1. Explaining Health Risk [NAACCR\2009\AnnualMeeting\TenRules\TenRules.PPT ]

2. Guidelines  How do we remain alert & prudent Versus Versus  Jumping to Conclusions

3. Health Risk Reports are Important  Public Preoccupation with Health Risk – Media Reports  Frequent  Alarming  Scientists are also Interested

4. Do migraines reduce risk of breast cancer? Cancer researchers in Seattle found “women who had a history of migraines had a 30 percent lower risk of breast cancer compared to women who did not have a history of such headaches” Li, et al. Fred Hutchinson Cancer Research Center. Li, et al. Fred Hutchinson Cancer Research Center. Cancer Epidemiology, Biomarkers and Prevention. San Diego Union-Tribune, Nov 6, 2008.

5. New Study Links Parkinson’s and Pesticides “Increasing levels of exposure to pesticides were associated with an increasing risk of Parkinson’s” Dana Hancock, PhD. Duke University. BMC Neurology.

6. Examples of Reported Health Risks  Second hand tobacco smoke  Radon within residences  Cell phones-brain tumors  DDT – breast cancer  Dump sites  Electromagnetic fields-childhood leukemia  Coffee drinking – pancreatic cancer

7. Other Examples  Silicone implants – connective tissue cancer  Agent Orange Gulf War Syndrome  Charred Meat  Neighborhood Clusters, Hot Spots  Saccharin/sweeteners  Oxidants  Salt

8. Different Consumers of Health Risk Data  Scientists (Epidemiologists & Environmental Toxicologists) – Looking for possibles/clues – Multivariate analysis  Public –Common sense –Not statistical –Large, or interesting, risk

9.  Balancing learning about: – every possible risk versus – Only being concerned with evidence proven risk.  Statisticians might call this balancing sensitivity versus specificity.

10.  Possible (commonsense) Guidelines for Explaining Health Risk

11. Guidelines 1.Agenda/Funding/Purpose of Presenter (Bias) 2.Knowledge/Preconception of Listener/Reader (Bias) 3.Characteristics/Biology of the Diagnosis 4.Biologic Mechanism 5.Risk Factor Mileau 6.Absolute vs Relative Risk 7.Other Supporting Evidence 8.Association versus Causation 9.Dosage 10.Control Bias/Confounding (external influence) 11.Nature/Reliability of Data and the Analysis 12.Opposing Findings/Hypotheses

12. What Have I Omitted?

13. Thank You Herman R. Menck, BS, MBA, CPhil, FACE Los Angeles Cancer Surveillance Program menckh@aol.com

14. Guidelines 1.Agenda/Funding/Purpose of Presenter (Bias) 2.Knowledge Preconception of Listener/Reader (Bias) 3.Characteristics/Biology of the Diagnosis 4.Biologic Mechanism 5.Risk Factor Mileau 6.Absolute vs Relative Risk

15. Guidelines 7.Other Supporting Evidence 8.Association versus Causation 9. Dosage 10. Control Bias/Confounding (external influence) 11. Nature/Reliability of Data and the Analysis 12. Opposing Findings/Hypotheses

16. 1. Agenda/Funding/Purpose of Presenter (Bias)  How Do they Get Their Funding? –Tobacco Institute –American Cancer Society –Trucking Association  Previous Work

17. 2. Knowledge/Preconception of Listener (Bias) Cultural - Ethnic – Geographic Media – Gender – Linguistic Political – Corporate – Advertising Sociologic – Personal Gain – Religious Sensationalist – Anti-Scientific

18. 3. Define Diagnosis  Is the Diagnosis Understood and Well Defined? –Organ/System Function –Biology of organ –Which Cancer/Disease – (Agent Orange?)  Are There Related/Confounding Diseases?

19. 4. Biologic Mechanism  How do headaches influence risk to breast cancer?  How does it biologically work?

20. 5. Risk Factor Mileau  What are the Major and Minor Risk Factors for this diagnosis?

21. Lung Cancer Risk Factors  Cigarettes  Secondary smoke  Chewing tobacco  Radon  Other

22. Breast Cancer Risk Factors  Hormonal mileau  Medication – HRT  Diet/Green Tea  Exercise  Other

23. 6. Absolute vs Relative Risk  Discuss Both  Establish Magnitude of Absolute Risk  Relative Risk can be misunderstood.

24. 7. Other Supporting Evidence  Natural Experiments/International Correlations  High & Low Risk Populations  International Correlations  Other Human Studies  Animal Studies

25. 8. Is it an Association vs Causation?

26. 9. Dosage Can Be Important Could the dosage in animal studies be unrealistic?

27. 9. Are Data Biases Controlled Healthy Worker Effect Married Men Live Longer Asians Have Higher SAT Scores Breast Cancer Patients Have Headaches

28. 11. Evaluate Nature of the Data and Its Analysis  Recall versus measurements  Recall error  Other Possible Data Bases

29. 12. Review Opposing Evidence/Hypotheses  Animal Studies  Null Findings  Opposing Findings/Hypotheses

30. Question for Scientists Which Role Do You Wish to Play? Which Role Do You Wish to Play? Can you be both an impartial scientist, and a health risk activist? Which role should the scientist play?

31. Guidelines 1.Agenda/Funding/Purpose of Presenter (Bias) 2.Knowledge/Preconception of Listener/Reader (Bias) 3.Characteristics/Biology of the Diagnosis 4.Biologic Mechanism 5.Risk Factor Mileau 6.Absolute vs Relative Risk 7.Other Supporting Evidence 8.Association versus Causation 9.Dosage 10.Control Bias/Confounding (external influence) 11.Nature/Reliability of Data and the Analysis 12.Opposing Findings/Hypotheses