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No racial disparities in stage at diagnosis – is Nevada doing better for cervical cancer?
Methods: The study population consisted of 1,434 women diagnosed with CC between 1995 and 2008, identified through the Nevada Central Cancer Registry. Multiple logistic regression modeling was used to calculate the odds of being diagnosed at an advanced stage in relation to localized stage.
Results: Adjusted for age, SES, marital status, insurance, histology, and diagnosis period; CC stage at diagnosis for Blacks [OR=0.8, 95% CI: 0.53-1.38], Hispanics [OR=0.9, 95%CI: 0.63-1.21], and American Indian women [OR=0.8, 95% CI: 0.25-2.72] were not significantly different compared to White women. Women who were uninsured [OR =1.9, 95% CI: 1.30-2.80] or insured under Medicaid [OR=2.8, 95% CI: 1.80-4.59] were more likely to be diagnosed at late stage than privately insured women.
Conclusions: Findings of this study indicate an absence of disparities in CC stage at diagnosis between minority groups and Whites, which could represent a progressive step in Public Health. However, given the unique public health context in the Silver State, these results suggest unfavorable patterns of early detection among Whites. Lower CC screening occurs among Nevadan Whites than national average. Consequently, evidence-based interventions to increase prevention levels among White Nevadan residents may be warranted.
Learning Areas:
Biostatistics, economicsEpidemiology
Learning Objectives:
Assess the determinants of cervical cancer stage at diagnosis in Nevadan females.
Analyze if differences exist between race/ethnic groups in terms of cervical cancer stage at diagnosis.
Identify public health measures warranted to dilute any ascertained disparities in prevention and early detection of cervical cancer.
Keyword(s): Cancer, Prevention
Qualified on the content I am responsible for because: I am a MPH candidate working on cancer epidemiology and surveillance projects under the supervision of Dr. Paulo Pinheiro who has 16+ years of experience in this field. I have training in data anlysis, data management, study designs, and research methods. I have worked with these datasets: Nevada Central Cancer Registry (NCCR), Surveillance, Epidemiology and End Results (SEER), and SEER-Medicare (ongoing training).
Any relevant financial relationships? No
I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.