Lecture Appraising articles on harm/etiology

This document includes these contents: Appraising articles on harm/etiology, cohort study, case control study, randomized controlled trial, clinical scenario, clinical resolution,...Invite you to result.

Appraising Articles on

Harm/Etiology

Cohort Study

• A cohort study is an analytical study in which

individuals with differing exposures to a suspected factor are identified and then observed for the

occurrence of certain health effects over some

period, commonly years rather than weeks or

months

• The occurrence rates of the disease of interest are measured and related to estimated exposure

levels

• Cohort studies can either be performed

prospectively or retrospectively from historical

records.

Cohort Study

• Patients who have developed

a disorder are identified and

their exposure to suspected

causative factors is compared

with that of controls who do

not have the disorder

• This permits estimation of

odds ratios (but not of absolute

risks)

• The advantages of

case-control studies are that they

are quick, cheap, and are the

only way of studying very rare

disorders or those with a long

time lag between exposure

and outcome

• Disadvantages include the

reliance on records to

determine exposure, difficulty

in selecting control groups,

and difficulty in eliminating

confounding variables.

Case Control Study

• A case-control study is an observational,

retrospective study which "involves

identifying patients who have the outcome

of interest (cases) and control patients

without the same outcome, and looking

back to see if they had the exposure of

interest."

Case Control Study

• Patients with and without

the exposure of interest are

identified and followed over

time to see if they develop

the outcome of interest,

allowing comparison of risk

• Cohort studies are cheaper

and simpler than RCTs, can

be more rigorous than

case-control studies in eligibility

and assessment, can

establish the timing and

sequence of events, and

are ethically safe

• However, they cannot

exclude unknown

confounders, blinding is

difficult, and identifying a

matched control group may

also be difficult.

Case Control - Retrospective

• Retrospective case-control studies rely on people’s memories, making them prone to error Also, it may be difficult to measure the exact amount of an exposure in the

past Among people with bladder cancer, how might researchers determine the

amount of artificial sweeteners used?

Researchers might ask patients to

self-report their estimated consumption This method is inexact at best.

Case Control - Retrospective

Randomized Controlled Trial

• A randomized controlled trial is an experimental ,

prospective study in which "participants are randomly

allocated into an experimental group or a control group and followed over time for the variables/outcomes of interest."

• Study participants are randomly assigned to ensure that each participant has an equal chance of being assigned to an

experimental or control group, thereby reducing potential bias Outcomes of interest may be death (mortality), a specific

disease state (morbidity), or even a numerical measurement such as blood chemistry level.

• Now let’s look at a diagram of a typical RCT that represents the flow of participants from the start of the study through the study outcome Notice in all diagrams the study start; studies progressing from left to right represent prospective studies,

“collecting data about a population whose outcome lies in the future”

Randomized Controlled Trial

• Similar subjects are

randomly assigned to a treatment group and

followed to see if they

develop the outcome of interest

• RCTs are the most

powerful method of

eliminating (known and unknown) confounding variables and permit the most powerful statistical analysis (including

Study Design

Is The Study Valid?

• In assessing an intervention's potential for harm, we are usually looking at

prospective cohort studies or retrospective case–control studies This is because

RCTs may have to be very large indeed to pick up small adverse reactions to

treatment.

Is The Study Valid?

• 1) Was there a clearly defined question?

• What question has the research been

designed to answer? Was the question focused in terms of the population group studied, the exposure received, and the outcomes considered?

Is The Study Valid?

• 2) Were there clearly defined, similar groups of patients?

• Studies looking at harm must be able to

demonstrate that the two groups of patients are clearly defined and sufficiently similar so as to be comparable

• For example, in a cohort study, patients are either exposed to the treatment or not according to a

decision This might mean that sicker patients – perhaps more likely to have adverse outcomes– are more likely to be offered (or demand)

potentially helpful treatment

• There may be some statistical adjustment to the results to take these potential confounders into

account.

Is The Study Valid?

• 3) Were treatment exposures and clinical outcomes measured the same ways in

both groups?

• You would not want one group to be

studied more exhaustively than the other, because this might lead to reporting a

greater occurrence of exposure or

outcome in the more intensively studied group.

Is The Study Valid?

• 4) Was the follow up complete and long enough?

• Follow up has to be long enough for the

harmful effects to reveal themselves, and complete enough for the results to be

trustworthy (lost patients may have very different outcomes from those who remain

in the study).

Is The Study Valid?

• 5) Does the suggested causative link

make sense?

• You can apply the following rationale to

help decide if the results make sense.

• Is it clear the exposure preceded the onset

of the outcome? It must be clear that the

exposure wasn't just a 'marker' of another disease.

Is The Study Valid?

• Is there a dose-response gradient? If the exposure

was causing the outcome, you might expect to see increased harmful effects as a result of increased exposure: a dose-response effect.

• Is there evidence from a 'dechallenge-rechallenge'

study? Does the adverse effect decrease when

the treatment is withdrawn ('dechallenge') and

worsen or reappear when the treatment is

restarted ('rechallenge')?

• Is the association consistent from study to study?

Try finding other studies, or, ideally, a systematic review of the question.

• Does the association make biological sense? If it

does, a causal association is more likely.

Are the Results Important?

• This means looking at the risk or odds of the adverse effect with (as opposed to

without) exposure to the treatment; the

higher the risk or odds, the stronger the

association and the more we should be

impressed by it

• We can use the single table to determine if the valid results of the study are important

Are the Results Important?

• A cohort study compares the risk of an adverse event amongst patients who received the exposure of

interest with the risk in a similar group who did not

receive it

• Therefore, we are able to calculate a relative risk (or risk ratio) In case-control studies, we are presented with the outcomes, and work backwards looking at

exposures Here, we can only compare the two groups

in terms of their relative odds (odds ratio).

• Statistical significance

• As with other measures of efficacy, we would be

concerned if the 95% CI around the results, whether relative risk or odds ratio, crossed the value of 1,

meaning that there may be no effect (or the opposite).

Interpretation: RISK

• There are a number of ways of

summarizing the outcome from binary data:

• Absolute Risk Reduction

This is expressed as 35/76 or 0.46 Or as a percentage as 46% For a

prospective study such as this, the proportion can be thought of as the

probability of an event happening or a risk.

Interpretation: RISK

Thus, under the standard therapy there was a risk of 35/76 = 0.46 (46%) of

dying or getting a shunt by 1 year of age In the drug plus standard therapy the risk was 49/75 = 0.65 (65%)

In clinical trials what we really want is to look at the contrast between differing

therapies

We do this by looking at the difference in risks, or alternatively the ratio of risks.The difference is usually expressed as the control risk minus the experimental

risk and is known as the absolute risk reduction (ARR).

The difference in risks in this case is 0.46-0.65 = -0.19 or -19% The negative sign indicates that the experimental treatment in this case appears to be doing harm

One way of thinking about this is if 100 patients were treated under standard therapy and 100 treated under drug therapy, we would expect 46 to have died

or have had a shunt in standard therapy and 65 in the experimental therapy

Another way of looking at this is to ask: how many patients would be treated for one extra person to be harmed by the drug therapy? 19 (65-46) adverse events resulted from treating 100 patients and so 100/19 = 5.26 patients would

be treated for 1 adverse event Thus roughly if 6 patients were treated with standard therapy and 6 with drug (experimental) therapy, we would expect 1 extra patient to die or require a shunt in the drug therapy group

This is know as the NNH (number needed to harm) and is simply expressed as the inverse of the absolute risk reduction, with the sign ignored

When beneficial, it is known as NNT=Numbers needed to treat

For screening studies it is known as NNS=Numbers needed to screen

Absolute Risk Reduction = 0.65-0.46 = 0.19; NNH =1/0.19 = 5.26

However, it is important to realize that comparison between NNTs can only be

made if the baseline risks are similar

Thus, suppose a new therapy managed to reduce 5 year mortality of Jakob disease from 100% on standard therapy to 90% on the new treatment This would be a major breakthrough and has a NNT of (1/(1-0.9))=10

Creutzfeldt-In contrast, a drug that reduced mortality from 50% to 40% would also have a NNT of 10, but would have much less impact

We can express the outcome as a risk ratio or relative risk (RR), which is the

ratio of the two risks, experimental divided by control risk, namely 0.65/0.46 =

1.41 With relative risk less than 1 the risk of an event is greater in the control group RR is often used in cohort studies

It is important to consider the absolute risk! The risk of DVT in women on a

new type of oral contraceptive is 30 per 100,000 women years, compared to 15 per 100,000 on the old treatment Thus the RR is 2 (200%) which shows that the new type of contraceptive carries quite a high risk of DVT However, an women need not be unduly concerned since she has a probability of 0.0003 of getting a DVT in 1 year on the new drug which is much less than if she were pregnant!

We can also consider the relative risk reduction (RRR) which is (control risk – experimental risk)/control risk; this is easily shown to be 1-RR, often expressed as

a percentage Thus in the drug arm of the PHVD trial there is a 41% higher risk of experiencing an adverse event relative to the risk of a patient on standard therapy

(0.65-0.46)/0.46 = 0.41

When the data come from a case-control study or a cross-sectional study, rather

than risks, we often use odds The odds of an event happening are the ratio of ratio of

the probability that it happens to the probability that is does not.

Thus the probability of throwing a 6 on a die is 1/6 = 16.67% (Notice the

denominator is the total of all outcomes (Happening + Not Happening) The

probability of throwing any other number is 5/6 = 83.33% If P is the probability of

an event we have:

Odds (event) = P/(1-P) = (Happening/Not Happening )1:5 = 0.1667/0.8333 =

0.2

(35/76=0.46) (49/75=0.65)

Calculate absolute risk of coronary event in the E+P vs Placebo Group:

E+P = 164/8506 = 0.0193 = 1.93%; Placebo = 122/8102 = 0.0151 = 1.51%

Absolute Risk INCREASE = 1.93% - 1.51% = 0.42% (0.0042)

Risk Ratio = 0.0193/0.0151 = 1.26 (26% increase)

Relative Risk Increase/Reduction =( 0.0193-0.0151)/0.0151 = 0.278=27.8% increase

Odds Ratio =/[0.0193/(1-0.0193)] /[0.0151/(1-0.0151)] = 1.29 = 29%

NNH=Numbers needed to harm = 1/|0.0151-0.0193| = 238

For PE

E+P = 70/8506 = 0.0082; Placebo = 31/8102 = 0.0038

Absolute Risk INCREASE = 0.0082-0.0038 =0.0044 = 0.44%

Risk Ratio =0.0082/0.0038=2.16 = (116% increase)

Relative Risk Increase/Reduction =(0.0082-0.0038)/0.0038 = 1.15 = 115%

Clinical Scenario

Do SSRIs Cause Gastrointenstinal

Bleeding?

• You are a general practitioner considering the optimal choice of antidepressant medication Your patient

is a 55-year-old previously cheerful and well-adjusted individual who, during the past 2 months, has

become sad and distressed for the first time in his life He has developed difficulty concentrating and experiences early morning wakening, but lacks thoughts of self-harm The patient has attended your practice for the past 20 years and you know him well You believe he is suffering from a major depressive episode and that he might benefit from antidepressant medication.

During recent years, you have been administering a selective serotonin reuptake inhibitor (SSRI),

paroxetine, as your first-line antidepressant agent However, recent reviews suggesting that the SSRIs are no more effective and do not have lower discontinuation rates than tricyclic antidepressants (TCAs) have led you to revert to your previous first choice, nortriptyline, in some patients Patients in your

practice usually consider the adverse effects in some depth before agreeing to any treatment decisions and many choose SSRIs on the basis of a preferable side-effect profile.

However, for the past 5 years the patient you are seeing today has been taking ketoprofen (a

nonsteroidal anti-inflammatory drug, or NSAID), 50 mg three times per day, which has controlled the pain from his hip osteoarthritis Your mind jumps to a review article suggesting that SSRIs may be associated with an increased risk of bleeding, and you become concerned about the risk of gastrointestinal bleeding

when you consider that the patient is also receiving an NSAID Unfortunately, an abstract from Evidence Based Mental Health, which you have used to obtain a summary of side effects of antidepressant

medications, provides no information regarding this issue.

You remember the review article and locate a copy in your files, but at a glance you realize that it will not help answer your question for three reasons: It did not use explicit inclusion and exclusion criteria, it failed to conduct a systematic and comprehensive search, and it did not evaluate the methodologic

quality of the original research it summarized In addition, it did not cite any original studies specific to

an association between SSRI treatment and gastrointestinal bleeding.

You consider that it is worth following up this issue before you make a final recommendation to the

patient You inform him that he will need antidepressant medication, but you explain your concern about the possible bleeding risk and your need to acquire more definitive information before making a final recommendation You schedule a follow-up visit two days later and you commit to presenting a strategy

at that time.