1.0 RANDOMIZED COMMUNITY STUDIES
1.1 OVERVIEW
A community intervention study targets the whole community and not individuals. It has 3 advantages over individual
intervention. It is easier to change the community social environment than to change individual behavior. High-risk lifestyles
and behaviors are influenced more by community norms than by individual preferences. Interventions are tested in the actual
natural conditions of the community, and cheaper.
The Salk vaccine trial carried out in 1954 had 200,000 subjects in the experimental
group and a similar number in the control group. The aspirin-myocardial infarction study was a therapeutic intervention that
randomized 4524 men to two groups. The intervention group received 1.0 gram of aspirin daily whereas the reference group received
a placebo. The Women’s Health Study involved randomization of 40,000 healthy women into two groups to study prevention
of cancer and cardiovascular disease. One group received vitamin E and low dose aspirin. The other group received a placebo.
The alpha tocopherol and beta carotene cancer prevention trial randomized 19,233 mid-age men who were cigarette smokers.
1.2 DESIGN OF A COMMMUNITY INTERVENTION STUDY
There are basically 4 different study designs. In a single community design, disease incidence is measured before and
after intervention. In a 2-community design, one community receives an intervention whereas another one serves as the control.
In a one-to-many, the intervention community has several control community. In a many-to-many design there are study with
multiple intervention communities and multiple control communities. Allocation of a community to either the intervention or
the control group is by randomization. Matching and stratification can also be used in more sophisticated designs. The intervention
and the assessment of the outcome may involve the whole community or a sample of the community. Outcome measures may be individual
level measures or community level measures.
1.3 COMMUNITY TRIALS: STRENGTHS AND WEAKNESSES
The strength of the community intervention study is that it can evaluate a public health intervention in natural field
circumstances. It however suffers from 2 main weaknesses: selection bias and controls getting the intervention. Selection
bias is likely to occur when allocation is by community. People in the control community may receive the intervention under
study on their own because tight control as occurs in laboratory experimental or animal studies is not possible with humans.
2.1 STUDY DESIGN FOR PHASE 3 RANDOMIZED CLINICAL TRIALS
The study protocol describes objectives, the background, the sample, the treatments,
data collection and analysis, informed consent; regulatory regulations, and drug ordering. Trials may be single center or
multi-center, single-stage or multi-stage, factorial, or crossover.
The aim of randomization in controlled clinical trials is to make sure that
there is no selection bias and that the two series are as alike as possible by randomly balancing confounding factors. Equal
allocation in randomization is the most efficient design. Methods of randomization include alternate cases and sealed serially
numbered envelopes. Randomization is not successful with small samples and does not always ensure correct conclusions.
2.2 DATA COLLECTION IN RANDOMIZED CLINICAL TRIALS
Data collected is on patients (eg weight), tumors (eg TNM staging); tumor
markers (eg AFP), response to treatment (complete response, partial response, no response, disease progression, no evidence
of disease, recurrence), survival (disease-free survival, time to recurrence, survival until death), adverse effects (type
of toxicity, severity, onset, duration), and quality of life (clinical observation, clinical interview, self report by patient).
Case report forms design must have a logical order, be clear and not ambiguous,
minimize text, have self-explanatory questions, and ensure that every question must be answered.
In single blinding the diagnosis is known but the treatment is not. In double
blinding both the treatment and the diagnosis are unknown.
The trial is stopped when there is evidence of a difference or when there
is risk to the treatment group.
Quality control involves measures to ensure that information is not lost.
Institutional differences in reporting, and patient management must be analyzed and eliminated if possible. A review panel
or carry out inter-observer rating to assure data consistence.
2.3 ANALYSIS and INTERPRETATION IN RANDOMIZED CLINICAL TRIALS
Comparison of response proportions is by chi-square, exact test, chi-square
for trend. Drawing survival curves is by K-M & life-table methods.
Comparing survival & remission is by the Wilcoxon and log-rank tests.
Prognostic factors of response, remission, duration, and survival times are
investigated using Cox’s proportional hazards regression model.
Meta-analysis combines data from several related clinical trials.
Differences between the two treatment and control groups are due to sampling
variation/chance, inherent differences not controlled by randomization, unequal evaluation not controlled by double-blinding,
true effects of the treatment, and non compliance.
Problems in trials are incomplete patient accounting, removing 'bad' cases
from series, failure to censor the dead, removing cases due to ‘competing causes of death’, analysis before study
maturation, misuse of the ‘p-value’, lack of proper statistical questions and conclusions, lack of proper substantive
questions and conclusions, use of partial of data; use of inappropriate formulas, errors in measuring response, and censoring
of various types.
