Literature DB >> 10679753

Analysis of recent trends in prostate cancer incidence and mortality.

L K Dennis1, M I Resnick.   

Abstract

BACKGROUND: There is debate over whether the recent increases seen in prostate cancer are due to lead-time bias from screening, or identification of clinically insignificant lesions.
METHODS: Population-based incidence rates for 1973-1996 were calculated, based on the Surveillance, Epidemiology, and End Results Program (SEER) tumor registries. Relative incidence rates for prostate cancer by stage, fatal incidence, and lymph nodes were calculated, adjusted for age.
RESULTS: Localized and regional stage prostate cancer increased through 1992 and then dropped. The rate of distant-stage disease was relatively stable from 1973-1991, with a decrease in distant stage starting in 1992. The 2-year mortality rates were constant for 1973-1989. A decline in the 2-year mortality among cases (fatal incidence) also began in 1992.
CONCLUSIONS: These data show large increases in early disease, followed by a drop and leveling off along with a decrease in advanced disease (distant stage, 2-year mortality, positive lymph nodes). This indicates that the increasing incidence rates for prostate cancer are largely due to lead-time bias from increased early detection and treatment of prostate cancer. However, since incidence rates have not declined to rates seen in the 1970s, the additional cases may also reflect length bias from insignificant lesions or a true increase in incidence over time. Copyright 2000 Wiley-Liss, Inc.

Entities:  

Mesh:

Year:  2000        PMID: 10679753     DOI: 10.1002/(sici)1097-0045(20000301)42:4<247::aid-pros1>3.0.co;2-5

Source DB:  PubMed          Journal:  Prostate        ISSN: 0270-4137            Impact factor:   4.104


  10 in total

1.  Hyperpolarized 13C Metabolic Magnetic Resonance Spectroscopy and Imaging.

Authors:  Eugen Kubala; Kim A Muñoz-Álvarez; Geoffrey Topping; Christian Hundshammer; Benedikt Feuerecker; Pedro A Gómez; Giorgio Pariani; Franz Schilling; Steffen J Glaser; Rolf F Schulte; Marion I Menzel; Markus Schwaiger
Journal:  J Vis Exp       Date:  2016-12-30       Impact factor: 1.355

2.  3-D photoacoustic and pulse echo imaging of prostate tumor progression in the mouse window chamber.

Authors:  Daniel R Bauer; Ragnar Olafsson; Leonardo G Montilla; Russell S Witte
Journal:  J Biomed Opt       Date:  2011-02       Impact factor: 3.170

3.  Success and failure of single-modality treatment for early prostate cancer.

Authors:  David G McLeod
Journal:  Rev Urol       Date:  2004

4.  Positron emission tomography with 11C-acetate and 18F-FDG in prostate cancer patients.

Authors:  E Fricke; S Machtens; M Hofmann; J van den Hoff; S Bergh; T Brunkhorst; G J Meyer; J H Karstens; W H Knapp; A R Boerner
Journal:  Eur J Nucl Med Mol Imaging       Date:  2003-02-13       Impact factor: 9.236

5.  Prostate biopsy in the supine position in a standard 1.5-T scanner under real time MR-imaging control using a MR-compatible endorectal biopsy device.

Authors:  K Engelhard; H P Hollenbach; B Kiefer; A Winkel; K Goeb; D Engehausen
Journal:  Eur Radiol       Date:  2006-02-01       Impact factor: 5.315

6.  Recent time trends in the epidemiology of stage IV prostate cancer in the United States: analysis of data from the Surveillance, Epidemiology, and End Results Program.

Authors:  Karynsa Cetin; Jennifer L Beebe-Dimmer; Jon P Fryzek; Richard Markus; Michael A Carducci
Journal:  Urology       Date:  2009-12-06       Impact factor: 2.649

Review 7.  [Role of lymph node dissection in prostate cancer].

Authors:  T Schlomm; C Börgermann; H Heinzer; H Rübben; H Huland; M Graefen
Journal:  Urologe A       Date:  2009-01       Impact factor: 0.639

Review 8.  Background to and management of treatment-related bone loss in prostate cancer.

Authors:  Alfredo Berruti; Marcello Tucci; Carlo Terrone; Gabriella Gorzegno; Roberto M Scarpa; Alberto Angeli; Luigi Dogliotti
Journal:  Drugs Aging       Date:  2002       Impact factor: 3.923

9.  Quantifying lead-time bias in risk factor studies of cancer through simulation.

Authors:  Rick J Jansen; Bruce H Alexander; Kristin E Anderson; Timothy R Church
Journal:  Ann Epidemiol       Date:  2013-08-27       Impact factor: 3.797

10.  alpha-Methylacyl-CoA racemase: expression levels of this novel cancer biomarker depend on tumor differentiation.

Authors:  Rainer Kuefer; Sooryanarayana Varambally; Ming Zhou; Peter C Lucas; Martin Loeffler; Hubertus Wolter; Torsten Mattfeldt; Richard E Hautmann; Juergen E Gschwend; Terrence R Barrette; Rodney L Dunn; Arul M Chinnaiyan; Mark A Rubin
Journal:  Am J Pathol       Date:  2002-09       Impact factor: 4.307

  10 in total

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