S1602 The Disproportionate Rise of Non-Cardia Primary Gastric Cancer Incidence Rates in Younger Women Is Driven by Black and White Race but Not Asian Race: A Population-Based Time-Trend Analysis Using the USCS Database

Abstract

Introduction: Recent population-based time-trend analysis of US nationwide databases showed a disproportional increase in non-cardia gastric cancer (NCGC) incidence rates in younger women (< 55 years) compared to counterpart men. However, the impact of race on the increasing trend in younger women has not been evaluated. Therefore, the aim of this study was to conduct sex and age-specific analysis of NCGC incidence rates among different race groups in a nationally representative US database. Methods: NCGC incidence rates per 100,000 population were obtained from the United States Cancer Statistics (USCS) database and were age-adjusted to the 2000 US population using SEER*Stat software (v8.4.1, NCI) between 2001-2018. The rates were stratified by age and sex and evaluated in patients of White, Black, and Asian races. Time trends of incidence rates were computed using Joinpoint Regression Software (v4.9.0.1, NCI) utilizing Monte Carlo Permutation analysis to identify the simplest segmented trend. Annual percentage change (APC) and average APC (AAPC) were estimated. Sex-specific pairwise comparison was conducted to assess identicalness and parallelism between the trends and the absolute AAPC difference was evaluated. Further age and sex-specific analysis was conducted in older (³55 years) and younger adults (< 55 years). A P-value cutoff of 0.05 was utilized. Results: A total of 169,517 patients were diagnosed with NCGC between 2001-2018 (45.4% women). Among Whites (11,991 patients; 47.4% women), incidence rates were decreasing in the overall age group and in older adults in both sexes. However, in younger White adults (17,790 patients; 49.9% women), incidence rates were increasing in women (AAPC=3.19, P< 0.001) at a significantly greater rate than in men (AAPC=1.58, P< 0.001) with an absolute AAPC difference of 1.60, P< 0.001. Similar results were seen in Black patients with a greater absolute AAPC difference between younger Black women and men (2.23, P< 0.001). Among Asian adults (16,132 patients; 46.4% women), there was no statistical difference in trends between women and men in all age groups (Table and Figure). Conclusion: Nationwide data from the USCS database, covering ≈100% of US population, showed a greater increase in NCGC incidence among younger White and Black women compared to counterpart men. However, this disproportionate increase was not seen in the Asian race. Future research should aim to evaluate risk factors for the increasing trend in younger women.Figure 1.: Sex-specific Trends and Age-Adjusted Incidence Rates Per 100,000 Population for Non-Cardia Gastric Cancer Among Different Age and Race-Specific Groups. A: The average annual percentage change (AAPC) is decreasing in older White men at a significantly greater rate than older White women (-1.31 vs -2.23, P=0.002). B: The average annual percentage change (AAPC) is increasing in younger White women at a significantly greater rate than younger White men (3.19 vs 1.58, P<0.001). C: The average annual percentage change (AAPC) is decreasing in older White women and men without a significant difference (1.57 vs 1.92, P=0.27). D: The average annual percentage change (AAPC) is increasing in younger Black women at a significantly greater rate than younger Black men (1.40 vs -0.83, P<0.001). E: The average annual percentage change (AAPC) is decreasing in older Asian women and men without a significant difference (-3.36 vs -3.34, P=0.97). F: The average annual percentage change (AAPC) is decreasing in younger Asian men but not in younger Asian women without a significant difference (-2.07 vs -0.87, P=0.48) Table 1. - Sex-Specific Trends for Non-Cardia Gastric Cancer Incidence Among Different Age and Race-Specific Groups Age group, y Cancer cases (N=169,517) a Trends b Sex-specific AAPC difference (95% CI) c Pairwise comparison P-values d Time period APC (95% CI) AAPC (95% CI) Sex-specific AAPC difference Coincidence e Parallelismf White All ages Women 53,115 (31.3%) 2001-2006 -1.85 (-3.56 to -0.12) -0.46 (-1.01 to 0.10) -1.29 (-1.93 to -0.65) < 0.001 < 0.001 < 0.001 2006-2018 0.13 (-0.33 to 0.59) Men 58,876 (34.7%) 2001-2006 -2.75 (-3.76 to -1.73) -1.74 (-2.07 to -1.42) 2006-2018 -1.32 (-1.59 to -1.05) Aged ≥55 Women 44,199 (26.1%) 2001-2008 -2.21 (-3.34 to -1.08) -1.31 (-1.86 to -0.76) -0.91 (-1.50 to -0.32) 0.002 < 0.001 < 0.001 2008-2018 -0.68 (-1.34 to -0.01) Men 49,953 (29.5%) 2001-2018 -2.23 (-2.45 to -2.00) -2.23 (-2.45 to -2.00) Aged < 55 # Women 8,882 (5.2%) 2001-2018 3.19 (2.75 to 3.62) 3.19 (2.75 to 3.62) -1.60 (-2.23 to -0.97) < 0.001 < 0.001 0.002 Men 8,908 (5.3%) 2001-2018 1.58 (1.06 to 2.11) 1.58 (1.06 to 2.11) Black All ages Women 14,945 (8.8%) 2001-2018 -1.04 (-1.50 to -0.57) -1.04 (-1.50 to -0.57) -0.73 (-1.32 to -0.14) 0.02 < 0.001 0.008 Men 18,118 (10.7%) 2001-2018 -1.77 (-2.20 to -1.34) -1.77 (-2.20 to -1.34) Aged ≥55 Women 11,969 (7.1%) 2001-2018 -1.57 (-2.08 to -1.05) -1.57 (-2.08 to -1.05) -0.36 (-0.98 to 0.27) 0.27 < 0.001 0.19 Men 14,494 (8.6%) 2001-2018 -1.92 (-2.36 to -1.48) -1.92 (-2.36 to -1.48) Aged < 55 # Women 3,624 (2.1%) 2001-2018 1.40 (0.46 to 2.34) 1.40 (0.46 to 2.34) -2.23 (-3.33 to -1.13) < 0.001 < 0.001 0.02 Men 2,976 (1.8%) 2001-2018 -0.83 (-1.55 to -0.11) -0.83 (-1.55 to -0.11) Asian All ages Women 7,480 (4.4%) 2001-2018 -2.90 (-3.73 to -2.43) -2.90 (-3.73 to -2.43) -0.29 (-0.93 to 0.35) 0.37 < 0.001 0.17 Men 8,652 (5.1%) 2001-2018 -3.19 (-3.70 to -2.68) -3.19 (-3.70 to -2.68) Aged ≥55 Women 5,785 (3.4%) 2001-2018 -3.36 (-3.88 to -2.83) -3.36 (-3.88 to -2.83) 0.01 (-0.65 to 0.67) 0.97 < 0.001 0.97 Men 7,100 (4.2%) 2001-2018 -3.34 (-3.83 to -2.86) -3.34 (-3.83 to -2.86) Aged < 55 # Women 1,694 (1.0%) 2001-2003 11.64 (-7.03 to 34.06) -0.87 (-4.02 to 2.38) -1.20 (-4.54 to 2.14) 0.48 0.07 0.24 2003-2010 -4.81 (-7.50 to -2.04) 2011-2013 10.44 (-6.07 to 29.86) 2013-2018 -6.23 (-9.34 to -3.02) Men 1,550 (0.9%) 2013-2018 -2.07 (-3.09 to -1.05) -2.07 (-3.09 to -1.05) aData are presented as count numbers followed by percentages of the count numbers from the total cases of cancer in the database.bTime-trends were computed using Joinpoint Regression Program (v4.9.0.1, NCI) with 3 maximum joinpoints allowed (4-line segments).cA negative value indicates a greater AAPC in women compared to men.dTests whether sex-specific trends were identical. A significant P-value indicates that the trends were not identical (i.e., they had different mortality rates and coincidence was rejected).eTests whether sex-specific trends were parallel. A significant P-value indicates that the trends were not parallel (i.e., parallelism was rejected).#Primary outcomes.