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Journal of Biometrics & Biostatistics

ISSN: 2155-6180

Open Access

Yu-Ting Chen


Tanzania

Publications
  • Research Article
    Over-diagnosis in Lung Cancer Screening using the MSKC-LCSP Data
    Author(s): Yu-Ting Chen, Diane Erwin and Dongfeng WuYu-Ting Chen, Diane Erwin and Dongfeng Wu

    We applied a newly developed probability method to predict long term outcomes and over diagnosis in lung cancer screening using the Memorial Sloan-Kettering Cancer study (MSKC-LCSP) data. All participants were categorized into four mutually exclusive groups depending on their diagnosis status and ultimate disease status: symptom-freelife, no-early-detection, true-early-detection and over-diagnosis. Probability of each group is a function of the three key parameters: screening sensitivity, sojourn time in preclinical state and transition density from disease free to the preclinical state. We first obtained reliable and accurate estimates of these three key parameters using the MSKCLCSP data and likelihood function with a Bayesian approach, and then calculate the probability of each group by inserting these Bayesian posterior samples to the probability formulae, to predict future long t.. Read More»
    DOI: 10.4172/2155-6180.1000201

    Abstract PDF

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Citations: 3254

Journal of Biometrics & Biostatistics received 3254 citations as per Google Scholar report

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