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Webinar Talk 1: The Planning and Conducting of a Prognostic Research Prognostic Studies Combination of predictors that give you quantitative knowledge on occurrence/complications in absolute risk (hot relative risk) the aim of true prognostic study is to provide absolute risk → not to confuse prognostic with aetiological study Model development validation → prove the score able to predict outcome accurately in real life situation. Good discrimination model: as much the positive, less false positive model AUC (Area under curve): 0.70 ( The closer to 1.0; the better the prediction of the probability) To adopt any prognostic model, must always validate in targeted population. Clinical implication - need to think also the practicality in real life.   SUMMARY Prognostic research is multivariable in nature follows usual clinical care It can actually work in real life Absolute risks are required validation   Further recommended readings: Karel G M Moons, Douglas G Altman, Yvonne Vergouwe, Patrick Royston. Prognosis and prognostic research: application and impact of prognostic models in clinical practice. BMJ. 2009 Jun 4;338:b606. doi: 10.1136/bmj.b606.                                https://www.bmj.com/content/338/bmj.b606.long Riley RD, Ensor J, Snell KIE, Harrell FE Jr, Martin GP, Reitsma JB, Moons KGM, Collins G, van Smeden M. Calculating the sample size required for developing a clinical prediction model. BMJ. 2020 Mar 18;368:m441. doi: 10.1136/bmj.m441. PMID: 32188600. https://eprints.keele.ac.uk/7880/1/bmj.m441.full.pdf

Updated:: 21/07/2023 [intanbasirah]