Estimation of mean sojourn time in breast cancer screening using a Markov chain model of both entry to and exit from the preclinical detectable phase

1995 ◽  
Vol 14 (14) ◽  
pp. 1531-1543 ◽  
Author(s):  
Stephen W. Duffy ◽  
Hsiu-Hsi Chen ◽  
Laszlo Tabar ◽  
Nicholas E. Day
Keyword(s):  
Breast Cancer ◽  
Markov Chain ◽  
Cancer Screening ◽  
Breast Cancer Screening ◽  
Sojourn Time ◽  
Markov Chain Model ◽  
Chain Model ◽  
Mean Sojourn Time

scholarly journals Test sensitivity of mammography and mean sojourn time over 40 years of breast cancer screening in Nijmegen (The Netherlands)

2018 ◽  
Vol 26 (3) ◽  
pp. 147-153 ◽  
Author(s):  
AMWM Aarts ◽  
SW Duffy ◽  
SME Geurts ◽  
DP Vulkan ◽  
JDM Otten ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Markov Chain ◽  
Markov Chain Monte Carlo ◽  
Cancer Screening ◽  
Linear Regression ◽  
Breast Cancer Screening ◽  
Sojourn Time ◽  
Likelihood Estimation ◽  
Non Linear ◽  
Mean Sojourn Time

Objectives We investigated whether changes in mammographic technique and screening policy have improved mammographic sensitivity, and elongated the mean sojourn time, since the introduction of biennial breast cancer screening in Nijmegen, the Netherlands, in 1975. Methods Maximum likelihood estimation, non-linear regression, and Markov Chain Monte Carlo simulation were used to estimate test sensitivity, mean sojourn time, and underlying breast cancer incidence in four time periods, covering 40 years of breast cancer screening in Nijmegen (1975–2012). Results Maximum likelihood estimation generated an estimated test sensitivity of approximately 90% and a mean sojourn time around three years, while the estimates based on non-linear regression and Markov Chain Monte Carlo simulation were 80% and four years, respectively. All three methods estimated a rise in the underlying breast cancer incidence over time, with approximately one case more per 1000 women per year in the final period compared with the first period. Conclusions The three methods showed a slightly higher mammographic sensitivity and a longer mean sojourn time in the last period, after the introduction of digital mammography. Estimates were more realistic for the more sophisticated methods, non-linear regression and Markov Chain Monte Carlo simulation, while the simple closed form approximation of maximum likelihood estimation led to rather high estimates for sensitivity in the early periods.

Estimation of age-specific sensitivity and sojourn time in breast cancer screening studies

2005 ◽  
Vol 24 (20) ◽  
pp. 3123-3138 ◽  
Author(s):  
Xiuyu J. Cong ◽  
Yu Shen ◽  
Anthony B. Miller
Keyword(s):  
Breast Cancer ◽  
Cancer Screening ◽  
Breast Cancer Screening ◽  
Sojourn Time ◽  
Specific Sensitivity

scholarly journals Prediction of Bone Metastasis in Inflammatory Breast Cancer Using a Markov Chain Model

2019 ◽  
Vol 24 (10) ◽  
pp. 1322-1330
Author(s):  
Takeo Fujii ◽  
Jeremy Mason ◽  
Angela Chen ◽  
Peter Kuhn ◽  
Wendy A. Woodward ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Markov Chain ◽  
Bone Metastasis ◽  
Inflammatory Breast Cancer ◽  
Markov Chain Model ◽  
Chain Model

A Markov chain model of a longitudinal breast cancer data set.

2014 ◽  
Vol 32 (15_suppl) ◽  
pp. 11040-11040
Author(s):  
Paul K. Newton ◽  
Jorge J. Nieva ◽  
Peter Kuhn ◽  
Larry Norton ◽  
Elizabeth Anne Comen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Markov Chain ◽  
Markov Chain Model ◽  
Chain Model ◽  
Breast Cancer Data ◽  
Data Set ◽  
Cancer Data

Estimating mean sojourn time and screening test sensitivity in breast cancer mammography screening: new results

2005 ◽  
Vol 12 (4) ◽  
pp. 172-178 ◽  
Author(s):  
Harald Weedon-Fekjær ◽  
Lars J Vatten ◽  
Odd O Aalen ◽  
Bo Lindqvist ◽  
Steinar Tretli
Keyword(s):  
Breast Cancer ◽  
Hormone Replacement Therapy ◽  
Cancer Screening ◽  
Replacement Therapy ◽  
Breast Cancer Screening ◽  
Sojourn Time ◽  
Screening Test ◽  
Hormone Replacement ◽  
Opportunistic Screening ◽  
Test Sensitivity

Objective: To assess if new screening techniques, increased use of hormone replacement therapy, or the transition from breast cancer screening trials to large scale screening programmes may influence the average time in preclinical screening detectable phase (mean sojourn time [MST]) or screening test sensitivity (STS). Setting: Screening and interval data for 395,188 women participating in the Norwegian Breast Cancer Screening Programme (NBCSP). Methods: Weighted non-linear least-square regression estimates using a tree step Markov chain model, and a sensitivity analysis of the possible impact by opportunistic screening between ordinary breast cancer screening rounds. Results: MST was estimated to 6.1 (95% confidence interval [CI] 5.1–7.0) years for women aged 50–59 years, and 7.9 (95% CI 6.0–7.9) years for those aged 60–69 years. Correspondingly, STS was estimated to 58% (95% CI 52–64 %) and 73 % (67–78 %), respectively. Simulations revealed that opportunistic screening may give a moderate estimation bias towards higher MST and lower STS. Assuming a probable 21% higher background incidence, due to increased hormone replacement therapy use, MST estimates decreased to 3.9 and 5.0 years for the two age groups, and STS increased to 75 and 85%. Conclusions: The new estimates indicate that screening detectable phase is longer than that found in previous mammography trials/programmes, but also that the sensitivity of the screening test is lower. Overall, the NBCSP detects more cancer cases than most previous trials/programmes.

scholarly journals Spatiotemporal progression of metastatic breast cancer: a Markov chain model highlighting the role of early metastatic sites

2015 ◽  
Vol 1 (1) ◽  
Author(s):  
Paul K Newton ◽  
Jeremy Mason ◽  
Neethi Venkatappa ◽  
Maxine S Jochelson ◽  
Brian Hurt ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Markov Chain ◽  
Metastatic Breast Cancer ◽  
Markov Chain Model ◽  
Metastatic Breast ◽  
Chain Model ◽  
Metastatic Sites

Screening Sensitivity and Sojourn Time From Breast Cancer Early Detection Clinical Trials: Mammograms and Physical Examinations

2001 ◽  
Vol 19 (15) ◽  
pp. 3490-3499 ◽  
Author(s):  
Yu Shen ◽  
Marvin Zelen
Keyword(s):  
Breast Cancer ◽  
Clinical Trials ◽  
Cancer Screening ◽  
Early Detection ◽  
Physical Examination ◽  
Breast Cancer Screening ◽  
Sojourn Time ◽  
Screening Programs ◽  
Screening Sensitivity ◽  
Screening Trials

PURPOSE: To estimate sensitivities of breast cancer screening modalities and preclinical duration of the disease from eight breast cancer screening clinical trials. PATIENTS AND METHODS: Screening programs invariably lead to diagnosis of disease before signs or symptoms are present. Two key quantities of screening programs are the sensitivity of the disease detection modality and the mean sojourn time (MST). The observed screening histories in a periodically screened cohort make it possible to estimate these quantities of interest. We applied recently developed statistical methods to data from eight randomized breast cancer screening trials to estimate the sensitivities of early detection modalities and MST. Moreover, when a screening trial involved two screening modalities, our methods enabled the estimation of the individual sensitivity of each screening modality. RESULTS: We analyzed breast cancer data from several screening trials and have relatively complete data from the Health Insurance Plan (HIP), Edinburgh, and two Canadian studies. The screening sensitivity for mammography, physical examination, and MST were, respectively, HIP: 0.39, 0.47, and 2.5 years; Edinburgh: 0.63, 0.40, and 4.3 years; Canadian (age 40 to 49 at entry): 0.61, 0.59, and 1.9 years; Canadian (age 50 to 59 at entry): 0.66, 0.39, and 3.1 years. CONCLUSION: The public debate on early breast cancer detection is mainly centered on mammograms. However, the current study indicates that a physical examination is of comparable importance. Cautious interpretation of trial differences is required as a result of various experimental designs and the age dependency of screening sensitivity and MST.

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