Clinical Trials

1
Clinical Trials
Reading Medical Reports

• Research in Medical Sciences Journal
• Isfahan University of Medical Sciences

A.M.Baghaei
2
Goals

• What is a clinical trial study? What are its
  characteristics? (brief review)
• Assessing the quality of controlled clinical
  trials

Internal validity External Validity

• What is CONSORT?

Consolidated Standards of Reporting of Trials

• What is MCID?

Minimal Clinically Importance Difference

• What is DISCERN ?

A.M Baghaei
3
Components of internal and external validity of
controlled clinical trials
Internal validity
Extent to which systematic error (bias)is
minimized in clinical trials
Biased allocation to comparison groups

• Selection bias
• Performance bias
• Detection bias
• Attrition bias

Unequal provision of care apart from treatment
under evaluation
Biased assessment of outcome
Biased occurrence and handling of deviations from
protocol and loss to follow up
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Components of internal and external validity of
controlled clinical trials (continued)
External validity
Extent to which results of trials provide a
correct basis for generalization to other
circumstances.

• Patients
• Treatment
  regimens
• Settings
• Modalities of outcomes

Age, sex, severity of disease and risk factors,
comorbidity
Dosage and route of administration, type of
treatment within a class of treatments,
concomitant treatments
Level of care (primary to tertiary) and
experience and specialization of care provider
Type or definition of outcomes and duration of
follow up be assessed
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CNOSORT
Consolidated Standards of Reporting Trials

• To comprehend the results of a randomized
  controlled trial (RCT), readers must understand
  its design, conduct, analysis and interpretation.
  That goal can only be achieved through complete
  transparency from authors. Despite several
  decades of educational efforts, the reporting of
  RCTs needs improvement. Investigators and editors
  developed the original
  CONSORT (Consolidated
  Standards of Reporting Trials)
  statement to help authors improve reporting
  by using a checklist (22
  items) and flow diagram.

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• Item 1

TITLE ABSTRACT

• How participants were allocated to interventions?
• (e.g., "random allocation", "randomized" or
  "randomly assigned").

Examples In title "Smoking reduction with oral
nicotine inhalers double blind, randomized
clinical trials of efficacy and safety " In
abstract "Design Randomized, double-blind,
placebo-controlled trial"
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• Item 2

INTRODUCTION
Scientific background and explanation of
rationale
Example "The carpal tunnel syndrome is caused by
compression of the median nerve at the wrist and
is a common cause of pain in the arm,
particularly in women. Injection with
corticosteroids is one of the many recommended
treatments. One of the techniques for such
injection entails injection just proximal to (not
into) the carpal tunnel. The rationale for this
injection site is that there is often a swelling
at the volar side of the forearm, close to the
carpal tunnel, which might contribute to
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Scientific background and explanation of
rationale (Example Cont)
compression of the median nerve. Moreover, the
risk of damaging the median nerve by injection at
this site is lower than by injection into the
narrow carpal tunnel. The rationale for using
lignocaine (lidocaine) together with
corticosteroids is twofold the injection is
painless, and diminished sensation afterwards
shows that the injection was properly carried
out. We investigated in a double blind
randomized trial, firstly, whether symptoms
disappeared after injection with corticosteroids
proximal to the carpal tunnel and, secondly, how
many patients remained free of symptoms at follow
up after this treatment."
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• Item 3(a)

METHODS Participants
Eligibility criteria for participants
M
Example " all women requesting an IUD at the
Family Welfare Center, Kenyatta National
Hospital, who were menstruating regularly and who
were between 20 and 44 years of age, were
candidates for inclusion in the study. They were
not admitted to the study if any of the following
criteria were present (1) a history of ectopic
pregnancy, (2) pregnancy within the past 42 days,
(3) leiomyomata of the uterus, (4) active PID,
(5) a cervical or endometrial malignancy, (6) a
known hypersensitivity to tetracycline, (7) use
of any antibiotics within the past 14 days or
long-acting injectable penicillin, (8) an
impaired response to infection, or (9) residence
outside the city of Nairobi, insufficient address
for follow-up, or unwillingness to return for
follow-up."
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• Item 3(b)

METHODS Participants
The settings and locations where the data were
collected.
Example "Volunteers were recruited in London
from four general practices and the ear, nose,
and throat outpatient department of Northwick
Park Hospital. The prescribes were familiar with
homeopathic principles but were not experienced
in homeopathic immunotherapy."
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• Item 4

METHODS Interventions
Precise details of the interventions intended for
each group and how and when they were actually
administered
Example "Patients with psoriatic arthritis were
randomised to receive either placebo or
etanercept (Enbrel) at a dose of 25 mg twice
weekly by subcutaneous administration for 12
weeks ... Etanercept was supplied as a sterile,
lyophilised powder in vials containing 25 mg
etanercept, 40 mg mannitol, 10 mg sucrose, and
12 mg tromethamine per vial. Placebo was
identically supplied and formulated except that
it contained no etanercept. Each vial was
reconstituted with 1 mL bacteriostatic water for
injection."
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• Item 5

METHODS Objectives
Specific objectives and hypotheses.
Example "In the current study we tested the
hypothesis that a policy of active management of
nulliparous labor would 1. reduce the rate of
cesarean section, 2. reduce the rate of prolonged
labor 3. not influence maternal satisfaction
with the birth experience."
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• Item 6(a)

METHODS Outcomes
Clearly defined primary and secondary outcome
measures
Example "The primary endpoint with respect to
efficacy in psoriasis was the proportion of
patients achieving a 75 improvement in psoriasis
activity from baseline to 12 weeks as measured by
the PASI. Additional analyses were done on the
percentage change in PASI scores and improvement
in target psoriasis lesions."
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• Item 6(b)

METHODS Outcomes
Any methods to enhance the quality of
measurements (e.g., multiple observations,
training of assessors)
Example "Blood pressure while the patient was
sitting and had rested for at least five minutes
was measured by a trained nurse with a Copal
UA-251 or a Takeda UA-751 electronic auscultatory
blood pressure reading machine (Andrew Stephens,
Brighouse, West Yorkshire) or with a Hawksley
random zero sphygmomanometer (Hawksley, Lancing,
Sussex) in patients with atrial fibrillation. The
first reading was discarded and the mean of the
next three consecutive readings with a
coefficient of variation below 15 was used in
the study, with additional readings if required."
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• Item 7(a)

METHODS Sample Size
How sample size was determined
Example "We believed that the incidence of
symptomatic deep venous thrombosis or pulmonary
embolism or death would be 4 in the placebo
group and 1.5 in the ardeparin sodium group.
Based on 0.9 power to detect a significant
difference (P 0.05, two-sided), 976 patients
were required for each study group. To compensate
for nonevaluable patients, we planned to enroll
1000 patients per group."
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• Item 7(b)

METHODS Sample Size
Explanation of any interim analyses and stopping
rules.
Example "The results of the study were reviewed
every six months to enable the study to be
stopped early if, as indeed occurred, a clear
result emerged."
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• Item 8(a)

METHODS Randomization - Sequence generation
Method used to generate the random allocation
sequence.
Example "Independent pharmacists dispensed
either active or placebo inhalers according to a
computer generated randomization list."
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• Item 8(b)

METHODS Randomization - Sequence generation
Details of any restriction (e.g. blocking,
stratification)
Example "Women had an equal probability of
assignment to the groups. The randomization code
was developed using a computer random number
generator to select random permuted blocks. The
block lengths were 4, 8, and 10 varied randomly .
. ."
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• Item 9

METHODS Randomization - Allocation concealment
Method used to implement the random allocation
sequence (e.g., numbered containers or central
telephone), clarifying whether the sequence was
concealed until interventions were assigned
Example "Women were assigned on an individual
basis to both vitamins C and E or to both placebo
treatments. They remained on the same allocation
throughout the pregnancy if they continued in the
study.
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METHODS Randomization - Allocation concealment
Example (Cont) A computer-generated
randomization list was drawn up by the
statistician and given to the pharmacy
departments. The researchers responsible for
seeing the pregnant women allocated the next
available number on entry into the trial (in the
ultrasound department or antenatal clinic), and
each woman collected her tablets direct from the
pharmacy department. The code was revealed to the
researchers once recruitment, data collection,
and laboratory analyses were complete."
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• Item 10

METHODS Randomization - Implementation
Who generated the allocation sequence, who
enrolled participants, and who assigned
participants to their groups
Example "Determination of whether a patient
would be treated by streptomycin and bed-rest (S
case) or by bed-rest alone (C case) was made by
reference to a statistical series based on random
sampling numbers drawn up for each sex at each
centre by Professor Bradford Hill the details of
the series were unknown to any of the
investigators or to the co-ordinator and were
contained in a set of sealed envelopes, each
bearing on the outside only the name of the
hospital and a number. After acceptance of a
patient by the panel, and before admission to the
streptomycin centre, the appropriate numbered
envelope was opened at the central office the
card inside told if the patient was to be an S or
a C case, and this information was then given to
the medical officer of the centre.
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• Item 11(a)

METHODS Randomization - Blinding (masking)
Whether or not participants, those administering
the interventions, and those assessing the
outcomes were blinded to group assignment
Example "All study personnel and participants
were blinded to treatment assignment for the
duration of the study. Only the study
statisticians and the data monitoring committee
saw unblinded data, but none had any contact with
study participants."
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• Item 11(b)

METHODS Randomization - Blinding (masking)
If done, how the success of blinding was
evaluated.
Example "To evaluate patient blinding, the
questionnaire asked patients to evaluate which
treatment they believed they had received
(acupuncture, placebo, or don't know) at 3 points
in time If patients answered either acupuncture
or placebo, they were asked to indicate what led
to that belief "
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• Item 12(a)

METHODS Statistical methods
Statistical methods used to compare groups for
primary outcome(s).
Example "All data analysis was carried out
according to a pre-established analysis plan.
Proportions were compared by using c2 tests with
continuity correction or Fisher's exact test when
appropriate. Multivariate analyses were conducted
with logistic regression. The durations of
episodes and signs of disease were compared by
using proportional hazards regression. Mean serum
retinol concentrations were compared by t test
and analysis of covariance ... Two sided
significance tests were used throughout."
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• Item 12(b)

METHODS Statistical methods
Methods for additional analyses, such as subgroup
analyses and adjusted analyses, indicating which
were pre-specified.
Example "Proportions of patients responding were
compared between treatment groups with the
Mantel-Haenszel c2 test, adjusted for the
stratification variable, methotrexate use."
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• Item 13(a)

Results Participant flow
Flow of participants through each stage (a
diagram is strongly recommended). Specifically,
for each group report the numbers of participants
randomly assigned, receiving intended treatment,
completing the study protocol, and analyzed for
the primary outcome.
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• Item 13(b)

Results Participant flow
Describe protocol deviations from study as
planned, together with reasons.
Examples "There was only one protocol deviation,
in a woman in the study group. She had an
abnormal pelvic measurement and was scheduled for
elective cesarean section. However, the attending
obstetrician judged a trial of labor acceptable
cesarean section was done when there was no
progress in the first stage of labor."
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• Item 14

Results Recruitment
Dates defining the period of recruitment and
follow-up.
Example "Age-eligible participants were
recruited from February 1993 to September 1994
Participants attended clinic visits at the time
of randomization (baseline) and at 6-month
intervals for 3 years."
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• Item 15

Results Baseline data
Baseline demographic and clinical characteristics
of each group.
Characteristic
Vitamin group(n141) Placebo
group(n142) Mean age (SD), y
28.9 (6.4)
29.8 (5.6) Smokers, n ()
22
(15.6) 14
(9.9) Mean body mass index (SD), kg/m2
25.3 (6.0)
25.6 (5.6) Mean blood pressure (SD), mm
HgSystolic
112 (15)
110 (12)Diastolic

67 (11) 68
(10) Coexisting disease, n ()Essential
hypertension
10 (7)
4 (3) Lupus/antiphospholipid syndrome
2 (1)
7 (5) Diabetes

1(1) 3
(2)
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• Item 16

Results Baseline data
Number of participants (denominator) in each
group included in each analysis and whether the
analysis was by "intention to treat". State the
results in absolute numbers when feasible (e.g.,
10/20, not 50).
Examples "One patient in the alendronate group
was lost to follow up thus data from 31 patients
were available for the intention-to-treat
analysis. Five patients were considered protocol
violators ... consequently 26 patients remained
for the per-protocol analyses."
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• Item 17

ResultsOutcomes and estimation
For each primary and secondary outcome, a summary
of results for each group, and the estimated
effect size with a measure of its precision
(e.g.,95 confidence interval).
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• Item 18

Results Ancillary analyses
Address multiplicity by reporting any
other analyses performed, including
subgroup analyses and adjusted analyses,
indicating those pre-specified and those
exploratory.
Example "Another interesting finding was the
evidence of some interaction between treatment
with vitamin A and severity of disease on
presentation, with results slightly in favor of
the vitamin A group among patients initially
admitted to hospital, the opposite occurring
among those treated as outpatients. Although this
finding comes from a subgroup analysis which was
preplanned, in no case did the different response
between the treatment groups reach significance
at the 5 level."
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• Item 19

Results Adverse effects
All important adverse events or side effects in
each intervention group.
Example "The proportion of patients experiencing
any adverse event was similar between the rBPI21
and placebo groups 168 (884) of 190 and 180
(887) of 203, respectively, and it was lower in
patients treated with rBPI21 than in those
treated with placebo for 11 of 12 body systems.
the proportion of patients experiencing a severe
adverse event, as judged by the investigators,
was numerically lower in the rBPI21 group than
the placebo group 53 (279) of 190 versus 74
(365) of 203 patients, respectively. There were
only three serious adverse events reported as
drug-related and they all occurred in the placebo
group"
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• Item 20

Discussion Interpretation
Interpretation of the results, taking into
account study hypotheses, sources of potential
bias or imprecision and the dangers associated
with multiplicity of analyses and outcomes.
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What are a component of a DISCUSSION ?

• Brief synopsis of the key findings
• Consideration of possible mechanisms and
  explanations
• Comparison with relevant findings from other
  published studies (whenever possible including a
  systematic review combining the results of the
  current study with the results of all previous
  relevant studies)
• Limitations of the present study (and methods
  used to minimize and compensate for those
  limitations)
• A brief section that summarizes the clinical and
  research implications of the work, as appropriate

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• Item 21

Discussion Generalizability
Generalizability (external validity) of the trial
findings
Example "Despite the size and duration of this
trial, the populations of patients with OA and RA
are much larger and therapy continues for
substantially longer than 6 months. Moreover,
many patients with OA and RA have comorbid
illnesses (e.g., active GI disease) that would
have excluded them from the current study.
Consequently, the results of this study do not
address the occurrence of rare adverse events,
nor can they be extrapolated to all patients seen
in general clinical practice."
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• Item 22

Discussion Overall evidence
General interpretation of the results in the
context of current evidence.
Example "Studies published before 1990 suggested
that prophylactic immunotherapy also reduced
nosocomial infections in very-low-birth-weight
infants. However, these studies enrolled small
numbers of patients employed varied designs,
preparations, and doses and included diverse
study populations. In this large multicenter,
randomized controlled trial, the repeated
prophylactic administration of intravenous immune
globulin failed to reduce the incidence of
nosocomial infections significantly in premature
infants weighing 501 to 1500 g at birth."
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MCID
Minimal Clinically Important Difference
The minimal clinically important difference
(MCID) of a therapy is defined as
The smallest treatment effect that would result
in a change in patient management, given its side
effects, costs and inconveniences (Delta Value).
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Type I (a) and Type II (b) Error
Test Result Positive (reject Ho) Negative
(not reject H0)
Studies, like diagnostic tests, suffer from 2
types of sampling error false-positive results
(type I, or alpha error) and false-negative
results (type II, or beta error). Finding no
peanuts in a handful of Cracker-Jacks when there
actually are peanuts in the box is an example of
a false-negative study or type II error. By
convention, we accept a 20 chance (beta 0.2)
that a study's results will be falsely negative
due to "bad luck" or sampling error. The "power"
of a study A study with a 20 chance of type II
error has 80 power to find the predefined
clinically important difference if it actually
exists.
Power 1-b
Type I error a
Truth H0 False
Type II error b
1-a
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Power is related to sample size, and small
studies are prone to sampling error. The only
sure way to determine the true popcornpeanuts
ratio is to study the whole population, in this
case the entire box of Cracker-Jacks. A highly
skilled researcher might be willing to tackle
this, but when you're studying people with
diseases, it's usually impossible to study the
whole population. Fortunately, studying a large
enough sample of patients can provide accurate
estimates of truth. Prior to embarking on a
study, researchers perform a sample size
calculation to determine the minimum number of
patients necessary to reduce the chance of
sampling error to an acceptable level.
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Statistical significance vs. clinical importance
Example Investigators turned their attention to
otitis media, and found, in a study of 40,000
children, that imipenem is superior to
amoxicillin (cure rate 96.1 vs. 95.2 p
0.002). This difference is statistically
significant but clinically unimportant. Contrast
this to the findings of the asthma study (n30),
where success rates were 27 for atrovent and 47
for salbutamol (p 0.55). The results are
clinically important but statistically
insignificant.
When interpreting the outcome of any study,
physicians should consider both the reported
effect size (best estimate of truth) and the p
value (likelihood that this difference arose by
chance). If the effect size was clinically
important, but the p value insignificant, the
sample size was probably too small (underpowered
study). If the effect size was clinically
unimportant but the p value significant, the
sample size was probably too large (overpowered
study).
Physicians should be aware that pharmaceutical
manufacturers may be tempted to design
overpowered studies, in the hopes of finding
small but statistically significant differences
that will increase use of their product. These
differences may be clinically unimportant, and
one of our great challenges as physicians is to
establish consensus about what are clinically
important outcome differences for various disease
states.
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MCID
Minimal Clinically Important Difference
The minimal clinically important difference
(MCID)of a therapy is defined as the smallest
treatment effect that would result in a change in
patient management, given its side effects,costs
and inconveniences. It is a key concept in the
design of clinical trials. Sample size
calculations for prospective trials require
determination of the magnitude of difference in
outcomes between treatment groups that the study
can reliably detect (often called the delta
value). In order for clinical trials to have the
best chance of detecting clinically important
effect sizes, their delta values should reflect
the MCIDs of the study interventions.
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The MCID is also a key concept in the
interpretation of clinical trial results.
Example
In individuals without previous myocardial
infarction (MI)or stroke,the regular use of ASA
will reduce the incidence of MI by 0.2per year
(from a baseline rate of 0.7/year to 0.5/year,
which is a relative risk reduction of about
25),but this benefit is possibly offset by a
concomitant absolute increase in the chance of
stroke of 0.02per year (from 0.30/year to
0.32/year,which is a relative increase of about
10/year)and of gastrointestinal bleeding of
about 1per year (from about 1/year to
2/year). After weighing the advantages and
disadvantages of ASA use in this clinical
situation,an influential expert panel did not
recommend its use,reasoning that the efficacy of
ASA in reverting MI was not sufficient to
overcome the increased incidence of stroke and
gastrointestinal bleeding in this low-risk group.
That is, the efficacy of ASA in this
clinical situation was insufficient to meet or
exceed its MCID.
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The comparison of actual study results (including
the point estimates and the accompanying
confidence intervals)with MCID values can also
give an indication of the clinical importance of
the study results.
If the MCID estimate is less than the value of
the lower limit of the 95 confidence interval,
the study results are statistically significant
and very likely to be clinically
important. Example Drug A vs B for HTN
Treatment. MCID 5 mmHg. Drug A decreases MAP
about 45 mmHg. Drug B decreases MAP about 30
mmHg. Mean difference 15 mmHg with CI95 8 ,
18.
Alternatively, if the MCID value is greater than
the upper limit of the 95confidence interval,the
results of the study are very likely to be
clinically unimportant. Example Drug A vs B for
HTN Treatment. MCID 20 mmHg. Drug A decreases
MAP about 45 mmHg. Drug B decreases MAP about 30
mmHg. Mean difference 15 mmHg with CI95 8 ,
18.
Finally, for study results in which the MCID
values are contained within the 95confidence
intervals,their clinical importance is less
clear. Example Drug A vs B for HTN
Treatment. MCID 10 mmHg. Drug A decreases MAP
about 45 mmHg. Drug B decreases MAP about 30
mmHg. Mean difference 15 mmHg with CI95 8 ,
18.
To allow readers to interpret the clinical
importance of trial results from their own
perspective,specific information must be
reported, including a clearly defined primary
outcome,a delta value or MCID,statistical
significance and confidence intervals around the
point estimates of the efficacy of the
intervention.
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Methodological attributes important in the
interpretation of study results from a clinical
perspective
Methods Explicit primary outcome stated Expected
magnitude of difference (delta value)
stated Expected magnitude of difference
identified explicitly as the MCID Delta/MCID
value reported as an absolute value Results
Statistical significance of primary outcome
reported Confidence intervals for primary outcome
reported Discussion Clinical importance of
primary outcome discussed Discussion explicit or
implicit Level of justification Appropriate
clinical interpretation of trial results
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Levels of justification for the discussion of the
clinical importance of study results
Level 1A - Explicitly discusses the clinical
importance of the primary study result in
relation to previous empirical work done to
determine the MCID of the therapy. e.g. the
MCID of the CRDQ (Chronic Respiratory Disease
Questionnaire) has been empirically determined as
a change of 4 points. Level 1B - Explicitly
discusses the clinical importance of the primary
study result in relation to an accepted, but not
empirically determined, MCID for the therapy. e.g
before starting the trial, a MCID in score for
each test was defined using a Delphi panel
consensus. Level 2 - Discusses the clinical
importance of the primary study result in
relation to the reported sample size MCID.
efficacy did not reach the level we initially
posed as necessary to justify surgery. Level 3 -
Discusses the clinical importance of the primary
study result in relation to previously performed
related studies. previous prevention
interventions have been relatively ineffective
at reducing body fatness. Level 4 - Mentions
the clinical importance of the study result but
with no accompanying justification. overall,
these results provide evidence of the clinical
benefits of celecoxib in the treatment of RA.
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Reporting characteristics of published randomized
controlled trials
Primary outcome explicitly reported 22/27
(81) Multiple outcomes measured without a clear
primary outcome being reported 5/27 (19) Sample
size calculation reported 20/27 (74) Delta value
reported in sample size calculation 18/20
(90) Delta value explicitly stated as MCID 2/18
(11) MCID is an absolute value13/18
(72) Primary outcome statistically significant
17/27 (63) Confidence intervals reported for
primary outcomes 11/27 (41) Clinical importance
mentioned 20/27 (74) Explicit discussion 10/20
(50) Implicit discussion 10/20
(50) Justification Level 1 AB 0/20 (0) Level 2
1/20 (5) Level 3 4/20 (20) Level 4 15/20 (75)
Trials were published between Dec. 1, 1998, and
Nov. 30, 1999, in the Annals of Internal
Medicine, BMJ, JAMA, The New England Journal of
Medicine and the Lancet.
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The DISCERN Instrument
What is DISCERN for? There is currently a lot of
written consumer health information on treatment
choices available from a variety of sources. Not
all of this information is good quality and only
a small proportion is based on good evidence.
Many of the publications available provide
inaccurate or confusing advice, and it may be
hard to know which information to use and which
to discard. DISCERN is an instrument, or tool,
which has been designed to help users of consumer
health information judge the quality of written
information about treatment choices.
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The DISCERN Instrument
Section 1 IS THE PUBLICATION RELIABLE?
1 Are the aims clear? 2 Does it achieve its
aims? 3 Is it relevant? 4 Is it clear what
sources of information were used to compile the
publication (other than the author or
producer)? 5 Is it clear when the information
used or reported in the publication was
produced? 6 Is it balanced and unbiased? 7 Does
it provide details of additional sources of
support and information? 8 Does it refer to areas
of uncertainty?
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The DISCERN Instrument
Section 2 HOW GOOD IS THE QUALITY OF INFORMATION
ON TREATMENT CHOICES?
9 Does it describe how each treatment works? 10
Does it describe the benefits of each
treatment? 11 Does it describe the risks of each
treatment? 12 Does it describe what would happen
if no treatment is used? 13 Does it describe how
the treatment choices affect overall quality of
life? 14 Is it clear that there may be more than
one possible treatment choice? 15 Does it provide
support for shared decision-making?
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The DISCERN Instrument
Section 3 OVERALL RATING OF THE PUBLICATION
16 Based on the answers to all of the above
questions, rate the overall quality of the
publication as a source of information about
treatment choices
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Quick reference guide to the DISCERN criteria
A good quality publication about treatment
choices will 1 Have explicit aims 2 Achieve its
aims 3 Be relevant to consumers 4 Make sources of
information explicit 5 Make date of information
explicit 6 Be balanced and unbiased 7 List
additional sources of information 8 Refer to
areas of uncertainty 9 Describe how treatment
works 10 Describe the benefits of treatment 11
Describe the risks of treatment 12 Describe what
would happen without treatment 13 Describe the
effects of treatment choices on overall quality
of life 14 Make it clear there may be more than
one possible treatment choice 15 Provide support
for shared decision-making
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Thanks for your Attention