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Biomedical subjects

Sarah Burdett

Publications and source records attributed to Sarah Burdett.

9 recordsLinked to original sources
PubMed2005

Postoperative radiotherapy in non-small-cell lung cancer: update of an individual patient data meta-analysis.

We report an updated systematic review and individual patient data meta-analysis of the effectiveness of postoperative radiotherapy (PORT) in non-small-cell lung cancer. Results continue to show PORT to be detrimental, with an 18% relative increase in the risk of death. Similar detriments were observed for local recurrence-free survival, distant recurrence-free survival and overall recurrence-free survival. There continues to be evidence that the effects of PORT are more harmful in those patients with stage I disease than those with stage II disease.

Carcinoma, Non-Small-Cell Lung↗
PubMed2005

Meta-analysis when only the median survival times are known: a comparison with individual patient data results.

BACKGROUND: The hazard ratio (HR) is the most appropriate measure for time to event outcomes such as survival. In systematic reviews, HRs can be calculated either from the raw trial data obtained as part of an individual patient data (IPD) meta-analysis or from the appropriate trial-level summary statistics. However, the information required for the latter are seldom reported in sufficient detail to allow reviewers to calculate HRs. In contrast, the median survival and survival rates at specific time points are frequently presented. We aimed to evaluate retrospectively the performance of meta-analyses using median survival times and survival rates by comparing them with meta-analyses using IPD to calculate HRs. METHODS: IPD from thirteen published meta-analyses (MAs) in cancers with high mortality rates were used. Median survival and survival rates were calculated from the IPD rather than taken from publications so that the same trials, patients, and extended follow-up are used in each analysis. RESULTS AND CONCLUSIONS: We show that using median survival times or survival rates at a particular point in time are not reasonable surrogate measures for meta-analyses of survival outcomes and that, wherever possible, HRs should be calculated. Individual trial publications reporting on time to event outcomes, therefore, should provide more detailed statistical information, preferably logHRs and their variances, or their estimators.

Data Interpretation, Statistical↗
PubMed2003

Publication bias and meta-analyses: a practical example.

OBJECTIVES: Publication bias is widely appreciated, but considerable time and effort are needed to locate and obtain data from unpublished randomized controlled trials (RCTs), those published in non-English language journals or those reported in the gray literature; for this publication, we will call this collection of trials the "gray+literature." However, excluding such trials from systematic reviews could introduce bias and give rise to misleading conclusions. METHODS: We aimed to explore and quantify the impact of inclusion of gray+ literature on the results of all completed individual patient data (IPD) reviews coordinated by our group (13 meta-analyses). For each IPD review, results were calculated for RCTs fully published in English language journals and RCTs fully published in English language journals and the gray+literature. RESULTS: The IPD meta-analyses based only on RCTs that were fully published in English language journals tended to give more favorable results than those that included RCTs from the gray+literature. Although in most cases the addition of gray+data gave less encouraging results, moving the estimated treatment effect toward a null result, the direction of effect was not always predictable. CONCLUSIONS: We recommend that all systematic reviews should at least attempt to identify trials reported in the gray+literature and, where possible, obtain data from them.

Humans↗
PubMed2002

A comparison of the results of checked versus unchecked individual patient data meta-analyses.

OBJECTIVES: Systematic reviews and meta-analyses of individual patient data involve the central collection, validation, and reanalysis of raw data from randomized controlled trials. Checking individual patient data before its inclusion in a meta-analysis involves a number of different procedures that can be both time- and resource-intensive. We therefore aimed to assess the utility of data checking by investigating whether checks made any appreciable difference to the results of an individual patient data meta-analysis. METHODS: Data that were included in a meta-analysis of postoperative radiotherapy in non-small-cell lung cancer were used in a comparison of checked and unchecked data to investigate whether checking impacted the final results of the meta-analysis. Data "as received" were compared with fully checked and with followed-up data. RESULTS: Checking influenced the results, in this case mainly due to the exclusion of a single trial that failed to meet checking procedures. Checking data from most trials had only a small effect and did not materially alter the overall results of the meta-analysis. CONCLUSIONS: Although data checking and cleaning is time-consuming, and for the majority of trials may make little difference to the analysis, such procedures provide a useful safeguard against rare occurrences of data with major problems. Checking may also lend additional confidence in the data set, which may be particularly important when using unpublished data that has not been subject to standard peer review.

Carcinoma, Non-Small-Cell Lung↗