Simulation Study for the Sensitivity and Mean Sojourn Time Spec ificLead Time in Cancer Screening When Human Lifetime is a Competin gRisk

Purpose: The purpose of this paper is to examine the sensitivity and mean sojourn time specific lead time distribution in cancer screening trials when lifetime is a random variable in order to explore possible optimal initial age at screening and screening frequency. Methods: Summarized methods from Wu et al. (2012). Simulation was used in order to estimate the distribution of the lead time for a hypothetical individual with a future screening schedule. The lifetime distribution used comes from the Social Security Administration’s actuarial life tables. The lead time distribution was then calculated based on a loglogistic sojourn time distribution with two mean sojourn times (2, and 10 years), using three different initial screening ages, t0=40, 50, 60, different screening sensitivities (0.3 and 0.5 for men; 0.8 and 0.9 for women), and two different screening frequencies, one and two years for both men and women. Results: Smaller time intervals between screenings yield a smaller probability of no early detection and a greater expected lead time.

[1]  Marvin Zelen,et al.  On the theory of screening for chronic diseases , 1969 .

[2]  T. Church,et al.  Fecal occult blood screening in the Minnesota study: sensitivity of the screening test. , 1997, Journal of the National Cancer Institute.

[3]  J. Wilbur American Family Physician , 2008 .

[4]  Ian M Thompson,et al.  Operating characteristics of prostate-specific antigen in men with an initial PSA level of 3.0 ng/ml or lower. , 2005, JAMA.

[5]  Stuart A. Taylor,et al.  CT colonography in the detection of colorectal polyps and cancer: systematic review, meta-analysis, and proposed minimum data set for study level reporting. , 2005, Radiology.

[6]  C. Rutter,et al.  Estimated Mean Sojourn Time Associated with Hemoccult SENSA for Detection of Proximal and Distal Colorectal Cancer , 2012, Cancer Epidemiology, Biomarkers & Prevention.

[7]  Philip C. Prorok IN THE DESIGN OF A REPETITIVE SCREENING PROGRAM , 1982 .

[8]  Tony Hsiu-Hsi Chen,et al.  Mean sojourn time and effectiveness of mortality reduction for lung cancer screening with computed tomography , 2008, International journal of cancer.

[9]  G. Giles,et al.  The sensitivity, specificity, and positive predictive value of screening mammography and symptomatic status , 2000, Journal of medical screening.

[10]  Dongfeng Wu,et al.  MLE and Bayesian Inference of Age‐Dependent Sensitivity and Transition Probability in Periodic Screening , 2005, Biometrics.

[11]  G. Rosner,et al.  Estimating key parameters in FOBT screening for colorectal cancer , 2009, Cancer Causes & Control.

[12]  Rhodri Hayward,et al.  Screening , 2008, The Lancet.

[13]  L. Broemeling,et al.  Bayesian Inference for the Lead Time in Periodic Cancer Screening , 2007, Biometrics.

[14]  Dongfeng Wu,et al.  The Lead Time Distribution When Lifetime is Subject to Competing Risks in Cancer Screening , 2012, The international journal of biostatistics.

[15]  Dongfeng Wu,et al.  Sojourn time and lead time projection in lung cancer screening. , 2011, Lung cancer.