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Predictive significance of preoperative CT findings for suboptimal cytoreduction in advanced ovarian cancer: a meta-analysis

Overview of attention for article published in Cancer Management and Research, July 2018
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Title
Predictive significance of preoperative CT findings for suboptimal cytoreduction in advanced ovarian cancer: a meta-analysis
Published in
Cancer Management and Research, July 2018
DOI 10.2147/cmar.s166658
Pubmed ID
Authors

Ting Wen Yi Hu, Dan Nie, Jin Hai Gou, Zheng Yu Li

Abstract

Computed tomography (CT) has been extensively used in predicting suboptimal cytoreduction (SCR) in advanced ovarian cancer (OC). However, disagreements remain in literatures on the predictive value of CT findings for SCR. This meta-analysis was designed to determine the ability of eight preoperative CT findings to predict SCR in advanced OC. A comprehensive literature search was conducted for eligible studies to identify the association between the eight preoperative CT findings and SCR in advanced OC. The predictive performances of preoperative CT findings were expressed in terms of sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR) and diagnostic odds ratio (DOR) with pooled proportion. A total of 10 studies and 1,614 patients were included in this meta-analysis. Large volume ascites had the highest sensitivity (64%, CI 56-71%), with a PLR of 1.3 (CI 1.1-1.5) and an NLR of 0.73 (0.59-0.90), while lymph node involvement had the highest specificity (89%, CI 79-94%). The highest DOR of 3 (CI 2-4) was achieved in peritoneal involvement and large bowel mesentery involvement. The other CT findings had poorer predictive performance. Preoperative CT findings have a poor discriminative capacity to predict SCR in advanced OC. Preoperative CT predictors should be used with caution amid clinical decision-making.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 21%
Other 2 14%
Researcher 2 14%
Student > Postgraduate 2 14%
Professor 1 7%
Other 4 29%
Readers by discipline Count As %
Medicine and Dentistry 10 71%
Linguistics 1 7%
Engineering 1 7%
Unknown 2 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 25 July 2018.
All research outputs
#10,572,698
of 13,278,410 outputs
Outputs from Cancer Management and Research
#365
of 651 outputs
Outputs of similar age
#200,517
of 268,418 outputs
Outputs of similar age from Cancer Management and Research
#33
of 51 outputs
Altmetric has tracked 13,278,410 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 651 research outputs from this source. They receive a mean Attention Score of 2.6. This one is in the 21st percentile – i.e., 21% of its peers scored the same or lower than it.
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We're also able to compare this research output to 51 others from the same source and published within six weeks on either side of this one. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.