The Anatomy Of Research

1. The Anatomy Of Research Pathways to Careers in Clinical and Translational Research (PACCTR) Curriculum Core

2. Case Study • Your 78 year old grandmother is still going strong. Tai Chi, power walking, Mahjong club, and weekly trips to the local casino with “the girls” – it’s tough to keep up with her schedule! She is taking lasix for hypertension, lipitor for high cholesterol, and fosamax for osteoporosis. Grandma now wants to replace her lower partial denture with implant teeth, and has asked you, her favorite grandchild for advice. • You have read some case studies where bisphosphonate (BisP) use appeared to be associated with osteonecrosis of the jaw (ONJ), but a definitive recommendation hasn’t yet been reached.

3. Research Question • What is the objective of your study? • Usually, you begin with a general uncertainty about a health issue, which you then focus into a concrete, researchable question.

4. Example: Research Question • Does bisphosphonate use lead to osteonecrosis of the jaw?

5. Significance • How does your research question contribute to the scientific knowledge base, influence clinical decision-making, or have some bearing on public health policy? • The significance section provides a rationale for your study, includes relevant previous research, and indicates how your study will take the knowledge base one-step further.

6. Example: Significance • BisP-associated ONJ first reported 2003 • BisP currently prescribed to ~20 million people • Although the risk for BisP-associated ONJ is low, the morbidity of BisP-associated ONJ is high • Consequences of long-term BisP use are not known

7. Hypothesis • How can now you re-phrase your study question so that it provides the basis for testing the statistical significance of your research findings?

8. Example: Hypothesis • Bisphosphonate use increases the risk for developing osteonecrosis of the jaw.

9. Study Design: Observational Studies • Cross-Sectional Study: Does your study measure the characteristics of a population at one point in time? • Case-Control Study: Does your study measure the characteristics of a population with a disease/condition and compare these characteristics with a similar population who doesn’t have the disease/condition? • Cohort Study: Does your study measure the characteristics of a population at baseline, and continue to monitor the population over time to determine who subsequently gets the disease/condition?

10. Study Design: Experimental Study • Clinical Trial: Does your study test the effects of an intervention on a disease/condition? • Are the study participants randomized to receive either the intervention or a placebo?

11. Example: Case-Control Study • Because ONJ is a rare disease, assembling a group of people with ONJ (cases) and comparing them with a similar group of people without ONJ (controls) would be the most efficacious study design.

12. Subjects • Selection Criteria: How are you defining your study population? • Inclusion criteria: What characteristics must your subjects possess in order to be considered for your study? • Exclusion criteria: What characteristics will preclude subjects from being considered for your study? • Sampling: How are you selecting your study subjects? • What subgroup of your overall study population will be chosen to be your study subjects? • Will they be randomly selected from a large population or will they be a convenience sample from the attendees of a particular clinic or hospital?

13. Example: Subjects • Selection Criteria • Cases: people diagnosed to have ONJ • Controls: people who do not have ONJ • Sampling • Cases: all people diagnosed with ONJ at the UCSF Division of Oral Medicine since 2003 • Controls: random sample of people in Northern California who have a similar range of age, gender and county of residence as do the cases

14. Sample Size • How many study subjects will you need in order to observe the expected outcome with adequate precision?

15. Example: Sample Size • A matched case-control study requires the following information: • Power: probability of detecting a real effect • Alpha: probability of detecting a false effect • r: correlation coefficient for exposure between cases and controls • PO: probability of exposure in the control group • m: number of control subjects for each case • OR: odds ratio

16. Variables • Which characteristics of the study subjects are you going to measure? • Descriptive variables: describe the distribution of disease and health-related characteristics • Analytical variables: analyze the relationships between two or more variables • Predictor variables are those which are biologically presumed to precede the outcome variables • Confounding variables: other predictors that can confuse the interpretation of the outcome

17. Example: Variables • Descriptive: age, gender, county of residence • Analytical: BisP brand, dose, duration; oral flora composition; dental procedure that resulted in ONJ • Confounding: co-morbidities, other medications, smoking

18. Physiology of Research

19. Inferences • Internal Validity: How well do your conclusions correctly describe what actually happened in your study? • External Validity: How well do your conclusions generalize to the population outside of your study sample? • Causality: How well does your predictor variable(s) explain a cause and effect relationship with the outcome?

20. Example: Causality • Strength of the association: the stronger the association observed between BisP and ONJ, the less likely it is due to error. • Dose-response effect: does the frequency of ONJ increase with the dose/duration of BisP? • Lack of temporal ambiguity: does exposure to BisP precede the occurrence of ONJ? • Consistency of findings: are your findings similar to those of other studies? • Biological plausibility of the hypothesis: does the model for BisP effects on ONJ make sense in the context of current biological knowledge? • Specificity of the association: is BisP associated with other diseases? Is ONJ associated with other predictors?

21. Research Error • Random: the findings from your study are incorrect due to chance variation • Increasing the sample size increases the precision of your findings and decreases the likelihood of a random error. • Systematic: the findings from your study are incorrect due to biased variation • Reducing the error with which subjects are sampled and measurements are made increases the accuracy of your findings.

22. Example: Random Error • There have been only 8 cases of ONJ presenting at UCSF since 2003, and your case-control study has failed to detect any increased risk associated with BisP use. • Since 8 cases and 8 controls is a very small sample size, you could increase the precision of your findings by increasing the sample size to include all cases of ONJ presenting at all Oral Medicine clinics in California since 2003 (with a corresponding increase in the number of controls)

23. Designing the Study • Outline: 1-2 page checklist of the components and sequence of your study • Protocol: 5-100+ pages of details used for planning your study and grant application • Operations Manual: instructions and procedures that assure quality control and a standardized approach to implementing your study

24. Example: Study Protocol • Research question • Significance • Design • Subjects • Sample size • Variables • Analysis plan

25. References • Designing Clinical Research, 3rd ed. SB Hulley et al. Lippincott Williams & Wilkins 2007. • Fundamentals of Clinical Trials, 3rd ed. LM Friedman et al. Springer 1998. • Epidemiologic Research. DG Kleinbaum et al. Van Nostrand Reinhold 1982.

26. PACCTR* Curriculum Core • Susan Hyde DDS, MPH, PhD, School of Dentistry • Jennifer Cocohoba, PharmD, School of Pharmacy • Roberta Oka RN, ANP, DNSc, School of Nursing • George Sawaya MD, School of Medicine • Rebecca Jackson MD, School of Medicine • Joel Palefsky MD School of Medicine * Pathways to Careers in Clinical and Translational Research