There is a lot of variation in the literature related to reports of rates of depression among cancer patients. Even with standardized tools, wide variations can still be observed. One good option would be to carry out more prevalence studies that focus on examining the causes for these variations and factors responsible for the differing rates. The timing of estimation of depressive symptoms appears to be a critical factor and may be responsible for the variance. A good option would be to develop a statistical model having the ability to predict the rate of depression when cancer and treatment demographics, as relevant to the population, are available. Studies must also include evaluation of the patient’s history of depression.

All of the current incidence studies that focus on assessing depression amongst cancer patients begin at a specific point of time after diagnosis has been made. More prospective studies should be started at the time when diagnosis is made, or even before that, to be able to get more precise estimates about the incidence of depression among cancer patients. These studies also need to examine the patient’s history of depression.

Different types of tools are currently being used for evaluating depression amongst people diagnosed with cancer. Researchers can choose from a wide range of tools after comparing factors like ease of use related to their study population and efficacy of individual tools as described in the evidence tables. Further trials need to be conducted to replicate the positive results associated with a single-item screening, asking the question, “Are you depressed?”

Even though use of some of these tools is quite common in clinical practice, more research is required to measure their effectiveness. The development of brief tools having the ability to evaluate all three symptoms (pain, fatigue and depression) can potentially be one major area of future research. Psychosocial, psychopharmacologic, and alternative interventions provide some benefit to cancer patients on treatment of depressive symptoms. Many opportunities exist for conducting research on psychopharmacologic interventions meant for treating depression co-morbid with cancer. Newly developed antidepressants, especially the atypical ones, should be studied in this specific population. While antidepressant trials are relatively more complicated to carry out in cancer patients, they still need to follow the standard study length of six weeks or more. Prevalent clinical practices, for instance, the use of psychostimulants for treating depression, should be assessed in controlled trials. More research also needs to be conducted on the use of antidepressants to prevent depressive symptoms in cancer patients.

There are hundreds of studies that focus on psychosocial interventions for people diagnosed with cancer and depression, but what is lacking is a meta-analysis of psychosocial therapies meant specifically for treating depression among cancer patients. Even though most patients may be relying on complementary and alternative treatment options, controlled trials are needed to measure their effectiveness in depression co-morbid with cancer.


Future research involving cancer-related fatigue must also include more exhaustive studies on the prevalence of fatigue in more complex environs that are characterized by a wide range of diseases and settings. Other requisites include longitudinal studies. Valuable prevalence data can be potentially extracted from studies that focus on health-related quality of life, common symptom surveys and treatment trials. For this, we need to devise a method to compare results derived from studies that use different assessment tools. Further research is required to explain the clinical importance of the fatigue scores that were obtained with the help of these tools.

There is ample preliminary evidence to confirm randomized controlled trials focusing on a number of interventions for fatigue related to cancer, including exercise regimens, stimulant medications and psychosocial interventions. More observational studies and laboratory research on the physiology of cancer-related fatigue are required to be able to develop rational hypotheses for potential future intervention trials. Clinical trials that focus on cancer-related fatigue should deploy appropriate study designs, including the potential identification of desired outcomes and sample sizes that are calculated to allow a logical likelihood of detecting those outcomes.

In all of the topics discussed in this evidence report, what is lacking are the studies on the pediatric population. Research is required on an urgent basis to address symptoms of pain, fatigue and depression in children.