Bivariate sequential designs for phase II trials.

M R Conaway; G R Petroni

Home/Archive/PubMed

PubMed · 7662852

Bivariate sequential designs for phase II trials.

M R Conaway·G R Petroni

View original source ↗Export metadata ↓

Abstract

In this paper we propose methods for designing group sequential phase II trials with two dependent binary endpoints. The emphasis is on the derivation of stopping rules for phase II trials which require the enrollment of a small number of patients. The methods are based on enumerating the exact distribution for the binary endpoints. We illustrate the methods with a recent study which required the use of group sequential design to monitor antitumor activity and toxicity.

Explore related subjects

Antineoplastic Agents Anus Neoplasms Clinical Trials, Phase II as Topic Humans Mathematics Models, Statistical Multicenter Studies as Topic Neoplasms Odds Ratio Postoperative Complications Research Design Journal Article Research Support, U.S. Gov't, P.H.S.

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

M R Conaway, G R Petroni. 1995. Bivariate sequential designs for phase II trials.. https://pubmed.ncbi.nlm.nih.gov/7662852/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2021

Deep generative neural network for accurate drug response imputation.

Drug response differs substantially in cancer patients due to inter- and intra-tumor heterogeneity. Particularly, transcriptome context, especially tumor microenvironment, has been shown playing a significant role in shaping the actual treatment outcome. In this study, we develop a deep variational autoencoder (VAE) model to compress thousands of genes into latent vectors in a low-dimensional space. We then demonstrate that these encoded vectors could accurately impute drug response, outperform standard signature-gene based approaches, and appropriately control the overfitting problem. We apply rigorous quality assessment and validation, including assessing the impact of cell line lineage, cross-validation, cross-panel evaluation, and application in independent clinical data sets, to warrant the accuracy of the imputed drug response in both cell lines and cancer samples. Specifically, the expression-regulated component (EReX) of the observed drug response achieves high correlation across panels. Using the well-trained models, we impute drug response of The Cancer Genome Atlas data and investigate the features and signatures associated with the imputed drug response, including cell line origins, somatic mutations and tumor mutation burdens, tumor microenvironment, and confounding factors. In summary, our deep learning method and the results are useful for the study of signatures and markers of drug response.

Antineoplastic Agents↗

PubMed1996

Selective effects of DNA damaging agents on HIV long terminal repeat activation and virus replication in vitro.

Much attention has recently focused on the observation that UV light can activate the long terminal repeat (LTR) of the human immunodeficiency virus (HIV). Although the mechanism of LTR activation remains obscure, several lines of investigation have suggested that it is a result of activation of the NF-kappa B transcription factor(s) following signaling events related to generalized DNA damage. In this report, we present data demonstrating that HIV LTR activation is not a general consequence of cellular DNA damage, but rather a process unique to specific genotoxic stimuli, and that it does not necessarily depend on activation of NF-kappa B. Furthermore, we demonstrate that several of these agents can significantly increase HIV replication and accelerate CD4-positive lymphocyte cytotoxicity in vitro. These findings, therefore, could have clinical significance to AIDS patients with malignancies who are undergoing radiotherapy and chemotherapy.

Antineoplastic Agents↗

PubMed1996

Antiproliferative responses to two human colon cancer cell lines to vitamin D3 are differently modified by 9-cis-retinoic acid.

1 alpha,25-Dihydroxyvitamin D3 [1,25(OH)2D3] exerts antiproliferative actions in colorectal cancer, but their underlying molecular mechanisms have not been determined. 1,25(OH)2D3 regulates target gene transcription via a specific nuclear vitamin D receptor (VDR), which mediates hormone action preferentially as a heterodimer with 9-cis-retinoic acid receptors (RXRs). We investigated the actions of 1,25(OH)2D3 and 9-cis-retinoic acid (RA) in two human colon cancer cell lines, HT-29 and Caco-2. Both expressed mRNAs encoding VDR, RXR alpha, and RXR gamma, and VDR was regulated posttranscriptionally in Caco-2 cells. There was an antiproliferative response of both cell lines to 1,25(OH)2D3. 9-cis-RA exerted antiproliferative effects on Caco-2 cells but blocked 1,25(OH)2D3 actions in HT-29 cells. The 1,25(OH)2D3-responsive gene 25-hydroxyvitamin D3 24-hydroxylase was induced in both cell lines b 1,25(OH)2D3 but in only HT-29 cells by 9-cis-RA. 1,25(OH)2D3 and 9-cis-RA cotreatment enhanced 24-hydroxylase expression in HT-29 cells only. The 24-hydroxylase enzyme is known to result in catabolism of 1,25(OH)2D3 and attenuation of its actions. Increased 24-hydroxylase activity in HT-29 cells, but not in Caco-2 cells, in response to 9-cis-RA may account for some of the complex cell-specific responses demonstrated in these studies.

Antineoplastic Agents↗