1. Vanderbilt Sports Medicine Chapter 4: Prognosis Presented by: Laurie Huston and Kurt Spindler Evidence-Based Medicine How to Practice and Teach EBM

2. VSM prognosis “In order to answer questions posed by patients, colleagues, or ourselves, we frequently need to consider questions about prognosis. In order to answer these questions, and to make judgments about when to start and stop treatment, we need to evaluate evidence about prognosis for its VALIDITY, IMPORTANCE, and RELEVANCE to our patients.”

3. VSM Is this evidence about prognosis valid? 1.Was a defined, representative sample of patients assembled at a common point in the course of their disease? Ideal Scenario: the entire population of patients who ever lived who developed the disease, studied from the instant it developed. Reality: need to know the standardized criteria that were used to diagnose the target disorder, and how the participants were assembled. Look to see that study patients were included at a uniformly early time in the disease, ideally when it becomes clinically manifest (called the ‘inception cohort’).

4. VSM Is this evidence about prognosis valid? 2. Was the follow-up of the study patients sufficiently long and complete? Ideal Scenario: every patient in the cohort would be followed until they fully recovered, or developed one of the disease outcomes. Reality: if follow-up is too short, too few people may develop the outcome of interest, and we would not have enough information to help us. Reality: if too many patients are lost (or unavailable) for follow-up, the less accurate of the risk of the outcome will be. It’s important to document and report.

5. VSM Is this evidence about prognosis valid? 2. How can we judge whether the follow-up is ‘sufficiently complete’? An analysis showing that the baseline demographics of the patients who were lost to follow-up are similar to those followed. However, such an analysis is limited to baseline characteristics. Suggest using the “5 and 20” rule: <5% loss probably leads to little bias. >20% loss seriously threatens the study validity. 5% 20% loss cause intermediate amounts of trouble. Sensitivity Analysis

6. VSM Is this evidence about prognosis valid? 3. Were objective outcome criteria applied in a blind fashion? Ideal Scenario: investigators making judgments about clinical outcomes are kept ‘blind’ to these patients’ clinical characteristics and prognostic factors. To minimize the effects of bias in measuring outcomes, investigators should have established specific criteria to define each important outcome BEFORE the study onset, and use them throughout patient follow-up.

7. VSM Is this evidence about prognosis valid? 4.If subgroups with different prognoses are identified, was there adjustment for important prognostic factors and validation in an independent ‘test set’ of patients? Adjusting for demographic, disease-specific, or comorbid variables, that may be associated with the outcome of interest (ie. with multiple regression). The initial group in which prognostic factors are found is called a ‘training set’ or ‘derivation set’. Subsequent, independent groups of patients are termed ‘test sets’ or ‘validation sets, which is used to validate the predictive power of the prognostic factors.

8. VSM Is this valid evidence about prognosis important? 1. How likely are the outcomes over time? Typically, results from prognosis studies are reported in one of three ways: As a percentage of survival at a particular point in time. As median survival (ie. the length of time by which 50% of the patients have died). Survival curves that depict the proportion (%) of the original study sample who have NOT yet had a disease outcome.

9. VSM Figure 4.1 (dashed line indicates median survival). A: Good prognosis (or too short a study!). B: Poor prognosis early, then slower increase in mortality, with median survival of 3 months. C: Good prognosis early, then worsening, with median survival of 9 months. D: Steady prognosis. Prognosis Shown as Survival Curves

10. VSM Is this valid evidence about prognosis important? 2. How precise are the prognostic estimates? We need some means by judging just how much the results vary by chance alone. Confidence Intervals provide the range of values that are likely to include the true estimate, and quantifies the uncertainty in measurement. Good prognostic studies include the confidence intervals in their text, tables, or graphs.

11. VSM Can we apply this valid, important evidence about prognosis to our patient? 1. Is my patient so different from those in the study that its results cannot apply? Compare your patients with those in the study, using descriptions of the study sample’s demographic and clinical characteristics. The book recommends framing the question: “Are the study patients so different from mine that I should not use the results at all in making predictions for my patients?” in order to answer this question.

12. VSM Can we apply this valid, important evidence about prognosis to our patient? 2. Will this evidence make a clinically important impact on our conclusions about what to offer or tell my patient? Evidence regarding prognosis is useful for deciding whether or not to initiate therapy, for monitoring therapy that has been initiated, and for deciding which diagnostic tests to order. Even when the prognostic evidence does NOT lead to a treat/don’t treat decision, valid evidence can be useful in providing patients and families with the information they want about what the future is likely to hold.

13. VSM Practicing EBM in Real Time After you’ve retrieved and appraised an article, it’s useful to keep a copy of the appraisal in case the same question arises again. On the EBM attached CD, CATMaker software is provided to make a record of the appraisal and save it in your own database. Warning – these appraisals should have an expiration date!