Causation Learning Objectives To be able to discuss Different Theories of causation Causation in Infectious vs. Chronic Disease Modern view of causation Original file - http://www.pitt.edu/~super7/50011-51001/50361.ppt

Jay M. Fleisher MS, Ph.D. Associate Professor, Nova Southeastern University Studied at: Columbia University School of Public Health MS Epidemiology NYU Ph.D. Environmental Epidemiology/Biostatistics

Causation Two types of medical research Bench work Epidemiology Bench work usually describes the underlying biology of disease Epidemiology either tests the results of bench work on human populations or provides input to the biomedical scientist on what we still do not know 1. Bench or laboratory Science usually can control the environment the experiment is taking place in - Control for diet, and environment Animal is in 2. Epidemiology cannot directly control for a human subjects environment - Therefore Epi uses certain methods to study illness among populations and attempts to control for differences in the individual study subjects “environment” - We do this using a combination of Methods of Study design and Statistical analyses

What does the term “ Causal” really mean?

Example #1 - HIV and AIDS Epidemiology identifies new disease caused by defect in immune system Bench science identifies the infectious agent Epidemiological studies confirm that agent causes disease in humans Causation is proven 1. Not everyone exposed to HIV seroconverts 2. Among health care workers, less that 1% of those exposed via needle sticks seroconvert 3. Why? WE DO NOT KNOW ALL THE REASONS 4. THEREFORE OUR KNOWLEDGE OF CAUSATION OF EVEN AIDS IS INCOMPLETE

Example #2 - What Causes an MI Epidemiological studies combined with laboratory study identify risk factors Cigarette smoking Cholesterol Elevated blood pressure Stress Family history Obesity Etc Which of the above contribute the most risk What are the relationships between risk factors 1. What is the ‘Cause” of an MI

Therefore: The issue of causation is not as simple as it first appears Thus, the need for a unifying concept of causation

A Unifying Model of Causal Relationships

The 2 Components: Sufficient Cause Necessary Cause precedes the disease if the cause is present, the disease always occurs Necessary Cause if the cause is absent, the disease cannot occur 1. Using these 2 components of Causation, we can produce a unified frame work of causation that will encompass all Disease Processes

The 4 Models of Causal Relationships

1. Necessary and Sufficient* Only Factor A Disease 1. If the Factor is Present, the Disease will Always Occur 2. Without the factor, the Disease NEVER develops 3. Most infectious diseases will not cause illness in everyone, and not all heavy smokers develop Lung Ca 3. Almost never exists in Medicine Except for certain types of genetic illness like Sickle cell Anemia, Downs Syndrome, and perhaps HIV -> AIDS Sickle Cell Anemia Genetic factors * RARELY OCCUR

2. Necessary but Not Sufficient Factor A + Factor B Disease 1. Each factor necessary but not in itself sufficient to cause the illness in itself , all are necessary to cause disease, but individually, none are sufficient to cause the disease 2. Each Risk factor alone Cannot Cause Disease 2. Thus multiple factors are required often in a specified temporal sequence 3. EX: Carcinogenesis -> + Factor C

2. Necessary but Not Sufficient - Example Initiation + Latent Period Cancer 1.Carcinogenesis is considered to be a multistage process involving Initiation and promotion -Promoter damages the cell in some way - theory of many hits to cell in order to produce the first Ca cell could comprise the Latent Period Finally last hit on cell is the Promoter that turns cell into a Ca cell + Promoter

3. Sufficient but Not Necessary Factor A Factor B Disease 1. In this model each risk factor Sufficient to cause disease, but not all risk factors necessary in disease causation ( If Factor C is absent, disease can still occur) 1. In this Model each risk factor can produce the illness without the other factors being present 2. Unlike the Concept of Necessary and Sufficient Model, the disease CAN develop without a specific Necessary cause 3. However, not really Sufficient because other co-factors either known or unknown are in the causal process Factor C

3. Sufficient but Not Necessary - Example Ionizing Radiation or Benzene Leukemia 1. In this Model each risk factor can produce the illness without the other factors being present 2. If exposed to enough Radiation, other 2 Risk factors not necessary to cause the illness Ionizing Radiation, Benzene exposure and possibly Electromagnetic fields can each cause Leukemia independently of each other However, other co – factors in causal process e.e., not all exposed to benzene will get Leukemia or Electromagnetic Fields?

4. Neither Sufficient Nor Necessary Factor A + Factor B and/or + Disease Factor C Factor D and/or 1. Illustrative of most of today’s Chronic diseases 2. Risk Factors combine in ways we know little about to produce disease 3. Therefore, No single factor will cause the disease by itself ( None are Sufficient Causes), and not all are necessary for the disease to Occur ( only a few can cause disease) + Factor E Factor F

4. Neither Sufficient Nor Necessary - Example Smoking + Cholesterol and/or + MI HBP Fam. History and/or 1. Which combination of Risk factors will cause an MI 2. Doesn’t have to be all of these risk factors 3. We just don’t know 4. If we look at the risk factors, none are sufficient by themselves, and not all are needed ( thus not all are necessary) + Stress Obesity

Therefore: Concept of Necessary vs. Sufficient Causes provides a theoretical framework for causation of all disease How do we actually assess whether a Risk Factor is indeed Causal

Criteria for Assessing Causation Temporal relationship Exposure precedes the disease Strength of the Association Measured by the Relative Risk ( either the Rate Ratio or the Odds Ratio) Dose-response Relationship As the dose of exposure increases the risk of disease also increases Example: Cigarette Smoking and Lung Ca Replication of the Findings Results replicated in other studies Biologic plausibility Does the association fit with what we know about the underlying biology Sometimes we know little or nothing about the undelieing biology ( “Black Box” epidemiology Consistency Alternative explanation eliminated Cessation effects Specificity of the Association Dose-response 1. Temporal relationship: Exposure to Risk factor occurred before Illness onset 2. Biological Plausibility - Sometimes we know, sometimes we don’t 3. The relationship is verified by repeated studies 4. Alternate Explaination Eliminated: Hard to prove a negative 5. Cessation Effect: Risk Drops in absence of exposure to the risk factor 6. Strength of Association: usually measured via relative Risk.. Higher the relative Risk, more likely Causal 7. Specificity of the Association: Specific Exposure Associated with only 1 disease - throw back to Infectious disease theory - Not generally applicable as Shown by previous discussion of Frame Work of Causation 8. Dose response strong evidence for Causal relationship

Criteria for Assessing Causation Biologic plausibility Does the association fit with what we know about the underlying biology Sometimes we know little or nothing about the underlying biology ( “Black Box” epidemiology) Example – Asbestosis and Lung Ca.. Only have theory of mechanism Consideration of Alternate Explanations If knowledge exists, rule out or make sure studies took into account Cessation of Exposure If exposure is reduced or eliminated Risk will decline Example Ex-Smokers Specificity of the Association A specific agent is associated with only 1 disease OK for infectious agents but falls apart with many Risk Factors for Chronic Illness Example: Cigarette Smoking associated with several diseases 1. Temporal relationship: Exposure to Risk factor occurred before Illness onset 2. Biological Plausibility - Sometimes we know, sometimes we don’t 3. The relationship is verified by repeated studies 4. Alternate Explaination Eliminated: Hard to prove a negative 5. Cessation Effect: Risk Drops in absence of exposure to the risk factor 6. Strength of Association: usually measured via relative Risk.. Higher the relative Risk, more likely Causal 7. Specificity of the Association: Specific Exposure Associated with only 1 disease - throw back to Infectious disease theory - Not generally applicable as Shown by previous discussion of Frame Work of Causation 8. Dose response strong evidence for Causal relationship

Relevant Web Sites http://www.defendingscience.org/sites/default/files/upload/Rothman-Greenland.pdf http://www.facmed.unam.mx/deptos/salud/censenanza/spiii/spiii/rothman.pdf http://www.defendingscience.org/sites/default/files/upload/Rothman-Greenland.pdf http://www.facmed.unam.mx/deptos/salud/censenanza/spiii/spiii/rothman.pdf