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Article

Association Between COVID-19 Infection and Thyroid Cancer Development: A Retrospective Cohort Study Using the TriNetX Database

by
Hsin-Yi Wang
1,2,
Yi-Ching Lin
1,3,
Jing-Uei Hou
1,
Chih-Hao Chao
4,* and
Shih-Chuan Tsai
1,5,*
1
Department of Nuclear Medicine, Taichung Veterans General Hospital, Taichung City 407219, Taiwan
2
National Defense Medical Center, School of Medicine, Taipei City 11490, Taiwan
3
Department of Public Health, China Medical University, Taichung City 406040, Taiwan
4
Division of Chest Medicine, Department of Internal Medicine, Yuanlin Christian Hospital, Changhua County 510012, Taiwan
5
Department of Medical Imaging and Radiological Technology, Institute of Radiological Science, Central Taiwan University of Science and Technology, Taichung City 406053, Taiwan
*
Authors to whom correspondence should be addressed.
Biomedicines 2025, 13(8), 1933; https://doi.org/10.3390/biomedicines13081933
Submission received: 15 May 2025 / Revised: 25 July 2025 / Accepted: 4 August 2025 / Published: 8 August 2025
(This article belongs to the Section Cancer Biology and Oncology)
Browse Figures
Versions Notes

Abstract

Background: Coronavirus Disease 2019 has been associated with dysfunction in multiple endocrine organs, including the thyroid gland. While evidence suggests SARS-CoV-2 may influence thyroid function and promote oncogenesis through inflammation and cytokine storms, its role in thyroid cancer remains unclear. This study investigates whether COVID-19 is associated with an increased risk of thyroid cancer development. Methods: We conducted a retrospective cohort study using the TriNetX global federated health research database, encompassing data from 151 healthcare organizations. Adult patients with confirmed COVID-19 between 1 December 2019 and 31 December 2023, were included and compared to a matched cohort without COVID-19. Patients with prior thyroid cancer history or who had received COVID-19 vaccination were excluded in both groups. Propensity score matching (1:1) was performed for age, gender, and overweight/obesity status. The primary outcome was that new-onset thyroid cancer was diagnosed at least one year after COVID-19 diagnosis. Hazard ratios were calculated using Cox proportional hazards models, and subgroup analyses were performed based on age, gender, thyroid function status and treatment modalities. Results: After matching, a significantly higher thyroid cancer incidence was observed between the post-COVID and non-COVID groups. Subgroup analysis revealed a significantly higher risk of thyroid cancer development following COVID-19 diagnosis in patients who developed hyperthyroidism (HR 2.14, 95% CI: 1.04–4.46) or hypothyroid-ism (HR 1.83, 95% CI: 1.12–2.97) compared with the non-COVID population. Male patients also exhibited a higher risk of thyroid cancer after COVID-19 (HR 1.22, 95% CI 1.02–1.46). For patients with hyperthyroidism or hypothyroidism, those who had prior COVID-19 exhibited a relatively higher risk of developing thyroid cancer than those without a history of COVID-19 (HR 4.387, 95% CI: 2.08–9.24 for hyperthyroidism; HR 2.58, 95% CI: 1.58–4.22 for hypothyroidism). Conclusions: Patients with COVID-19 exhibited an increase in thyroid cancer risk, with specific subgroups—male adults and those with post-infectious thyroid dysfunction—also exhibiting increased risk. These findings suggest a potential relationship between SARS-CoV-2 and thyroid oncogenesis, warranting further prospective research.

1. Introduction

Coronavirus Disease 2019 (COVID-19), caused by the novel coronavirus SARS-CoV-2, has had a profound impact on global health and economies [1]. As of April 2025, over 770 million confirmed infections and 7 million deaths have been reported worldwide [2]. COVID-19 presents with a wide spectrum of clinical manifestations, ranging from asymptomatic cases to severe respiratory failure and multi-organ dysfunction [3]. In addition to the direct effect of SARS-CoV-2 viral invasion, indirect effects—such as abnormal inflammatory responses and cytokine storms—can also impair various endocrine organs, including the pancreas, adrenal glands, pituitary glands, and thyroid gland [4].
Thyroid cancer is the most prevalent endocrine malignancy [5], and its incidence has been rising rapidly worldwide in recent years [6]. It is classified into differentiated thyroid cancer (including papillary and follicular thyroid carcinoma), medullary thyroid cancer, and anaplastic thyroid cancer [7]. Among these, papillary thyroid carcinoma is the most common type, accounting for approximately 90% of cases [8,9]. Established risk factors for thyroid cancer include childhood exposure to ionizing radiation and obesity. Other potential risk factors include endocrine-disrupting chemicals and thyroid dysfunction [6]. The incidence of thyroid cancer is higher in women than in men [9]. In the United States, thyroid cancer ranks as the 13th most commonly diagnosed cancer overall and the 6th most common among women [10]. Prognosis is generally favorable; the 5-year survival rate exceeds 90% for localized or regionally metastatic disease but declines to approximately 54.9% in cases with distant metastases [10].
The thyroid gland produces thyroid hormones, including the prohormone tetraiodothyronine (T4) and the active hormone triiodothyronine (T3). T3 regulates basal metabolic rate by influencing the central nervous system, respiratory system, cardiovascular system, and skeletal muscle [11]. SARS-CoV-2 infection can disrupt thyroid function, potentially leading to conditions such as thyrotoxicosis, hypothyroidism, and the nonthyroidal illness syndrome [12].
SARS-CoV-2 RNA has been detected in thyroid tissue [13], suggesting direct viral invasion. SARS-CoV-2 enters target cells through angiotensin-converting enzyme II (ACE2) receptors, which are highly expressed in endocrine tissues, including the thyroid and pituitary glands [14,15]. The binding of SARS-CoV-2 to ACE2 receptors downregulates the angiotensin I receptor, leading to dysregulation of the renin–angiotensin–aldosterone system. This, in turn, results in inflammation, fibrosis, vasoconstriction, oxidation, and increased capillary permeability [16,17,18,19], all of which may contribute to cancer development. Additionally, SARS-CoV-2 infection induces profound inflammation and cytokine storms [20], which could promote cancer stem cell growth in target organs and are associated with the development of thyroid cancer [21,22]. The inflammation and oxidative stress induced by SARS-CoV-2 may also play a role in the development and progression of thyroid cancer [23]. Infection with SARS-CoV-2 may also induce the expression of nonstructural protein (nsp) 15, which affects the function of the tumor suppressor retinoblastoma protein [24,25], and nsp 3, which degrades the tumor suppressor gene P53 [26,27]. This pathway is considered one of the most likely mechanisms by which SARS-CoV-2 could promote cancer development [28].
However, the literature on the relationship between COVID-19 and thyroid cancer development remains limited, and no consensus has been established. To address this gap, we conducted a retrospective cohort study to investigate whether COVID-19 contributes to the development of thyroid cancer.

2. Materials and Methods

2.1. Setting

In this retrospective cohort study, we utilized data from the Global Collaborative Network within the TriNetX database, which includes information from 151 healthcare organizations (HCOs). TriNetX is a global federated health research network that provides access to electronic medical records, encompassing diagnoses, procedures, medications, laboratory results, and genomic data from large HCOs.
The TriNetX platform complies with the Health Insurance Portability & Accountability Act and the General Data Protection Regulation. The Western Institutional Review Board granted TriNetX a waiver of informed consent, as the platform only aggregates counts and statistical summaries of deidentified information.

2.2. Cohort

We included adult patients (aged ≥18 years) with a positive SARS-CoV-2 PCR test (Table 1) or a COVID-19 diagnosis (ICD-10 codes: U07.1, U07.2, or J12.82) recorded in the TriNetX database during the study period. Patients with a prior history of thyroid cancer (ICD-10 codes: C73 or Z85.850) or those who had received any COVID-19 vaccine (Table 2) were excluded. For the subgroup analysis on abnormal thyroid function, we also excluded patients with a history of hyperthyroidism (ICD-10 codes: E05, E05.8, E05.3, E05.31, and E06) or hypothyroidism (ICD10 codes: E03.3 and E03.8). The index date was defined as the date of the COVID-19 diagnosis.
The study population was compared to a control group comprising individuals without a COVID-19 diagnosis, no history of COVID-19 vaccination, and no prior history of thyroid cancer. The primary outcome was a new diagnosis of thyroid cancer occurring at least one year after the COVID-19 diagnosis. A flowchart illustrating the cohort construction, including participants enrolled between 1 December 2019 and 31 December 2023, is presented in Figure 1. Detailed query criteria are provided in Supplementary File S1.
A subgroup analysis was performed to compare the risk of thyroid cancer development between patients with and without COVID-19 across different genders and age groups (18–40 years, 41–60 years, and over 60 years). We also assessed the risk among patients who received various antiviral therapies, as well as those who developed hyperthyroidism or hypothyroidism following COVID-19. Additional comparisons were made between COVID-19 patients aged 60 years and older and those aged 18 to 60 years, between those aged 40 years and older and those aged 18 to 40 years; between those who received antiviral therapy and those who did not, and between individuals with post-infectious thyroid dysfunction (hyperthyroidism or hypothyroidism) and those without any thyroid function alterations following infection. Finally, we compared COVID-19 patients who developed thyroid dysfunction with patients who had thyroid dysfunction in the absence of COVID-19. Detailed query criteria are provided in Supplementary Files S2 and S3.

2.3. Statistical Analysis

We performed 1:1 propensity score matching based on age at index, gender and overweight/obesity status, with the non-COVID cohort serving as the control group. In subsequent analyses, we additionally included personal history of irradiation and comorbidities (hypertension, ischemic heart disease, and diabetes mellitus) as matching covariates. Propensity score matching is an integrated function within the TriNetX platform. We selected the covariates to be included in the matching process, and the system conducted propensity score matching to compare outcomes between the cohorts.
The outcomes were compared using built-in functions within the TriNetX platform. We calculated the hazard ratio (HR) for thyroid cancer development in both groups. The proportional hazards assumption was tested using the generalized Schoenfeld approach, available in TriNetX. Survival probabilities were estimated using the Kaplan–Meier method. Statistical significance was defined as a p-value < 0.05, and a 95% confidence interval (CI) was used as additional evidence of statistical significance.

3. Results

The baseline demographic data is presented in Table 3. The post-COVID group included 2,176,997 patients, while the non-COVID group comprised 28,535,672 patients. Due to the limitations of the TriNetX built-in function, propensity score matching in such large populations can only be performed on age, genders, and overweight/obesity status. After matching, the mean age was 48.8 years, and 57.9% of the population was female. A higher proportion of patients in the post-COVID group had comorbidities such as hypertensive diseases, ischemic heart disease, or diabetes mellitus. Additionally, a greater proportion of patients in the post-COVID group had a personal history of irradiation, although this represented less than 1% of the population (0.9% vs. 0.5%). The Kaplan–Meier analysis revealed a significant difference in the incidence of thyroid cancer following a COVID-19 diagnosis (HR: 1.104, 95% CI: 1.02–1.20, p = 0.0146) (Figure 2).
The subgroup analysis revealed a significantly higher risk of thyroid cancer development following COVID-19 diagnosis in patients aged 60 years and older (HR 1.25, 95% CI: 1.04–1.43) and those aged between 41 and 60 years (HR 1.16, 95% CI: 1.02–1.33) compared with the non-COVID population within the same age range. Male patients also exhibited a higher risk of thyroid cancer after COVID-19 (HR 1.22, 95% CI 1.02–1.46). Additionally, the risk of thyroid cancer was also elevated in patients who developed hyperthyroidism (HR 2.14, 95% CI: 1.04–4.46) or hypothyroidism (HR 1.83, 95% CI: 1.12–2.97) compared with the non-COVID population. Antiviral therapy with Nirmatrelvir/Ritonavir was also associated with an increased risk of thyroid cancer (HR 1.67, 95% CI 1.07–2.61) compared with the non-COVID population. Antiviral agents such as Remdesivir and Molnupiravir had no significant impact on the incidence of thyroid cancer (Figure 3). Detailed data and a Kaplan–Meier graph are provided in Supplementary File S4.
Among the patients with COVID-19, those who developed hyperthyroidism or hypothyroidism had a significantly higher risk of developing thyroid cancer compared to those without thyroid function alterations following infection (HR 8.53, 95% CI: 2.86–25.39 for hyperthyroidism; HR 3.99, 95% CI: 2.27–7.06 for hypothyroidism). No statistically significant difference in thyroid cancer risk was observed between COVID-19 patients aged 60 years and older and those aged 18 to 60 years, between those aged 40 years and older and those aged 18 to 40 years, or between patients who received antiviral therapy and those who did not (Figure 4). Detailed data and Kaplan–Meier curves are provided in Supplementary File S5.
Furthermore, for patients with hyperthyroidism or hypothyroidism, those who had prior COVID-19 exhibited a relatively higher risk of developing thyroid cancer than those without a history of COVID-19 (HR 4.387, 95% CI: 2.08–9.24 for hyperthyroidism; HR 2.58, 95% CI: 1.58–4.22 for hypothyroidism) (Figure 5). Detailed data and Kaplan–Meier curves are provided in Supplementary File S6.

4. Discussion

This retrospective study using the TriNetX database demonstrated a direct association between COVID-19 and the overall development of thyroid cancer. Subgroup analysis revealed an increased risk of thyroid cancer in patients who developed hyperthyroidism or hypothyroidism following COVID-19, as well as in male patients. Individuals aged 60 years and older or those aged between 41 and 60 years, as well as those who received Nirmatrelvir/Ritonavir therapy, also exhibited a higher risk. However, among COVID-19 patients, only those who developed hyperthyroidism or hypothyroidism—compared with those without thyroid dysfunction—showed statistically significant results. Neither age (over 60 vs. 18–60 years or over 41 vs. 18–40 years) nor antiviral therapy (Nirmatrelvir/Ritonavir, Remdesivir, or Molnupiravir vs. no antiviral therapy) had a significant impact on thyroid cancer development.
There is limited evidence regarding the impact of COVID-19 on thyroid cancer development [29]. Xu et al. applied the Mendelian randomization (MR) method to analyze genome-wide association study data on COVID-19 susceptibility and severity in the European population. Their study suggested that hospitalization due to COVID-19 is associated with an increased risk of thyroid cancer development. However, MR results derived from genetic data did not show a significant association between COVID-19 susceptibility (risk of infection) or severity and thyroid cancer [30]. Hassan et al. conducted a retrospective study at an endocrine surgery center in the United Arab Emirates and found not only an increase in thyroid cancer cases undergoing surgery, but also more aggressive pathological features in the post-pandemic era (between January 2021 and December 2022) [31]. Our results demonstrated a direct association between COVID-19 diagnosis and the development of thyroid cancer. However, due to the limitations of the TriNetX database, we were unable to analyze the association between COVID-19 hospitalization and thyroid cancer development.
Given the indolent nature of thyroid cancer, the increased number of diagnoses observed after COVID-19 infection may partially reflect a diagnostic shift rather than a true rise in incidence. Several studies have reported delays in thyroid cancer screening and diagnosis during the pandemic, likely due to reduced healthcare access and concerns about aerosol-generating procedures such as fine-needle aspiration [32,33]. Bell et al. conducted a longitudinal analysis showing a decline in thyroid cancer diagnoses between March 2020 and December 2021, followed by a rebound exceeding pre-pandemic levels [34]. The authors attributed this to delayed diagnoses during the pandemic. Similarly, Virnceanu et al. noted not only a post-pandemic rise in incidence but also an increase in the presentation of giant thyroid cancers [35]. While such delays likely occurred equally across both COVID-19 and non-COVID-19 populations, this would only affect the results if patients with preexisting thyroid cancer had increased susceptibility to COVID-19. To address this issue, we note that to date, there is no evidence indicating increased susceptibility to COVID-19 among patients with thyroid cancer [29]. For example, a single-center study by Prete et al. reported no elevated prevalence of COVID-19 in patients with untreated thyroid cancer compared to the general population [36]. Thus, the likelihood of pre-existing, undiagnosed thyroid cancer should be similar between COVID-19 and non-COVID-19 groups.
Hyperthyroidism was previously thought to be associated with a decreased risk of thyroid cancer [37]. However, a systematic review and meta-analysis published in 2020 found that both hyperthyroidism and hypothyroidism are associated with an increased risk of thyroid cancer [38]. The potential for diagnostic bias may exist in those with pre-existing thyroid dysfunction, particularly due to increased medical attention and surveillance, such as thyroid ultrasonography. In our study, among COVID-19 patients, those who developed hyperthyroidism or hypothyroidism had a higher risk of thyroid cancer compared to those without thyroid dysfunction. To determine whether thyroid dysfunction or COVID-19 was primarily responsible for this increased risk, we specifically compared patients with thyroid dysfunction who had a prior COVID-19 infection to those with thyroid dysfunction who did not. Despite similar underlying thyroid conditions and likely comparable exposure to thyroid imaging, we observed a higher incidence of thyroid cancer in the post-COVID group. These findings suggest that the observed difference may not be solely attributed to increased ultrasound utilization associated with thyroid dysfunction. Instead, both thyroid dysfunction and COVID-19 itself may independently or synergistically contribute to an increased risk of thyroid cancer.
COVID-19 patients, especially those who were hospitalized, may have undergone more medical examinations, such as chest computed tomography scans to assess the severity of infection. These imaging studies could incidentally detect thyroid nodules, potentially leading to a higher likelihood of subsequent cancer diagnosis. This may partly explain our findings.
Many antiviral agents used to treat COVID-19 are known to reduce disease severity and shorten the duration of recovery [39,40,41]. Remdesivir, Nirmatrelvir/Ritonavir, and Molnupiravir have been shown to be effective in treating COVID-19 by inhibiting SARS-CoV-2 replication or viral RNA synthesis [42,43,44,45]. Additionally, Remdesivir has been reported to increase the ratio of T helper 2- to T helper 1-associated cytokines [39], while Nirmatrelvir/Ritonavir has been shown to reduce pro-inflammatory cytokine levels in COVID-19 patients [41,46]. In our study, compared to the non-COVID population, COVID-19 patients who received Nirmatrelvir/Ritonavir therapy exhibited an increased risk of thyroid cancer. However, when compared with COVID-19 patients who did not receive antiviral therapy, there was no significant difference in thyroid cancer risk after treatment with either antiviral agent. Therefore, none of these three antiviral agents appeared to reduce the incidence of thyroid cancer in our study.
Both mRNA and adenovirus-vectored COVID-19 vaccines have been reported to cause thyroiditis [47]. Thyroiditis can lead to alterations in thyroid function, potentially introducing bias into our analysis. Therefore, individuals who received any form of COVID-19 vaccination were excluded from this study.
Our study has several limitations. As noted by Ludwig et al. [48], studies utilizing electronic health records are subject to inherent biases. Retrospective cohort studies based on electronic data may suffer from incomplete access to raw clinical details, including hospitalization status, COVID-19 severity, patients’ vital signs, treatment regimens, thyroid cancer histological subtypes, and other important variables. Furthermore, due to limitations of the TriNetX platform, we were unable to perform full propensity score matching beyond age, gender, and obesity, which may affect the robustness of our comparisons. Differences in follow-up duration across subgroups may also lead to either an overestimation or an underestimation of thyroid cancer incidence. Additional sources of bias may arise from miscoding, inaccurate coding, or missing data related to comorbidities, socioeconomic status, gender and lifestyle factors, and family history of thyroid cancer. Finally, the observed increase in thyroid cancer incidence in certain subgroups may reflect delayed diagnoses or underdiagnosis during the pre-pandemic period, rather than a true increase in risk. The relatively small sample size, multiple comparisons, and absence of multivariable analysis in the subgroup analyses may also introduce bias.

5. Conclusions

This study identified an association between COVID-19 and the subsequent development of thyroid cancer across a large, diverse population. Subgroup analyses further revealed a significantly increased risk in male patients and in those who developed hyperthyroidism or hypothyroidism following COVID-19, suggesting that male sex and post-infectious thyroid dysfunction may amplify susceptibility to thyroid oncogenesis in the context of SARS-CoV-2 infection. However, limitations such as the retrospective design, incomplete clinical information, and constraints in propensity score matching warrant cautious interpretation of the findings. Prospective studies are needed to further clarify the relationship between COVID-19 and thyroid cancer.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/biomedicines13081933/s1. The original contributions presented in this study are included in the article/supplementary material. Further inquiries can be directed to the corresponding authors. Supplementary File S1: Detailed query criteria of post-COVID and non-COVID group. Query Criteria for Cohort post-COVID; Query Criteria for Cohort non-COVID. Supplementary File S2: Detailed query criteria of subgroups of population in post-COVID and non-COVID groups. Query Criteria for Cohort post-COVID, male; Query Criteria for Cohort non-COVID, male; Query Criteria for Cohort post-COVID, female; Query Criteria for Cohort non-COVID, female; Query Criteria for Cohort post-COVID, >60; Query Criteria for Cohort non-COVID, >60; Query Criteria for Cohort post-COVID, 41–60; Query Criteria for Cohort non-COVID, 41–60; Query Criteria for Cohort post-COVID, 18–40; Query Criteria for Cohort non-COVID, 18–40; Query Criteria for Cohort post-COVID, with hyperthyroidism; Query Criteria for Cohort post-COVID, with hypothyroidism; Query Criteria for Cohort post-COVID, s/p Nirmatrelvir/Ritonavir; Query Criteria for Cohort post-COVID, s/p Molnupiravir; Query Criteria for Cohort post-COVID, s/p Remdesivir. Supplementary File S3. Detailed query criteria of subgroup of population. Query Criteria for Cohort post-COVID, >41; Query Criteria for Cohort post-COVID, 18–40; Query Criteria for Cohort post-COVID, >60; Query Criteria for Cohort post-COVID, 18-60; Query Criteria for Cohort post-COVID, normal thyroid function; Query Criteria for Cohort post-COVID, with hypothyroidism; Query Criteria for Cohort post-COVID, with hyperthyroidism; Query Criteria for Cohort non-COVID, with hypothyroidism; Query Criteria for Cohort non-COVID, with hyperthyroidism. Supplementary File S4. Kaplan-Meier graph of thyroid cancer risk in different subgroups of COVID-19 patients. Supplementary Figure S4.1. Kaplan—Meier survival curve of thyroid cancer risk in male populations. Supplementary Figure S4.2. Kaplan—Meier survival curve of thyroid cancer risk in female populations. Supplementary Figure S4.3. Kaplan—Meier survival curve of thyroid cancer risk in populations aged between 18 and 40 years. Supplementary Figure S4.4. Kaplan—Meier survival curve of thyroid cancer risk in populations aged between 41 and 60 years. Supplementary Figure S4.5. Kaplan—Meier survival curve of thyroid cancer risk in populations aged over 60 years. Supplementary Figure S4.6. Kaplan—Meier survival curve of thyroid cancer risk in post-COVID populations who developed hyperthyroidism vs non-COVID populations. Supplementary Figure S4.7. Kaplan—Meier survival curve of thyroid cancer risk in post-COVID populations who developed hypothyroidism vs non-COVID populations. Supplementary Figure S4.8. Kaplan—Meier survival curve of thyroid cancer risk in post-COVID populations who had no thyroid function alteration vs non-COVID populations. Supplementary Figure S4.9. Kaplan—Meier survival curve of thyroid cancer risk in post-COVID populations who received Nirmatrelvir/Ritonavir treatment vs non-COVID populations. Supplementary Figure S4.10. Kaplan—Meier survival curve of thyroid cancer risk in post-COVID populations who received Remdesivir treatment vs non-COVID populations. Supplementary Figure S4.11. Kaplan—Meier survival curve of thyroid cancer risk in post-COVID populations who received Molnupiravir treatment vs non-COVID populations. Supplementary File S5. Kaplan-Meier graph of thyroid cancer risk in different subpopulations following COVID-19. Supplementary Figure S5.1. Kaplan—Meier survival curve of thyroid cancer risk in different age interval of post-COVID populations. Supplementary Figure S5.2. Kaplan—Meier survival curve of thyroid cancer risk in different age interval of post-COVID populations. Supplementary Figure S5.3. Kaplan—Meier survival curve of thyroid cancer risk in post-COVID populations with hyperthyroidism vs no thyroid function alteration. Supplementary Figure S5.4. Kaplan—Meier survival curve of thyroid cancer risk in post-COVID populations with hypothyroidism vs no thyroid function alteration. Supplementary Figure S5.5. Kaplan—Meier survival curve of thyroid cancer risk in post-COVID populations who received Nirmatrelvir/Ritonavir vs no antiviral treatment. Supplementary Figure S5.6. Kaplan—Meier survival curve of thyroid cancer risk in post-COVID populations who received Remdesivir vs no antiviral treatment. Supplementary Figure S5.7. Kaplan—Meier survival curve of thyroid cancer risk in post-COVID populations who received Molnupiravir vs no antiviral treatment. Supplementary File S6. Kaplan–Meier curve illustrating the risk of thyroid cancer in subpopulations with thyroid dysfunction, stratified by COVID-19 status. Supplementary Figure S6.1. Kaplan—Meier survival curve of thyroid cancer risk in hyperthyroidism populations with or without COVID-19. Supplementary Figure S6.2. Kaplan—Meier survival curve of thyroid cancer risk in hypothyroidism populations with or without COVID-19.

Author Contributions

H.-Y.W. wrote the draft of the manuscript; H.-Y.W. and C.-H.C. performed data analysis; C.-H.C. and S.-C.T. designed and supervised this study. S.-C.T., Y.-C.L., J.-U.H. and C.-H.C. revised the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The use of TriNetX for this study was approved under the authority of the Institutional Review Board of Taichung Veterans General Hospital (TCVGH-IRB No. CE25331B) on 12 June 2025. The Western Institutional Review Board granted TriNetX a waiver of informed consent, as the platform only aggregates counts and statistical summaries of deidentified information.

Informed Consent Statement

Not applicable.

Data Availability Statement

All data generated or analyzed during this study are included in this published article and its Supplementary Files.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
ACE2angiotensin-converting enzyme II
CIconfidence interval
HCOshealthcare organizations
HRhazard ratio
MRMendelian randomization
nspnonstructural protein

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Figure 1. Flowchart illustrating the construction of the study cohort from the TriNetX database.
Figure 1. Flowchart illustrating the construction of the study cohort from the TriNetX database.
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Figure 2. Kaplan–Meier survival curve comparing the risk of thyroid cancer between the post-COVID and non-COVID groups.
Figure 2. Kaplan–Meier survival curve comparing the risk of thyroid cancer between the post-COVID and non-COVID groups.
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Figure 3. Forest plot showing the risk of thyroid cancer across different subgroups of COVID-19 patients compared to non-COVID-19 individuals or to those of the corresponding gender or age group.
Figure 3. Forest plot showing the risk of thyroid cancer across different subgroups of COVID-19 patients compared to non-COVID-19 individuals or to those of the corresponding gender or age group.
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Figure 4. Forest plot illustrating thyroid cancer risk across different subpopulations following COVID-19.
Figure 4. Forest plot illustrating thyroid cancer risk across different subpopulations following COVID-19.
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Figure 5. Forest plot comparing thyroid cancer risk in patients with thyroid dysfunction, with and without a history of COVID-19.
Figure 5. Forest plot comparing thyroid cancer risk in patients with thyroid dysfunction, with and without a history of COVID-19.
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Table 1. Detailed criteria used to define a positive SARS-CoV-2 PCR test.
Table 1. Detailed criteria used to define a positive SARS-CoV-2 PCR test.
CodeName
UMLS:LNC:94500-6SARS-CoV-2 (COVID-19) RNA [Presence] in respiratory specimen by NAA with probe detection (labResult: Positive)
UMLS:LNC:94309-2SARS-CoV-2 (COVID-19) RNA [Presence] in specimen by NAA with probe detection (labResult: Positive)
UMLS:LNC:94565-9SARS-CoV-2 (COVID-19) RNA [Presence] in nasopharynx by NAA with non-probe detection (labResult: Positive)
UMLS:LNC:94759-8SARS-CoV-2 (COVID-19) RNA [Presence] in nasopharynx by NAA with probe detection (labResult: Positive)
UMLS:LNC:95608-6SARS-CoV-2 (COVID-19) RNA [Presence] in respiratory specimen by NAA with non-probe detection (labResult: Positive)
UMLS:LNC:94845-5SARS-CoV-2 (COVID-19) RNA [Presence] in saliva (oral fluid) by NAA with probe detection (labResult: Positive)
UMLS:LNC:95406-5SARS-CoV-2 (COVID-19) RNA [Presence] in nose by NAA with probe detection (labResult: Positive)
Table 2. Detailed criteria for defining SARS-CoV-2 vaccination status.
Table 2. Detailed criteria for defining SARS-CoV-2 vaccination status.
CodeName
NLM:CVX:208COVID-19, mRNA, LNP-S, PF, 30 mcg/0.3 mL dose
NLM:CVX:207COVID-19, mRNA, LNP-S, PF, 100 mcg/0.5 mL dose or 50 mcg/0.25 mL dose
NLM:CVX:212COVID-19 vaccine, vector-nr, rS-Ad26, PF, 0.5 mL
NLM:RXNORM:OMOP5042939COVID-19 vaccine
NLM:CVX:300COVID-19, mRNA, LNP-S, bivalent, PF, 30 mcg/0.3 mL dose
NLM:CVX:217COVID-19, mRNA, LNP-S, PF, 30 mcg/0.3 mL dose, tris-sucrose
NLM:CVX:229COVID-19, mRNA, LNP-S, bivalent, PF, 50 mcg/0.5 mL or 25 mcg/0.25 mL dose
NLM:CVX:218COVID-19, mRNA, LNP-S, PF, 10 mcg/0.2 mL dose, tris-sucrose
NLM:CVX:520COVID-19 mRNA, bivalent, original/Omicron BA.1, non-US vaccine product, Pfizer-BioNTech
NLM:CVX:519COVID-19 mRNA, bivalent, original/Omicron BA.1, non-US vaccine (Spikevax Bivalent), Moderna
NLM:CVX:301COVID-19, mRNA, LNP-S, bivalent, PF, 10 mcg/0.2 mL dose
NLM:CVX:219COVID-19, mRNA, LNP-S, PF, 3 mcg/0.2 mL dose, tris-sucrose
NLM:CVX:228COVID-19, mRNA, LNP-S, PF, pediatric 25 mcg/0.25 mL dose
NLM:CVX:230COVID-19, mRNA, LNP-S, bivalent booster, PF, 10 mcg/0.2 mL
NLM:CVX:221COVID-19, mRNA, LNP-S, PF, 50 mcg/0.5 mL dose
NLM:CVX:210COVID-19 vaccine, vector-nr, rS-ChAdOx1, PF, 0.5 mL
NLM:CVX:302COVID-19, mRNA, LNP-S, bivalent, PF, 3 mcg/0.2 mL dose
NLM:CVX:511COVID-19 IV non-US vaccine (CoronaVac, Sinovac)
NLM:RXNORM:2468231SARS-CoV-2 (COVID-19) vaccine, mRNA spike protein
UMLS:CPT:91300Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative-free, 30 mcg/0.3 mL dosage, diluent reconstituted, for intramuscular use
UMLS:CPT:0001AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative-free, 30 mcg/0.3 mL dosage, diluent-reconstituted; first dose
UMLS:CPT:0002AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative-free, 30 mcg/0.3 mL dosage, diluent-reconstituted; second dose
UMLS:CPT:91301Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative free, 100 mcg/0.5 mL dosage, for intramuscular use
UMLS:CPT:0011AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative-free, 100 mcg/0.5 mL dosage; first dose
UMLS:CPT:0012AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative-free, 100 mcg/0.5 mL dosage; second dose
UMLS:SNOMED:840534001Administration of SARS-CoV-2 antigen vaccine
NLM:CVX:213SARS-CoV-2 (COVID-19) vaccine
UMLS:CPT:1036660Immunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative-free, 30 mcg/0.3 mL dosage, diluent reconstituted
UMLS:CPT:1036663Immunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative-free, 100 mcg/0.5 mL dosage
UMLS:CPT:0124AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, bivalent spike protein, preservative free, 30 mcg/0.3 mL dosage, tris-sucrose formulation; booster dose
UMLS:CPT:0004AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative-free, 30 mcg/0.3 mL dosage, diluent-reconstituted; booster dose
UMLS:CPT:0003AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative-free, 30 mcg/0.3 mL dosage, diluent-reconstituted; third dose
UMLS:CPT:1037166Immunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative-free, 30 mcg/0.3 mL dosage, tris-sucrose formulation
UMLS:CPT:0054AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative-free, 30 mcg/0.3 mL dosage, tris-sucrose formulation; booster dose
UMLS:CPT:0064AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative free, 50 mcg/0.25 mL dosage; booster dose
UMLS:CPT:90480Immunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine; single dose
UMLS:CPT:1037171Immunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative-free, 10 mcg/0.2 mL dosage, diluent reconstituted, tris-sucrose formulation
UMLS:CPT:0071AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative-free, 10 mcg/0.2 mL dosage, diluent reconstituted, tris-sucrose formulation; first dose
UMLS:CPT:0072AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative-free, 10 mcg/0.2 mL dosage, diluent reconstituted, tris-sucrose formulation; second dose
NLM:RXNORM:2610319SARS-CoV-2 (COVID-19) vaccine, mRNA-BNT162b2 0.05 MG/ML/SARS-CoV-2 (COVID-19) vaccine, mRNA-BNT162b2 OMICRON (BA.4/BA.5) 0.05 MG/ML injectable suspension
UMLS:CPT:91313Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, bivalent, preservative-free, 50 mcg/0.5 mL dosage, for intramuscular use
UMLS:CPT:0134AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, bivalent, preservative-free, 50 mcg/0.5 mL dosage; booster dose
UMLS:CPT:1037175Immunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, DNA, spike protein, adenovirus type 26 (Ad26) vector, preservative-free, 5 × 1010 viral particles/0.5 mL dosage
NLM:RXNORM:26103470.3 ML SARS-CoV-2 (COVID-19) vaccine, mRNA-BNT162b2 0.05 MG/ML/SARS-CoV-2 (COVID-19) vaccine, mRNA-BNT162b2 OMICRON (BA.4/BA.5) 1 MG/ML injection
UMLS:CPT:1037228Immunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative-free, 3 mcg/0.2 mL dosage, diluent-reconstituted, tris-sucrose formulation
UMLS:CPT:0013AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative-free, 100 mcg/0.5 mL dosage; third dose
UMLS:CPT:0081AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative-free, 3 mcg/0.2 mL dosage, diluent-reconstituted, tris-sucrose formulation; first dose
UMLS:CPT:0082AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative-free, 3 mcg/0.2 mL dosage, diluent-reconstituted, tris-sucrose formulation; second dose
NLM:RXNORM:2610328SARS-CoV-2 (COVID-19) vaccine, mRNA-1273 0.05 MG/ML/SARS-CoV-2 (COVID-19) vaccine, mRNA-1273 OMICRON (BA.4/BA.5) 0.05 MG/ML injectable suspension
UMLS:CPT:0154AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, bivalent spike protein, preservative free, 10 mcg/0.2 mL dosage, diluent reconstituted, tris-sucrose formulation; booster dose
UMLS:CPT:0053AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative free, 30 mcg/0.3 mL dosage, tris-sucrose formulation; third dose
UMLS:CPT:1037332Immunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative free, 25 mcg/0.25 mL dosage
UMLS:CPT:0052AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative free, 30 mcg/0.3 mL dosage, tris-sucrose formulation; second dose
UMLS:CPT:0111AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative free, 25 mcg/0.25 mL dosage; first dose
UMLS:CPT:0051AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative free, 30 mcg/0.3 mL dosage, tris-sucrose formulation; first dose
UMLS:CPT:91311Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative free, 25 mcg/0.25 mL dosage, for intramuscular use
UMLS:CPT:0074AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative free, 10 mcg/0.2 mL dosage, diluent reconstituted, tris-sucrose formulation; booster dose
UMLS:CPT:0112AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative free, 25 mcg/0.25 mL dosage; second dose
UMLS:CPT:0083AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative free, 3 mcg/0.2 mL dosage, diluent reconstituted, tris-sucrose formulation; third dose
UMLS:CPT:0073AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative free, 10 mcg/0.2 mL dosage, diluent reconstituted, tris-sucrose formulation; third dose
UMLS:CPT:0173AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, bivalent spike protein, preservative free, 3 mcg/0.2 mL dosage, diluent reconstituted, tris-sucrose formulation; third dose
UMLS:CPT:0164AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, bivalent, preservative free, 10 mcg/0.2 mL dosage; booster dose
UMLS:CPT:1037838Immunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative free, 50 mcg/0.5 mL dosage
UMLS:CPT:0094AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative free, 50 mcg/0.5 mL dosage; booster dose, when administered to individuals aged 18 years and over
UMLS:CPT:0034AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, DNA, spike protein, adenovirus type 26 (Ad26) vector, preservative free, 5 × 1010 viral particles/0.5 mL dosage; booster dose
UMLS:CPT:0144AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, bivalent, preservative free, 25 mcg/0.25 mL dosage; booster dose
UMLS:CPT:0091AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative free, 50 mcg/0.5 mL dosage; first dose, when administered to individuals aged 6 through 11 years
UMLS:CPT:0174AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, bivalent spike protein, preservative free, 3 mcg/0.2 mL dosage, diluent reconstituted, tris-sucrose formulation; booster
UMLS:CPT:0092AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative free, 50 mcg/0.5 mL dosage; second dose, when administered to individuals aged 6 through 11 years
UMLS:CPT:1036682Immunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, recombinant spike protein nanoparticle, saponin-based adjuvant, preservative free, 5 mcg/0.5 mL dosage
UMLS:CPT:0041AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, recombinant spike protein nanoparticle, saponin-based adjuvant, preservative free, 5 mcg/0.5 mL dosage; first dose
UMLS:CPT:0113AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative free, 25 mcg/0.25 mL dosage; third dose
UMLS:CPT:0042AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, recombinant spike protein nanoparticle, saponin-based adjuvant, preservative free, 5 mcg/0.5 mL dosage; second dose
UMLS:CPT:0093AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, mRNA-LNP, spike protein, preservative free, 50 mcg/0.5 mL dosage; third dose, when administered to individuals aged 6 through 11 years
UMLS:CPT:1036666Immunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, DNA, spike protein, chimpanzee adenovirus Oxford 1 (ChAdOx1) vector, preservative free, 5 × 1010 viral particles/0.5 mL dosage
UMLS:CPT:0044AImmunization administration by intramuscular injection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease [COVID-19]) vaccine, recombinant spike protein nanoparticle, saponin-based adjuvant, preservative free, 5 mcg/0.5 mL dosage; booster
Table 3. Characteristics of the post-COVID group (Cohort 1) and non-COVID group (Cohort 2) before and after propensity score matching.
Table 3. Characteristics of the post-COVID group (Cohort 1) and non-COVID group (Cohort 2) before and after propensity score matching.
Before Propensity Score MatchingAfter Propensity Score Matching
Cohort PatientsMean ± SDp-ValueStd Diff.PatientsMean ± SDp-ValueStd Diff.
1
2		Age at Index2,176,997
28,535,672		48.8 +/− 20.1
48.5 +/− 20.4		<0.0010.0142,176,997
2,176,997		48.8 +/− 20.1
48.8 +/− 20.1		1<0.001
Cohort Patients% of Cohortp-ValueStd diff.Patients% of Cohortp-ValueStd diff.
1
2		Male916,516
12,413,017		42.1%
43.5%		<0.0010.028916,516
916,516		42.1%
42.1%		1<0.001
1
2		Female1,260,481
16,221,655		57.9%
56.5%		<0.0010.0281,260,481
1,260,481		57.9%
57.9%		1<0.001
1
2		White1,254,735
13,920,716		54.5%
49.4%		<0.0010.1021,254,735
1,174,062		54.5%
51.0%		<0.0010.070
1
2		Asian54,299
972,965		2.4%
3.5%		<0.0010.06554,299
74,568		2.4%
3.2%		<0.0010.053
1
2		Black or African American345,156
3,320,705		15.0%
11.8%		<0.0010.094345,156
295,739		15.0%
12.8%		<0.0010.062
1
2		Other Race66,799
1,072,646		2.9%
3.8%		<0.0010.05066,799
82,598		2.9%
3.6%		<0.0010.039
1
2		Unknown Race564,364
8,707,668		24.5%
30.9%		<0.0010.143564,364
659,678		24.5%
28.7%		<0.0010.094
1
2		Personal history of nicotine dependence197,813
790,130		8.6%
2.8%		<0.0010.252197,813
96,657		8.6%
4.2%		<0.0010.180
1
2		Personal history of irradiation19,856
101,810		0.9%
0.4%		<0.0010.06419,856
11,444		0.9%
0.5%		<0.0010.044
1
2		Overweight and obesity391,198
1,656,174		17.0%
5.9%		<0.0010.355391,198
391,198		17.0%
17.0%		1<0.001
1
2		Diabetes mellitus293,835
1,534,074		12.8%
5.4%		<0.0010.257293,835
189,472		12.8%
8.2%		<0.0010.148
1
2		Hypertensive diseases635,880
3,663,669		27.6%
13.0%		<0.0010.370635,880
413,136		27.6%
17.9%		<0.0010.232
1
2		Ischemic heart diseases213,759
1,160,544		9.3%
4.1%		<0.0010.208213,759
127,732		9.3%
5.5%		<0.0010.143
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Wang, H.-Y.; Lin, Y.-C.; Hou, J.-U.; Chao, C.-H.; Tsai, S.-C. Association Between COVID-19 Infection and Thyroid Cancer Development: A Retrospective Cohort Study Using the TriNetX Database. Biomedicines 2025, 13, 1933. https://doi.org/10.3390/biomedicines13081933

AMA Style

Wang H-Y, Lin Y-C, Hou J-U, Chao C-H, Tsai S-C. Association Between COVID-19 Infection and Thyroid Cancer Development: A Retrospective Cohort Study Using the TriNetX Database. Biomedicines. 2025; 13(8):1933. https://doi.org/10.3390/biomedicines13081933

Chicago/Turabian Style

Wang, Hsin-Yi, Yi-Ching Lin, Jing-Uei Hou, Chih-Hao Chao, and Shih-Chuan Tsai. 2025. "Association Between COVID-19 Infection and Thyroid Cancer Development: A Retrospective Cohort Study Using the TriNetX Database" Biomedicines 13, no. 8: 1933. https://doi.org/10.3390/biomedicines13081933

APA Style

Wang, H.-Y., Lin, Y.-C., Hou, J.-U., Chao, C.-H., & Tsai, S.-C. (2025). Association Between COVID-19 Infection and Thyroid Cancer Development: A Retrospective Cohort Study Using the TriNetX Database. Biomedicines, 13(8), 1933. https://doi.org/10.3390/biomedicines13081933

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