PubMed Health⌕ Search

Biomedical subjects

Edward L Korn

Publications and source records attributed to Edward L Korn.

At least 19 recordsLinked to original sources
PubMed2007

Stage-specific alterations of the genome, transcriptome, and proteome during colorectal carcinogenesis.

To identify sequential alterations of the genome, transcriptome, and proteome during colorectal cancer progression, we have analyzed tissue samples from 36 patients, including the complete mucosa-adenoma-carcinoma sequence from 8 patients. Comparative genomic hybridization (CGH) revealed patterns of stage specific, recurrent genomic imbalances. Gene expression analysis on 9K cDNA arrays identified 58 genes differentially expressed between normal mucosa and adenoma, 116 genes between adenoma and carcinoma, and 158 genes between primary carcinoma and liver metastasis (P < 0.001). Parallel analysis of our samples by CGH and expression profiling revealed a direct correlation of chromosomal copy number changes with chromosome-specific average gene expression levels. Protein expression was analyzed by two-dimensional gel electrophoresis and subsequent mass spectrometry. Although there was no direct match of differentially expressed proteins and genes, the majority of them belonged to identical pathways or networks. In conclusion, increasing genomic instability and a recurrent pattern of chromosomal imbalances as well as specific gene and protein expression changes correlate with distinct stages of colorectal cancer progression. Chromosomal aneuploidies directly affect average resident gene expression levels, thereby contributing to a massive deregulation of the cellular transcriptome. The identification of novel genes and proteins might deliver molecular targets for diagnostic and therapeutic interventions.

Adult↗
PubMed2006

Conditional power calculations for clinical trials with historical controls.

A trial of a new therapy is to be compared to results from a previous trial of patients treated with a standard therapy. For a given sample size for the trial of the new therapy, we desire the power, against a specific alternative hypothesis, for the hypothesis test of the null hypothesis that the therapies are equivalent. Alternatively, the sample size required for the trial of the new therapy is needed for a target power. We explain why a popular method for doing these calculations is wrong, and discuss alternative methods in the context of normal outcomes, binary outcomes, and time-to-event outcomes.

Clinical Trials as Topic↗
PubMed2006

The likelihood as statistical evidence in multiple comparisons in clinical trials: no free lunch.

The likelihood ratio summarizes the strength of statistical evidence for one simple pre-determined hypothesis versus another. However, it does not directly address the multiple comparisons problem. In this paper we discuss some concerns related to the application of likelihood ratio methods to several multiple comparisons issues in clinical trials, in particular, subgroup analysis, multiple variables, interim monitoring, and data driven choice of hypotheses.

Artificial Intelligence↗
PubMed2005

Design issues of randomized phase II trials and a proposal for phase II screening trials.

Future progress in improving cancer therapy can be expedited by better prioritization of new treatments for phase III evaluation. Historically, phase II trials have been key components in the prioritization process. There has been a long-standing interest in using phase II trials with randomization against a standard-treatment control arm or an additional experimental arm to provide greater assurance than afforded by comparison to historic controls that the new agent or regimen is promising and warrants further evaluation. Relevant trial designs that have been developed and utilized include phase II selection designs, randomized phase II designs that include a reference standard-treatment control arm, and phase II/III designs. We present our own explorations into the possibilities of developing "phase II screening trials," in which preliminary and nondefinitive randomized comparisons of experimental regimens to standard treatments are made (preferably using an intermediate end point) by carefully adjusting the false-positive error rates (alpha or type I error) and false-negative error rates (beta or type II error), so that the targeted treatment benefit may be appropriate while the sample size remains restricted. If the ability to conduct a definitive phase III trial can be protected, and if investigators feel that by judicious choice of false-positive probability and false-negative probability and magnitude of targeted treatment effect they can appropriately balance the conflicting demands of screening out useless regimens versus reliably detecting useful ones, the phase II screening trial design may be appropriate to apply.

Clinical Trials, Phase II as Topic↗
PubMed2005

Dose escalation trial designs based on a molecularly targeted endpoint.

Traditional phase I dose-finding studies for chemotoxic agents base dose escalation on toxicity, with escalation continuing until unacceptable toxicity is observed. Recent development of molecularly targeted agents that have little or no toxicity in the therapeutic dose range has raised questions over the best study designs for phase I studies. Two types of designs are proposed and evaluated in this paper. In these designs, escalation is based on a binary response that indicates whether or not the agent has had the desired effect on the molecular target. One design is developed to ensure that if the true target response rate is low there will be a high probability of escalating and if the true target response rate is high there will be a low probability of escalating. The other design is developed to continue to escalate as long as the true response rate is increasing and to stop escalating when the response rate plateaus or decreases. A limited simulation study is performed and the designs are compared with respect to the dose level at the end of escalation and the number of patients treated on study.

Clinical Trials, Phase I as Topic↗
PubMed2005

Preliminary data release for randomized clinical trials of noninferiority: a new proposal.

Noninferiority trials often require a long follow-up period for the data to reach the maturity needed for definitive analysis. A proposal is presented that allows for early release of outcome data from a carefully specified subset of noninferiority trials. This subset is defined so that the early release of the data will be potentially useful to patients who face a treatment decision but will not compromise the integrity of the trial or interfere with the completion of the trial to its definitive analysis. In particular, the release of the data will only occur after the last participant has been randomly assigned and is off treatment-arm-specific therapy and only if it is unlikely that subsequent treatment and/or follow-up practices will change based on the knowledge of released data. In contrast to standard interim monitoring, (1) the release of the data would be automatic and independent of the observed data, and (2) the trial would continue on to its planned final analysis and not be stopped. Examples are given demonstrating how the proposal would work, along with a discussion of possible objections to the proposal.

Clinical Trials Data Monitoring Committees↗
PubMed2005

Testing treatment effects in the presence of competing risks.

Competing risks are often encountered in clinical research. In the presence of multiple failure types, the time to the first failure of any type is typically used as an overall measure of the clinical impact for the patients. On the other hand, use of endpoints based on the type of failure directly related to the treatment mechanism of action allows one to focus on the aspect of the disease targeted by treatment. We review the methodology commonly used for testing failure specific treatment effects. Simulation results demonstrate that the cause-specific log-rank test is robust (in the sense of preserving the nominal level of the test) and has good power properties for testing for differences in the marginal latent failure-time distributions, whereas the use of a popular cumulative incidence based approach may be problematic for this aim.

Computer Simulation↗
PubMed2005

Assessing surrogates as trial endpoints using mixed models.

Having a surrogate for a definitive endpoint in a clinical trial can sometimes be useful when it is impractical, invasive or very time consuming to obtain the definitive endpoint. This paper discusses methods for assessing whether the surrogate-endpoint results of a trial can be used in place of definitive-endpoint results. It is important when examining this trial-level surrogacy to include the possibility of trial-level effects and to distinguish whether the treatment arms are naturally ordered, e.g. A vs A+B rather than A vs B. Methods using mixed models of trial-level summaries are discussed and compared to fixed-effects models and to the possibility of using models of individual-level data. We give estimators for definitive-endpoint results of a trial that are predicted from the surrogate-endpoint results of the trial and a set of results from previous trials in which both the definitive and surrogate trial results were available. Graphical displays are also suggested. Two sets of trial results previously analysed for trial-level surrogacy are used as examples.

Antineoplastic Agents↗
PubMed2005

Randomized, placebo-controlled, esophageal squamous cell cancer chemoprevention trial of selenomethionine and celecoxib.

BACKGROUND & AIMS: Esophageal squamous cell carcinoma remains a leading cause of cancer death worldwide. Squamous dysplasia, the accepted histological precursor for esophageal squamous cell carcinoma, represents a potentially modifiable intermediate end point for chemoprevention trials in high-risk populations. METHODS: We conducted a randomized, controlled trial of selenomethionine 200 microg daily and/or celecoxib 200 mg twice daily (2 x 2 factorial design) among residents of Linxian, People's Republic of China. Subjects had histologically confirmed mild or moderate esophageal squamous dysplasia at baseline. Esophagogastroduodenoscopy was performed before and after a 10-month intervention. Per-subject change (regression, stable, or progression) in the worst dysplasia grade was defined as the primary end point. Results were compared by agent group (selenomethionine vs placebo; celecoxib vs placebo). RESULTS: Two hundred sixty-seven subjects fulfilled all eligibility criteria, and 238 (89%) completed the trial. Overall, selenomethionine resulted in a trend toward increased dysplasia regression (43% vs 32%) and decreased dysplasia progression (14% vs 19%) compared with no selenomethionine (P = .08). In unplanned stratified analyses, selenomethionine favorably affected a change in dysplasia grade among 115 subjects with mild esophageal squamous dysplasia at baseline (P = .02), but not among 123 subjects with moderate esophageal squamous dysplasia at baseline (P = 1.00). Celecoxib status did not influence changes in dysplasia grade overall (P = .78) or by baseline histology subgroup. CONCLUSIONS: After a 10-month intervention, neither selenomethionine nor celecoxib inhibited esophageal squamous carcinogenesis for all high-risk subjects. However, among subjects with mild esophageal squamous dysplasia at baseline, selenomethionine did have a protective effect. Although it is based on unplanned stratified analyses, this finding is the first report of a possible beneficial effect for any candidate esophageal squamous cell carcinoma chemopreventive agent in a randomized controlled trial.

Adult↗
PubMed2004

Chromosome transfer induced aneuploidy results in complex dysregulation of the cellular transcriptome in immortalized and cancer cells.

Chromosomal aneuploidies are observed in essentially all sporadic carcinomas. These aneuploidies result in tumor-specific patterns of genomic imbalances that are acquired early during tumorigenesis, continuously selected for and faithfully maintained in cancer cells. Although the paradigm of translocation induced oncogene activation in hematologic malignancies is firmly established, it is not known how genomic imbalances affect chromosome-specific gene expression patterns in particular and how chromosomal aneuploidy dysregulates the genetic equilibrium of cells in general. To model specific chromosomal aneuploidies in cancer cells and dissect the immediate consequences of genomic imbalances on the transcriptome, we generated artificial trisomies in a karyotypically stable diploid yet mismatch repair-deficient, colorectal cancer cell line and in telomerase immortalized, cytogenetically normal human breast epithelial cells using microcell-mediated chromosome transfer. The global consequences on gene expression levels were analyzed using cDNA arrays. Our results show that regardless of chromosome or cell type, chromosomal trisomies result in a significant increase in the average transcriptional activity of the trisomic chromosome. This increase affects the expression of numerous genes on other chromosomes as well. We therefore postulate that the genomic imbalances observed in cancer cells exert their effect through a complex pattern of transcriptional dysregulation.

Aneuploidy↗
PubMed2004

Strength of accumulating evidence and data monitoring committee decision making.

The data monitoring committee (DMC) is a vital component of a randomized clinical trial. Its responsibilities include stopping the trial early for extreme results. The decision to stop the trial must be based on a careful synthesis of statistical methodology and clinical judgment. It is critical to ensure the validity of this complex process. In this paper we present results of a survey of 21 DMC members conducted to investigate how they evaluate accumulating evidence. The results indicate that some DMC members may be over-interpreting developing trends in the data.

Antineoplastic Agents↗
PubMed2004

Correcting log ratios for signal saturation in cDNA microarrays.

MOTIVATION: Pixel saturation occurs when the pixel intensity exceeds a threshold and the recorded pixel intensity is truncated. Microarray experiments are commonly afflicted with saturated pixels. As a result, estimators of gene expression are biased, with the amount of bias increasing as a function of the proportion of pixels saturated. Saturation is directly related to the photomultiplier tube (PMT) voltage settings and RNA abundance and is not necessarily associated with poor array or poor spot quality. When choosing PMT settings, higher PMT settings are desired because of improved signal-to-noise ratios of low-intensity spots. This improved signal is somewhat offset by saturation of high-intensity spots. In practice, spots with saturated pixels are discarded or the biased value is used. Neither of these approaches is appealing, particularly the former approach when a highly expressed gene is discarded because of saturation. RESULTS: We present a method to correct for saturation using pixel-level data. The method is based on a censored regression model. Evaluations on several arrays indicate that the method performs well. Simulation studies suggest that the method is robust under certain model violations.

Algorithms↗
PubMed2004

Objective method of comparing DNA microarray image analysis systems.

Many image analysis systems are available for processing the images produced by laser scanning of DNA microarrays. The image processing system takes pixel-level intensity data and converts it to a set of gene-level expression or copy number summaries that will be used in further analyses. Image analysis systems currently in use differ with regard to the specific algorithms they implement, ease of use, and cost. Thus, it would be desirable to have an objective means of comparing systems. Here we describe a systematic method of comparing image processing results produced by different image analysis systems using a series of replicate microarray experiments. We demonstrate the method with a comparison of cDNA microarray data generated by the UCSF Spot and the GenePix image processing systems.

Algorithms↗
PubMed2003

Breast cancer classification and prognosis based on gene expression profiles from a population-based study.

Comprehensive gene expression patterns generated from cDNA microarrays were correlated with detailed clinico-pathological characteristics and clinical outcome in an unselected group of 99 node-negative and node-positive breast cancer patients. Gene expression patterns were found to be strongly associated with estrogen receptor (ER) status and moderately associated with grade, but not associated with menopausal status, nodal status, or tumor size. Hierarchical cluster analysis segregated the tumors into two main groups based on their ER status, which correlated well with basal and luminal characteristics. Cox proportional hazards regression analysis identified 16 genes that were significantly associated with relapse-free survival at a stringent significance level of 0.001 to account for multiple comparisons. Of 231 genes previously reported by others [van't Veer, L. J., et al. (2002) Nature 415, 530-536] as being associated with survival, 93 probe elements overlapped with the set of 7,650 probe elements represented on the arrays used in this study. Hierarchical cluster analysis based on the set of 93 probe elements segregated our population into two distinct subgroups with different relapse-free survival (P < 0.03). The number of these 93 probe elements showing significant univariate association with relapse-free survival (P < 0.05) in the present study was 14, representing 11 unique genes. Genes involved in cell cycle, DNA replication, and chromosomal stability were consistently elevated in the various poor prognostic groups. In addition, glutathione S-transferase M3 emerged as an important survival marker in both studies. When taken together with other array studies, our results highlight the consistent biological and clinical associations with gene expression profiles.

Breast Neoplasms↗