Retrieval of individual patient data depended on study characteristics : a randomized controlled trial

OBJECTIVE: To examine the effect of providing a financial incentive to authors of randomized clinical trials (RCTs) to obtain individual patient data (IPD). STUDY DESIGN AND SETTING: Parallel-group RCT with authors identified in the RCTs eligible for two systematic reviews. The authors were randomly allocated to the intervention (financial incentive with several contact approaches) or control group (using the same contact approaches). Studied outcomes: proportion of authors who provided IPD, time to obtain IPD, and completeness of IPD received. RESULTS: Of the 129 authors contacted, 37 authors suggested or contacted a person/funder providing relevant details or showed interest to collaborate, while 45 authors directed us to contact a person/funder, lacked resources/time, did not have ownership/approval to share the IPD, or claimed IPD was too old. None of the authors shared their IPD. We contacted 17 sponsors and received two complete IPD datasets from one sponsor. The time to obtain IPD was >1 year after a sponsor's positive response. Common barriers included study identification, data ownership, limited data access, and required IPD licenses. CONCLUSIONS: IPD sharing may depend on study characteristics, including funding type, study size, study risk of bias, and treatment effect, but not on providing a financial incentive. TRIAL REGISTRATION: Clinical Trials.gov (NCT02569411), registered on October 5th, 2015

The use of human papillomavirus DNA methylation in cervical intraepithelial neoplasia : A systematic review and meta-analysis

Background: Methylation of viral DNA has been proposed as a novel biomarker for triage of human papillomavirus (HPV) positive women at screening. This systematic review and meta-analysis aims to assess how methylation levels change with disease severity and to determine diagnostic test accuracy (DTA) in detecting high-grade cervical intra-epithelial neoplasia (CIN). Methods: We performed searches in MEDLINE, EMBASE and CENTRAL from inception to October 2019. Studies were eligible if they explored HPV methylation levels in HPV positive women. Data were extracted in duplicate and requested from authors where necessary. Random-effects models and a bivariate mixed-effects binary regression model were applied to determine pooled effect estimates. Findings: 44 studies with 8819 high-risk HPV positive women were eligible. The pooled estimates for positive methylation rate in HPV16 L1 gene were higher for high-grade CIN (>= CIN2/high-grade squamous intra-epithelial lesion (HSIL) (95% confidence interval (95%CI:72.7% (47 8-92.2))) vs. low-grade CIN (= CIN2/HSIL vs. = CIN2/HSIL vs. Interpretation: Higher HPV methylation is associated with increased disease severity, whilst HPV16 L1/L2 genes demonstrated high diagnostic accuracy to detect high-grade CIN in HPV16 positive women. Direct clinical use is limited by the need for a multi-genotype and standardised assays. Next-generation multiplex HPV sequencing assays are under development and allow potential for rapid, automated and low-cost methylation testing. (C) 2019 The Authors. Published by Elsevier B.V.Peer reviewe

The final transformation of Étaín

Abstract Background Although serotonin (5-HT3) receptor antagonists are effective in reducing nausea and vomiting, they may be associated with increased cardiac risk. Our objective was to examine the comparative safety and effectiveness of 5-HT3 receptor antagonists (e.g., dolasetron, granisetron, ondansetron, palonosetron, tropisetron) alone or combined with steroids for patients undergoing chemotherapy. Methods We searched MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials from inception until December 2015 for studies comparing 5-HT3 receptor antagonists with each other or placebo in chemotherapy patients. The search results were screened, data were abstracted, and risk of bias was appraised by pairs of reviewers, independently. Random-effects meta-analyses and network meta-analyses (NMAs) were conducted. Results After screening 9226 citations and 970 full-text articles, we included 299 studies (n = 58,412 patients). None of the included studies reported harms for active treatment versus placebo. For NMAs on the risk of arrhythmia (primary outcome; three randomized controlled trials [RCTs], 627 adults) and mortality (secondary outcome; eight RCTs, 4823 adults), no statistically significant differences were observed between agents. A NMA on the risk of QTc prolongation showed a significantly greater risk for dolasetron + dexamethasone versus ondansetron + dexamethasone (four RCTs, 3358 children and adults, odds ratio 2.94, 95% confidence interval 2.13–4.17). For NMAs on the number of patients without nausea (44 RCTs, 11,664 adults, 12 treatments), number of patients without vomiting (63 RCTs, 15,460 adults, 12 treatments), and number of patients without chemotherapy-induced nausea or vomiting (27 RCTs, 10,924 adults, nine treatments), all agents were significantly superior to placebo. For a NMA on severe vomiting (10 RCTs, 917 adults), all treatments decreased the risk, but only ondansetron and ramosetron were significantly superior to placebo. According to a rank-heat plot with the surface under the cumulative ranking curve results, palonosetron + steroid was ranked the safest and most effective agent overall. Conclusions Most 5-HT3 receptor antagonists were relatively safe when compared with each other, yet none of the studies compared active treatment with placebo for harms. However, dolasetron + dexamethasone may prolong the QTc compared to ondansetron + dexamethasone. All agents were effective for reducing risk of nausea, vomiting, and chemotherapy-induced nausea or vomiting. Trial registration This study was registered at PROSPERO: ( CRD42013003564 )

Contacting authors to retrieve individual patient data : study protocol for a randomized controlled trial

BACKGROUND: Individual patient data (IPD) meta-analysis is considered the "gold standard" for exploring the effectiveness of interventions in different subgroups of patients. However, obtaining IPD is time-consuming and contact with the researchers responsible for the original trials is usually required. To date, there are no studies evaluating different strategies to optimize the process for retrieval of IPD from such researchers. Our aim is to examine the impact of providing incentives to the researchers responsible for the trials eligible for a meta-analysis to submit their IPD. METHODS/DESIGN: We updated our previously published systematic reviews for type 1 diabetes mellitus comparing long- and intermediate-acting insulin regimens (from January 2013 to June 2015) and for Alzheimer's dementia comparing cognitive enhancers (from January 2015 to May 2015). Eligible were randomized controlled trials (RCTs) fulfilling the eligibility criteria of the systematic reviews. We will randomly allocate authors of the reports of these RCTs into an intervention or control group. Those allocated to the intervention group will be contacted by email, mail, and phone, and will be asked to provide the IPD from their RCT and will be given a financial incentive. Those allocated to the control group will be contacted by email, mail, and phone, but will not receive a financial incentive. Our primary outcome will be the proportion of authors who provide the IPD. The secondary outcomes will be the time to return the dataset (defined as the period between the information request and the authors' response with the dataset), and completeness of data. We will compare the response rates in the two groups using the odds ratio and the corresponding 95 % confidence interval. We will also use binary logistic regression and cox regression analyses to examine whether different RCT characteristics, such as study size and sponsor information, influence the probability of providing IPD and the time needed to share the data. DISCUSSION: This study will determine whether a financial incentive affects response rates when seeking IPD from the original researchers. We will disseminate our findings in an open access scientific journal and present results at national and international conferences. TRIAL REGISTRATION: This trial is registered in Clinical Trials.gov, ID number NCT02569411 . Date of registration 5 October 2015

Using a distribution-based approach and systematic review methods to derive minimum clinically important differences

Abstract Background Clinical interpretation of changes measured on a scale is dependent on knowing the minimum clinically important difference (MCID) for that scale: the threshold above which clinicians, patients, and researchers perceive an outcome difference. Until now, approaches to determining MCIDs were based upon individual studies or surveys of experts. However, the comparison of meta-analytic treatment effects to a MCID derived from a distribution of standard deviations (SDs) associated with all trial-specific outcomes in a meta-analysis could improve our clinical understanding of meta-analytic treatment effects. Methods We approximated MCIDs using a distribution-based approach that pooled SDs associated with baseline mean or mean change values for two scales (i.e. Mini-Mental State Exam [MMSE] and Alzheimer Disease Assessment Scale – Cognitive Subscale [ADAS-Cog]), as reported in parallel randomized trials (RCTs) that were included in a systematic review of cognitive enhancing medications for dementia (i.e. cholinesterase inhibitors and memantine). We excluded RCTs that did not report baseline or mean change SD values. We derived MCIDs at 0.4 and 0.5 SDs of the pooled SD and compared our derived MCIDs to previously published MCIDs for the MMSE and ADAS-Cog. Results We showed that MCIDs derived from a distribution-based approach approximated published MCIDs for the MMSE and ADAS-Cog. For the MMSE (51 RCTs, 12,449 patients), we derived a MCID of 1.6 at 0.4 SDs and 2 at 0.5 SDs using baseline SDs and we derived a MCID of 1.4 at 0.4 SDs and 1.8 at 0.5 SDs using mean change SDs. For the ADAS-Cog (37 RCTs, 10,006 patients), we derived a MCID of 4 at 0.4 SDs and 5 at 0.5 SDs using baseline SDs and we derived a MCID of 2.6 at 0.4 SDs and 3.2 at 0.5 SDs using mean change SDs. Conclusion A distribution-based approach using data included in a systematic review approximated known MCIDs. Our approach performed better when we derived MCIDs from baseline as opposed to mean change SDs. This approach could facilitate clinical interpretation of outcome measures reported in RCTs and systematic reviews of interventions. Future research should focus on the generalizability of this method to other clinical scenarios

The Kilim plot: A tool for visualizing network meta-analysis results for multiple outcomes.

Network meta-analysis (NMA) can be used to compare multiple competing treatments for the same disease. In practice, usually a range of outcomes are of interest. As the number of outcomes increases, summarizing results from multiple NMAs becomes a non-trivial task, especially for larger networks. Moreover, NMAs provide results in terms of relative effect measures that can be difficult to interpret and apply in every-day clinical practice, such as the odds ratios. In this paper, we aim to facilitate the clinical decision-making process by proposing a new graphical tool, the Kilim plot, for presenting results from NMA on multiple outcomes. Our plot compactly summarizes results on all treatments and all outcomes; it provides information regarding the strength of the statistical evidence of treatment effects, while it illustrates absolute, rather than relative, effects of interventions. Moreover, it can be easily modified to include considerations regarding clinically important effects. To showcase our method, we use data from a network of studies in antidepressants. All analyses are performed in R and we provide the source code needed to produce the Kilim plot, as well as an interactive web application