Association between benign thyroid disease and breast cancer: a single center experience

Prevalence and risk factors of thyroid nodules in breast cancer women with different clinicopathological characteristics: a cross-sectional study

BACKGROUND

Association between breast cancer (BC) and thyroid nodules (TNs) is still unclear. This research was to estimate the prevalence and risk factors of TN in Chinese BC women at initial diagnosis.

METHODS

1731 Chinese early-stage BC women at initial diagnosis underwent thyroid ultrasound and 1:1 age-matched Chinese healthy women underwent health examination in corresponding period were enrolled for analysis.

RESULTS

Prevalence of TN and TI-RADS ≥ 4 TN in BC patients (56.27% and 9.76%) were higher than healthy people (46.04% and 5.49%), respectively, P < 0.001. Among BC patients, prevalence of TN and TI-RADS ≥ 4 TN in hormone receptor (HR)-positive patients (59.57% and 11.81%) were higher than HR-negative patients (48.77% and 5.10%), respectively, P < 0.001, while without difference between HR-negative patients and healthy people. After adjusting for age and BMI, HR-positive patients had higher risk of TN (OR = 1.546, 95%CI 1.251-1.910, P < 0.001) and TI-RADS ≥ 4 TN (OR = 3.024, 95%CI 1.943-4.708, P < 0.001) than HR-negative patients. Furthermore, the risk of TI-RADS ≥ 4 TN was higher in patients with estrogen receptor (ER) positive (OR = 2.933, 95%CI 1.902-4.524), progesterone receptor (PR) positive (OR = 1.973, 95%CI 1.378-2.826), Ki-67 < 20% (OR = 1.797, 95%CI 1.280-2.522), and tumor size < 2 cm (OR = 1.804, 95%CI 1.276-2.552), respectively, P < 0.001.

CONCLUSIONS

Prevalence of TN, especially TI-RADS ≥ 4 TN, in Chinese early-stage BC women was higher than healthy people. HR-positive patients had higher prevalence and risk of TN, while without difference between HR-negative patients and healthy people. The increased risk of TN was correlated with ER-positive, PR-positive, lower Ki-67 expression, and smaller tumor size.

The crosstalk between benign thyroid disease and breast cancer: A single center study

This study aims to investigate the relationship between benign thyroid disease and breast cancer. The clinical study includes a total of 600 participants, divided into 2 groups: the control group (N = 300), which consists of individuals from the checkup population during the same periods, and the experimental group (N = 300), which consists of patients with breast cancer. General data of the participants, including age, tumor diameter, tumor staging, pathological classification, lymph node metastasis, and classification of benign thyroid disease, were collected and analyzed. The levels of TT3, TT4, FT3, FT4, TSH, TPOAb, and TgAb in blood samples from the experimental and control groups were determined using a radioimmune method. The levels of TPOAb, TgAb, and TSH in the experimental group were significantly higher than those in the control group, while the levels of TT3, TT4, FT3, and FT4 in the experimental group were significantly lower. The general data of the participants contributed to the appropriate sample size and allocation. Furthermore, benign thyroid disease contributes to the development of breast cancer by regulating the levels of TT3, TT4, FT3, FT4, TSH, TPOAb, and TgAb.

Case Report of Graves' Disease in a 45-Year-Old Woman Secondary to Herceptin Treatment for Breast Cancer

Graves' disease is the most common cause of thyrotoxicosis and is characterized by ophthalmopathy with proptosis, chemosis, or conjunctival injection; pretibial myxedema; and thyroid acropachy. It is an autoimmune disease that can be genetic or influenced by coexisting environmental factors such as exposure to anticancer drugs, including immune checkpoint inhibitors. The incidence rate of breast cancer is increasing due to rising awareness of risk factors and screening for breast cancer, and the mortality rate is decreasing due to recent advances in cancer treatment. However, there are side effects that are attributed to these treatment modalities, manifesting in various forms in breast cancer survivors, which are reflected in the patient in this case study.

Refining personalized diagnosis, treatment and exploitation of hypothyroidism related to solid nonthyroid cancer

Hypothyroidism in the setting of cancer is a puzzling entity due to the dual role of the thyroid hormones (TH) in cancer – promoting versus inhibitory – and the complexity of the hypothyroidism itself. The present review provides a comprehensive overview of the personalized approach to hypothyroidism in patients with solid nonthyroid cancer, focusing on current challenges, unmet needs and future perspectives. Major electronic databases were searched from January 2011 until March 2022. The milestones of the refinement of such a personalized approach are prompt diagnosis, proper TH replacement and development of interventions and/or pharmaceutical agents to exploit hypothyroidism or, on the contrary, TH replacement as an anticancer strategy. Further elucidation of the dual role of TH in cancer – especially of the interference of TH signaling with the hallmarks of cancer – is anticipated to inform decision-making and optimize patient selection.

Hormonal Crosstalk Between Thyroid and Breast Cancer

Differentiated thyroid cancer and breast cancer account for a significant portion of endocrine-related malignancies and predominately affect women. As hormonally responsive tissues, the breast and thyroid share endocrine signaling. Breast cells are responsive to thyroid hormone signaling and are affected by altered thyroid hormone levels. Thyroid cells are responsive to sex hormones, particularly estrogen, and undergo protumorigenic processes upon estrogen stimulation. Thyroid and sex hormones also display significant transcriptional crosstalk that influences oncogenesis and treatment sensitivity. Obesity-related adipocyte alterations-adipocyte estrogen production, inflammation, feeding hormone dysregulation, and metabolic syndromes-promote hormonal alterations in breast and thyroid tissues. Environmental toxicants disrupt endocrine systems, including breast and thyroid homeostasis, and influence pathologic processes in both organs through hormone mimetic action. In this brief review, we discuss the hormonal connections between the breast and thyroid and perspectives on hormonal therapies for breast and thyroid cancer. Future research efforts should acknowledge and further explore the hormonal crosstalk of these tissues in an effort to further understand the prevalence of thyroid and breast cancer in women and to identify potential therapeutic options.

The Clinical Relevance of Hypothyroidism in Patients with Solid Non-Thyroid Cancer: A Tantalizing Conundrum

Hypothyroidism in patients with solid non-thyroid cancer is a tantalizing entity, integrating an intriguing thyroid hormones (THs)–cancer association with the complexity of hypothyroidism itself. The present narrative review provides a comprehensive overview of the clinical relevance of hypothyroidism in solid non-thyroid cancer. Hypothyroidism in patients with solid non-thyroid cancer is reminiscent of hypothyroidism in the general population, yet also poses distinct challenges due to the dual role of THs in cancer: promoting versus inhibitory. Close collaboration between oncologists and endocrinologists will enable the prompt and personalized diagnosis and treatment of hypothyroidism in patients with solid non-thyroid cancer. Clinical data indicate that hypothyroidism is a predictor of a decreased or increased risk of solid non-thyroid cancer and is a prognostic factor of favorable or unfavorable prognosis in solid non-thyroid cancer. However, the impact of hypothyroidism with respect to the risk and/or prognosis of solid non-thyroid cancer is not a consistent finding. To harness hypothyroidism, or THs replacement, as a personalized anticancer strategy for solid non-thyroid cancer, four prerequisites need to be fulfilled, namely: (i) deciphering the dual THs actions in cancer; (ii) identifying interventions in THs status and developing agents that block tumor-promoting THs actions and/or mimic anticancer THs actions; (iii) appropriate patient selection; and (iv) counteracting current methodological limitations.

Thyroid Diseases and Breast Cancer

Epidemiological studies aimed at defining the association of thyroid diseases with extra-thyroidal malignancies (EM) have aroused considerable interest in the possibility of revealing common genetic and environmental factors underlying disease etiology and progression. Over the years, multiple lines of evidence indicated a significant relationship between thyroid carcinomas and other primary EM, especially breast cancer. For the latter, a prominent association was also found with benign thyroid diseases. In particular, a meta-analysis revealed an increased risk of breast cancer in patients with autoimmune thyroiditis, and our recent work demonstrated that the odds ratio (OR) for breast cancer was raised in both thyroid autoantibody-positive and -negative patients. However, the OR was significantly lower for thyroid autoantibody-positive patients compared to the negative ones. This is in agreement with findings showing that the development of thyroid autoimmunity in cancer patients receiving immunotherapy is associated with better outcome and supports clinical evidence that breast cancer patients with thyroid autoimmunity have longer disease-free interval and overall survival. These results seem to suggest that factors other than oncologic treatments may play a role in the initiation and progression of a second primary malignancy. The molecular links between thyroid autoimmunity and breast cancer remain, however, unidentified, and different hypotheses have been proposed. Here, we will review the epidemiological, clinical, and experimental data relating thyroid diseases and breast cancer, as well as the possible hormonal and molecular mechanisms underlying such associations.

Correlation Analysis of Breast and Thyroid Nodules: A Cross-Sectional Study

Objective

Based on physical examination, to explore the relationship between breast mass (BM) and thyroid nodule (TN) prevalence, and to further explore other related factors that affect the occurrence of BM and TN.

Methods

From January 1, 2018, to January 1, 2021, 12,538 female subjects received breast and thyroid ultrasound examinations at the same time in the health examination center of the Affiliated Hospital of North Sichuan Medical College. Univariate analysis and multivariate logistic analysis were used to screen the relevant factors affecting TN and BM, and propensity score matching was used to further verify the results of the relationship between breast and thyroid.

Results

A total of 4975 (39.7%) of the included subjects have BM and a total of 6315 (50.4%) have TN,2557 (20.4%) had both BM and TN. The logistic regression results show that patients with TN are more likely to suffer from BM [OR = 1.185, 95% CI (1.099-1.278), p<0.0001]. In addition, age, free T4, HDL, height, BMI, systolic blood pressure, diastolic blood pressure, and albumin are independent factors affecting the occurrence of BM; patients with BM are more likely to have TN [OR = 1.180, 95% CI (1.094-1.272), p<0.0001], and age, free T3, free T4, AST, ALT, albumin, height, and BMI are independent influencing factors on the occurrence of TN. The result of propensity score matching confirmed the relationship between BM and TN.

Conclusion

There is a bidirectional pathogenic relationship between BM and TN, women with BM are at increased risk of TN, and women with TN are more likely to have BM. Thyroid hormone is not only related to the occurrence of TN but also affects the occurrence of BM.

Reproductive and menstrual factors for papillary thyroid cancer risk: A case-control study in Chinese women

BACKGROUND

Thyroid cancer (TC) is threefold more common in women than men. Reproductive and menstrual factors may be related to the onset of papillary thyroid cancer (PTC). This study aims to determine the association of reproductive and menstrual factors with PTC in Chinese females.

METHODS

A total of 335 histologically confirmed cases of PTC were recruited in this case-control study. The controls were matched for age with a deviation of ± 2 years, which conducted from September 2016 to February 2019. Logistic regression models were applied to identify the association of reproductive and menstrual factors with PTC.

RESULTS

After adjustment by some variables, early menarche age (OR ≤ 13 years vs. > 13years = 2.40, 95 % CI 1.12-5.13) and shorter lifetime breastfeeding (OR <6 months vs. ≥ 6 months = 1.99, 95 % CI 1.11-3.55) significantly increased the risk of PTC, whereas younger age at first pregnancy had a protective effect against PTC (OR ≤ 24years vs. > 24 years = 0.66, 95 % CI 0.44-0.98). There was a positive correlation between premenopausal and PTC in the lower age group (OR _{premenopausal vs. Menopause by natural} =2.34, 95 %CI 1.03-5.28).

CONCLUSIONS

Early menarche age, abortion, shorter breastfeeding duration and premenopausal may be related to the occurrence of PTC. Early age at first pregnancy and larger number of full-time pregnancies were possible to decrease the risk of PTC.

Breast cancer in previously thyroidectomized patients: which thyroid disorders are a risk factor?

The aim of this study was to evaluate whether there are thyroid diseases in which breast cancer will appear later as well as the role of autoimmunity. This was a retrospective observational study. A total of 410 females (thyroid surgery and later breast cancer) and 524 females (thyroid surgery only) were compared with regard to pathological thyroid findings, thyroid hormones, thyroid autoimmunity and type of breast cancer. Thyroid autoimmunity, especially antithyroid peroxidase antibodies, significantly increased the risk of breast cancer (p < 0.01); however, this was not true for other thyroid diseases, including thyroid cancer. No variant of breast cancer was predominant, and only thyroid autoimmunity was associated with the risk of breast cancer. Further research is needed to explain the impacts of different antithyroid antibodies.

Several studies have long hypothesized a link between thyroid disease and breast cancer. The authors' study retrospectively examined a large cohort of patients who initially underwent thyroid surgery and subsequently had breast cancer compared with a control group consisting of patients with only breast cancer. This comparison showed that only autoimmune thyroid disease was a risk factor for subsequent breast cancer, whereas no significant association of thyroid cancer with breast cancer was found.

A generic deep learning framework to classify thyroid and breast lesions in ultrasound images

Breast and thyroid cancers are the two common cancers to affect women worldwide. Ultrasonography (US) is a commonly used non-invasive imaging modality to detect breast and thyroid cancers, but its clinical diagnostic accuracy for these cancers is controversial. Both thyroid and breast cancers share some similar high frequency ultrasound characteristics such as taller-than-wide shape ratio, hypo-echogenicity, and ill-defined margins. This study aims to develop an automatic scheme for classifying thyroid and breast lesions in ultrasound images using deep convolutional neural networks (DCNN). In particular, we propose a generic DCNN architecture with transfer learning and the same architectural parameter settings to train models for thyroid and breast cancers (TNet and BNet) respectively, and test the viability of such a generic approach with ultrasound images collected from clinical practices. In addition, the potentials of the thyroid model in learning the common features and its performance of classifying both breast and thyroid lesions are investigated. A retrospective dataset of 719 thyroid and 672 breast images captured from US machines of different makes between October 2016 and December 2018 is used in this study. Test results show that both TNet and BNet built on the same DCNN architecture have achieved good classification results (86.5% average accuracy for TNet and 89% for BNet). Furthermore, we used TNet to classify breast lesions and the model achieves sensitivity of 86.6% and specificity of 87.1%, indicating its capability in learning features commonly shared by thyroid and breast lesions. We further tested the diagnostic performance of the TNet model against that of three radiologists. The area under curve (AUC) for thyroid nodule classification is 0.861 (95% CI: 0.792-0.929) for the TNet model and 0.757-0.854 (95% CI: 0.658-0.934) for the three radiologists. The AUC for breast cancer classification is 0.875 (95% CI: 0.804-0.947) for the TNet model and 0.698-0.777 (95% CI: 0.593-0.872) for the radiologists, indicating the model's potential in classifying both breast and thyroid cancers with a higher level of accuracy than that of radiologists.

Convolutional Neural Network for Breast and Thyroid Nodules Diagnosis in Ultrasound Imaging

Objective

The incidence of superficial organ diseases has increased rapidly in recent years. New methods such as computer-aided diagnosis (CAD) are widely used to improve diagnostic efficiency. Convolutional neural networks (CNNs) are one of the most popular methods, and further improvements of CNNs should be considered. This paper aims to develop a multiorgan CAD system based on CNNs for classifying both thyroid and breast nodules and investigate the impact of this system on the diagnostic efficiency of different preprocessing approaches.

Methods

The training and validation sets comprised randomly selected thyroid and breast nodule images. The data were subgrouped into 4 models according to the different preprocessing methods (depending on segmentation and the classification method). A prospective data set was selected to verify the clinical value of the CNN model by comparison with ultrasound guidelines. Diagnostic efficiency was assessed based on receiver operating characteristic (ROC) curves.

Results

Among the 4 models, the CNN model using segmented images for classification achieved the best result. For the validation set, the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, and area under the curve (AUC) of our CNN model were 84.9%, 69.0%, 62.5%, 88.2%, 75.0%, and 0.769, respectively. There was no statistically significant difference between the CNN model and the ultrasound guidelines. The combination of the two methods achieved superior diagnostic efficiency compared with their use individually.

Conclusions

The study demonstrates the probability, feasibility, and clinical value of CAD in the ultrasound diagnosis of multiple organs. The use of segmented images and classification by the nature of the disease are the main factors responsible for the improvement of the CNN model. Moreover, the combination of the CNN model and ultrasound guidelines results in better diagnostic performance, which will contribute to the improved diagnostic efficiency of CAD systems.