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

  1. Grace Hui-Min Wu1,2,
  2. Anssi Auvinen1,3,
  3. Amy Ming-Fang Yen2,4,
  4. Matti Hakama1,3,
  5. Stephen D. Walter5,
  6. Hsiu-Hsi Chen2,*

Article first published online: 23 DEC 2011

DOI: 10.1002/bimj.201000107

Issue

Biometrical Journal

Biometrical Journal

Special Issue: Survival and Event History Analysis

Volume 54, Issue 1, pages 20–44, January 2012

Additional Information

How to Cite

Wu, G. H.-M., Auvinen, A., Yen, A. M.-F., Hakama, M., Walter, S. D. and Chen, H.-H. (2012), A stochastic model for survival of early prostate cancer with adjustments for leadtime, length bias, and over-detection. Biom. J., 54: 20–44. doi: 10.1002/bimj.201000107

Author Information

  1. 1

    Tampere School of Public Health, University of Tampere, Tampere, Finland

  2. 2

    Division of Biostatistics, Graduate Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan

  3. 3

    Finnish Cancer Institute, Helsinki, Finland

  4. 4

    School of Oral Hygiene, College of Oral Medicine, Taipei Medical University, Taipei, Taiwan

  5. 5

    Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Canada

*Phone: +886-2-33668033, Fax: +886-2-23587707

Publication History

  1. Issue published online: 5 JAN 2012
  2. Article first published online: 23 DEC 2011
  3. Manuscript Accepted: 3 OCT 2011
  4. Manuscript Revised: 1 OCT 2011
  5. Manuscript Received: 9 MAY 2010

Funded by

  • Finnish Distinguished Professor (FiDiPro) Academy of Finland, Tampere University Hospital Research Fund
  • Taiwan National Science Council. Grant Numbers: NSC 91-2320-B-002-215, NSC 94-2314-B-002-106, NSC 97-2314-B-002-019-MY3

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Keywords:

  • Leadtime and length bias;
  • Mass screening;
  • Prostate neoplasms;
  • Prostate-specific antigen;
  • Stochastic processes

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.

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