Probability of major depression diagnostic classification using semi-structured versus fully structured diagnostic interviews

Background: Different diagnostic interviews are used as reference standards for major depression classification in research. Semi-structured interviews involve clinical judgement, whereas fully structured interviews are completely scripted. The Mini International Neuropsychiatric Interview (MINI), a brief fully structured interview, is also sometimes used. It is not known whether interview method is associated with probability of major depression classification. Aims: To evaluate the association between interview method and odds of major depression classification, controlling for depressive symptom scores and participant characteristics. Method: Data collected for an individual participant data meta-analysis of Patient Health Questionnaire-9 (PHQ-9) diagnostic accuracy were analyzed. Binomial Generalized Linear Mixed Models were fit. Results: 17,158 participants (2,287 major depression cases) from 57 primary studies were analyzed. Among fully structured interviews, odds of major depression were higher for the MINI compared to the Composite International Diagnostic Interview (CIDI) [OR (95% CI) = 2.10 (1.15–3.87)]. Compared to semi-structured interviews, fully structured interviews (MINI excluded) were non-significantly more likely to classify participants with low-level depressive symptoms (PHQ-9 scores ≤6) as having major depression [OR (95% CI) = 3.13 (0.98–10.00)], similarly likely for moderate-level symptoms (PHQ-9 scores 7–15) [OR (95% CI) = 0.96 (0.56–1.66)], and significantly less likely for high-level symptoms (PHQ-9 scores ≥16) [OR (95% CI) = 0.50 (0.26–0.97)] Conclusions: The MINI may identify more depressed cases than the CIDI, and semi- and fully structured interviews may not be interchangeable methods, but these results should be replicated

Accuracy of the Hospital Anxiety and Depression Scale Depression subscale (HADS-D) to screen for major depression:Systematic review and individual participant data meta-analysis

OBJECTIVE: To evaluate the accuracy of the depression subscale of the Hospital Anxiety and Depression Scale (HADS-D) to screen for major depression among people with physical health problems. DESIGN: Systematic review and individual participant data meta-analysis. DATA SOURCES: Medline, Medline In-Process and Other Non-Indexed Citations, PsycInfo, and Web of Science (from inception to 25 October 2018). REVIEW METHODS: Eligible datasets included HADS-D scores and major depression status based on a validated diagnostic interview. Primary study data and study level data extracted from primary reports were combined. For HADS-D cut-off thresholds of 5-15, a bivariate random effects meta-analysis was used to estimate pooled sensitivity and specificity, separately, in studies that used semi-structured diagnostic interviews (eg, Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders), fully structured interviews (eg, Composite International Diagnostic Interview), and the Mini International Neuropsychiatric Interview. One stage meta-regression was used to examine whether accuracy was associated with reference standard categories and the characteristics of participants. Sensitivity analyses were done to assess whether including published results from studies that did not provide raw data influenced the results. RESULTS: Individual participant data were obtained from 101 of 168 eligible studies (60%; 25 574 participants (72% of eligible participants), 2549 with major depression). Combined sensitivity and specificity was maximised at a cut-off value of seven or higher for semi-structured interviews, fully structured interviews, and the Mini International Neuropsychiatric Interview. Among studies with a semi-structured interview (57 studies, 10 664 participants, 1048 with major depression), sensitivity and specificity were 0.82 (95% confidence interval 0.76 to 0.87) and 0.78 (0.74 to 0.81) for a cut-off value of seven or higher, 0.74 (0.68 to 0.79) and 0.84 (0.81 to 0.87) for a cut-off value of eight or higher, and 0.44 (0.38 to 0.51) and 0.95 (0.93 to 0.96) for a cut-off value of 11 or higher. Accuracy was similar across reference standards and subgroups and when published results from studies that did not contribute data were included. CONCLUSIONS: When screening for major depression, a HADS-D cut-off value of seven or higher maximised combined sensitivity and specificity. A cut-off value of eight or higher generated similar combined sensitivity and specificity but was less sensitive and more specific. To identify medically ill patients with depression with the HADS-D, lower cut-off values could be used to avoid false negatives and higher cut-off values to reduce false positives and identify people with higher symptom levels. TRIAL REGISTRATION: PROSPERO CRD42015016761

External validation of a shortened screening tool using individual participant data meta-analysis: A case study of the Patient Health Questionnaire-Dep-4.

Shortened versions of self-reported questionnaires may be used to reduce respondent burden. When shortened screening tools are used, it is desirable to maintain equivalent diagnostic accuracy to full-length forms. This manuscript presents a case study that illustrates how external data and individual participant data meta-analysis can be used to assess the equivalence in diagnostic accuracy between a shortened and full-length form. This case study compares the Patient Health Questionnaire-9 (PHQ-9) and a 4-item shortened version (PHQ-Dep-4) that was previously developed using optimal test assembly methods. Using a large database of 75 primary studies (34,698 participants, 3,392 major depression cases), we evaluated whether the PHQ-Dep-4 cutoff of ≥ 4 maintained equivalent diagnostic accuracy to a PHQ-9 cutoff of ≥ 10. Using this external validation dataset, a PHQ-Dep-4 cutoff of ≥ 4 maximized the sum of sensitivity and specificity, with a sensitivity of 0.88 (95% CI 0.81, 0.93), 0.68 (95% CI 0.56, 0.78), and 0.80 (95% CI 0.73, 0.85) for the semi-structured, fully structured, and MINI reference standard categories, respectively, and a specificity of 0.79 (95% CI 0.74, 0.83), 0.85 (95% CI 0.78, 0.90), and 0.83 (95% CI 0.80, 0.86) for the semi-structured, fully structured, and MINI reference standard categories, respectively. While equivalence with a PHQ-9 cutoff of ≥ 10 was not established, we found the sensitivity of the PHQ-Dep-4 to be non-inferior to that of the PHQ-9, and the specificity of the PHQ-Dep-4 to be marginally smaller than the PHQ-9

Data-driven methods distort optimal cutoffs and accuracy estimates of depression screening tools: a simulation study using individual participant data

To evaluate, across multiple sample sizes, the degree that data-driven methods result in (1) optimal cutoffs different from population optimal cutoff and (2) bias in accuracy estimates.NIMH -National Institute of Mental Health(13/00

Patterns of patient-reported symptoms and association with sociodemographic and systemic sclerosis disease characteristics: a scleroderma Patient-centered Intervention Network (SPIN) Cohort cross-sectional study

Background Systemic sclerosis is a heterogenous disease in which little is known about patterns of patient-reported symptom clusters. We aimed to identify classes of individuals with similar anxiety, depression, fatigue, sleep disturbance, and pain symptoms and to evaluate associated sociodemographic and disease-related characteristics. Methods This multi-centre cross-sectional study used baseline data from Scleroderma Patient-centered Intervention Network Cohort participants enrolled from 2014 to 2020. Eligible participants completed the PROMIS-29 v2.0 measure. Latent profile analysis was used to identify homogeneous classes of participants based on patterns of anxiety, depression, fatigue, sleep disturbance, and pain scores. Sociodemographic and disease-related characteristics were compared across classes. Findings Among 2212 participants, we identified five classes, including four classes with “Low” (565 participants, 26%), “Normal” (651 participants, 29%), “High” (569 participants, 26%), or “Very High” (193 participants, 9%) symptom levels across all symptoms. Participants in a fifth class, “High Fatigue/Sleep/Pain and Low Anxiety/Depression” (234 participants, 11%) had similar levels of fatigue, sleep disturbance, and pain as in the “High” class but low anxiety and depression symptoms. There were significant and substantive trends in sociodemographic characteristics (age, education, race or ethnicity, marital or partner status) and increasing disease severity (diffuse disease, tendon friction rubs, joint contractures, gastrointestinal symptoms) across severity-based classes. Disease severity and sociodemographic characteristics of “High Fatigue/Sleep/Pain and Low Anxiety/Depression” class participants were similar to the “High” severity class. Interpretation Most people with systemic sclerosis can be classified by levels of patient-reported symptoms, which are consistent across symptoms and highly associated with sociodemographic and disease-related variables, except for one group which reports low mental health symptoms despite high levels of other symptoms and substantial disease burden. Studies are needed to better understand resilience in systemic sclerosis and to identify and facilitate implementation of cognitive and behavioural strategies to improve coping and overall quality of life

Individual participant data meta analysis to compare EPDS accuracy to detect major depression with and without the self-harm item

Item 10 of the Edinburgh Postnatal Depression Scale (EPDS) is intended to assess thoughts of intentional self-harm but may also elicit concerns about accidental self-harm. It does not specifically address suicide ideation but, nonetheless, is sometimes used as an indicator of suicidality. The 9-item version of the EPDS (EPDS-9), which omits item 10, is sometimes used in research due to concern about positive endorsements of item 10 and necessary follow-up. We assessed the equivalence of total score correlations and screening accuracy to detect major depression using the EPDS-9 versus full EPDS among pregnant and postpartum women. We searched Medline, Medline In-Process and Other Non-Indexed Citations, PsycINFO, and Web of Science from database inception to October 3, 2018 for studies that administered the EPDS and conducted diagnostic classification for major depression based on a validated semi-structured or fully structured interview among women aged 18 or older during pregnancy or within 12 months of giving birth. We conducted an individual participant data meta-analysis. We calculated Pearson correlations with 95% prediction interval (PI) between EPDS-9 and full EPDS total scores using a random effects model. Bivariate random-effects models were fitted to assess screening accuracy. Equivalence tests were done by comparing the confidence intervals (CIs) around the pooled sensitivity and specificity differences to the equivalence margin of δ = 0.05. Individual participant data were obtained from 41 eligible studies (10,906 participants, 1407 major depression cases). The correlation between EPDS-9 and full EPDS scores was 0.998 (95% PI 0.991, 0.999). For sensitivity, the EPDS-9 and full EPDS were equivalent for cut-offs 7-12 (difference range - 0.02, 0.01) and the equivalence was indeterminate for cut-offs 13-15 (all differences - 0.04). For specificity, the EPDS-9 and full EPDS were equivalent for all cut-offs (difference range 0.00, 0.01). The EPDS-9 performs similarly to the full EPDS and can be used when there are concerns about the implications of administering EPDS item 10.This study was funded by the Canadian Institutes of Health Research (CIHR, KRS-140994). Dr. Qiu was supported by a scholarship from the China Scholarship Council. Drs. Wu and Levis were supported by Fonds de recherche du Québec—Santé (FRQ-S) Postdoctoral Training Fellowships. Dr. Benedetti was supported by a Fonds de recherche du Québec – Santé (FRQS) researcher salary award. Dr. Thombs was supported by a Tier 1 Canada Research Chair. Ms. Rice was supported by a Vanier Canada Graduate Scholarship. The primary study by Alvarado et al. was supported by the Ministry of Health of Chile. The primary study by Barnes et al. was supported by a grant from the Health Foundation (1665/608). The primary study by Beck et al. was supported by the Patrick and Catherine Weldon Donaghue Medical Research Foundation and the University of Connecticut Research Foundation. The primary study by Helle et al. was supported by the Werner Otto Foundation, the Kroschke Foundation, and the Feindt Foundation. The primary study by Figueira et al. was supported by the Brazilian Ministry of Health and by the National Counsel of Technological and Scientific Development (CNPq) (Grant no.403433/2004-5). The primary study by Couto et al. was supported by the National Counsel of Technological and Scientific Development (CNPq) (Grant no. 444254/2014-5) and the Minas Gerais State Research Foundation (FAPEMIG) (Grant no. APQ-01954-14). The primary study by Chorwe-Sungani et al. was supported by the University of Malawi through grant QZA-0484 NORHED 2013. The primary study by de Figueiredo et al. was supported by Fundação de Amparo à Pesquisa do Estado de São Paulo. The primary study by Tissot et al. was supported by the Swiss National Science Foundation (grant 32003B 125493). The primary study by Fernandes et al. was supported by grants from the Child: Care Health and Development Trust and the Department of Psychiatry, University of Oxford, Oxford, UK, and by the Ashok Ranganathan Bursary from Exeter College, University of Oxford. Dr. Fernandes is supported by a University of Southampton National Institute for Health Research (NIHR) academic clinical fellowship in Paediatrics. The primary study by van Heyningen et al. was supported by the Medical Research Council of South Africa (fund no. 415865), Cordaid Netherlands (Project 103/10002 G Sub 7) and the Truworths Community Foundation Trust, South Africa. Dr. van Heyningen was supported by the National Research Foundation of South Africa and the Harry Crossley Foundation. VHYTHE001/1232209. The primary study by Tendais et al. was supported under the project POCI/SAU-ESP/56397/2004 by the Operational Program Science and Innovation 2010 (POCI 2010) of the Community Support Board III and by the European Community Fund FEDER. The primary study by Fisher et al. was supported by a grant under the Invest to Grow Scheme from the Australian Government Department of Families, Housing, Community Services and Indigenous Affairs. The primary study by Green et al. was supported by a grant from the Duke Global Health Institute (453-0751). The primary study by Howard et al. was supported by the National Institute for Health Research (NIHR) under its Programme Grants for Applied Research Programme (Grant Reference Numbers RP-PG-1210-12002 and RP-DG-1108-10012) and by the South London Clinical Research Network. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. The primary study by Kettunen et al. was supported with an Annual EVO Financing (Special government subsidies from the Ministry of Health and Welfare, Finland) by North Karelia Central Hospital and Päijät-Häme Central Hospital. The primary study by Phillips et al. was supported by a scholarship from the National Health and Medical and Research Council (NHMRC). The primary study by Roomruangwong et al. was supported by the Ratchadaphiseksomphot Endowment Fund 2013 of Chulalongkorn University (CU-56-457-HR). The primary study by Martínez et al. was supported by Iniciativa Científica Milenio, Chile, process # IS130005 and by Fondo Nacional de Desarrollo Científico y Tecnológico, Chile, process # 1130230. The primary study by Nakić Radoš et al. was supported by the Croatian Ministry of Science, Education, and Sports (134-0000000-2421). The primary study by Usuda et al. was supported by Grant-in-Aid for Young Scientists (A) from the Japan Society for the Promotion of Science (primary investigator: Daisuke Nishi, MD, PhD), and by an Intramural Research Grant for Neurological and Psychiatric Disorders from the National Center of Neurology and Psychiatry, Japan. The primary study by Pawlby et al. was supported by a Medical Research Council UK Project Grant (number G89292999N). The primary study by Rochat et al. was supported by grants from the University of Oxford (HQ5035), the Tuixen Foundation (9940), the Wellcome Trust (082384/Z/07/Z and 071571), and the American Psychological Association. Dr. Rochat receives salary support from a Wellcome Trust Intermediate Fellowship (211374/Z/18/Z). The primary study by Rowe et al. was supported by the diamond Consortium, beyondblue Victorian Centre of Excellence in Depression and Related Disorders. The primary study by Comasco et al. was supported by funds from the Swedish Research Council (VR: 521-2013-2339, VR:523-2014-2342), the Swedish Council for Working Life and Social Research (FAS: 2011-0627), the Marta Lundqvist Foundation (2013, 2014), and the Swedish Society of Medicine (SLS-331991). The primary study by Smith-Nielsen et al. was supported by a grant from the charitable foundation Tryg Foundation (Grant ID no 107616). The primary study by Prenoveau et al. was supported by The Wellcome Trust (grant number 071571). The primary study by Stewart et al. was supported by Professor Francis Creed’s Journal of Psychosomatic Research Editorship fund (BA00457) administered through University of Manchester. The primary study by Su et al. was supported by grants from the Department of Health (DOH94F044 and DOH95F022) and the China Medical University and Hospital (CMU94-105, DMR-92-92 and DMR94-46). The primary study by Tandon et al. was funded by the Thomas Wilson Sanitarium. The primary study by Tran et al. was supported by the Myer Foundation who funded the study under its Beyond Australia scheme. Dr. Tran was supported by an early career fellowship from the Australian National Health and Medical Research Council. The primary study by Vega-Dienstmaier et al. was supported by Tejada Family Foundation, Inc, and Peruvian-American Endowment, Inc. The primary study by Yonkers et al. was supported by a National Institute of Child Health and Human Development grant (5 R01HD045735). No other authors reported funding for primary studies or for their work on this study

Risk of bias assessments in individual participant data meta-analyses of test accuracy and prediction models:a review shows improvements are needed

OBJECTIVES: Risk of bias assessments are important in meta-analyses of both aggregate and individual participant data (IPD). There is limited evidence on whether and how risk of bias of included studies or datasets in IPD meta-analyses (IPDMAs) is assessed. We review how risk of bias is currently assessed, reported, and incorporated in IPDMAs of test accuracy and clinical prediction model studies and provide recommendations for improvement.STUDY DESIGN AND SETTING: We searched PubMed (January 2018-May 2020) to identify IPDMAs of test accuracy and prediction models, then elicited whether each IPDMA assessed risk of bias of included studies and, if so, how assessments were reported and subsequently incorporated into the IPDMAs.RESULTS: Forty-nine IPDMAs were included. Nineteen of 27 (70%) test accuracy IPDMAs assessed risk of bias, compared to 5 of 22 (23%) prediction model IPDMAs. Seventeen of 19 (89%) test accuracy IPDMAs used Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2), but no tool was used consistently among prediction model IPDMAs. Of IPDMAs assessing risk of bias, 7 (37%) test accuracy IPDMAs and 1 (20%) prediction model IPDMA provided details on the information sources (e.g., the original manuscript, IPD, primary investigators) used to inform judgments, and 4 (21%) test accuracy IPDMAs and 1 (20%) prediction model IPDMA provided information or whether assessments were done before or after obtaining the IPD of the included studies or datasets. Of all included IPDMAs, only seven test accuracy IPDMAs (26%) and one prediction model IPDMA (5%) incorporated risk of bias assessments into their meta-analyses. For future IPDMA projects, we provide guidance on how to adapt tools such as Prediction model Risk Of Bias ASsessment Tool (for prediction models) and QUADAS-2 (for test accuracy) to assess risk of bias of included primary studies and their IPD.CONCLUSION: Risk of bias assessments and their reporting need to be improved in IPDMAs of test accuracy and, especially, prediction model studies. Using recommended tools, both before and after IPD are obtained, will address this.</p

Accuracy of the Patient Health Questionnaire-9 for screening to detect major depression : updated systematic review and individual participant data meta-analysis

Objective: To update a previous individual participant data meta-analysis and determine the accuracy of the Patient Health Questionnaire-9 (PHQ-9), the most commonly used depression screening tool in general practice, for detecting major depression overall and by study or participant subgroups. Design: Systematic review and individual participant data meta-analysis. Data sources: Medline, Medline In-Process, and Other Non-Indexed Citations via Ovid, PsycINFO, Web of Science searched through 9 May 2018. Review methods: Eligible studies administered the PHQ-9 and classified current major depression status using a validated semistructured diagnostic interview (designed for clinician administration), fully structured interview (designed for lay administration), or the Mini International Neuropsychiatric Interview (MINI; a brief interview designed for lay administration). A bivariate random effects meta-analytic model was used to obtain point and interval estimates of pooled PHQ-9 sensitivity and specificity at cut-off values 5-15, separately, among studies that used semistructured diagnostic interviews (eg, Structured Clinical Interview for Diagnostic and Statistical Manual), fully structured interviews (eg, Composite International Diagnostic Interview), and the MINI. Meta-regression was used to investigate whether PHQ-9 accuracy correlated with reference standard categories and participant characteristics. Results: Data from 44 503 total participants (27 146 additional from the update) were obtained from 100 of 127 eligible studies (42 additional studies; 79% eligible studies; 86% eligible participants). Among studies with a semistructured interview reference standard, pooled PHQ-9 sensitivity and specificity (95% confidence interval) at the standard cut-off value of ≥10, which maximised combined sensitivity and specificity, were 0.85 (0.79 to 0.89) and 0.85 (0.82 to 0.87), respectively. Specificity was similar across reference standards, but sensitivity in studies with semistructured interviews was 7-24% (median 21%) higher than with fully structured reference standards and 2-14% (median 11%) higher than with the MINI across cut-off values. Across reference standards and cut-off values, specificity was 0-10% (median 3%) higher for men and 0-12 (median 5%) higher for people aged 60 or older. Conclusions: Researchers and clinicians could use results to determine outcomes, such as total number of positive screens and false positive screens, at different PHQ-9 cut-off values for different clinical settings using the knowledge translation tool at www.depressionscreening100.com/phq. Study registration: PROSPERO CRD42014010673