Selective Cutoff Reporting in Studies of Diagnostic Test Accuracy: A Comparison of Conventional and Individual-Patient-Data Meta-Analyses of the Patient Health Questionnaire-9 Depression Screening Tool

Diagnostic test accuracy of the Fungitell serum (1→3)-β-D-glucan assay for the diagnosis of Pneumocystis jirovecii pneumonia: a systematic review and meta-analysis

BACKGROUND

The diagnosis of Pneumocystis jirovecii pneumonia (PCP) can be challenging because of diagnostic tests that are imperfect and/or invasive. The Fungitell serum (1 → 3)-β-D-glucan (BDG) assay is a noninvasive blood test studied for PCP; however, the manufacturer-recommended cut-off of 80 pg/mL is not well validated for this disease.

OBJECTIVES

We conducted a systematic review and meta-analysis to determine the diagnostic test accuracy of the Fungitell BDG assay for the diagnosis of PCP.

METHODS

.

DATA SOURCES

A search strategy of MEDLINE and Embase from a previous meta-analysis on BDG was updated to 31 January 2024.

STUDY ELIGIBILITY CRITERIA

Observational studies.

PARTICIPANTS

Patients with risk factors for PCP. TEST: Fungitell BDG assay.

REFERENCE STANDARD

One or more of lung biopsy, bronchoalveolar lavage, induced sputum, or nasopharyngeal swab specimens tested for PCP by histopathology, microscopy using immunofluorescence or staining, or PCR.

ASSESSMENT OF RISK OF BIAS

The Quality Assessment of Diagnostic Accuracy Studies-2 tool.

METHODS OF DATA SYNTHESIS

Diagnostic test accuracy data of the Fungitell serum BDG assay across all reported cut-offs were pooled by meta-analysis. We then evaluated a categorical approach using <80 pg/mL as a rule-out threshold and ≥400 pg/mL as a rule-in threshold.

RESULTS

A total of 26 articles were included comprising 5111 patients and 1150 PCP cases. At the conventional cut-off of 80 pg/mL, the overall pooled sensitivity and specificity were 83.5% (95% 95% CI, 72.8-90.6) and 75.5% (95% CI, 66.0-83.0), respectively. At a pretest probability of <20% and a BDG <80 pg/mL, the post-test probability would be <5% (negative predictive value > 95%). At 400 pg/mL, sensitivity was reduced to 63.5% (95% CI, 45.8-78.1) with specificity increased to 93.6% (95% CI, 88.6-96.5). At a pretest probability of 47.5%, a BDG >400 pg/mL would have a post-test probability of >90%.

DISCUSSION

A categorical approach using <80 pg/mL to rule-out and >400 pg/mL to rule-in PCP may allow for a more nuanced interpretation based on pretest probability. More accurate estimates of pretest probability and further external validation are required.

Ethical Issues and Challenges Regarding the Use of Mental Health Questionnaires in Public Health Nutrition Research

BACKGROUND

The use of mental health questionnaires is common in desk-based public health epidemiological research; however, the burden this might put on participants and researchers has been questioned and has not been previously addressed. This paper delves into the ethical issues and challenges of using such scales and questionnaires, providing a real-life case study where the Beck's Depression Inventory-II was used.

METHODS/RESULTS

The ethical considerations raised by using mental health questionnaires in public health epidemiological research include incorrectly identifying participants as depressed or non-depressed; inability to identify participants for referral procedures due to the anonymous nature of some research studies; an increased burden on participants through depression and suicidal questions; and the high expectation of participants towards the researcher. Preventative measures to reduce these challenges include choosing appropriate cut-off scores for correctly identifying participants; highlighting whether the mental health questionnaires used may elicit negative emotional or psychological reactions related to suicidality; specifying the criteria for referral to clinical services; detailing the intended referral processes; including approaches where the researcher directly connects participants with a psychological service provider; and including a passive referral method such as contact details for participants to initiate their own referrals to clinical care.

CONCLUSIONS

This paper serves as a guide for researchers aiming to collect data on mental health through questionnaires. The ethical challenges discussed in this paper should be considered and reviewed at all stages of the research project.

2. Types of data and data collation for efficient processing

ABSTRACT

Data are the soul of most empirical research. Adequate data collection and their proper collation are essential to arrive at right conclusions. These conclusions are mostly drawn from the statistical analysis of properly collated data. Since the methods of statistical analysis are different for different types of data, a clear understanding of various types of data is necessary for their efficient processing. Whereas broad types of data-quantitative and qualitative-are well known, some researchers struggle with the proper collation of ordinal data and quantitative categories. Additionally, some young researchers need guidance on preparing tables to communicate their results effectively. Graphics add muscles to the skeleton of data and need to be judiciously chosen. This article provides details of various types of data, their adequacy, and their proper collation, including a brief on tables and graphics. Almost all medical researchers carry out these activities - thus, this may have wide ramifications. Although this article primarily targets postgraduate students and young researchers, our interaction with a diverse group of researchers suggests that many experienced researchers may also find this article useful in the management of their data for reaching the right conclusions.

Data-Driven Cutoff Selection for the Patient Health Questionnaire-9 Depression Screening Tool

Importance

Test accuracy studies often use small datasets to simultaneously select an optimal cutoff score that maximizes test accuracy and generate accuracy estimates.

Objective

To evaluate the degree to which using data-driven methods to simultaneously select an optimal Patient Health Questionnaire-9 (PHQ-9) cutoff score and estimate accuracy yields (1) optimal cutoff scores that differ from the population-level optimal cutoff score and (2) biased accuracy estimates.

Design, Setting, and Participants

This study used cross-sectional data from an existing individual participant data meta-analysis (IPDMA) database on PHQ-9 screening accuracy to represent a hypothetical population. Studies in the IPDMA database compared participant PHQ-9 scores with a major depression classification. From the IPDMA population, 1000 studies of 100, 200, 500, and 1000 participants each were resampled.

Main Outcomes and Measures

For the full IPDMA population and each simulated study, an optimal cutoff score was selected by maximizing the Youden index. Accuracy estimates for optimal cutoff scores in simulated studies were compared with accuracy in the full population.

Results

The IPDMA database included 100 primary studies with 44 503 participants (4541 [10%] cases of major depression). The population-level optimal cutoff score was 8 or higher. Optimal cutoff scores in simulated studies ranged from 2 or higher to 21 or higher in samples of 100 participants and 5 or higher to 11 or higher in samples of 1000 participants. The percentage of simulated studies that identified the true optimal cutoff score of 8 or higher was 17% for samples of 100 participants and 33% for samples of 1000 participants. Compared with estimates for a cutoff score of 8 or higher in the population, sensitivity was overestimated by 6.4 (95% CI, 5.7-7.1) percentage points in samples of 100 participants, 4.9 (95% CI, 4.3-5.5) percentage points in samples of 200 participants, 2.2 (95% CI, 1.8-2.6) percentage points in samples of 500 participants, and 1.8 (95% CI, 1.5-2.1) percentage points in samples of 1000 participants. Specificity was within 1 percentage point across sample sizes.

Conclusions and Relevance

This study of cross-sectional data found that optimal cutoff scores and accuracy estimates differed substantially from population values when data-driven methods were used to simultaneously identify an optimal cutoff score and estimate accuracy. Users of diagnostic accuracy evidence should evaluate studies of accuracy with caution and ensure that cutoff score recommendations are based on adequately powered research or well-conducted meta-analyses.

Two-Step Screening for Depression and Anxiety in Patients with Cancer: A Retrospective Validation Study Using Real-World Data

Background: Although screening for distress is recommended by many cancer care guidelines, the uptake of such screening in cancer centers remains limited. Improving the acceptability of screening programs in cancer centers requires a reduction in clinical burden and an improved detection of distress. The purpose of this study was to validate the performance of the two-step screening algorithm used in the Distress Assessment and Response Tool (DART) for identifying cases of anxiety and depression. Methods: This retrospective validation study consisted of patients at the Princess Margaret Cancer Centre (PM) who completed the DART, which includes the Edmonton Symptom Assessment System depression (ESAS-D) and anxiety (ESAS-A) items, the Patient Health Questionnaire (PHQ-9), and the Generalized Anxiety Disorder (GAD-7). We evaluated the performance of a two-step screening approach, which modeled the ESAS-D, followed by the PHQ-9 and ESAS-A, then the GAD-7 for predicting a diagnosis of depression and anxiety disorders, respectively. A clinical psychiatric assessment was used as the gold standard reference. Results: A total of 172 patients with cancer were included in this study. A total of 59/172 (34%) and 39/172 (23%) were diagnosed with a depression or anxiety disorder, respectively. The sequential administration of the PHQ-9 ≥15 following the ESAS-D (>2) significantly increased the post-test probability of depression from 37% to 60% and improved the performance of predicting depression compared to both the ESAS-D or the PHQ-9 as standalone tests. The sequential administration of the GAD-7 after the ESAS-A did not improve the predictability of an anxiety diagnosis beyond the performance of the ESAS-A or the GAD-7 as standalone tests. Conclusions: The present study is among the first to demonstrate that a two-step screening algorithm for depression may improve depression screening in cancer using real-world data. Further research on optimal screening approaches for anxiety in cancer is warranted.

Prevalence and associated factors for depressive symptoms among the general population from 31 provinces in China: The utility of social determinants of health theory

BACKGROUND

Depression is one of the most common types of mental disorders. Guided by the theory of social determinants of health (SDH), the study aimed to assess the prevalence of depressive symptoms and to identify factors related to depressive symptoms in the general population of China.

METHODS

A cross-sectional, online survey was conducted among 101,392 residents from 31 provinces of mainland China from January to March 2019, and 97,126 survey responses were included in the final analysis. Multilevel linear regression models were used to identify SDH associated with depressive symptoms.

RESULTS

The prevalence of depressive symptoms (PHQ-9 scores ≥10) in Chinese residents was 15.81 %. The results of the multilevel analysis demonstrated that depressive symptoms were affected by various factors on five levels, including individual characteristics, behavioral lifestyle, community support network, social structural factors, and macro social factors.

LIMITATIONS

The cross-sectional design of the study makes it difficult to establish causality between variables.

CONCLUSIONS

The prevalence of depressive symptoms is high among general population in China. According to the theory of SDH, the study shows that the depressive symptoms are complex and involves all areas of social life. Therefore, adopting a multi-level, cross-sectoral intervention approach will be instrumental to improving the mental health of residents in China.

An empirical comparison of statistical methods for multiple cut-off diagnostic test accuracy meta-analysis of the Edinburgh postnatal depression scale (EPDS) depression screening tool using published results vs individual participant data

BACKGROUND

Selective reporting of results from only well-performing cut-offs leads to biased estimates of accuracy in primary studies of questionnaire-based screening tools and in meta-analyses that synthesize results. Individual participant data meta-analysis (IPDMA) of sensitivity and specificity at each cut-off via bivariate random-effects models (BREMs) can overcome this problem. However, IPDMA is laborious and depends on the ability to successfully obtain primary datasets, and BREMs ignore the correlation between cut-offs within primary studies.

METHODS

We compared the performance of three recent multiple cut-off models developed by Steinhauser et al., Jones et al., and Hoyer and Kuss, that account for missing cut-offs when meta-analyzing diagnostic accuracy studies with multiple cut-offs, to BREMs fitted at each cut-off. We used data from 22 studies of the accuracy of the Edinburgh Postnatal Depression Scale (EPDS; 4475 participants, 758 major depression cases). We fitted each of the three multiple cut-off models and BREMs to a dataset with results from only published cut-offs from each study (published data) and an IPD dataset with results for all cut-offs (full IPD data). We estimated pooled sensitivity and specificity with 95% confidence intervals (CIs) for each cut-off and the area under the curve.

RESULTS

Compared to the BREMs fitted to the full IPD data, the Steinhauser et al., Jones et al., and Hoyer and Kuss models fitted to the published data produced similar receiver operating characteristic curves; though, the Hoyer and Kuss model had lower area under the curve, mainly due to estimating slightly lower sensitivity at lower cut-offs. When fitting the three multiple cut-off models to the full IPD data, a similar pattern of results was observed. Importantly, all models had similar 95% CIs for sensitivity and specificity, and the CI width increased with cut-off levels for sensitivity and decreased with an increasing cut-off for specificity, even the BREMs which treat each cut-off separately.

CONCLUSIONS

Multiple cut-off models appear to be the favorable methods when only published data are available. While collecting IPD is expensive and time consuming, IPD can facilitate subgroup analyses that cannot be conducted with published data only.

Patient Health Questionnaire-9 Item Pairing Predictiveness for Prescreening Depressive Symptomatology: Machine Learning Analysis

BACKGROUND

Anhedonia and depressed mood are considered the cardinal symptoms of major depressive disorder. These are the first 2 items of the Patient Health Questionnaire (PHQ)-9 and comprise the ultrabrief PHQ-2 used for prescreening depressive symptomatology. The prescreening performance of alternative PHQ-9 item pairings is rarely compared with that of the PHQ-2.

OBJECTIVE

This study aims to use machine learning (ML) with the PHQ-9 items to identify and validate the most predictive 2-item depressive symptomatology ultrabrief questionnaire and to test the generalizability of the best pairings found on the primary data set, with 6 external data sets from different populations to validate their use as prescreening instruments.

METHODS

All 36 possible PHQ-9 item pairings (each yielding scores of 0-6) were investigated using ML-based methods with logistic regression models. Their performances were evaluated based on the classification of depressive symptomatology, defined as PHQ-9 scores ≥10. This gave each pairing an equal opportunity and avoided any bias in item pairing selection.

RESULTS

The ML-based PHQ-9 items 2 and 4 (phq2&4), the depressed mood and low-energy item pairing, and PHQ-9 items 2 and 8 (phq2&8), the depressed mood and psychomotor retardation or agitation item pairing, were found to be the best on the primary data set training split. They generalized well on the primary data set test split with area under the curves (AUCs) of 0.954 and 0.946, respectively, compared with an AUC of 0.942 for the PHQ-2. The phq2&4 had a higher AUC than the PHQ-2 on all 6 external data sets, and the phq2&8 had a higher AUC than the PHQ-2 on 3 data sets. The phq2&4 had the highest Youden index (an unweighted average of sensitivity and specificity) on 2 external data sets, and the phq2&8 had the highest Youden index on another 2. The PHQ-2≥2 cutoff also had the highest Youden index on 2 external data sets, joint highest with the phq2&4 on 1, but its performance fluctuated the most. The PHQ-2≥3 cutoff had the highest Youden index on 1 external data set. The sensitivity and specificity achieved by the phq2&4 and phq2&8 were more evenly balanced than the PHQ-2≥2 and ≥3 cutoffs.

CONCLUSIONS

The PHQ-2 did not prove to be a more effective prescreening instrument when compared with other PHQ-9 item pairings. Evaluating all item pairings showed that, compared with alternative partner items, the anhedonia item underperformed alongside the depressed mood item. This suggests that the inclusion of anhedonia as a core symptom of depression and its presence in ultrabrief questionnaires may be incompatible with the empirical evidence. The use of the PHQ-2 to prescreen for depressive symptomatology could result in a greater number of misclassifications than alternative item pairings.

Depression screening tool accuracy individual participant data meta-analyses: data contribution was associated with multiple factors

OBJECTIVES

To examine the proportion of eligible primary studies that contributed data, study characteristics associated with data contribution, and reasons for noncontribution using diagnostic test accuracy Individual Participant Data Meta-Analysis (IPDMA) data sets from the DEPRESsion Screening Data project.

STUDY DESIGN AND SETTING

We reviewed data set contributions from four IPDMAs. A multivariable logistic regression model was fitted to evaluate study factors associated with data contribution.

RESULTS

Of 456 eligible studies from four included IPDMAs, 295 (65%) contributed data. More recent year of publication and higher journal impact factor were associated with greater odds of data contribution. Studies conducted in Europe (excluding the United Kingdom), Oceania, Canada, the Middle East, Africa, and Central or South America (reference = the United States), that have recruitment from inpatient care or nonmedical settings (reference = outpatient), that reported screening accuracy results, or that drew negative conclusions (reference = positive conclusions) were more likely to contribute data. Studies of the Geriatric Depression Scale (reference = the Patient Health Questionnaire) or lacking funding information were negatively associated with data contribution. Over 80% of noncontributions were due to authors being unreachable or data being unavailable.

CONCLUSION

The study identified factors associated with data contribution that may support future research to promote data contribution to IPDMAs.

Utility of PHQ-2, PHQ-8 and PHQ-9 for detecting major depression in primary health care: a validation study in Spain

BACKGROUND

Primary health care (PHC) professionals may play a crucial role in improving early diagnosis of depressive disorders. However, only 50% of cases are detected in PHC. The most widely used screening instrument for major depression is the Patient Health Questionnaire (PHQ), including the two-, eight- and nine-item versions. Surprisingly, there is neither enough evidence about the validity of PHQ in PHC patients in Spain nor indications about how to interpret the total scores. This study aimed to gather validity evidence to support the use of the three PHQ versions to screen for major depression in PHC in Spain. Additionally, the present study provided information for helping professionals to choose the best PHQ version according to the context.

METHODS

The sample was composed of 2579 participants from 22 Spanish PHC centers participating in the EIRA-3 study. The reliability and validity of the three PHQ versions for Spanish PHC patients were assessed based on responses to the questionnaire.

RESULTS

The PHQ-8 and PHQ-9 showed high internal consistency. The results obtained confirm the theoretically expected relationship between PHQ results and anxiety, social support and health-related QoL. A single-factor solution was confirmed. Regarding to the level of agreement with the CIDI interview (used as the criterion), our results indicate that the PHQ has a good discrimination power. The optimal cut-off values were: ⩾2 for PHQ-2, ⩾7 for PHQ-8 and ⩾8 for PHQ-9.

CONCLUSIONS

PHQ is a good and valuable tool for detecting major depression in PHC patients in Spain.

How to Critically Appraise and Interpret Systematic Reviews and Meta-Analyses of Diagnostic Accuracy: A User Guide

Systematic reviews of diagnostic accuracy studies can provide the best available evidence to inform decisions regarding the use of a diagnostic test. In this guide, the authors provide a practical approach for clinicians to appraise diagnostic accuracy systematic reviews and apply their results to patient care. The first step is to identify an appropriate systematic review with a research question matching the clinical scenario. The user should evaluate the rigor of the review methods to evaluate its credibility (Did the review use clearly defined eligibility criteria, a comprehensive search strategy, structured data collection, risk of bias and applicability appraisal, and appropriate meta-analysis methods?). If the review is credible, the next step is to decide whether the diagnostic performance is adequate for clinical use (Do sensitivity and specificity estimates exceed the threshold that makes them useful in clinical practice? Are these estimates sufficiently precise? Is variability in the estimates of diagnostic accuracy across studies explained?). Diagnostic accuracy systematic reviews that are judged to be credible and provide diagnostic accuracy estimates with sufficient certainty and relevance are the most useful to inform patient care. This review discusses comparative, noncomparative, and emerging approaches to systematic reviews of diagnostic accuracy using a clinical scenario and examples based on recent publications.

Accuracy of the Montreal Cognitive Assessment tool for detecting mild cognitive impairment: A systematic review and meta-analysis

INTRODUCTION

This systematic review evaluates the accuracy of the Montreal Cognitive Assessment (MoCA) for detecting mild cognitive impairment (MCI).

METHODS

We searched MEDLINE, PSYCInfo, EMBASE, and Cochrane CENTRAL (1995-2021) for studies comparing the MoCA with validated diagnostic criteria to identify MCI in general practice. Screening, data extraction, and risk of bias assessment were performed independently, in duplicate. Pooled sensitivity and specificity for MoCA cutoffs were estimated using bivariate meta-analysis.

RESULTS

Thirteen studies [2158 participants, 948(44%) with MCI] were included; 10 used Petersen criteria as the reference standard. Risk of bias of studies were high or unclear for all domains except reference standard. Sensitivity and specificity were 73.5%(95% confidence interval: 56.7-85.5) and 91.3%(84.6-95.3) at cutoff <23; 79.5%(67.1-88.0) and 83.7%(75.4-89.6) at cutoff <24; and 83.8%(75.6-89.6) and 70.8(62.1-78.3) at cutoff <25.

DISCUSSION

MoCA cutoffs <23 to <25 maximized the sum of sensitivity and specificity for detecting MCI. The risk of bias of included studies limits confidence in these findings.

Transparency and completeness of reporting of depression screening tool accuracy studies: A meta-research review of adherence to the Standards for Reporting of Diagnostic Accuracy Studies statement

OBJECTIVES

Accurate and complete study reporting allows evidence users to critically appraise studies, evaluate possible bias, and assess generalizability and applicability. We evaluated the extent to which recent studies on depression screening accuracy were reported consistent with Standards for Reporting of Diagnostic Accuracy Studies (STARD) statement requirements.

METHODS

MEDLINE was searched from January 1, 2018 through May 21, 2021 for depression screening accuracy studies.

RESULTS

106 studies were included. Of 34 STARD items or sub-items, the number of adequately reported items per study ranged from 7 to 18 (mean = 11.5, standard deviation [SD] = 2.5; median = 11.5), and the number inadequately reported ranged from 3 to 17 (mean = 10.1, SD = 2.5; median = 10.0). There were eight items adequately reported, seven partially reported, 11 inadequately reported, and four not applicable in ≥50% of studies; the remaining four items had mixed reporting. Items inadequately reported in ≥70% of studies related to the rationale for index test cut-offs examined, missing data management, analyses of variability in accuracy results, sample size determination, participant flow, study registration, and study protocol.

CONCLUSION

Recently published depression screening accuracy studies are not optimally reported. Journals should endorse and implement STARD adherence.

The German version of the neurofibromatosis 2 impact on quality of life questionnaire correlates with severity of depression and physician-reported disease severity

BACKGROUND

Neurofibromatosis type 2 (NF2) is a rare genetic disease that causes a wide range of disabilities leading to compromised quality of life (QOL). There is clear need for a validated disease-specific tool to assess quality of life among German-speaking patients with neurofibromatosis type 2 (NF2). The NFTI-QOL questionnaire has produced useful results in English-speaking cohorts. The aim of this study was to produce and validate a German version of the NFTI-QOL (NFTI-QOL-D) and to correlate QOL scores with a depression score (PHQ-9) and clinical disease severity.

METHODS

The original English-language NFTI-QOL was translated into German and then back-translated in order to preserve the questionnaire's original concepts and intentions. A link to an online survey encompassing the NFTI-QOL-D and the PHQ-9 depression questionnaire was then sent to 97 patients with NF2 by email. The respondents' scores were compared to clinician-reported disease severity scores.

RESULTS

77 patients completed the online survey in full. Internal reliability among NFTI-QOL-D responses was strong (Cronbach's alpha: 0.74). Both PHQ-9 and clinician disease severity scores correlated with NFTI-QOL-D scores (Pearson's rho 0.63 and 0.62, respectively).

CONCLUSIONS

The NFTI-QOL-D is a reliable and useful tool to assess patient-reported QOL in German-speaking patients with NF2. The correlation of QOL with both psychological and physical disease parameters underlines the importance of individualized interdisciplinary patient care for NF2 patients, with attention paid to mental well-being as well as to somatic disease manifestations.

Sample size and precision of estimates in studies of depression screening tool accuracy: A meta-research review of studies published in 2018-2021

OBJECTIVES

Depression screening tool accuracy studies should be conducted with large enough sample sizes to generate precise accuracy estimates. We assessed the proportion of recently published depression screening tool diagnostic accuracy studies that reported sample size calculations; the proportion that provided confidence intervals (CIs); and precision, based on the width and lower bounds of 95% CIs for sensitivity and specificity. In addition, we assessed whether these results have improved since a previous review of studies published in 2013-2015.

METHODS

MEDLINE was searched from January 1, 2018, through May 21, 2021.

RESULTS

Twelve of 106 primary studies (11%) described a viable sample size calculation, which represented an improvement of 8% since the last review. Thirty-six studies (34%) provided reasonably accurate CIs. Of 103 studies where 95% CIs were provided or could be calculated, seven (7%) had sensitivity CI widths of ≤10%, whereas 58 (56%) had widths of ≥21%. Eighty-four studies (82%) had lower bounds of CIs <80% for sensitivity and 77 studies (75%) for specificity. These results were similar to those reported previously.

CONCLUSION

Few studies reported sample size calculations, and the number of included individuals in most studies was too small to generate reasonably precise accuracy estimates.

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.

Is the center for epidemiologic studies depression scale as useful as the geriatric depression scale in screening for late-life depression? A systematic review

BACKGROUND

This study analyzed the predictive validity of the Center for Epidemiologic Studies Depression (CES-D) scale for late-life depression (LLD) over the age of 50 years and identified the usefulness of the CES-D compared with the Geriatric Depression Scale (GDS).

METHODS

Electronic searches were performed on the MEDLINE, EMBASE, CINAHL, and PsycINFO databases using the following keywords: depression, depressive disorder, major, and the CES-D scale. The Quality Assessment of Diagnostic Accuracy Studies-2 was applied to assess the risk of bias.

RESULTS

We reviewed 22 studies, including 27,742 older adults aged 50+ years that met the selection criteria. In the meta-analysis, the pooled sensitivity was 0.81 in the CES-D long version and 0.76 in the short version. The sROC AUC was 0.89 (SE=0.01) for the long version and 0.88 (SE=0.04) for the short version. The GDS was only compared to the CES-D long version. The pooled sensitivity was as follows: the CES-D, 0.82; the GDS long version, 0.86; and the GDS short version, 0.87. Further, there was no heterogeneity of 0.0% between studies. The pooled specificity was 0.78 and 0.77, respectively, and the sROC AUC was 0.88 for the CES-D (SE=0.02), 0.89 for the GDS long version (SE=0.04), and 0.91 for the GDS short version (SE=0.03).

LIMITATIONS

We could not consider cognitive function of older adults.

CONCLUSIONS

The CES-D showed similar predictive validity compared to the GDS developed in older adults. The CES-D is a useful tool that can be used for LLD screening in older adults over 50 years old.

Selective cutoff reporting in studies of the accuracy of the Patient Health Questionnaire-9 and Edinburgh Postnatal Depression Scale: Comparison of results based on published cutoffs versus all cutoffs using individual participant data meta-analysis

OBJECTIVES

Selectively reported results from only well-performing cutoffs in diagnostic accuracy studies may bias estimates in meta-analyses. We investigated cutoff reporting patterns for the Patient Health Questionnaire-9 (PHQ-9; standard cutoff 10) and Edinburgh Postnatal Depression Scale (EPDS; no standard cutoff, commonly used 10-13) and compared accuracy estimates based on published cutoffs versus all cutoffs.

METHODS

We conducted bivariate random effects meta-analyses using individual participant data to compare accuracy from published versus all cutoffs.

RESULTS

For the PHQ-9 (30 studies, N = 11,773), published results underestimated sensitivity for cutoffs below 10 (median difference: -0.06) and overestimated for cutoffs above 10 (median difference: 0.07). EPDS (19 studies, N = 3637) sensitivity estimates from published results were similar for cutoffs below 10 (median difference: 0.00) but higher for cutoffs above 13 (median difference: 0.14). Specificity estimates from published and all cutoffs were similar for both tools. The mean cutoff of all reported cutoffs in PHQ-9 studies with optimal cutoff below 10 was 8.8 compared to 11.8 for those with optimal cutoffs above 10. Mean for EPDS studies with optimal cutoffs below 10 was 9.9 compared to 11.8 for those with optimal cutoffs greater than 10.

CONCLUSION

Selective cutoff reporting was more pronounced for the PHQ-9 than EPDS.

PRIME-IPD SERIES Part 1. The PRIME-IPD tool promoted verification and standardization of study datasets retrieved for IPD meta-analysis

OBJECTIVES

We describe a systematic approach to preparing data in the conduct of Individual Participant Data (IPD) analysis.

STUDY DESIGN AND SETTING

A guidance paper proposing methods for preparing individual participant data for meta-analysis from multiple study sources, developed by consultation of relevant guidance and experts in IPD. We present an example of how these steps were applied in checking data for our own IPD meta analysis (IPD-MA).

RESULTS

We propose five steps of Processing, Replication, Imputation, Merging, and Evaluation to prepare individual participant data for meta-analysis (PRIME-IPD). Using our own IPD-MA as an exemplar, we found that this approach identified missing variables and potential inconsistencies in the data, facilitated the standardization of indicators across studies, confirmed that the correct data were received from investigators, and resulted in a single, verified dataset for IPD-MA.

CONCLUSION

The PRIME-IPD approach can assist researchers to systematically prepare, manage and conduct important quality checks on IPD from multiple studies for meta-analyses. Further testing of this framework in IPD-MA would be useful to refine these steps.

Sex differences in risk factors for depressive symptoms in patients with COPD: The 2014 and 2016 Korea National Health and Nutrition Examination Survey

Background

Although depression is a common comorbidity of chronic obstructive pulmonary disease (COPD), the role of sex remains unexplored. We evaluated sex differences of risk factors of depressive symptoms in adults with COPD.

Methods

This was a population-based cross-sectional study using data from the 2014 and 2016 Korea National Health and Nutrition Examination Survey. Spirometry was used to identify patients with COPD, defined as a FEV₁/FVC ratio < 0.7. Presence of depressive symptoms was defined as a total score ≥ 5 on the Patient Health Questionnaire-9.

Results

17.8% of participants expressed depressive symptoms. Relative regression analysis revealed that female sex (RR 2.38; 95% CI 1.55–3.66; p < 0.001), living alone (RR 1.46; 95% CI 1.08–1.97; p = 0.013), current smoker (RR 1.70; 95% CI 1.15–2.52; p = 0.008), underweight (RR 1.58 95% CI 1.00–2.49; p = 0.049), and GOLD Stage III/IV (RR 1.92; 95% CI 1.19–3.09; p = 0.007) were the risk factors for depressive symptoms. Low income, living alone, multiple chronic disorders, and low BMI were risk factors of depressive symptoms in male, whereas low educational attainment, urban living, and current smoking were risk factors in female.

Conclusions

Female sex is a main risk factor of depressive symptoms in adults with COPD. As risk factors of depressive symptoms in COPD patients vary according to their sex, different approaches are needed to manage depression in males and females with COPD.

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.

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

OBJECTIVE

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.

STUDY DESIGN AND SETTING

A total of 1,000 samples of sample size 100, 200, 500 and 1,000 each were randomly drawn to simulate studies of different sample sizes from a database (n = 13,255) synthesized to assess Edinburgh Postnatal Depression Scale (EPDS) screening accuracy. Optimal cutoffs were selected by maximizing Youden's J (sensitivity+specificity-1). Optimal cutoffs and accuracy estimates in simulated samples were compared to population values.

RESULTS

Optimal cutoffs in simulated samples ranged from ≥ 5 to ≥ 17 for n = 100, ≥ 6 to ≥ 16 for n = 200, ≥ 6 to ≥ 14 for n = 500, and ≥ 8 to ≥ 13 for n = 1,000. Percentage of simulated samples identifying the population optimal cutoff (≥ 11) was 30% for n = 100, 35% for n = 200, 53% for n = 500, and 71% for n = 1,000. Mean overestimation of sensitivity and underestimation of specificity were 6.5 percentage point (pp) and -1.3 pp for n = 100, 4.2 pp and -1.1 pp for n = 200, 1.8 pp and -1.0 pp for n = 500, and 1.4 pp and -1.0 pp for n = 1,000.

CONCLUSIONS

Small accuracy studies may identify inaccurate optimal cutoff and overstate accuracy estimates with data-driven methods.

Screening for depression in primary care with Patient Health Questionnaire-9 (PHQ-9): A systematic review

BACKGROUND

Depression is a leading cause of disability. International guidelines recommend screening for depression and the Patient Health Questionnaire 9 (PHQ-9) has been identified as the most reliable screening tool. We reviewed the evidence for using it within the primary care setting.

METHODS

We retrieved studies from MEDLINE, Embase, PsycINFO, CINAHL and the Cochrane Library that carried out primary care-based depression screening using PHQ-9 in populations older than 12, from 1995 to 2018.

RESULTS

Forty-two studies were included in the systematic review. Most of the studies were cross-sectional (N=40, 95%), conducted in high-income countries (N=27, 71%) and recruited adult populations (N=38, 90%). The accuracy of the PHQ-9 was evaluated in 31 (74%) studies with a two-stage screening system, with structured interview most often carried out by primary care and mental health professionals. Most of the studies employed a cut-off score of 10 (N=24, 57%, total range 5 - 15). The overall sensitivity of PHQ-9 ranged from 0.37 to 0.98, specificity from 0.42 to 0.99, positive predictive value from 0.09 to 0.92, and negative predictive value from 0.8 to 1.

LIMITATIONS

Lack of longitudinal studies, small sample size, and the heterogeneity of primary-care settings limited the generalizability of our results.

CONCLUSIONS

PHQ-9 has been widely validated and is recommended in a two-stage screening process. Longitudinal studies are necessary to provide evidence of long-term screening effectiveness.

An empirical comparison of three methods for multiple cutoff diagnostic test meta-analysis of the Patient Health Questionnaire-9 (PHQ-9) depression screening tool using published data vs individual level data

Selective cutoff reporting in primary diagnostic accuracy studies with continuous or ordinal data may result in biased estimates when meta-analyzing studies. Collecting individual participant data (IPD) and estimating accuracy across all relevant cutoffs for all studies can overcome such bias but is labour intensive. We meta-analyzed the diagnostic accuracy of the Patient Health Questionnaire-9 (PHQ-9) depression screening tool. We compared results for two statistical methods proposed by Steinhauser and by Jones to account for missing cutoffs, with results from a series of bivariate random effects models (BRM) estimated separately at each cutoff. We applied the methods to a dataset that contained information only on cutoffs that were reported in the primary publications and to the full IPD dataset that contained information for all cutoffs for every study. For each method, we estimated pooled sensitivity and specificity and associated 95% confidence intervals for each cutoff and area under the curve (AUC). The full IPD dataset comprised data from 45 studies, 15 020 subjects, and 1972 cases of major depression and included information on every possible cutoff. When using data available in publications, using statistical approaches outperformed the BRM applied to the same data. AUC was similar for all approaches when using the full IPD dataset, though pooled estimates were slightly different. Overall, using statistical methods to fill in missing cutoff data recovered the receiver operating characteristic (ROC) curve from the full IPD dataset well when using only the published subset. All methods performed similarly when applied to the full IPD dataset.

Neuropsychiatric issues after stroke: Clinical significance and therapeutic implications

A spectrum of neuropsychiatric disorders is a common complication from stroke. Neuropsychiatric disorders after stroke have negative effects on functional recovery, increasing the rate of mortality and disability of stroke survivors. Given the vital significance of maintaining physical and mental health in stroke patients, neuropsychiatric issues after stroke have raised concerns by clinicians and researchers. This mini-review focuses on the most common non-cognitive functional neuropsychiatric disorders seen after stroke, including depressive disorders, anxiety disorders, post-traumatic stress disorder, psychosis, and psychotic disorders. For each condition, the clinical performance, epidemiology, identification of the therapeutic implication, and strategies are reviewed and discussed; the main opinions and perspectives presented here are based on the latest controlled studies, meta-analysis, or updated systematic reviews. In the absence of data from controlled studies, consensus recommendations were provided accordingly.

Validity of the Patient Health Questionnaire-9 in neurologic populations

Background

Because of symptom overlap, there is uncertainty about the validity of depression rating scales in neurologic populations. The objectives of this study were to evaluate the validity of the Patient Health Questionnaire-9 (PHQ-9) for detecting Diagnostic and Statistical Manual-defined major depressive episodes in people with neurologic conditions.

Methods

Participants were recruited from outpatient clinics for multiple sclerosis, epilepsy, migraine, Parkinson disease, and stroke for this cross-sectional study. Participants were administered a questionnaire (this included the PHQ-9), chart review, and a follow-up telephone interview. The Structured Clinical Interview for Depression was used as the reference standard for psychiatric diagnoses. The performance of PHQ-9 was analyzed using sensitivity, specificity, diagnostic odds ratios (DORs), and receiver operator curve analysis.

Results

All neurologic subpopulations had a specificity greater than 78% and sensitivity greater than 79% at a cut-point of 10. Using a random-effects model, the I-squared value was 13.7%, and Tau² was 0.05, showing homogeneity across the neurologic subpopulations. The pooled DOR was 25.3 (95% confidence interval [CI] 14.9-42.8). Meta-analytic analysis found that for sensitivity, the pooled estimate was 90% (95% CI 81-97), and for specificity, it was 85% (95% CI 79-90).

Conclusions

Despite theoretical concerns about its validity, the PHQ-9 performed well at its standard cut-point of 10. Consistent with the literature, being able to use a validated, brief tool that is available publicly should improve case finding of depression in neurologic populations. When considering clinical practicality along with the findings of this analyzed, this study confirmed that the PHQ-9 is valid in a general outpatient neurologic population.

Depression in the medically ill

BACKGROUND

Depressive disorders are significantly more common in the medically ill compared to the general population. Depression is associated with worsening of physical symptoms, greater healthcare utilization and poorer treatment adherence. The present paper provides a critical review on the assessment and management of depression in the medically ill.

METHODS

Relevant articles pertaining to depression in the medically ill were identified, reviewed and synthesized qualitatively. A systematic review was not performed due to the large breadth of this topic, making a meaningful summary of all published and unpublished studies not feasible. Notable studies were reviewed and synthesized by a diverse set of experts to provide a balanced summary.

RESULTS

Depression is frequently under-recognized in medical settings. Differential diagnoses include delirium, personality disorders and depressive disorders secondary to substances, medications or another medical condition. Depressive symptoms in the context of an adjustment disorder should be initially managed by supportive psychological approaches. Once a mild to moderate major depressive episode is identified, a stepped care approach should be implemented, starting with general psychoeducation, psychosocial interventions and ongoing monitoring. For moderate to severe symptoms, or mild symptoms that are not responding to low-intensity interventions, the use of antidepressants or higher intensity psychotherapeutic interventions should be considered. Psychotherapeutic interventions have demonstrated benefits with small to moderate effect sizes. Antidepressant medications have also demonstrated benefits with moderate effect sizes; however, special caution is needed in evaluating side effects, drug-drug interactions as well as dose adjustments due to impairment in hepatic metabolism and/or renal clearance. Novel interventions for the treatment of depression and other illness-related psychological symptoms (e.g. death anxiety, loss of dignity) are under investigation.

LIMITATIONS

Non-systematic review of the literature.

CONCLUSION

Replicated evidence has demonstrated a bidirectional interaction between depression and medical illness. Screening and stepped care using pharmacological and non-pharmacological interventions is merited.

Quantifying how diagnostic test accuracy depends on threshold in a meta-analysis

Tests for disease often produce a continuous measure, such as the concentration of some biomarker in a blood sample. In clinical practice, a threshold C is selected such that results, say, greater than C are declared positive and those less than C negative. Measures of test accuracy such as sensitivity and specificity depend crucially on C, and the optimal value of this threshold is usually a key question for clinical practice. Standard methods for meta‐analysis of test accuracy (i) do not provide summary estimates of accuracy at each threshold, precluding selection of the optimal threshold, and furthermore, (ii) do not make use of all available data. We describe a multinomial meta‐analysis model that can take any number of pairs of sensitivity and specificity from each study and explicitly quantifies how accuracy depends on C. Our model assumes that some prespecified or Box‐Cox transformation of test results in the diseased and disease‐free populations has a logistic distribution. The Box‐Cox transformation parameter can be estimated from the data, allowing for a flexible range of underlying distributions. We parameterise in terms of the means and scale parameters of the two logistic distributions. In addition to credible intervals for the pooled sensitivity and specificity across all thresholds, we produce prediction intervals, allowing for between‐study heterogeneity in all parameters. We demonstrate the model using two case study meta‐analyses, examining the accuracy of tests for acute heart failure and preeclampsia. We show how the model can be extended to explore reasons for heterogeneity using study‐level covariates.

Red cell distribution width to platelet ratio for liver fibrosis: a systematic review and meta-analysis of diagnostic accuracy

Introduction: Red cell distribution width to platelet ratio (RPR) may be a useful marker for the evaluation of liver fibrosis in chronic liver disease (CLD). We sought to investigate its value in fibrosis-related outcomes in a meta-analysis of diagnostic accuracy. Areas covered: We searched MEDLINE (1966-2019), Clinicaltrials.gov (2008-2019), Cochrane Central Register of Controlled Trials (CENTRAL) (1999-2019), Google Scholar (2004-2019) and WHO (International Clinical Trials Register Platform) databases using a structured algorithm. The articles were assessed by Quality Assessment of Diagnostic Accuracy Studies tool (QUADAS-2). In over 1,800 patients for each outcome, pooled sensitivity and specificity for a) significant fibrosis, b) advanced fibrosis and c) cirrhosis were: a) 0.635 and 0.769 with an AUC of 0.747, b) 0.607 and 0.783 with an AUC of 0.773, c) 0.739 and 0.768 with an AUC of 0.818 respectively. Similar results were found for chronic hepatitis B in all outcomes. Subgroup analysis indicated a high specificity for advanced fibrosis detection in primary biliary cirrhosis. Sensitivity analysis did not alter the results. Expert opinion: RPR is a good predictor of fibrosis, especially as severity of chronic liver disease progresses. Future research should elucidate its value in specific etiologies of chronic liver disease.

Depression and congestive heart failure: A large prospective cohort study from Pakistan

OBJECTIVES

Evidence demonstrates the detrimental impact of depression in patients with congestive heart failure (CHF), however, large-scale prospective data from Low and Middle Income Countries (LMICs) is limited. We assessed the prevalence of depression in a large sample with CHF from Karachi, Pakistan, and the impact of depression on all-cause mortality, disability and health-related quality of life (QoL).

METHODS

1009 patients diagnosed with CHF were recruited from public hospitals in Karachi, Pakistan. Patients were screened for depression at baseline using the Beck Depression Inventory (BDI) and the diagnosis was confirmed using the Clinical Interview Schedule-Revised (CIS-R). Health-related QoL and disability were measured using the EuroQol (EQ-5D) and Brief Disability Questionnaire respectively at baseline and after a 6-month follow-up.

RESULTS

A total of 670 (66%) patients were depressed at baseline and 821 participants completed 6-month follow up assessments (retention rate: 81%). At baseline, lower income (p < 0.001) and lower education level (p = 0.03) were associated with higher BDI scores. Higher BDI scores were associated with a history of depression (p < 0.001), higher NYHA class (p < 0.001), diabetes (p < 0.001), COPD (p = 0.007), renal disease (p < 0.001) and stroke (p = 0.02). 145 participants were deceased at 6-months. Regression analysis showed that at follow up, higher BDI scores in depressed participants were associated with higher all-cause mortality (OR 1.23 (95% CI: 1.11-1.36); p < 0.001).

CONCLUSION

The rate of depression was high among Pakistani patients with CHF. Severity of depression correlated with increased mortality. Further research on controlled intervention trials in this population is warranted.

Accuracy of Patient Health Questionnaire-9 (PHQ-9) for screening to detect major depression: individual participant data meta-analysis

OBJECTIVE

To determine the accuracy of the Patient Health Questionnaire-9 (PHQ-9) for screening to detect major depression.

DESIGN

Individual participant data meta-analysis.

DATA SOURCES

Medline, Medline In-Process and Other Non-Indexed Citations, PsycINFO, and Web of Science (January 2000-February 2015).

INCLUSION CRITERIA

Eligible 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.

RESULTS

Data 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..

CONCLUSIONS

PHQ-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.

REGISTRATION

PROSPERO CRD42014010673.

Different patterns of alcohol consumption and the incidence and persistence of depressive and anxiety symptoms among older adults in Ireland: A prospective community-based study

BACKGROUND

The associations of different patterns of alcohol consumption and the incidence and persistence of depressive and anxiety symptoms in older age remain unclear.

METHODS

Data on 6095 adults aged ≥ 50 years old from the Irish Longitudinal Study on Aging (TILDA) was analyzed. Participants completed the CAGE instrument to screen for problematic alcohol use at baseline between October 2009 and February 2011. Outcomes were incident (assessed by the CES-D scale) and anxiety (assessed by the Hospital Anxiety and Depressive scale) symptoms after a two-year follow-up as well as persistence of probable depression and anxiety among those with a positive screen for those disorders at baseline. Associations were adjusted for potential confounders through multivariable models.

RESULTS

In the overall sample, problem drinking did not predict incident and persistent depression and anxiety in this sample. Among females, problem drinking increased the risk for incident depression (OR = 2.11; 95%CI = 1.12-4.00) and anxiety (OR = 2.22; 95%CI = 1.01-4.86). In addition, problem drinking increased the risk of persistent depressive symptoms (OR = 2.43; 95%CI = 1.05-5.06) among females.

CONCLUSION

Problem drinking may increase the risk of incident probable depression and anxiety among older females. Furthermore, problem drinking led to a higher likelihood of persistent depressive symptoms in older female participants. Interventions targeting problem drinking among older females may prevent the onset and persistence of depression in this population, while also decreasing the incidence of anxiety symptoms.

Depression and metabolic syndrome in the older population: A review of evidence

BACKGROUND

Metabolic syndrome (MetS) has been shown to be associated with depression in older adults but the results are mixed. We summarized and evaluated the association between depression and MetS in people aged 60 years or over.

METHODS

Relevant published studies from January 1997 to July 2017 were identified by searching two electronic databases: PubMed/Medline and EMBASE. Observational studies were considered.

RESULTS

Twelve studies were included in the systematic review. Depression seemed to be related with MetS in the majority of the studies (10/12 = 83.3%). As far as the longitudinal studies are concerned, the onset of depression was related to MetS in 2 out of 3 studies (66.6%), while a relation between chronicity of depression and MetS was reported (1 study). Regarding cross-sectional studies, 7 out of 9 (77.7%) concluded that there was a positive association between depression and MetS. Mixed evidence was found among studies concerning the association between depression and the individual components of MetS. Four out of ten studies (40%) reported that depression was significantly associated with the waist circumference, a component of MetS.

LIMITATIONS

There was a high degree of heterogeneity between studies regarding their design. Only studies written in English, from peer-reviewed journals were included.

CONCLUSIONS

Depression seemed to be significantly associated with MetS in people aged 60 years or over. Among the components of MetS, abdominal obesity seemed to be associated more strongly and consistently with depression. The direction of the causality and mechanisms underlying the relationship are still largely unknown.

Mapping risk factors for depression across the lifespan: An umbrella review of evidence from meta-analyses and Mendelian randomization studies

The development of depression may involve a complex interplay of environmental and genetic risk factors. PubMed and PsycInfo databases were searched from inception through August 3, 2017, to identify meta-analyses and Mendelian randomization (MR) studies of environmental risk factors associated with depression. For each eligible meta-analysis, we estimated the summary effect size and its 95% confidence interval (CI) by random-effects modeling, the 95% prediction interval, heterogeneity with I2, and evidence of small-study effects and excess significance bias. Seventy meta-analytic reviews met the eligibility criteria and provided 134 meta-analyses for associations from 1283 primary studies. While 109 associations were nominally significant (P < 0.05), only 8 met the criteria for convincing evidence and, when limited to prospective studies, convincing evidence was found in 6 (widowhood, physical abuse during childhood, obesity, having 4-5 metabolic risk factors, sexual dysfunction, job strain). In studies in which depression was assessed through a structured diagnostic interview, only associations with widowhood, job strain, and being a Gulf War veteran were supported by convincing evidence. Additionally, 8 MR studies were included and provided no consistent evidence for the causal effects of obesity, smoking, and alcohol consumption. The proportion of variance explained by genetic risk factors was extremely small (0.1-0.4%), which limited the evidence provided by the MR studies. Our findings suggest that despite the large number of putative risk factors investigated in the literature, few associations were supported by robust evidence. The current findings may have clinical and research implications for the early identification of individuals at risk for depression.

The association of depression and all-cause and cause-specific mortality: an umbrella review of systematic reviews and meta-analyses

BACKGROUND

Depression is a prevalent and disabling mental disorder that frequently co-occurs with a wide range of chronic conditions. Evidence has suggested that depression could be associated with excess all-cause mortality across different settings and populations, although the causality of these associations remains unclear.

METHODS

We conducted an umbrella review of systematic reviews and meta-analyses of observational studies. PubMed, PsycINFO, and Embase electronic databases were searched through January 20, 2018. Systematic reviews and meta-analyses that investigated associations of depression and all-cause and cause-specific mortality were selected for the review. The evidence was graded as convincing, highly suggestive, suggestive, or weak based on quantitative criteria that included an assessment of heterogeneity, 95% prediction intervals, small-study effects, and excess significance bias.

RESULTS

A total of 26 references providing 2 systematic reviews and data for 17 meta-analytic estimates met inclusion criteria (19 of them on all-cause mortality); data from 246 unique studies (N = 3,825,380) were synthesized. All 17 associations had P < 0.05 per random effects summary effects, but none of them met criteria for convincing evidence. Associations of depression and all-cause mortality in patients after acute myocardial infarction, in individuals with heart failure, in cancer patients as well as in samples from mixed settings met criteria for highly suggestive evidence. However, none of the associations remained supported by highly suggestive evidence in sensitivity analyses that considered studies employing structured diagnostic interviews. In addition, associations of depression and all-cause mortality in cancer and post-acute myocardial infarction samples were supported only by suggestive evidence when studies that tried to adjust for potential confounders were considered.

CONCLUSIONS

Even though associations between depression and mortality have nominally significant results in all assessed settings and populations, the evidence becomes weaker when focusing on studies that used structured interviews and those that tried to adjust for potential confounders. A causal effect of depression on all-cause and cause-specific mortality remains unproven, and thus interventions targeting depression are not expected to result in lower mortality rates at least based on current evidence from observational studies.

Meta-analysis of test accuracy studies using imputation for partial reporting of multiple thresholds

Introduction

For tests reporting continuous results, primary studies usually provide test performance at multiple but often different thresholds. This creates missing data when performing a meta‐analysis at each threshold. A standard meta‐analysis (no imputation [NI]) ignores such missing data. A single imputation (SI) approach was recently proposed to recover missing threshold results. Here, we propose a new method that performs multiple imputation of the missing threshold results using discrete combinations (MIDC).

Methods

The new MIDC method imputes missing threshold results by randomly selecting from the set of all possible discrete combinations which lie between the results for 2 known bounding thresholds. Imputed and observed results are then synthesised at each threshold. This is repeated multiple times, and the multiple pooled results at each threshold are combined using Rubin's rules to give final estimates. We compared the NI, SI, and MIDC approaches via simulation.

Results

Both imputation methods outperform the NI method in simulations. There was generally little difference in the SI and MIDC methods, but the latter was noticeably better in terms of estimating the between‐study variances and generally gave better coverage, due to slightly larger standard errors of pooled estimates. Given selective reporting of thresholds, the imputation methods also reduced bias in the summary receiver operating characteristic curve. Simulations demonstrate the imputation methods rely on an equal threshold spacing assumption. A real example is presented.

Conclusions

The SI and, in particular, MIDC methods can be used to examine the impact of missing threshold results in meta‐analysis of test accuracy studies.

A comparison of bivariate, multivariate random-effects, and Poisson correlated gamma-frailty models to meta-analyze individual patient data of ordinal scale diagnostic tests

Individual patient data (IPD) meta-analyses are increasingly common in the literature. In the context of estimating the diagnostic accuracy of ordinal or semi-continuous scale tests, sensitivity and specificity are often reported for a given threshold or a small set of thresholds, and a meta-analysis is conducted via a bivariate approach to account for their correlation. When IPD are available, sensitivity and specificity can be pooled for every possible threshold. Our objective was to compare the bivariate approach, which can be applied separately at every threshold, to two multivariate methods: the ordinal multivariate random-effects model and the Poisson correlated gamma-frailty model. Our comparison was empirical, using IPD from 13 studies that evaluated the diagnostic accuracy of the 9-item Patient Health Questionnaire depression screening tool, and included simulations. The empirical comparison showed that the implementation of the two multivariate methods is more laborious in terms of computational time and sensitivity to user-supplied values compared to the bivariate approach. Simulations showed that ignoring the within-study correlation of sensitivity and specificity across thresholds did not worsen inferences with the bivariate approach compared to the Poisson model. The ordinal approach was not suitable for simulations because the model was highly sensitive to user-supplied starting values. We tentatively recommend the bivariate approach rather than more complex multivariate methods for IPD diagnostic accuracy meta-analyses of ordinal scale tests, although the limited type of diagnostic data considered in the simulation study restricts the generalization of our findings.

Methodological quality of meta-analyses of the diagnostic accuracy of depression screening tools

OBJECTIVE

Concerns have been raised that primary studies of diagnostic accuracy of depression screening tools may exaggerate estimates of accuracy and that this could also influence the results of meta-analyses. No studies, however, have evaluated the quality of meta-analyses of depression screening tools. Our objective was to evaluate the quality of meta-analyses of the diagnostic accuracy of depression screening tools.

METHODS

We searched MEDLINE and PsycINFO from January 1, 2005 through March 13, 2016 for recent meta-analyses in any language on the diagnostic accuracy of depression screening tools. Two reviewers independently assessed methodological quality using the AMSTAR tool with appropriate adaptations made for studies of diagnostic test accuracy.

RESULTS

We identified 21 eligible meta-analyses. The majority provided a list of included studies (100%), included a comprehensive literature search (95%) and assessed risk of bias of included studies (71%). Meta-analyses less consistently included non-published evidence (38%), listed excluded studies (33%), incorporated risk of bias findings into conclusions (33%), and assessed selective cutoff reporting (29%). Meta-analyses rarely reported that duplicate study selection or data extraction occurred (14%), mentioned 'a priori' protocols (10%), or reported on conflicts of interest (0%) or funding sources (0%) of primary studies. Only 6 of 21 included meta-analyses complied with at least 7 of 14 adapted AMSTAR items.

CONCLUSIONS

The methodological quality of most meta-analyses of the diagnostic test accuracy of depression screening tools is suboptimal. Improving quality will reduce the risk of inaccurate estimates of accuracy and inappropriate inferences.

Diagnostic accuracy of the Depression subscale of the Hospital Anxiety and Depression Scale (HADS-D) for detecting major depression: protocol for a systematic review and individual patient data meta-analyses

INTRODUCTION

The Depression subscale of the Hospital Anxiety and Depression Scale (HADS-D) has been recommended for depression screening in medically ill patients. Many existing HADS-D studies have used exploratory methods to select optimal cut-offs. Often, these studies report results from a small range of cut-off thresholds; cut-offs with more favourable accuracy results are more likely to be reported than others with worse accuracy estimates. When published data are combined in meta-analyses, selective reporting may generate biased summary estimates. Individual patient data (IPD) meta-analyses can address this problem by estimating accuracy with data from all studies for all relevant cut-off scores. In addition, a predictive algorithm can be generated to estimate the probability that a patient has depression based on a HADS-D score and clinical characteristics rather than dichotomous screening classification alone. The primary objectives of our IPD meta-analyses are to determine the diagnostic accuracy of the HADS-D to detect major depression among adults across all potentially relevant cut-off scores and to generate a predictive algorithm for individual patients. We are already aware of over 100 eligible studies, and more may be identified with our comprehensive search.

METHODS AND ANALYSIS

Data sources will include MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations, PsycINFO and Web of Science. Eligible studies will have datasets where patients are assessed for major depression based on a validated structured or semistructured clinical interview and complete the HADS-D within 2 weeks (before or after). Risk of bias will be assessed with the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Bivariate random-effects meta-analysis will be conducted for the full range of plausible cut-off values, and a predictive algorithm for individual patients will be generated.

ETHICS AND DISSEMINATION

The findings of this study will be of interest to stakeholders involved in research, clinical practice and policy.