Literature DB >> 21546365

What if I don't treat my PSA-detected prostate cancer? Answers from three natural history models.

Roman Gulati1, Elisabeth M Wever, Alex Tsodikov, David F Penson, Lurdes Y T Inoue, Jeffrey Katcher, Shih-Yuan Lee, Eveline A M Heijnsdijk, Gerrit Draisma, Harry J de Koning, Ruth Etzioni.   

Abstract

BACKGROUND: Making an informed decision about treating a prostate cancer detected after a routine prostate-specific antigen (PSA) test requires knowledge about disease natural history, such as the chances that it would have been clinically diagnosed in the absence of screening and that it would metastasize or lead to death in the absence of treatment.
METHODS: We use three independently developed models of prostate cancer natural history to project risks of clinical progression events and disease-specific deaths for PSA-detected cases assuming they receive no primary treatment.
RESULTS: The three models project that 20%-33% of men have preclinical onset; of these 38%-50% would be clinically diagnosed and 12%-25% would die of the disease in the absence of screening and primary treatment. The risk that men age less than 60 at PSA detection with Gleason score 2-7 would be clinically diagnosed in the absence of screening is 67%-93% and would die of the disease in the absence of primary treatment is 23%-34%. For Gleason score 8 to 10 these risks are 90%-96% and 63%-83%.
CONCLUSIONS: Risks of disease progression among untreated PSA-detected cases can be nontrivial, particularly for younger men and men with high Gleason scores. Model projections can be useful for informing decisions about treatment. IMPACT: This is the first study to project population-based natural history summaries in the absence of screening or primary treatment and risks of clinical progression events following PSA detection in the absence of primary treatment. ©2011 AACR.

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Year:  2011        PMID: 21546365      PMCID: PMC3091266          DOI: 10.1158/1055-9965.EPI-10-0718

Source DB:  PubMed          Journal:  Cancer Epidemiol Biomarkers Prev        ISSN: 1055-9965            Impact factor:   4.254


  30 in total

1.  Calibrating disease progression models using population data: a critical precursor to policy development in cancer control.

Authors:  Roman Gulati; Lurdes Inoue; Jeffrey Katcher; William Hazelton; Ruth Etzioni
Journal:  Biostatistics       Date:  2010-06-07       Impact factor: 5.899

2.  A population model of prostate cancer incidence.

Authors:  A Tsodikov; A Szabo; J Wegelin
Journal:  Stat Med       Date:  2006-08-30       Impact factor: 2.373

3.  Estimating lead time and overdiagnosis associated with PSA screening from prostate cancer incidence trends.

Authors:  Donatello Telesca; Ruth Etzioni; Roman Gulati
Journal:  Biometrics       Date:  2007-05-14       Impact factor: 2.571

4.  Prostate cancer and the Will Rogers phenomenon.

Authors:  Peter C Albertsen; James A Hanley; George H Barrows; David F Penson; Pam D H Kowalczyk; M Melinda Sanders; Judith Fine
Journal:  J Natl Cancer Inst       Date:  2005-09-07       Impact factor: 13.506

5.  Mortality results from a randomized prostate-cancer screening trial.

Authors:  Gerald L Andriole; E David Crawford; Robert L Grubb; Saundra S Buys; David Chia; Timothy R Church; Mona N Fouad; Edward P Gelmann; Paul A Kvale; Douglas J Reding; Joel L Weissfeld; Lance A Yokochi; Barbara O'Brien; Jonathan D Clapp; Joshua M Rathmell; Thomas L Riley; Richard B Hayes; Barnett S Kramer; Grant Izmirlian; Anthony B Miller; Paul F Pinsky; Philip C Prorok; John K Gohagan; Christine D Berg
Journal:  N Engl J Med       Date:  2009-03-18       Impact factor: 91.245

6.  Quantifying the role of PSA screening in the US prostate cancer mortality decline.

Authors:  Ruth Etzioni; Alex Tsodikov; Angela Mariotto; Aniko Szabo; Seth Falcon; Jake Wegelin; Dante DiTommaso; Kent Karnofski; Roman Gulati; David F Penson; Eric Feuer
Journal:  Cancer Causes Control       Date:  2007-11-20       Impact factor: 2.506

7.  Natural history of early, localized prostate cancer.

Authors:  Jan-Erik Johansson; Ove Andrén; Swen-Olof Andersson; Paul W Dickman; Lars Holmberg; Anders Magnuson; Hans-Olov Adami
Journal:  JAMA       Date:  2004-06-09       Impact factor: 56.272

Review 8.  Systematic review: comparative effectiveness and harms of treatments for clinically localized prostate cancer.

Authors:  Timothy J Wilt; Roderick MacDonald; Indulis Rutks; Tatyana A Shamliyan; Brent C Taylor; Robert L Kane
Journal:  Ann Intern Med       Date:  2008-02-04       Impact factor: 25.391

9.  A prospective evaluation of plasma prostate-specific antigen for detection of prostatic cancer.

Authors:  P H Gann; C H Hennekens; M J Stampfer
Journal:  JAMA       Date:  1995-01-25       Impact factor: 56.272

10.  A model of the natural history of screen-detected prostate cancer, and the effect of radical treatment on overall survival.

Authors:  C Parker; D Muston; J Melia; S Moss; D Dearnaley
Journal:  Br J Cancer       Date:  2006-05-22       Impact factor: 7.640

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  26 in total

1.  Elevated HERV-K mRNA expression in PBMC is associated with a prostate cancer diagnosis particularly in older men and smokers.

Authors:  Tiffany A Wallace; Ronan F Downey; Caleb J Seufert; Aaron Schetter; Tiffany H Dorsey; Carol A Johnson; Radoslav Goldman; Christopher A Loffredo; Peisha Yan; Francis J Sullivan; Francis J Giles; Feng Wang-Johanning; Stefan Ambs; Sharon A Glynn
Journal:  Carcinogenesis       Date:  2014-05-23       Impact factor: 4.944

2.  Conditions for Valid Empirical Estimates of Cancer Overdiagnosis in Randomized Trials and Population Studies.

Authors:  Roman Gulati; Eric J Feuer; Ruth Etzioni
Journal:  Am J Epidemiol       Date:  2016-06-29       Impact factor: 4.897

3.  Early detection of prostate cancer: AUA Guideline.

Authors:  H Ballentine Carter; Peter C Albertsen; Michael J Barry; Ruth Etzioni; Stephen J Freedland; Kirsten Lynn Greene; Lars Holmberg; Philip Kantoff; Badrinath R Konety; Mohammad Hassan Murad; David F Penson; Anthony L Zietman
Journal:  J Urol       Date:  2013-05-06       Impact factor: 7.450

4.  Expected population impacts of discontinued prostate-specific antigen screening.

Authors:  Roman Gulati; Alex Tsodikov; Ruth Etzioni; Rachel A Hunter-Merrill; John L Gore; Angela B Mariotto; Matthew R Cooperberg
Journal:  Cancer       Date:  2014-07-25       Impact factor: 6.860

5.  Personalizing age of cancer screening cessation based on comorbid conditions: model estimates of harms and benefits.

Authors:  Iris Lansdorp-Vogelaar; Roman Gulati; Angela B Mariotto; Clyde B Schechter; Tiago M de Carvalho; Amy B Knudsen; Nicolien T van Ravesteyn; Eveline A M Heijnsdijk; Chester Pabiniak; Marjolein van Ballegooijen; Carolyn M Rutter; Karen M Kuntz; Eric J Feuer; Ruth Etzioni; Harry J de Koning; Ann G Zauber; Jeanne S Mandelblatt
Journal:  Ann Intern Med       Date:  2014-07-15       Impact factor: 25.391

6.  Economic Analysis of Prostate-Specific Antigen Screening and Selective Treatment Strategies.

Authors:  Joshua A Roth; Roman Gulati; John L Gore; Matthew R Cooperberg; Ruth Etzioni
Journal:  JAMA Oncol       Date:  2016-07-01       Impact factor: 31.777

7.  Active Surveillance Versus Watchful Waiting for Localized Prostate Cancer: A Model to Inform Decisions.

Authors:  Stacy Loeb; Qinlian Zhou; Uwe Siebert; Ursula Rochau; Beate Jahn; Nikolai Mühlberger; H Ballentine Carter; Herbert Lepor; R Scott Braithwaite
Journal:  Eur Urol       Date:  2017-08-23       Impact factor: 20.096

Review 8.  Defining the threshold for significant versus insignificant prostate cancer.

Authors:  Theo H Van der Kwast; Monique J Roobol
Journal:  Nat Rev Urol       Date:  2013-05-28       Impact factor: 14.432

9.  Response: Reading between the lines of cancer screening trials: using modeling to understand the evidence.

Authors:  Ruth Etzioni; Roman Gulati
Journal:  Med Care       Date:  2013-04       Impact factor: 2.983

10.  Racial disparities in prostate cancer survival in a screened population: Reality versus artifact.

Authors:  Dhamanpreet Kaur; Ernesto Ulloa-Pérez; Roman Gulati; Ruth Etzioni
Journal:  Cancer       Date:  2018-01-25       Impact factor: 6.860

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