Type III censoring occurs when the censoring is random, which is the case in clinical trials because of staggered entry not every patient enters the study on the first day and unequal follow-up on subjects. Statistical methods appropriate for event time data, survival analyses, do not discard the right-censored observations.
Instead, the methods account for the knowledge that the event did not occur in a subject up to the censoring time. Survival methods include life table analysis, Kaplan-Meier survival curves, logrank and Wilcoxon tests, and proportional hazards regression more discussion on these in a later lesson. In order to conduct event-time analyses, two measurements must be recorded, namely, the follow-up time for a subject and an indicator variable as to whether this is an event time or a censoring time.
These statistical methods assume that the censoring mechanisms and the event are independent. If this is not the case, e. When the event of interest is death, it is common to examine two different endpoints, namely, death from all causes and death primarily due to the disease.
At first glance, death primarily due to the disease appears to be the most appropriate. It is, however, susceptible to bias because the assumption of independent causes of death may not be valid. For example, subjects with a life-threatening cancer are prone to death due to myocardial infarction. It can also be very difficult to determine the exact cause of death. A surrogate endpoint is one that is measured in place of the biologically definitive or clinically meaningful endpoint.
A surrogate endpoint usually tracks the progress or extent of the disease. Investigators choose a surrogate endpoint when the definitive endpoint is inaccessible due to cost, time, or difficulty of measurement.
The problem with a surrogate endpoint in a clinical trial is determining whether it is valid i. Examples of surrogate endpoints include CD4 counts in AIDS patients, tumor size reduction in cancer patients, blood pressure in cardiovascular disease, and intraocular pressure in glaucoma patients. The response variables in translational research are surrogate endpoints.
Surrogate endpoints can potentially shorten and increase the efficiency of clinical trials. If, however, the surrogate is imprecisely associated with definitive endpoints, the use of the surrogate can lead to misleading results.
In order to determine the dose with the highest potential for efficacy in the patient population that still meets safety criteria, dose-finding studies are typically conducted by administering sequentially rising doses to successive groups of individuals. Such studies may be conducted in healthy volunteers or in patients with the disease.
A question the investigator must answer in designing a dose-finding study is how to characterize an optimum dose. Should the optimum dose be selected on the basis of the highest therapeutic index the maximal separation between risk and benefit? Or is the optimal dose the level that maximizes therapeutic benefit while maintaining risk below a predetermined threshold? What measures will denote risk and benefit? In another case, the optimal dose might be selected as the highest dose that is associated with serious side effects in no more than 1 of 20 patients.
This would be a maximum nontoxic dose MND. This is a maximum tolerated dose MTD. Care in defining the conditions for optimality is critical to a dose-finding study. Most DF trials are sequential studies such that the number of subjects is itself an outcome of the trial. Convincing evidence characterizing the relationship between dose and safety can be obtained after studying a small set of patients.
Hence sample size is not a major concern DF trials. When blinding is implemented in a clinical trial, a plan for assessing the effectiveness of the blinding may be arranged. This usually requires two blinding questionnaires, one completed by the trial participant and the other completed by the local investigator or person that conducts the evaluation of the trial participant.
Reviews of blinded trials suggest that many trials experience issues that jeopardize the blind. For example in a study assessing zinc for the treatment of the common cold Prasad et al the blinding failed because the taste and aftertaste of zinc was distinctive. Creative designs can be utilized to help maintain the blind. GV has staining potential which could jeopardize the blind when the assessors conduct oral examinations after treatment.
A staining cough drop could be given to study participants prior to evaluation to help maintain the blind. Unplanned unblinding should only be undertaken to protect participant safety i. Blinding has been poorly reported in the literature. Researchers should explicitly state whether a study was blinded, who was blinded, how blinding was achieved, the reasons for any unplanned unblinding, and state the results of an evaluation of the success of the blinding. A placebo can be defined as an inert pill, injection, or other sham intervention that masks as an active intervention in an effort to maintain blinding of treatment assignment.
One disadvantage to the use of placebos is that sometimes they can be costly to obtain. Although the placebo pill or injection has no activity for the disease being treated, it can provide impressive treatment effects. This is especially true when the endpoint is subjective e.
Evans et. Evans et al reported a significant improvement in pain in the placebo arm of a trial investigating an intervention for the treatment of painful HIV-associated peripheral neuropathy. There can be many logistic and ethical concerns in clinical trials where neither a placebo, nor a sham control can be applied. The inability to use placebos is common in the development of devices.
The selection of a control group is a critical decision in clinical trial design. The control group provides data about what would have happened to participants if they were not treated or had received a different intervention. Without a control group, researchers would be unable to discriminate the effects caused by the investigational intervention from effects due to the natural history of the disease, patient or clinician expectations, or the effects of other interventions.
The selection of a control group depends on the research question of interest. If it is desirable to show any effect, then placebo-controls are the most credible and should be considered as a first option. However placebo controls may not be ethical in some cases and thus active controls may be utilized. If it is desirable to show noninferiority or superiority to other active interventions then active controls may be utilized.
Historical controls are obtained from studies that have already been conducted and are often published in the medical literature. The data for such controls is external to the trial being designed and will be compared with data collected in the trial being designed. The advantage of using historical controls is that the current trial will require fewer participants and thus use of historical controls provides an attractive option from a cost and efficiency perspective.
The drawback of trials that utilize historical controls is that they are non-randomized studies i. Historical controls are rarely used in clinical trials for drug development due to the concerns for bias. However, when historical data are very reliable, well documented and other disease and treatment conditions have not changed since the historical trial was conducted, then they can be considered.
Historical controls have become common in device trials when placebo-controls are not a viable option. Historical controls can be helpful in interpreting the results from trials for which placebo controls are not ethical e. An active control is an active intervention that has often shown effectiveness to treat the disease under study. Often an active control is selected because it is the standard of care SOC treatment for the disease under study.
Active controls are selected for use in noninferiority trials. Active controls and placebo controls can be used simultaneously and provide useful data. For example, if the new intervention was unable to show superiority to placebo, but an active control group was able to demonstrate superiority to placebo, then this may be evidence that the new intervention is not effective.
However, if the active control with established efficacy did not demonstrate superiority to placebo, then it is possible the trial was flawed or may have been underpowered because of the placebo response or variability being unexpected high. In selecting a population to enroll into a trial, researchers must consider the target use of the intervention since it will be desirable to generalize the results of the trial to the target population. However researchers also select entry criteria to help ensure a high quality trial and to address the specific objectives of the trial.
The selection of a population can depend on the trial phase since different phases have different objectives. Early phase trials tend to select populations that are more homogenous since it is easier to reduce response variation and thus isolate effects. Later phase trials tend to target more heterogeneous populations since it is desirable to have the results of such trials to be generalizable to the population in which the intervention will be utilized in practice.
It is often desirable for this targeted patient population to be as large as possible to maximize the impact of the intervention. Thus phase III trials tend to have more relaxed entry criteria that are representative both in demographics and underlying disease status to the patient population for which the intervention is targeted to treat.
When constructing entry criteria, the safety of the study participant is paramount. Researcher should consider the appropriateness of recruiting participants with various conditions into the trial. The ability to accrue study participants can also affect the selection of entry criteria. Although strict entry criteria may be scientifically desirable in some cases, studies with strict entry criteria may be difficult to accrue particularly when the disease is rare or alternative interventions or trials are available.
Entry criteria may need to be relaxed so that enrollment can be completed within a reasonable time frame. Researchers should also consider restricting entry criteria to reduce variation and potential for bias. Participants that enroll with confounding indications that could influence treatment outcome could be excluded to reduce potential bias. For example, in a trial evaluating interventions for HIV-associated painful neuropathy, conditions that may confound an evaluation of neuropathy such as diabetes or a B12 deficiency may be considered exclusionary.
The selection of endpoints in a clinical trial is extremely important and requires a marriage of clinical relevance with statistical reasoning. The motivation for every clinical trial begins with a scientific question. The primary objective of the trial is to address the scientific question by collecting appropriate data. The selection of the primary endpoint is made to address the primary objective of the trial. The primary end-point should be clinically relevant, interpretable, sensitive to the effects of intervention, practical and affordable to measure, and ideally can be measured in an unbiased manner.
Endpoints can generally be categorized by their scale of measurement. The three most common types of endpoints in clinical trials are continuous endpoints e. The scale of the primary endpoint impacts the analyses, trial power, and thus costs. In many situations, more than one efficacy endpoints are used to address the primary objective.
This creates a multiplicity issue since multiple tests will be conducted. Decisions regarding how the statistical error rates e. Endpoints can be classified as being objective or subjective. Objective endpoints are those that can be measured without prejudice or favor. Death is an objective endpoint in trials of stroke. Subjective endpoints are more susceptible to individual interpretation. For example, neuropathy trials employ pain as a subjective endpoint.
Other examples of subjective endpoints include depression, anxiety, or sleep quality. Objective endpoints are generally preferred to subjective endpoints since they are less subject to bias. An intervention can have effects on several important endpoints. Composite endpoints combine a number of endpoints into a single measure. The advantages of composite endpoints are that they may result in a more completed characterization of intervention effects as there may be interest in a variety of outcomes.
Composite endpoints may also result in higher power and resulting smaller sample sizes in event-driven trials since more events will be observed assuming that the effect size is unchanged. Composite endpoints may also reduce the bias due to competing risks and informative censoring.
This is because one event can censor other events and if data were only analyzed on a single component then informative censoring can occur. Composite endpoints may also help avoid the multiplicity issue of evaluating many endpoints individually. Composite endpoints have several limitations. Firstly, significance of the composite does not necessarily imply significance of the components nor does significance of the components necessarily imply significance of the composite.
For example one intervention could be better on one component but worse on another and thus result in a non-significant composite. Another concern with composite endpoints is that the interpretation can be challenging particularly when the relative importance of the components differs and the intervention effects on the components also differ. For example, how do we interpret a study in which the overall event rate in one arm is lower but the types of events occurring in that arm are more serious?
Higher event rates and larger effects for less important components could lead to a misinterpretation of intervention impact. It is also possible that intervention effects for different components can go in different directions. Power can be reduced if there is little effect on some of the components i. When designing trials with composite endpoints, it is advisable to consider including events that are more severe e.
It is also advisable to collect data and evaluate each of the components as secondary analyses. This means that study participants should continue to be followed for other components after experiencing a component event. When utilizing a composite endpoint, there are several considerations including: i whether the components are of similar importance, ii whether the components occur with similar frequency, and iii whether the treatment effect is similar across the components.
In the treatment of some diseases, it may take a very long time to observe the definitive endpoint e. A surrogate endpoint is a measure that is predictive of the clinical event but takes a shorter time to observe. The definitive endpoint often measures clinical benefit whereas the surrogate endpoint tracks the progress or extent of disease. Surrogate endpoints could also be used when the clinical end-point is too expensive or difficult to measure, or not ethical to measure.
Surrogate markers must be validated. Ideally evaluation of the surrogate endpoint would result in the same conclusions if the definitive endpoint had been used. The criteria for a surrogate marker are: 1 the marker is predictive of the clinical event, and 2 the intervention effect on the clinical outcome manifests itself entirely through its effect on the marker. It is important to note that significant correlation does not necessarily imply that a marker will be an acceptable surrogate.
Missing data is one of the biggest threats to the integrity of a clinical trial. Missing data can create biased estimates of treatment effects. Thus it is important when designing a trial to consider methods that can prevent missing data. Researchers can prevent missing data by designing simple clinical trials e.
Similarly it is important to consider adherence to protocol e. Envision a trial comparing two treatments in which the trial participants in both groups do not adhere to the assigned intervention. Toggle navigation. Clinical Research Administration ClinicalTrials. University Quick Links.
They: Drive statistical planning e. Secondary outcome measures: Are written similarily to Primary outcome measures, and are specific measurements which include the time frame of assessment Usually address goals of secondary objectives. Tags: aims clinicaltrials. Research Administration Lifecycles Offices. CMS Login.
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