eprintid: 1502208 rev_number: 43 eprint_status: archive userid: 608 dir: disk0/01/50/22/08 datestamp: 2016-07-13 10:09:24 lastmod: 2021-12-13 03:19:38 status_changed: 2017-03-27 11:13:51 type: article metadata_visibility: show creators_name: Hollis, S creators_name: Fletcher, C creators_name: Lynn, F creators_name: Urban, HJ creators_name: Burger, HU creators_name: Tudur Smith, C creators_name: Sydes, MR creators_name: Gerlinger, C title: Best practice for analysis of shared clinical trial data ispublished: pub divisions: UCL divisions: B02 divisions: D65 divisions: J38 note: © 2016 The Author(s). Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. abstract: BACKGROUND: Greater transparency, including sharing of patient-level data for further research, is an increasingly important topic for organisations who sponsor, fund and conduct clinical trials. This is a major paradigm shift with the aim of maximising the value of patient-level data from clinical trials for the benefit of future patients and society. We consider the analysis of shared clinical trial data in three broad categories: (1) reanalysis - further investigation of the efficacy and safety of the randomized 3 intervention, (2) meta-analysis, and (3) supplemental analysis for a research question that is not directly assessing the randomized intervention. DISCUSSION: In order to support appropriate interpretation and limit the risk of misleading findings, analysis of shared clinical trial data should have a pre-specified analysis plan. However, it is not generally possible to limit bias and control multiplicity to the extent that is possible in the original trial design, conduct and analysis, and this should be acknowledged and taken into account when interpreting results. We highlight a number of areas where specific considerations arise in planning, conducting, interpreting and reporting analyses of shared clinical trial data. A key issue is that that these analyses essentially share many of the limitations of any post hoc analyses beyond the original specified analyses. The use of individual patient data in meta-analysis can provide increased precision and reduce bias. Supplemental analyses are subject to many of the same issues that arise in broader epidemiological analyses. Specific discussion topics are addressed within each of these areas. SUMMARY: Increased provision of patient-level data from industry and academic-led clinical trials for secondary research can benefit future patients and society. Responsible data sharing, including transparency of the research objectives, analysis plans and of the results will support appropriate interpretation and help to address the risk of misleading results and avoid unfounded health scares. date: 2016-08 date_type: published publisher: BioMed Central official_url: http://dx.doi.org/10.1186/s12874-016-0170-y oa_status: green full_text_type: pub language: eng primo: open primo_central: open_green article_type_text: Article verified: verified_manual elements_id: 1139359 doi: 10.1186/s12874-016-0170-y lyricists_name: Sydes, Matthew lyricists_id: MRSYD21 actors_name: Sydes, Matthew actors_id: MRSYD21 actors_role: owner full_text_status: public publication: BMC Medical Research Methodology volume: 16 number: Suppl 1 article_number: 76 issn: 1471-2288 citation: Hollis, S; Fletcher, C; Lynn, F; Urban, HJ; Burger, HU; Tudur Smith, C; Sydes, MR; Hollis, S; Fletcher, C; Lynn, F; Urban, HJ; Burger, HU; Tudur Smith, C; Sydes, MR; Gerlinger, C; - view fewer <#> (2016) Best practice for analysis of shared clinical trial data. BMC Medical Research Methodology , 16 (Suppl 1) , Article 76. 10.1186/s12874-016-0170-y <https://doi.org/10.1186/s12874-016-0170-y>. Green open access document_url: https://discovery.ucl.ac.uk/id/eprint/1502208/7/Sydes_art%253A10.1186%252Fs12874-016-0170-y.pdf