Pre Test

1. As you know this next topic is an overview of study design. By a show of hands, how many of you consider the selection of study design to be somewhat complex, as if you are choosing from a complex wed of possibilities? As you know this next topic is an overview of study design. By a show of hands, how many of you consider the selection of study design to be somewhat complex, as if you are choosing from a complex wed of possibilities?

2. My hope today is to provide you with a clear path or road map,that if followed will allow you to successfully reach that finish line of your research project. By doing this I also hope to keep you out the woods and avoid the obstacles along the way! My hope today is to provide you with a clear path or road map,that if followed will allow you to successfully reach that finish line of your research project. By doing this I also hope to keep you out the woods and avoid the obstacles along the way!

3. Pre Test! Let�s begin with a pretest �let�s take 2 minutes to answer the following pretest matching quiz. I don�t necessarily expect you to know each answer, but I�m hoping this exercise will help prime your memory for the material to be presented. Let�s begin with a pretest �let�s take 2 minutes to answer the following pretest matching quiz. I don�t necessarily expect you to know each answer, but I�m hoping this exercise will help prime your memory for the material to be presented.

4. Study Design 101 Matthew Fargo MD MAJ, MC, USA Faculty Development Fellow Today we will be discussing the various study designs . My name is Matt Fargo and I am one of the faculty Development Fellows here at Madigan. Today we will be discussing the various study designs . My name is Matt Fargo and I am one of the faculty Development Fellows here at Madigan.

5. Objectives Defined common study designs Applied your hypothesis to various study designs Our objectives for today: First, I want you to be able to discuss the basic quantitative study designs, to include a discussion of their strengths and weaknesses. And finally, I want you to be able to apply your research hypothesis to one or more study designs. You will get to practice this in a small group exercise at the end of the lecture. Our objectives for today: First, I want you to be able to discuss the basic quantitative study designs, to include a discussion of their strengths and weaknesses. And finally, I want you to be able to apply your research hypothesis to one or more study designs. You will get to practice this in a small group exercise at the end of the lecture.

6. Take Home Point Choose the �correct� study design BEFORE you start But first, my take home points! First, not all study designs are created equal. Ideally, you want to do a case series instead of a case report, a cohort study instead of a case-control study, a prospective study instead of a retrospective study, and a randomized clinical trial over almost anything! Second, make sure you choose the �correct� study design BEFORE you start. You don�t want to get halfway through your study and THEN realize you picked the wrong design. But first, my take home points! First, not all study designs are created equal. Ideally, you want to do a case series instead of a case report, a cohort study instead of a case-control study, a prospective study instead of a retrospective study, and a randomized clinical trial over almost anything! Second, make sure you choose the �correct� study design BEFORE you start. You don�t want to get halfway through your study and THEN realize you picked the wrong design.

7. Road Map Here is an overview of our basic road map for our study designs. It may initially seem somewhat tangled and complex, but fortunately we have a way greatly simplify the process of determining, and defining basic study designs. More specifically, we can apply 3 basic questions which will simplify this process�. Here is an overview of our basic road map for our study designs. It may initially seem somewhat tangled and complex, but fortunately we have a way greatly simplify the process of determining, and defining basic study designs. More specifically, we can apply 3 basic questions which will simplify this process�.

8. Road Map The first question is easy. We must first decide whether our study is descriptive (in other words merely gives us a picture or description of what is happening in a population), vs. an analytic study which tries to quantify or measure the relationship between an intervention/exposure with an outcome).The first question is easy. We must first decide whether our study is descriptive (in other words merely gives us a picture or description of what is happening in a population), vs. an analytic study which tries to quantify or measure the relationship between an intervention/exposure with an outcome).

9. Road Map Now most studies fall into the analytic category, so the second question we ask is that if the study is analytic, was the intervention randomaly allocated. If the answer is yes, then we have defined our RCT, essentially are Gold Standard of experiemental designs. If the answer to this question is no, then we are left with our group of observational studies, where studies investigate and record �exposures� (interventions or risk factors), and observe outcomes (such as disease), and as they occur. In other words, the researcher is NOT manipulating the variables of exposures. Now most studies fall into the analytic category, so the second question we ask is that if the study is analytic, was the intervention randomaly allocated. If the answer is yes, then we have defined our RCT, essentially are Gold Standard of experiemental designs. If the answer to this question is no, then we are left with our group of observational studies, where studies investigate and record �exposures� (interventions or risk factors), and observe outcomes (such as disease), and as they occur. In other words, the researcher is NOT manipulating the variables of exposures.

10. Road Map The third and final question applies to observational studies (record exposures and observe outcomes as they naturally occur � do not manipulate these variables), and allows us to differentiate between these studies by asking when were the outcomes determined? In other words, do I start with an outcome or disease and then look back in time to measure exposure (case-control), do I measure the outcome at the same time that I measure the exposure (cross sectional), or do I start with the exposure, and then follow subjects over time and measure outcomes/disease (cohort). My intention is to NOT have you remember everything I just stated , but to introduce you to a basic scheme. To further assist you I have provided you a handout (originates form the CEBM website � see link) which essentially gives you this same roadmap, the 3 questions we just discussed, and a brief description of these study designs. You can reference this throughout this presentation, and hopefully take home for your files as well. The third and final question applies to observational studies (record exposures and observe outcomes as they naturally occur � do not manipulate these variables), and allows us to differentiate between these studies by asking when were the outcomes determined? In other words, do I start with an outcome or disease and then look back in time to measure exposure (case-control), do I measure the outcome at the same time that I measure the exposure (cross sectional), or do I start with the exposure, and then follow subjects over time and measure outcomes/disease (cohort). My intention is to NOT have you remember everything I just stated , but to introduce you to a basic scheme. To further assist you I have provided you a handout (originates form the CEBM website � see link) which essentially gives you this same roadmap, the 3 questions we just discussed, and a brief description of these study designs. You can reference this throughout this presentation, and hopefully take home for your files as well.

11. Descriptive vs. Analytic Descriptive studies �Implicit� and exploratory Show patterns of disease occurrence Generate hypotheses Analytic studies �Explicit� Investigate relationships Test hypotheses Descriptive studies describe associations between exposures and diseases They are called �implicit� because they can only imply or suggest the existence of causal relationships; they can not prove them. They are very useful for generating or refining research hypotheses Analytic studies presume that you already have a hypothesis in mind. Analytic studies are called �explicit� because they are specifically designed to show causal relationships Analytic studies TEST hypothesis Take MS in the PNW for example. I have read that the prevalence of MS in the PNW is relatively high compared to the rest of the country. One could do a descriptive study which identifies the number of MS cases among individuals living in the PNW. Next someone might want to then do an analyitc study which aims to measure the relationship between autism, and say, cold, wet climates. Descriptive studies describe associations between exposures and diseases They are called �implicit� because they can only imply or suggest the existence of causal relationships; they can not prove them. They are very useful for generating or refining research hypotheses Analytic studies presume that you already have a hypothesis in mind. Analytic studies are called �explicit� because they are specifically designed to show causal relationships Analytic studies TEST hypothesis Take MS in the PNW for example. I have read that the prevalence of MS in the PNW is relatively high compared to the rest of the country. One could do a descriptive study which identifies the number of MS cases among individuals living in the PNW. Next someone might want to then do an analyitc study which aims to measure the relationship between autism, and say, cold, wet climates.

12. Descriptive Studies We�ll start our review of specific study designs by a review of descriptive studies, specifically case studies/series. Of note, your handout also includes survey studies. COL Clark will discuss qualitative study designs at the end of the day.We�ll start our review of specific study designs by a review of descriptive studies, specifically case studies/series. Of note, your handout also includes survey studies. COL Clark will discuss qualitative study designs at the end of the day.

13. Case Reports & Series Basic Number of individuals No comparison group Has anyone here done a case report or case series? These are good starting points for the budding researcher! Case reports & series provide descriptions of particular exposures or outcomes in one or a few individuals. Look at this example of a case series: it provided the very first descriptions of a previously unrecognized exposure and disease. This group of individuals reported observations that lead to the discovery of HIV and AIDS. The downside to case reports and case series are that there is no comparison group so they are prone to confounding and bias, it is not possible to show direct relationships between exposures and outcomes. Has anyone here done a case report or case series? These are good starting points for the budding researcher! Case reports & series provide descriptions of particular exposures or outcomes in one or a few individuals. Look at this example of a case series: it provided the very first descriptions of a previously unrecognized exposure and disease. This group of individuals reported observations that lead to the discovery of HIV and AIDS. The downside to case reports and case series are that there is no comparison group so they are prone to confounding and bias, it is not possible to show direct relationships between exposures and outcomes.

14. Randomized Trials Next we move on to question #2 � for analytic studies, which asks whether the intervention is randomly assigned. If the answer is yes, then we have our RCT�s which are experimental comparison study in which participants are allocated to treatment/intervention or control/placebo groups using a random mechanism. Next we move on to question #2 � for analytic studies, which asks whether the intervention is randomly assigned. If the answer is yes, then we have our RCT�s which are experimental comparison study in which participants are allocated to treatment/intervention or control/placebo groups using a random mechanism.

15. Randomized Trials So who here has done an RCT? Clinical trials are like a cohort, but the exposures are assigned instead of measured. The risks of bias and confounding are reduced through the use of control measures like blinding and randomization. The findings of a clinical trial are generally considered to be superior to other study designs. The clinical trial is considered the gold standard of research design. An example is the recent change in the prescribing of hormone replacement therapy to prevent coronary artery disease in women. The bulk of descriptive and observational evidence favored the use of HRT, but that practice was changed by the findings of the Women�s Health Initiative, an RCT. You start with the study population You then assign them to a treatment or control group. The subjects, their health care providers, and/or the researchers themselves can be blinded or non-blinded to these assignments. The control group might receive a placebo, an accepted standard treatment, or no treatment at all outcomes are assessed just like a cohort study, and similar calculations can be made.So who here has done an RCT? Clinical trials are like a cohort, but the exposures are assigned instead of measured. The risks of bias and confounding are reduced through the use of control measures like blinding and randomization. The findings of a clinical trial are generally considered to be superior to other study designs. The clinical trial is considered the gold standard of research design. An example is the recent change in the prescribing of hormone replacement therapy to prevent coronary artery disease in women. The bulk of descriptive and observational evidence favored the use of HRT, but that practice was changed by the findings of the Women�s Health Initiative, an RCT. You start with the study population You then assign them to a treatment or control group. The subjects, their health care providers, and/or the researchers themselves can be blinded or non-blinded to these assignments. The control group might receive a placebo, an accepted standard treatment, or no treatment at all outcomes are assessed just like a cohort study, and similar calculations can be made.

16. Randomized Trials What if we redid our coffee study as a clinical trial� We would assign half to drink coffee, and the other half to not drink coffee. Because we control the assignment, we effectively negate the chance that there is an unmeasured, confounding variable that is influencing the outcomes. We could even give the non-coffee drinkers an identical placebo coffee�called �Decaf�!! In an ideal clinical trial, you would perform your stats on each individual based upon which group they started in. This is called intention to treat. So if you spilled your coffee, we would still perform the stats as if you were in the coffee drinking group and not switch you over to the non-coffee drinking group.What if we redid our coffee study as a clinical trial� We would assign half to drink coffee, and the other half to not drink coffee. Because we control the assignment, we effectively negate the chance that there is an unmeasured, confounding variable that is influencing the outcomes. We could even give the non-coffee drinkers an identical placebo coffee�called �Decaf�!! In an ideal clinical trial, you would perform your stats on each individual based upon which group they started in. This is called intention to treat. So if you spilled your coffee, we would still perform the stats as if you were in the coffee drinking group and not switch you over to the non-coffee drinking group.

17. Randomized Trials Strengths Weaknesses As the gold standard for clinical trials, what do you think are some of the strengths and weaknesses of an RCT? As the gold standard for clinical trials, what do you think are some of the strengths and weaknesses of an RCT?

18. Randomized Trials Strengths Better controls for bias & confounding Assign variables Show causality Strongest evidence Weaknesses Expensive Ethical issues Compliance & crossover Generalizability So if Randomized Clinical Trials are so great� then why don�t we always do a Randomized Clinical Trial? �after all, they provide the best controls for bias and confounding, via the process of randomization and blinding, they ��and yield the strongest evidence for causality� Why?? Because�: They are often more expensive and time consuming than cohort studies, There are ethical considerations that must be considered. We can�t do an RCT on lung cancer by forcing half the patients to smoke�you have to do a cohort! There is also the possibility of subjects who are not compliant with their assigned intervention and who may �cross-over� to the other study arm or drop-out RCT results are not always generalizable to other populations. Too many inclusion/exclusion criteria makes the study population so unique you can�t conclude anything except about THAT study population.So if Randomized Clinical Trials are so great� then why don�t we always do a Randomized Clinical Trial? �after all, they provide the best controls for bias and confounding, via the process of randomization and blinding, they ��and yield the strongest evidence for causality� Why?? Because�: They are often more expensive and time consuming than cohort studies, There are ethical considerations that must be considered. We can�t do an RCT on lung cancer by forcing half the patients to smoke�you have to do a cohort! There is also the possibility of subjects who are not compliant with their assigned intervention and who may �cross-over� to the other study arm or drop-out RCT results are not always generalizable to other populations. Too many inclusion/exclusion criteria makes the study population so unique you can�t conclude anything except about THAT study population.

19. Observational Studies Now we will move on to observational studies, where the relationships between exposures and diseases are simply observed and then measured. As mentioned before, the type of observational study is determined by question #3 which asks when the outcome is determined�. Now we will move on to observational studies, where the relationships between exposures and diseases are simply observed and then measured. As mentioned before, the type of observational study is determined by question #3 which asks when the outcome is determined�.

20. Cross-sectional Studies Large number of individuals Prevalence No temporality As in the case of cross-sectional studies exposure and disease is measured simultaneously. Some refer to these as �prevalence studies� because they are designed to provide a �snapshot� of exposure and disease prevalence simultaneously. As in the case of cross-sectional studies exposure and disease is measured simultaneously. Some refer to these as �prevalence studies� because they are designed to provide a �snapshot� of exposure and disease prevalence simultaneously.

21. Incidence vs. Prevalence Incidence Number of new cases over time Prevalence Total cases at a point in time Includes new and old cases Before giving an example of a cross sectional study it is important to first discuss the difference between incidence and prevalence. For extra credit, who can tell me the difference b/t incidence and prevalence? Incidence is the measurement of NEW cases of a disease that develop over a specified period of time. Prevalence is the measurement of ALL cases of a disease, both old and new, that exist at a specific point in time.Before giving an example of a cross sectional study it is important to first discuss the difference between incidence and prevalence. For extra credit, who can tell me the difference b/t incidence and prevalence? Incidence is the measurement of NEW cases of a disease that develop over a specified period of time. Prevalence is the measurement of ALL cases of a disease, both old and new, that exist at a specific point in time.

22. The Prevalence Pot As an example, If you start with a certain number of marbles, Incidence describes the addition of new marbles� But don�t forget that some marbles are also being lost� So prevalence is the result of both the addition of new cases and the loss of old cases, either by cure or death.As an example, If you start with a certain number of marbles, Incidence describes the addition of new marbles� But don�t forget that some marbles are also being lost� So prevalence is the result of both the addition of new cases and the loss of old cases, either by cure or death.

23. Cross-sectional Study OK, back to the cross-sectional study, So here is how a cross-sectional study would occur: You identify your study population Then you measure exposures AND disease at the same time.OK, back to the cross-sectional study, So here is how a cross-sectional study would occur: You identify your study population Then you measure exposures AND disease at the same time.

24. Cross-sectional Study So let�s return to our fictitious coffee study. We again assume that 75 people drank coffee and 50 fell asleep, But this time my colleagues record exactly who drank coffee, who fell asleep, did both, or did neither. we can now calculate prevalence rates. We could do this for real right now! It�s that easy!So let�s return to our fictitious coffee study. We again assume that 75 people drank coffee and 50 fell asleep, But this time my colleagues record exactly who drank coffee, who fell asleep, did both, or did neither. we can now calculate prevalence rates. We could do this for real right now! It�s that easy!

25. Disease Prevalence Individuals in a group with the disease All individuals in the group Psleep-coffee drinkers = = 33% Psleep-coffee nondrinkers = = 100% Here again is the definition of prevalence. So we calculate the prevalence of sleeping in those who drank coffee, and the prevalence in those who did not. Based on our findings we can say that: Those who drank coffee were less likely to have fallen asleep. 1/3 of those who drank coffee fell asleep anyway. If a person did not drink coffee, they were not able to stay awake.Here again is the definition of prevalence. So we calculate the prevalence of sleeping in those who drank coffee, and the prevalence in those who did not. Based on our findings we can say that: Those who drank coffee were less likely to have fallen asleep. 1/3 of those who drank coffee fell asleep anyway. If a person did not drink coffee, they were not able to stay awake.

26. Exposure Prevalence Individuals in a group with the exposure All individuals in the group Pcoffee-sleepers = = 50% Pcoffee-nonsleepers = = 100% We can also look at exposure prevalence We can see that: Those who fell asleep were less likely to have drunk coffee. Everyone that stayed awake drank coffee. Since this is a �snapshot,� we can not tell for certain whether drinking coffee prevented sleep or sleeping prevented the drinking of coffee�the chicken and the egg issue, but we can hypothesize that there is a relationship between the two.We can also look at exposure prevalence We can see that: Those who fell asleep were less likely to have drunk coffee. Everyone that stayed awake drank coffee. Since this is a �snapshot,� we can not tell for certain whether drinking coffee prevented sleep or sleeping prevented the drinking of coffee�the chicken and the egg issue, but we can hypothesize that there is a relationship between the two.

27. Cross-sectional Studies Strengths Weaknesses What do you think are some of the strengths and weaknesses of these studies?What do you think are some of the strengths and weaknesses of these studies?

28. Cross-sectional Studies Strengths Several outcomes Quick Lead to cohort Yields prevalence Weaknesses No time reference No incidence Not useful for rare occurrences Summing up cross-sectional studies we see that they assess multiple outcomes and exposures at the same time They do not take a lot of time On the other hand, They provide no time reference, so they can not show cause-and-effect relationships And they measure disease prevalence, but not incidence. Remember our take home point, we prefer to measure incidence. We will talk more about why in a moment�Summing up cross-sectional studies we see that they assess multiple outcomes and exposures at the same time They do not take a lot of time On the other hand, They provide no time reference, so they can not show cause-and-effect relationships And they measure disease prevalence, but not incidence. Remember our take home point, we prefer to measure incidence. We will talk more about why in a moment�

29. Case-control Studies Next we have the case-control study. Has anybody here conducted a case control study? Here you observe or identify a number of subjects who have the disease or outcome of interest in advance, ..and a group of control subjects without the disease but who are otherwise as similar to the cases as possible. Then you look back into the past to see what exposures each had. You want to know if there is any difference in the exposure history of the cases compared to the controls that might explain why they developed the disease. You are attacking the problem backwards by proceeding from effect to cause These are always retrospective studies!!Next we have the case-control study. Has anybody here conducted a case control study? Here you observe or identify a number of subjects who have the disease or outcome of interest in advance, ..and a group of control subjects without the disease but who are otherwise as similar to the cases as possible. Then you look back into the past to see what exposures each had. You want to know if there is any difference in the exposure history of the cases compared to the controls that might explain why they developed the disease. You are attacking the problem backwards by proceeding from effect to cause These are always retrospective studies!!

30. Case-control Studies Let�s redesign the coffee study and say that I identify just 5 people who fell asleep during my talk. I also pick 20 controls that did not fall asleep. Then I survey them to see who drank coffee. In this case I can measure the relationship between exposure and outcomes by measuring what is called an odds ratio, in other words, I can compare the odds of having drank coffee (exposure) in the cases vs. the controls.Let�s redesign the coffee study and say that I identify just 5 people who fell asleep during my talk. I also pick 20 controls that did not fall asleep. Then I survey them to see who drank coffee. In this case I can measure the relationship between exposure and outcomes by measuring what is called an odds ratio, in other words, I can compare the odds of having drank coffee (exposure) in the cases vs. the controls.

31. Odds Ratio Odds of exposure in cases a/c Odds of exposure in controls b/d Here is the definition of the odds ratio.Here is the definition of the odds ratio.

32. Odds Ratio OR = a/c = 1/4 = 1 x 5 = 1 b/d 15/5 4 15 12 Plugging the numbers in from our fictitious coffee study, mathematically, this reduces to an odds ratio of 1 out of 12. The odds of drinking coffee were 12 times higher in those who stayed awake than in those who fell asleep. So what? The odds ratio is useful when analyzing data from case-control or cross-sectional studies that yield prevalence so you are not able to calculate incidence. Plugging the numbers in from our fictitious coffee study, mathematically, this reduces to an odds ratio of 1 out of 12. The odds of drinking coffee were 12 times higher in those who stayed awake than in those who fell asleep. So what? The odds ratio is useful when analyzing data from case-control or cross-sectional studies that yield prevalence so you are not able to calculate incidence.

33. Case-control Studies Strengths Weaknesses What do you think are some of the strengths and weaknesses of a case control study?What do you think are some of the strengths and weaknesses of a case control study?

34. Case-control Studies Strengths Rare outcomes Many exposures Simple & fast Inexpensive Weaknesses Single outcome High risk for bias and confounding Odds ratio Case-control studies are very good for studying rare conditions. Because they are retrospective, they are relatively quick and inexpensive. However, they only study one outcome and there is a relatively high risk for bias and confounding: Did you pick good cases & controls? �There may be selection bias. How accurately and honestly do the subjects recall and report their exposures?... recall or reporting bias. Are we sure that any observed association is not really the result of a 3rd factor? � confounding. Case-control studies may be the only way you can study rare diseases because you would have to recruit an incredibly large number of disease-free subjects to be followed over an extraordinary long period of time in order to use a longitudinal design. Which brings us to our next type of study design� Case-control studies are very good for studying rare conditions. Because they are retrospective, they are relatively quick and inexpensive. However, they only study one outcome and there is a relatively high risk for bias and confounding: Did you pick good cases & controls? �There may be selection bias. How accurately and honestly do the subjects recall and report their exposures?... recall or reporting bias. Are we sure that any observed association is not really the result of a 3rd factor? � confounding. Case-control studies may be the only way you can study rare diseases because you would have to recruit an incredibly large number of disease-free subjects to be followed over an extraordinary long period of time in order to use a longitudinal design. Which brings us to our next type of study design�

35. Cohort Studies �the Cohort. Anybody here conducted a cohort study? In contrast to the case-control design, here you: Start with a population of disease-free subjects Measure their exposure status (both groups must have the potential to develop the disease/outcome of interest), and should be same in every respect other than the exposure And follow them through time to see who develops disease and who does not. Most cohort studies are prospective. You want to know if there is any difference in the rate of development of new disease in those who have an exposure and those who do not.�the Cohort. Anybody here conducted a cohort study? In contrast to the case-control design, here you: Start with a population of disease-free subjects Measure their exposure status (both groups must have the potential to develop the disease/outcome of interest), and should be same in every respect other than the exposure And follow them through time to see who develops disease and who does not. Most cohort studies are prospective. You want to know if there is any difference in the rate of development of new disease in those who have an exposure and those who do not.

36. Cohort Studies Here is an example of a cohort study using our coffee data. Remember that this is not a snapshot, but rather an observation occurring over a period of time: We start with a 100 people who are all alike except that some are drinking coffee and some are not. We then follow them through this talk and see who falls asleep. Because there is a temporal relationship, we can calculate and compare the risk of sleeping in coffee drinkers to the risk in non-coffee drinkers. We call this the relative risk.Here is an example of a cohort study using our coffee data. Remember that this is not a snapshot, but rather an observation occurring over a period of time: We start with a 100 people who are all alike except that some are drinking coffee and some are not. We then follow them through this talk and see who falls asleep. Because there is a temporal relationship, we can calculate and compare the risk of sleeping in coffee drinkers to the risk in non-coffee drinkers. We call this the relative risk.

37. Relative Risk Incidence of disease in exposed Incidence of disease in unexposed RR = = 1 / 3 Here is the definition of relative risk. The risk of falling asleep was 25 out of 75 in the coffee drinkers, �and the risk was 25 out of 25 in the non-coffee drinkers. This reduces to a relative risk of 33%, meaning that the risk of falling asleep in coffee drinkers was 33% Coffee drinking is protective against sleeping.Here is the definition of relative risk. The risk of falling asleep was 25 out of 75 in the coffee drinkers, �and the risk was 25 out of 25 in the non-coffee drinkers. This reduces to a relative risk of 33%, meaning that the risk of falling asleep in coffee drinkers was 33% Coffee drinking is protective against sleeping.

38. Cohort Studies Strengths Weaknesses What do you think are some strengths and weaknesses of cohort designs? What do you think are some strengths and weaknesses of cohort designs?

39. Cohort Studies Strengths Rare exposures Multiple outcomes Temporality Incidence & relative risk Weaknesses Expensive Time consuming Losses to follow-up Risk of bias and confounding That brings us to the major strength of the cohort design: you can measure incidence rates and compare them to calculate relative risk! The longitudinal design has other benefits as well: You can assess for multiple disease outcomes; consider the Framingham study where a large cohort has been followed for over 50 yrs now and studies on everything from heart disease to cancer to osteoporosis have been published. Multiple diseases, but one population. Cohort studies lend themselves perfectly to inferring cause-and-effect relationships. However, because you must reevaluate every study subject multiple times for the entire study, cohorts can be very expensive and time consuming. If you are not able to keep track of all of the subjects, those losses to follow-up (drop-out, die, move) can limit your ability to draw meaningful conclusions. And there are still risks for bias and confounding All the above problems amplified if retrospectiveThat brings us to the major strength of the cohort design: you can measure incidence rates and compare them to calculate relative risk! The longitudinal design has other benefits as well: You can assess for multiple disease outcomes; consider the Framingham study where a large cohort has been followed for over 50 yrs now and studies on everything from heart disease to cancer to osteoporosis have been published. Multiple diseases, but one population. Cohort studies lend themselves perfectly to inferring cause-and-effect relationships. However, because you must reevaluate every study subject multiple times for the entire study, cohorts can be very expensive and time consuming. If you are not able to keep track of all of the subjects, those losses to follow-up (drop-out, die, move) can limit your ability to draw meaningful conclusions. And there are still risks for bias and confounding All the above problems amplified if retrospective

40. Small Group Exercise What is your study design? Be prepared to share with the group. Now for a final exercise! I know some of you came here today c research questions in mind. For the next 10 minutes, I want you to remain at your tables, and discuss applying your research hypothesis to the study design utilizing the 3 questions we reviewed. A research fellow will come to each table to help you. If you run out of time, feel free to continue this discussion over the break that follows or anytime today or tomorrow. Feel free to reference the handout of the different study designs provided. Now for a final exercise! I know some of you came here today c research questions in mind. For the next 10 minutes, I want you to remain at your tables, and discuss applying your research hypothesis to the study design utilizing the 3 questions we reviewed. A research fellow will come to each table to help you. If you run out of time, feel free to continue this discussion over the break that follows or anytime today or tomorrow. Feel free to reference the handout of the different study designs provided.

41. So this concludes my presentation. Good luck with your own study designs! So this concludes my presentation. Good luck with your own study designs!

42.  Questions? Thank you! Thank-you!! What are your questions?? Thanks!!Thank-you!! What are your questions?? Thanks!!