Biostatistics
But why?
• Why do we read scientific litterature?
• How do we read scientific litterature?
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
Anatomy of most articles
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Abstract
Introduction
Methods
Results
Discussion
Conclusion
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?
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
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?
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
Metode III (subjects)
Metode IV (subjects)
• Bias by selection of patients
– Prevalence
• E.g. if patients die before inclusion
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
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Deductive procedures
Different procedures for control and treatment groups
Concurrency
Randomization
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
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
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
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
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?
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?
Opgaver
• Discuss Leibovici (2000)
• 7, 8, 9, 11, 12, 66, 67, 68, 69