Literature DB >> 27653425

Urologist-Level Correlation in the Use of Observation for Low- and High-Risk Prostate Cancer.

Mark D Tyson1, Amy J Graves1, Brock O'Neil1, Daniel A Barocas1, Sam S Chang1, David F Penson2, Matthew J Resnick2.   

Abstract

Importance: The reporting of individual urologist rates of observation for localized prostate cancer may be a valuable performance measure with important downstream implications for patient and payer stakeholder groups. However, few studies have examined the urologist-level variation in the use of observation across all risk strata of prostate cancer.
Objectives: To measure variation in the use of observation at the urologist level by disease risk strata and to evaluate the association between the urologist-level rates of observation for men with low-risk and high-risk prostate cancer. Design, Setting, and Participants: With the use of linked Surveillance, Epidemiology, and End Results (SEER)-Medicare data, a population-based study of men diagnosed with prostate cancer from January 1, 2004, to December 31, 2009, was performed in SEER catchment areas of the United States. A total of 57 639 men with prostate cancer with 1884 diagnosing urologists were identified. Data were analyzed from October 1 to December 31, 2015. Main Outcomes and Measures: The main outcome was observation, which is defined as the absence of definitive treatment within 1 year of diagnosis. In each risk stratum, a multivariable mixed-effects model was fit to characterize associations between observation and selected patient characteristics. From these models, the estimated probability of observation was calculated for each urologist within each risk stratum, and the association between the physician-level estimated rates of observation for low-risk and high-risk disease was assessed.
Results: Among the 57 639 men included in the study, the estimated probability of observation for low-risk disease varied impressively (mean, 27.8%; range, 5.1%-71.2%) at the individual urologist level. Considerably less urologist-level variation was seen in the use of observation for intermediate-risk disease (11.1%; range, 4.8%-31.5%) and high-risk disease (5.8%; range, 3.2%-16.5%). Furthermore, the estimated rates of observation for low- and high-risk disease were correlated at the urologist level (Spearman ρ = 0.17; P < .001). A comparable correlation was likewise observed among urologists with high-volume prostate cancer practices (Spearman ρ = 0.24; P < .001). Conclusions and Relevance: Considerable urologist-level variation is seen in the use of observation for men with low-risk prostate cancer. More important, the use of observation for low-risk and high-risk patients with prostate cancer is correlated at the urologist level. This study reveals the strikingly variable use of observation among US urologists and establishes a framework for the use of urologist-level treatment signatures as a quality measure in the emerging value-based health care environment.

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Year:  2017        PMID: 27653425     DOI: 10.1001/jamasurg.2016.2907

Source DB:  PubMed          Journal:  JAMA Surg        ISSN: 2168-6254            Impact factor:   14.766


  5 in total

1.  Potential overtreatment among men aged 80 years and older with localized prostate cancer in Japan.

Authors:  Hiroyuki Masaoka; Hidemi Ito; Akira Yokomizo; Masatoshi Eto; Keitaro Matsuo
Journal:  Cancer Sci       Date:  2017-07-04       Impact factor: 6.716

2.  The effect of selection and referral biases for the treatment of localised prostate cancer with surgery or radiation.

Authors:  Christopher J D Wallis; Gerard Morton; Sender Herschorn; Ronald T Kodama; Girish S Kulkarni; Sree Appu; Bobby Shayegan; Roger Buckley; Arthur Grabowski; Steven A Narod; Robert K Nam
Journal:  Br J Cancer       Date:  2018-03-29       Impact factor: 7.640

3.  Associations of multimorbidity and patient-reported experiences of care with conservative management among elderly patients with localized prostate cancer.

Authors:  Ryan M Fiano; Gregory S Merrick; Kim E Innes; Malcolm D Mattes; Traci J LeMasters; Chan Shen; Usha Sambamoorthi
Journal:  Cancer Med       Date:  2020-07-06       Impact factor: 4.452

4.  Adoption of New Risk Stratification Technologies Within US Hospital Referral Regions and Association With Prostate Cancer Management.

Authors:  Michael S Leapman; Rong Wang; Henry S Park; James B Yu; Preston C Sprenkle; Michaela A Dinan; Xiaomei Ma; Cary P Gross
Journal:  JAMA Netw Open       Date:  2021-10-01

5.  Interventional oncology update.

Authors:  Alex Newbury; Chantal Ferguson; Daniel Alvarez Valero; Roberto Kutcher-Diaz; Lacey McIntosh; Ara Karamanian; Aaron Harman
Journal:  Eur J Radiol Open       Date:  2022-06-20
  5 in total

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