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Supporting Biomarker-Driven Therapies in Oncology: A Genomic Testing Cost Calculator.
Stenzinger, Albrecht; Cuffel, Brian; Paracha, Noman; Vail, Eric; Garcia-Foncillas, Jesus; Goodman, Clifford; Lassen, Ulrik; Vassal, Gilles; Sullivan, Sean D.
Afiliação
  • Stenzinger A; Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany.
  • Cuffel B; Bayer Pharmaceuticals, Basel, Switzerland.
  • Paracha N; Bayer Pharmaceuticals, Basel, Switzerland.
  • Vail E; Department of Pathology and Laboratory Medicine, Cedars Sinai Medical Center, Los Angeles, CA, USA.
  • Garcia-Foncillas J; University Cancer Institute and the Department of Oncology, University Hospital Fundacion Jimenez Diaz, Madrid, Spain.
  • Goodman C; The Lewin Group, Inc., Falls Church, VA, USA.
  • Lassen U; Department of Oncology, Copenhagen University Hospital, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark.
  • Vassal G; Gustave Roussy Comprehensive Cancer Center, Villejuif, France.
  • Sullivan SD; CHOICE Institute, Department of Pharmacy, School of Pharmacy, University of Washington, Seattle, WA, USA.
Oncologist ; 28(5): e242-e253, 2023 05 08.
Article em En | MEDLINE | ID: mdl-36961477
ABSTRACT

BACKGROUND:

Adoption of high-throughput, gene panel-based, next-generation sequencing (NGS) into routine cancer care is widely supported, but hampered by concerns about cost. To inform policies regarding genomic testing strategies, we propose a simple metric, cost per correctly identified patient (CCIP), that compares sequential single-gene testing (SGT) vs. multiplex NGS in different tumor types. MATERIALS AND

METHODS:

A genomic testing cost calculator was developed based on clinically actionable genomic alterations identified in the European Society for Medical Oncology Scale for Clinical Actionability of molecular Targets. Using sensitivity/specificity data for SGTs (immunohistochemistry, polymerase chain reaction, and fluorescence in situ hybridization) and NGS and marker prevalence, the number needed to predict metric was monetarized to estimate CCIP.

RESULTS:

At base case, CCIP was lower with NGS than sequential SGT for advanced/metastatic non-squamous non-small cell lung cancer (NSCLC), breast, colorectal, gastric cancers, and cholangiocarcinoma. CCIP with NGS was also favorable for squamous NSCLC, pancreatic, and hepatic cancers, but with overlapping confidence intervals. CCIP favored SGT for prostate cancer. Alternate scenarios using different price estimates for each test showed similar trends, but with incremental changes in the magnitude of difference between NGS and SGT, depending on price estimates for each test.

CONCLUSIONS:

The cost to correctly identify clinically actionable genomic alterations was lower for NGS than sequential SGT in most cancer types evaluated. Decreasing price estimates for NGS and the rapid expansion of targeted therapies and accompanying biomarkers are anticipated to further support NGS as a preferred diagnostic standard for precision oncology.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Carcinoma Pulmonar de Células não Pequenas / Neoplasias Pulmonares Idioma: En Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Alemanha

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Carcinoma Pulmonar de Células não Pequenas / Neoplasias Pulmonares Idioma: En Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Alemanha