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Journal of Clinical Oncology, Vol 25, No 33 (November 20), 2007: pp. 5328-5329 © 2007 American Society of Clinical Oncology. DOI: 10.1200/JCO.2007.13.8594
More Claims About Depression, Immune Function, and Survival That Exceed the EvidenceUniversity of Pennsylvania School of Medicine, Philadelphia, PA To the Editor: Claims that depression is highly prevalent among patients with cancer that it influences disease progression and mortality via immune system functioning, and that treatments addressing depression promote survival appeal to clinicians, researchers, and patients. Unfortunately, this appeal sometimes translates into a confirmatory bias when it comes to interpreting the relevant evidence. As a result of these claims, many patients with breast cancer attend support groups with the belief that they will bolster their immune systems and improve their chances of survival.1 Recently, Steel and colleagues2 generated data thought to suggest that depression influences survival of patients with hepatobiliary cancer through its effects on the immune system. An accompanying Editorial3 reinforces this interpretation of their data and calls for more aggressive treatment of depression as a potential way of promoting survival. Is depression highly prevalent among patients with cancer? Steel and colleagues found that the prevalence of elevated scores on a depression questionnaire was 37% at diagnosis. While this may sound extraordinarily high, the rate is similar to what is frequently found in primary care waiting rooms,4,5 and the mean value is only 2.1 points higher than the general population value cited by Steel and colleagues. Such similarities are all the more remarkable given the disease burden and awareness of likely death among many of the patients with hepatobiliary cancer. Moreover, an elevated score on a questionnaire cannot validly be interpreted as representing a depressive disorder; the probability that an elevated score represents major depressive disorder in a nonpsychiatric medical sample is probably in the 25% to 35% range.4,6
Steel and colleagues put forth an exploratory aim regarding depression and survival, namely, to "examine the relationship between depressive symptoms and survival while controlling for sociodemographic variables." Leaving aside the issue of control variables for the moment, examination of the Steel et al data reveal that the two-tailed significance of the unadjusted odds ratio for mortality associated with a report of elevated depression is P = .067 for a Fisher's exact test and P = .044 for the Pearson Steel et al also report an analysis purported to demonstrate that natural killer (NK) cell numbers mediate the relationship between depression and mortality among a subsample of 23 individuals. They end by suggesting that reduction in depressive symptoms may enhance immune system functioning and thereby promote survival. Examination of their data suggests a number of difficulties with their interpretations. First, there does not seem to be a significant relationship between NK cell number and survival (P = .07), a requirement for mediation. This produces another difficulty; the authors do not demonstrate that NK cell number continues to influence survival when holding depression constant. The largest problem, however, appears to be that the sample is simply too small to allow for meaningful conclusions, particularly given the large number of covariates included. With only 23 participants, the authors include at least 11 variables in their regression equation. Such overfitting is unlikely to shed light on how depression may be associated with survival. We are not suggesting that depression does not relate to survival, but rather it is best seen as a risk marker, and not an established causal risk factor. Self-reported depression relates to mortality from a wide variety of health problems,8,9 as well as all cause mortality.10 However, these associations often disappear when appropriate control variables are considered.10,11 Substantive interpretations of these associations require positing either a diversity of mechanisms that produce similar outcomes or a highly general mechanism, given the diverse contexts in which these relationships are found. A more parsimonious explanation is that associations are primarily due to measurement confounds between health status (objective and perceived) and affect. This explanation requires many fewer assumptions and is increasingly being accepted.11 Finally, the accompanying Editorial uses these results to call for more aggressive treatment of depression and depressive symptoms. The prevalence of major depression, the condition for which there are empirically based treatment guidelines, is certainly lower in this and other samples than what one would infer from equating elevated scores with the disorder. Recognition and treatment of major depressive disorder is a realistic goal in the cancer care center. Also, research efforts are needed to demonstrate efficacious treatments for the more diffuse construct of "elevated distress" given the lack of evidence for the efficacy of antidepressants in the absence of a diagnosis of major depression. Patients need accurate information on which to base their decisions concerning psychological treatment, and the rationale with which they are presented should not be based on premature claims for survival and immunologic benefits. AUTHORS' DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST The author(s) indicated no potential conflicts of interest. REFERENCES
1. Cameron LD, Booth RJ, Schlatter M, et al: Cognitive and affective determinants of decisions to attend a group psychosocial support program for women with breast cancer. Psychosom Med 67:584-589, 2005 2. Steel JL, Geller DA, Gamblin TC, et al: Depression, immunity, and survival in patients with hepatobiliary carcinoma. J Clin Oncol 25:2397-2405, 2007 3. Irwin MR: Depression and Risk of Cancer Progression: An Elusive Link. J Clin Oncol 2007; 25:2343-2344, 2007 4. Fechner-Bates S, Coyne JC, Schwenk TL: The relationship of self-reported distress to psychopathology. J Consult Clinical Psycol 62:550-559, 1994[CrossRef] 5. Herrman H, Patrick DL, Diehr P, et al: Longitudinal investigation of depression outcomes in primary care in six countries: The LIDO Study—Functional status, health service use and treatment of people with depressive symptoms. Psychol Med 32:889-902, 2002[CrossRef][Medline] 6. Coyne JC, Palmer SC, Shapiro PJ, et al: Distress, psychiatric morbidity and prescriptions for psychotropic medication in a breast cancer waiting room sample. Gen Hosp Psychiatry 26:121-128, 2004[CrossRef][Medline] 7. Babyak MA: What you see may not be what you get: A brief, nontechnical introduction to overfitting in regression-type models. Psychosom Med 66:411-421, 2004 8. Ng TP, Niti M, Tan WC, et al: Depressive symptoms and chronic obstructive pulmonary disease: Effect on mortality, hospital readmission, symptom burden, functional status, and quality of life. Arch Intern Med 167:60-67 2007 9. Drayer RA, Piraino B, Reynolds CF, et al: Characteristics of depression in hemodialysis patients: Symptoms, quality of life and mortality risk. Gen Hosp Psychiatry 28:306-312, 2006[CrossRef][Medline] 10. Everson-Rose SA, House JS, Mero RP: Depressive symptoms and mortality risk in a national sample: Confounding effects of health status. Psychosom Med 66:823-830, 2004 11. Macleod J, Smith GD: Psychosocial factors and public health: A suitable case for treatment? J Epidem Commun Health 57:565-570, 2003 Related Reply
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Copyright © 2007 by the American Society of Clinical Oncology, Online ISSN: 1527-7755. Print ISSN: 0732-183X
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2. This effect would be lost with reclassification of a single patient. The weakness of this relationship is remarkable, given the likelihood of confounding and reverse causality in such an ill population facing death. Steel et al do not report the unadjusted relationship between self-reported depression and survival, but do suggest that the relationship is "robust" when a variety of control variables are considered. However, the regression they perform is likely overfitted, given the number of deaths being explained. Also, the choice of covariates capitalized on chance by prescreening for significance.
