Literature DB >> 22213054

A stochastic model for survival of early prostate cancer with adjustments for leadtime, length bias, and over-detection.

Grace Hui-Min Wu1, Anssi Auvinen, Amy Ming-Fang Yen, Matti Hakama, Stephen D Walter, Hsiu-Hsi Chen.   

Abstract

To compare the survival between screen-detected and clinically detected cancers, we applied a series of non-homogeneous stochastic processes to deal with leadtime, length bias, and over-detection by using full information on detection modes obtained from the Finnish randomized controlled trial for prostate cancer screening. The results show after 9-year follow-up the hazard ratio of prostate cancer death for screen-detected cases against clinically detected cases increased from 0.24 (95% CI: 0.16-0.35) without correction for these biases, to 0.76 after correction for leadtime and length biases, and finally to 1.03 (95% CI: 0.79-1.33) for a further adjustment for over-detection. Adjustment for leadtime and length bias but no over-detection led to a 24% reduction in prostate cancer death as a result of prostate-specific antigen test. The further calibration of over-detection indicates no gain in survival of screen-detected prostate cancers (excluding over-detected case as stayer considered in the mover-stayer model) as compared with the control group in the absence of screening that is considered as the mover. However, whether the model assumption on over-detection is robust should be validated with other data sets and longer follow-up.
Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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Year:  2011        PMID: 22213054     DOI: 10.1002/bimj.201000107

Source DB:  PubMed          Journal:  Biom J        ISSN: 0323-3847            Impact factor:   2.207


  4 in total

1.  Prostate-cancer mortality at 11 years of follow-up.

Authors:  Fritz H Schröder; Jonas Hugosson; Monique J Roobol; Teuvo L J Tammela; Stefano Ciatto; Vera Nelen; Maciej Kwiatkowski; Marcos Lujan; Hans Lilja; Marco Zappa; Louis J Denis; Franz Recker; Alvaro Páez; Liisa Määttänen; Chris H Bangma; Gunnar Aus; Sigrid Carlsson; Arnauld Villers; Xavier Rebillard; Theodorus van der Kwast; Paula M Kujala; Bert G Blijenberg; Ulf-Hakan Stenman; Andreas Huber; Kimmo Taari; Matti Hakama; Sue M Moss; Harry J de Koning; Anssi Auvinen
Journal:  N Engl J Med       Date:  2012-03-15       Impact factor: 91.245

2.  Benefits and harms of prostate cancer screening - predictions of the ONCOTYROL prostate cancer outcome and policy model.

Authors:  Nikolai Mühlberger; Kristijan Boskovic; Murray D Krahn; Karen E Bremner; Willi Oberaigner; Helmut Klocker; Wolfgang Horninger; Gaby Sroczynski; Uwe Siebert
Journal:  BMC Public Health       Date:  2017-06-26       Impact factor: 3.295

3.  A pre-symptomatic incubation model for precision strategies of screening, quarantine, and isolation based on imported COVID-19 cases in Taiwan.

Authors:  Grace Hsiao-Hsuan Jen; Amy Ming-Fang Yen; Chen-Yang Hsu; Sam Li-Sheng Chen; Tony Hsiu-Hsi Chen
Journal:  Sci Rep       Date:  2022-04-11       Impact factor: 4.379

4.  Sojourn-time-corrected receiver operating characteristic curve (ROC) for prostate specific antigen (PSA) test in population-based prostate cancer screening.

Authors:  Hsiao-Hsuan Jen; Wei-Jung Chang; Chen-Yang Hsu; Amy Ming-Fang Yen; Anssi Auvinen; Tony Hsiu-Hsi Chen; Sam Li-Sheng Chen
Journal:  Sci Rep       Date:  2020-11-26       Impact factor: 4.379

  4 in total

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