Dataset Information

The Accuracy of the Patient Health Questionnaire-9 Algorithm for Screening to Detect Major Depression: An Individual Participant Data Meta-Analysis.

ABSTRACT:

Background

Screening for major depression with the Patient Health Questionnaire-9 (PHQ-9) can be done using a cutoff or the PHQ-9 diagnostic algorithm. Many primary studies publish results for only one approach, and previous meta-analyses of the algorithm approach included only a subset of primary studies that collected data and could have published results.

Objective

To use an individual participant data meta-analysis to evaluate the accuracy of two PHQ-9 diagnostic algorithms for detecting major depression and compare accuracy between the algorithms and the standard PHQ-9 cutoff score of ?10.

Methods

Medline, Medline In-Process and Other Non-Indexed Citations, PsycINFO, Web of Science (January 1, 2000, to February 7, 2015). Eligible studies that classified current major depression status using a validated diagnostic interview.

Results

Data were included for 54 of 72 identified eligible studies (n participants = 16,688, n cases = 2,091). Among studies that used a semi-structured interview, pooled sensitivity and specificity (95% confidence interval) were 0.57 (0.49, 0.64) and 0.95 (0.94, 0.97) for the original algorithm and 0.61 (0.54, 0.68) and 0.95 (0.93, 0.96) for a modified algorithm. Algorithm sensitivity was 0.22-0.24 lower compared to fully structured interviews and 0.06-0.07 lower compared to the Mini International Neuropsychiatric Interview. Specificity was similar across reference standards. For PHQ-9 cutoff of ?10 compared to semi-structured interviews, sensitivity and specificity (95% confidence interval) were 0.88 (0.82-0.92) and 0.86 (0.82-0.88).

Conclusions

The cutoff score approach appears to be a better option than a PHQ-9 algorithm for detecting major depression.

SUBMITTER: He C

PROVIDER: S-EPMC6960351 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

The Accuracy of the Patient Health Questionnaire-9 Algorithm for Screening to Detect Major Depression: An Individual Participant Data Meta-Analysis.

He Chen C Levis Brooke B Riehm Kira E KE Saadat Nazanin N Levis Alexander W AW Azar Marleine M Rice Danielle B DB Krishnan Ankur A Wu Yin Y Sun Ying Y Imran Mahrukh M Boruff Jill J Cuijpers Pim P Gilbody Simon S Ioannidis John P A JPA Kloda Lorie A LA McMillan Dean D Patten Scott B SB Shrier Ian I Ziegelstein Roy C RC Akena Dickens H DH Arroll Bruce B Ayalon Liat L Baradaran Hamid R HR Baron Murray M Beraldi Anna A Bombardier Charles H CH Butterworth Peter P Carter Gregory G Chagas Marcos Hortes Nisihara MHN Chan Juliana C N JCN Cholera Rushina R Clover Kerrie K Conwell Yeates Y de Man-van Ginkel Janneke M JM Fann Jesse R JR Fischer Felix H FH Fung Daniel D Gelaye Bizu B Goodyear-Smith Felicity F Greeno Catherine G CG Hall Brian J BJ Harrison Patricia A PA Härter Martin M Hegerl Ulrich U Hides Leanne L Hobfoll Stevan E SE Hudson Marie M Hyphantis Thomas N TN Inagaki Masatoshi M Ismail Khalida K Jetté Nathalie N Khamseh Mohammad E ME Kiely Kim M KM Kwan Yunxin Y Lamers Femke F Liu Shen-Ing SI Lotrakul Manote M Loureiro Sonia R SR Löwe Bernd B Marsh Laura L McGuire Anthony A Mohd-Sidik Sherina S Munhoz Tiago N TN Muramatsu Kumiko K Osório Flávia L FL Patel Vikram V Pence Brian W BW Persoons Philippe P Picardi Angelo A Reuter Katrin K Rooney Alasdair G AG da Silva Dos Santos Iná S IS Shaaban Juwita J Sidebottom Abbey A Simning Adam A Stafford Lesley L Sung Sharon S Tan Pei Lin Lynnette PLL Turner Alyna A van Weert Henk C P M HCPM White Jennifer J Whooley Mary A MA Winkley Kirsty K Yamada Mitsuhiko M Thombs Brett D BD Benedetti Andrea A

Psychotherapy and psychosomatics 20191008 1

<h4>Background</h4>Screening for major depression with the Patient Health Questionnaire-9 (PHQ-9) can be done using a cutoff or the PHQ-9 diagnostic algorithm. Many primary studies publish results for only one approach, and previous meta-analyses of the algorithm approach included only a subset of primary studies that collected data and could have published results.<h4>Objective</h4>To use an individual participant data meta-analysis to evaluate the accuracy of two PHQ-9 diagnostic algorithms fo ...[more]

PMID: 31593971

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Project description:ObjectiveTo determine the accuracy of the Patient Health Questionnaire-9 (PHQ-9) for screening to detect major depression.DesignIndividual participant data meta-analysis.Data sourcesMedline, Medline In-Process and Other Non-Indexed Citations, PsycINFO, and Web of Science (January 2000-February 2015).Inclusion criteriaEligible studies compared PHQ-9 scores with major depression diagnoses from validated diagnostic interviews. Primary study data and study level data extracted from primary reports were synthesized. For PHQ-9 cut-off scores 5-15, bivariate random effects meta-analysis was used to estimate pooled sensitivity and specificity, separately, among studies that used semistructured diagnostic interviews, which are designed for administration by clinicians; fully structured interviews, which are designed for lay administration; and the Mini International Neuropsychiatric (MINI) diagnostic interviews, a brief fully structured interview. Sensitivity and specificity were examined among participant subgroups and, separately, using meta-regression, considering all subgroup variables in a single model.ResultsData were obtained for 58 of 72 eligible studies (total n=17 357; major depression cases n=2312). Combined sensitivity and specificity was maximized at a cut-off score of 10 or above among studies using a semistructured interview (29 studies, 6725 participants; sensitivity 0.88, 95% confidence interval 0.83 to 0.92; specificity 0.85, 0.82 to 0.88). Across cut-off scores 5-15, sensitivity with semistructured interviews was 5-22% higher than for fully structured interviews (MINI excluded; 14 studies, 7680 participants) and 2-15% higher than for the MINI (15 studies, 2952 participants). Specificity was similar across diagnostic interviews. The PHQ-9 seems to be similarly sensitive but may be less specific for younger patients than for older patients; a cut-off score of 10 or above can be used regardless of age..ConclusionsPHQ-9 sensitivity compared with semistructured diagnostic interviews was greater than in previous conventional meta-analyses that combined reference standards. A cut-off score of 10 or above maximized combined sensitivity and specificity overall and for subgroups.RegistrationPROSPERO CRD42014010673.

Project description:ObjectiveTo 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.DesignSystematic review and individual participant data meta-analysis.Data sourcesMedline, Medline In-Process, and Other Non-Indexed Citations via Ovid, PsycINFO, Web of Science searched through 9 May 2018.Review methodsEligible 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.ResultsData 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.ConclusionsResearchers 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 registrationPROSPERO CRD42014010673.

Project description:OBJECTIVE:To evaluate the Edinburgh Postnatal Depression Scale (EPDS) for screening to detect major depression in pregnant and postpartum women. DESIGN:Individual participant data meta-analysis. DATA SOURCES:Medline, Medline In-Process and Other Non-Indexed Citations, PsycINFO, and Web of Science (from inception to 3 October 2018). ELIGIBILITY CRITERIA FOR SELECTING STUDIES:Eligible datasets included EPDS scores and major depression classification based on validated diagnostic interviews. Bivariate random effects meta-analysis was used to estimate EPDS sensitivity and specificity compared with semi-structured, fully structured (Mini International Neuropsychiatric Interview (MINI) excluded), and MINI diagnostic interviews separately using individual participant data. One stage meta-regression was used to examine accuracy by reference standard categories and participant characteristics. RESULTS:Individual participant data were obtained from 58 of 83 eligible studies (70%; 15?557 of 22?788 eligible participants (68%), 2069 with major depression). Combined sensitivity and specificity was maximised at a cut-off value of 11 or higher across reference standards. Among studies with a semi-structured interview (36 studies, 9066 participants, 1330 with major depression), sensitivity and specificity were 0.85 (95% confidence interval 0.79 to 0.90) and 0.84 (0.79 to 0.88) for a cut-off value of 10 or higher, 0.81 (0.75 to 0.87) and 0.88 (0.85 to 0.91) for a cut-off value of 11 or higher, and 0.66 (0.58 to 0.74) and 0.95 (0.92 to 0.96) for a cut-off value of 13 or higher, respectively. Accuracy was similar across reference standards and subgroups, including for pregnant and postpartum women. CONCLUSIONS:An EPDS cut-off value of 11 or higher maximised combined sensitivity and specificity; a cut-off value of 13 or higher was less sensitive but more specific. To identify pregnant and postpartum women with higher symptom levels, a cut-off of 13 or higher could be used. Lower cut-off values could be used if the intention is to avoid false negatives and identify most patients who meet diagnostic criteria. REGISTRATION:PROSPERO (CRD42015024785).

Project description: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.Trial registration: The original IPDMA was registered in PROSPERO (CRD42015024785).

Project description:ObjectiveTo 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.DesignSystematic review and individual participant data meta-analysis.Data sourcesMedline, Medline In-Process and Other Non-Indexed Citations, PsycInfo, and Web of Science (from inception to 25 October 2018).Review methodsEligible 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.ResultsIndividual 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.ConclusionsWhen 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 registrationPROSPERO CRD42015016761.

Project description:IntroductionThe 30-item Geriatric Depression Scale (GDS-30) and the shorter GDS-15, GDS-5 and GDS-4 are recommended as depression screening tools for elderly individuals. Existing meta-analyses on the diagnostic accuracy of the GDS have not been able to conduct subgroup analyses, have included patients already identified as depressed who would not be screened in practice and have not accounted for possible bias due to selective reporting of results from only better-performing cut-offs in primary studies. Individual participant data meta-analysis (IPDMA), which involves a standard systematic review, then a synthesis of individual participant data, rather than summary results, could address these limitations. The objective of our IPDMA is to generate accuracy estimates to detect major depression for all possible cut-offs of each version of the GDS among studies using different reference standards, separately and among participant subgroups based on age, sex, dementia diagnosis and care settings. In addition, we will use a modelling approach to generate individual participant probabilities for major depression based on GDS scores (rather than a dichotomous cut-off) and participant characteristics (eg, sex, age, dementia status, care setting).Methods and analysisIndividual participant data comparing GDS scores to a major depression diagnosis based on a validated structured or semistructured diagnostic interview will be sought via a systematic review. Data sources will include Medline, Medline In-Process & Other Non-Indexed Citations, PsycINFO and Web of Science. Bivariate random-effects models will be used to estimate diagnostic accuracy parameters for each cut-off of the different versions of the GDS. Prespecified subgroup analyses will be conducted. Risk of bias will be assessed with the Quality Assessment of Diagnostic Accuracy Studies-2 tool.Ethics and disseminationThe findings of this study will be of interest to stakeholders involved in research, clinical practice and policy.Prospero registration numberCRD42018104329.

Dataset Information

The Accuracy of the Patient Health Questionnaire-9 Algorithm for Screening to Detect Major Depression: An Individual Participant Data Meta-Analysis.

Background

Objective

Methods

Results

Conclusions

Publications

The Accuracy of the Patient Health Questionnaire-9 Algorithm for Screening to Detect Major Depression: An Individual Participant Data Meta-Analysis.

Similar Datasets

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