Synthesis: Causal Inference

Synthesis: Causal Inference Kassiani Mellou, based on EPIET material EPIET Introductory Course, Lazareto, Menorca 2011

How do we understand causality? Intuitively?

How is cause defined? “Antecedent event, condition, or characteristic that was necessary for the occurrence of the disease event and without, the disease event either would not have occurred at all or until some time later.” Rothman KJ, Greenland: Causation and Causal Inference in Epidemiology, (Am J PH, 2005)

Cause in the context of epidemiology Count and compare AND Search for cause and effect • Source of the outbreak? • Risk factor for disease? Why? • Implement control measures • Give recommendations

RR = 89.7 95%CI = 82.5 – 91.4 p<0.001 Does a statistical association automatically mean that there is a causal relationship?

Statistical association • Causal ? • Result of • chance • selection bias • information bias • confounding

Henle-Koch-Postulates (1890) • Pathogen must identified in ill person/animal • Pathogen must be culturable • Cultured pathogen should cause illness in test animal • Pathogen must be reisolated and found identical to original

Bradford Hill’s criteria (1965) 1. Strength of Association 2. Consistency 3. Specificity 4. Temporality 5. Biological gradient (dose response) 6. Plausibility 7. Coherence 8. Experimental Evidence 9. Analogy AB Hill: The Environment and Disease: Association or Causation?Proc Royal Soc Med 1965;58:295-300

Criteria for a Causal Relationship • Temporal relationship • Strength of the association • Biologic plausibility • Dose–response relationship • Replication of the findings • Effect of removing the exposure • Extent to which alternate explanations have been considered • Specificity of the association • Consistency with other knowledge L Gordis: Epidemiology 4th revised edition, W. Saunders publishers July 2008

Criteria for a Causal Relationship • Temporal relationship • Strength of the association • Biologic plausibility • Dose–response relationship • Replication of the findings • Effect of removing the exposure • Extent to which alternate explanations have been considered • Specificity of the association • Consistency with other knowledge L Gordis: Epidemiology 4th revised edition, W. Saunder publishers July 2008

Temporal Relationship Exposure must precede disease Essential criterion for causality Knowledge of: • Latency period • Incubation period

Strength of Association Strong associations are more likely being causal than weak ones. Smoking > 20 cigarettes/day  laryngeal carcinoma (RR 20) BUT not all strong associations are causal…

Cases of Down Syndrome by Birth Order

Cases of Down Syndrome by Maternal Age Groups

Strength of Association Strong associations are more likely being causal than weak ones. Smoking > 20 cigarettes/day  laryngeal carcinoma (RR 20) BUT: Not all strong associations are causal… And weak associations do not rule out causality…

Smoking and Lung cancer? Breast cancer? Passive smoking Cigarette smoking and lung cancer RR= ~ 10 Cigarette smoking and breast cancer RR = ~ 1 -1.5 Passive smoking and lung cancer RR = ~ 1.4

Biologic Plausibility Is consistent with current biological and medical common knowledge. Smoking Ingesting of chemicals and known carcinogens DNA mutations lung cancer

Biologic Plausibility Is consistent with current biological and medical common knowledge. • Percivall Pott - scrotum cancer observed in chimney sweeps (1775) • Peptic ulcers and Helicobacter pylori (1980s)

Dose-response Relationship Risk increases with more intense/more frequent exposure But: • High dose at which any further increase has no effect • Low dose may be that no response occurs or can be measured

Replication of findings Findings found in: • different populations • by using different study designs Jan Hendrik Schön – organic electronics Hwang Woo-suk – stem cell research

Effect of removing the exposure A decrease in the outcome of interest is seen when the exposure is removed.

Extent to which alternate explanations have been considered Has adjustment been made for possible confounding?

”The Norwegian comedian Marve Fleksnes once stated: I am probably allergic to leather because every time I go to bed with my shoes on, I wake up with a headache the next morning.”

Specificity of the association One cause has one effect. abestosis Asbestos exposure mesothelioma lung cancer

Rothman and Greenland One cause – one effect – simplistic and not true Most outcomes are as the result of many contributing causes • Necessary • Sufficient • Probabilistic

Condition of the sidewalk Earlier head trauma leading to equilibrium problems Use of cane to support walking Type of footwear Weather conditions brittle bones Source: Rothman KJ, Greenland: Causation and Causal Inference in Epidemiology, (Am J PH, 2005)

Consistency with other knowledge If an association is supported by the results of different disciplines

Summary • Not a checklist! (don’t stop thinking) • Beware of biologic plausibility • Always aim for better evidence • Association is not causality!!! • Keep an open mind • Remain critical (… especially of your own studies)

Thank you for your attention!

Synthesis: Causal Inference