Addressing the Gap: Racial Disparities and Public Health Strategies in the Epidemiology of Gastrointestinal Stromal Tumors

被引:0
|
作者
Rammohan, Rajmohan [1 ]
Joy, Melvin [2 ]
Magam, Sai Greeshma [2 ]
Lau, Wing Hang [2 ]
Natt, Dilman [2 ]
Tadikonda, Abhishek [2 ]
Magam, Sai Reshma [2 ]
Pannikodu, Leeza [2 ]
Desai, Jiten [2 ]
Jiyani, Rucha [1 ]
Sheikh, Saher [2 ]
Gomez, Sandra [3 ]
Bunting, Susan [2 ]
Anand, Prachi [4 ]
Subramani, Krishnaiyer [1 ]
Mustacchia, Paul [3 ]
机构
[1] Nassau Univ, Med Ctr, Gastroenterol, East Meadow, NY 11554 USA
[2] Nassau Univ, Internal Med, Med Ctr, East Meadow, NY USA
[3] Nassau Univ, Gastroenterol & Hepatol, Med Ctr, East Meadow, NY USA
[4] Nassau Univ, Rheumatol, Med Ctr, East Meadow, NY USA
关键词
Categories; Gastroenterology; Epidemiology/Public healthcare equity; healthcare gap; pearson correlation coefficient; pearson correlation; linear regression analysis; linear regression; race inequities; race; gist;
D O I
10.7759/cureus.61743
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background Gastrointestinal stromal tumors (GISTs) represent the most common mesenchymal neoplasms of the gastrointestinal tract, arising from the interstitial cells of Cajal. These tumors bridge the nervous system and muscular layers of the gastrointestinal tract, playing a crucial role in the digestive process. The incidence of GISTs demonstrates notable variations across different racial and ethnic groups, underscoring the need for in-depth analysis to understand the interplay of genetic, environmental, and socioeconomic factors behind these disparities. Linear regression analysis is a pivotal statistical tool in such epidemiological studies, offering insights into the temporal dynamics of disease incidence and the impact of public health interventions. Methodology This investigation employed a detailed dataset from 2009 to 2020, documenting GIST incidences across Asian, African American, Hispanic, and White populations. A meticulous preprocessing routine prepared the dataset for analysis, which involved data cleaning, normalization of racial terminologies, and aggregation by year and race. Linear regression models and Pearson correlation coefficients were applied to analyze trends and correlations in GIST incidences across the different racial groups, emphasizing an understanding of temporal patterns and racial disparities in disease incidence. Results The study analyzed GIST cases among four racial groups, revealing a male predominance (53.19%) and an even distribution of cases across racial categories: Whites (27.66%), Hispanics (25.53%), African Americans (24.47%), and Asians (22.34%). Hypertension was the most common comorbidity (32.98%), followed by heart failure (28.72%). The linear regression analysis for Asians showed a decreasing trend in GIST incidences with a slope of -0.576, an R -squared value of 0.717, and a non -significant p -value of 0.153. A significant increasing trend was observed for Whites, with a slope of 0.581, an R -squared value of 0.971, and a p -value of 0.002. African Americans exhibited a moderate positive slope of 0.277 with an R -squared value of 0.470 and a p -value of 0.201, indicating a non -significant increase. Hispanics showed negligible change over time with a slope of -0.095, an R -squared value of 0.009, and a p -value of 0.879, suggesting no significant trend. Conclusions This study examines GIST incidences across racial groups, revealing significant disparities. Whites show an increasing trend (p = 0.002), while Asians display a decreasing trend (p = 0.153), with stable rates in African Americans and Hispanics. Such disparities suggest a complex interplay of genetics, environment, and socioeconomic factors, highlighting the need for targeted research and interventions that address these differences and the systemic inequalities influencing GIST outcomes.
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页数:10
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