Critical review of published microarray studies for cancer outcome and guidelines on statistical analysis and reporting
- PMID: 17227998
- DOI: 10.1093/jnci/djk018
Critical review of published microarray studies for cancer outcome and guidelines on statistical analysis and reporting
Abstract
Background: Both the validity and the reproducibility of microarray-based clinical research have been challenged. There is a need for critical review of the statistical analysis and reporting in published microarray studies that focus on cancer-related clinical outcomes.
Methods: Studies published through 2004 in which microarray-based gene expression profiles were analyzed for their relation to a clinical cancer outcome were identified through a Medline search followed by hand screening of abstracts and full text articles. Studies that were eligible for our analysis addressed one or more outcomes that were either an event occurring during follow-up, such as death or relapse, or a therapeutic response. We recorded descriptive characteristics for all the selected studies. A critical review of outcome-related statistical analyses was undertaken for the articles published in 2004.
Results: Ninety studies were identified, and their descriptive characteristics are presented. Sixty-eight (76%) were published in journals of impact factor greater than 6. A detailed account of the 42 studies (47%) published in 2004 is reported. Twenty-one (50%) of them contained at least one of the following three basic flaws: 1) in outcome-related gene finding, an unstated, unclear, or inadequate control for multiple testing; 2) in class discovery, a spurious claim of correlation between clusters and clinical outcome, made after clustering samples using a selection of outcome-related differentially expressed genes; or 3) in supervised prediction, a biased estimation of the prediction accuracy through an incorrect cross-validation procedure.
Conclusions: The most common and serious mistakes and misunderstandings recorded in published studies are described and illustrated. Based on this analysis, a proposal of guidelines for statistical analysis and reporting for clinical microarray studies, presented as a checklist of "Do's and Don'ts," is provided.
Similar articles
-
Microarray gene expression profiling for predicting complete response to preoperative chemoradiotherapy in patients with advanced rectal cancer.Dis Colon Rectum. 2007 Sep;50(9):1342-53. doi: 10.1007/s10350-007-277-7. Dis Colon Rectum. 2007. PMID: 17665260
-
Gene expression profiling on lung cancer outcome prediction: present clinical value and future premise.Cancer Epidemiol Biomarkers Prev. 2006 Nov;15(11):2063-8. doi: 10.1158/1055-9965.EPI-06-0505. Cancer Epidemiol Biomarkers Prev. 2006. PMID: 17119029 Review.
-
Evidence-based medicine, systematic reviews, and guidelines in interventional pain management: part 6. Systematic reviews and meta-analyses of observational studies.Pain Physician. 2009 Sep-Oct;12(5):819-50. Pain Physician. 2009. PMID: 19787009
-
Challenges in projecting clustering results across gene expression-profiling datasets.J Natl Cancer Inst. 2007 Nov 21;99(22):1715-23. doi: 10.1093/jnci/djm216. Epub 2007 Nov 13. J Natl Cancer Inst. 2007. PMID: 18000217
-
Statistical analysis of DNA microarray data in cancer research.Clin Cancer Res. 2006 Aug 1;12(15):4469-73. doi: 10.1158/1078-0432.CCR-06-1033. Clin Cancer Res. 2006. PMID: 16899590 Review.
Cited by
-
The prognostic landscape of genes and infiltrating immune cells across human cancers.Nat Med. 2015 Aug;21(8):938-945. doi: 10.1038/nm.3909. Epub 2015 Jul 20. Nat Med. 2015. PMID: 26193342 Free PMC article.
-
The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models.Nat Biotechnol. 2010 Aug;28(8):827-38. doi: 10.1038/nbt.1665. Epub 2010 Jul 30. Nat Biotechnol. 2010. PMID: 20676074 Free PMC article.
-
Topologically inferring active miRNA-mediated subpathways toward precise cancer classification by directed random walk.Mol Oncol. 2019 Oct;13(10):2211-2226. doi: 10.1002/1878-0261.12563. Epub 2019 Aug 27. Mol Oncol. 2019. PMID: 31408573 Free PMC article.
-
Toward understanding the informatics and statistical aspects of micro-RNA profiling.J Cardiovasc Transl Res. 2010 Jun;3(3):204-11. doi: 10.1007/s12265-010-9180-z. Epub 2010 May 4. J Cardiovasc Transl Res. 2010. PMID: 20560041 Review.
-
Epithelial-Mesenchymal Transition Markers in HCVAssociated Hepatocellular Carcinoma: A Multivariate Follow Up Study.Asian Pac J Cancer Prev. 2022 Mar 1;23(3):839-849. doi: 10.31557/APJCP.2022.23.3.839. Asian Pac J Cancer Prev. 2022. PMID: 35345355 Free PMC article.
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Other Literature Sources