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The Many Flavors of Model-Based Meta-Analysis: Part I-Introduction and Landmark Data.

ABSTRACT: Meta-analysis is an increasingly important aspect of drug development as companies look to benchmark their own compounds with the competition. There is scope to carry out a wide range of analyses addressing key research questions from preclinical through to postregistration. This set of tutorials will take the reader through key model-based meta-analysis (MBMA) methods with this first installment providing a general introduction before concentrating on classical and Bayesian methods for landmark data.

SUBMITTER: Boucher M

PROVIDER: S-EPMC4761229 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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The Many Flavors of Model-Based Meta-Analysis: Part I-Introduction and Landmark Data.

Boucher M M Bennetts M M

CPT: pharmacometrics & systems pharmacology 20160213 2

Meta-analysis is an increasingly important aspect of drug development as companies look to benchmark their own compounds with the competition. There is scope to carry out a wide range of analyses addressing key research questions from preclinical through to postregistration. This set of tutorials will take the reader through key model-based meta-analysis (MBMA) methods with this first installment providing a general introduction before concentrating on classical and Bayesian methods for landmark ...[more]

PMID: 26933516

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Project description:ObjectivesDeep learning (DL) has been increasingly employed for automated landmark detection, e.g., for cephalometric purposes. We performed a systematic review and meta-analysis to assess the accuracy and underlying evidence for DL for cephalometric landmark detection on 2-D and 3-D radiographs.MethodsDiagnostic accuracy studies published in 2015-2020 in Medline/Embase/IEEE/arXiv and employing DL for cephalometric landmark detection were identified and extracted by two independent reviewers. Random-effects meta-analysis, subgroup, and meta-regression were performed, and study quality was assessed using QUADAS-2. The review was registered (PROSPERO no. 227498).DataFrom 321 identified records, 19 studies (published 2017-2020), all employing convolutional neural networks, mainly on 2-D lateral radiographs (n=15), using data from publicly available datasets (n=12) and testing the detection of a mean of 30 (SD: 25; range.: 7-93) landmarks, were included. The reference test was established by two experts (n=11), 1 expert (n=4), 3 experts (n=3), and a set of annotators (n=1). Risk of bias was high, and applicability concerns were detected for most studies, mainly regarding the data selection and reference test conduct. Landmark prediction error centered around a 2-mm error threshold (mean; 95% confidence interval: (-0.581; 95 CI: -1.264 to 0.102 mm)). The proportion of landmarks detected within this 2-mm threshold was 0.799 (0.770 to 0.824).ConclusionsDL shows relatively high accuracy for detecting landmarks on cephalometric imagery. The overall body of evidence is consistent but suffers from high risk of bias. Demonstrating robustness and generalizability of DL for landmark detection is needed.Clinical significanceExisting DL models show consistent and largely high accuracy for automated detection of cephalometric landmarks. The majority of studies so far focused on 2-D imagery; data on 3-D imagery are sparse, but promising. Future studies should focus on demonstrating generalizability, robustness, and clinical usefulness of DL for this objective.

Project description:BackgroundApproaches to support the health and well-being of family caregivers of adults with chronic conditions are increasingly important given the key roles caregivers play in helping family members to live in the community. Web-based interventions to support caregivers have the potential to lessen the negative health impacts associated with caregiving and result in improved health outcomes.ObjectiveThe primary objective of this systematic review and meta-analysis was to examine the effect of caregiver-focused, Web-based interventions, compared with no or minimal Web-based interventions, on caregiver outcomes. The secondary objective was to assess the effect of different types of Web-based interventions (eg, education, peer and professional psychosocial support, and electronic monitoring of the care recipient), compared with no or minimal Web-based interventions, on caregiver outcomes.MethodsMEDLINE, EMBASE, CIHAHL, PsychInfo, Cochrane, and AgeLine were searched from January 1995 to April 2017 for relevant randomized controlled trials (RCTs) or controlled clinical trials (CCTs) that compared caregiver-focused, Web-based intervention programs with no or minimal Web-based interventions for caregivers of adults with at least one chronic condition. Studies were included if they involved: adult family or friend caregivers (aged ≥18 years) of adults living in the community with a chronic condition; a caregiver-focused, Web-based intervention of education or psychosocial support or electronic monitoring of the care recipient; and general caregiver outcomes (ie, burden, life satisfaction, self-efficacy or mastery, reaction to problem behavior, self-esteem, strain, and social support). Title and abstract as well as full-text screening were completed in duplicate. Data were extracted by a single reviewer and verified by a second reviewer, and risk of bias assessments were completed accordingly. Where possible, data for these caregiver outcomes were meta-analyzed.ResultsThe search yielded 7927 unique citations, of which 294 studies were screened at full text. Of those, 14 studies met the inclusion criteria; 12 were RCTs and 1 study was a CCT. One study used an RCT design in 1 country and a CCT design in 2 other countries. The beneficial effects of any Web-based intervention program, compared with no or minimal Web-based intervention, resulted in a mean increase of 0.85 points (95% CI 0.12 to 1.57) for caregiver self-esteem, a mean increase of 0.36 points (95% CI 0.11 to 0.62) for caregiver self-efficacy or mastery, and a mean decrease of 0.32 points (95% CI -0.54 to -0.09) for caregiver strain. However, the results are based on poor-quality studies.ConclusionsThe review found evidence for the positive effects of Web-based intervention programs on self-efficacy, self-esteem, and strain of caregivers of adults living with a chronic condition. Further high-quality research is needed to inform the effectiveness of specific types of Web-based interventions on caregiver outcomes.Trial registrationPROSPERO CRD42018091715; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=91715 (Archived by WebCite at http://www.webcitation.org/738zAa5F5).

Dataset Information

The Many Flavors of Model-Based Meta-Analysis: Part I-Introduction and Landmark Data.

Publications

The Many Flavors of Model-Based Meta-Analysis: Part I-Introduction and Landmark Data.

Similar Datasets

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