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Equivalency of the diagnostic accuracy of the PHQ-8 and PHQ-9: a systematic review and individual participant data meta-analysis.
Wu, Y, Levis, B, Riehm, KE, Saadat, N, Levis, AW, Azar, M, Rice, DB, Boruff, J, Cuijpers, P, Gilbody, S, et al
Psychological medicine. 2020;(8):1368-1380
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Abstract
BACKGROUND 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. METHODS We conducted an individual patient data meta-analysis. We fit bivariate random-effects models to assess diagnostic accuracy. RESULTS 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). CONCLUSIONS PHQ-8 and PHQ-9 total scores were similar. Sensitivity may be minimally reduced with the PHQ-8, but specificity is similar.
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Performance of deep neural network-based artificial intelligence method in diabetic retinopathy screening: a systematic review and meta-analysis of diagnostic test accuracy.
Wang, S, Zhang, Y, Lei, S, Zhu, H, Li, J, Wang, Q, Yang, J, Chen, S, Pan, H
European journal of endocrinology. 2020;(1):41-49
Abstract
OBJECTIVE Automatic diabetic retinopathy screening system based on neural networks has been used to detect diabetic retinopathy (DR). However, there is no quantitative synthesis of performance of these methods. We aimed to estimate the sensitivity and specificity of neural networks in DR grading. METHODS Medline, Embase, IEEE Xplore, and Cochrane Library were searched up to 23 July 2019. Studies that evaluated performance of neural networks in detection of moderate or worse DR or diabetic macular edema using retinal fundus images with ophthalmologists' judgment as reference standard were included. Two reviewers extracted data independently. Risk of bias of eligible studies was assessed using QUDAS-2 tool. RESULTS Twenty-four studies involving 235 235 subjects were included. Quantitative random-effects meta-analysis using the Rutter and Gatsonis hierarchical summary receiver operating characteristics (HSROC) model revealed a pooled sensitivity of 91.9% (95% CI: 89.6% to 94.3%) and specificity of 91.3% (95% CI: 89.0% to 93.5%). Subgroup analyses and meta-regression did not provide any statistically significant findings for the heterogeneous diagnostic accuracy in studies with different image resolutions, sample sizes of training sets, architecture of convolutional neural networks, or diagnostic criteria. CONCLUSIONS State-of-the-art neural networks could effectively detect clinical significant DR. To further improve diagnostic accuracy of neural networks, researchers might need to develop new algorithms rather than simply enlarge sample sizes of training sets or optimize image quality.
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The Accuracy of the Patient Health Questionnaire-9 Algorithm for Screening to Detect Major Depression: An Individual Participant Data Meta-Analysis.
He, C, Levis, B, Riehm, KE, Saadat, N, Levis, AW, Azar, M, Rice, DB, Krishnan, A, Wu, Y, Sun, Y, et al
Psychotherapy and psychosomatics. 2020;(1):25-37
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Abstract
BACKGROUND Screening for major depression with the Patient Health Questionnaire-9 (PHQ-9) can be done using a cutoff or the PHQ-9 diagnostic algorithm. Many primary studies publish results for only one approach, and previous meta-analyses of the algorithm approach included only a subset of primary studies that collected data and could have published results. OBJECTIVE To use an individual participant data meta-analysis to evaluate the accuracy of two PHQ-9 diagnostic algorithms for detecting major depression and compare accuracy between the algorithms and the standard PHQ-9 cutoff score of ≥10. METHODS Medline, Medline In-Process and Other Non-Indexed Citations, PsycINFO, Web of Science (January 1, 2000, to February 7, 2015). Eligible studies that classified current major depression status using a validated diagnostic interview. RESULTS Data were included for 54 of 72 identified eligible studies (n participants = 16,688, n cases = 2,091). Among studies that used a semi-structured interview, pooled sensitivity and specificity (95% confidence interval) were 0.57 (0.49, 0.64) and 0.95 (0.94, 0.97) for the original algorithm and 0.61 (0.54, 0.68) and 0.95 (0.93, 0.96) for a modified algorithm. Algorithm sensitivity was 0.22-0.24 lower compared to fully structured interviews and 0.06-0.07 lower compared to the Mini International Neuropsychiatric Interview. Specificity was similar across reference standards. For PHQ-9 cutoff of ≥10 compared to semi-structured interviews, sensitivity and specificity (95% confidence interval) were 0.88 (0.82-0.92) and 0.86 (0.82-0.88). CONCLUSIONS The cutoff score approach appears to be a better option than a PHQ-9 algorithm for detecting major depression.
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Single-Field Non-Mydriatic Fundus Photography for Diabetic Retinopathy Screening: A Systematic Review and Meta-Analysis.
Hu, J, Chen, R, Lu, Y, Dou, X, Ye, B, Cai, Z, Pu, Z, Mou, L
Ophthalmic research. 2019;(2):61-67
Abstract
PURPOSE Single-field non-mydriatic fundus photography (NMFP) has been used to detect diabetic retinopathy (DR) in many studies; however, its value in a general clinical setting has not been established. Here we performed a meta-analysis to evaluate its diagnostic effectiveness. METHOD We systematically searched PubMed, EMBASE, and Cochrane databases for candidate studies published through May 19, 2018. A random-effect model was used to calculate the diagnostic indicators including the sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), area under the curve (AUC), and 95% confidence intervals. RESULTS Ten prospective studies were ultimately included. The pooled sensitivity, specificity, PLR, NLR, and DOR were 0.68, 0.94, 11.2, 0.34 and 33, respectively. The AUC was 0.88. Subgroup analysis showed that single-field NMFP had a respective sensitivity and specificity of 0.73 and 0.91 when compared to standard 7-field mydriatic stereoscopic photography (7SF), and 0.54 and 0.98 when compared to slit-lamp biomicroscopy as reference standard. CONCLUSIONS Single-field NMFP is inadequate to detect DR. Additionally, it showed higher sensitivity and lower specificity when 7SF was used as reference standard, as compared to slit-lamp biomicroscopy, suggesting that different reference standards used in DR screening might have affected the diagnostic results.