TYPES OF STUDIES AND TRIALS

1. Different Types of
Studies & Trials
Dr G Praveen Chandra

2. Types of Study Designs

3. META-ANALYSIS
• A way of combining data from many different
research studies.
• A meta-analysis is a statistical process that
combines the findings from individual studies.

5. SYSTEMATIC REVIEW
• A summary of the clinical literature.
• A systematic review is a critical assessment &
evaluation of all research studies that address a
particular clinical issue.
• Researchers use an organized method of locating,
assembling & evaluating a body of literature on a
particular topic using a set of specific criteria.

6. • A systematic review typically includes a
description of the findings of the collection of
research studies.
• The systematic review may also include a
quantitative pooling of data called a meta-
analysis.

8. • Systemic review is a summary of evidence on a
particular topic, typically by an expert or expert panel that
uses a rigorous process for identifying, appraising, and
synthesizing studies to answer a specific clinical question.
• Meta analysis : Many systemic reviews incorporate
quantitative methods to summarize the results from
multiple studies. These reviews are called Meta-
Analyses.
Melnyk, B. M., & Fineout-Overhault, E. (2005). Evidence-Based Practice in Nursing & Healthcare. Philadelphia, PA:Lippincott Williams &
Wilkins.

10. • A controlled clinical trial that randomly, by chance,
assigns participants to two or more groups.
• There are various methods to randomize study
participants to their groups.

11. Advantages:
• unbiased distribution of confounders;
• blinding more likely;
• randomization facilitates statistical analysis.
Disadvantages:
• expensive: time and money;
• volunteer bias;
• ethically problematic at times.

13. COHORT STUDY
• PROSPECTIVE OBSERVATIONAL STUDY
• A clinical research study in which people who
presently have a certain condition or receive a
particular treatment are followed over time &
compared with another group of people who are
not affected by the condition.

14. Advantages:
• ethically safe;
• subjects can be matched;
• can establish timing and
directionality of events;
• eligibility criteria and outcome
assessments can be
standardized;
• administratively easier and
cheaper than RCT.
Disadvantages:
• controls may be difficult to
identify;
• exposure may be linked to a
hidden confounder;
• blinding is difficult;
• randomization not present;
• for rare disease, large sample
sizes or long follow-up
necessary

16. CASE-CONTROL STUDY
• Case-control studies begin with the outcomes &
don’t follow people over time.
• Researchers choose people with a particular
result ( the cases ) & interview the groups or
check their records to ascertain what different
experiences they had.
• They compare the odds of having an experience
with the outcome to the odds of having an
experience withOUT the outcome.

17. • Advantages:
• quick and cheap;
• only feasible method for
very rare disorders or those
with long lag between
exposure and outcome;
• fewer subjects needed than
cross-sectional studies.
• Disadvantages:
• reliance on recall or records
to determine exposure
status;
• confounders;
• selection of control groups
is difficult;
• potential bias: recall,
selection.

20. CROSS-SECTIONAL
STUDY
• The observation of a defined population at a
single point in time or time interval.
• Exposure & outcome are determined
simultaneously.

21. • Advantages:
• cheap and simple;
• ethically safe.
• Disadvantages:
• establishes association at
most, not causality;
• recall bias susceptibility;
• confounders may be
unequally distributed;
• group sizes may be
unequal.

23. CASE REPORTS & SERIES
• A report on a series of patients with an outcome of
interest.
• No control group is involved.

26. IDEAS, EDITORIALS &
OPINIONS
• Put forth by experts in the field.

28. ANIMAL RESEARCH
STUDIES
• Studies conducted using animal subjects

29. TEST-TUBE LAB
RESEARCH
• Test tube experiments conducted in a controlled
laboratory setting.

30. • It should be finally noted that studies can
incorporate several design elements.
• For example, the control arm of a randomized trial
may also be used as a cohort study &
• the baseline measures of a cohort study may be
used as a cross-sectional study.

32. Spotting the Study Design
• The type of study can generally be worked at by
answering the following three issues….
Q1. What was the aim of the study?
• To simply describe a population (PO)
• Descriptive study
• To quantify the relationship between factors
(PICO)
• Analytical study.

33. Q2. If analytic, was the intervention randomly
allocated?
• Yes? RCT
• No? Observational study

34. For observational study the subtypes will then depend on the
timing of the measurement of outcome, so the next question
is:
Q3. When were the outcomes determined?
• Some time after the exposure or intervention?
• cohort study (‘prospective study’)
• At the same time as the exposure or intervention
• cross sectional study or survey
• Before the exposure was determined?
• case-control study (‘retrospective study’ based on recall of the
exposure)

37. PHASES OF
CLINICAL TRIALS
• Clinical trials are often conducted in 4 phases.
• The trials at each phase have a different purpose
& help answer different questions.

38. PHASE 1 TRIALS
• To test an experimental drug or treatment in a
small group of people for the 1st time
• The researchers
• evaluate the treatment’s safety,
• determine a safe dosage range &
• identify side effects.

40. PHASE 2 TRIALS
• The experimental drug or treatment is given to a
larger group of people to see if it is effective & to
further evaluate its safety.

42. PHASE 3 TRIALS
• The experimental study drug or treatment is given
to large groups of people.
• Researchers
• confirm its effectiveness,
• monitor side effects ,
• compare it to commonly used treatments &
• collect information that will allow the experimental
drug or treatment to be used safely.

44. PHASE 4 TRIALS
• Post-marketing studies, which are conducted after
a treatment is approved for use,
• Provide additional information including the
treatment or drug’s risks, benefits & best use.

46. p-value
• In statistics, the p-value is the probability that,
using a given statistical model, the statistical
summary (such as the sample mean difference
between two compared groups) would be the
same as or more extreme than the actual
observed results.

47. • Small p-value ( <0.05 ) indiactes strong evidence
against the null hypothesis, thus rejecting it.
• Large p-value ( >0.05 ) indicates weak evidence
against the null hypothesis, thus failing to reject it.

48. • In statistics, the standard deviation (SD, also
represented by the Greek letter sigma σ ) is a
measure that is used to quantify the amount of
variation or dispersion of a set of data values.

49. • A low standard deviation indicates that the data
points tend to be close to the mean (also called
the expected value) of the set,
• while a high standard deviation indicates that the
data points are spread out over a wider range of
values.