The document discusses biases in randomized control trials (RCTs) and their potential effects on study outcomes. It outlines various types of biases such as selection and ascertainment bias, along with methods to minimize their impact, including allocation concealment and blinding. The importance of assessing bias risk and maintaining high-quality evidence in trials is emphasized.

1. Biases in RCT
Dr. Ranit Bag
PGT in Pharmacology
CNMCH

2. Contents
Introduction
Reasons of bias
Randomized control trial
Types of bias in RCT
Ways to minimize bias
Summary

3. Introduction
Bias is defined as
Any factor or process ( intentional or
unintentional) tends to deviate the results or
Conclusions of a trial systematically away
from the truth
It can be postulated that the deviation from
the true outcome of the study.

4. Where biases can happen
 Study design
 Data collection
 Process of data analysis
 Publication of study

5. Types of study
Observational
Analytical Descriptive
Experimental
Randomized control
trial
Cohort
Case control
Cross-sectional
Case series
Case study

6. Reasons of biases
Improper and deficient knowledge of the
researcher
Lack of resource, commitment and proper
encouragement
Less adherence towards research guidelines

7. Randomized control trial
Compares two or more treatment or
intervention by estimating the outcome of the
study
Participants are randomized in different groups
Best way to study the safety and efficacy of
new treatment

9. Types of biases in RCT
1. Selection bias
2. Ascertainment bias
3. Hawthorne effect
4. Others

10. Selection bias
It occurs during identification of study
population
Study population not included in target
population
Randomized trial less prone to it

13. Ascertainment bias
One or more people involved in trial, know
about treatment
Drop out cases in case of placebo
Analyser may be biased in assessment of
outcome(observer bias)

15. Hawthorne effect
 Experimental effect is experiment itself and subject
at the center of attention
 Manifest itself as a spurt or elevation in performance

16. Example 1
Example 2

17. Others
 Choice of question bias
 Population choice bias
 Intervention choice bias
 Control group bias
 Outcome choice bias
 Withdrawal and attrition bias
 Selective reporting bias
 Publication bias
 Miscellaneous types(technology, resource allocation,
trial design bias etc.)

18. Ways to minimize bias

20. Allocation concealment
Preventing foreknowledge of next allocation and
implementation of the sequence .

21. Blinding
 Occurs during intervention and outcome of the study
 Minimizes ascertainment(performance) and
detection bias

22. Sl
no
Type of bias Methods to reduce bias
1. Selection bias  Allocation concealment(blinding) hides
randomization sequence before group allocation
and continues upto outcome
 Inclusion and exclusion criteria avoid
confounding results
 Participants from same general population
2. Ascertainment
bias
 Blinding or masking keeps people unaware about
group allocation or interventions
3. Withdrawal and
attrition bias
 Intension to treat analysis includes enrolment
of all study participants
 Sensitivity analysis
4. Selective
reporting bias
 Double blinding
 Instrument development, validation and proper
data collection
5. Publication
bias
 Compulsory registration trial

23. Summary
Randomized trial, the best way to reduce
bias
Researcher should assess the risk of bias
before any trial(Cochrane approach)
Quality of evidence of the trials should be
developed by various approach (e.g- GRADE)

25. References
www.cebm.net
Hernán MA, Robins JM. Causal Inference.
London: Chapman & Hall/ CRC; 2017
Heitjan DF. Ignorability and bias in clinical
trials. Stat Med. 1999;18:2421–2434
file:///D:/pharmacology/statistics/appf-
fm1.pdf