Dataset Information

Indicators to facilitate the early identification of patients with major depressive disorder in need of highly specialized care: A concept mapping study.

ABSTRACT:

Background

Early identification of the subgroup of patients with major depressive disorder (MDD) in need of highly specialized care could enhance personalized intervention. This, in turn, may reduce the number of treatment steps needed to achieve and sustain an adequate treatment response. The aim of this study was to identify patient-related indicators that could facilitate the early identification of the subgroup of patients with MDD in need of highly specialized care.

Methods

Initial patient indicators were derived from a systematic review. Subsequently, a structured conceptualization methodology known as concept mapping was employed to complement the initial list of indicators by clinical expertise and develop a consensus-based conceptual framework. Subject-matter experts were invited to participate in the subsequent steps (brainstorming, sorting, and rating) of the concept mapping process. A final concept map solution was generated using nonmetric multidimensional scaling and agglomerative hierarchical cluster analyses.

Results

In total, 67 subject-matter experts participated in the concept mapping process. The final concept map revealed the following 10 major clusters of indicators: 1-depression severity, 2-onset and (treatment) course, 3-comorbid personality disorder, 4-comorbid substance use disorder, 5-other psychiatric comorbidity, 6-somatic comorbidity, 7-maladaptive coping, 8-childhood trauma, 9-social factors, and 10-psychosocial dysfunction.

Conclusions

The study findings highlight the need for a comprehensive assessment of patient indicators in determining the need for highly specialized care, and suggest that the treatment allocation of patients with MDD to highly specialized mental healthcare settings should be guided by the assessment of clinical and nonclinical patient factors.

SUBMITTER: van Krugten FCW

PROVIDER: S-EPMC6282616 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Publications

Indicators to facilitate the early identification of patients with major depressive disorder in need of highly specialized care: A concept mapping study.

van Krugten F C W FCW Goorden M M van Balkom A J L M AJLM Spijker J J Brouwer W B F WBF Hakkaart-van Roijen L L

Depression and anxiety 20180325 4

<h4>Background</h4>Early identification of the subgroup of patients with major depressive disorder (MDD) in need of highly specialized care could enhance personalized intervention. This, in turn, may reduce the number of treatment steps needed to achieve and sustain an adequate treatment response. The aim of this study was to identify patient-related indicators that could facilitate the early identification of the subgroup of patients with MDD in need of highly specialized care.<h4>Methods</h4>I ...[more]

PMID: 29575387

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Project description:ObjectivesEarly identification of patients with major depressive disorder (MDD) that cannot be managed by secondary mental health services and who require highly specialized mental healthcare could enhance need-based patient stratification. This, in turn, may reduce the number of treatment steps needed to achieve and sustain an adequate treatment response. The development of a valid tool to identify patients with MDD in need of highly specialized care is hampered by the lack of a comprehensive understanding of indicators that distinguish patients with and without a need for highly specialized MDD care. The aim of this study, therefore, was to systematically review studies on indicators of patients with MDD likely in need of highly specialized care.MethodsA structured literature search was performed on the PubMed and PsycINFO databases following PRISMA guidelines. Two reviewers independently assessed study eligibility and determined the quality of the identified studies. Three reviewers independently executed data extraction by using a pre-piloted, standardized extraction form. The resulting indicators were grouped by topical similarity, creating a concise summary of the findings.ResultsThe systematic search of all databases yielded a total of 7,360 references, of which sixteen were eligible for inclusion. The sixteen papers yielded a total of 48 unique indicators. Overall, a more pronounced depression severity, a younger age of onset, a history of prior poor treatment response, psychiatric comorbidity, somatic comorbidity, childhood trauma, psychosocial impairment, older age, and a socioeconomically disadvantaged status were found to be associated with proxies of need for highly specialized MDD care.ConclusionsSeveral indicators are associated with the need for highly specialized MDD care. These indicators provide easily measurable factors that may serve as a starting point for the development of a valid tool to identify patients with MDD in need of highly specialized care.

Project description:BackgroundSelection of the optimal initial treatment in patients with major depressive disorder (MDD) in need of highly specialized care has the potential to benefit treatment outcomes and cost-effectiveness of treatment strategies. However, to date, there is a paucity of measures that could guide the selection of the initial treatment, in particular to indicate which patients with MDD are in need of highly specialized care. Recognizing this gap, this paper reports on the development and psychometric evaluation of the Decision Tool Unipolar Depression (DTUD), aimed to facilitate the early identification of patients with MDD in need of highly specialized care.MethodsThe DTUD was developed using a mixed-methods approach, consisting of a systematic review and a concept mapping study. To evaluate the psychometric features of the DTUD, a cross-sectional multicenter study was conducted. A total of 243 patients with MDD were evaluated with the DTUD. Feasibility was operationalized as the time required to complete the DTUD and the content clarity of the DTUD. Inter-rater reliability was evaluated using Krippendorf's alpha. The Maudsley Staging Method (MSM) and the Dutch Measure for quantification of Treatment Resistance in Depression (DM-TRD) were administered to assess the convergent validity. A receiver operator characteristic curve was generated to evaluate the criterion validity and establish the optimal cut-off value.ResultsThe mean administration time was 4.49?min (SD?=?2.71), and the content of the total DTUD was judged as clear in 94.7% of the evaluations. Inter-rater reliability values ranged from 0.69 to 0.91. Higher scores on the DTUD were associated with higher scores on the MSM (rs =?0.47) and DM-TRD (rs =?0.53). Based on the maximum Youden index (0.494), maximum discrimination was reached at a cut-off score of ?5 (sensitivity 67%, specificity 83%).ConclusionThe DTUD demonstrated to be a tool with solid psychometric properties and, therefore, is a promising measure for the early identification of patients with MDD in need of highly specialized care. Use of the DTUD has the potential to facilitate the selection and initiation of the optimal initial treatment in patients with MDD, which in turn may improve the clinical effectiveness and cost-effectiveness of treatment strategies.

Project description:Background: Major Depressive Disorder (MDD) is a moderately heritable disorder with a high lifetime prevalence. At present, laboratory blood tests to support MDD diagnosis are not available. Methods: We used a classifier approach on blood gene expression profiles of a unique set of non-medicated subjects (MDD patients and controls) to select genes of which expression is predictive for disease status. To reveal blood gene expression changes related to MDD disease, we applied a powerful ex vivo stimulus to the blood, i.e. incubation with lipopolysaccharide (LPS; 10 ng/ml blood). Results: Based on LPS-stimulated blood gene expression using whole-genome microarrays in 42 subjects (primary cohort; 21 MDD patients (mean age 42.3 years), 21 healthy controls (mean age 41.9 years)), we identified a set of genes (CAPRIN1, CLEC4A, KRT23, MLC1, PLSCR1, PROK2, ZBTB16) that serves as a molecular signature of MDD. These findings were validated for the primary cohort using an independent quantitative PCR method (P = 0.007). The difference between depressive patients and controls was confirmed (P = 0.019) in a replication cohort of 13 patients with MDD (mean age 42.8 years) and 14 controls (mean age 45.6 years). The MDD-signature score comprised of expression levels of 7 genes could discriminate depressive patients from controls with sensitivity of 76.9% and specificity of 71.8%. Conclusions: We show for the first time that molecular analysis of stimulated blood cells can be used as an endophenotype for MDD diagnosis, which is a milestone in establishing biomarkers for neuropsychiatric disorders with moderate heritability in general. Our results may provide a new entry point for following and predicting treatment outcome, as well as prediction of severity and recurrence of MDD. In total, 33 MDD patients and 34 healthy controls were analyzed using basal gene expression in whole blood, and gene expression from whole blood that was stimulated with LPS for 5-6 h, using microarrays. Patients were arbitrarily selected from all patients to serve as primary cohort (nMDD = 21 (MDD01-MDD21); nControls = 21 (Con01-Con21)), or replication cohort (nMDD = 12 (MDD22-MDD35); nControls = 13 (Con22-Con37)) using microarrays. This submission does not include Samples CON21_LPS or CON30_LPS.

Dataset Information

Indicators to facilitate the early identification of patients with major depressive disorder in need of highly specialized care: A concept mapping study.

Background

Methods

Results

Conclusions

Publications

Indicators to facilitate the early identification of patients with major depressive disorder in need of highly specialized care: A concept mapping study.

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