Evaluate bias in meta-analysis within meta-epidemiological studies -  Pubrica
                     HOW TO EVALUATE BIAS IN
META-ANALYSIS WITHIN
META-EPIDEMIOLOGICAL
STUDIES?
An Academic presentation by
Dr. Nancy Agnes, Head, Technical Operations, 
Pubrica
GEmroauipl::  www.pubrica.com
[email protected]
T O D A Y ' S D I S C U S S I O 
N
O u t l i n e
Introductio
nBias in meta-analysis 
within
meta-epidemiological 
studies
Conclusion
INTRODUCTI
ONMeta-analysis is a type of statistical 
approach
which synthesizes results from 
different
studies and the final result serves as a 
much
stronger evidence than the one 
cIto gllievcetse dan estimate of the success of a 
newly
from an individual study.
introduced treatment/ intervention or 
the risk
factors associated with a disease/ 
line of
Thus, it can serve as the best source 
ftoreratment (Hayden et al., 2021).
evidence-based clinical studies.
Contd...
The studies used in meta-analysis can combine results from 
systematic
review, randomised controlled trials (RCT) etc.
Meta epidemiological studies is a new type of method which 
helps in
closing the gap between trials and practice and is a much 
improved
version of systematic review (Page, 2020).
They adopt either systematic review or meta-analysis approach 
and aims
to understand the impact of certain factors on the outcome.
Thus, they try to confirm or nullify the hypothesis in 
question.
The object of analysis is a study and not a patient or an 
individual.
Contd...
Results of meta-epidemiological  study might be directly related to 
exposure but
can also be a result of an alternative effect that might have impacted 
the overall
study outcome.
These alternative effects can be a random error, a bias that can 
pinrcoodrurecect results(Steenland et al., 
2020).
Due to these effects, sometimes an association is falsely accounted 
for in the
outcome when it is not present and on the other hand, sometimes an 
association
is overlooked even in its presence.
BIAS IN META-ANALYSIS 
WITHIN
META-EPIDEMIOLOGICAL 
STInU sDomIeE mSeta epidemiological studies, the effect of
interventions in RCT’s (Randomised 
Controlled
Trials) can be misunderstood leading 
to
underestimation or overestimation of the 
iTnhteerrev encatino nbe several reasons which have 
been
(Christensen and Berthelsen, 2020).
elaborated bellow-
Bias arising due to randomisation- The 
procedure of
sequence generation or allocation concealment 
might Contd...
vary the effects of the introduced interventions.
These two factors also affects the in between 
heterogeneity.
Bias arising due to opting for unintended interventions- This type of 
bias arises
when the participant opts for an intervention different from which they 
have been
randomly allotted for.
Bias arising due to lack of proper outcome data- The exaggeration 
of the
intervention effect can arise when the data of outcomes are either not 
completely/
falsely reported.
There are some examples when there is overestimation and 
underestimation of the
intervention effect even when the outcome has been properly recorded.
Contd...
This is caused due to attrition, but the average bias reported due 
to attrition
could not be combined as the definition of attrition differs across 
studies.
Bias arising due to improper result selection- There has been 
reports of
bias when the outcomes are not properly generated due to 
discrepancies
between results and methods.
Bias arising due to incorrectly measuring outcomes- Due to lack 
of proper
outcome accessors, bias arises in properly measuring the 
outcomes.
This results in improper estimation of intervention 
effects.
Contd...
In most meta-epidemiological studies, a 
written
protocol for selecting the studies need to be 
framed
bIte fiso reim cpoonrdtuacntti ntgo  thinec lmudeeta  a alln athlyes irse. lated 
studies as
missing out on one can introduce bias and 
makes the
sTthued yp lreostso ecffoel ctmivues (tP afonc euts  alo.,n 2 0th2e0 ).selection 
criteria
(eligibility criteria, type of studies to be 
included, etc.)
of the studies to reduce section bias. Fig 1 
depicts a
flowchart of selecting studies. Contd...
Fig 1: Flowchart for selection of 
studies
Alongside these, the other important points 
to be
included in the protocol are objectives of the 
study,
hAyccpoortdhiensgis  ttoo  sboem tees taeudt heotcrs(S, tiet ecnalann bde e tq auli.t,e  
2tr0ic2k0y) .to
combine different study designs of 
meta-
epidemiological studies in a meta-analysis and 
thus
have stated “a meta-analysis may give a 
precise
estimate of average bias, rather than an 
estimate of
the intervention’s effect” and that Contd...
“heterogeneity
between study results may reflect differential 
biases
rather than true differences in an intervention’s 
effect”.
In order to understand the amount of bias that might have 
impacted the
study outcome, it has been unanimously agreed upon that all 
the non-
randomized and observational studies included in the meta-
analysis should
Bbeu ta tshseerses ehda(sP ublejaekn  ento a pl.r, o2p0e2r0 a)g. reement on the guidelines of 
assessing the
risk of bias in different meta-analyses(Mathur and VanderWeele, 
2021).
Meta epidemiological studies helps in overcoming the 
challenges of
systematic reviews.
Out of all, it focuses to get rid of publication 
bias.
Contd...
Publication bias is also an important type of 
bias that
stresses upon the fact that the data used in 
meta-
epidemiological studies should also be drawn 
Iutp oisn sometimes observed that few studies 
farroem n uontpublished study sources (Lin, 2020).
accepted for publishing as they report 
negative
rTehsuusl,t sm. issing out on these can enhance the 
risk of
bias and can give a false impression about 
the
effectiveness of the interpretation(Tan et al., 
2021).
CONCLUSI
ON
The bias which arises during different steps 
of the
meta-analysis must be addressed as this might 
report
cIto mnturasdt ibceto rnyo treedsu tlhtsa.t false reports can impact 
medical
research which can be fatal in few aspects.
The problem with meta-epidemiological study 
lies in
the fact that when the number of studies 
reduces, the
statistical power also reduces.
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