Individual Participant Data Meta-Analysis. Группа авторов

EORTC 30994 LOW RISK Was allocation sequence random? YES: Minimisation, stratified by institution, pathological T stage and lymph node status. Also, IPD checks show that the pattern of allocation is steady by treatment group and over time; there were no obvious imbalances by group on any day of the week; and there were few weekend randomisations. Was allocation sequence concealed? YES: Randomisation was done centrally at the EORTC headquarters. Did baseline differences suggest a problem? NO: IPD checks show no obvious imbalance by treatment group in baseline characteristics. LOW RISK Were participants aware of their assigned intervention during the trial? YES: Blinding not possible in a chemotherapy versus none trial, but awareness cannot affect survival outcome. Were carers and people delivering the interventions aware of participants' assigned intervention during the trial? YES: Blinding not possible in a chemotherapy versus none trial, but awareness is unlikely to affect how these treatments were given. Were there deviations from the intended intervention that arose because of the trial context? NO: There were no deviations from because of the context. Was an appropriate analysis used to estimate the effect of assignment to intervention? YES: An intention‐to‐treat analysis of all randomised patients was derived from the IPD. LOW RISK Were data available for all, or nearly all, participants randomised? YES: Data were provided for all patients randomised. LOW RISK Was method of measuring the outcome inappropriate? NO: Overall survival was derived from the IPD according to the meta‐analysis protocol and SAP. Could measurement of the outcome have differed between intervention groups? NO: Checks of the IPD revealed that follow‐up of participants was balanced by treatment group. Outcome assessor aware of intervention received? YES: This cannot affect the overall survival outcome. LOW RISK

4.8 Verification of Finalised Trial IPD

Once a trial’s IPD has been processed, checked and all issues resolved as far as possible, it is useful to give trial investigators a final opportunity to verify their data prior to it being used in any meta‐analysis. This is most easily achieved by sending a descriptive summary of the finalised data for each trial, any amendments made to the original data provided, and results of the primary analyses (Figure 4.13 gives an example), but offering the option to supply a copy of the full checked IPD, if required. Such a document may be useful if investigators raise queries about differences between trial data presented in the original trial publication and in the IPD meta‐analysis.

4.9 Merging IPD Ready for Meta‐Analysis

      After verification, the finalised dataset for each trial is ready to be used within subsequent IPD meta‐analyses. At this stage, it is helpful to merge the final IPD from all trials into a single dataset. Although statistical methods for IPD meta‐analysis can still be applied if trial datasets are located locally in different files, a single dataset that houses all the IPD is more convenient and potentially makes analyses faster. For example, Box 1.1 (Chapter 1) shows an example dataset containing IPD from 10 trials after data checking, harmonisation, verification and merging. Most statistical packages, such as Stata, SAS and R, have built‐in commands for merging datasets from different files, and these generally require the datasets to share common variable names, which will have been achieved at the data harmonisation stage (Section 4.5.3). Not all variables in every trial dataset need to be merged, and the statistician can restrict the variables to just those to be used in particular statistical analyses. It is important to check that no errors are introduced when merging the datasets. Therefore, it is sensible to calculate summary statistics (e.g. number of participants in each group, mean age, proportion of women, overall treatment effect) for each trial before (in the pre‐merge dataset) and after (in the merged dataset), to ensure they agree exactly. A single dataset comprising IPD from all trials will not be achievable if the IPD for some can only be accessed remotely, but the central research team can still proceed with a two-stage meta‐analysis as described in Chapter 5.

Figure 4.13 Example of items to include in summary of finalised trial IPD for verification by a trial investigator.

      Source: Ruth Walker and Lesley Stewart.

4.10 Concluding Remarks

      There is no doubt that development of the project protocol, managing a large‐scale collaboration and carefully collecting, processing and checking data is a lengthy and resource‐intensive phase of an IPD meta‐analysis project. However, these aspects are key to ensuring that the approach is scientifically rigorous and truly collaborative, and that the privacy of the participants in the included trials is maintained. Importantly, it also ensures that the collated IPD is as accurate, up to date, reliable and comprehensive as it can be, and that it is well understood by the central research team. In all, this provides a necessary solid foundation for the statistical analysis part of the IPD project that follows.

Part II Fundamental Statistical Methods and Principles