Comparison of major depression diagnostic classification probability using the SCID, CIDI, and MINI diagnostic interviews among women in pregnancy or postpartum: An individual participant data meta‐analysis

OBJECTIVES: A previous individual participant data meta-analysis (IPDMA) identified differences in major depression classification rates between different diagnostic interviews, controlling for depressive symptoms on the basis of the Patient Health Questionnaire-9. We aimed to determine whether similar results would be seen in a different population, using studies that administered the Edinburgh Postnatal Depression Scale (EPDS) in pregnancy or postpartum. METHODS: Data accrued for an EPDS diagnostic accuracy IPDMA were analysed. Binomial generalised linear mixed models were fit to compare depression classification odds for the Mini International Neuropsychiatric Interview (MINI), Composite International Diagnostic Interview (CIDI), and Structured Clinical Interview for DSM (SCID), controlling for EPDS scores and participant characteristics. RESULTS: Among fully structured interviews, the MINI (15 studies, 2,532 participants, 342 major depression cases) classified depression more often than the CIDI (3 studies, 2,948 participants, 194 major depression cases; adjusted odds ratio [aOR] = 3.72, 95% confidence interval [CI] [1.21, 11.43]). Compared with the semistructured SCID (28 studies, 7,403 participants, 1,027 major depression cases), odds with the CIDI (interaction aOR = 0.88, 95% CI [0.85, 0.92]) and MINI (interaction aOR = 0.95, 95% CI [0.92, 0.99]) increased less as EPDS scores increased. CONCLUSION: Different interviews may not classify major depression equivalently

Depression prevalence based on the Edinburgh Postnatal Depression Scale compared to Structured Clinical Interview for DSM DIsorders classification: systematic review and individual participant data meta‐analysis

Objectives: Estimates of depression prevalence in pregnancy and postpartum are based on the Edinburgh Postnatal Depression Scale (EPDS) more than on any other method. We aimed to determine if any EPDS cutoff can accurately and consistently estimate depression prevalence in individual studies. Methods: We analyzed datasets that compared EPDS scores to Structured Clinical Interview for DSM (SCID) major depression status. Random‐effects meta‐analysis was used to compare prevalence with EPDS cutoffs versus the SCID. Results: Seven thousand three hundred and fifteen participants (1017 SCID major depression) from 29 primary studies were included. For EPDS cutoffs used to estimate prevalence in recent studies (≥9 to ≥14), pooled prevalence estimates ranged from 27.8% (95% CI: 22.0%–34.5%) for EPDS ≥ 9 to 9.0% (95% CI: 6.8%–11.9%) for EPDS ≥ 14; pooled SCID major depression prevalence was 9.0% (95% CI: 6.5%–12.3%). EPDS ≥14 provided pooled prevalence closest to SCID‐based prevalence but differed from SCID prevalence in individual studies by a mean absolute difference of 5.1% (95% prediction interval: 13.7%, 12.3%). Conclusion: EPDS ≥14 approximated SCID‐based prevalence overall, but considerable heterogeneity in individual studies is a barrier to using it for prevalence estimation.This study was funded by the Canadian Institutes of Health Research (CIHR, KRS‐140994). Ms. Lyubenova was supported by the Mitacs Globalink Research Internship Program. Ms. Neupane was supported by G.R. Caverhill Fellowship from the Faculty of Medicine, McGill University. Drs. Levis and Wu were supported by Fonds de recherche du Québec‐Santé (FRQS) Postdoctoral Training Fellowships. Mr. Bhandari was supported by a studentship from the Research Institute of the McGill University Health Centre. Ms. Rice was supported by a Vanier Canada Graduate Scholarship. Ms. Azar was supported by a FRQS Masters Training Award. 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. Prof. Robertas Bunevicius, MD, PhD (1958‐2016) was Principal Investigator of the primary study by Bunevicius et al., but passed away and was unable to participate in this project. The primary study by Chaudron et al. was supported by a grant from the National Institute of Mental Health (grant K23 MH64476). The primary study by Tissot et al. was supported by the Swiss National Science Foundation (grant 32003B 125493). 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 Garcia‐Esteve et al. was supported by grant 7/98 from the Ministerio de Trabajo y Asuntos Sociales, Women's Institute, Spain. 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 Phillips et al. was supported by a scholarship from the National Health and Medical and Research Council (NHMRC). 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 Navarro et al. was supported by grant 13/00 from the Ministry of Work and Social Affairs, Institute of Women, Spain. The primary study by Pawlby et al. was supported by a Medical Research Council UK Project Grant (number G89292999N). The primary study by Quispel et al. was supported by Stichting Achmea Gezondheid (grant number z‐282). Dr. Robertson‐Blackmore was supported by a Young Investigator Award from the Brain and Behavior Research Foundation and NIMH grant K23MH080290. 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 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 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. Drs. Benedetti and Thombs were supported by FRQS researcher salary awards

Probability of major depression classification based on the SCID, CIDI, and MINI diagnostic interviews: A synthesis of three individual participant data meta-analyses

Introduction: Three previous individual 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. Objective: To compare the odds of the major depression classification based on the SCID, CIDI, and MINI. Methods: 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. Results: 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). Conclusions: 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.</p