Methods and Biostatistics in Oncology Understanding Clinical Research as an Applied Tool /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Araújo, Raphael. L.C (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Riechelmann, Rachel P. (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Έκδοση: 1st ed. 2018.
• Θέματα: Oncology .; Biostatistics.; Cancer research.; Oncology.; Cancer Research.

 This book introduces and discusses the most important aspects of clinical research methods and biostatistics for oncologists, pursuing a tailor-made and practical approach. Evidence-based medicine (EBM) has been in vogue in the last few decades, particularly in rapidly advancing fields such as oncology. This approach has been used to support decision-making processes worldwide, sparking new clinical research and guidelines on clinical and surgical oncology. Clinical oncology research has many peculiarities, including specific study endpoints, a special focus on survival analyses, and a unique perspective on EBM. However, during medical studies and in general practice, these topics are barely taught. Moreover, even when EBM and clinical cancer research are discussed, they are presented in a theoretical fashion, mostly focused on formulas and numbers, rather than on clinical application for a proper literature appraisal. Addressing that gap, this book discusse s more practical aspects of clinical research and biostatistics in oncology, instead of relying only on mathematical formulas and theoretical considerations. Methods and Biostatistics in Oncology will help readers develop the skills they need to understand the use of research on everyday oncology clinical practice for study design and interpretation, as well to demystify the use of EBM in oncology. 

 Preface -- Introduction -- 1. Background of scientific method in oncology -- 2. Writing a hypothesis for a oncology study -- 3. Type of variables and distributions -- 4. Testing measures of association -- 5. Sample size calculation for oncology trials -- 6. Uni and multivariate analysis (understanding of regressions) in cancer research -- 7. Survival analyses in cancer trials -- 8. The role of transversal and cohort studies in oncology -- 9. Design of retrospective and case-control studies in oncology -- 10. Minimizing differences by randomization -- 11. How to design phase I trials in oncology -- 12. The many different designs of phase II oncology trials -- 13. Superiority and non-inferiority phase III oncology trials -- 14. Phase IV oncology trials -- 15. Analysis of graphs in clinical cancer research -- 16. Identifying biases in clinical cancer research -- 17. Ethics in clinical cancer research -- 18. Cost-effectiveness studies in oncology -- 19. How to undertake outcomes research in oncology -- 20. Systematic review and meta-analysis of oncology studies -- 21. Meta-research in oncology -- 22. Analysis of quality of life and patient-reported outcomes in oncology -- Exercises -- Commented answers -- Glossary -- Remissive index.