clinical trials n.
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  2. Clinical trials A properly planned experiment and executed clinical trial is a powerful experimental technique for assessing the effectiveness of an intervention. Friedman, Furer and Demets

  3. Definition • The term clinical means “bedside”. It may be applied to any form of planned experiment, which involves patients and is designed to elucidate the most appropriate treatment for future patients, with a given medical condition. • A clinical trial must employ one or more intervention techniques and these may be prophylactic, diagnostic or therapeutics agents, devices, regimens, procedures etc. • A clinical trial must contain a control group against which the intervention is compared. At baseline, the control group must be similar in relevant respects to the intervention group so that differences in the outcome may reasonably be attributed to action of intervention.

  4. Why are clinical trials needed? • Evaluation of safety and efficacy of therapies, for which the results need to be: • Non-subjective • Scientifically valid Opportunity to screen new drugs in a drug development program Carefully designed trials are the only means to detect the usually small differences between drugs or methods of treatment or the advantages of one over another.

  5. Types of trials • Therapeutic trials measure the efficacy of drugs or other therapeutic procedures (for example: diet, bed-rest, surgery, physiotherapy and ionizing radiation). • Preventive trial measure the effect of preventive measures on the health of populations (for example, control of pollution of water supplies, immunizations, change of diet, change of smoking habits, fortification of foodstuffs, weight reduction, contraception).

  6. Phases of drug trials • Phase I trials: clinical pharmacology and toxicity These first experiments in man are primarily concerned with drug safety, not efficacy and usually performed on human volunteers. Phase I involves studies of: Acceptable single drug dosage Drug metabolism Bioavailability • Phase II trials: initial clinical investigation for treatment effect These are small-scale investigation into the efficacy and safety of a drug and require close monitoring of each patient. Seldom phase II trials go beyond 100-200 patients on drug.

  7. Phase III trials: full scale evaluation of treatment. This is done to compare the drug with the current standard treatment(s) for the same condition in a large trial involving substantial number of patient. • Phase IV trials: post-marketing surveillance After drug being approved for marketing, research to be undertaken as regards monitoring for adverse effects and additional large scale, long term studies of morbidity and mortality.

  8. Fundamental aspects of trial design a) Which patients are eligible? b) Which treatments are to be evaluated? c) How each patient’s response is to be assessed?

  9. Questions • Each clinical trial must have a primary question. The primary question as well as any secondary or subsidiary question, should be carefully selected, clearly defined and stated in advance.

  10. Primary question • Should be one the investigators are interested in answering • It is the one on which sample size of study is based and that must be emphasized in the reporting of trials results. • May be framed in the form of testing of hypothesis.

  11. Secondary question • Variety of subsidiary or secondary question related to primary question can be studies. • They can be of two types: 1. the response variable is different from that in primary question (eg: Primary question: Mortality from any cause is altered by the intervention) Secondary question might relate to cause specific death rates) 2. Second type of secondary question relates to sub-group hypothesis (for e.g.: the investigator may want to …… specifically at people by stage of disease at entry)

  12. Subgroup hypothesis should be • Specified before data collection begins • Based on reasonable expectations • Limited in number

  13. Study population • Definition The study population is the subset of the population with the condition or characteristic of interest defined by the eligibility criteria. Fundamental point The study population should be defined in advance stating unambiguous inclusion (eligibility) criteria. These criteria will have an impact on study design, ability to generalize and participant recruitment.

  14. Selection of study group This can be done in the following two ways: 1. Accural: in which the subjects needed for the trial is recruited during the course, of study. 2. Non accural: in which the subjects needed are recruited before the study begins.

  15. Reasons for specifying the study population 1. If an intervention is shown to be successful or unsuccessful, the medical and scientific communities must know what kinds of people the finding apply. 2. Knowledge of study population helps other investigators to assess the study’s merit and appropriateness. 3. In order for other investigators to be able to replicate the study, they need data descriptive of the participants enrolled.

  16. Controls • A control group is used to compare the history of exposure in the case with that in individuals who are free of the exposure. The control series is intended to provide an estimate of the disease rate that would be expected to occur in cases if there were no association between the study disease and exposure. • Individuals selected as controls should not be free of study disease/exposure but should also be similar to the cases in regard to the past potential for exposure/disease during the time period of risk under consideration.

  17. Source of controls • Controls may be selected either from hospitals or from the community. • If cases are chosen from the hospitals or groups of hospitals, considerations of practicality and cost confine the selection of controls to persons admitted to the same hospitals but with a disease or condition different from that under study, such persons are called Hospital controls.

  18. Eligibility criteria Definition • Eligibility criteria relate to participant safety and anticipated effect of intervention. Outline of eligibility criteria to be framed are: Participants who have the potential to benefit from the intervention are obviously candidates for enrollment into the study. In selecting participants to be studied, not only does the investigator requires people in whom the intervention might be worth, he also wants to choose people In whom there is a high likelihood that he can detect the hypothesized results of the intervention.

  19. Eligibility criteria • When deciding on these criteria, using excessive restrictions in all effort to obtain a pure (or homogenous) sample can lead to extreme difficulty in getting sufficient participants. • Capacity to recruit participants and carry out trial effectively could greatly depend on the eligibility criteria that are set.

  20. Response variable • A single response variable should be identified to answer the primary question. • If more than one are used, the probability of getting nominally significant result by chance alone is increased. If several response variables give inconsistent results, interpretation becomes difficult.

  21. Response variable • Combining events to make up a response variable might be useful if any one event occurs infrequently for the investigator reasonably to expect a significant difference without using a large number of participants.

  22. Response variable • Investigators should define and write the question in advance as specific as possible. • The primary response variable must be capable of being assessed in all participants. Selecting one response variable must be capable of being assessed in all participants. Selecting one response variable to answer the primary question from some participant and another variable to answer the same question from other participant is not a legitimate practice. • Unless there is a combination of primary response variable in which the participant remains at risk of having additional events, participation generally ends when primary response variable occurs. • Response variable should be capable of unbiased assessment. Truly, double blind studies have a distinct advantage over other studies in this regard. • It is important to have response variable that can be ascertained as completely as possible. In long terms participants may fail to return for follow-up. If response variable is based on return to follow-up, then information may be lost.

  23. Bias • Bias is a distortion in the perception of the effects of a treatment or in the measurement of differences between the effects of two treatments.

  24. Source of bias • Systematic differences between treatment groups at admission into the trial. Example: Suppose treatments A and B are assigned to two groups of children with leukemia. Patients receiving A are two to six years old and parents receiving B are either younger or older. It has been shown by several investigations that “middle” age children have a better prognosis than others. If results of the trial show a significant difference between groups A and B, there is no way to find out whether the difference is due to treatment alone, age alone or a combined effect of treatment and age.

  25. Methods of reducing bias • Randomization • Blinding • Uniform handling of procedures

  26. Need for randomization Three possibilities of why the observed difference between the two groups is not due to chance: • The two groups differ appreciably in factors related to their prognosis. • The two groups have been handled and looked after in different ways. • The particular therapy being examined has a beneficial effect. Randomization is the best method to ensure that the groups are similar in all respects except for the intervention given.

  27. Source of bias • Differential assessment of outcome in treatment groups • Example: The patients in the treatment group might be showed more interests than those in the control group receiving a placebo. • Differential exclusion or withdrawal of subjects from the study • Example: elimination of patients who were judged ineligible after enrollment by personnel who were aware of treatment assignment and course of treatment.

  28. Randomization • Randomization is a process by which all participants are equally assigned to either the intervention or control group.

  29. Advantages of randomization • Ensures that the physician running the trial is not consciously or unconsciously allocating certain patients to a particular group. • Produces comparable groups – Measured and the unknown prognostic factors will be on an average evenly balanced between the two groups. • Validity of statistical tests of significance are guaranteed.

  30. Masking (Blinding) • The knowledge of whether the participant was in treatment or control group can influence the study, resulting in biased inferences either consciously or subconsciously. • To remove this source of bias in observation, three procedures have been evolved: 1. Single blind 2. Double blind 3. Triple blind 4. Quadruple blinding (planner, patient, investigator, outcome analyzer)

  31. Single blinding/Masking • The participants are not given any indication whether they are in experimental or control group. The objective of single blinding is to prevent participant from introducing bias into the observations, and is usually accomplished by means of a placebo.

  32. Double blinding • Double blinding seeks to remove biases that occur as a result of either subject or the observer of the subject being influenced by knowledge that the subject is in control or experimental group.

  33. Triple blinding • Triple blinding studies carry the concept of blinding the subject, observer of the subject and the person analyzing the data are all blind with regard to the group to which a specific individual belongs.

  34. Protocol framework • Plan of clinical trial should be stated in a protocol that contains objective and specific procedures before start of a trial.

  35. Study protocol • A: Background of study • B: Objectives Primary question and response variable Secondary question and response variable Subgroup hypothesis Adverse effect

  36. C: Design of the study 1. Study population a. Inclusion criteria b. Exclusion criteria 2. Enrollment of participants a. Informed consent b. Assessment of eligibility c. Baseline examination d. Intervention allocation (e.g.: randomization method)

  37. 4. Intervention • Description and schedule • Measure of compliance 5. Follow-up visit description and schedule 6. Ascertainment of response variable a. training b. data collection c. Quality control 7. Data analysis • Interim analysis • Final analysis 8. Termination policy

  38. D. Organization 1. Participating investigators a. Statistical unit or data coordinating center b. Lab and other special units c. Clinical center(s) 2. Study administration • Steering committees and sub-committee • Data monitoring committee • Fund organization

  39. Adverse effect • Most interventions are likely to have adverse effects. The investigators needs to weigh these effects against possible benefit when he evaluates the feasibility of the study. However, any participant for whom the intervention is known to be harmful should not be admitted to the trial.

  40. Problems in timing of clinical trials • Trials need to be feasible: feasibility includes knowledge, tools, knowledge on safety of intervention, outcomes to be assessed. • Relative stability of intervention: If the intended intervention becomes outmoded in short duration, studying such intervention may be inappropriate. (In such case the best approach is to postpone the trial until a procedure has reached a plateau and is unlikely to change).

  41. Ethics of clinical trial • Safety of the drugs or methods of treatment • The existence of an honest hypothesis • Informed consent of the participants • The right of participants to withdraw from the study at any time without sanctions • Confidentiality of information • The use of finders fee i.e. payment to physician for referring participants to a clinical trial investigator is inappropriate in that it might lead to undue pressure on a prospective participant. • Randomization is a problem for physicians to randomly assign a therapy if the investigator believes that a preferred therapy exists. • Use of a placebo is acceptable if there is no known best therapy and in other special circumstances.

  42. Basic Study Designs • Randomized • Non randomized concurrent • Historical • Cross-over • Withdrawal studies • Factorial • Group allocation

  43. Randomized Control Studies • Studies that compare an intervention and a control group. • Assignment is based on randomization • Removes the potential bias in the allocation of participants to the groups. • Produces comparable groups i.e. the measured and unknown prognostic factors and other characteristics of the participants at the time of randomization will be on the average evenly balanced between the two groups. • Validity of statistical tests is guaranteed.

  44. Non randomized concurrent control studies • Controls are obtained at approximately the same time as the intervention group Historical control studies Compares a group of participants on a standard therapy. Source of historical data: Data available from literature Obtained from medical charts Bias involved in historical controls: Shift in diagnosis for a given disease because of improved technology can cause major changes in the recorded frequency of the disease and in the perceived prognosis of subjects with the disease. Concern on the accuracy and completeness with which control group data are collected.

  45. Cross over design • A special case of randomized control design in which each patient serves as his own control. • Avoids between participant variation in estimating the intervention effect. • Requires a small sample size. • Assumption: • The effects of intervention during the first period does not carry over into the second period.

  46. Withdrawal studies • Studies in which the participant on a particular treatment for a chronic disease are taken off therapy or have the dosage reduced. • Objective: Assess response to the discontinuation or reduction. • Used to validate the duration of benefit of intervention already known to be useful. • Limitations: • Highly selected sample – only participants who benefit from the study are likely to be on the study. • Overestimates benefit and under estimate toxicity. • Both disease and patients states change over time.

  47. Randomized Controlled trial • The purpose of RCT is to evaluate the effectiveness of some intervention. • To evaluate a new therapy, requires comparing its results on a group of treated patients with the results on a group with the same disease not so treated. These two groups are usually called the treatment and control groups respectively.

  48. Types of Trials • Clinical or therapeutic trial • The study group consists of persons with a particular disease or condition and the treatment is therapeutic. • Purpose: to determine if treatment can effect a ‘cure’ or remove manifestations of a disease already present in the patients. Primary preventive trial the treatment under investigation is prophylactic in that its purpose is the prevention of a particular manifestation of disease which is not present at the start of the trial. Secondary prevention trial in such trials the subjects already have the disease in question, or have suffered one event, and it is hoped to prevent or delay recurrences or death.

  49. Factorial Designs • Attempts to evaluate two interventions with a control in a single experiment • Incomplete factorial designs – when it is inappropriate, infeasible or unethical to address every possible treatment combination

  50. Merits of factorial design • A very essential design when there are two or more interventions • Allow effects of one intervention to be estimated at all the levels of the other intervention Demerits of factorial design • The basic concern in a factorial design is the existence of possible interaction and its impact on the sample size • When there are two separate outcomes, (eg: heart disease and cancer) but one of the interventions have effect on both, then data monitoring becomes complicated or sometimes impossible