Translational Medicine: Back to the Future (Practice)

Data

Official data in SubjectManager for the following academic year: 2023-2024

Topic

„You can be a good scientist without medicine, but you cannot be a good physician without science.”
The biggest challenge of modern medicine is the separation of basic and clinical sciences from each other. In most cases the two fields don’t understand each other. Consequently, in many cases there are lack of knowledge considering the onset of diseases, the pathomechanisms, also the shortcomings of prevention and our limited interventional, operative and pharmacological treatment options. Despite the excessive fundings of the development of pharmaceuticals, the number of drugs or new interventions used in clinical practise remains almost the same. Clinical research is far behind Basic Science in activity and clinical practice is in opposition to the latest findings of basic research in many countries. Considering all this, it’s clear that successful research is only possible through the co-operation of basic researchers and clinicians, which is Translational Medicine. The main role for Translational Medicine has to be the „interpreteur” for the two fields, by bringing their knowledge and research closer together.
One of the greatest advantages of this system is that the findings of basic research can be used in clinical practice almost immediately, therefore even in the short run the quality of health care can be increased.
This course is produced for those students who completed at least four semesters. Who opt for this subject we kindly ask to take it into consideration.

Lectures

Practices

• 1. Systematic literature search I.: electronic databases
• 2. Systematic literature search II.: search strategy
• 3. Questions of meta-analyses: the PICO system
• 4. Systematic data collection: theoretical and practical consideration
• 5. Statistics I.: data types
• 6. Statistics II: the forest plot
• 7. Statistics III.: heterogeneity and its causes
• 8. Risk of bias assessment
• 9. Evidence evaluation
• 10. Patient registries
• 11. Operation of registries
• 12. Data analysis, statistics
• 13. Observational clinical trials I.: analytical studies: cohort, case-control, cross-sectional studies
• 14. Observational clinical trials II.: descriptive studies
• 15. Intervention studies I.: randomization and blinding
• 16. Intervention studies II.: types of interventions, selection of endpoints
• 17. Statistics: sample size estimation, intention-to-treat and per-protocol analysis, subgroup analysis
• 18. Distortions in observational and interventional clinical trials
• 19. Implementation of the results in clinical practice and research planning
• 20. Abstract, presentation, publication: When, what, for what purpose and for whom?

Seminars

Reading material

Obligatory literature

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Literature developed by the Department

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Notes

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Recommended literature

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Conditions for acceptance of the semester

Maximum of 15 % absence allowed

Mid-term exams

At the end of the course students need to pass a written test-exam.

Making up for missed classes

There is no possibility for replacement of absence.

Exam topics/questions

Exam topics are based on the practices and seminars.

Examiners

Instructor / tutor of practices and seminars

• Dr. Hegyi Péter