Quality of Life (QOL) Studies
QOL studies can be integral or integrated tests, assays, and/or tools. They must be part of the clinical trial design from the beginning (assessments conducted while the trial is open). They are intended to inform on treatment options and side effects by validating the biological and functional clinical correlates of patient–reported outcome (PRO) data. These may also include biomarker assays and imaging tests that may be used for decision making in future trials.
Currently, DCP funds quality of life studies that obtain information for use in patient-physician decision making that help the patient prepare for and interpret the treatment experience. Examples of this DCP support may include studies where differences between treatments in survival or other disease-related endpoints are expected to be minimal or when treatment arms represent very different treatment scenarios. Assessments may include, but are not limited to, qualitative data, toxicity impact, convenience, psychosocial outcomes and function.
Eligible categories of quality of life studies and examples include:
- QOL studies to obtain additional information for use in patient–physician decision making or to help the patient prepare for and interpret the treatment experience when the collection of QOL data requires resources beyond the usual cancer control credits or per case reimbursement.
- Studies that validate measures previously tested in smaller studies. QOL measures that have been piloted in smaller studies and are supported by preliminary data require full validation in a phase 3 trial. This includes evaluating patient reported outcomes (PRO) as complementary adjuncts to clinician-assessed outcomes for measuring toxicity (e.g., adverse events as measured by Common Toxicity Criteria).
- Studies in the PRO measurement field with the integration of modern measurement theory for the development of brief, precise, and valid PRO measures. These advancements provide an examination of the benefits of integrating these measures, including electronic data capture, into clinical trials. Examples of studies that fall into this category may include: computer-based testing, experience sampling, and multiple brief symptom assessment (as opposed to infrequent and lengthier assessment).
There is growing interest in the role of objective measures such as biomarkers, imaging studies, and measures of activity such as pedometers and actigraphs that can further inform symptoms, QOL assessments, and selected measures that validate PRO data such as:
- Studies that provide "objective" correlates to self-report measures that are not easily supported through funding for clinical trials. Concurrent collection of an "objective" test along with a performance measure provides stronger data when following patients on a symptom management or quality of life trial. Examples of studies in this category may include: enhancing measures that validate patient self-report of fatigue or physical function with objective actigraphy; and neuropsychological testing in studies of cognitive effects from therapy, or in following patients with brain tumors or metastases.
- Studies that are "predictive" measures with testable hypothesis(es) and a high likelihood to give validated interpretations, and correlative measures to predict morbidity, safety, pathophysiologic mechanisms of symptom expression, and/or treatment efficacy and genetic determinates of symptom expression, quality of life endpoints and treatment efficacy. Examples of these study measurements may include: cytochrome P450 metabolism; cytokine analyses; pharmacokinetic studies for drug interactions; neuroendocrine studies, and fMRI for cognitive changes.
Criteria for Review of Quality of Life Studies
Prioritization and evaluation criteria include:
- The potential to impact patient morbidity or quality of life with clinically meaningful benefit
- The potential to move science forward in cancer related quality of life by adding critical knowledge
- The strength of the preliminary data supporting the hypothesis(es) to be tested and methods proposed
- A clearly defined process for data and specimen collection
- A statistical plan with adequate power for the quality of life correlative study hypothesis(es)
- Measures that are reliable, valid and appropriate to the population of interest
- Feasibility of proposal such that completion can be accomplished efficiently and in a reasonable time frame
