ORCID Profile
0000-0003-4220-3378
Current Organisation
University Medical Center Hamburg-Eppendorf
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: Cambridge University Press (CUP)
Date: 12-07-2019
DOI: 10.1017/S0033291719001314
Abstract: Item 9 of the Patient Health Questionnaire-9 (PHQ-9) queries about thoughts of death and self-harm, but not suicidality. Although it is sometimes used to assess suicide risk, most positive responses are not associated with suicidality. The PHQ-8, which omits Item 9, is thus increasingly used in research. We assessed equivalency of total score correlations and the diagnostic accuracy to detect major depression of the PHQ-8 and PHQ-9. We conducted an in idual patient data meta-analysis. We fit bivariate random-effects models to assess diagnostic accuracy. 16 742 participants (2097 major depression cases) from 54 studies were included. The correlation between PHQ-8 and PHQ-9 scores was 0.996 (95% confidence interval 0.996 to 0.996). The standard cutoff score of 10 for the PHQ-9 maximized sensitivity + specificity for the PHQ-8 among studies that used a semi-structured diagnostic interview reference standard ( N = 27). At cutoff 10, the PHQ-8 was less sensitive by 0.02 (−0.06 to 0.00) and more specific by 0.01 (0.00 to 0.01) among those studies ( N = 27), with similar results for studies that used other types of interviews ( N = 27). For all 54 primary studies combined, across all cutoffs, the PHQ-8 was less sensitive than the PHQ-9 by 0.00 to 0.05 (0.03 at cutoff 10), and specificity was within 0.01 for all cutoffs (0.00 to 0.01). PHQ-8 and PHQ-9 total scores were similar. Sensitivity may be minimally reduced with the PHQ-8, but specificity is similar.
Publisher: Cambridge University Press (CUP)
Date: 19-08-2019
Publisher: JMIR Publications Inc.
Date: 09-06-2017
DOI: 10.2196/JMIR.7367
Publisher: SAGE Publications
Date: 30-01-2020
Abstract: Researchers increasingly use meta-analysis to synthesize the results of several studies in order to estimate a common effect. When the outcome variable is continuous, standard meta-analytic approaches assume that the primary studies report the s le mean and standard deviation of the outcome. However, when the outcome is skewed, authors sometimes summarize the data by reporting the s le median and one or both of (i) the minimum and maximum values and (ii) the first and third quartiles, but do not report the mean or standard deviation. To include these studies in meta-analysis, several methods have been developed to estimate the s le mean and standard deviation from the reported summary data. A major limitation of these widely used methods is that they assume that the outcome distribution is normal, which is unlikely to be tenable for studies reporting medians. We propose two novel approaches to estimate the s le mean and standard deviation when data are suspected to be non-normal. Our simulation results and empirical assessments show that the proposed methods often perform better than the existing methods when applied to non-normal data.
Publisher: Elsevier BV
Date: 12-2020
DOI: 10.1016/J.JPSYCHORES.2020.110256
Abstract: Validated diagnostic interviews are required to classify depression status and estimate prevalence of disorder, but screening tools are often used instead. We used in idual participant data meta-analysis to compare prevalence based on standard Hospital Anxiety and Depression Scale - depression subscale (HADS-D) cutoffs of ≥8 and ≥11 versus Structured Clinical Interview for DSM (SCID) major depression and determined if an alternative HADS-D cutoff could more accurately estimate prevalence. We searched Medline, Medline In-Process & Other Non-Indexed Citations via Ovid, PsycINFO, and Web of Science (inception-July 11, 2016) for studies comparing HADS-D scores to SCID major depression status. Pooled prevalence and pooled differences in prevalence for HADS-D cutoffs versus SCID major depression were estimated. 6005 participants (689 SCID major depression cases) from 41 primary studies were included. Pooled prevalence was 24.5% (95% Confidence Interval (CI): 20.5%, 29.0%) for HADS-D ≥8, 10.7% (95% CI: 8.3%, 13.8%) for HADS-D ≥11, and 11.6% (95% CI: 9.2%, 14.6%) for SCID major depression. HADS-D ≥11 was closest to SCID major depression prevalence, but the 95% prediction interval for the difference that could be expected for HADS-D ≥11 versus SCID in a new study was -21.1% to 19.5%. HADS-D ≥8 substantially overestimates depression prevalence. Of all possible cutoff thresholds, HADS-D ≥11 was closest to the SCID, but there was substantial heterogeneity in the difference between HADS-D ≥11 and SCID-based estimates. HADS-D should not be used as a substitute for a validated diagnostic interview.
Publisher: Elsevier BV
Date: 02-2020
DOI: 10.1016/J.JPSYCHORES.2019.109892
Abstract: Two previous in idual participant data meta-analyses (IPDMAs) found that different diagnostic interviews classify different proportions of people as having major depression overall or by symptom levels. We compared the odds of major depression classification across diagnostic interviews among studies that administered the Depression subscale of the Hospital Anxiety and Depression Scale (HADS-D). Data accrued for an IPDMA on HADS-D diagnostic accuracy were analysed. We fit binomial generalized linear mixed models to compare odds of major depression classification for the Structured Clinical Interview for DSM (SCID), Composite International Diagnostic Interview (CIDI), and Mini International Neuropsychiatric Interview (MINI), controlling for HADS-D scores and participant characteristics with and without an interaction term between interview and HADS-D scores. There were 15,856 participants (1942 [12%] with major depression) from 73 studies, including 15,335 (97%) non-psychiatric medical patients, 164 (1%) partners of medical patients, and 357 (2%) healthy adults. The MINI (27 studies, 7345 participants, 1066 major depression cases) classified participants as having major depression more often than the CIDI (10 studies, 3023 participants, 269 cases) (adjusted odds ratio [aOR] = 1.70 (0.84, 3.43)) and the semi-structured SCID (36 studies, 5488 participants, 607 cases) (aOR = 1.52 (1.01, 2.30)). The odds ratio for major depression classification with the CIDI was less likely to increase as HADS-D scores increased than for the SCID (interaction aOR = 0.92 (0.88, 0.96)). Compared to the SCID, the MINI may diagnose more participants as having major depression, and the CIDI may be less responsive to symptom severity.
Publisher: S. Karger AG
Date: 02-09-2031
DOI: 10.1159/000509283
Abstract: b i Introduction: /i /b Three previous in idual participant data meta-analyses (IPDMAs) reported that, compared to the Structured Clinical Interview for the DSM (SCID), alternative reference standards, primarily the Composite International Diagnostic Interview (CIDI) and the Mini International Neuropsychiatric Interview (MINI), tended to misclassify major depression status, when controlling for depression symptom severity. However, there was an important lack of precision in the results. b i Objective: /i /b To compare the odds of the major depression classification based on the SCID, CIDI, and MINI. b i Methods: /i /b We included and standardized data from 3 IPDMA databases. For each IPDMA, separately, we fitted binomial generalized linear mixed models to compare the adjusted odds ratios (aORs) of major depression classification, controlling for symptom severity and characteristics of participants, and the interaction between interview and symptom severity. Next, we synthesized results using a DerSimonian-Laird random-effects meta-analysis. b i Results: /i /b In total, 69,405 participants (7,574 [11%] with major depression) from 212 studies were included. Controlling for symptom severity and participant characteristics, the MINI (74 studies 25,749 participants) classified major depression more often than the SCID (108 studies 21,953 participants aOR 1.46 95% confidence interval [CI] 1.11–1.92]). Classification odds for the CIDI (30 studies 21,703 participants) and the SCID did not differ overall (aOR 1.19 95% CI 0.79–1.75) however, as screening scores increased, the aOR increased less for the CIDI than the SCID (interaction aOR 0.64 95% CI 0.52–0.80). b i Conclusions: /i /b Compared to the SCID, the MINI classified major depression more often. The odds of the depression classification with the CIDI increased less as symptom levels increased. Interpretation of research that uses diagnostic interviews to classify depression should consider the interview characteristics.
Publisher: Elsevier BV
Date: 06-2020
DOI: 10.1016/J.JCLINEPI.2020.02.002
Abstract: Depression symptom questionnaires are not for diagnostic classification. Patient Health Questionnaire-9 (PHQ-9) scores ≥10 are nonetheless often used to estimate depression prevalence. We compared PHQ-9 ≥10 prevalence to Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders (SCID) major depression prevalence and assessed whether an alternative PHQ-9 cutoff could more accurately estimate prevalence. In idual participant data meta-analysis of datasets comparing PHQ-9 scores to SCID major depression status. A total of 9,242 participants (1,389 SCID major depression cases) from 44 primary studies were included. Pooled PHQ-9 ≥10 prevalence was 24.6% (95% confidence interval [CI]: 20.8%, 28.9%) pooled SCID major depression prevalence was 12.1% (95% CI: 9.6%, 15.2%) and pooled difference was 11.9% (95% CI: 9.3%, 14.6%). The mean study-level PHQ-9 ≥10 to SCID-based prevalence ratio was 2.5 times. PHQ-9 ≥14 and the PHQ-9 diagnostic algorithm provided prevalence closest to SCID major depression prevalence, but study-level prevalence differed from SCID-based prevalence by an average absolute difference of 4.8% for PHQ-9 ≥14 (95% prediction interval: -13.6%, 14.5%) and 5.6% for the PHQ-9 diagnostic algorithm (95% prediction interval: -16.4%, 15.0%). PHQ-9 ≥10 substantially overestimates depression prevalence. There is too much heterogeneity to correct statistically in in idual studies.
Publisher: Wiley
Date: 16-10-2016
DOI: 10.1002/MPR.1530
Publisher: S. Karger AG
Date: 08-10-2019
DOI: 10.1159/000502294
Abstract: b i Background: /i /b 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. b i Objective: /i /b To use an in idual 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. b i Methods: /i /b 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. b i Results: /i /b Data were included for 54 of 72 identified eligible studies ( i n /i participants = 16,688, i n /i 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). b i Conclusions: /i /b The cutoff score approach appears to be a better option than a PHQ-9 algorithm for detecting major depression.
No related grants have been discovered for Bernd Löwe.