Individual Participant Data Meta-Analysis. Группа авторов
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As there may be a considerable amount of information to collect, it is helpful to use a pre‐prepared paper or online data collection form, which may be included as an appendix in the project protocol and accompany the invitation to collaborate. An example is shown in Figure 4.3.
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
The searching and screening process will have produced a set of potentially eligible trials. This may have been refined by seeking early clarifications about trial characteristics, and possibly also by setting an information size threshold (e.g. based on contribution toward power; see Chapter 12), or a quality threshold (e.g. based on an initial risk of bias examination based on published information; see Section 4.2.1), which trials must pass in order to be included. Further clarification and consideration of these issues may be required when more detailed engagement with trial investigators begins, and the likely shape and size of the available IPD emerges.
Figure 4.3 Excerpt from a trial‐level data collection form for the STOPCAP M1 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
As for all systematic reviews, the pre‐specified outcomes for the IPD meta‐analysis project should be those judged to be most important and relevant to the objectives, even if ultimately there are insufficient data available to analyse all of them. While consideration of the participant‐level variables required begins when the IPD meta‐analysis questions are formulated, this should be re‐visited before requesting IPD from trial investigators, so that they can be specified more precisely and ensure that the planned analyses can be completed satisfactorily. Trial publications can provide an initial guide as to which data might be available, but more variables may have been collected in a trial than is evident from a trial report. Often the trial protocol and the associated case report forms can provide a more reliable indication of which data have been recorded. Irrespective of whether these documents are available or not, it is useful to supply trial investigators with a provisional list of desired variables via a paper or online form, or as a detailed data dictionary (Section 4.2.7), so that trial teams can clarify precisely which data items they can provide. An example of the typical types of data requested from trial investigators is shown in Box 4.3.
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.
In many cases, it will only be necessary to collect outcomes and participant characteristics as defined in the individual trials. However, additional variables might be required to provide greater granularity (e.g. sub‐scales in quality of life instruments), or to allow outcomes or other variables to be defined in a consistent way for each trial. For example, in an IPD meta‐analysis of anti‐platelet therapy for pre‐eclampsia in pregnancy, data on systolic and diastolic blood pressure plus presence of proteinurea were collected. This was to allow the central research team to analyse pre‐eclampsia according to both a pre‐defined meta‐analysis definition, as well as the individual trial definitions (of which there were many variations).97 Furthermore, if the IPD are to be maintained in perpetuity, to address new questions that might arise, additional data may be requested to effectively ‘future‐proof’ the database. For example, if there is a plan to use the IPD collected to produce conditional treatment effects (Chapter 5), to identify predictors of treatment effect (Chapter 7), or to identify prognostic factors (Chapter 16), then it would be sensible to request more detailed baseline data than might be necessary if just the overall (unadjusted) effects of treatments were of interest. Having said that, it is important to avoid collecting extraneous data, as these will still need to be checked and managed, and if not used, this represents an unnecessary burden for the trial teams who have spent time preparing data. Of course, it may be easier for trial teams to provide a complete trial data file, and let the IPD meta‐analysis research team extract what they need.
Box 4.3 Example of typical data obtained for trials to be included in an IPD meta‐analysis project
At a minimum, the IPD requested for each trial would