Performance of four diagnostic approaches to depression in adults with cancer

Saracino, Rebecca M.; Rosenfeld, Barry; Nelson, Christian J.

doi:10.1016/j.genhosppsych.2018.01.006

Cited by 18 publications

(10 citation statements)

References 37 publications

(37 reference statements)

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“…Although evidence on this issue is limited, studies suggest that patients with cancer report all depressive symptoms significantly more often than the general population, with particularly large differences in somatic symptoms (Hinz et al, 2016(Hinz et al, , 2010Osborne et al, 2004). Consequently, excluding or substituting somatic symptoms leads to substantially different prevalence estimates of depression (Saracino et al, 2018;Sharpley et al, 2017). Yet, few studies have investigated the interrelationship between somatic and cognitive-emotional depressive symptoms in cancer (Jones et al, 2015;Mitchell et al, 2012, Nikendei et al, 2018.…”

Section: Introductionmentioning

confidence: 99%

Frequency and network analysis of depressive symptoms in patients with cancer compared to the general population

Hartung

Fried

Mehnert

et al. 2019

Journal of Affective Disorders

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License: Article 25fa pilot End User AgreementThis publication is distributed under the terms of Article 25fa of the Dutch Copyright Act (Auteurswet) with explicit consent by the author. Dutch law entitles the maker of a short scientific work funded either wholly or partially by Dutch public funds to make that work publicly available for no consideration following a reasonable period of time after the work was first published, provided that clear reference is made to the source of the first publication of the work.This publication is distributed under The Association of Universities in the Netherlands (VSNU) 'Article 25fa implementation' pilot project. In this pilot research outputs of researchers employed by Dutch Universities that comply with the legal requirements of Article 25fa of the Dutch Copyright Act are distributed online and free of cost or other barriers in institutional repositories. Research outputs are distributed six months after their first online publication in the original published version and with proper attribution to the source of the original publication.You are permitted to download and use the publication for personal purposes. All rights remain with the author(s) and/or copyrights owner(s) of this work. Any use of the publication other than authorised under this licence or copyright law is prohibited.If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons.

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Section: Introductionmentioning

confidence: 99%

Frequency and network analysis of depressive symptoms in patients with cancer compared to the general population

Hartung

Fried

Mehnert

et al. 2019

Journal of Affective Disorders

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“…While there has been extensive study of the utility of somatic items in formulating a depression diagnosis among the medically ill broadly (e.g., medical inpatients—Rapp & Vrana, 1989; primary care—Hendrie et al, 1995; general medicine, cardiology, and neurology—Koenig, George, Peterson, & Pieper, 1997; Koenig, Pappas, Holsinger, & Bachar, 1995), there has not generally been consensus on the “optimal” approach, and specifically, whether or not somatic items are reliable indicators of depression among the medically ill. Recent research indicates that somatic items may explain variance in depressive symptoms without erroneously inflating the prevalence (Jones et al, 2015; Mitchell, Lord, & Symonds, 2012; Saracino, Rosenfeld, & Nelson, 2018; Simon & Von Korff, 2006), yet many settings continue to opt for screening measures that eliminate somatic items from consideration (Lambert et al, 2015; Stafford et al, 2014; Wakefield et al, 2015), which decreases sensitivity and the risk of “missing” patients who are experiencing elevated depressive symptoms. Despite recognition of this complexity, the manner by which aging might influence the expression of depressive symptoms specifically in older cancer patients remains largely undetermined.…”

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confidence: 99%

Latent Profile Analyses of Depressive Symptoms in Younger and Older Oncology Patients

et al. 2018

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The aging of America will include a significant increase in the number of older patients with cancer, many of whom will experience significant depressive symptoms. Although geriatric depression is a well-studied construct, its symptom presentation in the context of cancer is less clear. Latent profile analysis was conducted on depressive symptoms in younger (40-64 years) and older (≥65 years) patients with cancer ( N = 636). The sample was clinically heterogeneous (i.e., included all stages, dominated by advanced stage disease). Participants completed questionnaires including the Center for Epidemiological Studies Depression Scale, which was used for the latent profile analysis. A four-class pattern was supported for each age group. However, the four-class pattern was significantly different between the younger and older groups in terms of the item means within each corresponding latent class; differences were primarily driven by severity such that across classes, older adults endorsed milder symptoms. An unexpected measurement issue was uncovered regarding reverse-coded items, suggesting that they may generate unreliable scores on the Center for Epidemiological Studies Depression Scale for a significant subset of patients. The results indicate that cancer clinicians can expect to see depressive symptoms along a continuum of severity for patients of any age, with less severe symptoms among older patients.

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“…This clinical phenomenon needs further explanation and would benefit from the introduction of this objective measure to help facilitate its study as a unique psychological entity. The SBI-R may help inform the recognition and management of depression since both the diagnosis and treatment of depression is challenging in medical settings (Grassi et al, 2014;Saracino et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

The Sickness Behavior Inventory-Revised: Sickness behavior and its associations with depression and inflammation in patients with metastatic lung cancer

et al. 2020

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Background Inflammation may contribute to the high prevalence of depressive symptoms seen in lung cancer. “Sickness behavior” is a cluster of symptoms induced by inflammation that are similar but distinct from depressive symptoms. The Sickness Behavior Inventory-Revised (SBI-R) was developed to measure sickness behavior. We hypothesized that the SBI-R would demonstrate adequate psychometric properties in association with inflammation. Method Participants with stage IV lung cancer (n = 92) were evaluated for sickness behavior using the SBI-R. Concomitant assessments were made of depression (Patient Hospital Questionniare-9, Hospital Anxiety and Depression Scale) and inflammation [C-reactive protein (CRP)]. Classical test theory (CTT) was applied and multivariate models were created to explain SBI-R associations with depression and inflammation. Factor Analysis was also used to identify the underlying factor structure of the hypothesized construct of sickness behavior. A longitudinal analysis was conducted for a subset of participants. Results The sample mean for the 12-item SBI-R was 8.3 (6.7) with a range from 0 to 33. The SBI-R demonstrated adequate internal consistency with a Cronbach's coefficient of 0.85, which did not increase by more than 0.01 with any single-item removal. This analysis examined factor loadings onto a single factor extracted using the principle components method. Eleven items had factor loadings that exceeded 0.40. SBI-R total scores were significantly correlated with depressive symptoms (r = 0.78, p < 0.001) and CRP (r = 0.47, p < 0.001). Multivariate analyses revealed that inflammation and depressive symptoms explained 67% of SBI-R variance. Significance of results The SBI-R demonstrated adequate reliability and construct validity in this patient population with metastatic lung cancer. The observed findings suggest that the SBI-R can meaningfully capture the presence of sickness behavior and may facilitate a greater understanding of inflammatory depression.

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Performance of four diagnostic approaches to depression in adults with cancer

Cited by 18 publications

References 37 publications

Frequency and network analysis of depressive symptoms in patients with cancer compared to the general population

Frequency and network analysis of depressive symptoms in patients with cancer compared to the general population

Latent Profile Analyses of Depressive Symptoms in Younger and Older Oncology Patients

The Sickness Behavior Inventory-Revised: Sickness behavior and its associations with depression and inflammation in patients with metastatic lung cancer

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