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A systematic review of using and reporting survival analyses in acute lymphoblastic leukemia literature

Overview of attention for article published in BMC Hematology, June 2016
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Title
A systematic review of using and reporting survival analyses in acute lymphoblastic leukemia literature
Published in
BMC Hematology, June 2016
DOI 10.1186/s12878-016-0055-7
Pubmed ID
Authors

Chatree Chai-Adisaksopha, Alfonso Iorio, Christopher Hillis, Wendy Lim, Mark Crowther

Abstract

Survival analysis is commonly used to determine the treatment effect among acute lymphoblastic leukemia (ALL) patients who undergo allogeneic stem cell transplantation (allo-SCT) or other treatments. The aim of this study was to evaluate the use and reporting of survival analyses in these articles. We performed a systematic review by searching the MEDLINE, EMBASE and Cochrane library databases from inception to April 2015. Clinical trials of patients with ALL comparing allo-SCT compared to another treatment were included. We included only studies that used survival analysis as a part of the statistical methods. There were 14 studies included in the review. Sample size estimation was described in 4 (29 %) studies. Only 4 (29 %) studies reported the list of covariates assessed in the Cox regression and 6 (43 %) studies provided a description of censorship. All studies reported survival curves using the Kaplan-Meier method. The comparisons between groups were investigated using the log-rank test and Wilcoxon test. Crossing survival curves were observed in 11(79 %) studies. The Cox regression model was incorporated in 10 (71 %) studies. None of the studies assessed the Cox proportional hazards assumption or goodness-of-fit. The use and reporting of survival analysis in adult ALL patients undergoing allo-SCT have significant limitations. Notably, the finding of crossing survival curves was common and none of the studies assessed for the proportional hazards assumption. We encourage authors, reviewers and editors to improve the quality of the use and reporting of survival analysis in the hematology literature.

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Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Kenya 1 3%
Unknown 35 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 8 22%
Researcher 4 11%
Lecturer 3 8%
Student > Doctoral Student 3 8%
Professor 3 8%
Other 5 14%
Unknown 10 28%
Readers by discipline Count As %
Medicine and Dentistry 14 39%
Nursing and Health Professions 2 6%
Mathematics 2 6%
Social Sciences 2 6%
Decision Sciences 1 3%
Other 3 8%
Unknown 12 33%