Sex Bias in Differentiated Thyroid Cancer

Suteau, Valentine; Munier, Mathilde; Briet, Claire; Rodien, Patrice

doi:10.3390/ijms222312992

Cited by 56 publications

(47 citation statements)

References 173 publications

(235 reference statements)

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“…The results of one study confirm that patients with PTC with distant metastases have a good prognosis after treatment (Sampson et al, 2007). Another study found that sex is a prognostic factor for DTCDM, likely because estrogen production limits cancer progression (Suteau et al, 2021). The current study found that tumor size was an important factor affecting DTCDM OS, with relatively significant scores for both 1-27 mm and 28-65 mm, a finding supported by Nguyen et al (Nguyen et al, 2018).…”

Section: Discussionsupporting

confidence: 81%

A Predictive Model for the 10-year Overall Survival Status of Patients With Distant Metastases From Differentiated Thyroid Cancer Using XGBoost Algorithm-A Population-Based Analysis

et al. 2022

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Purpose: To explore clinical and non-clinical characteristics affecting the prognosis of patients with differentiated thyroid cancer with distant metastasis (DTCDM) and establish an accurate overall survival (OS) prognostic model.Patients and methods: Study subjects and related information were obtained from the National Cancer Institute’s surveillance, epidemiology, and results database (SEER). Kaplan‐Meier analysis, log-rank test, and univariate and multivariate Cox analysis were used to screen for factors influencing the OS of patients with DTCDM. Nine variables were introduced to build a machine learning (ML) model, receiver operating characteristic (ROC) was used to evaluate the recognition ability of the model, calibration plots were used to obtain prediction accuracy, and decision curve analysis (DCA) was used to estimate clinical benefit.Results: After applying the inclusion and exclusion criteria, a total of 3,060 patients with DTCDM were included in the survival analysis from 2004 to 2017. A machine learning prediction model was developed with nine variables: age at diagnosis, gender, race, tumor size, histology, regional lymph node metastasis, primary site surgery, radiotherapy, and chemotherapy. After excluding patients who survived <120 months, variables were sub-coded and machine learning was used to model OS prognosis in patients with DTCDM. Patients 6–50 years of age had the highest scores in the model. Other variables with high scores included small tumor size, male sex, and age 51–76. The AUC and calibration curves confirm that the XGBoost model has good performance. DCA shows that our model can be used to support clinical decision-making in a 10-years overall survival model.Conclusion: An artificial intelligence model was constructed using the XGBoost algorithms to predict the 10-years overall survival rate of patients with DTCDM. After model validation and evaluation, the model had good discriminative ability and high clinical value. This model could serve as a clinical tool to help inform treatment decisions for patients with DTCDM.

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Section: Discussionsupporting

confidence: 81%

A Predictive Model for the 10-year Overall Survival Status of Patients With Distant Metastases From Differentiated Thyroid Cancer Using XGBoost Algorithm-A Population-Based Analysis

et al. 2022

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“…Although thyroid cancer was diagnosed less frequently in male patients, we observed a higher rate of mortality from nearly all causes in male patients with thyroid malignancy in this study. Studies have demonstrated that thyroid malignancy characteristically presents at a more advanced stage and there is a worse tumor prognosis in males ( 46 , 47 ). Research on the influence of sex hormones on thyroid malignancy has continued to be inconclusive, while plenty of experimental research studies have indicated that estrogen and other hormones and their receptors may lead to tumorigenesis and tumor progression ( 46 , 47 ).…”

Section: Discussionmentioning

confidence: 99%

Cause of Death Among Patients With Thyroid Cancer: A Population-Based Study

et al. 2022

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BackgroundOver the last decades, the number of patients diagnosed with thyroid carcinoma has been increasing, highlighting the importance of comprehensively evaluating causes of death among these patients. This study aimed to comprehensively characterize the risk of death and causes of death in patients with thyroid carcinoma.MethodsA total of 183,641 patients diagnosed with an index thyroid tumor were identified from the Surveillance, Epidemiology, and End Result database (1975–2016). Standardized mortality rates (SMRs) for non-cancer deaths were calculated to evaluate mortality risk and to compare mortality risks with the cancer-free US population. Cumulative mortality rates were calculated to explore the factors associated with higher risk of deaths.ResultsThere were 22,386 deaths recorded during follow-up, of which only 31.0% were due to thyroid cancer and 46.4% due to non-cancer causes. Non-cancer mortality risk among patients with thyroid cancer was nearly 1.6-fold (SMR=1.59) that of the general population. Cardiovascular diseases were the leading cause of non-cancer deaths, accounting for 21.3% of all deaths in thyroid cancer patients. Non-cancer causes were the dominant cause of death in thyroid cancer survivors as of the third year post-diagnosis. We found that males with thyroid cancer had a higher risk of all-cause mortality compared with females. The risk of suicide was highest in the first post-diagnostic year (<1 year: SMR=1.51). The long-term risk of Alzheimer’s disease was notably increased in thyroid cancer patients (>5 years: SMR=8.27).ConclusionNon-cancer comorbidities have become the major risks of death in patients with thyroid tumor in the US, as opposed to death from the tumor itself. Clinicians and researchers should be aware of these risk trends in order to conduct timely intervention strategies.

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“…Women are traditionally more keen on undergoing routine clinical examination along their lives as compared to men ( 27 , 28 ), which could be part of the reasons why thyroid nodules and cancers are more frequently detected in the female population. However, another studies showed that male gender was the clinical factor associated with the high risk of TC ( 16 , 29 ). Our results showed that the number of TC was more in male than in female, and gender was an independent risk factor associated with TC.…”

Section: Discussionmentioning

confidence: 99%

“…Moreover, clinicians estimate the risk of TNs and make subsequent decisions based on comprehensive information including clinical and US findings ( 3 , 16 , 17 ). The existing RSSs are limited to B-mode US features and do not address clinical, Color Doppler and elastographic US characteristics.…”

Section: Introductionmentioning

confidence: 99%

“…The existing RSSs are limited to B-mode US features and do not address clinical, Color Doppler and elastographic US characteristics. Previous studies have shown that there were gender and age differences in patients with thyroid cancer (TC), but this is still controversial in recent years ( 16 , 18 ). In addition, routine TSH (Thyroid Stimulating Hormone) measurement is recommended by the ATA (American Thyroid Association) guideline which not only aimed to exclude hyperthyroidism but to better stratify the risk of malignancy as well, since higher serum TSH levels have been correlated with an increased risk of malignancy ( 19 ).…”

Section: Introductionmentioning

confidence: 99%

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Development and validation of a novel diagnostic tool for predicting the malignancy probability of thyroid nodules: A retrospective study based on clinical, B-mode, color doppler and elastographic ultrasonographic characteristics

Zhou

et al. 2022

Front. Endocrinol.

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BackgroundClinicians estimate the risk of thyroid nodules and make subsequently decision on the basis of clinical and ultrasonographic findings. Currently, there is no comprehensive diagnostic tool for predicting the malignancy rates of thyroid nodules. Our aim was to develop and validate a novel integrate diagnostic tool for predicting the malignancy probability of thyroid nodules based on clinical, B-mode, Color Doppler and elastographic ultrasonographic characteristics.MethodsA total of 1016 nodules in 1016 patients who underwent thyroid ultrasonography and surgery from July 2021 to December 2021 were included in this retrospective study. All nodules were confirmed by pathology and randomly classified into the training and validation groups. Clinical, B-mode, Color Doppler and elastographic (CBCE) ultrasonographic characteristics of nodules were recorded. Univariate and multivariate analyses were performed to screen independent predictors associated with thyroid cancer. A multivariate model containing the extracted predictors was constructed and presented in the form of a nomogram. The validation and applicability of the CBCE nomogram was evaluated using the receiver operating characteristic (ROC) curve. Diagnostic performances were calculated to compare the CBCE nomogram with ACR-TIRADS (Thyroid Imaging Reporting Data System by American College of Radiology) and EU-TIRADS (Thyroid Imaging Reporting Data System by European Thyroid Association).ResultsThe following factors were included in the CBCE nomogram: patient gender, age, shape, margin, composition and echogenicity, calcification, vascularization distribution, vascularization degree, suspicious lymph node metastases and elastography. The area under the curve (AUC) values were 0.978 and 0.983 for the training and validation groups, respectively. Compared with ACR-TIRADS and EU-TIRADS, the CBCE nomogram showed improved accuracy (0.944) and specificity (0.913) without sacrificing sensitivity (0.963) and showed the highest AUC with an optimal cutoff value of 0.55.ConclusionThe CBCE nomogram has good and high clinical practicability in predicting the malignancy probability of thyroid nodules.

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Sex Bias in Differentiated Thyroid Cancer

Cited by 56 publications

References 173 publications

A Predictive Model for the 10-year Overall Survival Status of Patients With Distant Metastases From Differentiated Thyroid Cancer Using XGBoost Algorithm-A Population-Based Analysis

A Predictive Model for the 10-year Overall Survival Status of Patients With Distant Metastases From Differentiated Thyroid Cancer Using XGBoost Algorithm-A Population-Based Analysis

Cause of Death Among Patients With Thyroid Cancer: A Population-Based Study

Development and validation of a novel diagnostic tool for predicting the malignancy probability of thyroid nodules: A retrospective study based on clinical, B-mode, color doppler and elastographic ultrasonographic characteristics

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