
AJUNTAMENT D'ALCOI
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Generalitat Valenciana
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Ayuntamiento de Valencia
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Cicloplast
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Ayuntamiento de Onil
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Anarpla
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Ayuntamiento de Mislata
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nlWA, North London Waste Authority
Website

Ayuntamiento de Salinas
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Zicla
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Fondazione Ecosistemi
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PEFC
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ALQUIENVAS
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DIPUTACI� DE VAL�NCIA
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AYUNTAMIENTO DE REQUENA
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UNIVERSIDAD DE ZARAGOZA
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OBSERVATORIO CONTRATACIÓN PÚBLICA
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AYUNTAMIENTO DE PAIPORTA
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AYUNTAMIENTO DE CUENCA
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BERL� S.A.
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CM PLASTIK
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TRANSFORMADORES INDUSTRIALES ECOL�GICOS

INDUSTRIAS AGAPITO
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RUBI KANGURO
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If you want to support our LIFE project as a STAKEHOLDER, please contact with us: life-future-project@aimplas.es
In this section, you can access to the latest technical information related to the FUTURE project topic.
EGFR testing and erlotinib use in non-small cell lung cancer patients in Kentucky
This study determined the frequency and factors associated with EGFR testing rates and erlotinib treatment as well as associated survival outcomes in patients with non small cell lung cancer in Kentucky. Data from the Kentucky Cancer Registry (KCR) linked with health claims from Medicaid, Medicare and private insurance groups were evaluated. EGFR testing and erlotinib prescribing were identified using ICD-9 procedure codes and national drug codes in claims, respectively. Logistic regression analysis was performed to determine factors associated with EGFR testing and erlotinib prescribing. Cox-regression analysis was performed to determine factors associated with survival. EGFR mutation testing rates rose from 0.1% to 10.6% over the evaluated period while erlotinib use ranged from 3.4% to 5.4%. Factors associated with no EGFR testing were older age, male gender, enrollment in Medicaid or Medicare, smoking, and geographic region. Factors associated with not receiving erlotinib included older age, male gender, enrollment in Medicare or Medicaid, and living in moderate to high poverty. Survival analysis demonstrated EGFR testing or erlotinib use was associated with a higher likelihood of survival. EGFR testing and erlotinib prescribing were slow to be implemented in our predominantly rural state. While population-level factors likely contributed, patient factors, including geographic location (areas with high poverty rates and rural regions) and insurance type, were associated with lack of use, highlighting rural disparities in the implementation of cancer precision medicine.

» Author: Kara L. Larson, Bin Huang, Quan Chen, Thomas Tucker, Marissa Schuh, Susanne M. Arnold, Jill M. Kolesar
» Reference: https://doi.org/10.1371/journal.pone.0237790
» Publication Date: 18/08/2020
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