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Completed Systematic Reviews




Phenotypes and body mass in women with PCOS identified in Referral vs. Unselected populations: systematic review and meta-analysis


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Statistics: 43 Studies, 2 Key Questions, 1 Extraction Form,
Date Published: Aug 01, 2019 12:55PM
Description: Objective: To compare the prevalence of PCOS phenotypes and obesity of PCOS women seen in the clinical (referred) setting vs. those identified in general population.
Contributor(s): Daria Lizneva, Richard Kirubakaran, Katerina Mykhalchenko, Larisa Suturina, Chernukha Galina, Michael P. Diamond, Ricardo Azziz.
Funding Source: Funds from the Career Development Award (MD Medical Group) were used to support D.L. throughout the manuscript preparation. No other funding recourses were identified.
Methodology Description: Objective: To compare the prevalence of polycystic ovary syndrome (PCOS) phenotypes and obesity among patients detected in referral versus unselected populations. Design: Systematic review and meta-analysis. Setting: Not applicable. Patient(s): Thirteen thousand seven hundred ninety-six reproductive-age patients with PCOS, as defined by the extended 2003 Rotterdam criteria. Intervention(s): Review of PUBMED, EMBASE, and Cochrane Library, 2003–2016. Only observational studies were included. Data were extracted using a web-based, piloted form and combined for meta-analysis. Main Outcome Measure(s): PCOS phenotypes were classified as follows: phenotype A, clinical and/or biochemical hyperandrogenism (HA) + oligo-/anovulation (OA) + polycystic ovarian morphology (PCOM); phenotype B, HA+OA; phenotype C, HA+PCOM; and phenotype D, OA+PCOM. Result(s): Forty-one eligible studies, reporting on 43 populations, were identified. Pooled estimates of detected PCOS phenotype prevalence were consequently documented in referral versus unselected populations, as [1] phenotype A, 50% (95% confidence interval [CI], 46%–54%) versus 19% (95% CI, 13%–27%); [2] phenotype B, 13% (95% CI, 11%–17%) versus 25% (95% CI, 15%–37%); [3] phenotype C, 14% (95% CI, 12%–16%) versus 34% (95% CI, 25–46%); and [4] phenotype D, 17% (95% CI, 13%–22%) versus 19% (95% CI, 14%– 25%). Differences between referral and unselected populations were statistically significant for phenotypes A, B, and C. Referral PCOS subjects had a greater mean body mass index (BMI) than local controls, a difference that was not apparent in unselected PCOS. Conclusion(s): The prevalence of more complete phenotypes in PCOS and mean BMI were higher in subjects identified in referral versus unselected populations, suggesting the presence of significant referral bias.

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Decision Aids for Cancer Screening and Treatment


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Statistics: 75 Studies, 2 Key Questions, 2 Extraction Forms,
Date Published: May 23, 2019 03:00PM
Description: Background: Many health decisions about screening and treatment for cancers involve uncertainty or tradeoffs between the expected benefits and harms. Patient decision aids have been developed to help health care consumers and their providers identify the available alternatives and choose the one that aligns with their values. It is unclear whether the effectiveness of decision aids for decisions related to cancers differs by people’s average risk of cancer or by the content and format of the decision aid.; Objectives: We sought to appraise and synthesize the evidence assessing the effectiveness of decision aids targeting health care consumers who face decisions about cancer screening or prevention, or early cancer treatment (Key Question 1), particularly with regard to decision aid or patient characteristics that might function as effect modifiers. We also reviewed interventions targeting providers for promotion of shared decision making using decision aids (Key Question 2).; Data sources: We searched MEDLINE®, Embase®, the Cochrane Central Register of Controlled Trials (CENTRAL), PsycINFO®, and the Cumulative Index to Nursing and Allied Health Literature (CINAHL®) from inception to the end of June 2014.; Review methods: For Key Question 1, we included randomized controlled trials comparing decision aid interventions among themselves or with a control. We included trials of previously developed decision aids that were delivered at the point of the actual decision. We predefined three population groups of interest based on risk or presence of cancer (average cancer risk, high cancer risk, early cancer). The assessed outcomes pertained to measurements of decisional quality and cognition (e.g., knowledge scores), attributes of the decision-making process (e.g., Decisional Conflict Scale), emotion and quality of life (e.g., decisional regret), and process and system-level attributes. We assessed for effect modification by population group, by the delivery format or content of the decision aid or other attributes, or by methodological characteristics of the studies. For Key Question 2, we included studies of any intervention to promote patient decision aid use, regardless of study design and outcomes assessed.; Results: Of the 16,669 screened citations, 87 publications were eligible, corresponding to 83 (68 trials; 25,337 participants) and 5 reports for Key Questions 1 and 2, respectively. Regarding the evolution of the decision aid format and content over time, more recent trials increasingly studied decision aids that were more practical to deliver (e.g., over the Internet or without human mediation) and more often clarified preferences explicitly. Overall, participants using decision aids had higher knowledge scores compared with those not using decision aids (standardized mean difference, 0.23; 95% credible interval [CrI], 0.09 to 0.35; 42 comparison strata with 12,484 participants). Compared with not using decision aids, using decision aids resulted in slightly lower decisional conflict scores (weighted mean difference of -5.3 units [CrI, -8.9 to - 1.8] on the 0-100 Decisional Conflict Scale; 28 comparison strata; 7,923 participants). There was no difference in State-Trait Anxiety Inventory scores (weighted mean difference = 0.1; 95% CrI, -1.0 to 0.7 on a 20-80 scale; 16 comparison strata; 2,958 participants). Qualitative synthesis suggested that patients using decision aids are more likely to make informed decisions and have accurate risk perceptions; further, they may make choices that best agree with their values and may be less likely to remain undecided. Because there was insufficient, sparse, or no information about effects of decision aids on patient-provider communication, patient satisfaction with decision-making process, resource use, consultation length, costs, or litigation rates, a quantitative synthesis was not done. There was no evidence for effect modification by population group, by the delivery format or content of the decision aid or other attributes, or by methodological characteristics of the studies. Data on Key Question 2 were very limited.; Conclusions: Cancer-related decision aids have evolved over time, and there is considerable diversity in both format and available evidence. We found strong evidence that cancer-related decision aids increase knowledge without adverse impact on decisional conflict or anxiety. We found moderate- or low-strength evidence that patients using decision aids are more likely to make informed decisions, have accurate risk perceptions, make choices that best agree with their values, and not remain undecided. This review adds to the literature that the effectiveness of cancer-related decision aids does not appear to be modified by specific attributes of decision aid delivery format, content, or other characteristics of their development and implementation. Very limited information was available on other outcomes or on the effectiveness of interventions that target providers to promote shared decision making by means of decision aids.
Contributor(s): Gaelen Adam Thomas Trikalinos L. Susan Wieland Anja Zgodic Evangelia Ntzani
Funding Source: AHRQ
Methodology Description: Eligible Studies for Key Question 1: We included randomized controlled trials comparing use of patient decision aids with other patient decision aids or with no decision aid intervention. We included trials of mature patient decision aids delivered at the point of the actual decision. We excluded trials about hypothetical treatment decisions. For example, we excluded hypothetical questions about early cancer treatment in people not yet diagnosed with cancer, or trials about cancer screening among people who would not be typical screening candidates. We predefined three populations of interest, based on risk or presence of cancer. The first population included people without cancer who are at average risk and face decisions about cancer screening (whether or how to be screened). The second population included people without cancer but with high risk of cancer, e.g., because they are suspected or known to have a hereditary cancer-related condition, such as the Lynch or von Hippel-Lindau syndromes, or are carriers of deleterious BRCA gene mutations. This group may face decisions about further diagnostic workup or about undergoing preventive interventions. The third population included patients diagnosed with early cancer, defined as being at a stage with favorable prognosis (typically local disease only) and where interventions have curative intent (e.g., stage IIa or lower for prostate cancer). We accepted the individual study claims for the definition of early cancer. When a study used an alternative cancer staging, we adjudicated an early cancer stage using information for the National Cancer Institute site. We included only studies in people who were legally able to make decisions for themselves or an underage minor. We followed the IPDAS collaboration and previous systematic reviews in defining decision aid-based interventions as, at a minimum, (1) informing about available options and the expected associated benefits and harms, and (2) incorporating at least implicit clarification of the decisionmaker’s values.3,4 ; Eligible Studies for Key Question 2: For the second Key Question, we included comparative studies informing on the effectiveness of interventions for promoting shared decision making to providers caring for the populations discussed for the first Key Question, specifically provider-targeted interventions to increase shared decision making with the use or increased use of a decision aid. Because so few studies have been done on this topic, eligible designs included randomized and cluster- randomized trials, nonrandomized studies with concurrent comparators, before-after studies, and interrupted time series studies.

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Early Intensive Intervention for Children with Autism Spectrum Disorder: A Systematic Review Update


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Statistics: 80 Studies, 1 Key Question, 1 Extraction Form,
Date Published: Mar 25, 2019 05:51AM
Description: The objective of this study was to systematically review studies of early intensive behavioral and developmental approaches that may improve outcomes for children with ASD.
Contributor(s): Amy S. Weitlauf, Ph.D. Melissa L. McPheeters, Ph.D., M.P.H. Brittany Peters, M.D. Nila Sathe, M.A., M.L.I.S. Rebekah Travis, Psy.D. Rachel Aiello, Ph.D. Edwin Williamson, M.D. Jeremy Veenstra-VanderWeele, M.D. Shanthi Krishnaswami, M.B.B.S., M.P.H. Rebecca Jerome, M.L.I.S., M.P.H. Zachary Warren, Ph.D.
Funding Source: This project was supported by the Agency for Healthcare Research and Quality (contract number: HHSA290201200009I)
Methodology Description: Our primary literature search employed three databases: MEDLINE® via the PubMed interface, PsycINFO® (psychology and psychiatry literature), and the Educational Resources Information Clearinghouse. Our search strategies used a combination of subject heading terms appropriate for each database and key words relevant to ASD (e.g., autism, Asperger). We limited searches to the English language and literature published since the development of the 2011 AHRQ review on management of ASD. Two reviewers independently assessed studies against predetermined inclusion/exclusion criteria. Two reviewers independently extracted data regarding participant and intervention characteristics, assessment techniques, and outcomes and assigned quality and strength of evidence ratings using predetermined methods.

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The shortcomings of cluster-randomized controlled trials for the assessment of complex interventions in general practices: a systematic review


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Statistics: 29 Studies, 1 Key Question, 1 Extraction Form,
Date Published: Mar 25, 2019 05:50AM
Description: None Provided
Contributor(s): Professor Andrea Siebenhofer-Kroitzsch, Institute of General Practice, Goethe Univ. Frankfurt, Germany Dr Christiane Muth, Institute of General Practice, Goethe Univ. Frankfurt, Germany Dr Birgit Fullerton, Institute of General Practice, Goethe Univ. Frankfurt, Germany Professor Paul Glasziou, Centre for Research in Evidence-Based Practice, Bond University, Australia Professor Elaine Beller, Centre for Research in Evidence-Based Practice, Bond University, Australia Mrs Sarah Thorning, Centre for Research in Evidence-Based Practice, Bond University, Australia Professor Andrea Berghold, Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Austria Dr Klaus Jeitler, Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Austria Ms Gudrun Pregartner, Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Austria Ms Jennifer Engler, Institute of General Practice, Goethe Univ. Frankfurt, Germany Dr Gudrun Klein, Institute of General Practice, Goethe Univ. Frankfurt, Germany Mr Michael Paulitsch, Institute of General Practice, Goethe Univ. Frankfurt, Germany
Funding Source: This review will be funded by German Federal Ministry of Education and Research (FKZ: 01KG1504); approval date: 05/2015
Methodology Description: None Provided

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Psychological and Pharmacological Treatments for Adults With Posttraumatic Stress Disorder (PTSD): A Systematic Review Update


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Statistics: 0 Studies, 4 Key Questions, 1 Extraction Form,
Date Published: Mar 21, 2019 09:12AM
Description: This systematic review is an update of a 2013 report that evaluated psychological and pharmacological treatments of adults with posttraumatic stress disorder (PTSD). The purpose of this review is to update the earlier work, expand the range of treatments examined, address earlier uncertainties, identify ways to improve care for PTSD patients, and reduce variation in existing treatment guidelines.
Contributor(s): Valerie Hoffman, Ph.D., M.P.H.; Jennifer Cook Middleton, Ph.D.; Cynthia Feltner, M.D., M.P.H.; Bradley N. Gaynes, M.D., M.P.H.; Rachel Palmieri Weber, Ph.D.; Carla Bann, Ph.D.; Meera Viswanathan, Ph.D.; Kathleen N. Lohr, Ph.D., M.Phil., M.A.; Claire Baker; Joshua Green, B.A.
Funding Source: This report is based on research conducted by the RTI-UNC Evidence-based Practice Center (EPC) under contract to the Agency for Healthcare Research and Quality (AHRQ), and funded by the Patient-Centered Outcomes Research Institute (PCORI).
Methodology Description: We systematically searched, reviewed, and analyzed the scientific evidence gathered to help answer our KQs. We began with a focused MEDLINE® search for eligible interventions using a combination of medical subject headings (MeSH®) and title and abstract keywords, limiting the search to human-only studies (from inception through September 29, 2017). We also searched the Cochrane Library, the Cochrane Clinical Trials Registry, PsycINFO, the Cumulative Index to Nursing and Allied Health Literature, and the Published International Literature on Traumatic Stress database using analogous search terms. These searches included randomized controlled trials (RCTs), controlled clinical trials, and systematic reviews. All titles and abstracts identified via searches were duly reviewed by trained research team members, and the full texts of those included articles were then retrieved and reviewed, and a final determination about inclusion was made. Data from included articles was abstracted, and information included in the report and appendices (see supplemental data files).

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