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51. How to plan and manage an individual participant data meta‐analysis. An illustrative toolkit.

Author

Maxwell, Lauren, Shreedhar, Priya, Carabali, Mabel, and Levis, Brooke

Subjects
STANDARD operating procedure, PROJECT management, PROGNOSTIC models, BUDGET, TIME management
Abstract

Individual participant data meta‐analyses (IPD‐MAs) have several benefits over standard aggregate data meta‐analyses, including the consideration of additional participants, follow‐up time, and the joint consideration of study‐ and participant‐level heterogeneity for improved diagnostic and prognostic model development and evaluation. However, IPD‐MAs are resource‐intensive and require careful budgeting of time from data contributing groups, a dedicated management team, diversity of expertise, clearly documented data sharing and authorship agreements, and consistent and clear communication. We present a toolkit to facilitate the implementation and management of IPD‐MAs, from study recruitment to retrospective harmonization. The toolkit was developed and refined over our work on multiple multinational IPD‐MA projects over the last 13 years. The toolkit's budget and email templates, agreements, project management spreadsheets, and standard operating procedures are meant to facilitate routine IPD‐MA tasks to expedite implementing and managing future IPD‐MA projects. [ABSTRACT FROM AUTHOR]

Published
2024
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52. CT/MRI and CEUS LI-RADS Major Features Association with Hepatocellular Carcinoma: Individual Patient Data Meta-Analysis

Author

van der Pol, Christian B., primary, McInnes, Matthew D. F., additional, Salameh, Jean-Paul, additional, Levis, Brooke, additional, Chernyak, Victoria, additional, Sirlin, Claude B., additional, Bashir, Mustafa R., additional, Allen, Brian C., additional, Burke, Lauren M. B., additional, Choi, Jin-Young, additional, Choi, Sang Hyun, additional, Forner, Alejandro, additional, Fraum, Tyler J., additional, Giamperoli, Alice, additional, Jiang, Hanyu, additional, Joo, Ijin, additional, Kang, Zhen, additional, Kierans, Andrea S., additional, Kang, Hyo-Jin, additional, Khatri, Gaurav, additional, Kim, Jung Hoon, additional, Kim, Myeong-Jin, additional, Kim, So Yeon, additional, Kim, Yeun-Yoon, additional, Kwon, Heejin, additional, Lee, Jeong Min, additional, Lewis, Sara C., additional, McGinty, Katrina A., additional, Mulazzani, Lorenzo, additional, Park, Mi-Suk, additional, Piscaglia, Fabio, additional, Podgórska, Joanna, additional, Reiner, Caecilia S., additional, Ronot, Maxime, additional, Rosiak, Grzegorz, additional, Song, Bin, additional, Song, Ji Soo, additional, Tang, An, additional, Terzi, Eleonora, additional, Wang, Jin, additional, Wang, Wei, additional, Wilson, Stephanie R., additional, and Yokoo, Takeshi, additional

Published
2023
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55. How to Critically Appraise and Interpret Systematic Reviews and Meta-Analyses of Diagnostic Accuracy: A User Guide

Author

Frank, Robert A., primary, Salameh, Jean-Paul, additional, Islam, Nayaar, additional, Yang, Bada, additional, Murad, Mohammad Hassan, additional, Mustafa, Reem, additional, Leeflang, Mariska, additional, Bossuyt, Patrick M., additional, Takwoingi, Yemisi, additional, Whiting, Penny, additional, Dawit, Haben, additional, Kang, Stella K., additional, Ebrahimzadeh, Sanam, additional, Levis, Brooke, additional, Hutton, Brian, additional, and McInnes, Matthew D. F., additional

Published
2023
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56. Comparison of mental health symptoms before and during the covid-19 pandemic: evidence from a systematic review and meta-analysis of 134 cohorts

Author

Sun, Ying, primary, Wu, Yin, additional, Fan, Suiqiong, additional, Dal Santo, Tiffany, additional, Li, Letong, additional, Jiang, Xiaowen, additional, Li, Kexin, additional, Wang, Yutong, additional, Tasleem, Amina, additional, Krishnan, Ankur, additional, He, Chen, additional, Bonardi, Olivia, additional, Boruff, Jill T, additional, Rice, Danielle B, additional, Markham, Sarah, additional, Levis, Brooke, additional, Azar, Marleine, additional, Thombs-Vite, Ian, additional, Neupane, Dipika, additional, Agic, Branka, additional, Fahim, Christine, additional, Martin, Michael S, additional, Sockalingam, Sanjeev, additional, Turecki, Gustavo, additional, Benedetti, Andrea, additional, and Thombs, Brett D, additional

Published
2023
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58. Psychosocial Aspects of Scleroderma

Author

Kwakkenbos, Linda, Delisle, Vanessa C., Fox, Rina S., Gholizadeh, Shadi, Jewett, Lisa R., Levis, Brooke, Milette, Katherine, Mills, Sarah D., Malcarne, Vanessa L., and Thombs, Brett D.

Published
2015
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59. The association of sociodemographic and objectively-assessed disease variables with fatigue in systemic sclerosis: an analysis of 785 Canadian Scleroderma Research Group Registry patients

Author

Levis, Brooke, Kwakkenbos, Linda, Hudson, Marie, Baron, Murray, Thombs, Brett D., Baron, M., Hudson, M., Gyger, G., Pope, J., Larché, M., Khalidi, N., Masetto, A., Sutton, E., Robinson, D., Rodriguez-Reyna, T.S., Smith, D., Thorne, C., Fortin, P.R., Fritzler, M., and and the Canadian Scleroderma Research Group

Published
2017
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61. Additional file 1 of Randomized controlled trial of an internet-based self-guided hand exercise program to improve hand function in people with systemic sclerosis: the Scleroderma Patient-centered Intervention Network Hand Exercise Program (SPIN-HAND) trial

Author

Kwakkenbos, Linda, Carrier, Marie-Eve, Welling, Joep, Levis, Brooke, Levis, Alexander W., Sauve, Maureen, Turner, Kimberly A., Tao, Lydia, Aguila, Kylene, Carboni-Jiménez, Andrea, Cañedo-Ayala, Mara, Harb, Sami, van den Ende, Cornelia, Hudson, Marie, van Breda, Ward, Nguyen, Christelle, Boutron, Isabelle, Rannou, François, Thombs, Brett D., and Mouthon, Luc

Abstract

Additional file 1. Supplementary material.

Published
2023
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64. A qualitative interview study exploring the psychological health impacts of the SPIN-CHAT program among people with systemic sclerosis at the onset of COVID-19: perceptions of trial participants and research team members

Author

Wurz, Amanda, primary, Duchek, Delaney, additional, Ellis, Kelsey, additional, Bansal, Mannat, additional, Carrier, Marie-Eve, additional, Tao, Lydia, additional, Dyas, Laura, additional, Kwakkenbos, Linda, additional, Levis, Brooke, additional, El-Baalbaki, Ghassan, additional, Rice, Danielle B., additional, Wu, Yin, additional, Henry, Richard S., additional, Bustamante, Laura, additional, Harb, Sami, additional, Hebblethwaite, Shannon, additional, Patten, Scott B., additional, Bartlett, Susan J., additional, Varga, John, additional, Mouthon, Luc, additional, Markham, Sarah, additional, Thombs, Brett D., additional, Culos-Reed, S. Nicole, additional, Fortuné, Catherine, additional, Gietzen, Amy, additional, Guillot, Geneviève, additional, Nielsen, Karen, additional, Lewis, Nancy, additional, Richard, Michelle, additional, Sauvé, Maureen, additional, Welling, Joep, additional, Battaglio, Lacey, additional, Burger, Tina, additional, Burleigh, Adrienne, additional, Collins, Peggy, additional, Davila, Jacob, additional, Inglese, Louise, additional, Kaplan, Franny, additional, Konrad, Violet, additional, Petrella, Silvia, additional, Potvin, Audrey, additional, Puccio, Natalie, additional, Gottesman, Karen, additional, Hudson, Marie, additional, Hummers, Laura K., additional, Lawrie-Jones, Amanda, additional, Malcarne, Vanessa L., additional, Mayes, Maureen D., additional, Nielson, Warren R., additional, Assassi, Shervin, additional, Ells, Carolyn, additional, Fligelstone, Kim, additional, Frech, Tracy, additional, Harel, Daphna, additional, Hinchcliff, Monique, additional, Johnson, Sindhu R., additional, Larche, Maggie, additional, Leite, Catarina, additional, Nguyen, Christelle, additional, Pope, Janet, additional, Rannou, François, additional, Rodriguez-Reyna, Tatiana Sofia, additional, Schouffoer, Anne A., additional, Suarez-Almazor, Maria E., additional, Agard, Christian, additional, Ait Abdallah, Nassim, additional, André, Marc, additional, Bernstein, Elana J., additional, Berthier, Sabine, additional, Bissonnette, Lyne, additional, Bruns, Alessandra, additional, Carreira, Patricia, additional, Casadevall, Marion, additional, Chaigne, Benjamin, additional, Chung, Lorinda, additional, Crichi, Benjamin, additional, Denton, Christopher, additional, Domsic, Robyn, additional, Dunne, James V., additional, Dunogue, Bertrand, additional, Fare, Regina, additional, Farge-Bancel, Dominique, additional, Fortin, Paul R., additional, Gordon, Jessica, additional, Granel-Rey, Brigitte, additional, Guffroy, Aurélien, additional, Gyger, Genevieve, additional, Hachulla, Eric, additional, Herrick, Ariane L., additional, Hoa, Sabrina, additional, Ikic, Alena, additional, Jones, Niall, additional, Khalidi, Nader, additional, Lambert, Marc, additional, Launay, David, additional, Lee, Yvonne C., additional, Maillard, Hélène, additional, Maltez, Nancy, additional, Manning, Joanne, additional, Marie, Isabelle, additional, Lopez, Maria Martin, additional, Martin, Thierry, additional, Masetto, Ariel, additional, Maurier, François, additional, Mekinian, Arsene, additional, Díaz, Sheila Melchor, additional, Nikpour, Mandana, additional, Olagne, Louis, additional, Poindron, Vincent, additional, Proudman, Susanna, additional, Régent, Alexis, additional, Rivière, Sébastien, additional, Robinson, David, additional, Rodríguez Almazar, Esther, additional, Roux, Sophie, additional, Smets, Perrine, additional, Sobanski, Vincent, additional, Spiera, Robert, additional, Steen, Virginia, additional, Sutton, Evelyn, additional, Thorne, Carter, additional, Wilcox, Pearce, additional, Ayala, Mara Cañedo, additional, Discepola, Marie-Nicole, additional, Montemurro, Laury, additional, Nassar, Elsa Lynn, additional, Neyer, Marieke Alexandra, additional, Nordlund, Julia, additional, Østbø, Nora, additional, and Provencher, Sabrina, additional

Published
2023
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66. ‘Optimal’ cutoff selection in studies of depression screening tool accuracy using the PHQ‐9, EPDS, or HADS‐D: A meta‐research study

Author

Brehaut, Eliana, primary, Neupane, Dipika, additional, Levis, Brooke, additional, Wu, Yin, additional, Sun, Ying, additional, Ioannidis, John P. A., additional, Markham, Sarah, additional, Cuijpers, Pim, additional, Patten, Scott B., additional, Benedetti, Andrea, additional, and Thombs, Brett D., additional

Published
2022
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69. 'Optimal' cutoff selection in studies of depression screening tool accuracy using the PHQ‐9, EPDS, or HADS‐D: A meta‐research study.

Author

Brehaut, Eliana, Neupane, Dipika, Levis, Brooke, Wu, Yin, Sun, Ying, Ioannidis, John P. A., Markham, Sarah, Cuijpers, Pim, Patten, Scott B., Benedetti, Andrea, and Thombs, Brett D.

Subjects
MEDICAL screening, EDINBURGH Postnatal Depression Scale, MENTAL depression
Abstract

Objectives: Optimal cutoff thresholds are selected to separate 'positive' from 'negative' screening results. We evaluated how depression screening tool studies select optimal cutoffs. Methods: We included studies from previously conducted meta‐analyses of Patient Health Questionnaire‐9, Edinburgh Postnatal Depression Scale, or Hospital Anxiety and Depression Scale—Depression accuracy. Outcomes included whether an optimal cutoff was selected, method used, recommendations made, and reporting guideline and protocol citation. Results: Of 212 included studies, 172 (81%) attempted to identify an optimal cutoff, and 147 of these 172 (85%) reported one or more methods. Methods were heterogeneous with Youden's J (N = 35, 23%) most common. Only 23 of 147 (16%) studies described a rationale for their method. Rationales focused on balancing sensitivity and specificity without describing why desirable. 131 of 172 studies (76%) identified an optimal cutoff other than the standard; most did not make use recommendations (N = 56; 43%) or recommended using a non‐standard cutoff (N = 53; 40%). Only 4 studies cited a reporting guideline, and 4 described a protocol with optimal cutoff selection methods, but none used the protocol method in the published study. Conclusions: Research is needed to guide how selection of cutoffs for depression screening tools can be standardized and reflect clinical considerations. [ABSTRACT FROM AUTHOR]

Published
2023
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72. Individual participant data meta-analysis to compare EPDS accuracy to detect major depression with and without the self-harm item

Author

Qiu, Xia, primary, Wu, Yin, additional, Sun, Ying, additional, Levis, Brooke, additional, Tian, Jizhou, additional, Boruff, Jill, additional, Cuijpers, Pim, additional, Ioannidis, John, additional, Markham, Sarah, additional, Ziegelstein, Roy, additional, Vigod, Simone, additional, Benedetti, Andrea, additional, and Thombs, Brett, additional

Published
2022
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73. External validation of a shortened screening tool using individual participant data meta-analysis: A case study of the Patient Health Questionnaire-Dep-4

Author

Harel, Daphna, primary, Levis, Brooke, additional, Sun, Ying, additional, Fischer, Felix, additional, Ioannidis, John P.A., additional, Cuijpers, Pim, additional, Patten, Scott B., additional, Ziegelstein, Roy C., additional, Markham, Sarah, additional, Benedetti, Andrea, additional, Thombs, Brett D., additional, He, Chen, additional, Wu, Yin, additional, Krishnan, Ankur, additional, Mani Bhandari, Parash, additional, Neupane, Dipika, additional, Negeri, Zelalem, additional, Imran, Mahrukh, additional, Rice, Danielle B., additional, Riehm, Kira E., additional, Azar, Marleine, additional, Levis, Alexander W., additional, Boruff, Jill, additional, Gilbody, Simon, additional, Kloda, Lorie A., additional, Amtmann, Dagmar, additional, Ayalon, Liat, additional, Baradaran, Hamid R., additional, Beraldi, Anna, additional, Bernstein, Charles N., additional, Bhana, Arvin, additional, Imma Buji, Ryna, additional, Chagas, Marcos H., additional, C. N. Chan, Juliana, additional, Fong Chan, Lai, additional, Chibanda, Dixon, additional, Conway, Aaron, additional, Daray, Federico M., additional, de Man-van Ginkel, Janneke M., additional, Diez-Quevedo, Crisanto, additional, Field, Sally, additional, R. W. Fisher, Jane, additional, Fung, Daniel, additional, Garman, Emily C., additional, Flisher, Alan J, additional, Gelaye, Bizu, additional, Gholizadeh, Leila, additional, Gibson, Lorna J., additional, Green, Eric P., additional, Hall, Brian J., additional, Hantsoo, Liisa, additional, Haroz, Emily E., additional, Härter, Martin, additional, Hegerl, Ulrich, additional, Hides, Leanne, additional, Hobfoll, Stevan E., additional, Honikman, Simone, additional, Hudson, Marie, additional, Hyphantis, Thomas, additional, Inagaki, Masatoshi, additional, Jin Jeon, Hong, additional, Jetté, Nathalie, additional, Khamseh, Mohammad E., additional, Köhler, Sebastian, additional, Kohrt, Brandon A., additional, Kwan, Yunxin, additional, Lamers, Femke, additional, Asunción Lara, Maria, additional, Levin-Aspenson, Holly F., additional, Liu, Shen-Ing, additional, Lotrakul, Manote, additional, Loureiro, Sonia R., additional, Löwe, Bernd, additional, Luitel, Nagendra P., additional, Lund, Crick, additional, Ann Marrie, Ruth, additional, Marx, Brian P., additional, Mohd Sidik, Sherina, additional, Munhoz, Tiago N., additional, Muramatsu, Kumiko, additional, E. M. Nakku, Juliet, additional, Navarrete, Laura, additional, Osório, Flávia L., additional, Persoons, Philippe, additional, Picardi, Angelo, additional, Pugh, Stephanie L., additional, Quinn, Terence J., additional, Rancans, Elmars, additional, Rathod, Sujit D., additional, Reuter, Katrin, additional, Rowe, Heather J., additional, Santos, Iná S., additional, Schram, Miranda T., additional, Shaaban, Juwita, additional, Shinn, Eileen H., additional, Spangenberg, Lena, additional, Stafford, Lesley, additional, Sung, Sharon C., additional, Suzuki, Keiko, additional, Lin Lynnette Tan, Pei, additional, Taylor-Rowan, Martin, additional, Tran, Thach D., additional, van der Feltz-Cornelis, Christina M., additional, van Heyningen, Thandi, additional, van Weert, Henk C., additional, Wagner, Lynne I., additional, Li Wang, Jian, additional, Watson, David, additional, Wynter, Karen, additional, Yamada, Mitsuhiko, additional, Zhi Zeng, Qing, additional, and Zhang, Yuying, additional

Published
2022
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75. Templates and resources for individual participant data meta-analyses (IPD-MAs)

Author

Maxwell, Lauren, Levis, Brooke, Carabali, Mabel, and Shreedhar, Priya

Subjects
Individual participant data meta-analyses, Toolkit, Project management, Templates, IPD-MA
Abstract

Toolkit containing budget template, gantt chart, data sharing and authorship agreements, email templates, project management spreadsheets, and standard operating procedures, as a starting point for many common IPD-MA tasks in order to expedite the development and management of future IPD-MA projects

Published
2022
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78. Exploring research team members' and trial participants' perceptions of acceptability and implementation within one videoconference-based supportive care program for individuals affected by systemic sclerosis during COVID-19: a qualitative interview study

Author

Wurz, Amanda, Ellis, Kelsey, Duchek, Delaney, Bansal, Mannat, Carrier, Marie-Eve, Tao, Lydia, Dyas, Laura, Kwakkenbos, Linda, Levis, Brooke, El-Baalbaki, Ghassan, Rice, Danielle B, Wu, Yin, Henry, Richard S, Bustamante, Laura, Harb, Sami, Hebblethwaite, Shannon, Patten, Scott B, Bartlett, Susan J, Varga, John, and Mouthon, Luc

Abstract

The SPIN-CHAT Program was designed to support mental health among individuals with systemic sclerosis (SSc; commonly known as scleroderma) and at least mild anxiety symptoms at the onset of COVID-19. The program was formally evaluated in the SPIN-CHAT Trial. Little is known about program and trial acceptability, and factors impacting implementation from the perspectives of research team members and trial participants. Thus, the propose of this follow-up study was to explore research team members' and trial participants' experiences with the program and trial to identify factors impacting acceptability and successful implementation. Data were collected cross-sectionally through one-on-one, videoconference-based, semi-structured interviews with 22 research team members and 30 purposefully recruited trial participants (M age = 54.9, SD = 13.0 years). A social constructivist paradigm was adopted, and data were analyzed thematically. Data were organized into seven themes: (i) getting started: the importance of prolonged engagement and exceeding expectations; (ii) designing the program and trial: including multiple features; (iii) training: research team members are critical to positive program and trial experiences; (iv) offering the program and trial: it needs to be flexible and patient-oriented; (v) maximizing engagement: navigating and managing group dynamics; (vi) delivering a videoconference-based supportive care intervention: necessary, appreciated, and associated with some barriers; and (vii) refining the program and trial: considering modification when offered beyond the period of COVID-19 restrictions. Trial participants were satisfied with and found the SPIN-CHAT Program and Trial to be acceptable. Results offer implementation data that can guide the design, development, and refinement of other supportive care programs seeking to promote psychological health during and beyond COVID-19. [ABSTRACT FROM AUTHOR]

Published
2023
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79. A case study of an individual participant data meta-analysis of diagnostic accuracy showed that prediction regions represented heterogeneity well.

Author

de Lara, Aurelio López Malo Vázquez, Bhandari, Parash Mani, Wu, Yin, Levis, Brooke, Thombs, Brett, Benedetti, Andrea, DEPRESsion Screening Data (DEPRESSD) PHQ-9 Collaboration, Sun, Ying, He, Chen, Krishnan, Ankur, Neupane, Dipika, Negeri, Zelalem, Imran, Mahrukh, Rice, Danielle B., Riehm, Kira E., Saadat, Nazanin, Azar, Marleine, Boruff, Jill, Cuijpers, Pim, and Gilbody, Simon

Subjects
HETEROGENEITY, MEDICAL screening, MENTAL depression, FORECASTING, SENSITIVITY & specificity (Statistics), RANDOM effects model, BIVARIATE analysis
Abstract

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]

Published
2023
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81. Overestimation of Postpartum Depression Prevalence Based on a 5-item Version of the EPDS:Systematic Review and Individual Participant Data Meta-analysis

Author

Thombs, Brett D., Levis, Brooke, Lyubenova, Anita, Neupane, Dipika, Negeri, Zelalem, Wu, Yin, Sun, Ying, He, Chen, Krishnan, Ankur, Vigod, Simone N., Bhandari, Parash Mani, Imran, Mahrukh, Rice, Danielle B., Azar, Marleine, Chiovitti, Matthew J., Saadat, Nazanin, Riehm, Kira E., Boruff, Jill T., Cuijpers, Pim, Gilbody, Simon, Ioannidis, John P.A., Kloda, Lorie A., Patten, Scott B., Shrier, Ian, Ziegelstein, Roy C., Comeau, Liane, Mitchell, Nicholas D., Tonelli, Marcello, Barnes, Jacqueline, Beck, Cheryl Tatano, Bindt, Carola, Figueiredo, Barbara, Helle, Nadine, Howard, Louise M., Kohlhoff, Jane, Kozinszky, Zoltán, Leonardou, Angeliki A., Radoš, Sandra Nakić, Quispel, Chantal, Rochat, Tamsen J., Stein, Alan, Stewart, Robert C., Tadinac, Meri, Tandon, S. Darius, Tendais, Iva, Töreki, Annamária, Tran, Thach D., Trevillion, Kylee, Turner, Katherine, Vega-Dienstmaier, Johann M., and Benedetti, Andrea

Subjects
obstetrics and gynecology, SDG 3 - Good Health and Well-being, statistics and research methods, epidemiology, evidence-based medicine, psychiatry
Abstract

Objective: The Maternal Mental Health in Canada, 2018/2019, survey reported that 18% of 7,085 mothers who recently gave birth reported “feelings consistent with postpartum depression” based on scores ≥7 on a 5-item version of the Edinburgh Postpartum Depression Scale (EPDS-5). The EPDS-5 was designed as a screening questionnaire, not to classify disorders or estimate prevalence; the extent to which EPDS-5 results reflect depression prevalence is unknown. We investigated EPDS-5 ≥7 performance relative to major depression prevalence based on a validated diagnostic interview, the Structured Clinical Interview for DSM (SCID). Methods: We searched Medline, Medline In-Process & Other Non-Indexed Citations, PsycINFO, and the Web of Science Core Collection through June 2016 for studies with data sets with item response data to calculate EPDS-5 scores and that used the SCID to ascertain depression status. We conducted an individual participant data meta-analysis to estimate pooled percentage of EPDS-5 ≥7, pooled SCID major depression prevalence, and the pooled difference in prevalence. Results: A total of 3,958 participants from 19 primary studies were included. Pooled prevalence of SCID major depression was 9.2% (95% confidence interval [CI] 6.0% to 13.7%), pooled percentage of participants with EPDS-5 ≥7 was 16.2% (95% CI 10.7% to 23.8%), and pooled difference was 8.0% (95% CI 2.9% to 13.2%). In the 19 included studies, mean and median ratios of EPDS-5 to SCID prevalence were 2.1 and 1.4 times. Conclusions: Prevalence estimated based on EPDS-5 ≥7 appears to be substantially higher than the prevalence of major depression. Validated diagnostic interviews should be used to establish prevalence.

Published
2020
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82. CT/MRI and CEUS LI-RADS Major Features Association with Hepatocellular Carcinoma: Individual Patient Data Meta-Analysis

Author

van der Pol, Christian B, McInnes, Matthew D F, Salameh, Jean-Paul, Levis, Brooke, Chernyak, Victoria, Sirlin, Claude B, Bashir, Mustafa R, Allen, Brian C, Burke, Lauren M B, Choi, Jin-Young, Choi, Sang Hyun, Forner, Alejandro, Fraum, Tyler J, Giamperoli, Alice, Jiang, Hanyu, Joo, Ijin, Kang, Zhen, Kierans, Andrea S, Kang, Hyo-Jin, Khatri, Gaurav, Kim, Jung Hoon, Kim, Myeong-Jin, Kim, So Yeon, Kim, Yeun-Yoon, Kwon, Heejin, Lee, Jeong Min, Lewis, Sara C, McGinty, Katrina A, Mulazzani, Lorenzo, Park, Mi-Suk, et al, University of Zurich, and McInnes, Matthew D F

Subjects
10042 Clinic for Diagnostic and Interventional Radiology, 2741 Radiology, Nuclear Medicine and Imaging, 610 Medicine & health
Published
2022

83. CT/MRI and CEUS LI-RADS Major Features Association with Hepatocellular Carcinoma: Individual Patient Data Meta-Analysis

Author

van der Pol, Christian B; https://orcid.org/0000-0002-1718-2619, McInnes, Matthew D F; https://orcid.org/0000-0001-8404-4075, Salameh, Jean-Paul; https://orcid.org/0000-0002-4105-2056, Levis, Brooke; https://orcid.org/0000-0002-4310-3689, Chernyak, Victoria; https://orcid.org/0000-0002-5715-1403, Sirlin, Claude B; https://orcid.org/0000-0002-6639-9072, Bashir, Mustafa R; https://orcid.org/0000-0001-8800-5057, Allen, Brian C; https://orcid.org/0000-0003-2273-0162, Burke, Lauren M B; https://orcid.org/0000-0003-1074-5543, Choi, Jin-Young; https://orcid.org/0000-0002-9025-6274, Choi, Sang Hyun; https://orcid.org/0000-0002-6898-6617, Forner, Alejandro; https://orcid.org/0000-0002-9014-4950, Fraum, Tyler J; https://orcid.org/0000-0001-6573-5081, Giamperoli, Alice; https://orcid.org/0000-0003-3717-8104, Jiang, Hanyu; https://orcid.org/0000-0002-7726-1618, Joo, Ijin; https://orcid.org/0000-0002-1341-4072, Kang, Zhen, Kierans, Andrea S; https://orcid.org/0000-0001-9672-1803, Kang, Hyo-Jin; https://orcid.org/0000-0002-6771-2112, Khatri, Gaurav; https://orcid.org/0000-0002-3485-1650, Kim, Jung Hoon; https://orcid.org/0000-0002-8090-7758, Kim, Myeong-Jin; https://orcid.org/0000-0001-7949-5402, Kim, So Yeon, Kim, Yeun-Yoon; https://orcid.org/0000-0003-2018-5332, Kwon, Heejin; https://orcid.org/0000-0002-2001-953X, Lee, Jeong Min; https://orcid.org/0000-0003-0561-8777, Lewis, Sara C; https://orcid.org/0000-0002-4713-6453, McGinty, Katrina A; https://orcid.org/0000-0001-8707-4958, Mulazzani, Lorenzo, Park, Mi-Suk; https://orcid.org/0000-0001-5817-2444, et al, van der Pol, Christian B; https://orcid.org/0000-0002-1718-2619, McInnes, Matthew D F; https://orcid.org/0000-0001-8404-4075, Salameh, Jean-Paul; https://orcid.org/0000-0002-4105-2056, Levis, Brooke; https://orcid.org/0000-0002-4310-3689, Chernyak, Victoria; https://orcid.org/0000-0002-5715-1403, Sirlin, Claude B; https://orcid.org/0000-0002-6639-9072, Bashir, Mustafa R; https://orcid.org/0000-0001-8800-5057, Allen, Brian C; https://orcid.org/0000-0003-2273-0162, Burke, Lauren M B; https://orcid.org/0000-0003-1074-5543, Choi, Jin-Young; https://orcid.org/0000-0002-9025-6274, Choi, Sang Hyun; https://orcid.org/0000-0002-6898-6617, Forner, Alejandro; https://orcid.org/0000-0002-9014-4950, Fraum, Tyler J; https://orcid.org/0000-0001-6573-5081, Giamperoli, Alice; https://orcid.org/0000-0003-3717-8104, Jiang, Hanyu; https://orcid.org/0000-0002-7726-1618, Joo, Ijin; https://orcid.org/0000-0002-1341-4072, Kang, Zhen, Kierans, Andrea S; https://orcid.org/0000-0001-9672-1803, Kang, Hyo-Jin; https://orcid.org/0000-0002-6771-2112, Khatri, Gaurav; https://orcid.org/0000-0002-3485-1650, Kim, Jung Hoon; https://orcid.org/0000-0002-8090-7758, Kim, Myeong-Jin; https://orcid.org/0000-0001-7949-5402, Kim, So Yeon, Kim, Yeun-Yoon; https://orcid.org/0000-0003-2018-5332, Kwon, Heejin; https://orcid.org/0000-0002-2001-953X, Lee, Jeong Min; https://orcid.org/0000-0003-0561-8777, Lewis, Sara C; https://orcid.org/0000-0002-4713-6453, McGinty, Katrina A; https://orcid.org/0000-0001-8707-4958, Mulazzani, Lorenzo, Park, Mi-Suk; https://orcid.org/0000-0001-5817-2444, and et al

Abstract

Background The Liver Imaging Reporting and Data System (LI-RADS) assigns a risk category for hepatocellular carcinoma (HCC) to imaging observations. Establishing the contributions of major features can inform the diagnostic algorithm. Purpose To perform a systematic review and individual patient data meta-analysis to establish the probability of HCC for each LI-RADS major feature using CT/MRI and contrast-enhanced US (CEUS) LI-RADS in patients at high risk for HCC. Materials and Methods Multiple databases (MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and Scopus) were searched for studies from January 2014 to September 2019 that evaluated the accuracy of CT, MRI, and CEUS for HCC detection using LI-RADS (CT/MRI LI-RADS, versions 2014, 2017, and 2018; CEUS LI-RADS, versions 2016 and 2017). Data were centralized. Clustering was addressed at the study and patient levels using mixed models. Adjusted odds ratios (ORs) with 95% CIs were determined for each major feature using multivariable stepwise logistic regression. Risk of bias was assessed using Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) (PROSPERO protocol: CRD42020164486). Results A total of 32 studies were included, with 1170 CT observations, 3341 MRI observations, and 853 CEUS observations. At multivariable analysis of CT/MRI LI-RADS, all major features were associated with HCC, except threshold growth (OR, 1.6; 95% CI: 0.7, 3.6; P = .07). Nonperipheral washout (OR, 13.2; 95% CI: 9.0, 19.2; P = .01) and nonrim arterial phase hyperenhancement (APHE) (OR, 10.3; 95% CI: 6.7, 15.6; P = .01) had stronger associations with HCC than enhancing capsule (OR, 2.4; 95% CI: 1.7, 3.5; P = .03). On CEUS images, APHE (OR, 7.3; 95% CI: 4.6, 11.5; P = .01), late and mild washout (OR, 4.1; 95% CI: 2.6, 6.6; P = .01), and size of at least 20 mm (OR, 1.6; 95% CI: 1.04, 2.5; P = .04) were associated with HCC. Twenty-five studies (78%) had high risk of bias due to reporting ambiguity or study desig

Published
2022

85. Additional file 1 of Effects of a support group leader education program jointly developed by health professionals and patients on peer leader self-efficacy among leaders of scleroderma support groups: a two-arm parallel partially nested randomised controlled trial

Author

Thombs, Brett D., Levis, Brooke, Carrier, Marie-Eve, Dyas, Laura, Nordlund, Julia, Tao, Lydia, Aguila, Kylene, Bourgeault, Angelica, Konrad, Violet, Sauvé, Maureen, Connolly, Kerri, Henry, Richard S., Østbø, Nora, Levis, Alexander W., Kwakkenbos, Linda, Malcarne, Vanessa L., El-Baalbaki, Ghassan, Hudson, Marie, Wurz, Amanda, Culos-Reed, S. Nicole, Platt, Robert W., and Benedetti, Andrea

Abstract

Additional file1. S1: Examples of support groups for people with systemic sclerosis.

Published
2022
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86. Additional file 3 of Effects of a support group leader education program jointly developed by health professionals and patients on peer leader self-efficacy among leaders of scleroderma support groups: a two-arm parallel partially nested randomised controlled trial

Author

Thombs, Brett D., Levis, Brooke, Carrier, Marie-Eve, Dyas, Laura, Nordlund, Julia, Tao, Lydia, Aguila, Kylene, Bourgeault, Angelica, Konrad, Violet, Sauvé, Maureen, Connolly, Kerri, Henry, Richard S., Østbø, Nora, Levis, Alexander W., Kwakkenbos, Linda, Malcarne, Vanessa L., El-Baalbaki, Ghassan, Hudson, Marie, Wurz, Amanda, Culos-Reed, S. Nicole, Platt, Robert W., and Benedetti, Andrea

Abstract

Additional file3. S3: Detailed trial outcome measures.

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2022
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87. Additional file 2 of Effects of a support group leader education program jointly developed by health professionals and patients on peer leader self-efficacy among leaders of scleroderma support groups: a two-arm parallel partially nested randomised controlled trial

Author

Thombs, Brett D., Levis, Brooke, Carrier, Marie-Eve, Dyas, Laura, Nordlund, Julia, Tao, Lydia, Aguila, Kylene, Bourgeault, Angelica, Konrad, Violet, Sauvé, Maureen, Connolly, Kerri, Henry, Richard S., Østbø, Nora, Levis, Alexander W., Kwakkenbos, Linda, Malcarne, Vanessa L., El-Baalbaki, Ghassan, Hudson, Marie, Wurz, Amanda, Culos-Reed, S. Nicole, Platt, Robert W., and Benedetti, Andrea

Abstract

Additional file2. S2: Links to SPIN-SSLED Participant Program Manual, Instructor Manual, and PowerPoint slides in English and French.

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2022
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88. Additional file 6 of Effects of a support group leader education program jointly developed by health professionals and patients on peer leader self-efficacy among leaders of scleroderma support groups: a two-arm parallel partially nested randomised controlled trial

Author

Thombs, Brett D., Levis, Brooke, Carrier, Marie-Eve, Dyas, Laura, Nordlund, Julia, Tao, Lydia, Aguila, Kylene, Bourgeault, Angelica, Konrad, Violet, Sauvé, Maureen, Connolly, Kerri, Henry, Richard S., Østbø, Nora, Levis, Alexander W., Kwakkenbos, Linda, Malcarne, Vanessa L., El-Baalbaki, Ghassan, Hudson, Marie, Wurz, Amanda, Culos-Reed, S. Nicole, Platt, Robert W., and Benedetti, Andrea

Abstract

Additional file6. S6: Client Satisfaction Questionnaire-8 item and total scores.

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2022
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89. Additional file 4 of Effects of a support group leader education program jointly developed by health professionals and patients on peer leader self-efficacy among leaders of scleroderma support groups: a two-arm parallel partially nested randomised controlled trial

Author

Thombs, Brett D., Levis, Brooke, Carrier, Marie-Eve, Dyas, Laura, Nordlund, Julia, Tao, Lydia, Aguila, Kylene, Bourgeault, Angelica, Konrad, Violet, Sauvé, Maureen, Connolly, Kerri, Henry, Richard S., Østbø, Nora, Levis, Alexander W., Kwakkenbos, Linda, Malcarne, Vanessa L., El-Baalbaki, Ghassan, Hudson, Marie, Wurz, Amanda, Culos-Reed, S. Nicole, Platt, Robert W., and Benedetti, Andrea

Abstract

Additional file4. S4: Statistical analysis plan.

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2022
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91. Comparison of mental health symptoms before and during the covid-19 pandemic: evidence from a systematic review and meta-analysis of 134 cohorts.

Author

Ying Sun, Yin Wu, Suiqiong Fan, Dal Santo, Tiffany, Letong Li, Xiaowen Jiang, Kexin Li, Yutong Wang, Tasleem, Amina, Krishnan, Ankur, Chen He, Bonardi, Olivia, Boruff, Jill T., Rice, Danielle B., Markham, Sarah, Levis, Brooke, Azar, Marleine, Thombs-Vite, Ian, Neupane, Dipika, and Agic, Branka

Subjects
COVID-19, PSYCHOLOGY information storage & retrieval systems, CINAHL database, META-analysis, MEDICAL information storage & retrieval systems, SYSTEMATIC reviews, SEX distribution, MENTAL depression, RESEARCH funding, MEDLINE, ANXIETY, COVID-19 pandemic, MENTAL illness
Published
2023
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92. 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.

Author

Nassar, Elsa‐Lynn, Levis, Brooke, Neyer, Marieke A., Rice, Danielle B., Booij, Linda, Benedetti, Andrea, and Thombs, Brett D.

Subjects
*MEDICAL screening, *MENTAL depression, *DATA management, *STANDARD deviations, *SAMPLE size (Statistics)
Abstract

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. [ABSTRACT FROM AUTHOR]

Published
2023
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93. Comparison of the Accuracy of the 7-Item HADS Depression Subscale and 14-Item Total HADS for Screening for Major Depression: A Systematic Review and Individual Participant Data Meta-Analysis.

Author

Wu, Yin, Levis, Brooke, Daray, Federico M., Ioannidis, John P. A., Patten, Scott B., Cuijpers, Pim, Ziegelstein, Roy C., Gilbody, Simon, Fischer, Felix H., Fan, Suiqiong, Sun, Ying, He, Chen, Krishnan, Ankur, Neupane, Dipika, Bhandari, Parash Mani, Negeri, Zelalem, Riehm, Kira E., Rice, Danielle B., Azar, Marleine, and Yan, Xin Wei

Subjects
*DIAGNOSIS of mental depression, *META-analysis, *CONFIDENCE intervals, *SYSTEMATIC reviews, *MEDICAL screening, *PSYCHOLOGICAL tests, *RESEARCH funding, *DESCRIPTIVE statistics, *PREDICTIVE validity, *SENSITIVITY & specificity (Statistics)
Abstract

The seven-item Hospital Anxiety and Depression Scale Depression subscale (HADS-D) and the total score of the 14-item HADS (HADS-T) are both used for major depression screening. Compared to the HADS-D, the HADS-T includes anxiety items and requires more time to complete. We compared the screening accuracy of the HADS-D and HADS-T for major depression detection. We conducted an individual participant data meta-analysis and fit bivariate random effects models to assess diagnostic accuracy among participants with both HADS-D and HADS-T scores. We identified optimal cutoffs, estimated sensitivity and specificity with 95% confidence intervals, and compared screening accuracy across paired cutoffs via two-stage and individual-level models. We used a 0.05 equivalence margin to assess equivalency in sensitivity and specificity. 20,700 participants (2,285 major depression cases) from 98 studies were included. Cutoffs of ≥7 for the HADS-D (sensitivity 0.79 [0.75, 0.83], specificity 0.78 [0.75, 0.80]) and ≥15 for the HADS-T (sensitivity 0.79 [0.76, 0.82], specificity 0.81 [0.78, 0.83]) minimized the distance to the top-left corner of the receiver operating characteristic curve. Across all sets of paired cutoffs evaluated, differences of sensitivity between HADS-T and HADS-D ranged from −0.05 to 0.01 (0.00 at paired optimal cutoffs), and differences of specificity were within 0.03 for all cutoffs (0.02–0.03). The pattern was similar among outpatients, although the HADS-T was slightly (not nonequivalently) more specific among inpatients. The accuracy of HADS-T was equivalent to the HADS-D for detecting major depression. In most settings, the shorter HADS-D would be preferred. Public Significance Statement: The present study suggests that the accuracy of 14-item Hospital Anxiety and Depression Scale (HADS-D) and the seven-item HADS Depression subscale (HADS-D) are equivalent for detecting major depression. Using the seven-item HADS-D for depression screening instead of the full 14-item HADS-T has minimal influence on performance of the measure but would reduce patient and participant burden in most clinical and research settings. [ABSTRACT FROM AUTHOR]

Published
2023
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96. CT/MRI and CEUS LI-RADS Major Features Association with Hepatocellular Carcinoma: Individual Patient Data Meta-Analysis

Author

van der Pol, Christian B., primary, McInnes, Matthew D. F., additional, Salameh, Jean-Paul, additional, Levis, Brooke, additional, Chernyak, Victoria, additional, Sirlin, Claude B., additional, Bashir, Mustafa R., additional, Allen, Brian C., additional, Burke, Lauren M. B., additional, Choi, Jin-Young, additional, Choi, Sang Hyun, additional, Forner, Alejandro, additional, Fraum, Tyler J., additional, Giamperoli, Alice, additional, Jiang, Hanyu, additional, Joo, Ijin, additional, Kang, Zhen, additional, Kierans, Andrea S., additional, Kang, Hyo-Jin, additional, Khatri, Gaurav, additional, Kim, Jung Hoon, additional, Kim, Myeong-Jin, additional, Kim, So Yeon, additional, Kim, Yeun-Yoon, additional, Kwon, Heejin, additional, Lee, Jeong Min, additional, Lewis, Sara C., additional, McGinty, Katrina A., additional, Mulazzani, Lorenzo, additional, Park, Mi-Suk, additional, Piscaglia, Fabio, additional, Podgórska, Joanna, additional, Reiner, Caecilia S., additional, Ronot, Maxime, additional, Rosiak, Grzegorz, additional, Song, Bin, additional, Song, Ji Soo, additional, Tang, An, additional, Terzi, Eleonora, additional, Wang, Jin, additional, Wang, Wei, additional, Wilson, Stephanie R., additional, and Yokoo, Takeshi, additional

Published
2022
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97. Accuracy of the Patient Health Questionnaire-9 for screening to detect major depression: updated systematic review and individual participant data meta-analysis

Author

Negeri, Zelalem F, Levis, Brooke, Sun, Ying, He, Chen, Krishnan, Ankur, Wu, Yin, Bhandari, Parash Mani, Neupane, Dipika, Brehaut, Eliana, Benedetti, Andrea, Thombs, Brett D, Imran, Mahrukh, Rice, Danielle B, Riehm, Kira E, Azar, Marleine, Levis, Alexander W, Boruff, Jill T, Cuijpers, Pim, Gilbody, Simon, Ioannidis, John P A, Kloda, Lorie A, Patten, Scott B, Shrier, Ian, Ziegelstein, Roy C, Markham, Sarah, Alamri, Sultan H, Amtmann, Dagmar, Arroll, Bruce, Ayalon, Liat, Baradaran, Hamid R, Beraldi, Anna, Bernstein, Charles N, Bhana, Arvin, Bombardier, Charles H, Buji, Ryna Imma, Butterworth, Peter, Carter, Gregory, Chagas, Marcos H, Chan, Juliana C N, Chan, Lai Fong, Chibanda, Dixon, Clover, Kerrie, Conway, Aaron, Conwell, Yeates, Daray, Federico M, de Man-van Ginkel, Janneke M, Delgadillo, Jaime, Diez-Quevedo, Crisanto, Fann, Jesse R, Fischer, Felix H, Field, Sally, Fisher, Jane R W, Fung, Daniel, Garman, Emily C, Gelaye, Bizu, Gholizadeh, Leila, Gibson, Lorna J, Goodyear-Smith, Felicity, Green, Eric P, Greeno, Catherine G, Hall, Brian J, Hantsoo, Liisa, Haroz, Emily E, Härter, Martin, Hegerl, Ulrich, Hides, Leanne, Hobfoll, Stevan E, Honikman, Simone, Hudson, Marie, Hyphantis, Thomas, Inagaki, Masatoshi, Jeon, Hong Jin, Jetté, Nathalie, Khamseh, Mohammad E, Kӧhler, Sebastian, Kohrt, Brandon A, Kwan, Yunxin, Lamers, Femke, Lara, Maria Asunción, Levin-Aspenson, Holly F, Liu, Shen-Ing, Lotrakul, Manote, Loureiro, Sonia R, Löwe, Bernd, Luitel, Nagendra P, Lund, Crick, Marrie, Ruth Ann, Marsh, Laura, Marx, Brian P, McGuire, Anthony, Mohd Sidik, Sherina, Munhoz, Tiago N, Muramatsu, Kumiko, Nakku, Juliet E M, Navarrete, Laura, Osório, Flávia L, Pence, Brian W, Persoons, Philippe, Petersen, Inge, Picardi, Angelo, Pugh, Stephanie L, Quinn, Terence J, Rancans, Elmars, Rathod, Sujit D, Reuter, Katrin, Rooney, Alasdair G, Rowe, Heather J, Santos, Iná S, Schram, Miranda T, Shaaban, Juwita, Shinn, Eileen H, Sidebottom, Abbey, Simning, Adam, Spangenberg, Lena, Stafford, Lesley, Sung, Sharon C, Suzuki, Keiko, Tan, Pei Lin Lynnette, Taylor-Rowan, Martin, Tran, Thach D, Turner, Alyna, van der Feltz-Cornelis, Christina M, van Heyningen, Thandi, van Weert, Henk C, Vöhringer, Paul A, Wagner, Lynne I, Wang, Jian Li, Wang, Wenzheng, Watson, David, White, Jennifer, Whooley, Mary A, Winkley, Kirsty, Wynter, Karen, Yamada, Mitsuhiko, Zeng, Qing Zhi, and Zhang, Yuying

Subjects
Adult, Male, medicine.medical_specialty, MEDLINE, PsycINFO, Patient Health Questionnaire, Sex Factors, Medicine, Humans, Mini-international neuropsychiatric interview, Psychiatric Status Rating Scales, Depressive Disorder, Major, business.industry, Research, Age Factors, General Medicine, Middle Aged, Reference Standards, Random effects model, Confidence interval, ROC Curve, Meta-analysis, Family medicine, Structured interview, Female, business
Abstract

ObjectiveTo 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.DesignSystematic review and individual participant data meta-analysis.Data sourcesMedline, Medline In-Process, and Other Non-Indexed Citations via Ovid, PsycINFO, Web of Science searched through 9 May 2018.Review methodsEligible 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.ResultsData 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.ConclusionsResearchers 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 atwww.depressionscreening100.com/phq.Study registrationPROSPERO CRD42014010673.

Published
2021

98. Pain levels and associated factors in the Scleroderma Patient-centered Intervention Network (SPIN) cohort: a multicentre cross-sectional study

Author

Lee, Yvonne C, primary, Fox, Rina S, additional, Kwakkenbos, Linda, additional, Levis, Brooke, additional, Carrier, Marie-Eve, additional, Welling, Joep, additional, Sauvé, Maureen, additional, Mouthon, Luc, additional, Benedetti, Andrea, additional, Bartlett, Susan J, additional, Varga, John, additional, Thombs, Brett D, additional, Henry, Richard S., additional, Gottesman, Karen, additional, Hudson, Marie, additional, Hummers, Laura K., additional, Malcarne, Vanessa L., additional, Mayes, Maureen D., additional, Nielson, Warren R., additional, Riggs, Robert, additional, Assassi, Shervin, additional, El-Baalbaki, Ghassan, additional, Ells, Carolyn, additional, Fligelstone, Kim, additional, Fortuné, Catherine, additional, Frech, Tracy, additional, Gietzen, Amy, additional, Guillot, Geneviève, additional, Harel, Daphna, additional, Hinchcliff, Monique, additional, Johnson, Sindhu R., additional, Larche, Maggie, additional, Leite, Catarina, additional, Nguyen, Christelle, additional, Nielsen, Karen, additional, Pope, Janet, additional, Rannou, François, additional, Richard, Michelle, additional, Rodriguez-Reyna, Tatiana Sofia, additional, Schouffoer, Anne A., additional, Suarez-Almazor, Maria E., additional, Agard, Christian, additional, Ait Abdallah, Nassim, additional, Albert, Alexandra, additional, André, Marc, additional, Bernstein, Elana J., additional, Berthier, Sabine, additional, Bissonnette, Lyne, additional, Bruns, Alessandra, additional, Carreira, Patricia, additional, Casadevall, Marion, additional, Chaigne, Benjamin, additional, Chung, Lorinda, additional, Correia, Chase, additional, Crichi, Benjamin, additional, Denton, Christopher, additional, Domsic, Robyn, additional, Dunne, James V., additional, Dunogue, Bertrand, additional, Fare, Regina, additional, Farge-Bancel, Dominique, additional, Fortin, Paul R., additional, Gordon, Jessica, additional, Granel-Rey, Brigitte, additional, Gyger, Genevieve, additional, Hachulla, Eric, additional, Herrick, Ariane L, additional, Hoa, Sabrina, additional, Ikic, Alena, additional, Jones, Niall, additional, Kafaja, Suzanne, additional, Khalidi, Nader, additional, Lambert, Marc, additional, Launay, David, additional, Maillard, Hélène, additional, Maltez, Nancy, additional, Manning, Joanne, additional, Marie, Isabelle, additional, Martin, Maria, additional, Martin, Thierry, additional, Masetto, Ariel, additional, Maurier, François, additional, Mekinian, Arsene, additional, Melchor, Sheila, additional, Nikpour, Mandana, additional, Olagne, Louis, additional, Poindron, Vincent, additional, Proudman, Susanna, additional, Régent, Alexis, additional, Rivière, Sébastien, additional, Robinson, David, additional, Rodriguez, Esther, additional, Roux, Sophie, additional, Smets, Perrine, additional, Sobanski, Vincent, additional, Spiera, Robert, additional, Steen, Virginia, additional, Sutton, Evelyn, additional, Thorne, Carter, additional, Wilcox, Pearce, additional, Bourgeault, Angelica, additional, Cañedo Ayala, Mara, additional, Carboni Jiménez, Andrea, additional, Discepola, Marie-Nicole, additional, Gagarine, Maria, additional, Nordlund, Julia, additional, and Østbø, Nora, additional

Published
2021
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100. Comparison of different scoring methods based on latent variable models of the PHQ-9: an individual participant data meta-analysis.

Author

Fischer, Felix, Levis, Brooke, Falk, Carl, Sun, Ying, Ioannidis, John P. A., Cuijpers, Pim, Shrier, Ian, Benedetti, Andrea, Thombs, Brett D., the Depression Screening Data (DEPRESSD) PHQ Collaboration, He, Chen, Krishnan, Ankur, Wu, Yin, Negeri, Zelalem, Bhandari, Parash Mani, Neupane, Dipika, Rice, Danielle B., Riehm, Kira E., Saadat, Nazanin, and Azar, Marleine

Subjects
*MEDICAL screening, *MENTAL depression, *QUESTIONNAIRES, *DESCRIPTIVE statistics, *STATISTICAL models, *DATA analysis software, *SECONDARY analysis
Abstract

Background: Previous research on the depression scale of the Patient Health Questionnaire (PHQ-9) has found that different latent factor models have maximized empirical measures of goodness-of-fit. The clinical relevance of these differences is unclear. We aimed to investigate whether depression screening accuracy may be improved by employing latent factor model-based scoring rather than sum scores. Methods: We used an individual participant data meta-analysis (IPDMA) database compiled to assess the screening accuracy of the PHQ-9. We included studies that used the Structured Clinical Interview for DSM (SCID) as a reference standard and split those into calibration and validation datasets. In the calibration dataset, we estimated unidimensional, two-dimensional (separating cognitive/affective and somatic symptoms of depression), and bi-factor models, and the respective cut-offs to maximize combined sensitivity and specificity. In the validation dataset, we assessed the differences in (combined) sensitivity and specificity between the latent variable approaches and the optimal sum score (⩾10), using bootstrapping to estimate 95% confidence intervals for the differences. Results: The calibration dataset included 24 studies (4378 participants, 652 major depression cases); the validation dataset 17 studies (4252 participants, 568 cases). In the validation dataset, optimal cut-offs of the unidimensional, two-dimensional, and bi-factor models had higher sensitivity (by 0.036, 0.050, 0.049 points, respectively) but lower specificity (0.017, 0.026, 0.019, respectively) compared to the sum score cut-off of ⩾10. Conclusions: In a comprehensive dataset of diagnostic studies, scoring using complex latent variable models do not improve screening accuracy of the PHQ-9 meaningfully as compared to the simple sum score approach. [ABSTRACT FROM AUTHOR]

Published
2022
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