Framework for the synthesis of non-randomised studies and randomised controlled trials: a guidance on conducting a systematic review and meta-analysis for healthcare decision making
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Grammati Sarri | Elisabetta Patorno | Hongbo Yuan | Jianfei Jeff Guo | Dimitri Bennett | Xuerong Wen | Andrew R Zullo | Joan Largent | Mary Panaccio | Mugdha Gokhale | Daniela Claudia Moga | M Sanni Ali | Thomas P A Debray | D. Moga | T. Debray | J. Largent | M. Gokhale | M. S. Ali | E. Patorno | J. Guo | D. Bennett | Hongbo Yuan | A. Zullo | G. Sarri | M. Panaccio | X. Wen | Jianfei Guo | M Sanni Ali | Elisabetta Patorno | M. Ali
[1] Michele Tarsilla. Cochrane Handbook for Systematic Reviews of Interventions , 2010, Journal of MultiDisciplinary Evaluation.
[2] Richard D Riley,et al. Interpretation of random effects meta-analyses , 2011, BMJ : British Medical Journal.
[3] Cathal Walsh,et al. Incorporating data from various trial designs into a mixed treatment comparison model , 2013, Statistics in medicine.
[4] E. Nicod,et al. Developing an evidence-based methodological framework to systematically compare HTA coverage decisions: A mixed methods study. , 2016, Health policy.
[5] Julian P T Higgins,et al. Commentary: Heterogeneity in meta-analysis should be expected and appropriately quantified. , 2008, International journal of epidemiology.
[6] Olaf Klungel,et al. Reporting to Improve Reproducibility and Facilitate Validity Assessment for Healthcare Database Studies V1.0. , 2017, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.
[7] D. Altman,et al. Measuring inconsistency in meta-analyses , 2003, BMJ : British Medical Journal.
[8] Donald B Rubin,et al. Bridging observational studies and randomized experiments by embedding the former in the latter , 2017, Statistical methods in medical research.
[9] David J Spiegelhalter,et al. Bias modelling in evidence synthesis , 2009, Journal of the Royal Statistical Society. Series A,.
[10] S. Pocock,et al. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and Elaboration , 2007, PLoS medicine.
[11] Gerta Rücker,et al. Detecting and adjusting for small‐study effects in meta‐analysis , 2011, Biometrical journal. Biometrische Zeitschrift.
[12] David J. Spiegelhalter,et al. Multiple-bias modelling for analysis of observational data - Discussion , 2005 .
[13] L. Bero,et al. Healthcare outcomes assessed with observational study designs compared with those assessed in randomized trials. , 2014, The Cochrane database of systematic reviews.
[14] P. Tugwell,et al. Including non‐randomized studies on intervention effects , 2019, Cochrane Handbook for Systematic Reviews of Interventions.
[15] Kerrie Mengersen,et al. Adjusted Likelihoods for Synthesizing Empirical Evidence from Studies that Differ in Quality and Design: Effects of Environmental Tobacco Smoke , 2004 .
[16] E. Perfetto,et al. Patient-Community Perspectives on Real-World Evidence: Enhancing Engagement, Understanding, and Trust , 2019, The Patient - Patient-Centered Outcomes Research.
[17] P. Tugwell,et al. Non‐randomized studies as a source of complementary, sequential or replacement evidence for randomized controlled trials in systematic reviews on the effects of interventions , 2013, Research synthesis methods.
[18] B. Vandermeer,et al. Handling Continuous Outcomes in Quantitative Synthesis , 2013 .
[19] J. Krause,et al. Real-World Evidence in the Real World: Beyond the FDA , 2018, American Journal of Law & Medicine.
[20] Guidelines for good pharmacoepidemiology practice (GPP) , 2016, Pharmacoepidemiology and drug safety.
[21] K. Abrams,et al. The inclusion of real world evidence in clinical development planning , 2018, Trials.
[22] Cynthia P Iglesias,et al. A bias-adjusted evidence synthesis of RCT and observational data: the case of total hip replacement. , 2017, Health economics.
[23] S. Palmer,et al. The assessment and appraisal of regenerative medicines and cell therapy products: an exploration of methods for review, economic evaluation and appraisal. , 2017, Health technology assessment.
[24] Dimitris Mavridis,et al. Combining randomized and non‐randomized evidence in network meta‐analysis , 2017, Statistics in medicine.
[25] Alex J. Sutton,et al. Evidence Synthesis for Decision Making 2 , 2013, Medical decision making : an international journal of the Society for Medical Decision Making.
[26] Pablo Emilio Verde,et al. The hierarchical metaregression approach and learning from clinical evidence , 2019, Biometrical journal. Biometrische Zeitschrift.
[27] Alison Cave,et al. Real‐World Data for Regulatory Decision Making: Challenges and Possible Solutions for Europe , 2019, Clinical pharmacology and therapeutics.
[28] M. Epstein,et al. Guidelines for good pharmacoepidemiology practices (GPP) , 2008 .
[29] C Daniel Mullins,et al. A questionnaire to assess the relevance and credibility of observational studies to inform health care decision making: an ISPOR-AMCP-NPC Good Practice Task Force report. , 2014, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.
[30] Paul Landais,et al. Meta-regression detected associations between heterogeneous treatment effects and study-level, but not patient-level, factors. , 2004, Journal of clinical epidemiology.
[31] T. Stürmer,et al. Methodological considerations when analysing and interpreting real-world data. , 2020, Rheumatology.
[32] J. Higgins,et al. Cochrane Handbook for Systematic Reviews of Interventions , 2010, International Coaching Psychology Review.
[33] Pablo Emilio Verde,et al. Two Examples of Bayesian Evidence Synthesis with the Hierarchical Meta-Regression Approach , 2017 .
[34] Louise J Jackson,et al. Effects of antenatal diet and physical activity on maternal and fetal outcomes: individual patient data meta-analysis and health economic evaluation. , 2017, Health technology assessment.
[35] Malcolm Rowland,et al. Bridging the efficacy–effectiveness gap: a regulator's perspective on addressing variability of drug response , 2011, Nature Reviews Drug Discovery.
[36] J. Pearl,et al. Causal diagrams for epidemiologic research. , 1999, Epidemiology.
[37] S. Pauker,et al. The Discrepancy between Observational Studies and Randomized Trials of Menopausal Hormone Therapy: Did Expectations Shape Experience? , 2003, Annals of Internal Medicine.
[38] S. Burgess. Estimating and contextualizing the attenuation of odds ratios due to non collapsibility , 2017 .
[39] J. Guo,et al. Real‐World Evidence: What It Is and What It Can Tell Us According to the International Society for Pharmacoepidemiology (ISPE) Comparative Effectiveness Research (CER) Special Interest Group (SIG) , 2018, Clinical pharmacology and therapeutics.
[40] Alex J. Sutton,et al. Evidence Synthesis for Decision Making 7 , 2013, Medical decision making : an international journal of the Society for Medical Decision Making.
[41] M. Rovers,et al. The effects of clinical and statistical heterogeneity on the predictive values of results from meta-analyses. , 2014, Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases.
[42] Sander Greenland,et al. Multiple‐bias modelling for analysis of observational data , 2005 .
[43] Sofia Dias,et al. Threshold Analysis as an Alternative to GRADE for Assessing Confidence in Guideline Recommendations Based on Network Meta-analyses , 2019, Annals of Internal Medicine.
[44] Richard Grieve,et al. THE USE OF REAL WORLD DATA FOR THE ESTIMATION OF TREATMENT EFFECTS IN NICE DECISION MAKING , 2016 .
[45] M. Mcclellan,et al. Understanding the Need for Non-Interventional Studies Using Secondary Data to Generate Real-World Evidence for Regulatory Decision Making, and Demonstrating Their Credibility , 2019 .
[46] John P A Ioannidis,et al. Commentary: Adjusting for bias: a user's guide to performing plastic surgery on meta-analyses of observational studies. , 2011, International journal of epidemiology.
[47] T. Trikalinos,et al. Do observational studies using propensity score methods agree with randomized trials? A systematic comparison of studies on acute coronary syndromes. , 2012, European heart journal.
[48] Christian Ohmann,et al. Combining randomized and non‐randomized evidence in clinical research: a review of methods and applications , 2015, Research synthesis methods.
[49] Uwe Siebert,et al. Good research practices for comparative effectiveness research: approaches to mitigate bias and confounding in the design of nonrandomized studies of treatment effects using secondary data sources: the International Society for Pharmacoeconomics and Outcomes Research Good Research Practices for Retr , 2009, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.
[50] Michael L. Johnson,et al. Good research practices for comparative effectiveness research: analytic methods to improve causal inference from nonrandomized studies of treatment effects using secondary data sources: the ISPOR Good Research Practices for Retrospective Database Analysis Task Force Report--Part III. , 2009, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.
[51] S. Cummings,et al. Effect of bisphosphonate use on risk of postmenopausal breast cancer: results from the randomized clinical trials of alendronate and zoledronic acid. , 2014, JAMA internal medicine.
[52] P. Bauer,et al. The risks of methodology aversion in drug regulation , 2014, Nature Reviews Drug Discovery.
[53] J. Johnston,et al. Reweighting Randomized Controlled Trial Evidence to Better Reflect Real Life – A Case Study of the Innovative Medicines Initiative , 2020, Clinical pharmacology and therapeutics.
[54] M. Borenstein,et al. Publication Bias in Meta-Analysis: Prevention, Assessment and Adjustments , 2006 .
[56] M. Sydes,et al. Practical methods for incorporating summary time-to-event data into meta-analysis , 2007, Trials.
[57] Sally C Morton,et al. Standards and guidelines for observational studies: quality is in the eye of the beholder. , 2016, Journal of clinical epidemiology.
[58] Guideline on good pharmacovigilance practices ( GVP ) Module , 2013 .
[59] David J Spiegelhalter,et al. Bayesian approaches to multiple sources of evidence and uncertainty in complex cost‐effectiveness modelling , 2003, Statistics in medicine.
[60] D. Scott,et al. Critical appraisal of nonrandomized studies—A review of recommended and commonly used tools , 2019, Journal of evaluation in clinical practice.
[61] Wolfgang Viechtbauer,et al. Publication bias in meta-analysis: Prevention, assessment and adjustments , 2007, Psychometrika.
[62] J. Hanley,et al. Recovering the raw data behind a non-parametric survival curve , 2014, Systematic Reviews.
[63] Alex J. Sutton,et al. Heterogeneity: Subgroups, Meta-Regression, Bias And Bias-Adjustment , 2011 .
[64] R. Chlebowski,et al. Menopausal hormone therapy after breast cancer: a meta-analysis and critical appraisal of the evidence , 2005, Breast Cancer Research.
[65] Adrian Towse,et al. Real-world evidence for coverage decisions: opportunities and challenges. , 2018, Journal of comparative effectiveness research.
[66] J. Ioannidis. Why Most Published Research Findings Are False , 2019, CHANCE.
[67] Johannes B Reitsma,et al. An overview of methods for network meta-analysis using individual participant data: when do benefits arise? , 2018, Statistical methods in medical research.
[68] Anthonius de Boer,et al. Systematic differences in treatment effect estimates between propensity score methods and logistic regression. , 2008, International journal of epidemiology.
[69] P. Austin. An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies , 2011, Multivariate behavioral research.
[70] D. Moher,et al. Establishing a Minimum Dataset for Prospective Registration of Systematic Reviews: An International Consultation , 2011, PloS one.
[71] Nikolaos A Patsopoulos,et al. Uncertainty in heterogeneity estimates in meta-analyses , 2007, BMJ : British Medical Journal.
[72] Olaf Klungel,et al. What Is Real-World Data? A Review of Definitions Based on Literature and Stakeholder Interviews. , 2016, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.
[73] Canary Wharf,et al. The European Network of Centres for Pharmacoepidemiology and Pharmacovigilance (ENCePP) , 2012 .
[74] M. Egger,et al. Methods to systematically review and meta-analyse observational studies: a systematic scoping review of recommendations , 2018, BMC Medical Research Methodology.
[75] Tamara Rader,et al. Searching for and selecting studies , 2019, Cochrane Handbook for Systematic Reviews of Interventions.
[76] Jelle J Goeman,et al. Plea for routinely presenting prediction intervals in meta-analysis , 2016, BMJ Open.
[77] A. Mebazaa,et al. Propensity score estimators for the average treatment effect and the average treatment effect on the treated may yield very different estimates , 2016, Statistical methods in medical research.
[78] P. Tugwell,et al. Checklists of methodological issues for review authors to consider when including non‐randomized studies in systematic reviews , 2013, Research synthesis methods.
[79] David Madigan,et al. Good practices for real‐world data studies of treatment and/or comparative effectiveness: Recommendations from the joint ISPOR‐ISPE Special Task Force on real‐world evidence in health care decision making , 2017, Pharmacoepidemiology and drug safety.
[80] R. Platt,et al. A FRAMEWORK FOR REGULATORY USE OF REAL-WORLD EVIDENCE , 2017 .
[81] M. Parmar,et al. Extracting summary statistics to perform meta-analyses of the published literature for survival endpoints. , 1998, Statistics in medicine.
[82] J. Ioannidis. Why Most Published Research Findings Are False , 2005, PLoS medicine.
[83] U. Ekelund,et al. A proposed method of bias adjustment for meta-analyses of published observational studies , 2010, International journal of epidemiology.
[84] Kelvin K. W. Chan,et al. Developing a framework to incorporate real-world evidence in cancer drug funding decisions: the Canadian Real-world Evidence for Value of Cancer Drugs (CanREValue) collaboration , 2020, BMJ Open.
[85] D. Moher,et al. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. , 2010, International journal of surgery.
[86] Richard F MacLehose,et al. Good practices for quantitative bias analysis. , 2014, International journal of epidemiology.