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Application of ensemble clustering and survival tree analysis for identifying prognostic clinicogenomic features in patients with colorectal cancer from the 100,000 Genomes Project

Overview of attention for article published in BMC Research Notes, October 2021
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Title
Application of ensemble clustering and survival tree analysis for identifying prognostic clinicogenomic features in patients with colorectal cancer from the 100,000 Genomes Project
Published in
BMC Research Notes, October 2021
DOI 10.1186/s13104-021-05789-0
Pubmed ID
Authors

Yuguo Wei, Nikolaos Papachristou, Stefanie Mueller, Wai Hoong Chang, Alvina G. Lai

Abstract

The objective of this study was to employ ensemble clustering and tree-based risk model approaches to identify interactions between clinicogenomic features for colorectal cancer using the 100,000 Genomes Project. Among the 2211 patients with colorectal cancer (mean age of diagnosis: 67.7; 59.7% male), 16.3%, 36.3%, 39.0% and 8.4% had stage 1, 2, 3 and 4 cancers, respectively. Almost every patient had surgery (99.7%), 47.4% had chemotherapy, 7.6% had radiotherapy and 1.4% had immunotherapy. On average, tumour mutational burden (TMB) was 18 mutations/Mb and 34.4%, 31.3% and 25.7% of patients had structural or copy number mutations in KRAS, BRAF and NRAS, respectively. In the fully adjusted Cox model, patients with advanced cancer [stage 3 hazard ratio (HR)  =  3.2; p  <  0.001; stage 4 HR  =  10.2; p  <  0.001] and those who had immunotherapy (HR  =  1.8; p  <  0.04) or radiotherapy (HR  =  1.5; p  <  0.02) treatment had a higher risk of dying. The ensemble clustering approach generated four distinct clusters where patients in cluster 2 had the best survival outcomes (1-year: 98.7%; 2-year: 96.7%; 3-year: 93.0%) while patients in cluster 3 (1-year: 87.9; 2-year: 70.0%; 3-year: 53.1%) had the worst outcomes. Kaplan-Meier analysis and log rank test revealed that the clusters were separated into distinct prognostic groups (p  <  0.0001). Survival tree or recursive partitioning analyses were performed to further explore risk groups within each cluster. Among patients in cluster 2, for example, interactions between cancer stage, grade, radiotherapy, TMB, BRAF mutation status were identified. Patients with stage 4 cancer and TMB  ≥  1.6 mutations/Mb had 4 times higher risk of dying relative to the baseline hazard in that cluster.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 33%
Student > Ph. D. Student 1 11%
Unknown 5 56%
Readers by discipline Count As %
Medicine and Dentistry 2 22%
Sports and Recreations 1 11%
Biochemistry, Genetics and Molecular Biology 1 11%
Unknown 5 56%
Attention Score in Context

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 08 October 2021.
All research outputs
#20,788,175
of 25,539,438 outputs
Outputs from BMC Research Notes
#3,266
of 4,522 outputs
Outputs of similar age
#329,360
of 437,239 outputs
Outputs of similar age from BMC Research Notes
#42
of 56 outputs
Altmetric has tracked 25,539,438 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
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