Literature DB >> 34765725

Inference of Sojourn Time and Transition Density using the NLST X-ray Screening Data in Lung Cancer.

Farhin Rahman1, Dongfeng Wu1.   

Abstract

AIMS: The aim of this study is to provide statistical inference of the sojourn time and the transition probability from the disease free to the preclinical state of lung cancer for male and female smokers using lung cancer data from the National Lung Screening Trial (NLST).
MATERIALS AND METHODS: We applied a likelihood function to the lung cancer data, to obtain Bayesian inference of the transition probability and the sojourn time distribution. A log-normal distribution was used for the transition probability density function multiplied by 30%, and a Weibull distribution was used to model the sojourn time in the preclinical state.
RESULTS: The estimate of screening sensitivity is 0.61 for males and 0.62 for females. Early transition happened before age 50 and lasted until after age 90. The transition probability from the disease free to the preclinical state has a single maximum at around age 73 for males and 72 for females. For male, the Bayesian posterior mean, and median sojourn time are 1.33 and 1.27 years, respectively. For female, the corresponding posterior mean, and median sojourn time are 1.23 and 1.21 years, respectively.
CONCLUSION: Our estimation showed that male smokers are more vulnerable to lung cancer, because they have a higher transition probability density than the same aged female smokers. The female smokers have a slightly shorter mean sojourn time than the male, meaning that they are quicker to develop clinical symptom of lung cancer.

Entities:  

Keywords:  Lung Cancer Screening; Markov Chain Monte Carlo; National Lung Screening Trial; Sensitivity; Sojourn Time; Transition Density

Year:  2021        PMID: 34765725      PMCID: PMC8580138          DOI: 10.18103/mra.v9i5.2399

Source DB:  PubMed          Journal:  Med Res Arch        ISSN: 2375-1916


  11 in total

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Review 5.  Sensitivity and specificity of chest X-ray screening for lung cancer: review article.

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7.  Estimation of mean sojourn time for lung cancer by chest X-ray screening with a Bayesian approach.

Authors:  Chun-Ru Chien; Mei-Shu Lai; Tony Hsiu-Hsi Chen
Journal:  Lung Cancer       Date:  2008-04-09       Impact factor: 5.705

8.  Sensitivity and specificity of lung cancer screening using chest low-dose computed tomography.

Authors:  Y Toyoda; T Nakayama; Y Kusunoki; H Iso; T Suzuki
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9.  Bayesian lead time estimation for the Johns Hopkins Lung Project data.

Authors:  Hyejeong Jang; Seongho Kim; Dongfeng Wu
Journal:  J Epidemiol Glob Health       Date:  2013-06-14
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