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When we study symptoms over time, we have a number of goals. One goal may be to characterize the average trajectory of symptom severity over time. Often we are asking questions such as: Do symptoms change over time? If so, what factors (eg, treatment) modify that trajectory? We also may be interested in characterizing the impact of symptoms and answering questions such as: Which symptoms have the greatest impact on subjects? How do changes in symptoms affect patient reports of health status and quality of life? How does the level of severity influence that impact? Finally, the goals of the investigation may be to characterize between-subject and within-subject variation, to answer questions such as: Are there groups of symptoms that change within individuals in a similar manner? Are there biological factors (eg, cytokines) that change in conjunction with the development of symptoms? For example, we might be interested in the relationship of inflammatory cytokines to fatigue, pain, and other symptoms of cancer and cancer treatment.
These questions differ from traditional analysis, in which we would typically test whether the average change in symptoms is a function of biological factors by examining the mean scores for groups of subjects with high versus low values of the biological factors. When our interest becomes focused on change and variation at the level of the individual rather than the group, we might be interested in questions such as: Do individuals with generally higher levels of interleukin (IL)-6, an inflammatory cytokine strongly associated with lung cancer, report more pain?
While clinical outcomes are often the primary method of evaluation in clinical trials, endpoints requiring patient-reported measures are essential. The scientific literature is full of reports where investigators make logical but unsubstantiated claims of quality-of-life benefits to patients based on the assumption that a change in treatment or a traditional biomedical outcome will improve the patient's quality of life. While in many cases this may be true, surprising results are sometimes obtained when the patient is asked directly. One classic example occurred with a study by Sugarbaker et al. comparing two therapeutic approaches for soft-tissue sarcoma. The first was limb-sparing surgery followed by radiation therapy. The second treatment approach was full amputation of the affected limb. The investigator hypothesized that “Sparing a limb, as opposed to amputating it, offers a quality of life advantage.” Rather than assuming this was true, the investigators tested their hypothesis. Subjects who received the limb-sparing procedures reported limitations in mobility and sexual functioning. These observations were confirmed with physical assessments of mobility and endocrine function. As a result of these studies, the original hypothesis was rejected, radiation therapy was modified, and physical rehabilitation was added to the limb-sparing therapeutic approach.
There is a danger of adding patient-based outcomes to every clinical trial. If the majority of these studies either fail to answer clinically relevant questions or are methodologically weak, eventually a negative perception about patient-centered outcomes will grow in the research community.
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