A model established using marital status and other factors from the Surveillance, Epidemiology, and End Results database for early stage gastric cancer

Zhang, Lixiang; Zhou, Baichuan; Luo, Pei; Xu, Aiming; Han, Wenxiu; Wei, Zhijian

doi:10.1136/jim-2021-002285

Cited by 2 publications

(2 citation statements)

References 28 publications

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“…Marital status is an interesting predictor of cancer outcomes. A 2022 study demonstrates that married patients have superior survival after GC diagnosis, compared to those who are single or separated, suggesting that social support provides beneficial outcomes regarding early detection, treatment and survival [ 45 ].…”

Section: Discussionmentioning

confidence: 99%

Demographics, distance to gastrointestinal specialists, and social deprivation are associated with advanced stage of gastrointestinal cancer diagnosis

Kumar

2024

aog

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Background Gastrointestinal (GI) luminal cancers can be detected at early stages by endoscopic procedures. Place-based factors, such as social deprivation and distance to specialist care, are under-investigated with regard to the stage of diagnosis. Methods This was a retrospective cohort study among persons ≥18 years of age in the Florida Cancer Data System, a population-based cancer incidence registry. We included persons diagnosed with esophageal cancer, gastric canceror colorectal cancer, with at least 1 measure of geographic location during the period January 1, 1981, to December 31, 2016. Multivariate multinomial logistic regression was used to identify factors associated with the stage of diagnosis, including social deprivation and proximity to GI care. Results Among 379,054 persons, the median age was 71 years, and 54% were male. Distant stage disease was significantly less likely than local stage in those of non-Hispanic/Latino ethnicity (odds ratio [OR] 0.92, 95% confidence interval [CI] 0.89-0.94, P<0.001). Distant disease was more likely in African Americans (OR 1.30, 95%CI 1.26-1.34) and Asians (OR 1.41, 95%CI 1.27-1.56, P<0.001), with each 5-min increase in travel time to specialists, (OR 1.02, 95%CI 1.01-1.02, P<0.001), and with each 10-point increase in Social Deprivation Index (OR 1.01, 95%CI 1.01-1.02, P<0.001). Conclusions A greater distance from care and living in areas with increased deprivation are associated with an advanced stage of diagnosis and should be recipients of policy-driven efforts to improve access to care. That the strongest risk factors include minority race and ethnicity underlines the complexity of healthcare disparities.

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Section: Discussionmentioning

confidence: 99%

Demographics, distance to gastrointestinal specialists, and social deprivation are associated with advanced stage of gastrointestinal cancer diagnosis

Kumar

2024

aog

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“…However, the international tumor-node-metastasis (TNM) staging system only relies on anatomical and pathological features for disease assessment, without considering many other important relevant factors, such as age, sex, and other demographic characteristics [86,87]. Numerous studies have shown that the clinical stage alone is not sufficient to predict the prognosis of patients with cancer [87][88][89][90]; therefore, further analysis of demographic characteristics is necessary [36].…”

Section: Demographic Characteristicsmentioning

confidence: 99%

Critical Analysis of Risk Factors and Machine-Learning-Based Gastric Cancer Risk Prediction Models: A Systematic Review

Fan

Miao

et al. 2023

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The gastric cancer risk prediction model used for large-scale gastric cancer screening and individual risk stratification is an artificial intelligence tool that combines clinical diagnostic data with a classification algorithm. The ability to automatically make a quantitative assessment of complex clinical data contributes to increased accuracy for diagnosis with higher efficiency, significantly reducing the incidence of advanced gastric cancer. Previous studies have explored the predictive performance of gastric cancer risk prediction models, as well as the predictive factors and algorithms between each model, but have reached controversial conclusions. Thus, the performance of current machine-learning-based gastric cancer risk prediction models alongside the clinical relevance of different predictive factors needs to be evaluated to help build more efficient and feasible models in the future. In this systematic review, we summarize the current research progress related to the gastric cancer risk prediction model; discuss the predictive factors and methods used to construct the model; analyze the role of important predictive factors in gastric cancer, the preference of the selected classification algorithm, and the emphasis of evaluation criteria; and provide suggestions for the subsequent construction and improvement of the gastric cancer risk prediction model. Finally, we propose an improved approach based on the ethical issues of artificial intelligence in medicine to realize the clinical application of the gastric cancer risk prediction model in the future.

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A model established using marital status and other factors from the Surveillance, Epidemiology, and End Results database for early stage gastric cancer

Cited by 2 publications

References 28 publications

Demographics, distance to gastrointestinal specialists, and social deprivation are associated with advanced stage of gastrointestinal cancer diagnosis

Demographics, distance to gastrointestinal specialists, and social deprivation are associated with advanced stage of gastrointestinal cancer diagnosis

Critical Analysis of Risk Factors and Machine-Learning-Based Gastric Cancer Risk Prediction Models: A Systematic Review

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