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Prevalence of mental disorders in patients with cancer compared to matched controls - secondary analysis of two nationally representative surveys

AIM

To compare prevalence rates of mental disorders in patients with cancer and general population controls.

METHOD

In two stratified nationally representative surveys, the 12-month prevalence of mental disorders was assessed in 2141 patients with cancer and 4883 general population controls by the standardized Composite International Diagnostic Interview (CIDI). We determined odds ratios (ORs) to compare the odds for mental disorders (combined and subtypes) in cancer patients with age- and gender-matched controls.

RESULTS

The 12-month prevalences rate for any mental disorder was significantly higher in patients with cancer compared to controls (OR 1.28, 95% CI 1.14-1.45). Prevalence rates were at least two times higher for unipolar mood disorders (major depression: OR 2.07, 95% CI 1.71-2.51; dysthymia: OR 2.93, 95% CI 2.13-4.02) and mental disorders due to a general medical condition (OR 3.31, 95% CI 2.32-4.71). There was no significant elevation for anxiety disorders overall (OR 0.95, 95% CI 0.81-1.11). Mildly elevated prevalence rates emerged for post-traumatic stress disorder (OR 1.57, 95% CI 1.11-2.23) and social phobia (OR 1.57, 95% CI 1.07-2.31), while specific phobia (OR 0.82, 95% CI 0.67-1.00) and agoraphobia (OR 0.49, 95% CI 0.33-0.73) were significantly less frequent in cancer.

CONCLUSIONS

While elevated depression rates reinforce the need for its systematic diagnosis and treatment, lower prevalences were unexpected given previous evidence. Whether realistic illness-related fears and worries contribute to lower occurrence of anxiety disorders with excessive fears in cancer may be of interest to future research.

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

BACKGROUND

The use of sum scores of depressive symptoms has been increasingly criticized and may be particularly problematic in oncological settings. Frameworks analyzing individual symptoms and their interrelationships such as network analysis represent an emerging alternative.

METHODS

We aimed to assess frequencies and interrelationships of 9 DSM-5 symptom criteria of major depression reported in the PHQ-9 questionnaire by 4020 patients with cancer and 4020 controls from the general population. We estimated unregularized Gaussian graphical models for both samples and compared network structures as well as predictability and centrality of individual symptoms.

RESULTS

Depressive symptoms were more frequent, but less strongly intercorrelated in patients with cancer than in the general population. The overall network structure differed significantly between samples (correlation of adjacency matrices: rho=0.73, largest between-group difference in any edge weight: 0.20, p < 0.0001). Post-hoc tests showed significant differences in interrelationships for four symptom pairs. The mean variance of symptoms explained by all other symptoms in the same network was lower among cancer patients than in the general population (29% vs. 43%).

LIMITATIONS

Cross-sectional data do not allow for temporal or causal inferences about the directions of associations and results from population-based samples may not apply to clinical psychiatric populations.

CONCLUSIONS

In patients with cancer, both somatic and cognitive/affective depression symptoms are less likely to be explained by other depressive symptoms than in the general population. Rather than assuming a consistent depression construct, future research should study individual depressive symptom patterns and their potential causes in patients with cancer.