Group 2: Nabilah, Jing Kai, Soon Guan Experimental Design Group 2: Nabilah, Jing Kai, Soon Guan

Outline Experimental Design Prospective Study vs Retrospective Study Flaws in Studies Cause and Effect Case Study: Smoking and Lung Cancer Conclusion Outline Experimental Design

Reading Salsburg, David (2001). The Lady Tasting Tea: How Statistics Revolutionized Science in the Twentieth Century, W.H. Freeman (Chapter 18, Does smoking cause lung cancer?)

Prospective Study Subjects are selected and monitored over a period of time for development of disease Problems: Extrapolation issues Time consuming -The study normally only focuses on a particular population and hence cannot be generalized with other parts of the world

Retrospective Study Subjects with disease are identified Investigations for prior conditions associated with disease Problems: Rare diseases Not enough/Difficult to find subjects for the study

Flaws in Studies Every study has its flaws Non-random samples → Reinforcement of results through consistency over many studies

Correlation Does Not Imply Causation!

A implies B = Not A implies not B Cause and Effect: A implies B = Not A implies not B Defined by the famous scientist, Bertrand Russell in 1930s

Postulates for Causation Whenever the agent can be cultured, the disease is there Whenever the disease is not there, the agent can’t be cultured When the agent is removed, the disease goes away Robert Koch in the 19th century expanded on Russell’s theory

Does Smoking Cause Lung Cancer? Case Study

Overview Prospective & retrospective studies done Widely reported that smoking causes lung cancer Prospective: Doctors were interviewed about their smoking habits and followed for 5 years, doctors who smoked more had higher probability of contracting lung cancer Retrospective: In countries eg, US, Japan, France, 10x as many smokers in the lung cancer patients compared to patients without lung cancer

However...

Flaws in experimental design Publication bias (Fisher, 1958) Postulates not met Flaws in experimental design Publication bias (Fisher, 1958) Confounders Eg. Genetics → When a patient smokes, he develops lung cancer When a patient doesn’t have lung cancer, it means he doesn’t smoke When a patient stops smoking, he is cured of lung cancer But still difficult to establish a conclusion as there are many other factors affecting lung cancer → Opportunistic samples → Publicity bias: Results are carefully selected to publish whatever is acceptable to the scientific community and reject that which is not acceptable. Speculation that non-inhalers actually had higher risk of lung cancer than inhalers but this wasn’t published, researchers did not address his claims. → Confounders eg. Genetics that affect rates of smoking and rates of lung cancer Cannot say for sure that smoking causes lung cancer

Conclusion Correlation does not imply causation Not easy to determine cause and effect Studies are still important as they can still give an idea and provide clues on the possible underlying causes of a disease There could just be statistical correlation. SG: The evidence that smoking causes cancer: arduous fight against the the tobacco companies. - Took a lot of lobbying by scientist and statisticians to refute the claims made by the tobacco companies -

Thank You!