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Depression questionnaire cutoffs are calibrated for screening accuracy and not to assess prevalence, but the Geriatric Depression Scale (GDS-15) is often used to estimate diagnostic prevalence among older adults, most commonly with scores of ≥ 5. We conducted an individual participant data meta-analysis to compare depression prevalence based on GDS-15 ≥ 5 to Structured Clinical Interview for Diagnostic and Statistical Manual (SCID) diagnoses and assessed whether an alternative cutoff could be more accurate. We used generalized linear mixed models to estimate prevalence. Data from 14 studies (3602 participants, 434 SCID major depression) were included. Pooled GDS-15 ≥ 5 prevalence was 34.2% (95% confidence interval [CI] 27.5–41.6%), and pooled SCID prevalence was 14.8% (95% CI 10.0–21.5%; difference of 17.6%, 95% CI 11.6–23.6%). GDS-15 ≥ 8 provided the closest estimate to SCID with mean difference of − 0.3% (95% prediction interval − 17.0–16.5%). Prevalence estimate differences were not associated with study or participant characteristics. In sum, GDS-15 ≥ 5 substantially overestimated depression prevalence. A cutoff of ≥ 8 was accurate overall, but heterogeneity was too high for implementation in practice. Validated diagnostic interviews should be used to estimate major depression prevalence among older adults. [ABSTRACT FROM AUTHOR]

Background: Many individuals with systemic sclerosis (SSc) are at heightened risk for COVID-19 related morbidity and isolation due to interstitial lung disease, frailty, and immunosuppressant use. Minimal research has explored loneliness predictors in individuals with chronic illnesses during COVID-19. This study evaluated moderators of loneliness trajectories in individuals with SSc during COVID-19. Methods: Longitudinal data were analyzed across 30 timepoints from April 2020 to May 2022 from 775 adults in the Scleroderma Patient-centered Intervention Network (SPIN) COVID-19 Cohort. Hierarchical linear modeling evaluated cross-level moderators of loneliness trajectories, including marital status, baseline number of household members, number of virtual or telephone one-on-one or virtual group conversations, number of hours spent enjoying in-person household conversations or activities, and satisfaction with quality of in-person household conversations (all in the past week). Level-1 moderation analyses assessed effects of conversation, activity, and satisfaction means and slopes over time. Results: Baseline values were not statistically significant moderators of loneliness trajectories. Higher mean (averaged over time) virtual or telephone one-on-one and in-person household conversations, in-person household activity, and in-person household conversation satisfaction were associated with lower loneliness trajectories (ps <.05). The relationship between in-person household conversation satisfaction and loneliness trajectory was statistically significantly but minimally attenuated over time (p <.001). Conclusions: For people with SSc, higher mean conversation, activity, and satisfaction variables were associated with lower levels of loneliness during the pandemic, but changes in these social variables were generally not predictive of changes in loneliness. [ABSTRACT FROM AUTHOR]

The diagnostic accuracy of a screening tool is often characterized by its sensitivity and specificity. An analysis of these measures must consider their intrinsic correlation. In the context of an individual participant data meta-analysis, heterogeneity is one of the main components of the analysis. When using a random-effects meta-analytic model, prediction regions provide deeper insight into the effect of heterogeneity on the variability of estimated accuracy measures across the entire studied population, not just the average. This study aimed to investigate heterogeneity via prediction regions in an individual participant data meta-analysis of the sensitivity and specificity of the Patient Health Questionnaire-9 for screening to detect major depression. From the total number of studies in the pool, four dates were selected containing roughly 25%, 50%, 75% and 100% of the total number of participants. A bivariate random-effects model was fitted to studies up to and including each of these dates to jointly estimate sensitivity and specificity. Two-dimensional prediction regions were plotted in ROC-space. Subgroup analyses were carried out on sex and age, regardless of the date of the study. The dataset comprised 17,436 participants from 58 primary studies of which 2322 (13.3%) presented cases of major depression. Point estimates of sensitivity and specificity did not differ importantly as more studies were added to the model. However, correlation of the measures increased. As expected, standard errors of the logit pooled TPR and FPR consistently decreased as more studies were used, while standard deviations of the random-effects did not decrease monotonically. Subgroup analysis by sex did not reveal important contributions for observed heterogeneity; however, the shape of the prediction regions differed. Subgroup analysis by age did not reveal meaningful contributions to the heterogeneity and the prediction regions were similar in shape. Prediction intervals and regions reveal previously unseen trends in a dataset. In the context of a meta-analysis of diagnostic test accuracy, prediction regions can display the range of accuracy measures in different populations and settings. [ABSTRACT FROM AUTHOR]

The diagnostic accuracy of a screening tool is often characterized by its sensitivity and specificity. An analysis of these measures must consider their intrinsic correlation. In the context of an individual participant data meta-analysis, heterogeneity is one of the main components of the analysis. When using a random-effects meta-analytic model, prediction regions provide deeper insight into the effect of heterogeneity on the variability of estimated accuracy measures across the entire studied population, not just the average. This study aimed to investigate heterogeneity via prediction regions in an individual participant data meta-analysis of the sensitivity and specificity of the Patient Health Questionnaire-9 for screening to detect major depression. From the total number of studies in the pool, four dates were selected containing roughly 25%, 50%, 75% and 100% of the total number of participants. A bivariate random-effects model was fitted to studies up to and including each of these dates to jointly estimate sensitivity and specificity. Two-dimensional prediction regions were plotted in ROC-space. Subgroup analyses were carried out on sex and age, regardless of the date of the study. The dataset comprised 17,436 participants from 58 primary studies of which 2322 (13.3%) presented cases of major depression. Point estimates of sensitivity and specificity did not differ importantly as more studies were added to the model. However, correlation of the measures increased. As expected, standard errors of the logit pooled TPR and FPR consistently decreased as more studies were used, while standard deviations of the random-effects did not decrease monotonically. Subgroup analysis by sex did not reveal important contributions for observed heterogeneity; however, the shape of the prediction regions differed. Subgroup analysis by age did not reveal meaningful contributions to the heterogeneity and the prediction regions were similar in shape. Prediction intervals and regions reveal previously unseen trends in a dataset. In the context of a meta-analysis of diagnostic test accuracy, prediction regions can display the range of accuracy measures in different populations and settings. [ABSTRACT FROM AUTHOR]

Item 10 of the Edinburgh Postnatal Depression Scale (EPDS) is intended to assess thoughts of intentional self-harm but may also elicit concerns about accidental self-harm. It does not specifically address suicide ideation but, nonetheless, is sometimes used as an indicator of suicidality. The 9-item version of the EPDS (EPDS-9), which omits item 10, is sometimes used in research due to concern about positive endorsements of item 10 and necessary follow-up. We assessed the equivalence of total score correlations and screening accuracy to detect major depression using the EPDS-9 versus full EPDS among pregnant and postpartum women. We searched Medline, Medline In-Process and Other Non-Indexed Citations, PsycINFO, and Web of Science from database inception to October 3, 2018 for studies that administered the EPDS and conducted diagnostic classification for major depression based on a validated semi-structured or fully structured interview among women aged 18 or older during pregnancy or within 12 months of giving birth. We conducted an individual participant data meta-analysis. We calculated Pearson correlations with 95% prediction interval (PI) between EPDS-9 and full EPDS total scores using a random effects model. Bivariate random-effects models were fitted to assess screening accuracy. Equivalence tests were done by comparing the confidence intervals (CIs) around the pooled sensitivity and specificity differences to the equivalence margin of δ = 0.05. Individual participant data were obtained from 41 eligible studies (10,906 participants, 1407 major depression cases). The correlation between EPDS-9 and full EPDS scores was 0.998 (95% PI 0.991, 0.999). For sensitivity, the EPDS-9 and full EPDS were equivalent for cut-offs 7–12 (difference range − 0.02, 0.01) and the equivalence was indeterminate for cut-offs 13–15 (all differences − 0.04). For specificity, the EPDS-9 and full EPDS were equivalent for all cut-offs (difference range 0.00, 0.01). The EPDS-9 performs similarly to the full EPDS and can be used when there are concerns about the implications of administering EPDS item 10. Trial registration: The original IPDMA was registered in PROSPERO (CRD42015024785). [ABSTRACT FROM AUTHOR]

Women and gender-diverse individuals have faced disproportionate socioeconomic burden during COVID-19. There have been reports of greater negative mental health changes compared to men based on cross-sectional research that has not accounted for pre-COVID-19 differences. We compared mental health changes from pre-COVID-19 to during COVID-19 by sex or gender. MEDLINE (Ovid), PsycINFO (Ovid), CINAHL (EBSCO), EMBASE (Ovid), Web of Science Core Collection: Citation Indexes, China National Knowledge Infrastructure, Wanfang, medRxiv (preprints), and Open Science Framework Preprints (preprint server aggregator) were searched to August 30, 2021. Eligible studies included mental health symptom change data by sex or gender. 12 studies (10 unique cohorts) were included, all of which reported dichotomized sex or gender data. 9 cohorts reported results from March to June 2020, and 2 of these also reported on September or November to December 2020. One cohort included data pre-November 2020 data but did not provide dates. Continuous symptom change differences were not statistically significant for depression (standardized mean difference [SMD] = 0.12, 95% CI -0.09–0.33; 4 studies, 4,475 participants; I2 = 69.0%) and stress (SMD = − 0.10, 95% CI -0.21–0.01; 4 studies, 1,533 participants; I2 = 0.0%), but anxiety (SMD = 0.15, 95% CI 0.07–0.22; 4 studies, 4,344 participants; I2 = 3.0%) and general mental health (SMD = 0.15, 95% CI 0.12–0.18; 3 studies, 15,692 participants; I2 = 0.0%) worsened more among females/women than males/men. There were no significant differences in changes in proportions above cut-offs: anxiety (difference = − 0.05, 95% CI − 0.20–0.11; 1 study, 217 participants), depression (difference = 0.12, 95% CI -0.03–0.28; 1 study, 217 participants), general mental health (difference = − 0.03, 95% CI − 0.09–0.04; 3 studies, 18,985 participants; I2 = 94.0%), stress (difference = 0.04, 95% CI − 0.10–0.17; 1 study, 217 participants). Mental health outcomes did not differ or were worse by small amounts among women than men during early COVID-19. [ABSTRACT FROM AUTHOR]

Fatigue is prevalent among patients with systemic sclerosis (SSc). To date, studies investigating fatigue in SSc have been hampered by the instruments used to measure fatigue in SSc and have included patient-reported rather than objectively-rated measures of disease. The Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F) scale is a validated measure for assessing fatigue in SSc that, compared to other instruments, provides good coverage of the full range of the fatigue spectrum. The objective of this study was to assess sociodemographic and objectively-rated disease-related associates of fatigue, as measured by the FACIT-F, in a large sample of patients with SSc. Fatigue was assessed using the FACIT-F scale. Disease severity was assessed using Medsger's severity scale. Multivariable linear regression was performed to assess the independent associations between sociodemographic and medical variables and fatigue. Among 785 patients, the mean FACIT-F score was 32.2 (SD = 12.1). Being age 40-49 (reference = 60+; standardized regression coefficient ( β) = −0.11), less than post-secondary education ( β = 0.07), having more medical comorbidities ( β = −0.11) and more severe muscle ( β = −0.10), gastrointestinal ( β = −0.15), lung ( β = −0.13), and general system disease severity ( β = −0.13) were independently associated with more fatigue ( p < 0.05). Fatigue in SSc was independently associated with more severe disease. These data contribute to a better understanding of fatigue in SSc and help inform patient-centered research in SSc. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to the article "Validation of the Patient Health Questionnaire (PHQ)-9 for prenatal depression screening," by A.C. Sidebottom and colleagues in the October 2012 issue.

Background: The Liver Imaging Reporting and Data System (LI-RADS) does not consider factors extrinsic to the observation of interest, such as concurrent LR-5 observations.To evaluate whether the presence of a concurrent LR-5 observation is associated with a difference in the probability that LR-3 or LR-4 observations represent hepatocellular carcinoma (HCC) through an individual participant data (IPD) meta-analysis.Multiple databases were searched from 1/2014 to 2/2023 for studies evaluating the diagnostic accuracy of CT/MRI for HCC using LI-RADS v2014/2017/2018. The search strategy, study selection, and data collection process can be found at https://osf.io/rpg8x. Using a generalized linear mixed model (GLMM), IPD were pooled across studies and modeled simultaneously with a one-stage meta-analysis approach to estimate positive predictive value (PPV) of LR-3 and LR-4 observations without and with concurrent LR-5 for the diagnosis of HCC. Risk of bias was assessed using a composite reference standard and Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2).Twenty-nine studies comprising 2591 observations in 1456 patients (mean age 59 years, 1083 [74%] male) were included. 587/1960 (29.9%) LR-3 observations in 1009 patients had concurrent LR-5. The PPV for LR-3 observations with concurrent LR-5 was not significantly different from the PPV without LR-5 (45.4% vs 37.1%, p = 0.63). 264/631 (41.8%) LR-4 observations in 447 patients had concurrent LR-5. The PPV for LR-4 observations with concurrent LR-5 was not significantly different from LR-4 observations without concurrent LR-5 (88.6% vs 69.5%, p = 0.08). A sensitivity analysis for low-risk of bias studies (n = 9) did not differ from the primary analysis.The presence of concurrent LR-5 was not significantly associated with differences in PPV for HCC in LR-3 or LR-4 observations, supporting the current LI-RADS paradigm, wherein the presence of synchronous LR-5 may not alter the categorization of LR-3 and LR-4 observations.Purpose: The Liver Imaging Reporting and Data System (LI-RADS) does not consider factors extrinsic to the observation of interest, such as concurrent LR-5 observations.To evaluate whether the presence of a concurrent LR-5 observation is associated with a difference in the probability that LR-3 or LR-4 observations represent hepatocellular carcinoma (HCC) through an individual participant data (IPD) meta-analysis.Multiple databases were searched from 1/2014 to 2/2023 for studies evaluating the diagnostic accuracy of CT/MRI for HCC using LI-RADS v2014/2017/2018. The search strategy, study selection, and data collection process can be found at https://osf.io/rpg8x. Using a generalized linear mixed model (GLMM), IPD were pooled across studies and modeled simultaneously with a one-stage meta-analysis approach to estimate positive predictive value (PPV) of LR-3 and LR-4 observations without and with concurrent LR-5 for the diagnosis of HCC. Risk of bias was assessed using a composite reference standard and Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2).Twenty-nine studies comprising 2591 observations in 1456 patients (mean age 59 years, 1083 [74%] male) were included. 587/1960 (29.9%) LR-3 observations in 1009 patients had concurrent LR-5. The PPV for LR-3 observations with concurrent LR-5 was not significantly different from the PPV without LR-5 (45.4% vs 37.1%, p = 0.63). 264/631 (41.8%) LR-4 observations in 447 patients had concurrent LR-5. The PPV for LR-4 observations with concurrent LR-5 was not significantly different from LR-4 observations without concurrent LR-5 (88.6% vs 69.5%, p = 0.08). A sensitivity analysis for low-risk of bias studies (n = 9) did not differ from the primary analysis.The presence of concurrent LR-5 was not significantly associated with differences in PPV for HCC in LR-3 or LR-4 observations, supporting the current LI-RADS paradigm, wherein the presence of synchronous LR-5 may not alter the categorization of LR-3 and LR-4 observations.Methods: The Liver Imaging Reporting and Data System (LI-RADS) does not consider factors extrinsic to the observation of interest, such as concurrent LR-5 observations.To evaluate whether the presence of a concurrent LR-5 observation is associated with a difference in the probability that LR-3 or LR-4 observations represent hepatocellular carcinoma (HCC) through an individual participant data (IPD) meta-analysis.Multiple databases were searched from 1/2014 to 2/2023 for studies evaluating the diagnostic accuracy of CT/MRI for HCC using LI-RADS v2014/2017/2018. The search strategy, study selection, and data collection process can be found at https://osf.io/rpg8x. Using a generalized linear mixed model (GLMM), IPD were pooled across studies and modeled simultaneously with a one-stage meta-analysis approach to estimate positive predictive value (PPV) of LR-3 and LR-4 observations without and with concurrent LR-5 for the diagnosis of HCC. Risk of bias was assessed using a composite reference standard and Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2).Twenty-nine studies comprising 2591 observations in 1456 patients (mean age 59 years, 1083 [74%] male) were included. 587/1960 (29.9%) LR-3 observations in 1009 patients had concurrent LR-5. The PPV for LR-3 observations with concurrent LR-5 was not significantly different from the PPV without LR-5 (45.4% vs 37.1%, p = 0.63). 264/631 (41.8%) LR-4 observations in 447 patients had concurrent LR-5. The PPV for LR-4 observations with concurrent LR-5 was not significantly different from LR-4 observations without concurrent LR-5 (88.6% vs 69.5%, p = 0.08). A sensitivity analysis for low-risk of bias studies (n = 9) did not differ from the primary analysis.The presence of concurrent LR-5 was not significantly associated with differences in PPV for HCC in LR-3 or LR-4 observations, supporting the current LI-RADS paradigm, wherein the presence of synchronous LR-5 may not alter the categorization of LR-3 and LR-4 observations.Results: The Liver Imaging Reporting and Data System (LI-RADS) does not consider factors extrinsic to the observation of interest, such as concurrent LR-5 observations.To evaluate whether the presence of a concurrent LR-5 observation is associated with a difference in the probability that LR-3 or LR-4 observations represent hepatocellular carcinoma (HCC) through an individual participant data (IPD) meta-analysis.Multiple databases were searched from 1/2014 to 2/2023 for studies evaluating the diagnostic accuracy of CT/MRI for HCC using LI-RADS v2014/2017/2018. The search strategy, study selection, and data collection process can be found at https://osf.io/rpg8x. Using a generalized linear mixed model (GLMM), IPD were pooled across studies and modeled simultaneously with a one-stage meta-analysis approach to estimate positive predictive value (PPV) of LR-3 and LR-4 observations without and with concurrent LR-5 for the diagnosis of HCC. Risk of bias was assessed using a composite reference standard and Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2).Twenty-nine studies comprising 2591 observations in 1456 patients (mean age 59 years, 1083 [74%] male) were included. 587/1960 (29.9%) LR-3 observations in 1009 patients had concurrent LR-5. The PPV for LR-3 observations with concurrent LR-5 was not significantly different from the PPV without LR-5 (45.4% vs 37.1%, p = 0.63). 264/631 (41.8%) LR-4 observations in 447 patients had concurrent LR-5. The PPV for LR-4 observations with concurrent LR-5 was not significantly different from LR-4 observations without concurrent LR-5 (88.6% vs 69.5%, p = 0.08). A sensitivity analysis for low-risk of bias studies (n = 9) did not differ from the primary analysis.The presence of concurrent LR-5 was not significantly associated with differences in PPV for HCC in LR-3 or LR-4 observations, supporting the current LI-RADS paradigm, wherein the presence of synchronous LR-5 may not alter the categorization of LR-3 and LR-4 observations.Conclusion: The Liver Imaging Reporting and Data System (LI-RADS) does not consider factors extrinsic to the observation of interest, such as concurrent LR-5 observations.To evaluate whether the presence of a concurrent LR-5 observation is associated with a difference in the probability that LR-3 or LR-4 observations represent hepatocellular carcinoma (HCC) through an individual participant data (IPD) meta-analysis.Multiple databases were searched from 1/2014 to 2/2023 for studies evaluating the diagnostic accuracy of CT/MRI for HCC using LI-RADS v2014/2017/2018. The search strategy, study selection, and data collection process can be found at https://osf.io/rpg8x. Using a generalized linear mixed model (GLMM), IPD were pooled across studies and modeled simultaneously with a one-stage meta-analysis approach to estimate positive predictive value (PPV) of LR-3 and LR-4 observations without and with concurrent LR-5 for the diagnosis of HCC. Risk of bias was assessed using a composite reference standard and Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2).Twenty-nine studies comprising 2591 observations in 1456 patients (mean age 59 years, 1083 [74%] male) were included. 587/1960 (29.9%) LR-3 observations in 1009 patients had concurrent LR-5. The PPV for LR-3 observations with concurrent LR-5 was not significantly different from the PPV without LR-5 (45.4% vs 37.1%, p = 0.63). 264/631 (41.8%) LR-4 observations in 447 patients had concurrent LR-5. The PPV for LR-4 observations with concurrent LR-5 was not significantly different from LR-4 observations without concurrent LR-5 (88.6% vs 69.5%, p = 0.08). A sensitivity analysis for low-risk of bias studies (n = 9) did not differ from the primary analysis.The presence of concurrent LR-5 was not significantly associated with differences in PPV for HCC in LR-3 or LR-4 observations, supporting the current LI-RADS paradigm, wherein the presence of synchronous LR-5 may not alter the categorization of LR-3 and LR-4 observations. [ABSTRACT FROM AUTHOR]