Evidence-Based Medicine
How to Practice and Teach EBM
Chapter 4: Prognosis
Presented by:
Laurie Huston and Kurt Spindler
Vanderbilt Sports Medicine
“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.”
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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
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cohort’).
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.
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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% < x > 20% loss cause intermediate amounts of
trouble.
Sensitivity Analysis
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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.
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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.
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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.
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Prognosis Shown as Survival Curves
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.
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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.
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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.
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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.
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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!
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