{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T21:21:14Z","timestamp":1777929674267,"version":"3.51.4"},"reference-count":26,"publisher":"SAGE Publications","issue":"8","license":[{"start":{"date-parts":[[2016,12,15]],"date-time":"2016-12-15T00:00:00Z","timestamp":1481760000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Stat Methods Med Res"],"published-print":{"date-parts":[[2018,8]]},"abstract":"<jats:p>Population-based cancer screening is often asked but hardly addressed by a question: \u201cHow many rounds of screening are required before identifying a cancer of interest staying in the pre-clinical detectable phase (PCDP)?\u201d and also a similar one related to the number of screens required for stopping screening for the low risk group. It can be answered by using longitudinal follow-up data on repeated rounds of screen, namely periodic screen, but such kind of data are rather complicated and fraught with intractable statistical properties including correlated multistate outcomes, unobserved and incomplete (censoring or truncation) information, and imperfect measurements. We therefore developed a negative-binomial-family-based discrete-time stochastic process, taking sensitivity and specificity into account, to accommodate these thorny issues. The estimation of parameters was implemented with Bayesian Markov Chain Monte Carlo method. We demonstrated how to apply this proposed negative-binomial-family-based model to the empirical data similar to the Finnish breast cancer screening program.<\/jats:p>","DOI":"10.1177\/0962280216682284","type":"journal-article","created":{"date-parts":[[2017,1,19]],"date-time":"2017-01-19T04:13:25Z","timestamp":1484799205000},"page":"2519-2539","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Bayesian negative-binomial-family-based multistate Markov model for the evaluation of periodic population-based cancer screening considering incomplete information and measurement errors"],"prefix":"10.1177","volume":"27","author":[{"given":"Chen-Yang","family":"Hsu","sequence":"first","affiliation":[{"name":"Division of Biostatistics, College of Public Health, National Taiwan University, Taipei, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ming-Fang","family":"Yen","sequence":"additional","affiliation":[{"name":"School of Oral Hygiene, College of Oral Medicine, Taipei Medical University, Taipei, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anssi","family":"Auvinen","sequence":"additional","affiliation":[{"name":"Tampere School of Health Science, University of Tampere, Tampere, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yueh-Hsia","family":"Chiu","sequence":"additional","affiliation":[{"name":"Department of Health Care Management, College of Management, Chang Gung University, Tao-Yuan, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hsiu-Hsi","family":"Chen","sequence":"additional","affiliation":[{"name":"Division of Biostatistics, College of Public Health, National Taiwan University, Taipei, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2016,12,15]]},"reference":[{"key":"bibr1-0962280216682284","doi-asserted-by":"publisher","DOI":"10.1002\/cncr.20171"},{"key":"bibr2-0962280216682284","doi-asserted-by":"publisher","DOI":"10.1007\/s10549-009-0604-x"},{"key":"bibr3-0962280216682284","doi-asserted-by":"publisher","DOI":"10.1007\/s10549-009-0701-x"},{"key":"bibr4-0962280216682284","doi-asserted-by":"publisher","DOI":"10.1111\/j.1572-0241.2008.01875.x"},{"key":"bibr5-0962280216682284","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.11110469"},{"key":"bibr6-0962280216682284","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(12)61611-0"},{"key":"bibr7-0962280216682284","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.g2467"},{"key":"bibr8-0962280216682284","doi-asserted-by":"publisher","DOI":"10.1038\/bjc.1987.112"},{"key":"bibr9-0962280216682284","first-page":"9","volume":"2","author":"Chen HH","year":"1997","journal-title":"J Epidemio Biostat"},{"key":"bibr10-0962280216682284","first-page":"23","volume":"2","author":"Chen HH","year":"1997","journal-title":"J Epidemio Biostat"},{"key":"bibr11-0962280216682284","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2012.716335"},{"key":"bibr12-0962280216682284","doi-asserted-by":"publisher","DOI":"10.1177\/096914139500200104"},{"key":"bibr13-0962280216682284","doi-asserted-by":"publisher","DOI":"10.1093\/ije\/25.6.1139"},{"key":"bibr14-0962280216682284","doi-asserted-by":"publisher","DOI":"10.1093\/jncimono\/1997.22.93"},{"key":"bibr15-0962280216682284","doi-asserted-by":"publisher","DOI":"10.1111\/j.0006-341X.2000.00167.x"},{"key":"bibr16-0962280216682284","doi-asserted-by":"publisher","DOI":"10.1002\/sim.1277"},{"key":"bibr17-0962280216682284","first-page":"307","volume":"45","author":"Chen HH","year":"1996","journal-title":"J R Stat Soc Series D"},{"key":"bibr18-0962280216682284","doi-asserted-by":"publisher","DOI":"10.1158\/1055-9965.EPI-09-1028"},{"key":"bibr19-0962280216682284","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejca.2004.06.017"},{"key":"bibr20-0962280216682284","volume-title":"The Theory of Stochastic Processes","author":"Cox DR","year":"1977"},{"key":"bibr21-0962280216682284","volume-title":"Introduction to Stochastic Process and their Applications, Ch 5","author":"Chiang CL","year":"1980"},{"key":"bibr22-0962280216682284","doi-asserted-by":"publisher","DOI":"10.1002\/1097-0142(19950515)75:10<2507::AID-CNCR2820751017>3.0.CO;2-H"},{"key":"bibr23-0962280216682284","doi-asserted-by":"publisher","DOI":"10.1093\/oxfordjournals.aje.a113705"},{"key":"bibr24-0962280216682284","doi-asserted-by":"crossref","unstructured":"Hilbe JM.\n                      Negative Binomial Regression\n                      . 2nd ed. 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