Thyroid nodule was one of the common diseases of the endocrine system. In 2010, the prevalence of TNs was 18.6%, based on the epidemiological survey of ten cities in China [1]. In recent studies, the cases were found to be emergingly increased due to the lifestyle modification. In current situation, cytology from fine-needle aspiration and thyroid ultrasonography are still becoming the main examination for thyroid nodule, deciding the role of surgery, either lobectomy or total thyroidectomy [2]. However, the rate calculation of thyroid cancer probability in Indonesian subjects has not yet been carried out.

There are a number of well-established predictors of malignancy in thyroid nodules including physical, radiological, and cytology examination. Not all parameters being tested in previous study could be applied in developing country such as Indonesia. Thus, this study aimed to determine the cancer probability risk of a single thyroid nodule by using parameters before surgery. This study was carried out to reduce the need of second surgery for completion thyroidectomy if malignancy is found in advanced.

Study Design

This cohort prospective study was conducted in Sanglah General Hospital, from 2016 to 2021. All data was obtained by Cancer Registry and electronic medical records. All subjects were consented and signed the informed consent.

Study Population

In this study, we included all the subjects with single thyroid nodule underwent surgery in Surgical Oncology Department. The subject with multiple nodules examined physically or radiologically and with presence of other malignancy was excluded from this study. The eligible 

subjects were categorized to case (cancer) and control (benign) group by the final histopatholgy results after surgery. There were nine variables that being analyzed in this study, such as age, gender, side, size, consistency, vascularization, node, and cytology.

Study Flow

All eligible subjects were followed from the outpatient clinic, operating theatre, and until the histopathology results obtained. In outpatient clinic, authors did history taking about age and gender. Physical examination was done for nodule side (location), largest diameter size, and its consistency. Then, we collected the status of vascularization and presence of neck lymph nodes from thyroid ultrasound. The ultrasound was carried out by two radiologists, which if the interpretation was different, both radiologists will discuss until a final imaging judgement was done. In all patients, surgery was carried out by our Surgical Oncology team. Surgical specimen was sent to Pathology laboratory for histopathology examination. The radiologist, pathologist, and data collector were blinded to this study. 

Data Analysis

All data were recorded in SPSS. Categorical data were presented as number and proportion. Numerical data were presented as mean and standard deviation. For age and size variables, Youden Index in ROC analysis was calculated to determine the cut off points. Side dan consistency was determined by physical examination and categorized as hard or firm. Thyroid ultrasound was used to determine the presence of nodule size, calcification, vascularization, and node. Chi square test was carried out for analyzing the difference risk of cancer in each variable. Then, all the significance variabels were further analyzed in regression logistic model. Nomogram was developed by R studio using rms package.

From 2016-2021, there were 198 subjects with single thyroid nodules underwent surgeries in Sanglah General Hospital, Denpasar, Bali, Indonesia. As many as 98 subjects were histopathology proven cancer (follicular, papillary) after surgery. About 14.3% was follicular cancer, 75.5% was papillary cancer, 2% was medullary cancer, and 8% was mixed papillary-follicular cancer.

Among those, only 22 subjects were detected to be cancer by cytology examination and all the subjects underwent total thyroidectomy. The remaining subjects (77.5%) underwent two times surgeries, lobectomy, then completion surgery.

This study analyzed eight parameters, as described in methods section. Most subject with cancer had age older than 42 years old, right side of thyroid nodule, nodule size less than 4 cm, hard consistency, presence of calcification, high vascularity, presence of node, and malignant cytology (either cancer or follicular neoplasm). From these parameters, nodule side and size were not significant after Chi square analysis. The age, consistency, calcification, vascularization, and cytology were continued to logistic regression analysis (Table 1).

This logistic regression model was developed using SPSS. Due to unsignificant result of node parameter after the first logistic regression, it was being eliminated and the new model by only significant variable, age, consistency, calcification, vascularzation, and cytology was developed. This model was considered appropriate to be tested (Hosmer Lemeshow test’ p = 0.459) with accuracy of model 88.8%. The overall effect size of this model was 74.5% (Nagelkerke R square test). The most significant variable was vascularization, followed by calcification, age, consistency, and cytology (Table 2).

Further, nomogram was developed to plot the probability of cancer from significant variables (Figure 1). By using only cytology parameter, the cancer predictive value was only less than 10%. Even age and consistency parameter by physical examination gave a higher value of 30% predictive value. The ultrasound parameters, combining the presence of calcification and vascularization, had a good predictive value of 60%. Overall, the cancer prediction score had to be combined by using all parameters to receive a better predictionof cancer and reducing the need of second surgery.

Table 1. Decription of Parameters in Thyroid Cancer and Benign Nodule

Table 2: The model of Logistic Regression of Thyroid Cancer Parameters

Figure 1: The Development of Nomogram for Thyroid Cancer Probability

Thyroid cancer is the most common endocrine malignancy in Indonesia. Indonesian Cancer Registration reported that thyroid cancer still ranked the ninth out of tenth most common malignancies [2]. The challenge for the clinician is to determine and predict which thyroid nodules are malignant, thus preventing unnecessary intervention for benign nodules.

In preoperative condition, the prediction of malignancy in thyroid nodules could be determined by physical and laboratory examinations. The characteristics of nodule, including a firm, hard, rapidly enlarging nodule, have traditionally been associated with an increased malignancy risk [3]. The noninvasive examination, ultrasonography, was still the main imaging study for thyroid nodules. The imaging provided the diameter size of thyroid nodule, its vascularity and margin, presence of calcification, and assessment of lymphadenopathy [4]. Then, fine needle aspiration biopsy served as minimal invasive examination for cytology analysis of nodule. However, the terminology in interpreting cytology result varied between institutions making it was not generalized [5]. Few thyroids cancer prediction model has been developed but most studies focused in including molecular factor that was not available in Indonesia. In the modern era, clinicians are now incorporating artificial intelligence to aid the process in the decision making of management. The development of nomogram should provide an approximate rate of an outcome prediction by a formulated model. In this study, we have produced an accurate nomogram for the prediction of malignancy for a single thyroid nodule.

The combination of the ultrasound characteristics, age and physical examination able to accurately predict thyroid cancer.

Acknowledgment

The authors had nothing to acknowledge

Conflict of Interest

This study has no conflict of interest to be declared.

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