Literature DB >> 24566445

Specialty bias in treatment recommendations and quality of life among radiation oncologists and urologists for localized prostate cancer.

S P Kim1, C P Gross2, P L Nguyen, P Y Nguyen3, M C Smaldone4, R H Thompson5, N D Shah6, A Kutikov4, L C Han7, R J Karnes5, J Y Ziegenfuss8, J C Tilburt9.   

Abstract

BACKGROUND: Given the importance of physician attitudes about different treatments and the quality of life (QOL) in prostate cancer, we performed a national survey of specialists to assess treatment recommendations and perceptions of treatment-related survival and QOL.
METHODS: We mailed a self-administered survey instrument to a random sample of 1366 specialists in the U.S. Respondents were asked for treatment recommendations and survival that varied by PSA levels and Gleason scores and estimate QOL outcomes. Pearson's chi-square and multivariable regression models were used to test for differences in each outcome.
RESULTS: Response rates were similar for radiation oncologists (52.6%) and urologists (52.3%; P=0.92). Across all risk strata, urologists were more likely to recommend surgery than were radiation oncologists, for conditions ranging from PSA>20 and Gleason score 8-10 (35.2 vs. 0.2%; P<0.001) to PSA 4-10 and Gleason score 7 (87.5 vs. 20.9%; P<0.001). Radiation oncologists were also more likely to recommend radiation therapy relative to urologists (all P<0.001). From low- to high-risk prostate cancer, radiation oncologists and urologists perceived their treatment as being better for improving survival (all P<0.001). Each specialty also viewed their treatment as having less urinary incontinence (all P<0.001).
CONCLUSIONS: Radiation oncologists and urologists both prefer the treatment modalities they offer, perceive them to be more effective and to lead to a better QOL. Patients may be receiving biased information, and a truly informed consent process with shared decision-making may be possible only if they are evaluated by both specialties before deciding upon a treatment course.

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Year:  2014        PMID: 24566445     DOI: 10.1038/pcan.2014.3

Source DB:  PubMed          Journal:  Prostate Cancer Prostatic Dis        ISSN: 1365-7852            Impact factor:   5.554


  7 in total

1.  A national survey of radiation oncologists and urologists on prediction tools and nomograms for localized prostate cancer.

Authors:  Boris Gershman; Paul Maroni; Jon C Tilburt; Robert J Volk; Badrinath Konety; Charles L Bennett; Alexander Kutikov; Marc C Smaldone; Victor Chen; Simon P Kim
Journal:  World J Urol       Date:  2019-01-22       Impact factor: 4.226

2.  How Men with Prostate Cancer Choose Specialists: A Qualitative Study.

Authors:  Tammy Jiang; Christian H Stillson; Craig Evan Pollack; Linda Crossette; Michelle Ross; Archana Radhakrishnan; David Grande
Journal:  J Am Board Fam Med       Date:  2017 Mar-Apr       Impact factor: 2.657

3.  Opportunities for theory-informed decision science in cancer control.

Authors:  Arielle S Gillman; Rebecca A Ferrer
Journal:  Transl Behav Med       Date:  2021-11-30       Impact factor: 3.046

4.  Personal prostate-specific antigen screening and treatment choices for localized prostate cancer among expert physicians.

Authors:  Christopher Wallis; Douglas Cheung; Laurence Klotz; Venu Chalasani; Ricardo Leao; Juan Garisto; Gerard Morton; Robert Nam; Ian Tannock; Raj Satkunasivam
Journal:  Can Urol Assoc J       Date:  2017-12-01       Impact factor: 1.862

5.  Early experience with Watson for Oncology: a clinical decision-support system for prostate cancer treatment recommendations.

Authors:  Seong Hyeon Yu; Myung Soo Kim; Ho Seok Chung; Eu Chang Hwang; Seung Il Jung; Taek Won Kang; Dongdeuk Kwon
Journal:  World J Urol       Date:  2020-04-25       Impact factor: 4.226

6.  Individual prognosis at diagnosis in nonmetastatic prostate cancer: Development and external validation of the PREDICT Prostate multivariable model.

Authors:  David R Thurtle; David C Greenberg; Lui S Lee; Hong H Huang; Paul D Pharoah; Vincent J Gnanapragasam
Journal:  PLoS Med       Date:  2019-03-12       Impact factor: 11.069

7.  Decision Science Can Inform Clinical Trade-Offs Regarding Cardiotoxic Cancer Treatments.

Authors:  Arielle S Gillman; Jacqueline B Vo; Anju Nohria; Rebecca A Ferrer
Journal:  JNCI Cancer Spectr       Date:  2021-06-24
  7 in total

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