Hypertension Was Associated with Higher Tumor Stages in Papillary Thyroid Cancer: A Large Sample Single-Center Study

Associations Between Metabolic Obesity Phenotypes and Pathological Characteristics of Papillary Thyroid Carcinoma

OBJECTIVE

The association between obesity, metabolic dysregulation, and the aggressive pathological traits of papillary thyroid carcinoma (PTC) continues to be a contentious issue. To date, no investigations have examined the impact of metabolic status on the malignant pathological features of PTC in relation to obesity.

METHODS

This research involved 855 adult patients with PTC from Shandong Provincial Hospital, classified into 4 groups based on metabolic and obesity status: metabolically healthy nonobese, metabolically unhealthy nonobese (MUNO), metabolically healthy obese, and metabolically unhealthy obese. We employed logistic regression to investigate the relationship between these metabolic obesity phenotypes and PTC's pathological characteristics. Mediation analysis was also performed to determine metabolic abnormalities' mediating role in the nexus between obesity and these characteristics.

RESULTS

Relative to metabolically healthy nonobese individuals, the metabolically unhealthy obese group was significantly associated with an elevated risk of larger tumor sizes and a greater number of tumor foci in PTC. Mediation analysis indicated that obesity directly influences tumor size, whereas its effect on tumor multifocality is mediated through metabolic dysfunctions. Specifically, high-density lipoprotein cholesterol levels were notably associated with tumor multifocality within obese subjects, serving as a mediator in obesity's impact on this trait.

CONCLUSION

The concurrent presence of obesity and metabolic dysregulation is often connected to more aggressive pathological features in PTC. The mediation analysis suggests obesity directly affects tumor size and indirectly influences tumor multifocality via low high-density lipoprotein cholesterol levels.

Development and validation of prediction models for papillary thyroid cancer structural recurrence using machine learning approaches

BACKGROUND

Although papillary thyroid cancer (PTC) patients are known to have an excellent prognosis, up to 30% of patients experience disease recurrence after initial treatment. Accurately predicting disease prognosis remains a challenge given that the predictive value of several predictors remains controversial. Thus, we investigated whether machine learning (ML) approaches based on comprehensive predictors can predict the risk of structural recurrence for PTC patients.

METHODS

A total of 2244 patients treated with thyroid surgery and radioiodine were included. Twenty-nine perioperative variables consisting of four dimensions (demographic characteristics and comorbidities, tumor-related variables, lymph node (LN)-related variables, and metabolic and inflammatory markers) were analyzed. We applied five ML algorithms-logistic regression (LR), support vector machine (SVM), extreme gradient boosting (XGBoost), random forest (RF), and neural network (NN)-to develop the models. The area under the receiver operating characteristic (AUC-ROC) curve, calibration curve, and variable importance were used to evaluate the models' performance.

RESULTS

During a median follow-up of 45.5 months, 179 patients (8.0%) experienced structural recurrence. The non-stimulated thyroglobulin, LN dissection, number of LNs dissected, lymph node metastasis ratio, N stage, comorbidity of hypertension, comorbidity of diabetes, body mass index, and low-density lipoprotein were used to develop the models. All models showed a greater AUC (AUC = 0.738 to 0.767) than did the ATA risk stratification (AUC = 0.620, DeLong test: P < 0.01). The SVM, XGBoost, and RF model showed greater sensitivity (0.568, 0.595, 0.676), specificity (0.903, 0.857, 0.784), accuracy (0.875, 0.835, 0.775), positive predictive value (PPV) (0.344, 0.272, 0.219), negative predictive value (NPV) (0.959, 0.959, 0.964), and F1 score (0.429, 0.373, 0.331) than did the ATA risk stratification (sensitivity = 0.432, specificity = 0.770, accuracy = 0.742, PPV = 0.144, NPV = 0.938, F1 score = 0.216). The RF model had generally consistent calibration compared with the other models. The Tg and the LNR were the top 2 important variables in all the models, the N stage was the top 5 important variables in all the models.

CONCLUSIONS

The RF model achieved the expected prediction performance with generally good discrimination, calibration and interpretability in this study. This study sheds light on the potential of ML approaches for improving the accuracy of risk stratification for PTC patients.

TRIAL REGISTRATION

Retrospectively registered at www.chictr.org.cn (trial registration number: ChiCTR2300075574, date of registration: 2023-09-08).

Effect and Interactions of BRAF on Lymph Node Metastasis in Papillary Thyroid Carcinoma With Hashimoto Thyroiditis

CONTEXT

The role of B-Raf proto-oncogene (BRAF) in papillary thyroid carcinoma (PTC) with Hashimoto thyroiditis (HT) is unknown.

OBJECTIVE

We aimed to explore risk factors affecting lymph node (LN) metastasis and interaction effect of BRAF in PTC patients with HT.

METHODS

We retrospectively collected the data of 994 PTC patients with HT who underwent surgery at the West China Hospital. We analyzed the correlations between preoperative characteristics and LN metastasis in overall, and different BRAFV600E-mutation patients. Logistic regression was applied to analyze the risk factors for LN metastasis. Finally, we performed an interaction effect analysis to identify the interaction effect of BRAF.

RESULTS

The overall LN metastasis rate was 52.71% (524/994); the overall BRAF mutation rate was 26.9% (268/994). BRAF mutation rates were significantly different in LN metastasis and nonmetastasis patients (31.7% vs 21.5%; P < .001). In all 994 patients, age, body mass index (BMI), hypertension, tumor maximum diameter, BRAF mutation, tumor location, aspect ratio, calcification, and extrathyroidal invasion were risk factors for LN metastasis (P < .05). In BRAF-mutant patients, smoking, hypertension, maximum diameter, calcification, and multifocality were risk factors for LN metastasis (P < .05). In BRAF wild-type patients, age, BMI, maximum diameter, tumor location, aspect ratio, tumor shape, calcification, and extrathyroidal invasion were risk factors (P < .05). Additionally, we found statistically significant interactions between BRAF and BMI, hypertension, maximum diameter, and calcification (P < .05), suggesting the potential interaction effect of BRAF.

CONCLUSION

BRAF is a risk factor for LN metastasis in PTC with HT. Meanwhile, BRAF can interact with age, BMI, hypertension, and calcification, which together influence LN metastasis.

Hypertension and hyperglycaemia are positively correlated with local invasion of early cervical cancer

Background

Metabolic disorders are involved in the development of numerous cancers, but their association with the progression of cervical cancer is unclear. This study aims to investigate the association between metabolic disorders and the pathological risk factors and survival in patients with early cervical cancer.

Methods

Patients with FIGO IB1 (2009) primary cervical cancer who underwent radical hysterectomy and systematic pelvic lymph node dissection at our institution from October 2014 to December 2017 were included retrospectively. Clinical data regarding the metabolic syndrome and surgical pathology of the patient were collected. The correlations between metabolic disorders (hypertension, hyperglycemia, and obesity) and clinicopathological characteristics as well as survival after surgery were analyzed.

Results

The study included 246 patients with clinical IB1 cervical cancer, 111 (45.1%) of whom had at least one of the comorbidities of hypertension, obesity, or hyperglycemia. Hypertension was positively correlated with parametrial invasion and poorly differentiated histology; hyperglycemia was positively correlated with stromal invasion; obesity was negatively associated with lymph node metastasis; but arbitrary disorder did not show any correlation with pathologic features. Hypertension was an independent risk factor for parametrial invasion (OR=6.54, 95% CI: 1.60-26.69); hyperglycemia was an independent risk factor for stromal invasion (OR=2.05, 95% CI: 1.07-3.95); and obesity was an independent protective factor for lymph node metastasis (OR=0.07, 95% CI: 0.01-0.60). Moreover, the patients with hypertension had a significantly lower 5-year OS rate (70.0% vs. 95.3%, P<0.0001) and a significantly lower 5-year PFS rate than those without hypertension (70.0% vs. 91.2%, P=0.010).

Conclusion

Hypertension and hyperglycemia are positively associated with local invasion of early cervical cancer, which need to be verified in multi-center, large scale studies.