Se

C

LINICAL

DEFINITION145

ETHICAL ASPECTS146

PURPOSE OF A CLINICAL TRIAL146

GUIDE TO QUALITY IN CLINICAL TRIALS147

CLASSIFICATION OF CLINICAL TRIALS

Phase I147

Phase II147

Phase III148

Phase IV148

DESIGN OF A CLINICAL TRIAL148

SELECTION OF PARTICIPANTS

Eligibility criteria149

Criteria for exclusion149

ASSIGNMENT OF THE INTERVENTION

Randomization149

Masking (Blinding)150

STANDARD OPERATING PROCEDURES (SOPs)150

SAMPLE SIZE150

DOCUMENTATION

Information on the product151

Protocol of the study151

Operating manual151

Records of the monitor151

Case-record form151

STATISTICAL ANALYSIS

Comparability of study groups152

Comparison of proportions152

Persons/time of follow-up153

Interim analysis153

Intention-to-treat153

DATA SAFETY AND MONITORING COMMITTEE 154

CHECKLIST FOR DESIGN OF A CLINICAL TRIAL155

ADDITIONAL READING157

EXERCISES158

DATA FILE DICTIONARY172

DEFINITION

Clinical trials are used to evaluate the safety and efficacy of (1) a new product; (2) a new formulation or combination of an existing product(s); or (3) a new clinical indication for an existing approved product. Trials can evaluate a therapeutic (drugs) or prophylatic (vaccine) effect.

For regulatory purpose, all studies with new products should follow standard guidelines as proposed by regulatory authorities and provide detailed documentation. Clinical trials are only initiated when a full dossier of the product containing pre-clinical information is assembled, reviewed and approved. This should include all preliminary analysis and studies performed with the candidate product including chemical description, pharmacological effects, mechanisms of action and results from toxicity tests and evaluations in animal models when available. International standards for “Good Clinical Practices” (GCP) are required to assure that proper documentation and safety of patients are guaranteed in clinical trials.

Clinical trials are always prospective in the design. The figure below represents a basic flow chart of an intervention study. Comparison groups are defined according to pre-established objectives and criteria. Follow-up is based on clinical and laboratory parameters as defined. The comparison groups have to be similar in all aspects except with regard the type of intervention received - the biological and clinical characteristics of the individuals selected and assigned to each group, and the clinical monitors must be independent of the products administered.

Population

Sample

Intervention 1

Intervention 2

(placebo)

Disease

No Disease

No Disease

Disease

PRESENT

FUTURE

Adapted from Hulley & Cummings, 1988.

Steps:

1. Select sample from reference population

2. Measure the outcome variables before intervention

3. Randomize the participants to receive intervention 1 or intervention 2

4. Apply the product to be compared

5. Follow-up for therapeutic or prophylactic effect

6. Measure surrogate variables of potential effect

ETHICAL ASPECTS

Experimentation on human beings involves ethical aspects that require careful examination in each specific case. The risks of intervention (and nonintervention for the placebo group) and the potential benefits of the study must be weighed. The principles of free choice and confidentiality of information are fundamental. The participants must be informed of the nature of the research, its methodology, the examinations and sampling to be performed, and the fact that participation is voluntary and they may leave the study whenever they like. This information and their consent to participate must be put in writing.

Whenever possible, the best comparable intervention available should be used in the control/ comparison group. Usually, the conventional treatment or another vaccine is used in cases in which there is no immunizing product for the disease under study. In situations where one product is found superior to another, all the individuals who are not cured or immunized must be given the opportunity to receive the more effective medication at the end of the study.

The protocols for clinical trials must be reviewed and approved by an institutional ethics committee that has the function of evaluating the scientific justification for the study, the qualifications of the investigators, the adequacy of the protocols and documentation, the recruitment criteria and the safety of the participants. The ethical principles are set forth in the Helsinki Declaration, originally adopted in 1964 at the 18th World Health Assembly and since revised. These principles are reviewed in the document International Ethical Guidelines for Biomedical Research Involving Human Subjects, 1993, published by the Council of International Organizations of the Medical Sciences (CIOMS)

PURPOSE OF A CLINICAL TRIAL

The purpose of a clinical trial must be clearly defined in advance, specifying the product, its dosage, the route of administration, the type of patient for whom it is intended, the expected effect, and the parameters to be measured (toxicity, changes in biochemical tests, immune response, and therapeutic or preventive effect). The design of the study, the calculation of the sample size, the procedures for monitoring the participants and the interpretation of the final results depend on a precise statement of the purpose of the study. In some cases it is possible to define a primary objective (based on primary endpoint to be evaluated) and secondary objectives (based on secondary endpoints to be studied).

Examples of trial objectives:

Trials for evaluation of a drug - To determine whether the administration of drug A in a dose of 20 mg IM/kg/day x 7 days to previously untreated adult patients presenting one lesion of cutaneous leishmaniasis is at least 30% more efficacious than the conventional treatment with drug B in a dose of 50 mg IM/kg/day x 20 days over a clinical observation period of 4 months. (a cure criteria should be defined. eg: 100% re-epithelialization and parasitologic negativity of lesions)

Trials for evaluation of a vaccine - To determine whether product QT01-97, administered subcutaneously in two doses, 30 days apart, to children aged 1 to 5 years, residing in areas endemic for malaria, can reduce by at least 50% the number of clinical episodes of malaria following vaccination diagnosed by active and passive surveillance over a 12-month period of monitoring.

Note that in clinical trials it is always necessary to establish a definition of a case or final effect to be observed. A case definition is required for the recruitment of cases for therapeutic trials and for detecting incident cases in prophylactic studies. The definition of a case has implications for the external validity of the results and extrapolation of the conclusions.

GUIDE TO QUALITY FOR CLINICAL TRIALS

The World Health Organization, taking as reference the experience of several countries, has published the document Guidelines for Good Clinical Practice for Trials on Pharmaceutical Products - GCP (WHO Technical Report Series No. 859, 1995, pp. 97-137), as a guide to the design, conduct and reporting of clinical studies. This document presents standards for the conduct of clinical trials so that results can be internationally recognized and suitable for registration. It includes recommendations on ethical aspects and the protection of participants, the investigator’s responsibilities throughout the conduct and analysis of the research, the responsibilities of the sponsor, those of the monitor, the clinical monitoring of toxicity, record keeping, the analysis plan and the role of the drug regulation authorities.

CLASSIFICATION OF CLINICAL TRIALS

Clinical trials are classed as (I-IV) based on their level of complexity, the stage of development of the product to be tested, and the purpose of the evaluation.

Phase I

This is the first stage in the evaluation of a pharmaceutical product in human beings. Phase-I trials are generally preceded by tests on experimental models in animals to evaluate toxicity and efficacy. Phase I studies are usually conducted in the country in which the drug or vaccine was produced (even if the product is not intended for that population). They are held under rigorous medical supervision, usually in hospitals, and involve a limited number of healthy, generally male, adult volunteers. The principal purpose in this phase is to evaluate the product’s toxicity and pharmacokinetics.

Phase II

This phase consists of pilot clinical trials limited to a small number of participants or patients for the purpose of determining preliminary therapeutic activity of a drug or the immunogenic activity of a vaccine. In phase-II trials a comparison group is required. Toxicity of the product is also evaluated in the individuals (or patients) for whom the product is being developed. Dose-response studies are done to find the optimal dosage/schedule for administration of the product and better immunization schemes. A Phase IIa has been described for vaccine studies in which artificial infection challenge are used after immunization to determine the protective effect of the candidate vaccine. These studies evaluate the efficacy of vaccines in the optimal time and at the optimal cost. Phase IIb evaluates efficacy under natural challenge, that is, natural exposure to infection in areas of transmission.

Phase III

Phase III trials are considered pivotal for registration and approval of a pharmaceutical product. They involve large numbers of participants, possibly in multicentre studies, following the same research protocol. The main purpose is to demonstrate efficacy and safety in the short and long term. Evaluations of the efficacy of vaccines must be conducted on the general population, and individuals must be selected from those who will be subject to vaccination in the future (for example, infants in the first year of life). These trials must be conducted under conditions similar to the future routine practice of the intervention. It is essential that they be designed as controlled, double-blind, randomized studies.

Phase IV

Phase IV evaluations are conducted after a pharmaceutical product has been approved, registered and marketed. These trials are carried out primarily to evaluate the occurrence of rare or unknown adverse effects. In public health interventions such as vaccinations, phase-IV studies are used to (i) evaluate alternative operating strategies for administration, (ii) determine the duration of the effect (immunity), (iii) evaluate the effect of the intervention in different epidemiological situations, and (iv) evaluate the epidemiological impact of the intervention on transmission of the disease. Once the product is available on the market, clinical trials designed to explore a new indication, new combinations of drugs or alternative routes of administration must be treated as trials of new pharmaceutical products.

DESIGN OF A CLINICAL TRIAL

Clinical trials comprise by at least two study groups: an intervention group and a control group. In the classical parallel design, the participants are assigned to the two study groups blindly and at random to ensure that the participants are of similar characteristics and that the results are analyzed comparatively and impartially. The control group is given a substance with no pharmacological effect (a placebo) or some other product of known therapeutic or prophylactic effect. This design is called controlled, double-blind, randomized clinical trial. The term “double-blind” refers to the masking – neither the investigators or their staff, nor the volunteers know which of the products under comparison/evaluation has been administered. Other designs for clinical trials such as sequential and cross-over studies may be used in special situations.

SELECTION OF PARTICIPANTS

Eligibility criteria - The criteria for selection of participants must be clearly spelled out in the protocol. In general, the participants represent the group of individuals or population for which the product has been developed and those who could benefit the most from the intervention. Treatment trials include patients selected according to a specified diagnostic criteria. To reduce the number of factors that could hamper the study, modify the effect of the intervention or confound the interpretation of the results, a study is commonly confined to individuals sharing a few general characteristics, for example, age, place of residence, the possibility of presenting for the follow-up examinations, and absence of prior treatment.

In studies for which incident cases must be recruited (for example, vaccine trials) areas of greatest transmission must be chosen, where the number of cases is large enough for the conduct of the study and interpretation of the results. Stable populations (with low migration rates) must be chosen for studies requiring prolonged epidemiological monitoring with successive evaluations.

Criteria for exclusion - These are special characteristics that place individuals in situations of risk if they are included in a clinical trial; such as pregnant mothers, undernourished children, individuals using other drugs with a potential for chemical interaction, and chronic diseases. These criteria must be defined in the protocol and be part of the routine and of the guide for the conduct of the clinical trial.

If severe clinical manifestations are observed during the trial, regardless of the intervention group, the participant must be withdrawn from the study. Medical care must be offered and the case documented and included in the final report.

ASSIGNMENT OF THE INTERVENTION

Two general principles are involved in the assignment of participants to the study groups:

randomization and masking (blinding).

Randomization

Randomization is the process of assigning patients or healthy volunteers at random to the different interventions under comparison. The objective is to ensure a balanced distribution of participants among the comparison groups by reducing or eliminating any bias of allocation and any bias in evaluation of the effects of an intervention. The unit of randomization may the individual or group of individuals during recruitment (using for example, treatment codes in sealed envelopes); or in the intervention itself (with suitable coding of pill bottles and syringes), with the participants assigned in sequence.

Block randomization (for example, at every 10 participants) is used to assure proper balance when the number of participants in a study is small. Randomization can also be stratified, for example, by place of recruitment when there is interest in conducting analyses for each place of recruitment, or when there are reasons for examining a different response in connection with the place of treatment or recruitment.

In population-based trials it is recommended that a list of volunteers who meet the criteria for inclusion be drawn up and the individuals be assigned identification numbers at random. This procedure has the advantage of allowing the randomization process to be repeated several times until a balance is achieved among the critical variables to be used to evaluate the effect of the intervention between the two groups, for example: age, distance from the health facility, etc.

Masking (Blinding)

Masking is needed in a clinical trial to avoid observation bias during the clinical-laboratory follow-up and to preserve complete impartiality in the evaluation of effects. To ensure perfect masking there must be complete separation between the investigators who apply the intervention (a drug or vaccine) and those conducting the clinical follow-up. The products used in the intervention and control groups must, as far as possible, resemble each other in color, size, shape and taste, and have identical dosage schedules (numbers of pills, frequency) to make it impossible to identify differences among the individuals receiving one drug or another. A specific coding system using letters or numbers must be devised and be kept in the custody of the clinical monitor or monitoring committee.

STANDARD OPERATING PROCEDURES (SOPs)

Precise written instructions for all clinical, laboratory and management procedure should be available. This would include selection, enrollment, assignment to study groups, administration of the intervention, records, criteria for interrupting the intervention, etc. All the activities to be carried on must be pre-established in the form of a checklist of tasks assigned to the research staff. This guide will allow external monitors to supervise the quality of the study and its compliance with the protocol.

SAMPLE SIZE

In conventional clinical trials, in which the effects of two drugs/vaccines are compared in parallel, the data analysis is based on a comparison of two proportions/rate of cure/protection: the intervention group vs. the control group. The sample size calculation will be based on:

(1)Minimum value of the difference to be detected between the groups

(2)Ratio of the number of participants in one group to the second group

(3)Level of significance, generally specified at = 5%

(4)Power of the test (1-), generally specified at 1 - = 90%

For example, to evaluate the efficacy of the combination atovaquone and proguanil for the treatment of malaria (in comparison with amodiaquine) a sample size was calculated in order to estimated a difference between a possible 90% negative parasitaemia in the experimental group vs. 65% in the amodiaquine group at day 28. A total of 65 patients in each group would be needed for the study. The information was entered in EPIINFO (Epinfo- Epitable-sample two-proportions option) as follow:

(1)Ratio of the number of participants = 1

(2)Proportion of cure expected in group 2 = 90%

(3)Proportion of cure expected in group 1 = 65%

(4)Value = 5%

(5)Power of test = 90%

Total number of participants in each group = 65

This calculation, however, can become more complicated when other factors have to be adjusted for, such as an unequal number of participants in the two groups, stratified analyses based on patient subgroups, interest in making an interim analysis before the study is finished. More complicated designs and comparisons of multiple effects entail special calculations.

For vaccine evaluation studies in which rates of incidence are compared on the basis of person-exposure time, calculation of the sample size is similar to that in cohort studies (see Epinfo 6-Epitable-Sample cohort option).

For more elaborate estimations, such as those needed to calculate samples with a view to a specified precision or to pre-establish the power to detect a difference, we suggest consulting Smith & Morrow, 1996. In this stage of designing a project it is important to have the advice of a statistician to analyze the sample size requirements for the data analysis proposed.

DOCUMENTATION

A well-organized clinical trial, and especially one in which documentation is prepared for the registration of drugs, must have a set of documents and registration system that allow thorough analysis of the quality of the study.

Information on the product - This is usually supplied by the producing laboratory; must include a description of the product, the features of the production process, quality assurance, and the results of preclinical studies and of studies in progress.

Protocol of the study - A detailed description of the basis, design, conduct and plan of analysis of the study.

Operating manual - A detailed description of all procedures used in the clinical trial.

Records of the monitor - Forms for observation/supervision of initial visits/feasibility, of commencement, periodic visiting monitoring, and completion of the study.

Case-record form - The individual record of each participant (clinical history) containing all clinical, laboratory and follow-up data for timely monitoring of the execution of the study.

STATISTICAL ANALYSIS

The analytical procedures of a clinical trial are determined by the nature of the trial, the parameters estimated, and the effects measured. The plan of analysis must be part of the protocol. This plan must identify the primary and secondary endpoints to be evaluated and how they are to be compared. The criteria for definition of the analytical variables, confounders and subgroups for analysis must be based on scientific logic. Establishing the plan of analysis in advance avoids an exploratory statistical analysis with multiple comparisons, which ultimately leads to a significant difference with no scientific foundation.

The final report of the study must be confined to the comparisons proposed in the pre-established plan of analysis. Thorough manipulation of the data to find comparisons/differences that the study was not designed for will detract from the credibility of the final result.

Comparability of study groups - As a general rule, data analysis must first determine the comparability (resulting from randomization) of the groups in the study relative to the characteristics that may be associated with response to the treatment or risk of infection. In treatment studies these characteristics are usually age, sex, time of disease and severity of the clinical picture, etc. Vaccine evaluations may also include the evaluation of antibody levels before vaccination, place of residence, socioeconomic conditions, etc.

Comparison of proportions - The comparison of proportions is done with the chi-square test, and a 95% confidence interval is estimated for the difference found between treatments. This interval indicates that the true difference or additional benefit of the intervention would lie, for the number of participants in the study, within those calculated limits. The net efficacy of a therapeutic intervention is calculated by the formula:

Efficacy =

% failure in placebo group – % failure in intervention group

% failure in placebo group

Example: The table below shows the result of a clinical trial enrolling 50 patients in each one of the groups. The experimental treatment was successful in 45/50 (90%) and the placebo group showed 13/50 (26%) of spontaneous recovery.

Outcome

Group

Failure

Success

Total

Experimental

5

45

50

Placebo

37

13

50

Total

42

58

100

EF= [(37/50) - (5/50)] / (37/50) = 86.5%

The same result can also be obtained by the formula:

Efficacy = 1 - RR

where:

Relative risk (RR) = 0.14

Efficacy = 1 - 0.14 = 86.5% (68.5% - 94.2%)

Person-time of follow-up - In studies that involve the observation of groups of participants for long period of time, comparison should be made based on the density of incidence, which uses person-time of follow-up as denominator to estimate rates. There are several statistical methods that can be used for this analysis. The construction of life tables with an estimate of the log-rank test compares the times of occurrence of the events of interest to the study. Survival curves are used to analyze the pace of occurrence of events. The relative risk and confidence limits comparing rates of incidence or of cure can be calculated by multivariate logistic regression (Poisson regression), with which therapeutic or preventive efficacy can be calculated.

“Interim” analysis - Interim or intermediate data analysis are recommended for studies of long duration in which a pre-established level of efficacy or disease enhancement/susceptibility can be tested before the follow-up of the study is completed. The analysis should be conducted by independent statistician and results communicated to a data safety and monitoring committee. For example, an interim analysis in a 2-year vaccine evaluation could ascertain whether there is significant evidence for protection or increased susceptibility to infection at the end of the first year of follow-up. In either situation (protection or increase of susceptibility) the study should be interrupted for ethical reasons.

Intention-to-treat - A more rigorous data analysis is the one termed intention-to-treat, which includes all the individuals who began the clinical trial regardless of whether they have completed the intervention and period of follow-up. All cases that were withdrawn from the study because of side effects and those who were unable to complete the evaluation follow-up are taken as therapeutic failures in the analysis.

For example, the table that follows presents the results of a study comparing the efficacy of the combination artemisine/mefloquine with mefloquine alone in the treatment of falciparum malaria. The efficacy, including only the participants who completed the follow-up, was estimated at 71.1%.

Patients

Treatment

Failure

Cure

Losses

evaluated

enrolled

Artemisine +

mefloquine

26

194

20

220

240

Mefloquine

94

136

10

230

240

Total

120

330

30

450

480

Efficacy based on

patients who completed

the follow-up

=

(94/230) - (26/220)

=

71.1% (95% CI 57.2 - 80.5)

(94/230)

The analysis on intention-to-treat, counting all follow-up losses as therapeutic failures (next table), would yield a more conservative efficacy:

Treatment

Failure

Cure

Artemisine +

mefloquine

46 (26 + 20)

194/240

Mefloquine

104 (94 + 10)

136/240

Total

150

330/480

Efficacy based on

intention-to-treat

=

(104/240) - (46/240)

=

55.8% (95% CI 40.5 - 67.1)

(104/240)

Although the efficacy rates are different the 95% confidence intervals overlap, indicating no statistically significant difference between estimates by one or other

DATA SAFETY AND MONITORING COMMITTEE

Data Safety and Monitoring Committee are required by some institutions or regulatory agencies to supervise all stages of the clinical trial and its compliance with the protocol assuring a scientific and ethical acceptability. The committee must have the authority to terminate the trial in the event of unexpected occurrences that prejudice the satisfactory conclusion of the study or of major risk to participants.

CHECKLIST FOR THE DESIGN OF A CLINICAL TRIAL

(. Clearly frame the question to be answered by the study

. specify the type of intervention (dosage, route), the characteristics of the individuals who will receive it (primary disease), the time and method of follow-up, the variable(s) to be used to evaluate the effect of the intervention, the size of the difference that the study is intended to detect and the statistical power of the study

(. Explain the ethical issues

. describe the procedures for obtaining informed consent

. define at which point individuals in the control group will be treated in the event that the intervention proves effective

. establish rules for deciding on the withdrawal participants and for

interrupting the study

. name the authority to which the protocol will be submitted for ethical approval

(. Spell out the criteria for eligibility and the definition of a case

. demographic characteristics

. laboratory tests, clinical examination

. interpretation and categorization of the parameters to be evaluated

(. Describe the interventions to be applied in the intervention and control groups

. describe products, route of administration, dosage, time of administration

. procedures for evaluating compliance with the protocol

(. Describe the methods for the recruitment of participants and their assignment to the intervention

. source from which the participants will be selected

. assignment of participants to the intervention: simple, stratified and block stratification

. masking: double-blind, triple-blind

(. Describe the methods for measuring the effect of the intervention

. laboratory methods, parameters to be evaluated, interpretation, clinical examination

. adverse effects of the intervention and how they will be evaluated – laboratory tests, clinical examinations, intervals, and interpretation

CHECKLIST FOR THE DESIGN OF A CLINICAL TRIAL

(. Describe the methodology for follow-up of the participants

. strategies to be used to minimize losses from follow-up during the study

. criteria for code-breaking

(. Calculate the sample size

. specify the minimum magnitude of the difference expected to be detected

. define the statistical power the level of statistical significance (alpha)

. make sure that the study is feasible in terms of logistics and the time to recruit participants

. estimate the time of follow-up versus the “endpoint” of the study

(. Describe the stages of analysis of the data

. indicate the parameters (proportions, means), statistical methods and subgroups for evaluation of the basic characteristics of the study groups and the effect of the intervention

. explain the type of analysis to be used – “intention-to-treat,” persons-time, survival analysis, intermediate analysis

ADDITIONAL READING

CLAYTON, D. & HILLS, M. Statistical Models in Epidemiology, New York:Oxford University Press, 1993.

COUNCIL FOR INTERNATIONAL ORGANIZATIONS OF MEDICAL SCIENCES. International ethical guidelines for biomedical research involving human subjects. Geneva, CIOMS, 1993, Annex 1.

HULLEY, S. B. B., THOMAS B. N., WARREN S.B. & CUMMINGS, S.R. Designing Clinical Research: An Epidemiologic Approach. Lippincott Williams & Wilkins 2nd edition, 2000.

MEINERT, C. Clinical trials. New York, Oxford University Press, 1986.

POCOCK, S.J. Clinical trials - a practical approach. A Wiley Medical Publication, 1983.

SMITH, P.G. & MORROW, R.H. A "tool-box" for field trials of intervention against tropical diseases. UNDP/World bank/ WHO Special Programme for research and training in tropical diseases(TDR). Geneva, 1988.

WORLD HEALTH ORGANIZATION - WHO Technical Report Series, No 850. Guidelines for good clinical practice (GCP) for trials on pharmaceutical products. Geneva, 1995, pgs 97-13

EXERCISES

Files:

1. ViewMaltrial

2. ViewBam.

Exercise 1

Efficacy of chloroquine for P. falciparum malaria. A double-blind clinical trial was designed to compare the 2 treatment regimens for P. falciparum with oral chloroquine (of 50 mg/kg and 25 mg/kg). Parasitemia were evaluated daily up to the 7th day and on the 14th, 21st and 30th day. The file Viewmaltrial part of EPIGUIDE.MDB project contains information on 124 participants randomly assigned to both groups. Details on the methodology may be found in Andrade et al., 1992. The analysis compared basic characteristics of the participants at the beginning of the trial, and parasitemia levels on the 7th and 30th days after treatment.

**Before starting the exercise route out the results to a HTML file named “Results MALTRIAL”. ROUTEOUT 'Results MALTRIAL' [Figure 1]

Question 1.How many patients were assigned to each treatment group (50 and 25 mg/kg)?

Note 1:

[open the data file]

READ 'C:\epi_info\EpiGuide.mdb':viewMALTRIAL [Figure 2]

FREQ GROUP [Figure 3]

[Figure 1 – Route Out results]

[Figure 2 – Read (Import) data file]

[Figure 3 – Frequencies command]

Question 2.Compare the baseline characteristics of the two patient groups: (“AGE”), sex (“SEX”), occupations (“OCCUP”), drug administered in the last malaria episodes (“MEDIC”), and parasitemias (“PARD0"). To compare the numbers of malaria episodes in the last 5 years (“XMAL”), create a new variable (“XMALGR”) and stratify participants into groups of 1-3, 4-6 and >=7 episodes. For the time of onset of symptoms (“DAYS”), create a new variable (“DAYSGR”) and group the participants into the classes 1-5, 6-10 and >=11 days. Are two groups similar?

Note 2:

MEANS AGE GROUP TABLES=(-) [Figure 4]

[Compare using percentages]

TABLES SEX GROUP [Figure 5]

TABLES OCCUP GROUP

TABLES MEDIC GROUP

[Compare parasitemias using the geometrical mean of the densities of parasitemia and creating a new variable (“LPARD0”)]

DEFINE LPARD0 [standard] [Figure 6]

ASSIGN LPARD0 = LOG(PARD0)

[parasitemia before the treatment] [Figure 7]

MEANS LPARD0 GROUP TABLES=(-)

[Note the means, standard deviations and size of each group]

For Epitable:

Run EPITABLE to calculate the CI (95%)

Select DESCRIBE, then select MEAN

[Use the noted values]

[Note the calculated CIs]

Press F10 to leave EPITABLE

Return to ANALYSIS

For Open Epi:

Access Open Epi from the Epiguide CD or from www.openepi.com, click on MEAN CI from the Continuous Variables folder located in the command tree. Click on ENTER NEW DATA, type the values for the Open Epi Input Table. Click CALCULATE. Note the calculated CIs. [Figure 8]

Return to ANALYSIS

[To convert the means and 95% CIs obtained in LPARD0 use base 10] [Example: 102.993 (10mean; mean=2.993); 102.89 (10lower limit of 95% CI; lower limit of 95% CI = 2.89); 103.10 (10upper limit of 95% CI; upper limit of CI=3.10)]

DEFINE XMALGR [standard]

RECODE XMAL TO XMALGR

1-3=1

4-6=2

7-20=3

END [Figure 9]

TABLES XMALGR GROUP

DEFINE DAYSGR [standard] [grouping of symptom onset times]

RECODE DAYS TO DAYSGR

1-5=1

6-10=2

11-40=3

END

TABLES DAYSGR GROUP

[Figure 4 – Means command]

[Figure 5 – Tables command]

[Figure 6 – Define New Variable]

[Figure 7 – Assign new values]

[Figure 8 – Open Epi – CI for a sample Mean]

[Figure 9 – Recode command]

Question 3.Using the “intention-to-treat” strategy, calculate the success rate (cure rate) on days 7 and 30 based on parasitemia clearance. Is chloroquine efficacious to treat malaria from P. falciparum in the study area?

Note 3:

[To calculate the success rate by the “intention-to-treat” strategy, assume all losses from follow-up as treatment failure. Create new variables “DAY7R” and “DAY30R”]

DEFINE DAY7R [standard]

[recoding loss from follow-up as positive for parasitemia on day 7]

RECODE DAY7 to DAY7R

1=1

2-3=2

END

TABLES DAY7R GROUP

DEFINE DAY30R [standard]

[recoding loss from follow-up as positive for parasitemia on day 30]

RECODE DAY30 TO DAY30R

1=1

2-3=2

END

TABLES DAY30R GROUP

EXIT [to leave Analysis] [Figure 10]

[Figure 10 EXIT Analysis]

Exercise 2

Randomised vaccine trial of single dose of killed L. major plus BCG against anthroponotic cutaneous leishmaniasis in Bam, Iran. Sharifi et al., 1998

A randomized double-blind controlled trial was conducted in Bam, Iran, to evaluate the safety and protective efficacy of a single dose of an autoclaved-killed L. major promastigotes vaccine (ALM), mixed with BCG against anthroponotic cutaneous leishmaniasis (CL) vs. BCG as control group. A total of 3633 children aged 6 to 15 years old recruited in 49 primary schools were enrolled. The children were examined on days 1, 7, 30 and 80 after vaccination to assess the presence of systemic and local side effects. A leishmanin skin test (LST) was performed on day -80. CL incidence was assessed by passive surveillance and by active follow-up visits in school every two months for a period of 2 years. The file ViewBam part of the EPIGUIDE.MDB project contains records of 3633 participants, the list of the variables and codes is appended.

**Before starting the exercise route out the results to a HTML file named “Results BAM”. ROUTEOUT 'Results BAM'

Question 1.Sample size

The study was designed to detect a 50% reduction in the incidence of CL, at 5% significance level with a power of 80%, assuming an annual incidence of 2%, a dropout rate of 10% and 2 years of follow-up. Was the number of participants enrolled sufficient?

Note 1:[Open the file]

READ 'C:\epi_info\EpiGuide.mdb':viewBAM

Run EPITABLE to calculate the sample size

Select SAMPLE, then SAMPLE SIZE, and TWO PROPORTIONS

Press F10 to leave EPITABLE

Return to ANALYSIS

Question 2.Side Effects

Compare the two groups with regard to side effects at days 7 and 30 after vaccination. Calculate the frequency of redness (RED7 and RED30); ulcer (ULCER7 and ULCER30); lymphadenopathy (LYMPH7 and LYMPH30); itching (ITCH7 and ITCH30); pain (PAIN7 and PAIN30) and induration (INDUR7 and INDUR30). Recode variables as binary: 0=no side effects and 1=side-effects of any grade. Is there any difference in frequency of adverse reactions between the two groups?

Note 2:

[Create new variables to receive the coded values]

DEFINE RED7R [standard]

RECODE RED7 TO RED7R

0=0

1-3=1

END

DEFINE RED30R [standard]

RECODE RED30 TO RED30R

0=0

1-3=1

END

TABLES RED7R GROUP

TABLES RED30R GROUP

DEFINE ULCER7R [standard]

RECODE ULCER7 TO ULCER7R

0=0

1-3=1

END

DEFINE ULCER30R [standard]

RECODE ULCER30 TO ULCER30R

0=0

1-3=1

END

TABLES ULCER7R GROUP

TABLES ULCER30R GROUP

DEFINE LYMPH7R [standard]

RECODE LYMPH7 TO LYMPH7R

0=0

1-3=1

END

DEFINE LYMPH30R [standard]

RECODE LYMPH30 TO LYMPH30R

0=0

1-3=1

END

TABLES LYMPH7R GROUP

TABLES LYMPH30R GROUP

DEFINE ITCH7R [standard]

RECODE ITCH7 TO ITCH7R

0=0

1-3=1

END

DEFINE ITCH30R [standard]

RECODE ITCH30 TO ITCH30R

0=0

1-3=1

END

TABLES ITCH7R GROUP

TABLES ITCH30R GROUP

DEFINE PAIN7R [standard]

RECODE PAIN7 TO PAIN7R

0=0

1-3=1

END

DEFINE PAIN30R [standard]

RECODE PAIN30 TO PAIN30R

0=0

1-3=1

END

TABLES PAIN7R GROUP

TABLES PAIN30R GROUP

DEFINE INDUR7R [standard]

RECODE INDUR7 TO INDUR7R

0=0

1-3=1

END

DEFINE INDUR30R [standard]

RECODE INDUR30 TO INDUR30R

0=0

1-3=1

END

TABLES INDUR7R GROUP

TABLES INDUR30R GROUP

Question 3.Skin test response

Compare LST conversion rates (LST>=5 mm) between the two groups. Recode LST80 as a binary variable (LST80GR); conversion=1, no conversion=2.

Is there any significant difference in skin test response between the two groups?

Note 3:[Create a new variable “LST80GR”]

DEFINE LST80GR [standard]

IF LST80>=5 THEN

ASSIGN LST80GR=1

END [Figure 11]

IF LST80>=0 AND LST80<5 THEN

ASSIGN LST80GR=2

END

TABLES LST80GR GROUP

[Figure 11 – IF command]

1 – Click IF to establish conditions for the new variable

2 – Choose the variable to build the condition

3 – Create the condition(s) to assign the values for the new variable

4 – Click THEN to access the THEN Block

5 – Click ASSIGN

6 – Choose the variable to receive the new values

7 – Choose from the Available variables to construct the expression

8 – Revise the assign expression

9 – Click ADD to return to the IF window

10 – Click OK when finished

Question 4.CL Incidence – Vaccine efficacy

Calculate the 2-year overall cumulative incidence of CL in each group. What was the ALM+BCG vaccine efficacy? Calculate vaccine efficacy stratified by sex. Calculate vaccine efficacy considering only those cases diagnosed after 9 months (270 days) of vaccination.

Note 4:TABLES GROUP LEISH

Run EPITABLE to calculate the vaccine efficacy

Select STUDY, then select VACCINE EFFICAY, and then select COHORT STUDY.

Leave EPITABLE open, click on R[Reset] to clear the data

Return to ANALYSIS

[For stratified analysis by sex]

TABLES GROUP LEISH SEX

Return to EPITABLE to calculate the vaccine efficacy

Press F10 to leave EPITABLE.

Return to return to ANALYSIS

[Note that the variable “DATEINF” has a text format. Before calculating the days (based on dates) you should create another variable “DATEINF2” that will contain the DATEINF value in the proper date format]

DEFINE DATEINF2 [standard]

ASSIGN DATEINF2= TXTTODATE(DATEINF)

[Create a new variable “DAYSVAC”]

DEFINE DAYSVAC [standard]

ASSIGN DAYSVAC = DAYS(VACDATE ,DATEINF2)

Define a new variable “LEISH9M” considering cases only the CL incident cases that occurred after 9 months of vaccination

DEFINE LEISH9M [standard]

IF LEISH=1 AND DAYSVAC >=270 THEN

ASSIGN LEISH9M=1

END

IF LEISH=1 AND DAYSVAC <270 THEN

ASSIGN LEISH9M=2

END

IF LEISH=2 THEN

ASSIGN LEISH9M=2

END

TABLES GROUP LEISH9M

Run EPITABLE to calculate the vaccine efficacy

Select STUDY, then select VACCINE EFFICAY, and then select COHORT STUDY

Press F10 to leave EPITABLE

Return to ANALYSIS

EXIT [to leave ANALYSIS]

REFERENCES

ANDRADE, J.G., ANDRADE, A.L.S.S., ARAUJO, E.S.O., OLIVEIRA, R.M., SILVA, S.A., MARTELLI, C.M.T. & ZICKER, F. A randomized clinical trial with high dose of chloroquine for treatment of Plasmodium falciparum malaria in Brazil. Revista do Instituto de Medicina Tropical de São Paulo,34(5):467-473, 1992.

SHARIFI I., FEKRI A.R., AFLATONIAN M., KHAMESIPUOUR A, NADIM A. MOUSAVI M.A., MOMENI A.Z., DOWLATI Y., GODAL T., ZICKER F. & SMITH P.G. Randomised vaccine trial of single dose killed Leishmania major plus BCG against anthroponotic cutaneous leishmaniasis in Bam, Iran. The Lancet, 351:1540-1543, 1998.

For Analysis:

DEAN AG, ARNER TG, SUNKI GG, FRIEDMAN R, LANTINGA M, SANGAM S, ZUBIETA JC,  SULLIVAN KM, BRENDEL KA, GAO Z, FONTAINE N, SHU M, FULLER G.  Epi Info™ a database and statistics program for public health professionals.  Centers for Disease Control and Prevention, Atlanta, Georgia, USA, 2002. http://www.cdc.gov/epiinfo/downloads.htm

DEAN A.G., DEAN J.A., COULOMBIER D. et al.  Epi Info™, Version 6.04, a word processing, database, and statistics program for public health on IBM-compatible microcomputers.  http://www.cdc.gov/epiinfo/Epi6/ei6.htm

DEAN, A., SULLIVAN, K, & SOE, M.M. OpenEpi - Open Source Epidemiologic Statistics for Public Health. http://www.openepi.com

DATA FILE DICTIONARY

Project: EPIGUIDE.MDB

File: ViewMaltrial

Variable

Description

Code

Description of code

ID

Identification number

GROUP

Treatment group

1

2

50 mg/kg

25 mg/kg

AGE

Age in completed years

15 to 62

SEX

Sex

1

2

Male

Female

OCCUP

Occupation

1

2

3

4

5

Miner

Fisherman

Laborer

Commerce

Other

XMAL

Number of malaria episodes in last 5 years

1 - 20

MEDIC

Medication taken in latest malaria episode

1

2

3

4

Chloroquine

Quinine

More than one drug

Other

DAYS

Days since onset of symptoms

1 to 40

DAY7

Parasitemia on day 7 of follow-up

1

2

3

No parasitemia

Parasitemia

Loss from follow-up

DAY30

Parasitemia on day 30 of follow-up

1

2

3

No parasitemia

Parasitemia

Loss from follow-up

PARD0

Parasitemia levels before treatment

10 to 37,800

trophozoites / field

Project: EPIGUIDE.MDB

File: ViewBam

Variable

Description

Code

Description of code

NUMBER

Identification number of the participants

SEX

Sex

F

M

Female

Male

RESPPD

PPD reactivity

0-10.0

VACDATE

Date of vaccination

RED7

Redness at day 7

0

1

2

3

Absence

Mild

Moderate

Severe

ULCER7

Ulcer at day 7

0

1

2

3

Absence

Mild

Moderate

Severe

LYMPH7

Lymphadenopathy at day 7

0

1

Absence

Mild

ITCH7

Itching at day 7

0

1

2

3

Absence

Mild

Moderate

Severe

PAIN7

Local pain at day 7

0

1

2

3

Absence

Mild

Moderate

Severe

INDUR7

Induration at day 7

0

1

2

3

Absence

Mild

Moderate

Severe

RED30

Redness at day 30

0

1

2

3

Absence

Mild

Moderate

Severe

ULCER30

Ulcer at day 30

0

1

2

3

Absence

Mild

Moderate

Severe

LYMPH30

Lymphadenopathy at day 30

0

1

2

3

Absence

Mild

Moderate

Severe

ITCH30

Itching at day 30

0

1

2

3

Absence

Mild

Moderate

Severe

PAIN30

Local pain at day 30

0

1

2

Absence

Mild

Moderate

INDUR30

Induration at day 30

0

1

2

3

Absence

Mild

Moderate

Severe

LST80

Leishmanin skin test at day 80

0.0-15.0

DATEINF

Date of the appearance of first lesion

LEISH

Case identification

1

2

Yes

No

GROUP

Vaccine allocation group

1

2

ALM+BCG

BCG

1- Click on RouteOut

2- Define the folder to save the HTM file

4- Mark this box if you want to replace an existing file

3- Write the file name

1- Click on Read from the Analysis Commands tree

TRIALS

2 – Change to the desired project:

EPIGUIDE.MDB

3 – Identify the data file you will use

in the exercise

4 – Click Ok

1- Click Frequencies

2 – Choose the variable(s)

3 - Click OK when finished

5 – Uncheck the Show Tables in Output box

4- Click Settings

3- Choose the variable to use for comparison

2- Choose the variable to apply the means command

1- Click Means

2- Choose the

Exposure Variable

4 – Click Ok

3- Choose the

Outcome variable

1- Click on Tables

2 – Type the new variable name

1- Click Define to create a new variable

5 – Click OK

1 – Click Assign

4 - Revise the Assign Expression

3 - Choose from the Available Variables to construct the expression

2 - Choose the variable to receive the new values

4 – Click Calculate

3 – type the values to calculate the CI

2- Click Enter New Data

1 – Click Mean CI

6 – Type the new values. Press enter to go to the next line

2 – Click Recode

7 – Click OK

1 – Define the new variable

5 – Type old values or range of values

4 – Choose destination variable (new)

3 - Choose source variable

Click EXIT to close Analysis

10

9

8

7

6

5

1

4

3

2

PAGE