Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 3 de 3
Filtrar
1.
Tumour Biol ; 43(1): 115-127, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-34219680

RESUMEN

BACKGROUND: The widespread introduction of immunotherapy in patients with advanced non-small cell lung cancer (NSCLC) has led to durable responses but still many patients fail and are treated beyond progression. OBJECTIVE: This study investigated whether readily available blood-based tumor biomarkers allow accurate detection of early non-responsiveness, allowing a timely switch of therapy and cost reduction. METHODS: In a prospective, observational study in patients with NSCLC treated with nivolumab or pembrolizumab, five serum tumor markers were measured at baseline and every other week. Six months disease control as determined by RECIST was used as a measure of clinical response. Patients with a disease control <  6 months were deemed non-responsive. For every separate tumor marker a criterion for predicting of non-response was developed. Each marker test was defined as positive (predictive of non-response) if the value of that tumor marker increased at least 50% from the value at baseline and above a marker dependent minimum value to be determined. Also, tests based on combination of multiple markers were designed. Specificity and sensitivity for predicting non-response was calculated and results were validated in an independent cohort. The target specificity of the test for detecting non-response was set at >  95%, in order to allow its safe use for treatment decisions. RESULTS: A total of 376 patients (training cohort: 180, validation cohort: 196) were included in our analysis. Results for the specificity of the single marker tests in the validation set were CEA: 98·3% (95% CI: 90·9-100%), NSE: 96·5% (95% CI: 87·9-99·6%), SCC: 96·5% (95% CI: 88·1-99·6%), Cyfra21·1 : 91.8% (95% CI: 81·9-97·3%), and CA125 : 86·0% (95% CI: 74·2-93·7%). A test based on the combination of Cyfra21.1, CEA and NSE accurately predicted non-response in 32.3% (95% CI 22.6-43.1%) of patients 6 weeks after start of immunotherapy. Survival analysis showed a significant difference between predicted responders (Median PFS: 237 days (95% CI 184-289 days)) and non-responders (Median PFS: 58 days (95% CI 46-70 days)) (p <  0.001). CONCLUSIONS: Serum tumor marker based tests can be used for accurate detection of non-response in NSCLC, thereby allowing early and safe discontinuation of immunotherapy in a significant subset of patients.


Asunto(s)
Protocolos de Quimioterapia Combinada Antineoplásica/uso terapéutico , Biomarcadores de Tumor/sangre , Carcinoma de Pulmón de Células no Pequeñas/patología , Inmunoterapia/mortalidad , Neoplasias Pulmonares/patología , Anticuerpos Monoclonales Humanizados/administración & dosificación , Carcinoma de Pulmón de Células no Pequeñas/sangre , Carcinoma de Pulmón de Células no Pequeñas/tratamiento farmacológico , Técnicas de Apoyo para la Decisión , Femenino , Estudios de Seguimiento , Humanos , Neoplasias Pulmonares/sangre , Neoplasias Pulmonares/tratamiento farmacológico , Masculino , Persona de Mediana Edad , Nivolumab/administración & dosificación , Pronóstico , Estudios Prospectivos , Tasa de Supervivencia
2.
Hum Mutat ; 40(12): 2230-2238, 2019 12.
Artículo en Inglés | MEDLINE | ID: mdl-31433103

RESUMEN

Each year diagnostic laboratories in the Netherlands profile thousands of individuals for heritable disease using next-generation sequencing (NGS). This requires pathogenicity classification of millions of DNA variants on the standard 5-tier scale. To reduce time spent on data interpretation and increase data quality and reliability, the nine Dutch labs decided to publicly share their classifications. Variant classifications of nearly 100,000 unique variants were catalogued and compared in a centralized MOLGENIS database. Variants classified by more than one center were labeled as "consensus" when classifications agreed, and shared internationally with LOVD and ClinVar. When classifications opposed (LB/B vs. LP/P), they were labeled "conflicting", while other nonconsensus observations were labeled "no consensus". We assessed our classifications using the InterVar software to compare to ACMG 2015 guidelines, showing 99.7% overall consistency with only 0.3% discrepancies. Differences in classifications between Dutch labs or between Dutch labs and ACMG were mainly present in genes with low penetrance or for late onset disorders and highlight limitations of the current 5-tier classification system. The data sharing boosted the quality of DNA diagnostics in Dutch labs, an initiative we hope will be followed internationally. Recently, a positive match with a case from outside our consortium resulted in a more definite disease diagnosis.


Asunto(s)
Enfermedades Genéticas Congénitas/diagnóstico , Variación Genética , Secuenciación de Nucleótidos de Alto Rendimiento/métodos , Difusión de la Información/métodos , Exactitud de los Datos , Bases de Datos Genéticas , Enfermedades Genéticas Congénitas/genética , Guías como Asunto , Humanos , Laboratorios , Países Bajos , Análisis de Secuencia de ADN
SELECCIÓN DE REFERENCIAS
DETALLE DE LA BÚSQUEDA