Prognosis Flashcards
Prognosis
Prognosis speaks to outcomes in patients
with disease
Prognostic factors versus risk factors
• Prognosis speaks to outcomes in patients
with disease • Risk factors predict disease development
• Some factors are both risk and prognostic
factors
ex// • Hypertension in acute coronary
syndromes
aspects of prognosis in patient care
- telling families and patients what’s in store
- identifying the high-risk/poor prognosis patients
- matching resources to need
- implicit prognostcation is constant and ongoing– must be evidenced based
three layers of prognosis (LVM)
- prognostic significance of specific variables
- history, physical exam, labs - likelihood of a given outcome in a given disease
- multi-variable models to predict outcome.
what studies inform prognosis
cohort studies
RCTs
administrative data
systematic reviews
factors that determine result validity
- representative sample
- patients should be homogenous with respect to pronostic risk
- was follow up complete?
- were objective and unbiased outcome criteria used?
factors to think about when asking the question “what are the results”?
- how likely are the outcomes over time?
- how precise are the estimates of likelihood?
Simple Odds Ratios represent the results of
a __ analysis.
Multivariate analysis yields adjusted ___
Ratios and ___ predictors
Simple Odds Ratios represent the results of
a univariate analysis.
Multivariate analysis yields adjusted Odds
Ratios and independent predictors
questions to ask yourself when considering “How can I apply the results to patient care? “
- Were the study patients and their management similar to my own?
- Was the follow-up sufficiently long?
- Can I use the results in managing patients in my practice?
• Simple Odds Ratios represent the results of a univariate analysis • Multivariate analysis yields adjusted Odds Ratios and independent predictors
Odds Ratio
measure of association between an exposure and an outcome. OR represents odds that an outcome will occur given a particular exposure compared to the odds of the outcome occurring in the absence of that exposure
The exposure-odds ratio for case control data is
s the ratio of the odds in favor of exposure among cases to the odds in favor of exposure among noncases
the disease-odds ratio for a cohort or cross section is:
is the ratio of the odds in favor of disease among the exposed to the odds in favor of disease among the unexposed
prevalence-odds ratio
refers to an odds ratio derived cross-sectionally from studies of prevalent cases.
formula for odds ratio
when does an odds ratio kind of estimate relative risk
when the disease is infrequent. odds ratio DOES NOT equal relaitve risk when the disease is more common.
Prognostic models use multiple prognostic factors in combination to predict the risk of future clinical outcomes in individual patients. A useful model provides accurate predictions that inform patients and their care givers, supports clinical research, and allows for informed decisions to improve patient outcomes.
Prognostic model research has three main phases:
model development (including internal validation), external validation, and investigations of impact in clinical practice. Although many prognostic models are proposed, relatively few are currently used in clinical practice.
Development of a prognostic model needs to consider various steps, such as the __ and coding of predictors for the model, and how to estimate the model ___.
__ modeling is the most common approach, while ___ learning techniques are gaining interest.
It is important to evaluate the ___ of the predictions for the derivation cohort (___ validation) as well as for new settings that may differ from the derivation cohort (____ validation)
Development of a prognostic model needs to consider various steps, such as the specification and coding of predictors for the model, and how to estimate the model parameters.
Regression modeling is the most common approach, while machine learning techniques are gaining interest.
It is important to evaluate the quality of the predictions for the derivation cohort (internal validation) as well as for new settings that may differ from the derivation cohort (external validation)
Apparent aka ___ validation implies assessment of model performance directly in the derivation cohort. This approach yields an optimistic estimate of model performance, because the regression coefficients are optimized for the derivation cohort
Internal Validation
____ validation relates to the generalizability and transportability of the prognostic model to another population
external
The classic measures to express model performance are __ and __.
___ refers to the ability of the prognostic model to distinguish between high and low risk patients, and is commonly quantified with the ___ statistic
. ___ indicates the agreement between observed outcomes and predicted probabilities.
The classic measures to express model performance are discrimination and calibration. Discrimination refers to the ability of the prognostic model to distinguish between high and low risk patients, and is commonly quantified with the concordance statistic.
Calibration indicates the agreement between observed outcomes and predicted probabilities.
Decision Support
Some prognostic models explicitly aim to support clinical decision making. For these models, an additional __-___ evaluation is required, beyond the normal discrimination and calibration for other prognostic models.
A __-__ measure that can be used to express this balance is __ __ (NB).
NB is calculated as a weighted sum of true and false positive classification: (true positives – weight × false positives) / total number of patients
Decision Support
Some prognostic models explicitly aim to support clinical decision making. For these models, an additional decision-analytic evaluation is required, beyond discrimination and calibration.
A decision-analytic measure that can be used to express this balance is net benefit (NB).
NB is calculated as a weighted sum of true and false positive classification: (true positives – weight × false positives) / total number of patients
how is net benefit calculated?
NB is calculated as a weighted sum of true and false positive classification: (true positives – weight × false positives) / total number of patients
Q1. Research that addresses a prognosis question can inform which of the following scenarios?
a. The likelihood that a former smoker will develop lung cancer
b. The clinical findings, in a comatose survivor of cardiac arrest which can help physicians and loved ones decide when to withdraw life support.
c. Which elements of the history and physical exam can be combined as a rule to eliminate the need for radiography in patients with ankle sprains.
d. Which genetic variants of aspirin metabolism determine response to treatment in acute myocardial infarction.
The answeris B
a. The likelihood that a former smoker will develop lung cancer. (no this is a study about harm, where smoking is a risk factor)
b. The clinical findings, in a comatose survivor of cardiac arrest which can help physicians and loved ones decide when to withdraw life support. (yes, the clinical findings may be used to predict outcome, which can help guide decisions about care)
c. Which elements of the history and physical exam can be combined as a rule to eliminate the need for radiography in patients with ankle sprains. (This is a clinical decision rule designed for diagnostic purposes)
d. Which genetic variants of aspirin metabolism determine response to treatment in acute myocardial infarction. (This is about guiding choice of therapy)
