Clinical Scenario

Step 1: Ask an answerable clinical question--P. I. C. O.

Patient / Problem : Intervention / Exposure:

Comparison: Outcome:

PICO

Question:

• Patient / Problem : • Intervention / Exposure: • Comparison: • Outcome:

Step 2: Effective searches for the best Evidence

搜尋策略的設計表 SEARCH STRATEGY DESIGN TABLE

　　主要詞彙 Primary Term

同義字 Synonym 1 同義字 Synonym 2

P OR OR AND

I OR OR AND

C OR OR AND

O OR OR AND

實際搜尋 ACTUAL SEARCHES

Cochrane 搜尋　　　　　　　　　　　

文獻數　　　　　　　　　　　　

PubMed 搜尋 文獻數　　　　　　　　　　　　

Step 3: Critically appraise that evidence for its validity and

importance

A. 文獻的結果能令人信服嗎 ? Are the results of this prognosis study

valid?

1. Was a defined, representative sample of patients assembled at a common (usually early) point in the

course of their disease?

本文獻： □ Yes □No □Unclear

評論 Comment ：

2. Was patient follow-up sufficiently long and complete?

本文獻： □ Yes □No □Unclear

評論 Comment ：

3. Were objective outcome criteria applied in a “blind” fashion?

本文獻： □ Yes □No □Unclear

評論 Comment ：

4. If subgroups with different prognoses are identified, was there adjustment for important prognostic factors?

本文獻： □ Yes □No □Unclear

評論 Comment ：

5. Was there validation in an independent group (“test set”) of patients?

•   本文獻： □ Yes □No □Unclear

評論 Comment ：

B. 文獻的結果夠重要嗎 ?Are the valid results of this prognosis

study important?

6. How likely are the outcomes over time?

Prognosis shown as survival curves (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.

Typically, results from prognosis studies are reported in one of three ways: 1)as a percentage of survival at a particular point in time (such as 1-year or 5-year survival rates); 2) as median survival (the length of follow-up by which 50% of study patients have died); or 3) as survival curves that depict, at each point in time, the proportion (expressed as a percentage) of the original study sample who have NOT yet had a specified outcome.In prognosis studies we often find results presented as Kaplan–Meier curves, which are a type of survival curve.

7. How precise are the prognostic estimates?If you want to calculate a Confidence Interval around the measure of Prognosis:

Clinical Measure Standard Error (SE) Typical calculation of CI

Proportion (as in the rate of some

prognostic event, etc) where:

the number of patients = n

the proportion of these patients

who experience the event = p

SE = {p x (1-p) / n}

where p is proportion and n is

number of patients

If p = 24/60 = 0.4 (or 40%) &

n=60

SE={0.4 x (1-0.4) / 60} = 0.063

(or 6.3%)

95% CI is 40% +/- 1.96 x 6.3% or

27.6% to 52.4%

n from your evidence: ________

p from your evidence: ________

{p x (1-p) / n}

where p is proportion and n is

number of patients

Your calculation:

SE: ____________

95% CI:

C. 文獻的結果能應用到我們的病人嗎 ? Can we apply this valid, important

evidence about prognosis in caring for our patient?

8. Were the study patients similar to our own?

9. Will this evidence make a clinically important impact on our conclusions about what to offer

or tell our patient?