Clinical Trial Background Issues - page 2

PICO Intervention Issues

The item to be tested in a clinical trial (e.g., new drug, surgical procedure, psychosocial intervention) is described in great detail in a protocol document.

		This document lists all types of contingencies to ensure that all patients are treated in the same way to produce reliable results. By being very precise, the protocol enables independent researchers to repeat the trial to see if they come up with the same result. Such replication is common in science to ensure that the results that may be used to change clinical practice are real and are not the result of random errors.

The following items are Federal Drug Administration (FDA) standard required protocol elements. They help investigators answer key questions and make sure that participants and health care professionals clearly understand the goals of a clinical trial:

• General information
• Background information (referenced)
• Trial objectives and purpose
• Trial design
• Participant eligibility and withdrawal
• Participant treatment
• Efficacy (will it work?) assessment
• Safety assessment
• Statistics
• Quality control and quality assurance
• Ethics
• Data handling and record keeping
• Financing and insurance
• Publication policy

If government funding is used for the study, the protocol must be reviewed and approved by the National Cancer Institute (NCI).

PICO Comparison Issues

Assessing an experimental intervention properly requires the use of a control (or comparison) intervention so that the two can be compared and contrasted.

The specific conclusions that can be drawn from a clinical trial depend upon what comparisons are specified in the protocol. For example, a new drug may be compared to a placebo (e.g., inactive sugar pill); if patients receiving the new drug live longer, investigators can conclude that the new drug is helpful.

However, they cannot conclude that the trial drug is superior to other drugs that may be used currently. In order to conclude that a new drug is superior to the standard treatment it would have to be compared to the standard treatment in a trial, rather than a placebo.

It is important to avoid bias (various distortions that can lead to ambiguous or erroneous conclusions). This can happen when there is confounding (i.e., when a variable other than the experimental intervention of interest is varies along with it). In such cases the results may be a consequence of the confounding variable, rather than the experimental intervention.

		This chart describes several types of confounding and how they can be avoided. Making sure to avoid all types of potential bias is a major challenge of designing excellent clinical trials.

PICO Outcome Issues (Endpoints)

Clinical trials assess the effect of different treatments on the course of disease by measuring specific outcomes (or endpoints) that indicate an intervention's effectiveness. Endpoints differ depending on the phase and type of trial.

The choice of outcomes or endpoints typically involves trade-offs due to conflicting priorities such as speed, completeness, and clinical value.

Primary endpoints (those of highest interest) are selected and the trial is designed to ensure that these endpoints can be adequately assessed.

• Tumor response rate (TRR) - the proportion of trial participants whose tumor was reduced in size by a specific amount, usually described as a percentage. If 7 of 10 patients responded, the response rate is 70 percent.
• Disease-free survival (DFS) - the amount of time a participant with localized disease survives without cancer occurring or recurring, usually measured in months.
• Progression-free survival (PFS) - the amount of time a participant with advanced disease survives without cancer occurring or recurring, usually measured in months.
• Response duration (RD) - the response duration is occasionally used to analyze the results of the treatment for the advanced disease. The event measured is progression of the disease (relapse). This endpoint involves selecting a subgroup of the patients and measures the length of time of the response in those patients who responded. The patients who don't respond to treatment aren't included in the endpoint analysis.
• Overall survival (OS) - the amount of time a participant lives, typically measured from the beginning of the clinical trial or the date of diagnosis until the time of death.

Secondary endpoints are of lesser interest. They are also specified in the protocol but the trial may not be powered (have enough numbers) to adequately assess them.

• Side-effect profile
• Quality of life (QOL)

The examples above can be used as primary or secondary endpoints depending on the study, although that is rarely done. Additionally, many current clinical trials include the collection of a host of demographic and biomarker measures (sometimes referred to as secondary endpoints) that are analyzed to identify interesting questions for future study. Analysis of these variables is call correlative science.