Foundations of Medical Knowledge (Medical Humanities curriculum)
Foundations of Medical Knowledge (Medical Humanities curriculum)
8-25 June 2020
Milan
Teacher: Paolo Bruzzi, Genova
Dates: 8-10-12 June 2020; 15-17-18-19 June 2020; 22-24-25 June 2020
Format: Online course
Timetable
9.30-12.30
Lesson Argument
Medicine and Statistics:
Failure of the old mechanistic medical models
Indeterminism in modern medicine
Individual patient
Prediction of outcome
Assessment of the effect of an intervention
Prediction in the effects of an intervention
How to assess the effects of an intervention:
Activity vs Efficacy
The randomised trial
Timetable
9.30-12.30
Lesson Argument
Statistics (1)
Variables
Types & Distributions
Summary indicators
Statistics and Parameters
Errors in Estimates: Sampling error & Bias
Sampling error – Central Limit theorem
Standard Error and Confidence Limits
Timetable
9.30-12.30
Lesson Argument
Statistics (2)
Continuous Variables: Mean, Standard Deviation, Standard Error
Binary Variables: Proportion, Standard Error
Discrete Variables: Frequency Distribution
Time-to-event variables (Survival analyses)
Timetable
9.30-12.30
Lesson Argument
Study designs:
Observational vs Experimental studies
Observational studies
Retrospective vs Prospective
Descriptive
Ecological correlation
Analytical (cross-sectional vs case-control vs cohort studies)
Experimental studies (trials)
Phases of trials
Uncontrolled vs Controlled efficacy trials
The Randomised Controlled Trial (RCT)
Specific aims
Study design (Contrast)
Randomization
Endpoint and Masking
Selection of patients
Statistical Plan (Contents)
Timetable
9.30-12.30
Lesson Argument
Statistics (3)
Probability (Definitions)
Frequentist and Bayesian Probabilities
Test of significance: definition
Test of significance vs estimation
Associations between variables and commonly used tests of significance
Continuous with binary/discrete
Continuous with continuous
Binary with binary
Discrete with discrete
Timetable
9.30-12.30
Lesson Argument
Statistics (4)
The analysis of a controlled trial
Intention to treat
Statistical Plan - Introduction to Multiplicity
Multplicity: general Principles
Multiple endpoints
Interim analyses
Subgroup analyses
Timetable
9.30-12.30
Lesson Argument
Endpoints & Surrogate endpoints
Definitions and concepts
Properties
Surrogacy: relevance
Validity and Validation of a surrogate endpoint
Timetable
9.30-12.30
Lesson Argument
Statistics (5)
Accuracy and Precision of a measurement
Sensitivity, Specificity and predictive value of a diagnostic test
The theory of screening
Statistics (6)
Survival Analysis: Summary indicators of treatment effect
Hazard ratio and the Cox Model
Introduction to multivariate analyses