Socioeconomic factors are associated with the prognosis of Thyroid Cancer

Li, Yu; Huang, Da; Wang, Baoxin; Mao, Wei; Chen, Xinwei; Dong, Pin

doi:10.7150/jca.52329

Cited by 17 publications

(13 citation statements)

References 15 publications

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“…Compared with TT, one-sided thyroid LO plus IO or partial thyroidectomy also can achieve a good prognosis, which is of positive significance for guiding clinical practice. In recent years, some studies have revealed that marital status is closely related to the prognosis of TC (11,12,53) and married TC patients have a significant survival advantage. A study from 126,160 patients with all types of TC showed that widowed or divorced patients were closely related to poor CSS and overall survival (OS) (11).…”

Section: Discussionmentioning

confidence: 99%

“…In recent years, some studies have revealed that marital status is closely related to the prognosis of TC (11,12,53) and married TC patients have a significant survival advantage. A study from 126,160 patients with all types of TC showed that widowed or divorced patients were closely related to poor CSS and overall survival (OS) (11). Shi et al explored 61077 DTC patients and found that widowed patients had a higher tumor mortality in DTC (12).…”

Section: Discussionmentioning

confidence: 99%

“…However, at present, for the question which surgical method is the best for improving the prognosis of patients, there is still a lack of long-term follow-up study. In recent years, some studies have indicated that sociological factors such as marital status have important impacts on TC ( 11 , 12 ), but this effect is unclear in patients suffering from FTC only. Other prognostic factors of FTC, such as race, histological type, regional environment, and lymphadenectomy also need to be considered.…”

Section: Introductionmentioning

confidence: 99%

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Surgical Methods and Social Factors Are Associated With Long-Term Survival in Follicular Thyroid Carcinoma: Construction and Validation of a Prognostic Model Based on Machine Learning Algorithms

Mao

Huang

et al. 2022

Front. Oncol.

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BackgroundThis study aimed to establish and verify an effective machine learning (ML) model to predict the prognosis of follicular thyroid cancer (FTC), and compare it with the eighth edition of the American Joint Committee on Cancer (AJCC) model.MethodsKaplan-Meier method and Cox regression model were used to analyze the risk factors of cancer-specific survival (CSS). Propensity-score matching (PSM) was used to adjust the confounding factors of different surgeries. Nine different ML algorithms,including eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), Random Forests (RF), Logistic Regression (LR), Adaptive Boosting (AdaBoost), Gaussian Naive Bayes (GaussianNB), K-Nearest Neighbor (KNN), Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP),were used to build prognostic models of FTC.10-fold cross-validation and SHapley Additive exPlanations were used to train and visualize the optimal ML model.The AJCC model was built by multivariate Cox regression and visualized through nomogram. The performance of the XGBoost model and AJCC model was mainly assessed using the area under the receiver operating characteristic (AUROC).ResultsMultivariate Cox regression showed that age, surgical methods, marital status, T classification, N classification and M classification were independent risk factors of CSS. Among different surgeries, the prognosis of one-sided thyroid lobectomy plus isthmectomy (LO plus IO) was the best, followed by total thyroidectomy (hazard ratios: One-sided thyroid LO plus IO, 0.086[95% confidence interval (CI),0.025-0.290], P<0.001; total thyroidectomy (TT), 0.490[95%CI,0.295-0.814], P=0.006). PSM analysis proved that one-sided thyroid LO plus IO, TT, and partial thyroidectomy had no significant differences in long-term prognosis. Our study also revealed that married patients had better prognosis than single, widowed and separated patients (hazard ratios: single, 1.686[95%CI,1.146-2.479], P=0.008; widowed, 1.671[95%CI,1.163-2.402], P=0.006; separated, 4.306[95%CI,2.039-9.093], P<0.001). Among different ML algorithms, the XGBoost model had the best performance, followed by Gaussian NB, RF, LR, MLP, LightGBM, AdaBoost, KNN and SVM. In predicting FTC prognosis, the predictive performance of the XGBoost model was relatively better than the AJCC model (AUROC: 0.886 vs. 0.814).ConclusionFor high-risk groups, effective surgical methods and well marital status can improve the prognosis of FTC. Compared with the traditional AJCC model, the XGBoost model has relatively better prediction accuracy and clinical usage.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Surgical Methods and Social Factors Are Associated With Long-Term Survival in Follicular Thyroid Carcinoma: Construction and Validation of a Prognostic Model Based on Machine Learning Algorithms

Mao

Huang

et al. 2022

Front. Oncol.

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“…As it is, the Yost index is a valuable covariate that improves model fit or helps to explain relationships between SES and healthcare and/or outcomes (Butler et al 2020, Li et al 2021, Liu et al 2021); however, the Yost Index is based on a statistically unreliable one-factor structure with unbalanced weights. Inclusion of low weighted indicators (e.g., working class, unemployment, education) gives the impression that those indicators do little to predict the latent variable; however, if all relevant factors are considered, they are influential.…”

Section: Discussionmentioning

confidence: 99%

Empirical Approach to Developing an Optimal Socioeconomic Status Index for Health Surveillance

LaFantasie

Boscoe

2022

Preprint

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The association between multi-dimensional deprivation and public health is well established, and many area-based indices have been developed to measure or account for socioeconomic status in health surveillance. The Yost Index, developed in 2001, has been adopted in the US for cancer surveillance and is based on the combination of two heavily weighted (household income, poverty) and five lightly weighted (rent, home value, employment, education and working class) indicator variables. Our objectives were to 1) update indicators and find a more parsimonious version of the Yost Index by examining potential models that included indicators with more balanced weights/influence and reduced redundancy and 2) test the statistical consistency of the factor upon which the Yost Index is based. Despite the usefulness of the Yost Index, a one-factor structure including all seven Yost indicator variables is not statistically reliable and should be replaced with a three-factor model to include the true variability of all seven indicator variables. To find a one-dimensional alternative, we conducted maximum likelihood exploratory factor analysis on a subset of all possible combinations of fourteen indicator variables to find well-fitted one-dimensional factor models and completed confirmatory factor analysis on the resulting models. One indicator combination (poverty, education, employment, public assistance) emerged as the most stable unidimensional model. This model is more robust to extremes in local cost of living conditions, is comprised of ACS variables that rarely require imputation by the end-user and is a more parsimonious solution than the Yost index with a true one-factor structure.

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“…One such index is the Yost Index, developed from a factor analysis of seven variables or combinations of variables from the American Community Survey (ACS) of the United States Census related to household income, poverty, rent, house value, education, employment type and employment status ( Yost et al 2001 ; Yu, Tatalovich, Gibson, & Cronin, 2014 ). Most of its applications have been in cancer surveillance ( Abdel-Rahman, 2019 ; Li et al, 2021 ; Rajeshuni et al, 2020 ; Ross et al, 2017 ; Swords, Mulvihill, Brooke, Firpo, & Scaife, 2020 ), and it is endorsed by the Surveillance, Epidemiology and End Results (SEER) program of the National Cancer Institute ( National Cancer Institute, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Estimating uncertainty in a socioeconomic index derived from the American community survey

Boscoe

Liu

LaFantasie

et al. 2022

SSM - Population Health

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Socioeconomic factors are associated with the prognosis of Thyroid Cancer

Cited by 17 publications

References 15 publications

Surgical Methods and Social Factors Are Associated With Long-Term Survival in Follicular Thyroid Carcinoma: Construction and Validation of a Prognostic Model Based on Machine Learning Algorithms

Surgical Methods and Social Factors Are Associated With Long-Term Survival in Follicular Thyroid Carcinoma: Construction and Validation of a Prognostic Model Based on Machine Learning Algorithms

Empirical Approach to Developing an Optimal Socioeconomic Status Index for Health Surveillance

Estimating uncertainty in a socioeconomic index derived from the American community survey

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