Prognosis Research in Healthcare Concepts, Methods, and Impact

"What is going to happen to me?" Most patients ask this question during a clinical encounter with a health professional. As well as learning what problem they have (diagnosis) and what needs to be done about it (treatment), patients want to know about their future health and wellbeing (prognosis). Prognosis research can provide answers to this question and satisfy the need for individuals to understand the possible outcomes of their condition, with and without treatment.

Central to modern medical practise, the topic of prognosis is the basis of decision making in healthcare and policy development. It translates basic and clinical science into practical care for patients and populations. Prognosis Research in Healthcare: Concepts, Methods and Impact provides a comprehensive overview of the field of prognosis and prognosis research and gives a global perspective on how prognosis research and prognostic information can improve the outcomes of healthcare. It details how to design, carry out, analyse and report prognosis studies, and how prognostic information can be the basis for tailored, personalised healthcare. In particular, the book discusses how information about the characteristics of people, their health, and environment can be used to predict an individual's future health.

Prognosis Research in Healthcare: Concepts, Methods and Impact, addresses all types of prognosis research and provides a practical step-by-step guide to undertaking and interpreting prognosis research studies, ideal for medical students, health researchers, healthcare professionals and methodologists, as well as for guideline and policy makers in healthcare wishing to learn more about the field of prognosis.

Richard Riley, Professor of Biostatistics, Research Institute of Primary Care and Health Sciences, Keele University, UK,Danielle van der Windt, Professor of Primary Care Epidemiology, Research Institute of Primary Care and Health Sciences, Keele University, UK,Peter Croft, Professor of Primary Care Epidemiology, Research Institute of Primary Care and Health Sciences, Keele University, UK,Karel G.M. Moons, Professor of Clinical Epidemiology, Julius Center for Health Sciences and Primary Care, Utrecht University Medical Centre, The Netherlands

Richard Riley is a Professor of Biostatistics at Keele University since 2014, having previous held posts at the Universities of Birmingham, Liverpool and Leicester. He is focused on statistical and methodological research for prognosis and meta-analysis, and supports clinical projects in these areas. He is also a Statistics Editor for the BMJ and a co-convenor of the Cochrane Prognosis Methods Group. Prof Riley co-leads a summer school in Prognosis Research Methods, and leads a number of statistical training courses for risk prediction and meta-analysis

Professor Danielle van der Windt received her academic training in epidemiology in the Netherlands at the EMGO+ Institute for Health and Care Research of the VU University in Amsterdam where she worked in a programme of research on the diagnosis, prognosis and management of musculoskeletal disorders. She is currently a Professor of primary care epidemiology at Keele, and is part of the Centre's executive management team

Professor Peter Croft is a Professor of Primary Care Epidemiology at Keele since 1994. Previously, he worked as a General Practitioner in Newcastle-under-Lyme, before training as an epidemiologist at the Medical Research Council's Environmental Epidemiology Unit in Southampton, and at the Arthritis Research Campaign's Epidemiology Research Unit in Manchester

Professor Karel G.M. Moons is Professor of Clinical Epidemiology at the Julius Center for Health Sciences and Primary Care. He is Director of Research in the management team of the Julius Center, and leads the research programme 'Methodology'. Since 2005 also he has an Adjunct Professorship at VanderBilt University, Nashville, USA. Having obtained his PhD in Epidemiology at Erasmus University, Rotterdam, he has been Visiting Professor at the University of Virginia, Charlottesville, USA in 2002, and at Tokai University, Japan.

Part 1: Introduction to prognosis and prognosis research
1. Prognosis in healthcare, Peter Croft, Richard D. Riley, Danielle A. van der Windt, and Karel G.M. Moons
2. A framework for prognosis research, Peter Croft, Richard D. Riley, Danielle A. van der Windt, Karel G.M. Moons, and Harry Hemingway
Part 2: Fundamental statistics for prognosis research
3. Fundamental statistical methods for prognosis research, Richard D. Riley, Kym I.E. Snell, Karel G.M. Moons, and Thomas P.A. Debray
4. Ten principles to strengthen prognosis research, Richard D. Riley, Kym I.E. Snell, Karel G.M. Moons, and Thomas P.A. Debray
Part 3: Undertaking prognosis research
5. Overall prognosis research, Danielle A. van der Windt, Harry Hemingway, Peter Croft
6. Prognostic factor research, Richard D. Riley, Karel G.M. Moons, Jill A. Hayden, Willi Sauerbrei, Douglas G. Altman
7. Prognostic model research, Richard D. Riley, Karel G.M. Moons, Thomas P.A. Debray, Kym I.E. Snell, Ewout W. Steyerberg, Douglas G. Altman, Gary S. Collins
8. Predictors of treatment effect, Danielle A. van der Windt, Richard D. Riley, Aroon Hingorani, Karel G.M. Moons
9. Systematic reviews and meta-analysis of prognosis research studies, Richard D. Riley, Karel G.M. Moons, Thomas P.A. Debray, Douglas G. Altman, Gary S. Collins
Part 4: Exemplars of prognosis research impact
10. Prognosis research in people with low back pain, Nadine E Foster, Danielle A. van der Windt, Kate M. Dunn, Peter Croft
11. Prognosis research in people with coronary heart disease, Adam Timmis, Pablo Perel, Peter Croft
12. Prognosis research in people with traumatic bleeding, Katherine I. Morley, Pablo Perel
Part 5: Novel Topics in prognosis research
13. Individual participant data meta-analysis of prognosis studies, Richard D. Riley, Thomas P.A. Debray, Karel G.M.Moons
14. Electronic healthcare records and prognosis research, Kelvin P. Jordan, Karel G.M. Moons
15. Novel statistical methods for prognosis research, Michael J. Crowther
16. Machine learning in prognosis research, Mihaela van der Schaar, Harry Hemingway