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Enhanced secondary analysis of survival data: reconstructing the data from published Kaplan-Meier survival curves

Overview of attention for article published in BMC Medical Research Methodology, February 2012
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)

Mentioned by

blogs
1 blog
policy
1 policy source
twitter
10 tweeters

Citations

dimensions_citation
708 Dimensions

Readers on

mendeley
395 Mendeley
citeulike
3 CiteULike
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Title
Enhanced secondary analysis of survival data: reconstructing the data from published Kaplan-Meier survival curves
Published in
BMC Medical Research Methodology, February 2012
DOI 10.1186/1471-2288-12-9
Pubmed ID
Authors

Patricia Guyot, AE Ades, Mario JNM Ouwens, Nicky J Welton

Abstract

The results of Randomized Controlled Trials (RCTs) on time-to-event outcomes that are usually reported are median time to events and Cox Hazard Ratio. These do not constitute the sufficient statistics required for meta-analysis or cost-effectiveness analysis, and their use in secondary analyses requires strong assumptions that may not have been adequately tested. In order to enhance the quality of secondary data analyses, we propose a method which derives from the published Kaplan Meier survival curves a close approximation to the original individual patient time-to-event data from which they were generated.

Twitter Demographics

The data shown below were collected from the profiles of 10 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 395 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 5 1%
France 2 <1%
United States 2 <1%
Canada 2 <1%
South Africa 1 <1%
Unknown 383 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 99 25%
Student > Ph. D. Student 53 13%
Student > Master 41 10%
Other 38 10%
Student > Bachelor 24 6%
Other 70 18%
Unknown 70 18%
Readers by discipline Count As %
Medicine and Dentistry 120 30%
Pharmacology, Toxicology and Pharmaceutical Science 31 8%
Economics, Econometrics and Finance 28 7%
Agricultural and Biological Sciences 26 7%
Mathematics 23 6%
Other 67 17%
Unknown 100 25%

Attention Score in Context

This research output has an Altmetric Attention Score of 22. 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 21 December 2020.
All research outputs
#1,078,620
of 17,349,416 outputs
Outputs from BMC Medical Research Methodology
#155
of 1,610 outputs
Outputs of similar age
#10,581
of 224,355 outputs
Outputs of similar age from BMC Medical Research Methodology
#1
of 1 outputs
Altmetric has tracked 17,349,416 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,610 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.9. This one has done particularly well, scoring higher than 90% 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 224,355 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them