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Bias and precision of methods for estimating the difference in restricted mean survival time from an individual patient data meta-analysis

Overview of attention for article published in BMC Medical Research Methodology, March 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

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6 tweeters

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37 Mendeley
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Title
Bias and precision of methods for estimating the difference in restricted mean survival time from an individual patient data meta-analysis
Published in
BMC Medical Research Methodology, March 2016
DOI 10.1186/s12874-016-0137-z
Pubmed ID
Authors

Béranger Lueza, Federico Rotolo, Julia Bonastre, Jean-Pierre Pignon, Stefan Michiels

Abstract

The difference in restricted mean survival time ([Formula: see text]), the area between two survival curves up to time horizon [Formula: see text], is often used in cost-effectiveness analyses to estimate the treatment effect in randomized controlled trials. A challenge in individual patient data (IPD) meta-analyses is to account for the trial effect. We aimed at comparing different methods to estimate the [Formula: see text] from an IPD meta-analysis. We compared four methods: the area between Kaplan-Meier curves (experimental vs. control arm) ignoring the trial effect (Naïve Kaplan-Meier); the area between Peto curves computed at quintiles of event times (Peto-quintile); the weighted average of the areas between either trial-specific Kaplan-Meier curves (Pooled Kaplan-Meier) or trial-specific exponential curves (Pooled Exponential). In a simulation study, we varied the between-trial heterogeneity for the baseline hazard and for the treatment effect (possibly correlated), the overall treatment effect, the time horizon [Formula: see text], the number of trials and of patients, the use of fixed or DerSimonian-Laird random effects model, and the proportionality of hazards. We compared the methods in terms of bias, empirical and average standard errors. We used IPD from the Meta-Analysis of Chemotherapy in Nasopharynx Carcinoma (MAC-NPC) and its updated version MAC-NPC2 for illustration that included respectively 1,975 and 5,028 patients in 11 and 23 comparisons. The Naïve Kaplan-Meier method was unbiased, whereas the Pooled Exponential and, to a much lesser extent, the Pooled Kaplan-Meier methods showed a bias with non-proportional hazards. The Peto-quintile method underestimated the [Formula: see text], except with non-proportional hazards at [Formula: see text]= 5 years. In the presence of treatment effect heterogeneity, all methods except the Pooled Kaplan-Meier and the Pooled Exponential with DerSimonian-Laird random effects underestimated the standard error of the [Formula: see text]. Overall, the Pooled Kaplan-Meier method with DerSimonian-Laird random effects formed the best compromise in terms of bias and variance. The [Formula: see text] estimated with the Pooled Kaplan-Meier method was 0.49 years (95 % CI: [-0.06;1.03], p = 0.08) when comparing radiotherapy plus chemotherapy vs. radiotherapy alone in the MAC-NPC and 0.59 years (95 % CI: [0.34;0.84], p < 0.0001) in the MAC-NPC2. We recommend the Pooled Kaplan-Meier method with DerSimonian-Laird random effects to estimate the difference in restricted mean survival time from an individual-patient data meta-analysis.

Twitter Demographics

The data shown below were collected from the profiles of 6 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 2 5%
Japan 1 3%
Unknown 34 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 24%
Student > Ph. D. Student 6 16%
Professor > Associate Professor 4 11%
Student > Bachelor 4 11%
Student > Master 3 8%
Other 8 22%
Unknown 3 8%
Readers by discipline Count As %
Medicine and Dentistry 8 22%
Mathematics 6 16%
Agricultural and Biological Sciences 3 8%
Pharmacology, Toxicology and Pharmaceutical Science 2 5%
Immunology and Microbiology 2 5%
Other 8 22%
Unknown 8 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 April 2016.
All research outputs
#1,651,275
of 7,540,906 outputs
Outputs from BMC Medical Research Methodology
#269
of 775 outputs
Outputs of similar age
#78,984
of 271,154 outputs
Outputs of similar age from BMC Medical Research Methodology
#12
of 31 outputs
Altmetric has tracked 7,540,906 research outputs across all sources so far. Compared to these this one has done well and is in the 77th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 775 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.8. This one has gotten more attention than average, scoring higher than 65% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 271,154 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.