Evidence map›Paper›PMID 25196658›Full record

ArticleThe Journal of urology2015

Increasing use of observation among men at low risk for prostate cancer mortality.

Chad R Ritch, Amy J Graves, Kirk A Keegan, Shenghua Ni, Jeffrey C Bassett, Sam S Chang, Matthew J Resnick, David F Penson, Daniel A Barocas

Abstract read
In one paragraph

Article in The Journal of urology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

  1. Article
  2. Article
  3. Selecting Active Surveillance: Decision Making Factors for Men with a Low-Risk Prostate Cancer.Medical decision making : an international journal of the Society for Medical Decision Making · 2019
    Article
  4. Article
  5. Article
  6. Review
  7. Observational
  8. Article
  9. Decision Support and Shared Decision Making About Active Surveillance Versus Active Treatment Among Men Diagnosed with Low-Risk Prostate Cancer: a Pilot Study.Journal of cancer education : the official journal of the American Association for Cancer Education · 2018
    Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Treatment Preferences for Active Surveillance versus Active Treatment among Men with Low-Risk Prostate Cancer.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2016
    Article
  15. Article
  16. A hospital-based study of initial observation for low-risk prostate cancer and its predictors in the United States.Canadian Urological Association journal = Journal de l'Association des urologues du Canada
    Article
  17. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Chad R RitchDepartment of Urology, University of Miami, Miami, Florida. Electronic address: ritch.chad@gmail.com.
Amy J GravesVanderbilt University Medical Center, Nashville, Tennessee.
Kirk A KeeganDivision of Urology, San Antonio Military Medical Center, San Antonio, Texas.
Shenghua NiCenter for Surgical Quality and Outcomes Research, Nashville, Tennessee.
Jeffrey C BassettVanderbilt University Medical Center, Nashville, Tennessee.
Sam S ChangDepartment of Urologic Surgery, Nashville, Tennessee.
Matthew J ResnickVanderbilt University Medical Center, Nashville, Tennessee.
David F PensonVanderbilt University Medical Center, Nashville, Tennessee.
Daniel A BarocasVanderbilt University Medical Center, Nashville, Tennessee.

Funding

Vanderbilt Clinical Oncology Research Career Development ProgramK12CA090625 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Debra L. Friedman, Paula Jill Hurley · 2001 to 2026
$16.9M
Trends in Surveillance for Localized Prostate Cancer and Barriers to its UseR03CA173812 · NCI · VANDERBILT UNIVERSITY · PI BAROCAS, DANIEL A · 2013 to 2014
$154k
NCI NIH HHS 1R03CA173812-01NCI NIH HHS CA-90625NCI NIH HHS K12 CA090625NCI NIH HHS R03 CA173812
6 · The paper itself

Abstract

purposeThere are growing concerns regarding the overtreatment of localized prostate cancer. It is also relatively unknown whether there has been increased uptake of observational strategies for disease management. We assessed the temporal trend in observation of clinically localized prostate cancer, particularly in men with low risk disease, who were young and healthy enough to undergo treatment. MATERIALS AND

methodsWe performed a retrospective cohort study using the SEER-Medicare database in 66,499 men with localized prostate cancer between 2004 and 2009. The main study outcome was observation within 1 year after diagnosis. We performed multivariable analysis to develop a predictive model of observation adjusting for diagnosis year, age, risk and comorbidity.

resultsObservation was performed in 12,007 men (18%) with a slight increase with time from 17% to 20%. However, there was marked increase in observation from 18% in 2004 to 29% in 2009 in men with low risk disease. Men 66 to 69 years old with low risk disease and no comorbidities had twice the odds of undergoing observation in 2009 vs 2004 (OR 2.12, 95% CI 1.73-2.59). Age, risk group, comorbidity and race were independent predictors of observation (each p <0.001), in addition to diagnosis year.

conclusionsWe identified increasing use of observation for low risk prostate cancer between 2004 and 2009 even in men young and healthy enough for treatment. This suggests growing acceptance of surveillance in this group of patients.

Indexed as

AgedAged, 80 and overCohort StudiesHumansMaleProstatic NeoplasmsRetrospective StudiesRisk AssessmentWatchful Waitingage groupscomorbiditycontinental population groupsprostatic neoplasmstherapy

Identifiers

PMID25196658
PMCPMC4363002

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.