, R., Wynants, L., Valentin, L., Leone, F. P. G., Pascual, M. A., Fruscio, R., Testa, A. C., Buonomo, F., Guerriero, S., Epstein, E., Bourne, T., Timmerman, D., Van den Bosch, T., & IETA consortium (2024). Estimating risk of endometrial malignancy and other intracavitary uterine pathology in women without abnormal uterine bleeding using IETA-1 multinomial regression model: validation study. Ultrasound in Obstetrics & Gynecology, 63(4), 556-563. https://doi.org/10.1002/uog.27530

Barreñada, L., Ledger, A., Dhiman, P., Collins, G., Wynants, L., Verbakel, J. Y., Timmerman, D., Valentin, L., & Van Calster, B. (2024). ADNEX risk prediction model for diagnosis of ovarian cancer: systematic review and meta-analysis of external validation studies. BMJ Medicine, 3(1), Article 000817. https://doi.org/10.1136/bmjmed-2023-000817

Deisenhofer, A.-K., Barkham, M., Beierl, E. T., Schwartz, B., Aafjes-van Doorn, K., Beevers, C. G., Berwian, I. M., Blackwell, S. E., Bockting, C. L., Brakemeier, E.-L., Brown, G., Buckman, J. E. J., Castonguay, L. G., Cusack, C. E., Dalgleish, T., de Jong, K., Delgadillo, J., DeRubeis, R. J., Driessen, E., ... Et al. (2024). Implementing precision methods in personalizing psychological therapies: Barriers and possible ways forward. Behaviour Research and Therapy, 172, Article 104443. https://doi.org/10.1016/j.brat.2023.104443

Dillen, H., Wouters, J., Snijders, D., Wynants, L., & Verbakel, J. Y. (2023). Factors associated with inappropriateness of antibiotic prescriptions for acutely ill children presenting to ambulatory care in high-income countries: a systematic review and meta-analysis. Journal of Antimicrobial Chemotherapy, 79(3), 498-511. Article dkad383. https://doi.org/10.1093/jac/dkad383

Gao, S., Albu, E., Tuand, K., Cossey, V., Rademakers, F. E., Van Calster, B., & Wynants, L. (2023). Systematic review finds risk of bias and applicability concerns for models predicting central line-associated bloodstream infection (CLA-BSI). Journal of Clinical Epidemiology, 161(1), 127-139. https://doi.org/10.1016/j.jclinepi.2023.07.019

Sadatsafavi, M., Lee, T. Y., Wynants, L., Vickers, A. J., & Gustafson, P. (2023). Value-of-Information Analysis for External Validation of Risk Prediction Models. Medical Decision Making, 43(5), 564-575. https://doi.org/10.1177/0272989X231178317

Vickers, A. J., Van Claster, B., Wynants, L., & Steyerberg, E. W. (2023). Decision curve analysis: confidence intervals and hypothesis testing for net benefit. Diagnostic and prognostic research, 7(1), Article 11. https://doi.org/10.1186/s41512-023-00148-y

Arshi, B., Wynants, L., Rijnhart, E., Reeve, K., Cowley, L. E., & Smits, L. J. (2023). What proportion of clinical prediction models make it to clinical practice? Protocol for a two-track follow-up study of prediction model development publications. BMJ Open, 13(5), Article e073174. https://doi.org/10.1136/bmjopen-2023-073174