Quality appraisal of clinical validation studies for multigene prediction assays of chemotherapy response in early-stage breast cancer.

Kuderer, N. M.; Culakova, Eva; Huang, Ming‐De; Poniewierski, Marek S.; Ginsburg, G. S.; Barry, WT; Marcom, P. Kelly; Ready, N.; Abernethy, A. P.; Lyman, Gary H.

doi:10.1200/jco.2011.29.15_suppl.3082

Cited by 3 publications

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“…Information incorporated into the registry included, but was not limited to, patient demographics, drug and treatment information, radiology and surgical procedures, outpatient medications, pathology, comorbidities, and outcome measures (eg, symptoms, quality-of-life, survival). As a first step, this information was used to evaluate the ability of novel gene expression biomarkers to direct treatments and predict toxicities and recurrence or other outcomes related to lung and breast cancer (20)(21)(22). Additional ongoing studies using the registry include developing second-generation genomic biomarkers in breast cancer, identifying genomic biomarkers for chemotherapy sensitivity in lung cancer using microarray gene expression analysis, and comparing these markers to usual care.…”

Section: Infrastructurementioning

confidence: 99%

Comparative Effectiveness Research in Cancer Genomics and Precision Medicine: Current Landscape and Future Prospects

Simonds¹,

Khoury²,

Schully³

et al. 2013

JNCI Journal of the National Cancer Institute

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A major promise of genomic research is information that can transform health care and public health through earlier diagnosis, more effective prevention and treatment of disease, and avoidance of drug side effects. Although there is interest in the early adoption of emerging genomic applications in cancer prevention and treatment, there are substantial evidence gaps that are further compounded by the difficulties of designing adequately powered studies to generate this evidence, thus limiting the uptake of these tools into clinical practice. Comparative effectiveness research (CER) is intended to generate evidence on the "real-world" effectiveness compared with existing standards of care so informed decisions can be made to improve health care. Capitalizing on funding opportunities from the American Recovery and Reinvestment Act of 2009, the National Cancer Institute funded seven research teams to conduct CER in genomic and precision medicine and sponsored a workshop on CER on May 30, 2012, in Bethesda, Maryland. This report highlights research findings from those research teams, challenges to conducting CER, the barriers to implementation in clinical practice, and research priorities and opportunities in CER in genomic and precision medicine. Workshop participants strongly emphasized the need for conducting CER for promising molecularly targeted therapies, developing and supporting an integrated clinical network for open-access resources, supporting bioinformatics and computer science research, providing training and education programs in CER, and conducting research in economic and decision modeling.

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Section: Infrastructurementioning

confidence: 99%

Comparative Effectiveness Research in Cancer Genomics and Precision Medicine: Current Landscape and Future Prospects

Simonds¹,

Khoury²,

Schully³

et al. 2013

JNCI Journal of the National Cancer Institute

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show abstract

Comparative Effectiveness Research, Genomics-Enabled Personalized Medicine, and Rapid Learning Health Care: A Common Bond

Ginsburg

Kuderer

2012

JCO

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Despite stunning advances in our understanding of the genetics and the molecular basis for cancer, many patients with cancer are not yet receiving therapy tailored specifically to their tumor biology. The translation of these advances into clinical practice has been hindered, in part, by the lack of evidence for biomarkers supporting the personalized medicine approach. Most stakeholders agree that the translation of biomarkers into clinical care requires evidence of clinical utility. The highest level of evidence comes from randomized controlled clinical trials (RCTs). However, in many instances, there may be no RCTs that are feasible for assessing the clinical utility of potentially valuable genomic biomarkers. In the absence of RCTs, evidence generation will require well-designed cohort studies for comparative effectiveness research (CER) that link detailed clinical information to tumor biology and genomic data. CER also uses systematic reviews, evidence-quality appraisal, and health outcomes research to provide a methodologic framework for assessing biologic patient subgroups. Rapid learning health care (RLHC) is a model in which diverse data are made available, ideally in a robust and real-time fashion, potentially facilitating CER and personalized medicine. Nonetheless, to realize the full potential of personalized care using RLHC requires advances in CER and biostatistics methodology and the development of interoperable informatics systems, which has been recognized by the National Cancer Institute's program for CER and personalized medicine. The integration of CER methodology and genomics linked to RLHC should enhance, expedite, and expand the evidence generation required for fully realizing personalized cancer care.

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Special Series on Comparative Effectiveness Research: Challenges to Real-World Solutions to Quality Improvement in Personalized Medicine

Browman

2012

JCO

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Quality appraisal of clinical validation studies for multigene prediction assays of chemotherapy response in early-stage breast cancer.

Cited by 3 publications

References 0 publications

Comparative Effectiveness Research in Cancer Genomics and Precision Medicine: Current Landscape and Future Prospects

Comparative Effectiveness Research in Cancer Genomics and Precision Medicine: Current Landscape and Future Prospects

Comparative Effectiveness Research, Genomics-Enabled Personalized Medicine, and Rapid Learning Health Care: A Common Bond

Special Series on Comparative Effectiveness Research: Challenges to Real-World Solutions to Quality Improvement in Personalized Medicine

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