Sequential interim analyses of survival data in DNA microarray experiments. 2011

Andreas Leha, and Tim Beissbarth, and Klaus Jung
Department of Medical Statistics, University Medical Center Göttingen, D-37099 Göttingen, Germany.

BACKGROUND Discovery of biomarkers that are correlated with therapy response and thus with survival is an important goal of medical research on severe diseases, e.g. cancer. Frequently, microarray studies are performed to identify genes of which the expression levels in pretherapeutic tissue samples are correlated to survival times of patients. Typically, such a study can take several years until the full planned sample size is available.Therefore, interim analyses are desirable, offering the possibility of stopping the study earlier, or of performing additional laboratory experiments to validate the role of the detected genes. While many methods correcting the multiple testing bias introduced by interim analyses have been proposed for studies of one single feature, there are still open questions about interim analyses of multiple features, particularly of high-dimensional microarray data, where the number of features clearly exceeds the number of samples. Therefore, we examine false discovery rates and power rates in microarray experiments performed during interim analyses of survival studies. In addition, the early stopping based on interim results of such studies is evaluated. As stop criterion we employ the achieved average power rate, i.e. the proportion of detected true positives, for which a new estimator is derived and compared to existing estimators. RESULTS In a simulation study, pre-specified levels of the false discovery rate are maintained in each interim analysis, where reduced levels as used in classical group sequential designs of one single feature are not necessary. Average power rates increase with each interim analysis, and many studies can be stopped prior to their planned end when a certain pre-specified power rate is achieved. The new estimator for the power rate slightly deviates from the true power rate but is comparable to other estimators. CONCLUSIONS Interim analyses of microarray experiments can provide evidence for early stopping of long-term survival studies. The developed simulation framework, which we also offer as a new R package 'SurvGenesInterim' available at http://survgenesinter.R-Forge.R-Project.org, can be used for sample size planning of the evaluated study design.

UI MeSH Term Description Entries
D012107 Research Design A plan for collecting and utilizing data so that desired information can be obtained with sufficient precision or so that an hypothesis can be tested properly. Experimental Design,Data Adjustment,Data Reporting,Design, Experimental,Designs, Experimental,Error Sources,Experimental Designs,Matched Groups,Methodology, Research,Problem Formulation,Research Methodology,Research Proposal,Research Strategy,Research Technics,Research Techniques,Scoring Methods,Adjustment, Data,Adjustments, Data,Data Adjustments,Design, Research,Designs, Research,Error Source,Formulation, Problem,Formulations, Problem,Group, Matched,Groups, Matched,Matched Group,Method, Scoring,Methods, Scoring,Problem Formulations,Proposal, Research,Proposals, Research,Reporting, Data,Research Designs,Research Proposals,Research Strategies,Research Technic,Research Technique,Scoring Method,Source, Error,Sources, Error,Strategies, Research,Strategy, Research,Technic, Research,Technics, Research,Technique, Research,Techniques, Research
D001943 Breast Neoplasms Tumors or cancer of the human BREAST. Breast Cancer,Breast Tumors,Cancer of Breast,Breast Carcinoma,Cancer of the Breast,Human Mammary Carcinoma,Malignant Neoplasm of Breast,Malignant Tumor of Breast,Mammary Cancer,Mammary Carcinoma, Human,Mammary Neoplasm, Human,Mammary Neoplasms, Human,Neoplasms, Breast,Tumors, Breast,Breast Carcinomas,Breast Malignant Neoplasm,Breast Malignant Neoplasms,Breast Malignant Tumor,Breast Malignant Tumors,Breast Neoplasm,Breast Tumor,Cancer, Breast,Cancer, Mammary,Cancers, Mammary,Carcinoma, Breast,Carcinoma, Human Mammary,Carcinomas, Breast,Carcinomas, Human Mammary,Human Mammary Carcinomas,Human Mammary Neoplasm,Human Mammary Neoplasms,Mammary Cancers,Mammary Carcinomas, Human,Neoplasm, Breast,Neoplasm, Human Mammary,Neoplasms, Human Mammary,Tumor, Breast
D003198 Computer Simulation Computer-based representation of physical systems and phenomena such as chemical processes. Computational Modeling,Computational Modelling,Computer Models,In silico Modeling,In silico Models,In silico Simulation,Models, Computer,Computerized Models,Computer Model,Computer Simulations,Computerized Model,In silico Model,Model, Computer,Model, Computerized,Model, In silico,Modeling, Computational,Modeling, In silico,Modelling, Computational,Simulation, Computer,Simulation, In silico,Simulations, Computer
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D013997 Time Factors Elements of limited time intervals, contributing to particular results or situations. Time Series,Factor, Time,Time Factor
D016019 Survival Analysis A class of statistical procedures for estimating the survival function (function of time, starting with a population 100% well at a given time and providing the percentage of the population still well at later times). The survival analysis is then used for making inferences about the effects of treatments, prognostic factors, exposures, and other covariates on the function. Analysis, Survival,Analyses, Survival,Survival Analyses
D018401 Sample Size The number of units (persons, animals, patients, specified circumstances, etc.) in a population to be studied. The sample size should be big enough to have a high likelihood of detecting a true difference between two groups. (From Wassertheil-Smoller, Biostatistics and Epidemiology, 1990, p95) Sample Sizes,Size, Sample,Sizes, Sample
D020411 Oligonucleotide Array Sequence Analysis Hybridization of a nucleic acid sample to a very large set of OLIGONUCLEOTIDE PROBES, which have been attached individually in columns and rows to a solid support, to determine a BASE SEQUENCE, or to detect variations in a gene sequence, GENE EXPRESSION, or for GENE MAPPING. DNA Microarrays,Gene Expression Microarray Analysis,Oligonucleotide Arrays,cDNA Microarrays,DNA Arrays,DNA Chips,DNA Microchips,Gene Chips,Oligodeoxyribonucleotide Array Sequence Analysis,Oligonucleotide Microarrays,Sequence Analysis, Oligonucleotide Array,cDNA Arrays,Array, DNA,Array, Oligonucleotide,Array, cDNA,Arrays, DNA,Arrays, Oligonucleotide,Arrays, cDNA,Chip, DNA,Chip, Gene,Chips, DNA,Chips, Gene,DNA Array,DNA Chip,DNA Microarray,DNA Microchip,Gene Chip,Microarray, DNA,Microarray, Oligonucleotide,Microarray, cDNA,Microarrays, DNA,Microarrays, Oligonucleotide,Microarrays, cDNA,Microchip, DNA,Microchips, DNA,Oligonucleotide Array,Oligonucleotide Microarray,cDNA Array,cDNA Microarray

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