Extensive scientific investigation of drugs in man and introduction of numerous new drugs over the past few decades is gradually transforming the practice of medicine from ‘experience based’ wherein clinical decisions are made based on the experience (or rather impression) of the physician to ‘evidence based’ wherein the same are guided by scientifically credible evidence from well designed clinical studies.
EVIDENCE BASED MEDICINE
Extensive scientific
investigation of drugs in man and introduction of numerous new drugs over the past
few decades is gradually transforming the practice of medicine from ‘experience based’ wherein clinical
decisions are made based on the experience (or rather impression) of the
physician to ‘evidence based’ wherein
the same are guided by scientifically credible evidence from well designed
clinical studies. Evidence based medicine is the process of systematically
finding, evaluating and using contemporary research findings as the basis of
clinical decisions. Results of well designed multicentric interventional trials
are forming the basis of constantly evolving guidelines for disease management.
Today’s physician has to be skilled in searching and evaluating the literature
on efficacy, safety and appropriateness of a particular therapeutic measure
(drug). Therapeutic evaluation of a drug includes:
§ Quantitation of
benefit afforded by it.
§ The best way (dosage,
duration, patient selection, etc.) to use it.
§ How it compares with
other available drugs.
§ Surveillance of
adverse effects produced by it.
Clinical studies are basically of the
following three types:
a. Clinical trials
b. Cohort studies
c. Case control studies
It
is a prospective ethically designed investigation in human subjects to
objectively discover/verify/ compare the results of two or more therapeutic
measures (drugs). Depending on the objective of the study, clinical trial may
be conducted in healthy volunteers or in volunteer patients. Healthy volunteers
may be used to determine pharmacokinetic characteristics, tolerability, safety
and for certain type of drugs (e.g. hypoglycaemic, hypnotic, diuretic) even
efficacy. For majority of drugs (e.g. antiepileptic, antipsychotic, antiinflammatory,
antitubercular, etc.) therapeutic efficacy can only be assessed in patients.
The inclusion of a
proper comparator (control) group in
clinical trials is crucial. The control group, which should be as similar to
the test group as possible, receives either a placebo (if ethically
permissible) or the existing standard treatment. Separate test and control
groups may run simultaneously (parallel
group design), or all the subjects may be treated by the two options one
after the other (cross over design)
so that the same subjects serve as their own controls. In the cross over design,
some patients are treated first by drug ‘A’ followed by drug ‘B’, while in
others the order is reversed. This nullifies the effect (if any) of order of
treatment. This design is applicable only to certain chronic diseases which
remain stable over long periods.
It
is well known that both the participants and the investigators of the trial are
susceptible to conscious as well as unconscious bias in favour of or against
the test drug. The greatest challenge in the conduct of clinical trial is the
elimination of bias. The credibility of the trial depends on the measures that
are taken to minimize bias. The two basic strategies for minimizing bias are
‘randomization’ and concealment or ‘blinding’.
Randomization
The subjects are
allocated to either group using a
preselected random number table or computer programme so that any subject has
equal chance of being assigned to the test or the control group. Discretion
(and likely bias) of the investigator/subject in treatment allocation is thus
avoided. If considered necessary, stratified
randomization according to
age/sex/disease severity/other
patient variable may be adopted.
Blinding (masking)
This refers to
concealment of the nature of
treatment (test or control) from the subject (single blind) or both the subject
as well as the investigator (double blind). For this purpose the two
medications have to appear similar in looks, number, weight, taste, etc. and
are to be supplied in unlabelled packets marked for each patient. In double
blind, the key/code to treatment allocation is kept by a third ‘data management’
party who is not involved in treating or recording observations. The code is
broken at the completion of the trial and the results are analysed according to
prespecified statistical method. However, all clinical trials need not be
blinded. Those in which the nature of treatment is not concealed are called ‘open’ trials.
Randomized controlled
double blind trial is the most credible method of obtaining evidence of
efficacy, safety or comparative value of treatments.
Inclusion/Exclusion Criteria
The characteristics of the subject/patient (age, sex,
disease/symptom, severity and/or duration of illness, coexistant and past
diseases, concurrent/preceeding drug therapy, etc.) who are to be recruited in
the trial or excluded from it must be decided in advance. The trial results are
applicable only to the population specified by these criteria.
End point
The primary and
secondary (if any) end points (cure,
degree of improvement, symptom relief, surrogate marker, avoidance of complication,
curtailment of hospitalization, survival, quality of life, etc.) of the trial
must be specified in advance. The results are analysed in relation to the
specified end points.
Higher efficacy may
not always be the aim of a clinical trial. A trial may be designed to prove ‘non
inferiority’ (of the new drug) to the existing treatment, and possibly afford
advantages in terms of tolerability, safety, convenience, cost or applicability
to special patient subgroup(s).
Sample Size:
The number of subjects
in the trial for obtaining a
decisive conclusion (test better than control/control better than test/no
difference between the two) must be calculated statistically beforehand.
Because the trial is conducted on a sample of the whole patient population,
there is always a chance that the sample was not representative of the population.
Two types of errors
are possible:
Type I (α) error: a difference is found between the two groups while none exists. Its possibility is
called ‘significance’ of the result,
e.g. if test drug is found to be better than control at a significance level of
0.05, it means that there is 5% chance that this is not real.
Type II (β) error: no difference is found while it really exists. The probability of failing to detect
an actual difference is expressed by the ‘power’
of the trial. A power of 0.9 means that there is 10% chance of missing a real
difference.
The
sample size of the trial depends on the desired level of significance and
power. The other input needed for calculation of sample size is the magnitude
of difference between the two groups that is expected or is considered
clinically significant, e.g. a 10% reduction in pain intensity may not be
considered clinically significant, while a 10% reduction in mortality may be
worthwhile. Larger sample size is required to detect smaller difference. Also,
higher the significance and power level desired, greater is the number of
subjects.
Many
large scale trials are subjected to interim analysis from time to time as the
trial progresses by an independent committee which can order an early
termination if a decisive result (positive or negative) is obtained; because it
would be unethical to subject some of the remaining patients to a treatment
(test or control) which has been found inferior.
Multicentric trial
Many large trials are
conducted at more than one
centre by as many teams of investigators, sometimes spread over several
countries. The advantages are:
§ Larger number of patients
can be recruited in a shorter period of time.
§ Results are applicable
to a wider population base which may cover several countries/ ethnic groups.
§ Regulatory
requirements of several countries may be satisfied.
§ Credibility of the
trial is enhanced.
Sequential Trial
This design attempts
to detect a significant result as soon as it is achieved, minimizing the number
of subjects. The trial is conducted on matched pairs of subjects and is scored
as ‘A’ treatment better than ‘B’ or ‘B’ better than ‘A’ or no difference. This
is plotted continuously as the trial proceeds till the
boundries of
predetermined level of significant superiority/inferiority/no difference are
touched. The trial is then terminated. This design is applicable only to
certain types of drugs and diseases for which clinical end points are achieved
quickly and paired comparisons are possible. Moreover, it may not always be
practicable to recruit matching pairs of trial subjects.
Meta-Analysis
This is an exercise in
which data from several similarly conducted randomized controlled clinical
trials with the same drug (or class of drugs) examining the same clinical end
point(s) is pooled to bring out the overall balance of evidence by enlarging
the number of test and control subjects and increasing the significance and
power of the conclusions. Because individual trials are often conducted on
relatively smaller number of patients, some may fail to detect a significant difference,
while others may find it. Discordant results are published which confuse the
medical practitioner. Though there are many criticisms of metaanalysis, such
as:
§ bias in the selection
of trials for analysis;
§ unintentional
exclusion of negative results which are less likely to be published
(publication bias);
§ nonuniformity of the
trials in details of methodology and conduct;
it is a useful tool to
arrive at conclusions that may influence medical practice. For example, metaanalysis
of trials has strongly supported the use of βadrenergic blockers in
heart failure and use of statins to reduce risk of coronary artery disease.
To be reliable, the
metaanalysis should observe the following:
§ Comprehensive search
of the literature to identify all eligible trials.
§ Use objective criteria
for selecting the trials for inclusion.
§ Include only
randomized trials of assured quality.
§ Employ proper
statistical methods in pooling and treating the data from individual trials.
Metaanalysis are now
frequently published on contemporary therapeutic issues.
This is a type of
observational study in which no intervention for the sake of the study is done.
‘Cohort’ is a group of individuals having some common feature. In the context
of drug research, the common feature is that all study subjects have taken a
particular drug. Occurrence of events (beneficial or adverse) in users and nonusers
of the drug is compared. It can be a prospective or a retrospective study. In
the prospective design, all patients who receive the study drug are followed up
for therapeutic outcomes or adverse effects. A matching group of patients who
have not received the drug is identified and followed up to serve as control.
Cohort studies are primarily used to discover uncommon adverse effects that may
be missed during formal therapeutic trials which involve fewer patients and
often exclude certain type of patients who may be susceptible to that adverse
effect. Its value for defining therapeutic outcomes is less credible. The limitations
of cohort studies are that controls included may not be appropriate, and
relatively long period of follow up is needed.
In the retrospective
cohort study, health records of a population are scrutinized for exposure to
the study drug and the subsequent beneficial/adverse events. Its value is
questionable because many events may have been missed in the records and
several unknown factors may have contributed to the findings. However, it may
serve as pointer, or to arouse suspicion.
This type of
observational study is used mainly to reveal association of a suspected rare
adverse event with the use of a particular drug. Cases of the suspected adverse
event (e.g. agranulocytosis) are collected from hospital records or disease
registries, etc. A matched control group similar in other respects but not
having the adverse event is selected. Drug histories of both groups are traced
backwards to compare exposure to the indicted drug (e.g. phenylbutazone) among
patients with the adverse event to those without it. The suspicion is
strengthened if high association is found. Though case control studies can be
performed rather quickly because the number of patients analysed is small
compared to the cohort design, they do not prove causality. Also, the causative
drug and the adverse event have to be suspected first to plan the study,
whereas cohort study can reveal unsuspected adverse events. Variable accuracy
of retrospective records, non randomly selected control group, chances of bias
and a variety of unknown factors make the case control study a weak instrument
for affording convincing evidence.
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