Individual Participant Data Meta-Analysis. Группа авторов

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Individual Participant Data Meta-Analysis - Группа авторов

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allocation concealment, blinding, planned and actual recruitment, and any stopping rules that were applied can be valuable when assessing risk of bias (Section 4.6), particularly if these aspects are not clearly reported in trial publications.48 This may be particularly pertinent for older trials with limited documentation.

      This form is also useful for seeking administrative details for each trial, such as the trial identifier and/or acronym, the International Standard Randomised Controlled Trial Number (ISRCTN) number (if relevant), trial title and up‐to‐date trial publication information. Also, it is worth including a question about whether the principal trial investigator will be the key contact for the IPD meta‐analysis project, or whether another individual, such as the trial statistician or data manager, will be responsible (providing space for their contact details). This would also be the place to ask trial investigators if they are aware of any potentially eligible trials not currently included in the draft protocol.

      4.2.5 Deciding How Much IPD Are Needed

Schematic illustration of excerpt from a trial-level data collection form for the STOPCAP programme of IPD meta-analyses of therapies for metastatic prostate cancer.94

      Source: Based on Tierney JF, Vale CL, Parelukar WR, et al. Evidence Synthesis to Accelerate and Improve the Evaluation of Therapies for Metastatic Hormone-sensitive Prostate Cancer. Eur Urol Focus 2019;5(2):137–43.

      Given this set of eligible trials, how much IPD should be sought from them? As a general rule, the aim should be to maximise the quantity and quality of IPD available, in order to fulfil the project objectives and complete the planned analyses reliably. For conventional reviews, aggregate data would ordinarily be sought for all studies relevant to the question of interest. Similarly, and ideally, IPD should be sought from all the eligible trials, for all participants recruited to those trials, and for all relevant outcomes, even if they were not published or included in the original analyses. This will help circumvent the risk of publication bias, outcome reporting bias, attrition bias, and other data availability biases (Chapter 9).46.58,95 For example, in trials of the effectiveness of recombinant human bone morphogenetic protein‐2 for spinal fusion, the adverse event data were not reported sufficiently to allow a rigorous evaluation of safety,96 whereas the collection of IPD allowed a complete, detailed, and in‐depth analysis.65 If it is not feasible or practical to seek IPD from all trials, the potential impact of these ‘missing’ trials should be taken into account (Chapter 9).

      4.2.6 Deciding Which Variables Are Needed in the IPD

      In addition, it is important to anticipate what supplementary analyses might be needed in the IPD meta‐analysis project to explore the main results. For example, for a question about the effects of chemotherapy on long‐term cancer survival, it may be helpful to collect data which would allow the investigation of the effects of treatment on different (competing) causes of death, such as those due to cancer, treatment‐related side effects or co‐morbid conditions.

      At a minimum, the IPD requested for each trial would

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