EBM Prof Darwin 4. Prognosis EBM_dr Kuntjoro

8/11/2019 EBM Prof Darwin 4. Prognosis EBM_dr Kuntjoro

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Appraising

Prognostic Study


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Introduction - Prognosis

Important phase of a disease

progressionof a disease.

Patients, doctors, insurances concern

Prognosis: the prediction of the futurecourse of events following the onset ofdisease.

can include death, complications,

remission/recurrence, morbidity, disabilityand social or occupational function.


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Introduction - Prognosis

Possible outcomes of a disease and thefrequency with which they can be

expected to occur.

Natural history: the evolution of diseasewithoutmedical intervention.

Clinical course:the evolution of disease in

responseto medical intervention.


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Natural History Studies

Degree to which natural history can be studieddepends on the medical system (Scandinavia)and the type of disease (rare, high risk).

The natural history of somediseases can be

studied because: remain unrecognized (i.e., asymptomatic) e.g., anemia,

hypertension.

considered normal discomforts e.g., arthritis, mild

depression.


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Natural History Studies

Natural history studies permit the

development of rational strategies for:

early detectionof disease e.g., Invasive Cervical CA.

treatmentof disease

e.g. Diabetes


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Prognosis

Patients at riskof target event

Prognosticfactor

Time

Suffer target

outcome

Do not suffer

target outcome

?

?


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

of their disease?

2. Was the follow-up of the study patients sufficiently long

and complete?3. Were objective outcome criteria applied in a blind fashion?

4. If subgroups with different prognoses are identified, was

there adjustment for important prognostic factors and

validation in an independent test set patients?

A. ARE THE RESULTS OF THIS

PROGNOSIS STUDY VALID?


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How well defined the individuals in the study

criteria - representative of the underlying

population.

inclusion, exclusion

sampling method

similar, well-defined point in the course of

their diseasecohort

A.1. Was a defined, representative sample of

patients assembled at a common (usually early)

point in the course of their disease?


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A.2. Was follow-up sufficiently long and

complete? Ideal follow-up period

Until EVERY patient recovers or has one of the otheroutcomes of interest,

Until the elapsed time of observation is of clinical interest toclinicians or patients.

Short follow up timetoo few study patients with outcome of

interest little information of use to patient Loss to follow upinfluence the estimate of the risk of the

outcomevalidity?.

Patients are too ill (or too well); Die; Move, etc

Most journals require at least 80% follow-up for a prognosisstudy to be considered valid.

Best and worst case scenario (sensitivity analysis)


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A.3. Were objective outcome criteria

applied in a blind fashion?

Investigators making judgments

about clinical outcomes are kept

blind to subjects clinicalcharacteristics and prognostic

factors.

Minimize measurement bias!


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Measurement bias

Measurement bias can be minimized by: ensuring observers are blindedto the exposurestatus of the patients.

using careful criteria (definitions)for all

outcome events. apply equallyrigorous efforts to ascertain all

eventsin both exposure groups.


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Prognostic factors: factors associated with aparticular outcome among disease subjects. Canpredict good or bad outcome

Need not necessarily cause the outcome, just beassociated with them strongly enough to predict theirdevelopment examples includes age, co-morbidities, tumor size, severity

of disease etc.

often different from disease risk factors e.g., BMI and pre-menopausal breast CA.

A.4. If subgroups with different prognoses are

identified, was there adjustment for important

prognostic factors and validation in an independent

test set patients?


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Risk factors

distinct from prognostic factors,

include lifestyle behaviors and environmental exposures

that are associated with the development of a targetdisorder.

Ex: smoking = important risk factor for developing lung

cancer, but tumor stage is the most important prognostic

factor in individuals who have lung cancer.

A.4. If subgroups with different prognoses are

identified, was there adjustment for important

prognostic factors and validation in an independent

test set patients?


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Bias in Follow-up Studies

A. Selection or Confounding Bias1. Assembly or susceptibility bias: when exposed

and non-exposed groups differother than by the

prognostic factors under study, and the

extraneous factoraffects the outcome of thestudy.

Examples:

differences in starting point of disease (survival cohort)

differences in stage or extent of disease, co-morbidities, priortreatment, age, gender, or race.


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Bias in Follow-up Studies

A. Selection or Confounding Bias2. Migration bias:

patients drop out of the study (lost-to-follow-up).usually subjects drop out because of a valid reasone.g., died, recovery, side effects or disinterest.

these factors are often related to prognosis. asses extent of bias by using a best/worst caseanalysis.

patients can also cross-overfrom one exposure groupto another

if cross-over occurs at random = non-differentialmisclassification of exposure


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Bias in Follow-up StudiesA. Selection or Confounding Bias

3. Generalizability bias

related to the selective referral of

patients to tertiary (academic) medicalcenters.

highly selected patient pool have

different clinical spectrum of disease.

influences generalizability


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Survival Cohorts

Survival cohort(or available patient cohort) studies

can be very biased because:

convenience sample of current patients are likely to be at

various stages in the course of their disease. individuals not accounted for have different experiences

from those included e.g., died soon after trt.

Not a true inception cohort e.g., retrospective case

series.

Ob d T


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Surviva

lCohorts

B

ias

True Cohort

Survival Cohort

Observed

Improvement

True

Improvement

Assemble

Cohort

N=150

Measure Outcomes

Improved = 75

Not improved = 75

50% 50%

80% 50%Measure OutcomesImproved = 40

Not improved = 10

Assemble

patients

Begin

Follow-up

N = 50

Not

ObservedN = 100

Dropouts:

Improved = 35Not improved = 65


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II. Bias in Follow-Up Studies

B. Measurement bias

Measurement (or assessment) biasoccurs when

one group has a higher (or lower) probability of

having their outcome measured or detected.

likely for softer outcomes

side effects, mild disabilities, subclinical disease or

the specific cause of death.


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B. Are the results of this study

important?

1. How likely are the outcomes over

time?

2. How precise is this prognostic

estimate?


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B.1. How likely are the outcomes over time?

% of outcome of interest at a particular point in

time (1 or 5 year survival rates)

Median time to the outcome (e.g. the length of

follow-up by which 50% of patients have died) Event curves (e.g. survival curves) that

illustrate, at each point in time, the proportion

of the original study sample who have not yet

had a specified outcome.


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Survival Rate

1 year survival

A. Good

B. 20%

C. 20%

D. 20%

Median survival

A. ?

B. 3 months

C. 9 monthsD. 7.5 months


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B.2 How precise is this prognostic

estimate?

Precision95% confidence interval

The narrower the confidence interval, the more

precise is the estimate.

If survival over time is the outcome of interestshorter follow-up periods results in more

precisionfollow up period important to be

clinically important


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C. Can we apply this valid, important

evidence about prognosis to our patients?

1. Is our patient so different from those in

the study that its results cannot apply?

2. Will this evidence make a clinically

important impact on our conclusions

about what to offer or tell our patient?


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Is our patient so different from those in

the study that its results cannot apply?

How well do the study results generalize to thepatients in your practice? Compare patients' important clinical characteristics,

Read the definitions thoroughly

The closer the match between the patient beforeyou and those in the study, the more confident youcan be in applying the study results to that patient.

For most differences, the answer to thisquestion is no,we can use the study results

to inform our prognostic conclusions.


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C.2 Will this evidence make a clinically

important impact on our conclusions about

what to offer or tell our patient?

Useful for

Initiating or not therapy,

monitoring therapy that has been initiated, deciding which diagnostic tests to order.

providing patients and families with theinformation they want about what the future

is likely to hold for them and their illness.

C 2 Will hi id k li i ll


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C.2 Will this evidence make a clinically

important impact on our conclusions

about what to offer or tell our patient?

Communicating to patients their likely

fate

Guiding treatment decisions

Comparing outcomes to make

inferences about quality of care


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Conclusion

Prognosis study beneficial

Communicating to patients their likely fate

Guiding treatment decisions

Comparing outcomes to make inferences

about quality of care


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EBM Prof Darwin 4. Prognosis EBM_dr Kuntjoro

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