EVIDENCE BASED PRACTICE-PROGNOSTICS

1. EVIDENCE BASED PRACTICE-PROGNOSTICS FAJAR AWALIA YULIANTO

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3. Does every patients with ACD become heart failure grade 4? • Does every patients with ARF become RHD? • Will the patients of leukemia survive for 3 months? • Will the patients die or stay healthy for a few years?

4. Cohort studies: best design for answering prognosis questions • Randomized trial: particularly since they usually include detailed documentation of baseline data • Case control studies: particularly useful when the outcome is rare or the required follow up is long • Systematic review: combines all prognosis studies • Inception cohort: the similarity of other prognostic factors at the beginning of the study PROGNOSTIC STUDIES

5. Was a defined, representative sample of patients assembled at a common point in the course of their disease? • Was follow-up of study patients sufficiently long and complete? • Were objective outcome criteria applied in a “blind” fashion? • If sub-groups with different prognosis are identified: • Was there adjustment for important prognostic factor? • Was there validation in an independent group of ‘test-set” patients? VALID COMPONENTS

6. How likely are the outcomes over time? • How precise are the prognostic estimates IMPORTANT COMPONENTS

7. The study started with collected samples according to standardized criteria • The target disorder is defined and how the samples FIRSTLY assembled is described • Ideally, the best of its kind is participants are all at a similar stage in the course of the same disease • Inception cohort SAMPLE ASSEMBLED AT A COMMON POINT

8. Ideally, every patient in the cohort would be followed until fully recover or develop one of the disease outcomes • Too short=too few patients develop the outcome of interest • Too little=the less accurate the estimate of the risk of the outcome will be • “5 and 20” rule= fewer than 5% loss leads to little bias, greater than 20% loss threatens validity FOLLOW UP SUFFICIENTLY LONG AND COMPLETE

9. The investigators use the established specific criteria to define each important outcome and then used them throughout the patient follow up • Death is objective, but judging underlying cause is very prone to error • Determining the underlying cause of death (or clinical outcomes), the investigator must not knowing prior clinical characteristic and prognostic factors-> blinding BLINDED OBJECTIVE OUTCOME CRITERIA

10. Adjustment of (other) prognostic factors similar to adjustment of confounding factors • Prognostic factor are associated to the outcome of interest • If the study reports that one group of patients had a different prognosis than another, first we need to see if there was any adjustment for known prognostic factors ADJUSTMENT OF PROGNOSTIC FACTORS IN DIFFERENT PROGNOSIS SUB-GROUPS

11. Typical results of prognosis study: • As a percentage of survival at particular point in time (such as 1-year or 5-year survival rate) • As a median survival (the length of follow up by which 50% of study patients have died) • As a survival curves that depict the proportion of the original study sample who have not yet had a specified outcome (Kaplan-Meier curves) LIKELIHOOD OF THE OUTCOMES OVER TIME

12. A: Good prognosis (or too short study!). B: Poor prognosis early, then slower increase in mortality, with median survival of three months. C: Good prognosis early, then worsening, with median survival of 9 months. D: Steady prognosis. KAPLAN-MEIER CURVES

13. A good prognostic study include the confidence intervals for its estimates of prognosis PRECISION OF PROGNOSIS ESTIMATION

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