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Andreas Lundh

Bio: Andreas Lundh is an academic researcher from University of Southern Denmark. The author has contributed to research in topics: Systematic review & Clinical trial. The author has an hindex of 17, co-authored 44 publications receiving 2337 citations. Previous affiliations of Andreas Lundh include Copenhagen University Hospital & Cochrane Collaboration.


Papers
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Journal ArticleDOI
TL;DR: The analyses suggest the existence of an industry bias that cannot be explained by standard 'Risk of bias' assessments.
Abstract: Background Clinical research affecting how doctors practice medicine is increasingly sponsored by companies that make drugs and medical devices. Previous systematic reviews have found that pharmaceutical industry sponsored studies are more often favorable to the sponsor’s product compared with studies with other sources of sponsorship. This review is an update using more stringent methodology and also investigating sponsorship of device studies. Objectives To investigate whether industry sponsored drug and device studies have more favorable outcomes and differ in risk of bias, compared with studies having other sources of sponsorship. Search methods We searched MEDLINE (1948 to September 2010), EMBASE (1980 to September 2010), the Cochrane Methodology Register (Issue 4, 2010) and Web of Science (August 2011). In addition, we searched reference lists of included papers, previous systematic reviews and author files. Selection criteria Cross-sectional studies, cohort studies, systematic reviews and meta-analyses that quantitatively compared primary research studies of drugs or medical devices sponsored by industry with studies with other sources of sponsorship. We had no language restrictions. Data collection and analysis Two assessors identified potentially relevant papers, and a decision about final inclusion was made by all authors. Two assessors extracted data, and we contacted authors of included papers for additional unpublished data. Outcomes included favorable results, favorable conclusions, effect size, risk of bias and whether the conclusions agreed with the study results. Two assessors assessed risk of bias of included papers. We calculated pooled risk ratios (RR) for dichotomous data (with 95% confidence intervals). Main results Forty-eight papers were included. Industry sponsored studies more often had favorable efficacy results, risk ratio (RR): 1.32 (95% confidence interval (CI): 1.21 to 1.44), harms results RR: 1.87 (95% CI: 1.54 to 2.27) and conclusions RR: 1.31 (95% CI: 1.20 to 1.44) compared with non-industry sponsored studies. Ten papers reported on sponsorship and effect size, but could not be pooled due to differences in their reporting of data. The results were heterogeneous; five papers found larger effect sizes in industry sponsored studies compared with non-industry sponsored studies and five papers did not find a difference in effect size. Only two papers (including 120 device studies) reported separate data for devices and we did not find a difference between drug and device studies on the association between sponsorship and conclusions (test for interaction, P = 0.23). Comparing industry and non-industry sponsored studies, we did not find a difference in risk of bias from sequence generation, allocation concealment and follow-up. However, industry sponsored studies more often had low risk of bias from blinding, RR: 1.32 (95% CI: 1.05 to 1.65), compared with non-industry sponsored studies. In industry sponsored studies, there was less agreement between the results and the conclusions than in non-industry sponsored studies, RR: 0.84 (95% CI: 0.70 to 1.01). Authors' conclusions Sponsorship of drug and device studies by the manufacturing company leads to more favorable results and conclusions than sponsorship by other sources. Our analyses suggest the existence of an industry bias that cannot be explained by standard 'Risk of bias' assessments.

1,095 citations

Journal ArticleDOI
TL;DR: Whether delivery of a medication review by a physician, pharmacist or other healthcare professional leads to improvement in health outcomes of hospitalised adult patients compared with standard care is examined.
Abstract: Background Pharmacotherapy in the elderly population is complicated by several factors that increase the risk of drug-related harms and less favourable effectiveness. The concept of medication review is a key element in improving the quality of prescribing and in preventing adverse drug events. Although there is no generally accepted definition of medication review, it can be broadly defined as a systematic assessment of pharmacotherapy for an individual patient that aims to optimise patient medication by providing a recommendation or by making a direct change. Medication review performed in adult hospitalised patients may lead to better patient outcomes. Objectives We examined whether delivery of a medication review by a physician, pharmacist or other healthcare professional leads to improvement in health outcomes of hospitalised adult patients compared with standard care. Search methods We searched the Specialised Register of the Cochrane Effective Practice and Organisation of Care (EPOC) Group; the Cochrane Central Register of Controlled Trials (CENTRAL); MEDLINE; EMBASE; and the Cumulative Index to Nursing and Allied Health Literature (CINAHL) to November 2014, as well as International Pharmaceutical Abstracts and Web of Science to May 2015. In addition, we searched reference lists of included trials and relevant reviews. We searched trials registries and contacted experts to identify additional published and unpublished trials. We applied no language restrictions. Selection criteria We included randomised controlled trials (RCTs) of medication review in hospitalised adult patients. We excluded trials of outclinic and paediatric patients. Our primary outcome was all-cause mortality, and secondary outcomes included hospital readmissions, emergency department contacts and adverse drug events. Data collection and analysis Two review authors independently included trials, extracted data and assessed trials for risk of bias. We contacted trial authors for clarification of data and for additional unpublished data. We calculated risk ratios for dichotomous data and mean differences for continuous data (with 95% confidence intervals (CIs)). The GRADE (Grades of Recommendation, Assessment, Development and Evaluation) approach was used to assess the overall certainty of evidence for the most important outcomes. Main results We identified 6600 references (4647 references in our initial review) and included 10 trials (3575 participants). Follow-up ranged from 30 days to one year. Nine trials provided mortality data (3218 participants, 466 events), with a risk ratio of 1.02 (95% CI 0.87 to 1.19) (low-certainty evidence). Seven trials provided hospital readmission data (2843 participants, 1043 events) with a risk ratio of 0.95 (95% CI 0.87 to 1.04) (high-certainty evidence). Four trials provided emergency department contact data (1442 participants, 244 events) with a risk ratio of 0.73 (95% CI 0.52 to 1.03) (low-certainty evidence). The estimated reduction in emergency department contacts of 27% (with a CI ranging from 48% reduction to 3% increase in contacts) corresponds to a number needed to treat for an additional beneficial outcome of 37 for a low-risk population and 12 for a high-risk population over one year. Subgroup and sensitivity analyses did not significantly alter our results. Authors' conclusions We found no evidence that medication review reduces mortality or hospital readmissions, although we did find evidence that medication review may reduce emergency department contacts. However, because of short follow-up ranging from 30 days to one year, important treatment effects may have been overlooked. High-quality trials with long-term follow-up (i.e. at least up to a year) are needed to provide more definitive evidence for the effect of medication review on clinically important outcomes such as mortality, readmissions and emergency department contacts, and on outcomes such as adverse events. Therefore, if used in clinical practice, medication reviews should be undertaken as part of a clinical trial with long-term follow-up.

262 citations

Journal ArticleDOI
TL;DR: Recommendations by some groups were not based on empirical evidence and many groups had no recommendations on how to use the quality assessment in reviews, with sensitivity analysis, quality as an inclusion threshold and subgroup analysis being the most commonly recommended methods.
Abstract: Assessing the risk of bias in individual studies in a systematic review can be done using individual components or by summarizing the study quality in an overall score. We examined the instructions to authors of the 50 Cochrane Review Groups that focus on clinical interventions for recommendations on methodological quality assessment of studies. Forty-one of the review groups (82%) recommended quality assessment using components and nine using a scale. All groups recommending components recommended to assess concealment of allocation, compared to only two of the groups recommending scales (P < 0.0001). Thirty-five groups (70%) recommended assessment of sequence generation and 21 groups (42%) recommended assessment of intention-to-treat analysis. Only 28 groups (56%) had specific recommendations for using the quality assessment of studies analytically in reviews, with sensitivity analysis, quality as an inclusion threshold and subgroup analysis being the most commonly recommended methods. The scales recommended had problems in the individual items and some of the groups recommending components recommended items not related to bias in their quality assessment. We found that recommendations by some groups were not based on empirical evidence and many groups had no recommendations on how to use the quality assessment in reviews. We suggest that all Cochrane Review Groups refer to the Cochrane Handbook for Systematic Reviews of Interventions, which is evidence-based, in their instructions to authors and that their own guidelines are kept to a minimum and describe only how methodological topics that are specific to their fields should be handled.

250 citations

Journal ArticleDOI
03 Jan 2012-BMJ
TL;DR: The effect of including unpublished trial outcome data obtained from the Food and Drug Administration on the results of meta-analyses of drug trials varies by drug and outcome.
Abstract: Objective To investigate the effect of including unpublished trial outcome data obtained from the Food and Drug Administration (FDA) on the results of meta-analyses of drug trials. Design Reanalysis of meta-analyses. Data sources Drug trials with unpublished outcome data for new molecular entities that were approved by the FDA between 2001 and 2002 were identified. For each drug, eligible systematic reviews containing at least one meta-analysis were identified by searches of Medline, Embase, and the Cochrane Library in November 2010. Selection criteria Eligible systematic reviews were done after FDA approval of the drug, were published in English, and had outcomes and comparators that were the same as those of the trials with unpublished FDA trial outcomes, and the characteristics of participants in the systematic reviews were consistent with the FDA approved indication for the drug. Clinical guidelines, conference proceedings, duplicate systematic reviews, and systematic reviews in which included trials were not referenced or that combined trials across multiple drug classes were excluded. Systematic reviews using non-standard meta-analytic techniques (such as Bayesian or network meta-analyses) and those that used inappropriate or invalid methods for calculation of summary statistics (such as unweighted pooled analyses) were also excluded. Data extraction Two authors independently extracted data from both the published systematic reviews and the FDA’s medical and statistical reviews of the trials submitted to FDA. Main outcome measure Summary statistics (risk ratios, odds ratios, or weighted mean differences) for relevant outcomes with and without unpublished FDA trial data. Results 42 meta-analyses (41 efficacy outcomes, one harm outcome) for nine drugs across six drug classes were reanalysed. Overall, addition of unpublished FDA trial data caused 46% (19/41) of the summary estimates from the meta-analyses to show lower efficacy of the drug, 7% (3/41) to show identical efficacy, and 46% (19/41) to show greater efficacy. The summary estimate of the single harm outcome showed more harm from the drug after inclusion of unpublished FDA trial data. Conclusion The effect of including unpublished FDA trial outcome data varies by drug and outcome. Unpublished FDA trial outcome data should be available and included in meta-analysis. Making these data easily accessible is particularly important because the effects of including unpublished data vary.

214 citations


Cited by
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Journal ArticleDOI
18 Oct 2011-BMJ
TL;DR: The Cochrane Collaboration’s tool for assessing risk of bias aims to make the process clearer and more accurate.
Abstract: Flaws in the design, conduct, analysis, and reporting of randomised trials can cause the effect of an intervention to be underestimated or overestimated. The Cochrane Collaboration’s tool for assessing risk of bias aims to make the process clearer and more accurate

22,227 citations

Journal ArticleDOI
02 Jan 2015-BMJ
TL;DR: The PRISMA-P checklist as mentioned in this paper provides 17 items considered to be essential and minimum components of a systematic review or meta-analysis protocol, as well as a model example from an existing published protocol.
Abstract: Protocols of systematic reviews and meta-analyses allow for planning and documentation of review methods, act as a guard against arbitrary decision making during review conduct, enable readers to assess for the presence of selective reporting against completed reviews, and, when made publicly available, reduce duplication of efforts and potentially prompt collaboration. Evidence documenting the existence of selective reporting and excessive duplication of reviews on the same or similar topics is accumulating and many calls have been made in support of the documentation and public availability of review protocols. Several efforts have emerged in recent years to rectify these problems, including development of an international register for prospective reviews (PROSPERO) and launch of the first open access journal dedicated to the exclusive publication of systematic review products, including protocols (BioMed Central's Systematic Reviews). Furthering these efforts and building on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines, an international group of experts has created a guideline to improve the transparency, accuracy, completeness, and frequency of documented systematic review and meta-analysis protocols--PRISMA-P (for protocols) 2015. The PRISMA-P checklist contains 17 items considered to be essential and minimum components of a systematic review or meta-analysis protocol.This PRISMA-P 2015 Explanation and Elaboration paper provides readers with a full understanding of and evidence about the necessity of each item as well as a model example from an existing published protocol. This paper should be read together with the PRISMA-P 2015 statement. Systematic review authors and assessors are strongly encouraged to make use of PRISMA-P when drafting and appraising review protocols.

9,361 citations

Journal ArticleDOI
28 Aug 2019-BMJ
TL;DR: The Cochrane risk-of-bias tool has been updated to respond to developments in understanding how bias arises in randomised trials, and to address user feedback on and limitations of the original tool.
Abstract: Assessment of risk of bias is regarded as an essential component of a systematic review on the effects of an intervention. The most commonly used tool for randomised trials is the Cochrane risk-of-bias tool. We updated the tool to respond to developments in understanding how bias arises in randomised trials, and to address user feedback on and limitations of the original tool.

9,228 citations

Journal ArticleDOI
TL;DR: The SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) 2013, a guideline for the minimum content of a clinical trial protocol, is presented in this paper.
Abstract: The protocol of a clinical trial serves as the foundation for study planning, conduct, reporting, and appraisal. However, trial protocols and existing protocol guidelines vary greatly in content and quality. This article describes the systematic development and scope of SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) 2013, a guideline for the minimum content of a clinical trial protocol.The 33-item SPIRIT checklist applies to protocols for all clinical trials and focuses on content rather than format. The checklist recommends a full description of what is planned; it does not prescribe how to design or conduct a trial. By providing guidance for key content, the SPIRIT recommendations aim to facilitate the drafting of high-quality protocols. Adherence to SPIRIT would also enhance the transparency and completeness of trial protocols for the benefit of investigators, trial participants, patients, sponsors, funders, research ethics committees or institutional review boards, peer reviewers, journals, trial registries, policymakers, regulators, and other key stakeholders.

3,672 citations

Journal ArticleDOI
09 Jan 2013-BMJ
TL;DR: The SPIRIT 2013 Explanation and Elaboration paper provides important information to promote full understanding of the checklist recommendations and strongly recommends that this explanatory paper be used in conjunction with the SPIRit Statement.
Abstract: High quality protocols facilitate proper conduct, reporting, and external review of clinical trials. However, the completeness of trial protocols is often inadequate. To help improve the content and quality of protocols, an international group of stakeholders developed the SPIRIT 2013 Statement (Standard Protocol Items: Recommendations for Interventional Trials). The SPIRIT Statement provides guidance in the form of a checklist of recommended items to include in a clinical trial protocol. This SPIRIT 2013 Explanation and Elaboration paper provides important information to promote full understanding of the checklist recommendations. For each checklist item, we provide a rationale and detailed description; a model example from an actual protocol; and relevant references supporting its importance. We strongly recommend that this explanatory paper be used in conjunction with the SPIRIT Statement. A website of resources is also available (www.spirit-statement.org). The SPIRIT 2013 Explanation and Elaboration paper, together with the Statement, should help with the drafting of trial protocols. Complete documentation of key trial elements can facilitate transparency and protocol review for the benefit of all stakeholders.

3,108 citations