ArticleClinical cancer research : an official journal of the American Association for Cancer Research2012
Developing and validating continuous genomic signatures in randomized clinical trials for predictive medicine.
Article in Clinical cancer research : an official journal of the American Association for Cancer Research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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The trial behind it
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Who cites it
14 citing papers in PubMed.
- Genomic signatures define three subtypes of EGFR-mutant stage II-III non-small-cell lung cancer with distinct adjuvant therapy outcomes.Nature communications · 2021Trial
- Robust estimation of the expected survival probabilities from high-dimensional Cox models with biomarker-by-treatment interactions in randomized clinical trials.BMC medical research methodology · 2017Trial
- Developing a predictive signature for two trial endpoints using the cross-validated risk scores method.Biostatistics (Oxford, England) · 2023Article
- Transcriptomic signature defines two subtypes of locally advanced PCa with distinct neoadjuvant therapy benefits.Frontiers in oncology · 2023Article
- Innovative trial approaches in immune-mediated inflammatory diseases: current use and future potential.BMC rheumatology · 2021Article
- High Serine-arginine Protein Kinase 1 Expression with PTEN Loss Defines Aggressive Phenotype of Prostate Cancer Associated with Lethal Outcome and Decreased Overall Survival.European urology open science · 2021Article
- Developing and testing high-efficacy patient subgroups within a clinical trial using risk scores.Statistics in medicine · 2020Article
- Combined loss of TFF3 and PTEN is associated with lethal outcome and overall survival in men with prostate cancer.Journal of cancer research and clinical oncology · 2019Article
- Clinical utility of assessing PTEN and ERG protein expression in prostate cancer patients: a proposed method for risk stratification.Journal of cancer research and clinical oncology · 2018Article
- Statistical controversies in clinical research: prognostic gene signatures are not (yet) useful in clinical practice.Annals of oncology : official journal of the European Society for Medical Oncology · 2016Review
- An NGS Workflow Blueprint for DNA Sequencing Data and Its Application in Individualized Molecular Oncology.Cancer informatics · 2015Review
- Drug-diagnostics co-development in oncology.Frontiers in oncology · 2013Review
- Impact of bioinformatic procedures in the development and translation of high-throughput molecular classifiers in oncology.Clinical cancer research : an official journal of the American Association for Cancer Research · 2013Review
- Genomic biomarkers for personalized medicine: development and validation in clinical studies.Computational and mathematical methods in medicine · 2013Review
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
purposeIt is highly challenging to develop reliable diagnostic tests to predict patients' responsiveness to anticancer treatments on clinical endpoints before commencing the definitive phase III randomized trial. Development and validation of genomic signatures in the randomized trial can be a promising solution. Such signatures are required to predict quantitatively the underlying heterogeneity in the magnitude of treatment effects. EXPERIMENTAL
designWe propose a framework for developing and validating genomic signatures in randomized trials. Codevelopment of predictive and prognostic signatures can allow prediction of patient-level survival curves as basic diagnostic tools for treating individual patients.
resultsWe applied our framework to gene-expression microarray data from a large-scale randomized trial to determine whether the addition of thalidomide improves survival for patients with multiple myeloma. The results indicated that approximately half of the patients were responsive to thalidomide, and the average improvement in survival for the responsive patients was statistically significant. Cross-validated patient-level survival curves were developed to predict survival distributions of individual future patients as a function of whether or not they are treated with thalidomide and with regard to their baseline prognostic and predictive signature indices.
conclusionThe proposed framework represents an important step toward reliable predictive medicine. It provides an internally validated mechanism for using randomized clinical trials to assess treatment efficacy for a patient population in a manner that takes into consideration the heterogeneity in patients' responsiveness to treatment. It also provides cross-validated patient-level survival curves that can be used for selecting treatments for future patients.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.