Original Article

Population-Based Analysis of Patient Age and Other Disparities in the Treatment of Ovarian Cancer in Central Appalachia and Kentucky

Authors: Robert M. Ore, MD, Quan Chen, PhD, Christopher P. DeSimone, MD, Rachel W. Miller, MD, Lauren A. Baldwin, MD, John R. van Nagell, MD, Bin Huang, PhD, Thomas C. Tucker, PhD, M. Symmes Johnson, MD, Tricia I. Fredericks, MD, Frederick R. Ueland, MD

Abstract

Objectives: Adherence to National Comprehensive Cancer Network (NCCN) guidelines for ovarian cancer treatment improves patient outcomes. The aim of this study was to assess disparities associated with ovarian cancer treatment in the state of Kentucky and central Appalachia.

Methods: Data on patients diagnosed as having ovarian cancer from 2007 through 2011 were extracted from administrative claims-linked Kentucky Cancer Registry data. NCCN compliance was defined by stage, grade, surgical procedure, and chemotherapy. Selection criteria were reviewed carefully to ensure data quality and accuracy. Descriptive analysis, logistic regression, and Cox regression analyses were performed to examine factors associated with guidelines compliance and survival.

Results: Most women were aged 65 years or older (62.5%) and had high-grade (65.9%) and advanced-stage (61.0%) ovarian cancer. Two-thirds of cases (65.9%) received NCCN-recommended treatment for ovarian cancer. The hazard ratio of death for women who did not receive NCCN-compliant care was 62% higher compared with the women who did receive NCCN-compliant treatment. Results from the logistic regression showed that NCCN-compliant treatment was more likely for women aged 65 to 74 years compared with women aged 20 to 49 years, late-stage compared with early-stage cancers, receipt of care at tertiary care hospitals, and privately insured compared with Medicaid or Medicare.

Conclusions: When the treatment of ovarian cancer did not follow NCCN recommendations, patients had a significantly higher risk of death. Women were less likely to receive NCCN-compliant care if they were younger (20–49 years), had early-stage disease, did not have private insurance, or had care provided at a nontertiary care hospital.

This content is limited to qualifying members.

Existing members, please login first.

If you have an existing account please login now to access this article or view your purchase options.

Purchase only this article ($15)

Create a free account, then purchase this article to download or access it online for 24 hours.

Purchase an SMJ online subscription ($75)

Create a free account, then purchase a subscription to get complete access to all articles for a full year.

Purchase a membership plan (fees vary)

Premium members can access all articles plus recieve many more benefits. View all membership plans and benefit packages.

References

1. Harlan LC, Clegg LX, Trimble EL. Trends in surgery and chemotherapy for women diagnosed with ovarian cancer in the United States. J Clin Oncol 2003;21:3488-3494.
 
2. Bristow RE, Chang J, Ziogas A, et al. Adherence to treatment guidelines for ovarian cancer as a measure of quality care. Obstet Gynecol 2013;121:1226-1234.
 
3. Earle CC, Schrag D, Neville BA, et al. Effect of surgeon specialty on processes of care and outcomes for ovarian cancer patients. J Natl Cancer Inst 2006;98:172-180.
 
4. Carney ME, Lancaster JM, Ford C, et al. A population-based study of patterns of care for ovarian cancer: who is seen by a gynecologic oncologist and who is not? Gynecol Oncol 2002;84:36-42.
 
5. Bristow RE, Chang J, Ziogas A, et al. Impact of National Cancer Institute Comprehensive Cancer Centers on ovarian cancer treatment and survival. J Am Coll Surg 2015;220:940-950.
 
6. Hodeib M, Chang J, Liu F, et al. Socioeconomic status as a predictor of adherence to treatment guidelines for early-stage ovarian cancer. Gynecol Oncol 2015;138:121-127.
 
7. Bristow RE, Chang J, Ziogas A, et al. Spatial analysis of adherence to treatment guidelines for advanced-stage ovarian cancer and the impact of race and socioeconomic status. Gynecol Oncol 2014;134:60-67.
 
8. Bristow RE, Chang J, Ziogas A, et al. Sociodemographic disparities in advanced ovarian cancer survival and adherence to treatment guidelines. Obstet Gynecol 2015;125:833-842.
 
9. Surveillance, Epidemiology, and End Results Program. Cancer stat facts: ovarian cancer. https://seer.cancer.gov/statfacts/html/ovary.html. Accessed April 5, 2017.
 
10. Erickson BK, Martin JY, Shah MM, et al. Reasons for failure to deliver National Comprehensive Cancer Network (NCCN)-adherent care in the treatment of epithelial ovarian cancer at an NCCN cancer center. Gynecol Oncol 2014;133:142-146.
 
11. Fleming ST, Mackley HB, Camacho F, et al. Clinical, sociodemographic, and service provider determinants of guideline concordant colorectal cancer care for Appalachian residents. J Rural Health 2014;30:27-39.
 
12. Kentucky Cancer Registry. Homepage. https://www.kcr.uky.edu. Accessed February 28, 2017.
 
13. National Comprehensive Cancer Network. NCCN history. https://www.nccn.org/about/history.aspx. Accessed November 16, 2017.
 
14. Goff BA, Matthews BJ, Wynn M, et al. Ovarian cancer: patterns of surgical care across the United States. Gynecol Oncol 2006;103:383-390.
 
15. American College of Obstetricians and Gynecologists. ACOG Practice Bulletin. Management of adnexal masses. Obstet Gynecol 2007;110: 201-214.
 
16. Chan JK, Urban R, Cheung MK, et al. Ovarian cancer in younger vs older women: a population-based analysis. Br J Cancer 2006;95:1314-1320.
 
17. Giede KC, Kieser K, Dodge J, et al. Who should operate on patients with ovarian cancer? An evidence-based review. Gynecol Oncol 2005;99:447-461.
 
18. Joslin CE, Brewer KC, Davis FG, et al. The effect of neighborhood-level socioeconomic status on racial differences in ovarian cancer treatment in a population-based analysis in Chicago. Gynecol Oncol 2014;135:285-291.
 
19. Yao N, Alcalá HE, Anderson R, et al. Cancer disparities in rural Appalachia: incidence, early detection, and survivorship. J Rural Health 2017;33:375-381.
 
20. Ueland FR, DePriest PD, Pavlik EJ, et al. Preoperative differentiation of malignant from benign ovarian tumors: the efficacy of morphology indexing and Doppler flow sonography. Gynecol Oncol 2003;91:46-50.
 
21. Timmerman D, Van Calster B, Testa AC, et al. Ovarian cancer prediction in adnexal masses using ultrasound-based logistic regression models: a temporal and external validation study by the IOTA group. Ultrasound Obstet Gynecol 2010;36:226-234.
 
22. Pavlik EJ, Ueland FR, Miller RW, et al. Frequency and disposition of ovarian abnormalities followed with serial transvaginal ultrasonography. Obstet Gynecol 2013;122( 2 Pt 1 ):210-217.
 
23. Elder JW, Pavlik EJ, Long A, et al. Serial ultrasonographic evaluation of ovarian abnormalities with a morphology index. Gynecol Oncol 2014;135:8-12.
 
24. Ueland FR, Desimone CP, Seamon LG, et al. Effectiveness of a multivariate index assay in the preoperative assessment of ovarian tumors. Obstet Gynecol 2011;117:1289-1297.
 
25. Moore RG, Miller MC, Disilvestro P, et al. Evaluation of the diagnostic accuracy of the risk of ovarian malignancy algorithm in women with a pelvic mass. Obstet Gynecol 2011;118( 2 Pt 1 ):280-288.
 
26. Bristow RE, Smith A, Zhang Z, et al. Ovarian malignancy risk stratification of the adnexal mass using a multivariate index assay. Gynecol Oncol 2013;128:252-259.
 
27. Coleman RL, Herzog TJ, Chan DW, et al. Validation of a second-generation multivariate index assay for malignancy risk of adnexal masses. Am J Obstet Gynecol 2016;215:82.e1-82.e11.
 
28. Longoria TC, Ueland FR, Zhang Z, et al. Clinical performance of a multivariate index assay for detecting early-stage ovarian cancer. Am J Obstet Gynecol 2014;210:78.e1-e9.
 
29. Goodrich ST, Bristow RE, Santoso JT, et al. The effect of ovarian imaging on the clinical interpretation of a multivariate index assay. Am J Obstet Gynecol 2014;211:65.e1-65.e11.