Journal of Biometrics & Biostatistics

Yu-Ting Chen

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