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. 2022 Mar 1;139(3):440-442.
doi: 10.1097/AOG.0000000000004676.

The Changing Landscape of Gynecologic Cancer Mortality in the United States

Affiliations

The Changing Landscape of Gynecologic Cancer Mortality in the United States

Angela N Giaquinto et al. Obstet Gynecol. .

Abstract

Uterine corpus cancer mortality is now similar to that for ovarian cancer, and the disproportionate burden among Black women is widening.

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Conflict of interest statement

Financial Disclosure The authors did not report any potential conflicts of interest.

Figures

Figure 1.
Figure 1.
Trends in uterine corpus and ovarian cancer mortality rates by race and ethnicity in the United States, 1990–2019. Deaths were classified according to International Classification of Diseases, Ninth Revision (ICD-9) codes 179 and 182 for uterus and 183.0 for ovary during years 1990–1998 and ICD-10 codes C54 and C55 for uterus and C56 for ovary during 1999–2019. All races and ethnicities (A), uterus:ovary rate ratio (B), non-Hispanic White (C), non-Hispanic Black (D), non-Hispanic Asian/Pacific Islander (E), Hispanic (F). American Indian/Alaskan Native rates not shown due to sparse data. Rates were age-adjusted to the 2000 U.S. standard population; data shown in C–F exclude Louisiana, New Hampshire, and Oklahoma due to incomplete ethnicity information. *The average annual percent change (average annual percent change) was calculated using Joinpoint version 4.9.0.0, based on up to 5 Joinpoints, and all were statistically significantly different from zero (2-sided P<.05). Mortality rate ratio calculated using Tiwari Method.
Figure 2.
Figure 2.
Uterine cancer mortality rates and rate ratios by race and ethnicity in the United States, 1990–1994 vs. 2015–2019. Rates were age-adjusted to the 2000 U.S. standard population and exclude Louisiana, New Hampshire, and Oklahoma due to incomplete ethnicity data. American Indian/Alaskan Native rates not shown due to sparse data. *Mortality rate ratios were calculated using the Tiwari method with non-Hispanic Whites as the referent group and tested for statistical significance between 1990–1994 and 2015–2019 with SAS 9.4 Wald Chi-Square test. All rate ratios were statistically significantly different (P<.001).

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