1. Biostatistics

2. But why? Why do we read scientific litterature? How do we read scientific litterature?

3. Different types of literature Experimental studies –Clinical trials Observational studies –Cohort study Longitudinal, and prospective, time and patient consuming –Case-control study Can be applied with low sampling number, difficult to choose the control –Cross-sectional study / survey Inexpensive, historical, provides the current –Case-series study Usually reports unexpected clinical observations Meta-analysis Reviews

4. Anatomy of most articles Abstract Introduction Methods Results Discussion Conclusion

5. Abstracts Usually structured as a mini-article The purpose is to ‘sell’ the article By reading the abstract you should be able to tell the conclusions made by the authors By only reading the abstract you cannot judge the validity of the conclusions. Consider this: –If the study is well performed, is the results interesting? –If the results are statistically significant, is the magnitude of changes/differences clinically relevant? –If the results are not statistically significant, was the sample size large enough?

6. Introduction Justification / Rationale, why was the study done? Context Hypothesis Aim of the study –Usually the last paragraph of the introduction. Population in the study –Location, time, subjects

7. Method I How was the study performed –You should be able to understand the method section, and if you are familiar with the research field you should be able to reproduce the experiment What is studies? –Patients, Which? Exclusion / inclusion How is the study performed? How is the data analyzed? –E.g. normalization Which statistics is applied? –Are assumptions violated?

8. Metode II (Subjects) How are the patients selected? –How are they randomized? What are the inclusion/exclusion criterions? –Is it reasonable? –Are these patients relevant for your research? Are there follow-up? –How are they handled? How are withdrawers handled? –Intention to treat

9. Metode III (subjects)

10. Metode IV (subjects) Bias by selection of patients –Prevalence E.g. if patients die before inclusion

11. Method V (Subjects) Bias by selection of patients –Admission rate bias E.g. if control and treatment groups are not concurrent –Non-responders and voluntariness Recall the example with vaccine from first lecture. –Grouping bias Causality and the healthy worker –Choice of procedure Deductive procedures Different procedures for control and treatment groups Concurrency Randomization

12. Method VI Procedure in the study –Procedure bias If the groups are not treated in the same way If e.g. one treatment group demands more follow-ups than other treatments –Memory bias Use diary instead –Apparatus bias Inaccurate devices Poor handling –Diagnostic bias E.g. if two groups are not diagnosed in the same way. –Compliance It may be more difficult for patients/subjects to cooperate if one treatment is painful or unpleasant than others

13. Method VII Measurements –Variations in the measurements Whatever is measured will have a natural variation The person who measures is not measuring accurately e.g. røntgen Some outcomes are not well-defined, e.g. pain The device or the method is not accurate or indirect –Reliability and validity New methods must describe the usefulness –Blinding –Data quality, questioners, multi-center studies

14. Method VIII Number of subjects –Type II error: No difference were found due to low number of subjects. –Power test, if negative results are reported

15. Method IX Statistical methods –Are the methods appropriate and valid? –Are the assumptions violated? –Is it a fishing trip? –Multi-significance Type I errors, false positives Analysis along the way must be scheduled before performing the study –Migration bias Intention-to-treat –Entry time

16. Results This is where results, figures, tables and the statistics are presented Does the results support the conclusion? –What is the baseline? –Risk of multiple comparison errors –Is the result consistent?

17. Diskussion og konklusion Is there connection between the hypothesis, results and the conclusion? Are there any short-comings? How does the conclusion affect your research?

18. Opgaver Discuss Leibovici (2000) 7, 8, 9, 11, 12, 66, 67, 68, 69