Low-Dose Aspirin Use After Diagnosis of Colorectal Cancer Does Not Increase Survival: A Case–Control Analysis of a Population-Based Cohort

BACKGROUND & AIMS: Individuals who began taking low-dose aspirin before they were diagnosed with colorectal cancer were reported to have longer survival times than patients who did not take this drug. We investigated survival times of patients who begin taking low-dose aspirin after a diagnosis of colorectal cancer in a large population-based cohort study.

METHODS: We performed a nested case-control analysis using a cohort of 4794 patients diagnosed with colorectal cancer from 1998 through 2007, identified from the UK Clinical Practice Research Datalink and confirmed by cancer registries. There were 1559 colorectal cancer-specific deaths, recorded by the Office of National Statistics; these were each matched with up to 5 risk-set controls. Conditional logistic regression was used to calculate odds ratios (OR) and 95% confidence intervals (CI), based on practitioner-recorded aspirin usage.

RESULTS: Overall, low-dose aspirin use after a diagnosis of colorectal cancer was not associated with colorectal cancer-specific mortality (adjusted OR = 1.06; 95% CI: 0.92-1.24) or all-cause mortality (adjusted OR = 1.06; 95% CI: 0.94-1.19). A dose-response association was not apparent; for example, low-dose aspirin use for more than 1 year after diagnosis was not associated with colorectal cancer-specific mortality (adjusted OR = 0.98; 95% CI: 0.82-1.19). There was also no association between low-dose aspirin usage and colon cancer-specific mortality (adjusted OR = 1.02; 95% CI: 0.83-1.25) or rectal cancer-specific mortality (adjusted OR = 1.10; 95% CI: 0.88-1.38).

CONCLUSIONS: In a large population-based cohort, low-dose aspirin usage after diagnosis of colorectal cancer did not increase survival time.

samExploreR: exploring reproducibility and robustness of RNA-seq results based on SAM files

MOTIVATION: Data from RNA-seq experiments provide us with many new possibilities to gain insights into biological and disease mechanisms of cellular functioning. However, the reproducibility and robustness of RNA-seq data analysis results is often unclear. This is in part attributed to the two counter acting goals of (a) a cost efficient and (b) an optimal experimental design leading to a compromise, e.g., in the sequencing depth of experiments.

RESULTS: We introduce an R package called samExploreR that allows the subsampling (m out of n bootstraping) of short-reads based on SAM files facilitating the investigation of sequencing depth related questions for the experimental design. Overall, this provides a systematic way for exploring the reproducibility and robustness of general RNA-seq studies. We exemplify the usage of samExploreR by studying the influence of the sequencing depth and the annotation on the identification of differentially expressed genes.

AVAILABILITY: Availability: samExploreR is available as an R package from Bioconductor (after acceptance of the paper, download link: http://www.bio-complexity.com/samExploreR_1.0.0.tar.gz).