Research methodology & principles and pitfalls of a clinical trial design

RESEARCH METHODOLOGY–
principles & pitfalls of clinical trial design
BY
DR. ANTARLEENA SENGUPTA
PG, DEPT. OF PERIODONTOLOGY,
MCODS MANGALORE
2020

CONTENTS
 Introduction
 Objectives of research
 Research methodology
 Clinical trials– principles of research design
 Pitfalls of clinical trial design
 Adaptive designs in clinical trials
 Conclusion
 References

INTRODUCTION
 RESEARCH is an art of scientific investigation
 According to Redman and Mory,
Research is a “Systematized effort to gain new knowledge”
 Research is an original addition to the available knowledge, which contributes to it’s
further advancement
 In sum, Research is the search for knowledge, using objective and systematic
methods to find solution to a problem.
“ A careful investigation or inquiry specially through
search for new facts in any branch of knowledge”
The Oxford Advanced Learner’s Dictionary
The oxford advanced learner’s dictionary
3

OBJECTIVES OF RESEARCH
 To gain familiarity with new insights into a phenomenon
 To accurately portray the characteristics of a particular individual, group, or
a situation
 To analyse the frequency with which something occurs or its association
with something else.
 To examine the Hypothesis of a causal relationship between two variables
4
PURPOSE OF ORAL HEALTH RESEARCH
1. To promote the oral health of the public by improving education, service,
practice and delivery
2. To contribute new knowledge or re-evaluate current knowledge to improve all
phases of oral healthcare
3. To improve the techniques and practices of identifying, preventing and treating
oral diseases in individuals/groups

RESEARCH METHODOLOGY
- The science of studying how research is done scientifically
- Method to systematically solve the research problem by logically adopting
various steps
- Methodology helps to understand not only the products of scientific enquiry but
the process itself
- Aims to describe and analyze methods
- Throw light on limitations and resources
- Clarify the hypotheses and consequences
- Relates the potentialities of the research done to enrich scientific knowledge
5

- TYPES OF RESEARCH:
BASIC v/s APPLIED
QUANTITATIVE
v/s QUALITATIVE
EMPIRICAL v/s
THEORETICAL
6

- TYPES OF RESEARCH:
 QUALITATIVE RESEARCH refers to the use of non-numerical observations to
answer "Why?" questions, while quantitative methods use data that can be
counted or converted into numerical form to address "How?" questions.
QUANTITATIVE
RESEARCH
ANALYICAL
Observational
Cohort study
Case-control
study
Experimental
Randomized
trials
DESCRIPTIVE
Case report
Case series
Cross-sectional
study
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1. Problem formulation
2. Hypothesis formulation
3. Sampling and sample designs
4. Collection of data
5. Presentation of data
6. Analysis and interpretation
7. Writing the report
8
SCIENTIFIC METHOD: refers to a series of standardized procedures used in research to increase
the likelihood that information gathered will be relevant, reliable and unbiased.

1. Problem formulation
- IDEAL REQUIREMENTS:
1. A problem must be significant to some aspect of oral health care
2. If solved, it should contribute to oral health delivery by leading to new knowledge,
confirming or improving current practices or developing new theories
3. The problem must be observable and capable of measurement through known
methods of quantification
4. The problem should be of interest to the researcher, who must be capable of
accessing the necessary resources for proper scientific investigation.
9

2. Hypothesis formulation
- Carefully constructed statements about a phenomenon in the population
- May be generated by deductive reasoning/inductive reasoning
- When tested, will lead to the identification of the most likely causes of disease
- Constructed and tested to identify causes and to explain the distribution of
diseases in populations
10

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HOW TO WRITE A PROTOCOL?
PROTOCOL
Problem to be investigated
1. Project title
2. The research problem
3. Background (Literature
review)
4. The aims & objectives
5. The hypothesis
Method of investigation
1. Plan of investigation
(sample size and statistics)
2. Project milestones
3. Dissemination of results
4. Resources required
- Most important
- Attracts attention
- Short and to-the-point
- Self-explanatory
- Precise and concise
- Must show an understanding of
the research phenomena
- Summarized
- Resist temptation to give
background at this point
- Brief and to-the-point
- No longer than 2 pages (A4)
- Limit papers quoted to <20
- Draw attention to existing gap of
knowledge/deficiencies of
previous study
- Writing flow
- Should logically lead to statement
of aims of proposal
- Explicitly stated
- Confined to the intention of the
project
- Measurable
- Achievable
- Statements to achieve aim
- Appropriate to group under study
- Tentative prediction/explanation of
relationship between 2 or more
variables
- Reflect depth of knowledge
- All relevant variables should be
identified
- Describe tactics of research
- Easiest part to prepare
- Better to use active voice
- Future tense
- Subheadings:
- Subjects
1. The sample population
2. Total no. of subgroups if any
3. All aspects that will inform removal of
bias
4. Inclusion and exclusion criteria
- Design: choice of strategy
- Sample size calculation
- Selection of sampling method
- Determine sample size
- Ensure representativeness
- Reliability– minimize sampling
errors
- Procedure: detailed description,
consent/permission taken, conduct of pilot
study
- Materials, measurements and apparatus
used
- Questionnaires/interview
schedules
- Medical exam
- Laboratory tests
- Screening procedures
- Statistical methods– in detail, rationale for
choice
- Method of dissemination of findings: not
essential, informs reader
- Resources required: cost implications,
funding etc.

SAMPLE is part of a population, called the Universe/ Reference/ Parent population.
SAMPLING is the process or technique of selecting a sample of appropriate characteristics and adequate size.
SAMPLING FRAME: total of the elements of the survey population, redefined according to certain specifications.
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ADVANTAGES
- Reduces the cost of the
investigation, the time
required and the no. of
personnel required.
- Allows thorough
investigation of the units of
observation
- Helps to provide adequate
and in-depth coverage of
the sample units.
IDEAL REQUIREMENTS
1. Efficiency
2. Representativeness
3. Measurability
4. Size
5. Coverage
6. Goal orientation
7. Feasibility
8. Economy and cost
efficiency
METHODS
1. Purposive selection
- Easy
- No preparation of
sampling frame
- Under-representation of
rates of reference
population
2. Random selection: All
variables have an equal
chance of appearance in the
sample

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SAMPLINGDESIGNS
SIMPLE RANDOM
SYSTEMATIC RANDOM
STRATIFIED RANDOM
CLUSTER
MULTIPHASE
MULTISTAGE

- SAMPLE SIZE  precision of estimates
- Characteristics of an optimum sample size—
- An approximate idea of estimate of characteristics under study and its variability from unit to unit in the population
- Knowledge about the characteristic under study
- Probability level within which desired precision is to be maintained
- Availability of experimental material, resources and other practical considerations
Where, n = sample size
p = approximate prevalence rate of disease
q = 1-p
L = permissible error in estimation of p
SAMPLE SIZE, n = 4pq/ L2
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- ERRORS IN SAMPLING:
SAMPLING ERRORS
- Due to the sampling process
- Faulty sample design
- Small sample size
NON- SAMPLING ERRORS
(a) COVERAGE ERROR: due
to non-response from
informant
(b) OBSERVATIONAL
ERROR: interviewer’s bias/
imperfect experimental
technique
(c) PROCESSING ERROR:
errors in statistical analysis
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- Depending on nature of variable:
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QUALITATIVE
DATA
QUANTITATIVE
DATA
DISCRETE VARIABLE
CONTINUOUS
VARIABLE

17
PRIMARY SOURCE
- Firsthand information
- Methods:
[a] DIRECT PERSONAL INTERVIEWS
- face-to-face
- Subjective phenomena– oral health status, opinions & beliefs, behavior
- Advantage: accurate collection of information; clarification of ambiguity
- Disadvantage: time-consuming, more personnel needed
[b] ORAL HEALTH EXAMINATION
- Dentists and auxiliary dental personnel
- Expensive
- Not extensive
[c] QUESTIONNAIRE METHOD
- Either personally/through post
- Easy to adapt for a wide geographic area
- Economical and expeditious
- Requires literate participants.
SECONDARY SOURCE
- Data already recorded
- Serve the purpose of objective of study
- E.g., past records of OPD at a dental clinic

(a) TABULATION
(b) CHARTS & DIAGRAMS
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IDEAL PRINCIPLES OF TABLE CONSTRUCTION
a. Should be as simple as possible
b. 2/3 small tables are more preferred to a single large table containing many details or variables
[maximum = 3]
c. Data must be presented according to size/importance– chronologically or alphabetically
d. Should be self-explanatory: codes, abbreviations, symbols should be explained in a footnote
e. Label each column and row concisely and clearly
f. Units of measure to be mentioned
g. Title: clear, concise, to-the-point
h. Total should be shown
i. Source of unoriginal data in footnote

(a) TABULATION
1. Master table
2. Simple table
3. Frequency distribution table
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ADVANTAGES OF CHARTS & DIAGRAMS
a. Attractive
b. Bird’s eye-view of entire data
c. Lasting impression
d. Facilitate comparison of data relating to different time periods and region

1. Bar chart
- Simple
- Multiple
- Proportional/component
2. Pie diagram/ chart
3. Line diagram
4. Histogram
5. Frequency polygon
6. Cartogram/spot map/shaded map
7. Pictogram
8. Scatter diagram
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0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
Category 1 Category 2 Category 3 Category 4
Chart Title
Series 1 Series 2 Series 3
0
1
2
3
4
5
6
7
8
9
10
Chart Title
Series 1 Column1 Series 3
58%23%
10%
9%
SALES
1st Qtr 2nd Qtr 3rd Qtr 4th Qtr
4.3
2.5
3.5
4.5
2.4 4.4
1.8
2.8
2 2
3
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14
Chart Title
Series 1 Series 2 Series 3
0
0.5
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Y-Values

BIOSTATISTICS: branch of statistics concerned with mathematical facts and data related to
biological events.
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USES
- To test whether difference between 2
populations is real or a chance occurrence
- Study the correlation between attributes in
same population
- Evaluate the efficacy of vaccines, serum
etc
- Measure morbidity and mortality
- Evaluate achievements of public health
programs
- Help promote legislation and create
administrative standards for oral health
POPULATION, U
VARIABLES, V
PROBABILITY
DISTRIBUTION, P
BASIS FOR
STATISTICAL
ANALYSIS

TERMINOLOGIES:
1. Dependent and independent variables:
- A concept which can take on different quantitative values is called a VARIABLE. E.g.,
weight, height etc
- Phenomena which can take on quantitatively different values even in decimal points are
called ‘CONTINUOUS VARIABLES’.
- If it can only be expressed in integer values, they are non-continuous variables or in
statistical language ‘DISCRETE VARIABLES’.
- If one variable depends upon or is a consequence of the other variable, it is termed as
a DEPENDENT VARIABLE, and the variable that is antecedent to the dependent
variable is termed as an INDEPENDENT VARIABLE.
- For instance, if we say that height depends upon age, then height is a dependent
variable and age is an independent variable.
23

TERMINOLOGIES:
2. Extraneous variable:
- Independent variables that are not related to the purpose of the study, but may
affect the dependent variable are termed as EXTRANEOUS VARIABLES or
CONFOUNDING variables.
- Whatever effect is noticed on dependent variable as a result of extraneous
variable(s) is technically described as an ‘EXPERIMENTAL ERROR’.
- A study must always be so designed that the effect upon the dependent variable
is attributed entirely to the independent variable(s), and not to some extraneous
variable or variables.
24

TERMINOLOGIES:
3. Control:
- One important characteristic of a good research design is to minimize the influence or effect of
extraneous variable(s).
- The technical term ‘CONTROL’ is used when we design the study minimizing the effects of
extraneous independent variables.
- In experimental researches, the term ‘control’ is used to refer to restrain experimental conditions.
4. Experimental and control groups:
- In an experimental hypothesis-testing research when a group is exposed to usual conditions, it is
termed a ‘CONTROL GROUP’, but when the group is exposed to some novel or special condition, it
is termed an ‘EXPERIMENTAL GROUP’
5. Treatments:
- The different conditions under which experimental and control groups are put are usually referred to
as ‘TREATMENTS’.
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MEASURES OF CENTRAL TENDENCY aka Statistical averages
26
- Should be easy to understand and compute
- Should be based on each and every item in
the series
- Should not be affected by extreme
observations (too small/ too large)
- Should have sampling stability
MEAN
MEDIAN
MODE

27
MEAN
MEDIAN
MODE
MEAN: simplest measure of central tendency
∑Xi/ n
- Easy to calculate and understand
- Most useful of all averages
- May be unduly influenced by abnormal values
MEDIAN: middle value in a distribution such that one half of the units
have a value smaller and other half of units have a value higher or same
as the middle.
- EVEN no. of observations: Median = mean of 2 middle values
MODE: that value in a series of observations that occurs with the
greatest frequency
- Can be more than one in a series
- Mode = 3 Median – 2 Mean

MEASURES OF DISPERSION: helps to know how widely the observations are spread on either
side of the average
1. RANGE: simplest method. Difference between the value of the largest item and the value
of the smallest item.
2. MEAN DEVIATION:
3. STANDARD DEVIATION:
- aka root mean square deviation
-  magnitude of dispersion from the mean
- Smaller the S.D., greater will be the degree of uniformity of the observations
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M.D = ∑(X –Xi) / n
S.D = √[(X –Xi)2 / n]

THE NORMAL CURVE
- aka Normal or Gaussian distribution
- Resultant curve from data collected from LARGE NO. OF PEOPLE and NARROW CLASS
DISTRIBUTION
- CHARACTERISTICS:
- Bell-shaped
- Only one standard normal curve
- Perfectly symmetrical
- Total area = 1, Mean = 0, S.D.= 1
- Mean, Median and Mode coincide.
29

TESTS OF SIGNIFICANCE: deals with techniques to know how far the differences between the
estimates of different samples is due to sampling variation.
(A) Standard Error of Mean: S.D. of means of several samples from the same population.
(B) Standard Error of Proportion:
(C) Standard Error of difference between two Means:
(D) Standard Error of difference between two Proportions:
30
S.E. of mean = S.D/ √ n
S.E. of proportion = √[pq/n]
S.E. between means = √[1
2/n1 + 2
2/n2]
S.E. between proportions =
√[ p1q1/ n1 + p2q2 / n2]

TESTS OF SIGNIFICANCE
31
CHI-SQUARE (2) TEST
- Analysis of qualitative data
- Karl Pearson
- To test whether the difference in the
distribution of attributes in different groups
is due to sampling variation
2 = [∑(O – E)2]/ E
Where, O = Observed frequency
E = Expected frequency
- STEPS:
1. Test the null hypothesis
2. Calculate 2
3. Apply 2 test
4. Find degree of freedom (d.f) = (column-
1) x (row-1)
5. Inference: if 2 value lesser than observed
value on application NULL hypothesis is
false.
Z TEST
- Used to test significance of difference
in means for larger samples
- Pre-requisites:
1. Sample must be randomly selected
2. Data must be quantitative
3. Variable follows a normal distribution
in the population
4. Sample should be >30
Z = X - 𝐗 / S.D
t TEST
- W S Gossett (Student)
- Small sample size
- t = ratio of observed difference between 2
means of small samples to the S.E of
difference between the same
Unpaired ‘t’ test
Unpaired data of independent observations
made on individuals of two different or separate
groups or samples drawn from 2 populations, to
test if the difference between the means is real
or it can be attributed to sampling variability.
S.E = √ [1/n1 + 1/n2]
t = X1
2 - X2
2 / S.E

TESTS OF SIGNIFICANCE
32
ANOVA
- Analysis Of Variance
- Test the equality of >3 means of
more than 2 groups.
- E.g., comparison of several
different treatment approaches,
drugs, dosage levels etc at the
same time.
CORRELATION-REGRESSION
- Correlation is the relationship between
2 sets of variables
- Denoted by ‘r’
- Correlation coefficient ranges from -1 <
r < +1
- Plotted using a scatter diagram usually
- X  Y  partial positive correlation
- X  1/Y  partial negative correlation
r = [ ∑(x- 𝐱) (y- 𝐲) ] / [ √[ ∑(x- 𝒙)2 (y- 𝒚)2]
t TEST
- W S Gossett (Student)
- Small sample size
- t = ratio of observed difference between 2
means of small samples to the S.E of
difference between the same
Paired ‘t’ test
Paired data of independent observations from
one sample only when each individual gives a
pair of observations.
S.E = S.D/ √ n
t = 𝐗 / S.E
 Find the d.f. = n-1
 Refer to probability of t corresponding to n-1
 If p> 0.05, STATISTICALLY INSIGNIFICANT
(chance occurrence)

- General information
- Contents
1) Title page
2) Table of contents
 CHAPTER I – Introduction
- Statement of the problem
- Purpose
- Significance of the study
- Hypotheses
 CHAPTER II – Background
- Review of literature
- Operational definitions
33

- Contents
1) Title page
 CHAPTER III – Methodology
- Complete research plan
- Validity
- Reliability
 CHAPTER IV – Results
 CHAPTER V – Conclusions & recommendations
- Citing references
- Bibliography
- Secondary referencing
- Citation & reference styles – HARVARD & VANCOUVER
34
Delange, N., Lindsay, S., Lemus, H., Finlayson,
T.L., Kelley, S.T. and Gottlieb, R.A., 2018.
Periodontal disease and its connection to systemic
biomarkers of cardiovascular disease in young
American Indian/Alaskan natives. Journal of
periodontology, 89(2), pp.219-227.
HARVARD STYLE
VANCOUVER STYLE

- Contents
1) Title page
3) Appendix
35

CLINICAL TRIALS
WHAT EXACTLY ARE CLINICAL TRIALS?
- Clinical trials are scientific investigations that examine and evaluate safety and efficacy of
different therapies in human subjects.
- There are various definitions available as different individuals have tried to which try to capture
the essence of clinical trials at different times, e.g.
- Meinert (1986) indicated that a clinical trial is a research activity that involves administration of a
test treatment to some experimental unit in order to evaluate the treatment.
- Piantadosi (1997) simply defined a clinical trial as an experimental testing of medical treatment on
human subject.
“The clinical investigation of a drug that is administered or
dispensed to, or used involving one or more human
subjects”
The Code of Federal Regulations (CFR), USFDA
36

CLINICAL TRIALS– PRINCIPLES OF
RESEARCH DESIGN
EXPERIMENTAL
UNIT
TREATMENT
EVALUATION
An experimental unit is usually
referred to as a subject from a
targeted population under study.
Therefore the experimental unit
is usually used to specify the
intended study population to
which the results of the study
are inferred. For example, the
intended population could be
patients with certain diseases at
certain stages or healthy human
subjects.
In clinical trials a treatment can be a
placebo or any combinations of a
new pharmaceutical identity (e.g., a
compound or drug), a new diet, a
surgical procedure, a diagnostic test,
a medical device, a health education
program, or no treatment.
In addition to the traditional
evaluation of effectiveness and
safety of a test treatment, clinical
trials are also designed to assess
quality of life, pharmacogenomics,
and pharmacoeconomics such as
cost-minimization, cost-
effectiveness, and cost-benefit
analyses to human subjects
associated with the treatment under
study. It is therefore recommended
that clinical trials should not only
evaluate the effectiveness and safety
of the treatment but also assess
quality of life, impact of genetic
factors, pharmacoeconomics, and
research outcomes associated with
the treatment
21 CFR (CODE OF FEDERAL REGULATIONS), USFDA
37

RESEARCH DESIGN
 PHASES OF CLINICAL TRIALS
PRE-CLINICAL PHASE I PHASE II PHASE III PHASE IV
It involves in vitro (test
tube or cell culture) and
in vivo (animal)
experiments using wide-
ranging doses of the
study drug to obtain
preliminary efficacy,
toxicity &
pharmacokinetic
information. Such tests
assist pharmaceutical
companies to decide
whether a drug
candidate has scientific
merit for further
development as an
investigational new
drug (IND).
Initial studies to
determine the
metabolism and
pharmacologic actions of
drugs in humans, the
side effects associated
with increasing doses,
and to gain early
evidence of
effectiveness; may
include healthy
participants and/or
patients.
Controlled clinical
studies conducted to
evaluate the
effectiveness of the drug
for a particular indication
or indications in patients
with the disease or
condition under study
and to determine the
common short-term side
effects and risks.
Expanded controlled and
uncontrolled trials after
preliminary evidence
suggesting effectiveness
of the drug has been
obtained, and are
intended to gather
additional information to
evaluate the overall
benefit-risk relationship
of the drug and provide
an adequate basis for
physician labelling.
“GOLD STANDARD” for
evaluation of therapeutic
interventions’ efficacy.
[DAFNI, 2019]
Post-marketing studies
to delineate additional
information including the
drug's risks, benefits,
and optimal use.
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RESEARCH DESIGN
I. OBJECTIVE OF THE TRIAL
 The medical questions that need to be answered should be clearly formulated
 Accurate and reliable statistical/clinical inference with respect to resources used
 Objectives may be more than one and may be segregated into primary and secondary:
- Primary Objectives – This is a randomized, single‐blind, controlled, parallel‐group
clinical trial to evaluate improvement in CAL post-exposure to PDT
- Secondary Objectives - Secondary objectives of the trial are to evaluate improvement in
probing depth and reduction of bleeding on probing, clinical recession and the plaque
index.
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RESEARCH DESIGN
II. TARGET POPULATION AND PATIENT SELECTION
 a set of eligibility criteria is usually developed to define the target patient population from
which qualified/eligible can be recruited
 INCLUSION CRITERIA
 EXCLUSION CRITERIA
 To be eligible for the intended study, patients must meet all the inclusion criteria
used to roughly outline the target patient population
used to fine-tune the target patient population by removing the expected
sources of variability
40

RESEARCH DESIGN
II. TARGET POPULATION AND PATIENT SELECTION
41

RESEARCH DESIGN
III. ELIGIBILITY CRITERIA FOR THERAPY
Inclusion criteria:
1. ≥4 periodontal pockets with a probing depth ≥5 mm
2. bleeding on probing.
Exclusion criteria:
1. patients who had undergone periodontal, antibiotic, photosensitizing or anticoagulant treatment in the
last three months
2. Smokers
3. had a Silness and Löe plaque index of 2 for more than 30% of the teeth (Persson, Falk, &
Laurell, 2000)
4. pregnant or breastfeeding
5. allergic to the components used in the treatments.
42

RESEARCH DESIGN
IV. SELECTION OF CONTROLS
 In clinical trials, bias and variability can occur in many ways depending on the
experimental conditions
 They have an impact on the accuracy and reliability of statistical and clinical inference of
the trials.
 Uncontrolled (or non-comparative) studies are rarely of value in clinical research.
 FDA requires that adequate well-controlled clinical trials be conducted to provide an
unbiased and valid evaluation of the effectiveness and safety of study medicines.
 The purpose of a well-controlled study is not only to eliminate bias but also to minimize
the variability, and consequently to improve the accuracy and reliability of the statistical
and clinical inference of the study.
43

RESEARCH DESIGN
V. STATISTICAL CONSIDERATIONS
- manner in which the data will be tabulated and analyzed at the end of the study
- considerations include
- primary and secondary response variables
- criteria for efficacy and safety assessment
- sample size estimation
- possible interim analysis and data monitoring
- and statistical and clinical inference.
• Descriptive statistical analysis was performed for the clinical, microbiological and biochemical variables
according to group (control, SRP, SRP + PDT).
• Measurements were obtained at the site level, corresponding to different teeth and patients; the observations
are, therefore, not completely independent.
• These intra- subject and intra- tooth correlation effects were controlled by means of generalized estimation
equation models (Wald χ 2).
• The effects of time, group and interaction were assessed by the model. Due to the involvement of three
groups and to avoid type- I error propagation, the Bonferroni test was applied for multiple comparisons.
• Logarithmic transformation of the microbiological data was performed, and repeated measurement analysis of
variance (ANOVA) models were used to assess differences according to group, with the same type of post
hoc testing as that performed previously (Bonferroni test).
• As important deviations from normality were found for the biochemical parameters, even after transformation,
a nonparametric approach was used. Brunner- Langer models for longitudinal data were estimated to assess
the effects of time, treatment and interaction.
• An analysis of variance (ANOVA)- type test was used for comparisons.
• The level of significance was established as 5% (α = 0.05).
44

RESEARCH DESIGN
VI. OTHER CONSIDERATIONS
- Treatment duration
- Patient compliance
- Missing value
- Dropouts
45

RESEARCH DESIGN
VII. RANDOMIZATION & BLINDING
RANDOMIZATION: process in which the study subjects, after assessment of eligibility and recruitment,
but before the intervention to be studied begins, are randomly allocated to receive one or other of the
alternative treatments under study.
- Some ethical considerations may arise as some subjects receive the treatment under study while the
remaining receive the standard treatment or the placebo
- Benefits:
 It eliminates selection bias .
 It eliminates confounding by adjusting for co-variates.
 It facilitates blinding of the identity of treatments from investigators, participants, and assessors.
 It permits the use of probability theory to express the likelihood that any difference in outcome between
treatment groups merely indicates chance.
- Different randomization procedures are there like simple randomization, restricted randomization and
adaptive randomization.
46

RESEARCH DESIGN
BLINDING: aka Masking. An experimental condition in which various groups of the individuals involved
with the trial are withheld from the knowledge of the treatments assigned to patients and corresponding
relevant information.
- purpose of blinding is to eliminate bias in subjective judgment due to knowledge of the treatment
- Randomization does not guarantee there will be no bias HENCE, BLINDING IS REQUIRED.
- Blinding in clinical trials can be classified into four types:
 An open-label study is a clinical trial in which no blinding is employed.
 A single-blind trial is a trial in which only the patient is unaware of his or her treatment assignment.
 A double-blind trial is a trial in which neither the patients nor the investigator are aware of patient’s
treatment assignment. In addition to the patient’s treatment assignment, the blindness also applies to
concealment of the overall results of the trial.
 A triple-blind study refers to a clinical trial or other experiment in which neither the subject nor the person
administering treatment nor the person evaluating the response to treatment knows which subjects are
receiving a particular treatment or lack of treatment. It can provide the highest degree for the validity of a
controlled clinical trial.
47

RESEARCH DESIGN
- A randomized, single- blind, controlled design was used.
- Simple randomization of the patients (1:1 allocation ratio) to the SRP or SRP + PDT group was carried
out by staff external to the study using a computer- generated random number table.
- Blinding to the randomization was ensured using sealed and opaque envelopes numbered in sequence.
48

PITFALLS OF CLINICAL TRIAL DESIGN
A. THE HYPOTHESIS
 Investigator must first be guided by the overall hypothesis underlying the rationale for the trial,
taking into account—
 the proposed mechanism of action of the mode of therapy
 the planned target population
 anticipated useful clinical effect.
 Failure to clearly define the aims of the study
 Additional aims must be considered in determining the experimental design and specific
outcomes to be used for the trial.
 Trial must be specifically designed to simultaneously provide evidence in relation to efficacy of
agent and pathogenicity
For example, most efficacy studies for Periodontitis agents seek
- determine whether or not a significant decrease in probing attachment loss or bone loss is associated with the test therapy.
- may present difficulty as a study to determine efficacy of a proposed agent, the specific bacterial pathogens responsible for periodontal
disease, and the potential role of several gingival crevicular fluid cytokines as markers for periodontal disease activity is most difficult to
design.
- Issues such as
- sampling strategy
- frequency of sampling
- order of samples taken are key to the success of the second two aims
- may be more peripheral to the determination of the efficacy of the agent.
For example, administration of test agents is sometimes used to test hypotheses concerning the pathophysiology of
Periodontitis. An example of this type of trial would be to use an antibiotic with known efficacy against bacteria x, measure
bacteria before and after treatment with the antibiotic or placebo, and determine the effect on progressive Periodontitis. This
type of trial is often designed to shed light on the role of bacteria in the pathogenesis of periodontal disease. This type of trial
must be specifically designed to simultaneously provide evidence as to the pathogenic role of the test bacteria as well as to
the efficacy of the antibiotic in slowing progressive Periodontitis.
49

A. THE HYPOTHESIS
 The only possible conclusions in hypothesis testing are:
1. Reject the Null Hypothesis, and thus prove the desired alternative hypothesis (positive trial), or
2. Not able to reject the null hypothesis (negative trial).
- Any trial needs to be designed in such a way that it is known a-priori what the errors relative with each of the two possible
conclusions will be.
- Rejecting the null wrongly (false positive result), is subject to Type-I error (alpha), or significance level
- while not rejecting the null hypothesis wrongly (false negative result), is subject to Type-II error (beta)
- Superiority vs Equivalence/Non-inferiority:
- Clear distinction should be made between superiority and equivalence/ non-inferiority Phase III trials, with each testing a
different type of null hypothesis.
- In a superiority trial we aim to reject a null hypothesis of “no effect” or “no difference”,
- while in an equivalence trial we aim to reject a null hypothesis of “different effect”.
- More particularly, in a superiority trial we aim to demonstrate the superiority of a new therapy compared to an established
therapy or placebo.
- Failure to reject the Null hypothesis should not be confused with acceptance of the Null hypothesis.
50

B. ISSUES WITH PLACEBO – the Hawthorne effect
 The double-blind placebo-controlled clinical trial:
 frequently performed in support of a New Drug Application (or a new indication for an existing drug)
to be submitted to FDA
 requires that neither the patient nor the investigators have knowledge of the treatment regimen
administered to each group of subjects.
 investigator is not even aware which subjects comprise a single group
 The Hawthorne Effect– e.g., in case of large case report studies, they should be followed by double-
blind placebo-controlled trials in order to assure that the observed effects are due to the active
therapy and not due to participation in the trial itself. Patients frequently appear to improve merely
from the effects of being placed in a clinical trial. This often occurs because patients may improve
oral hygiene or compliance with the treatment regimen as a result of the special attention or frequent
examinations that often result from study participation. This phenomenon has been termed the
Hawthorne effect.
 A double-blind trial is critical to controlling for the Hawthorne effect.
 The double-blind design also serves to reduce investigator bias.
For example, it is not unlikely that the many subjective indices used in Periodontitis and gingivitis trials
could be affected by the natural and honest desire for successful treatment on the part of the
investigators. The need for a placebo may seem obvious, but the formulation of an adequate placebo is
not always a simple task. Agents that have a distinctive taste or smell or that stain the teeth may be
difficult to duplicate in an inactive form. Side effects can also un-blind the investigator as to the treatment
regimen of a particular patient. Furthermore, the placebo itself must not affect the course of the disease.
51

C. ISSUES OF OVERALL EXPERIMENTAL DESIGN
1. The randomized parallel design. Patients are assigned to
receive either treatment 1 or 2 based on a random code.
Patients remain on the assigned regimen throughout the
course of the study.
The randomized parallel design with stratification. Patients are
assigned to strata based on criteria defined by investigator. In this example
stratification levels 1, 2, and 3 could be comprised ofpatients with probing
attachment loss < 5 mm, 5 to 7 mm, and > 7 mm, respectively. Each
stratum has its own randomized code. This design is intended to balance
treatment groups on the basis of the stratification factor.
2. The cross-over design. Patients are randomly assigned to first
receive either treatment 1 or 2 based on a random code. After a fixed
period, the treatments are crossed and the groups now receive treatment
2 or 1, respectively.
3. The split mouth design. In this design sites, teeth, quadrants,
or half mouths are randomly assigned to receive placebo or test treatments
4. The pre-treatment period design. Patients are examined repeatedly
for a pre-treatment period and disease activity calculated. This
calculated disease activity serves either as an enrollment criterion or is
used to stratify patients by disease activity.
52

1. The randomized parallel design. Patients are assigned to
receive either treatment 1 or 2 based on a random code.
Patients remain on the assigned regimen throughout the
course of the study.
The randomized parallel design with stratification. Patients are
assigned to strata based on criteria defined by investigator. In this example
stratification levels 1, 2, and 3 could be comprised ofpatients with probing
attachment loss < 5 mm, 5 to 7 mm, and > 7 mm, respectively. Each
stratum has its own randomized code. This design is intended to balance
treatment groups on the basis of the stratification factor.
 Advantage-
1. Simple
2. Requires minimal prior knowledge of the history of the course of the disease in each individual
patients
 Disadvantage- randomization may result in many more patients with active sites in either the test group or
placebo group.
53

2. The cross-over design. Patients are randomly assigned to first
receive either treatment 1 or 2 based on a random code. After a fixed
period, the treatments are crossed and the groups now receive treatment
2 or 1, respectively.
 Advantage-
1. ability to use the patient as their own control
2. reducing some of the biologic variation inherent to clinical trials
3. economical both in terms of financial savings and in terms of the power of the design allowing the study
of fewer patients
 Disadvantage- Not appropriate to test all hypotheses; results are nearly impossible to interpret
54

3. The split mouth design. In this design sites, teeth, quadrants,
or half mouths are randomly assigned to receive placebo or test treatments
 Treatment or control regimens are randomly assigned to half mouths, quadrants, sextants, or when appropriate to
the treatment, individually affected teeth
 Attempts to account for individual variation and to increase the power of the experiment using the paired design.
 Concerns:
- such designs are not appropriate for certain forms of therapy, such as systemic drugs.
- certain local treatments, such as surgery, may have distant effects through the entire mouth of the patient. Further
research will continue to shed light on this important matter.
 Most potential for utility in the assessment of therapy
 Exerts its effect solely on a local level.
55

4. The pre-treatment period design. Patients are examined repeatedly
for a pre-treatment period and disease activity calculated. This
calculated disease activity serves either as an enrollment criterion or is
used to stratify patients by disease activity.
 Each patient is studied for a fixed pre-treatment period
 Outcome variables for the main efficacy portion of the study are measured on a repeated basis
 Allow treatment and control groups to be balanced based on the prevalence and severity of progressive disease
as determined by comparison of sequential examinations in addition to the usual indices measured in a single
examination
 Advantage- ability to use the treated patient as his own control as well as in comparison to the matched control
group.
 Disadvantage- our lack of knowledge of the natural history of periodontal disease progression.
56

D. THE PATIENT POPULATION
 MOST important to the conduct and results of a clinical trial
 Careful attention to the inclusion and exclusion criteria
- to assure the safety of the patients involved in the study
- ensure a population that reflects the hypothesis being tested.
The proceedings of the World Workshop of AAP-EFP 2017 has defined the clinical appearance of several forms of Periodontitis
including:
1. Necrotizing periodontitis
2. Periodontitis as a direct manifestation of systemic diseases
3. Periodontitis
 Special populations, such as patients with molar-incisor distribution of Periodontitis or Periodontitis classified by indirect
evidence of progression i.e., bone loss % : age, can make especially interesting populations for study.
 Particularly true with respect to the pathophysiology of the disease process and may make it easier to detect treatment
effects because the disease may be more rapidly progressive in these patients in comparison to Periodontitis patients
classified to a lower grade.
Nonetheless, care must be exercised if attempting to generalize the results of special populations to a target population
composed of Periodontitis patients.
57

E. OUTCOMES TO BE MEASURED
- WWP Consensus 1989, 99: the gold standard for determining the presence of active periodontal disease is
represented by histologic evidence of periodontal tissue destruction.
- AAP-EFP Consensus 2017: Differences in etiology and pathophysiology are required to indicate presence
of distinct periodontitis entities; variations in clinical presentation per se, i.e. extent and severity, do not
support the concept of different diseases.
 Unfortunately there is no satisfactory gold standard for the clinical diagnosis of periodontal disease
 Probing attachment levels
 Radiographic measures
 Time taken for examination
 Outcomes measured match the hypothesis being tested and the proposed mechanisms of action of
the mode of therapy under study
Imperfect– prone to FALSE-
POSITIVE or FALSE NEGATIVE
For example,
a. an increase in gingival inflammation may increase probe penetration independent of a "true" change in
the soft tissue attachment. This phenomenon would result in a false positive result.
b. the use of interpretive radiography is a relatively crude tool that often does not register bone loss until
30% or more of the bone mineral has been lost. In this case false-negative results may be likely.
For example, a bite-wing radiograph may be interpreted in a minute or less, measurements of bone height
from the same film may take 5 to 10 minutes, and state-of-the-art quantitative digital subtraction
radiography could take 20 minutes.
Since all patients will be studied longitudinally in any of the experimental designs described above, it is safer
for the conduct of the experiment to define the surrogates as secondary outcomes and be sure to track probing
attachment level and/or bone loss over the course of the study. This assertion does not belittle the need for
quick, accurate, and easily-performed measurements related to progressive disease.
58

F. ISSUES OF SAMPLE SIZE
 Determination of sample size: function of the difference expected in outcome between test and control
agents as well as the variance within each group.
 The no. of patients needed to demonstrate a statistically significant superiority between a placebo
and a test mode of therapy is dependent on
- observed mean difference in the primary outcome between placebo and test groups
- variance for the outcome in each group
 Increased duration of study– lengthening study makes it easier to demonstrate differences between
groups
 Increased sample size–
i. Use of conventional therapy as part of protocol
ii. Measurement tool– high variance
iii. Cost factor
For example, the use of special populations such as Stage III Grade B Periodontitis patients may
increase the mean observed difference between test and placebo groups since the mean rate of
progression is relatively high [11%, Sadat et al., 2016] in this special population in comparison to
Stage I Periodontitis patients.
59

F. ISSUES OF SAMPLE SIZE
 Subgroup Analysis
- Another issue that should be taken into account in the design of a trial is subgroup analysis,
involving multiplicity issues.
- It is common practice to perform multiple subgroup analyses
- Probability of a false positive finding (type-I error) increases as the number of subgroup
analyses increases “curse of multiplicity”
60

G. THE ISSUE OF CONTROLS, INCLUDING CUSTOMARY CARE
 Difficulty and expense – do NOT dictate the experimental design
 Primary concern: hypothesis under test
 ALWAYS CONSIDER protection of human subjects
“Therapy by
itself has an
effect on
disease
progression”
“Mode of
therapy is an
adjunct to
conventional
therapy”
Conventional therapy
control is NEEDED
Conventional therapy
may not be needed
61

H. TYPE OF TRIAL
PROOF-OF-PRINCIPLE
TRIAL
• Intended to determine
efficacy of test mode
• May involve study of
special populations for
relatively short periods
• Results do not represent
the definitive answer
concerning the efficacy
• Can be used to design
efficacy trial (multi-
centered)
EFFICACY TRIAL
• utilize a clinical design and
study period that follows
from the intended use of
the mode of therapy
• Patient population should
reflect target population
• Use of measurement tools
PATHOPHYSIOLOGICAL
MECHANISM TRIAL
62

ADAPTIVE DESIGNS IN CLINICAL TRIAL
Why, what and when to adapt in clinical trials?
 Inflexible
 Does not include options for changes necessary during course of the trial
 Viable alternative to traditional design
 Include decision rules to change key trial design elements during the RCT.
 Promises to provide answers to therapeutic research questions as efficiently as possible without compromising
reliability.
 Can be designed such that a conclusive answer is always reached and that—during the course of the study—the
proportion of patients receiving the most promising treatment increases
 Benefit for individual patients
- May overcome ethical barriers to apply deferred or waived consent for randomization
- Increase generalizability of the results.
[Pallmann et al. BMC Medicine, 2018]
63

SAMPLE SIZE INTERVENTION
ALLOCATION
RATIO
STUDY
POPULATION
[Werkhoven et al., 2019]
64

 CHANGING THE SAMPLE SIZE
- several methods that allow adaptation of the sample size during a study
- conducting frequent interim analyses in order to continue the trial until a reliable
conclusion is reached.
- If done with a fixed maximum sample size, this allows for early termination for superiority
or futility (termed “group-sequential design”).
- It can also be done without a fixed maximum sample size (termed “adaptive group-
sequential design”) in which case recalculation of a maximum sample size during each
interim analysis is included.
- This implies that the trial doesn’t stop as long as the interim result is inconclusive, and
thus the planned maximum sample size can increase during the study.
- In an adaptive design, randomization could continue (assuming sufficient funding)
until a clinically relevant benefit has been convincingly demonstrated or excluded.
Arguably, the study will be more expensive, but also more informative, with
research budget better spent.
65

 CHANGING THE INTERVENTION
- Adaptation can be suitable when comparing
- more than two different drugs,
- dosages and/or
- durations of treatment for the same indication.
- This adaptation is referred to as a “drop-the-loser” or “pick-the-winner” design
and is often applied in dose-finding studies.
66

 CHANGING THE ALLOCATION RATIO
- “Response-adaptive randomization” -- allocation ratio of randomized interventions is
changed during the study
- Based on the results of interim analyses.
- For instance, consider a three-arm trial with an initial allocation ratio of 1:1:1 for
arms A, B, and C. In the first interim analysis, A and B have a better outcome,
although C is not statistically significantly inferior. Based on a predefined plan,
the allocation ratio could be changed to 2:2:1, with less patients being
randomized to C. In a subsequent interim analysis C may be found inferior and
will then be dropped, leaving more patients for the comparison of A versus B.
67

 CHANGING THE STUDY POPULATION
- Subgroup-specific effects, e.g. due to
- differences in pathophysiology
- risk of side effects
- pharmacology, occur in many interventions.
- By measuring subgroup effects during interim analyses, all aforementioned adaptations
can be applied to subgroups.
- An example of this can be the clinical trial on NSPT regimens in stage-II/III
periodontitis patients with biomarker-based subgroups. The investigators can
publish the results for one of these subgroups, while in the meantime the trial goes
on to determine the optimal treatment for the other subgroups
68

ADVANTAGES
1. Most are not specific to infectious
diseases.
2. Patients have the advantage of a
higher chance of receiving better
treatment.
3. For researchers and funders there is
reasonable chance (though without
guarantee) that research questions can
be answered with fewer patients
4. More efficient use of research
resourses.
5. May include study domains to be
activated in case of emerging diseases or
epidemics.
REQUIREMENTS
1. Need to account for multiple testing due to
the frequent interim analyses.
2. Due to low numbers within subgroups,
imbalance of baseline characteristics is
possible, which needs to be corrected for
during each interim analysis.
3. Time trends may confound effects,
particularly if response adaptive
randomization is used.
4. Operational characteristics such as the
expected sample size and the chance of
incorrect conclusions require simulation
studies.
5. Involvement of qualified statisticians is
required, and a detailed statistical analysis
plan specifying all possible adaptations must
be designed before the study starts.
69

CONCLUSION
As compared to the classical RCT, adaptive trials can answer research
questions in a more efficient and effective way, but require an extensive
and much more complex statistical preparation.
Broader use of adaptive trials is expected to improve the cost–benefit ratio
of clinical trials in critically ill patients.
70

REFERENCES
1. Soben Peter. Essentials of Preventive And Community Dentistry, 6th Edn. 2017.
2. Igwenagu C. Fundamentals of research methodology and data collection. LAP LAMBERT Academic
Publishing; 2016.
3. Goundar S. Chapter 3 - Research Methodology and Research Method; 2012.
4. Jeffcoat MK. Principles and pitfalls of clinical trials design. Journal of periodontology. 1992
Dec;63:1045-51.
5. Segarra-Vidal M, Guerra-Ojeda S, Vallés LS, et al. Effects of photodynamic therapy in periodontal
treatment: A randomized, controlled clinical trial. J Clin Periodontol. 2017;44(9):915‐925.
6. Pallmann P, Bedding AW, Choodari-Oskooei B, Dimairo M, Flight L, Hampson LV, Holmes J,
Mander AP, Sydes MR, Villar SS, Wason JM. Adaptive designs in clinical trials: why use them, and
how to run and report them. BMC medicine. 2018 Dec;16(1):29.
7. van Werkhoven CH, Harbarth S, Bonten MJ. Adaptive designs in clinical trials in critically ill
patients: principles, advantages and pitfalls. Intensive care medicine. 2019 May 1;45(5):678-82.

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