Literature DB >> 17420977

Predictors of comprehensive surgical treatment in patients with ovarian cancer.

Barbara A Goff1, Barbara J Matthews, Eric H Larson, C Holly A Andrilla, Michelle Wynn, Denise M Lishner, Laura-Mae Baldwin.   

Abstract

BACKGROUND: Providing appropriate surgical treatment for women with ovarian cancer is one of the most effective ways to improve ovarian cancer outcomes. In this study, the authors identified factors that were associated with a measure of comprehensive surgery, so that interventions may be targeted appropriately to improve surgical care.
METHODS: Using Healthcare Cost and Utilization Project hospital discharge data from 1999 to 2002 for 9 states, the authors identified 10,432 admissions of women who had an International Classification of Disease, 9th Revision (ICD-9) primary diagnosis of ovarian cancer and who had undergone oophorectomy. Based on National Institutes of Health Consensus Panel recommendations, surgeries were categorized as comprehensive by using ICD-9 diagnosis and procedure codes. Logistic regression analysis using data from 5 states with a full set of variables (n = 6854 patients)was used to identify factors that were associated with the receipt of comprehensive surgical care.
RESULTS: Overall, 66.9% of admissions (range, 46.3-80.8% of admissions) received comprehensive surgery. Factors that were associated independently with comprehensive surgical care included age (ages 21-50 years vs ages 71-80 years or > or = 81 years), race (Caucasian vs African American or Hispanic), payer (private insurance vs Medicaid), cancer stage (advanced vs early), annual surgeon volume (low/medium [2-9 surgeries per year] or high [>10 surgeries per year] vs very low [1 surgery per year]), and surgeon specialty (gynecologic oncologists vs obstetrician gynecologists or general surgeons). Among nonteaching hospitals, medium-volume hospitals (10-19 ovarian cancer surgeries per year) and high-volume hospitals (> or = 20 surgeries per year) had significantly higher comprehensive surgery rates than low-volume facilities (1-9 surgeries per year). Volume did not influence comprehensive surgery rates in teaching hospitals.
CONCLUSIONS: Many women with ovarian cancer, especially those in poor, elderly, or minority groups, are not receiving recommended comprehensive surgery. Efforts should be made to ensure that all women with ovarian cancer, especially those in vulnerable populations, have the opportunity to receive care from centers or surgeons with higher comprehensive surgery rates.

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Mesh:

Year:  2007        PMID: 17420977     DOI: 10.1002/cncr.22604

Source DB:  PubMed          Journal:  Cancer        ISSN: 0008-543X            Impact factor:   6.860


  45 in total

1.  Spatial analysis of adherence to treatment guidelines for advanced-stage ovarian cancer and the impact of race and socioeconomic status.

Authors:  Robert E Bristow; Jenny Chang; Argyrios Ziogas; Hoda Anton-Culver; Veronica M Vieira
Journal:  Gynecol Oncol       Date:  2014-03-25       Impact factor: 5.482

2.  Comparison of a novel multiple marker assay vs the Risk of Malignancy Index for the prediction of epithelial ovarian cancer in patients with a pelvic mass.

Authors:  Richard G Moore; Moune Jabre-Raughley; Amy K Brown; Katina M Robison; M Craig Miller; W Jeffery Allard; Robert J Kurman; Robert C Bast; Steven J Skates
Journal:  Am J Obstet Gynecol       Date:  2010-05-14       Impact factor: 8.661

3.  Spatial analysis of advanced-stage ovarian cancer mortality in California.

Authors:  Robert E Bristow; Jenny Chang; Argyrios Ziogas; Daniel L Gillen; Lu Bai; Veronica M Vieira
Journal:  Am J Obstet Gynecol       Date:  2015-01-31       Impact factor: 8.661

Review 4.  Gynecologic cancer disparities: a report from the Health Disparities Taskforce of the Society of Gynecologic Oncology.

Authors:  Yvonne Collins; Kevin Holcomb; Eloise Chapman-Davis; Dineo Khabele; John H Farley
Journal:  Gynecol Oncol       Date:  2014-01-07       Impact factor: 5.482

5.  Impact of National Cancer Institute Comprehensive Cancer Centers on ovarian cancer treatment and survival.

Authors:  Robert E Bristow; Jenny Chang; Argyrios Ziogas; Belinda Campos; Leo R Chavez; Hoda Anton-Culver
Journal:  J Am Coll Surg       Date:  2015-02-14       Impact factor: 6.113

6.  The Effect of Gynecologic Oncologist Availability on Ovarian Cancer Mortality.

Authors:  Sherri L Stewart; Darryl Cooney; Shawn Hirsch; Lauren Westervelt; Thomas B Richards; Sun Hee Rim; Cheryll C Thomas
Journal:  World J Obstet Gynecol       Date:  2014-05-10

7.  Observed-to-expected ratio for adherence to treatment guidelines as a quality of care indicator for ovarian cancer.

Authors:  Valerie B Galvan-Turner; Jenny Chang; Argyrios Ziogas; Robert E Bristow
Journal:  Gynecol Oncol       Date:  2015-09-24       Impact factor: 5.482

8.  Socioeconomic status as a predictor of adherence to treatment guidelines for early-stage ovarian cancer.

Authors:  Melissa Hodeib; Jenny Chang; Fong Liu; Argyrios Ziogas; Sarah Dilley; Leslie M Randall; Hoda Anton-Culver; Robert E Bristow
Journal:  Gynecol Oncol       Date:  2015-04-22       Impact factor: 5.482

9.  Disparities in ovarian cancer care quality and survival according to race and socioeconomic status.

Authors:  Robert E Bristow; Matthew A Powell; Noor Al-Hammadi; Ling Chen; J Philip Miller; Phillip Y Roland; David G Mutch; William A Cliby
Journal:  J Natl Cancer Inst       Date:  2013-03-28       Impact factor: 13.506

10.  Does equal treatment yield equal outcomes? The impact of race on survival in epithelial ovarian cancer.

Authors:  Mishka Terplan; Sarah Temkin; Ana Tergas; Ernst Lengyel
Journal:  Gynecol Oncol       Date:  2008-09-26       Impact factor: 5.482

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