CASE CONTROL STUDY

A breif introduction to analytical study designs and case control study in detail. Will be useful for lectures.

1. ANALYTICAL STUDY DESIGNS CASE CONTROL STUDY

2. LEARNING OBJECTIVES To develop an understanding of………. What case-control studies are?? The value of such studies The basic methodology Pros and Cons of such studies

3. Lesson plan: Target group: Third year BDS students LO Content Method Time Media 1 Study designs introduction Explanation 5 min Slide 5– 6 2 Analytical study design Explanation 5 min Slide 7 - 10 3 Case control study design Explanation 10 min Slide 11 - 18 4 Matching Explanation 5 min Slide 19 -21 5 Odds ratio Explanation 10 min Slide 22 - 24 6 Bias in case control Explanation 10 min Slide 25 - 27 7 Pro and cons of case control Explanation 5 min Slide 27 - 28

4. CONTENTS STUDY DESIGNS – RECAP ANALYTICAL STUDY DESIGNS INTRODUCTION TO CASE CONTROL STUDY DESIGN OF A CASE CONTROL STUDY ELEMENTS OF A CASE CONTROL STUDY MATCHING ODDS RATIO – CALCULATION AND INTERPRETATION PROS AND CONS OF CASE CONTROL STUDY SUMMARY

5. STUDY DESIGNS - RECAP

6. Epidemiological Study Cycle DESCRIPTIVE STUDY Ca Lung increasing  mostly smokers Death rates higher in populations with higher per capita cigarette consumption Ochsner , 1939 CASE CONTROL STUDY Ca Lung patients and non patients Clarifies if it was smokers who contributed to high Ca Lung Doll, 1947-52 COHORT STUDY Follows a cohort of smokers and non smokers without Ca Lung Smokers develop Ca Lung more frequently INTERVENTIONAL TRIAL (RCT) Proves hypothesis conclusively Gives inputs regarding other factors, control measures. Hypothesis: Smoking causes Ca Lung Hill, 1951-61

7. Analytical studies History of medicine has always been fascinated in discovering the causes of the disease and the ways in which these could be modified. CAUSES OF DISEASE EVENT, CONDITION, CHARACTERISTIC OR COMBINATION OF FACTORS DISEASE EXPOSURE SEVERAL OBSERVATIONS HAVE TO BE MADE ANALYTICAL EPIDEMIOLOGY

8. Analytical studies Investigator does not assign the exposure Makes careful measurement of patterns of exposure and disease in populations Comparison group Make inferences about exposure and disease

9. RESEARCH DESIGNS IN ANALYTICAL STUDIES COHORT STUDY CROSS SECTIONAL STUDY CASE CONTROL STUDY

10. CASE CONTROL COHORT STUDIES RETROSPECTIVE Ca Lung patients and non patients Clarifies if it was smokers who contributed to high Ca Lung PROSPECTIVE Follows a cohort of smokers and non smokers without Ca Lung Smokers develop Ca Lung more frequently

11. Case-Control Studies The observational epidemiologic study of persons with the disease (or other outcome variable) of interest and a suitable control (comparison/ reference) group of persons without the disease . ( Dictionary of Epidemiology: 3 rd ed ; John M Last. 2000)

12. Case-Control Studies A case control study involves two populations – cases and controls and has three distinct features : Both exposure and outcome have occurred before the start of the study. The study proceeds backwards from effect to cause. It uses a control or comparison group to support or refute an inference. ( Park’s Textbook of Preventive and Social Medicine – 20 th ed ; K. Park. 2009)

13. Design of case‐control study Objective: Test association between cigarette smoking and lung cancer (Doll and Hill, 1952) EXPOSED NON EXPOSED EXPOSED NON EXPOSED CASES (with lung cancer) CONTROL Non – cancer patients Exposure odds Exposure odds O D D S RA T I O EXPOSED SMOKER NON EXPOSED NON SMOKER OUTCOME TIME EXPOSURE

14. ELEMENTS OF A CASE CONTROL STUDY SELECTION OF CASES SELECTION OF CONTROLS INFORMATION ON EXPOSURE ANALYSIS

15. Selection of cases • All people in source population who develop the disease of interest Sample of cases Independent of the exposure under study • Clear definition of outcome studied • Prevalent vs. incident cases Prevalent cases may be related more to survival with disease than to development of disease.

16. Sources of cases • Hospital/clinic based cases Easier to find May represent severe cases • Population based (cancer registry) - not biased by factors drawing a patient to a particular hospital

17. Selection of controls • Represent the distribution of exposure in the source population of cases - Selected from the same source population that gives rise to the cases • Selected independently of their exposure status

18. SELECTION OF CONTROLS Population based • Sampling of the general population Health care facility based • Patients with other diseases Case‐based Friends , Neighbourhood

19. MATCHING Defined as “ the process by which we select controls in such a way that they are similar to cases with regard to certain pertinent selected variable which are known to influence the outcome of disease and which if not adequately for comparability could distort or confound the result ”

20. TYPES OF MATCHING Type 1 Group Matching : assigning cases to subcategories based on their characteristics like age occupation, etc. and then establishing appropriate controls. Type 2 Pair matching : It is finding a control for particular case as closely resembling as possible except for disease under study.

21. S electing good data on exposure 1.Objectively • Reproducibility of exposure measurement 2. Accurately • Information reflecting as closely as possible the effect of exposure 3 . Precisely • Quality management in exposure measurement

22. Presentation of the data of a case‐control study in a 2 x 2 table

23. ODDS RATIO

24. INTERPRETING ODDS RATIO OR = 1 - Odds of exposure among cases and controls are same - Exposure is not associated with disease OR > 1 - Odds of exposure among cases are higher than controls - Exposure is positively associated with disease OR < 1 - Odds of exposure among cases are lower than controls - Exposure is negatively associated with disease

25. Bias in case control studies BIAS – is a systematic error in design, conduct or analysis of a study which leads us to an erroneous conclusion. 1.Bias in selection of cases - selection bias or diagnostic bias 2.Bias in investigating controls. - recall bias, the controls are less likely to recall exposure variables than the cases. -The interview/tests/investigation etc may lack depth in controls whereas the cases are thoroughly worked up

26. 3. CONFOUNDING BIAS (distortion of study effect with another effect because of variables EXTRANEOUS to the exposure affecting the prediction of the disease) When the disease has multiple risk factors which are related to each other SOLUTION – MATCHING BETWEEN CASES AND CONTROLS

27. 4. Problems due to over matching : - This is where a potential confounder ( religion in substance abuse) is matched among cases and controls. The study thus loses the power of proving an obvious association. 5.Bias in analysis - the presence of a confounder is mostly identified at the time of analysis. - It is due to non- uniform distribution of confounders. Solution – Stratification ( limit the size of study and no of confounding factors)

28. STRENGHTS Good for examining rare outcomes or outcomes with long latency Relatively quick to conduct, inexpensive Requires comparatively few subjects Multiple exposures or risk factors can be examined .

29. WEAKNESSES Susceptible to recall bias Selection of an appropriate comparison group may be difficult Rates of disease in exposed and unexposed individuals cannot be determined

30. SUMMARY STUDY DESIGNS DESIGN ELEMENTS MATCHING ODDS RATIO BIAS STRENGTHS & WEAKNESSES OBSERVATIONAL EXPERIMENTAL ANALYTICAL DESCRIPTIVE CASE CONTROL COHORT CROSS SECTIONAL

31. REFERENCES 1) Soben Peter. Essentials of Public Health Dentistry. 5th ed. New Delhi: Arya Publising House; 2013. 2)Park, Park’s Textbook of Preventive &Social Medicine, 22nd Edition, Jabalpur: Banarsidas Bhanot,2013.

32. THANK YOU!