1. Unit 4 Seminar Contd… (we shall pick up where we left off last seminar to discuss some key concepts)

2. Key Concepts Accuracy: Ability of a measurement to be correct on the average (in one study) Precision: Ability of a measurement to give the same results with repeated measurements of the same thing (in several studies) Both of these are necessary in statistics and neither takes a back seat to the other 2

3. Variability Who looks can make all the difference…or none at all Intra observer variability = A difference of observation/interpretation of data when studied by the same person Inter observer variability = A difference of observation/interpretation of data when studied by more than one person 3

4. False is False and True is True Or is it? Type I Error ▫Also known as a false-positive error or alpha error ▫The error is in the fact that a positive reading is registered when the results are actually negative 4

5. Continued… Type II Error ▫Also known as a false-negative error or a beta error ▫The error is in the fact that a negative reading is registered when the results are actually positive 5

6. Sensitivity Vs. Specificity (Diagnostic tests) Sensitivity – Ability of a test to detect the disease when present Specificity – Ability of a test to indicate non- disease status when no disease is present 6

7. Improving Decisions in Clinical Medicine Chapter 8: Tools for the practice of evidence-based medicine Copyright Kaplan University 2009

8. Bayes Theorum A mathematical theory that is used to determine the probability that a symptom or a test (if postive) is indicative of a particular disease. Provides a way to answer the following Q: ▫If the test results are +ve what is the probability that the patient has a certain disease? ▫If the test results are –ve what is the probability that the patient does not have the disease?

9. Example: A fourteen year old girl goes to the county fair, during the course of a three hour visit to the fair, she eats a funnel cake, cotton candy, and a candy apple after consuming a foot-long chili dog.

10. Two hours after arriving home from the fair she is rushed to the local ER for stomach pains, dizziness and vomiting.

11. The Visit Upon arrival at the ER, blood chemistries and a CBC are drawn as well as collection of a free catch urine sample.

12. Patient Data Examination: ▫Temperature 98.7 ▫Pulse 84 ▫Respiration 24 ▫Weight 136 ▫Height 5 ft 6 Laboratory Report ▫Complete Blood Count: within normal limits ▫Chemistries: Within normal limits except for glucose (sugar) which is 198  Normal glucose reading is 100-120

13. Symptoms of Diabetes Increased water consumption Weight gain or loss (unexpected) Glucose readings that are above normal Increased and frequent urination Frequent night-time urination

14. Question.. Based on the history of the patient and what we now know of diabetes, does this patient have diabetes?

15. Bayes Theorum A way of predicting through observation of probability whether or not a symptom is caused by a certain disease.

16. Let us think about this.. If a population has a low prevalence (occurrence) of a disease, it is likely that positive results may be false positives ▫These positive results should be examined further before a diagnosis is positively made. ▫This is an area where good epidemiological examination can make all the difference in avoiding a panic.

17. Evidence Based Medicine A form of medical practice that: ▫Bases a diagnosis on symptoms and prevalence ▫Relies heavily on the use of Bayes Theorum or decision trees ▫Must perform tests to rule out diseases as part of the diagnostic process ▫Uses a sequential approach to tests  Begin with most sensitive test for fastest and most accurate results  Continues with other tests in a sequence until a satisfactory answer is arrived at (i.e. diagnosis)

18. Decision Trees A method of improving decision making in times of uncertainty ▫A systematic way of outlining one’s thoughts and rationale concerning a medical dilemma  Create a decision tree (5 steps)  Identify/set limits to the problem  Diagram options  Obtain information on each option (P values)  Compare the values  Perform sensitivity analysis to arrive at an answer

19. When do they use Decision Trees? Clinical settings Public health problem solving

20. Meta-analysis Definition: ▫Collection of related methods used to combine data from similar studies to obtain the best estimate of the results or conclusion on the outcome of interest. Types: ▫Pooled Quantitative Analysis: deals with actual numbers (i.e. quantity)

21. Meta-analysis - Continued Methodological Qualitative Analysis: deals with quality or benefits derived from something such as a treatment or drug therapy.

22. An example forest plot of five odds ratios (squares, proportional to weights used in meta-analysis), with the summary measure (centre line of diamond) and associated confidence intervals (lateral tips of diamond), and solid vertical line of no effect. Names of (fictional) studies are shown on the left, odds ratios and confidence intervals on the right. Taken from http://en.wikipedia.org/wiki/Forest_plotodds ratiosweights

23. Questions ??

24. Discussion Time

25. Page 130, Figure 8-2 If you took your mother to the ER with the symptom of chest pain at rest, how would you feel about a physician using Figure 8-2 as a basis for his treatment decisions?

26. The End Any questions, concerns or discourse on assignments so far within the course?