Search PubMed⌕ Search

PubMed · 15515150

Assessing surrogates as trial endpoints using mixed models.

Abstract

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.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Edward L Korn, Paul S Albert, Lisa M McShane. 2005-01-30. Assessing surrogates as trial endpoints using mixed models.. https://doi.org/10.1002/sim.1779

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

KEEP EXPLORING

Related citations

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↗

Favorable response of intraommaya topotecan for leptomeningeal metastasis of neuroblastoma after intravenous route failure.

A 3-year-old male, diagnosed with stage 4 neuroblastoma, developed recurrent leptomeningeal metastasis after multi-modality treatment including multi-agent chemotherapy, surgery, high dose chemotherapy plus stem cell rescue, cis-retinoic acid and intravenous (IV) topotecan. He then received intraommaya (IO) topotecan three times weekly (maximum dose; 0.4 mg). A complete response was achieved by a resolution of malignant cells in cerebrospinal fluid and resolution leptomeningeal enhancement by brain MRI. Treatment toxicities included low-grade fever and minimal headache. The duration of treatment response from IO topotecan was 18 weeks. The survival time from CNS recurrence in this patient was 13 months. We suggest IO topotecan be considered for neoplastic meningitis of tumors with known sensitivity to topotecan.

Antineoplastic Agents↗

Mobilization of Ph chromosome-negative peripheral blood stem cells in a child with chronic myeloid leukemia after imatinib-induced complete molecular remission.

Chronic myelogenous leukemia (CML) is rare in the pediatric population. Allogeneic stem cell transplant remains the only curative therapy; however, identifying a fully matched donor is not always possible. Imatinib mesylate has been shown to induce hematologic and cytogenetic response in adults and children with CML. We describe a child who achieved molecular remission with imatinib mesylate. BCR-ABL negative peripheral blood stem cells (PBSC) were successfully collected after mobilization with filgrastim.

Antineoplastic Agents↗