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Influence Of Insurance,Marital Status,and Socioeconomic Indicators On Prognoses Of Cancer Patients In America

Posted on:2021-02-14Degree:MasterType:Thesis
Country:ChinaCandidate:G Q ChengFull Text:PDF
GTID:2404330623981348Subject:Biochemistry and Molecular Biology
Abstract/Summary:PDF Full Text Request
Cancer is regarded as an important public health issue worldwide.Exploring factors that have influence on the survival outcome of cancer patients would help deliver better management and care to them,thus improving their prognoses.Most studies have focused on the effect of types and stages of cancers,the nature of cancer cells,previous health condition,and treatment response on cancer prognosis,but ignored the socioeconomic status(SES)influence.Previous researches indicates that SES at both individual and regional levels could explain the disparity in the survival of patients with a certain cancer,but as each cancer is of its unique nature,SES may contribute differently to the prognosis of varied cancer types.In the present study,we collected patient records of six cancer cohorts based on the site of tumor from Surveillance,Epidemiology,and End Results(SEER)Database,and examined the effect of regional socioeconomic factors,along with the individual insurance and marital status on patients' prognosis across varied cancer types with machine learning methods.We further selected different regional SES indicators and explored their influence on patient prognoses across different cancer types.Our study demonstrates that regional socioeconomic factors can contribute to over 30% influence on certain cancers,married patients and those with private insurance/supplement would enjoy more satisfying prognoses,and being in an advantageous regional SES has a very positive impact on their survival.We also found that varied socioeconomic indicators have different impacts on patients of varied cancer types,which raises awareness of the important role of government on improving the survival of cancer patients and eliminating health inequity across regions.
Keywords/Search Tags:cancer prognosis, SEER, SES, machine learning, survival analysis
PDF Full Text Request
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