Sex and Mortality Among Patients with Papillary Thyroid Cancer

Liufeng Wu; Zhuo Wang; Shuhuang Lin; Aarti Mathur; Ying Li; Bela Bendlova; Vlasta Kuklikova; Miguel Melo; Tito Teles Jesus; Paula Soares; Carla Colombo; Laura Fugazzola; Norisato Mitsutake; Michiko Matsuse; Ayaka Sako; Ana P Estrada-Florez; Mabel E Bohórquez; Luis G Carvajal-Carmona; Caterina Mian; Federica Vianello; Christine J O’Neill; Roderick Clifton-Bligh; Agnieszka Czarniecka; Barbara Jarzab; Chan Kwon Jung; Bayu Brahma; Paul W Ladenson; Young Joo Park; Mingzhao Xing

doi:10.1001/jamanetworkopen.2026.35582

. 2026 Sep 29;9(9):e2635582. doi: 10.1001/jamanetworkopen.2026.35582

Sex and Mortality Among Patients with Papillary Thyroid Cancer

Liufeng Wu ¹, Zhuo Wang ¹, Shuhuang Lin ¹, Aarti Mathur ², Ying Li ³, Bela Bendlova ⁴, Vlasta Kuklikova ⁴, Miguel Melo ^5,⁶, Tito Teles Jesus ⁶, Paula Soares ^6,⁷, Carla Colombo ^8,⁹, Laura Fugazzola ^10,¹¹, Norisato Mitsutake ¹², Michiko Matsuse ¹², Ayaka Sako ¹², Ana P Estrada-Florez ^13,¹⁴, Mabel E Bohórquez ¹⁴, Luis G Carvajal-Carmona ^13,²⁵, Caterina Mian ¹⁵, Federica Vianello ¹⁶, Christine J O’Neill ¹⁷, Roderick Clifton-Bligh ¹⁸, Agnieszka Czarniecka ¹⁹, Barbara Jarzab ²⁰, Chan Kwon Jung ²¹, Bayu Brahma ²², Paul W Ladenson ²³, Young Joo Park ^3,²⁴, Mingzhao Xing ^1,^23,^✉

¹School of Medicine, Southern University of Science and Technology, Shenzhen, Guangdong, China

²Division of Endocrine Surgery, Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, Maryland

³Department of Internal Medicine, College of Medicine, Seoul National University, Seoul, Korea

⁴Department of Molecular Endocrinology, Institute of Endocrinology, Prague, Czech Republic

⁵Department of Endocrinology, Diabetes and Metabolism, Coimbra Local Health Unit, Coimbra, Portugal

⁶Cancer Signalling & Metabolism, Instituto de Investigação e Inovação em Saúde (i³S), Universidade do Porto and Instituto de Patologia e Imunologia Molecular da Universidade do Porto (Ipatimup), Porto, Portugal

⁷Faculty of Medicine, the University of Porto, Porto, Portugal

⁸Endocrine Oncology Unit, Department of Endocrine and Metabolic Diseases, Istituto Auxologico Italiano IRCCS, Milan, Italy

⁹Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy

¹⁰Department of Health Sciences, University of Milan, Milan, Italy

¹¹Department of Endocrinology, ASST Santi Paolo e Carlo, Milan, Italy

¹²Department of Molecular Oncology, Atomic Bomb Disease Institute, Nagasaki University, Nagasaki, Japan

¹³The Health Equity Leadership, Science, and Community Research Laboratory, Genome Center, University of California, Davis

¹⁴Grupo de Citogenética, Filogenia y Evolución de Poblaciones, Facultades de Ciencias y Facultad de Ciencias de la Salud, Universidad del Tolima, Ibagué, Colombia

¹⁵Endocrinology Unit, Department of Medicine (DIMED), University of Padua, Padua, Italy

¹⁶Department of Radiotherapy, Istituto Oncologico Veneto-IRCCS, Padua, Italy

¹⁷Surgical Services, John Hunter Hospital and University of Newcastle, Newcastle, New South Wales, Australia

¹⁸Cancer Genetics, Kolling Institute of Medical Research, University of Sydney, St Leonards, New South Wales, Australia

¹⁹The Third Department of Oncological Surgery, Maria Sklodowska-Curie National Research Institute of Oncology Gliwice Branch, Gliwice, Poland

²⁰Nuclear Medicine and Endocrine Oncology Department, Maria Sklodowska-Curie National Research Institute of Oncology Gliwice Branch, Gliwice, Poland

²¹Department of Hospital Pathology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea

²²Department of Surgical Oncology, Dharmais Cancer Hospital–National Cancer Center, Jakarta, Indonesia

²³Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland

²⁴Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Korea

²⁵Department of Biochemistry and Molecular Medicine, School of Medicine, University of California, Davis

Accepted for Publication: July 13, 2026.

Published: September 29, 2026. doi:10.1001/jamanetworkopen.2026.35582

Open Access: This is an open access article distributed under the terms of the CC-BY-NC-ND License, which does not permit alteration or commercial use, including those for text and data mining, AI training, and similar technologies. © 2026 Wu L et al. JAMA Network Open.

^✉

Corresponding Author: Mingzhao Xing, MD, PhD, School of Medicine, Southern University of Science and Technology, 1088 Xueyuan Ave, Nanshan District, Shenzhen, Guangdong 518055, China (mxing1@jhmi.edu; xingmz@sustech.edu.cn).

Author Contributions: Drs Xing and Wu had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Drs Wu and Wang were co–first authors.

Concept and design: Xing.

Acquisition, analysis, or interpretation of data: Wu, Wang, Lin, Mathur, Li, Bendlova, Kuklikova, Melo, Jesus, Soares, Colombo, Fugazzola, Mitsutake, Matsuse, Sako, Estrada-Florez, Bohorquez-Lozano, Carvajal Carmona, Mian, Vianello, O’Neill, Clifton-Bligh, Czarniecka, Jarzab, Jung, Brahma, Ladenson, Park, Xing.

Drafting of the manuscript: Wu, Wang, Xing.

Critical review of the manuscript for important intellectual content: Wu, Wang, Lin, Mathur, Li, Bendlova, Kuklikova, Melo, Jesus, Soares, Colombo, Fugazzola, Mitsutake, Matsuse, Sako, Estrada-Florez, Bohorquez-Lozano, Carvajal Carmona, Mian, Vianello, O’Neill, Clifton-Bligh, Czarniecka, Jarzab, Jung, Brahma, Ladenson, Park, Xing.

Statistical analysis: Wu, Wang, Lin, Xing.

Obtained funding: Bendlova, Jesus, Soares, Carvajal Carmona, Park, Xing.

Administrative, technical, or material support: Wu, Wang, Mathur, Bendlova, Kuklikova, Melo, Jesus, Colombo, Mitsutake, Matsuse, Sako, Bohorquez-Lozano, Vianello, O’Neill, Clifton-Bligh, Czarniecka, Jung, Brahma, Park, Xing.

Supervision: Melo, Fugazzola, Carvajal Carmona, Mian, Vianello, Jarzab, Ladenson, Park, Xing.

Conflict of Interest Disclosures: Dr Melo reported receiving personal fees from Bial and Abbott; he reported receiving nonfinancial support from Lilly for providing assistance with statistical analysis outside the submitted work; and he reported receiving travel support from Menarini outside the submitted work. Dr Soares reported grants from Fundação para a Ciência e a Tecnologia (Foundation for Science and Technology) during the conduct of the study; in addition, Dr Soares had a patent for TERT promoter mutations licensed. Dr Clifton-Bligh reported speaker fees from Kyowa Kirin, Specialized Therapeutics, and Lilly outside the submitted work; he reported personal fees from Amgen, Pfizer, and The Endocrine Society outside the submitted work. Dr Jarzab reported holding multiple US patents (issued, EP4303323 and EP4023770; pending, EP4303324). Dr Xing reported a patent for US 7 378 233 B2 with royalties paid through Johns Hopkins University as an inventor on the patent related to a BRAF mutation in thyroid cancer, and he also receives royalties for another patent (US 7 923 460 B2). No other disclosures were reported.

Funding/Support: This study was partially supported by a merit-based research funding from the Southern University of Science and Technology in Shenzhen, China (to Dr Xing); the National Institute on Aging (grant No. R01AG076834, to Dr Mathur); Government of the Czech Republic (AZV No. NU21-01-00448 and EU No. 00023761, Drs Bendlova and Kuklikova); the Prémio Francisco Augusto da Fonseca Dias e Maria José Melenas da Fonseca para Jovens Investigadores (Drs Melo, Jesus, and Soares); Plano de Recuperação e Resiliência and Fundos Europeus NextGenerationEU, through Agendas para a Inovação Empresarial (No. C644919832-00000035, to Dr Jesus); the Italian Ministry of Health (THY-CANC No. 2.773.026, to Drs Colombo and Fugazzola); Japan Society for the Promotion of Science KAKENHI (grant No. 23H02860, to Dr Mitsutake); the HEAL HER program (Heart, Breast, and Brain Health Equity Research program) and the National Institutes of Health (grant No. D43CA260869, to Dr Carvajal-Carmona); the American Association for Cancer Research Fellowship (No. 21-40-69-ESTR), Minciencias of Colombia (graduate scholarship No. 647/2014), and L’Oreal-UNESCO of Colombia (project No. 3900917/2017, to Dr Estrada-Florez); Universidad del Tolima of Colombia (project Nos. 400111, 360113, and 170130517; to Dr Bohórquez); the National Center for Research and Development, Poland (No. STRATEGMED2/267398/4/NCBR/2015, to Drs Jarzab and Czarniecka); Ministry of Health of the Republic of Indonesia (grant No. HK.05.01/I/2283/2014, to Dr Brahma); and the Information and Communications Technology and Future Planning of the Basic Science Research Program via the National Research Foundation of Korea (NRF), funded by the Korean Ministry of Science (grant No. NRF-2019R1A2C2084332, to Dr Park).

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement 2.

Additional Contributions: We would like to acknowledge the Colombian Thyroid Cancer Epidemiology Collaborative Group members in Colombia, including Alejandro Vélez, MD (Hospital Pablo Tobón Uribe), Carlos S. Duque, MD (Hospital Pablo Tobón Uribe), Jorge H. Donado, MD (Hospital Pablo Tobón Uribe), Gilbert Mateus, MD (Hospital Federico Lleras Acosta), Cesar Panqueba-Tarazona, MD (Hospital Hernando Moncaleano Perdomo), Guadalupe Polanco-Echeverry, MSc (University of California, Davis), Ruta Sahasrabudhe, MSc (University of California, Davis), and Magdalena Echeverry, PhD (Universidad del Tolima); the Collaborative Outcomes Research Group in Endocrine Surgery at Johns Hopkins members in the US, including Rachel Stemme; the Czech collaborators involved in this research, especially pathologist Daniela Nováková Kodetová, MD (Charles University and Motol University Hospital); the Royal North Shore Hospital/Kolling Institute Thyroid Cancer Group members in Australia, including Mark Sywak, MBBS (Royal North Shore Hospital), Stan Sidhu, PhD (Royal North Shore Hospital), Bruce Robinson, MD (Royal North Shore Hospital), Matti Gild, PhD (Royal North Shore Hospital), Ahmad (Adam) Mohammadi Aniss, PhD (Royal North Shore Hospital), Anthony Gill, and Martyn Bullock, PhD (Royal North Shore Hospital).

^✉

Corresponding author.

PMCID: PMC13624873 PMID: 42809287

Key Points

Question

Is patient sex a primary mortality risk factor in papillary thyroid cancer (PTC)?

Findings

In this cohort study of 4746 adults diagnosed with PTC, male sex was found to be a significant patient age- and tumor genetic–dependent mortality risk specific to PTC; it was highest in male patients aged 45 years or older with dual BRAF V600E/TERT promoter mutations, with an adjusted male-to-female hazard ratio of 3.07.

Meaning

This study supports the integration of patient sex, in conjunction with patient age and tumor genetics, into the risk prognostication of PTC to improve its clinical precision management.

This cohort study of adults diagnosed with papillary thyroid cancer examines the association of cancer-specific mortality risk with patient sex in combination with age and tumor genetic mutations.

Abstract

Importance

Unlike patient age, which has been a well-established and routinely used primary biological prognostic factor in the risk stratification of papillary thyroid cancer (PTC), the prognostic value of patient sex remains controversial in this common endocrine malignant neoplasm.

Objective

To examine PTC-specific mortality risk of sex with respect to patient age and tumor genetics—specifically the status of BRAF V600E and TERT promoter (TERTp) mutations.

Design, Setting, and Participants

This cohort study was conducted among patients with PTC with an overall median (IQR) follow-up time of 51.0 (26.4-109.1) months after initial treatment at 15 centers in 10 countries between 1979 and 2023. Data analysis was completed in December 2025 and examined aggregately for the association of PTC-specific mortality and patient sex with respect to patient age and BRAF V600E and TERTp mutation.

Main Outcome and Measure

Patient deaths specifically caused by PTC.

Results

The study included 4746 patients with PTC (median [IQR] age, 48 [37-59] years; 3612 women [76.1%]). Male patients, compared with female patients, demonstrated a higher overall PTC-specific mortality (3.7% [42 of 1134] vs 1.7% [60 of 3612]; P < .001). This male sex–associated risk was observed only in patients harboring BRAF V600E or TERTp mutations, not wild-type genes. PTC-specific mortality particularly paralleled the occurrence and accumulation of dual BRAF V600E and TERTp mutations, which all exhibited a patient age-dependent rise, beginning to be prominent around age 45 years and markedly amplified by male sex. A male sex-age synergy index of 1.81 (95% CI, 1.02-3.16) and a male-to-female hazard ratio of 3.07 (95% CI, 1.35-6.97; P = .007) after adjustment for clinicopathologic factors in mortality risk were observed in patients aged 45 years or older with dual mutations.

Conclusions and Relevance

This cohort study reconciled previous controversies on the prognostic value of patient sex and establishes male sex as a cardinal mortality risk in PTC in a patient age- and tumor genetic-dependent manner, defining especially male patients aged 45 years and older with dual BRAF V600E and TERTp mutations as having the worst prognosis and supporting integration of patient sex into risk stratification of PTC.

Introduction

Papillary thyroid cancer (PTC), accounting for 85% to 90% of all thyroid malignant neoplasms, is a common endocrine disease.^1,2,3 Appropriate management of this disease, which relies on the accurate assessment of its prognostic risk, particularly mortality risk, is important and often challenging. In fact, mortality risk assessment is a cardinal step in defining the management strategy for individual patients with PTC. This is currently achieved primarily using clinicopathologic-based assessment systems, such as the American Joint Committee on Cancer (AJCC) staging system.^4,5 One prominent biological factor in this assessment, which has long been appreciated but not formally employed, is patient sex. Many studies have suggested that male patients with PTC more frequently present with aggressive tumor behaviors, including larger tumor, lymph node metastasis, distant metastasis, tumor recurrence, and patient mortality.^{6,7,8,9,10,11} Yet, many other studies have not confirmed this role of patient sex.^{12,13,14,15,16,17} Thus, unlike patient age, which is a well-established and routinely used primary biological prognostic risk factor in PTC,^{3,18,19,20,21} patient sex remains controversial for its prognostic value. Consequently, while patient age is a cardinal variable in the AJCC system for the mortality risk stratification of thyroid cancer, patient sex has been excluded from it.^4,5

Over the past decade, the value of tumor genetics in risk prognostication of PTC has been increasingly recognized.^{3,22,23,24,25} In particular, BRAF V600E and TERT promoter (TERTp) mutations, especially when coexisting, have been recognized as important genetic predictors of poor prognosis in PTC.^{26,27,28,29,30} We have previously observed an association of male sex⁸ and older patient age³¹ with PTC-specific mortality, both in a BRAF V600E–dependent manner. Moreover, several studies have reported that TERTp mutation in PTC is more prevalent in male^32,33,34 and older patients.³⁵ Based on these previous observations, we tested the hypothesis that 3 basic biological factors—patient sex, patient age, and tumor genetics (specifically BRAF V600E and TERTp mutations)—may interact to adversely affect PTC-specific mortality risk; as such, patient sex may be a patient age- and tumor genetic–dependent prognostic risk factor.

Methods

Study Design and Participants

This was an international, multicenter, and retrospective cohort study, including patients with PTC retrospectively and consecutively recruited at each of the 15 medical centers in 10 countries from January 1979 to July 2023 as reported previously (eAppendix, eTable 1 in Supplement 1).³⁰ The median (IQR) clinical follow-up time of patients from their initial thyroid surgery was 51.0 (26.4-109.1) months. All patients had histopathologically confirmed diagnosis of PTC, which was made according to contemporary World Health Organization criteria of thyroid neoplasm pathology. Patients received total thyroidectomy or hemithyroidectomy as the initial primary treatments, with or without cervical lymphadenectomy, postoperative radioiodine ablation, and thyroid-stimulating hormone suppression as clinically indicated in accordance with contemporary clinical guidelines. They were routinely followed up and monitored for disease progression with periodic clinic visits following standard clinical practice. Patients were included if they had a histopathologically confirmed diagnosis of PTC, with available thyroid tumor specimens for genetic testing and follow-up information. Patients meeting these criteria were included at the participating centers. Sample sizes varied across analyses depending on the availability of relevant variables. No other exclusion criteria were applied.

Procedures and Outcomes

This report followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cohort studies. With institutional review board (IRB) approval at all participating centers and informed patient consent or consent waiver per IRB approval, primary thyroid tumor tissues were obtained for genetic testing, and clinicopathologic data were collected in patient records using a centralized uniform-criteria protocol. The status of BRAF V600E and TERTp mutations (chr5:1,295,228C>T and 1,295,250C>T) was analyzed using polymerase chain reaction–based assays on genomic DNA from primary thyroid tumors as described previously.³⁰ Clinical treatment decisions were made independently of genetic results of the tumor. The pooled clinicopathologic and genetic data were used to analyze aggregately patient sex, age, and tumor genetics and their intertwining association with clinicopathologic outcomes. Patients were stratified according to their inherent characteristics, including sex, age, and BRAF V600E/TERTp mutation status. Group assignments were not randomized, consistent with the observational nature of this study. The primary end point of the study was disease-specific mortality defined as patient death attributable to incurable PTC. Follow-up time was calculated from the date of initial surgery to the last clinical encounter for survivors and those with non-PTC deaths or to PTC-related death.

Statistical Analyses

Continuous variables were presented as median with IQR and compared using the t test or Wilcoxon Mann-Whitney test as appropriate. Categorical variables were presented as numbers and percentages and compared using Pearson χ² test or Fisher exact test for sample sizes below 5. Mortality was reported as percentages and deaths per 1000 person-years. Survival analysis was performed using the Kaplan-Meier method, with between-group differences assessed by the log-rank test. Univariable and multivariable Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% CIs for PTC-specific mortality. In cases with complete separation (eg, zero events in one group), a Firth penalized likelihood Cox regression was applied to reduce bias. Interaction between male sex and age in affecting mortality was analyzed using the synergy index (SI),³⁶ with 95% CIs estimated via nonparametric bootstrap resampling (2000 replicates).³⁷ Univariable logistic regression was used to assess associations between sex and mutation rates across genotypes, with results reported as odds ratios (ORs) and 95% CIs. Correlation between age and mutation or mortality rates was also evaluated using Spearman rank correlation. A propensity score-matched sensitivity analysis was performed using nearest-neighbor matching at a 1:3 male-to-female ratio with a caliper of 0.2. All P values were 2-sided, with a value less than .05 considered significant. Analyses were conducted using R version 4.2.2 (R Project for Statistical Computing) and Graphpad version 6.01; RRID:SCR_002798 (GraphPad Software Inc) software. Data analyses were completed in December 2025.

Results

Association of Male Sex With Aggressive Clinicopathologic Features, Mutations, and Mortality in PTC

This study was performed on a pooled multicenter cohort of 4746 individuals with PTC, including 3612 women (76.1%) and 1134 men (23.9%), with a median (IQR) age of 48 (37-59) years at the time of diagnosis of PTC (eTable 1 in Supplement 1). Given the long-standing controversy on the prognostic value of patient sex in PTC, we used this large multicenter cohort first to examine the association between sex and clinicopathologic characteristics of PTC. Male patients, compared with female patients, showed a higher prevalence of multiple high-risk clinicopathologic characteristics, including older patient age (median [IQR] age, 50 [38-60] years vs 47 [36-58] years), larger tumor size (median [IQR], 1.5 [0.9-2.5] cm vs 1.3 [0.8-2.0] cm), extrathyroidal extension (24.0% [260 of 1085] vs 20.4% [684 of 3360]), lymph node metastasis (54.1% [598 of 1105] vs 38.3% [1329 of 3470]), distant metastasis (5.7% [64 of 1125] vs 3.5% [125 of 3553]), and advanced AJCC stages (III or IV) (8.2% [93 of 1132] vs 5.0% [182 of 3605]) (eTable 2 in Supplement 1). Male patients had higher rates of BRAF V600E (66.0% [746 of 1130] vs 62.3% [2239 of 3593]; P = .03), TERTp mutation (12.5% [140 of 1122] vs 7.8% [277 of 3568]; P < .001), and coexistence of both mutations (9.0% [101 of 1118] vs 5.0% [177 of 3549]; P < .001). Male patients also displayed a higher PTC-specific mortality compared with female patients (3.7% [42 of 1134] vs 1.7% [60 of 3612]; P < .001) (eTable 2 in Supplement 1). This corresponded to an HR of 2.38 (95% CI, 1.60-3.53; P < .001), which became nonsignificant after adjustment for patient age and BRAF and TERTp status. TERTp mutation was more prevalent in male than female patients (13.7% [101 of 739] vs 8.0% [177 of 2221]; P < .001) and mortality was higher in male than female patients (4.2% [31 of 746] vs 1.5% [34 of 2239]; P < .001) in the BRAF V600E group, but not in the wild-type BRAF group (eTable 3 in Supplement 1). These results suggested a patient age- and tumor genetic-dependent role of male sex in PTC-specific mortality.

Interactions Among Sex, Age, and BRAF V600E and TERTp Mutations in PTC

In exploring mortality risks associated with this combination of factors, we focused particularly on how they affected the occurrence of TERTp mutation given its well-known aggressive role in PTC. In wild-type BRAF patients there was a slight rise in TERTp mutation rates with increasing patient age, with no overall difference between male and female patients (Figure 1A). There was a sharp rise in TERTp mutation rates with increasing patient age in the BRAF V600E group, becoming prominent around age 45 years, particularly in male patients (Figure 1B). In this BRAF V600E group, male patients had nearly twice the risk of TERTp mutation occurrence as female patients (OR, 1.83; 95% CI, 1.41-2.38; P < .001). Spearman correlation analysis revealed a perfect positive correlation between patient age and TERTp mutation in male patients harboring BRAF V600E (r = 1.00; P < .001), but the correlation was not perfect in other groups (eTable 4 in Supplement 1).

Four-panel line graphs of T E R T p and dual mutation rates by age and sex. Four panels labeled A, B, C, and D arranged in a two by two grid. Each panel contains three line series with markers and a legend using gray triangles for All, orange circles for Female, and blue squares for Male. Panel A title Wild-type B R A F. Horizontal axis labeled Age, y with categories less than 25, 25 to 34, 35 to 44, 45 to 54, 55 to 64, 65 to 74, and greater than or equal to 75. Vertical axis labeled T E R T p mutation rates, percent, ranging from 0 to 50. Values remain mostly between about 4 and 12 percent through age 65 to 74, then rise at greater than or equal to 75 for All about 16 percent and Female about 18 percent, while Male remains about 12 percent; a small letter a appears near the Male point around age 35 to 44 at about 12 percent. Panel B title B R A F V 600 E with the same axes and ranges; rates increase with age, with Male higher than Female at older ages: at 45 to 54 Male about 10 percent, All about 5 percent, Female about 3 percent; at 55 to 64 Male about 19 percent, All about 14 percent, Female about 12 percent; at 65 to 74 Male about 29 percent, All about 23 percent, Female about 21 percent; at greater than or equal to 75 Male about 47 percent, All about 39 percent, Female about 36 percent. Letters b near age 45 to 54 and a near age 55 to 64 appear adjacent to the Male series. Panel C title Prevalence of dual B R A F V 600 E and T E R T p in all P T C. Horizontal axis Age, y with the same age categories; vertical axis Dual mutation rates, percent, ranging from 0 to 40. Values are near 0 to 2 percent below age 45, then increase: at 45 to 54 Male about 7 percent, All about 2 percent, Female about 2 percent; at 55 to 64 Male about 12 percent, All about 9 percent, Female about 8 percent; at 65 to 74 Male about 19 percent, All about 16 percent, Female about 15 percent; at greater than or equal to 75 Male about 31 percent, All about 27 percent, Female about 26 percent. Letters b near 45 to 54 and c near 55 to 64 appear near the Male series. Panel D title Cumulative prevalence of dual B R A F V 600 E and T E R T p in all P T C. Horizontal axis Age, y with categories less than 25, less than 35, less than 45, less than 55, less than 65, less than 75, and All. Vertical axis Accumulated dual mutation rates, percent, ranging from 0 to 10. Male increases from about 0 at less than 25 to about 1 point 6 at less than 35, about 2 point 8 at less than 45, about 4 point 5 at less than 55, about 6 point 6 at less than 65, about 8 point 0 at less than 75, and about 9 point 0 at All; All increases to about 6 point 0 at All; Female increases to about 5 point 0 at All. Letters a near less than 35 and multiple b labels appear near later Male points. — ^aP for sex difference < .05.

^bP for sex difference < .001.

^cP for sex difference < .01.

A significant age-dependent increase in rates of dual BRAF V600E and TERTp mutation also existed, with a perfect correlation on Spearman correlation analysis in male patients (r = 1.00; P < .001), and a correlation that was not perfect in female patients (r = 0.96; P = .003). An association was also observed between increasing age and the occurrence of dual mutations when the data were examined using age-stratified prevalence curves (Figure 1C), with higher effect sizes in male than female patients (OR, 1.89; 95% CI, 1.46-2.43; P < .001). Cumulative prevalence of dual BRAF V600E and TERTp mutations with increasing age similarly rose more robustly in male than female patients (Figure 1D). These also began to be prominent around patient age 45 years.

Genetic Duet of BRAF V600E and TERTp Mutation as the Basis for Association of Age With Male Sex on PTC-Specific Mortality

Like the BRAF V600E–dependent effect of male sex on mortality, higher mortality in male than female patients occurred with TERTp mutation, but not wild-type TERTp (eTable 3 in Supplement 1; Table 1). To dissect the individual roles of BRAF V600E and TERTp mutations in this sex effect on mortality, we divided the cohort into 4 genotype groups and found no sex difference in mortality among patients with dual wild-type BRAF and TERTp, BRAF V600E only, or TERTp mutation only. Only in the dual mutation group was there a higher mortality in male than female patients, 22.8% (23 of 101) vs 11.9% (21 of 177) (P = .02), with the corresponding HR of 2.63 (95% CI, 1.74-9.00; P = .01) after adjustment for histopathologic characteristics (Table 1).

Table 1. Papillary Thyroid Cancer (PTC)-Specific Mortality and Hazard Ratios (HRs) for Male vs Female Sex by BRAF and TERT Promoter (TERTp) Status.

BRAF V600E	TERTp mutation	Mortality rate, No./Total No. (%)			Deaths per 1000 person-years (95% CI)		HR (95% CI)	P value	Adjusted HR (95% CI)^a	P value
BRAF V600E	TERTp mutation	Female patients	Male patients	P value	Female patients	Male patients	HR (95% CI)	P value	Adjusted HR (95% CI)^a	P value
*Grouped by BRAF* V600E status^b**
Negative	NA	26/1354 (1.9)	11/384 (2.9)	.26	2.54 (1.66-3.73)	3.85 (1.92-6.89)	1.49 (0.73-3.01)	.27	0.86 (0.35-2.10)	.74
Positive	NA	34/2239 (1.5)	31/746 (4.2)	<.001	2.96 (2.04-4.13)	8.72 (5.93-12.39)	3.19 (1.94-5.25)	<.001	2.75 (1.51-5.02)	<.001
*Grouped by TERTp status^b*
NA	Negative	29/3291 (0.9)	12/982 (1.2)	.44	1.49 (1.00-2.14)	2.27 (1.17-3.96)	1.56 (0.80-3.06)	.20	0.81 (0.34-1.97)	.65
NA	Positive	31/277 (11.2)	28/140 (20)	<.001	15.26 (10.37-21.67)	26.82 (17.82-38.77)	1.75 (1.05-2.92)	.03	2.23 (1.19-4.18)	.01
*Grouped by BRAF* V600E and TERTp status^b**
Negative	Negative	16/1229 (1.3)	5/340 (1.5)	.81	1.75 (1.00-2.85)	2.04 (0.66-4.76)	1.14 (0.42-3.11)	.80	0.63 (0.17-2.39)	.50
Positive	Negative	13/2044 (0.6)	7/638 (1.1)	.24	1.27 (0.68-2.18)	2.48 (1.00-5.11)	2.62 (0.995-6.90)	.051	1.37 (0.40-4.73)	.62
Negative	Positive	10/99 (10.1)	5/39 (12.8)	.64	11.37 (5.45-20.91)	13.68 (4.44-31.91)	1.21 (0.41-3.54)	.72	1.14 (0.33-3.95)	.83
Positive	Positive	21/177 (11.9)	23/101 (22.8)	.02	18.34 (11.36-28.04)	33.91 (21.50-50.89)	1.65 (0.91-2.99)	.10	2.63 (1.74-9.00)	.01

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Abbreviation: NA, not applicable.

^{^a}

HR was adjusted for clinicopathologic characteristics, including vascular invasion, extrathyroidal extension, lymph node metastasis, distant metastasis, and radioiodine-131 treatment.

^{^b}

Stratified analyses excluded cases with missing data for the respective mutation status: 23 for BRAF V600E, 56 for TERTp groups.

We next introduced patient age into the association among sex, tumor genetics, and PTC mortality. In patients with dual wild-type BRAF and TERTp, mortality remained low with increasing patient age, with no sex difference (Figure 2A). The accumulated mortality rates also remained low with increasing age, with no sex difference (Figure 2B). In contrast, patients with dual mutations exhibited robustly higher mortality with increasing patient age, beginning at around 35 to 45 years (Figure 2C). Of note, male patients between ages 45 and 54 years experienced the highest mortality, which was much younger than both male and female patients with dual wild-type BRAF and TERTp, who had only a modest mortality peak at age 65 to 75 years (Figure 2A). Also beginning with the age 35 to 45 year cohort, patients with dual mutations showed rising cumulative mortality with increasing age, particularly prominent in male patients (Figure 2D).

Four-panel line graphs of mortality rate by age, sex, and mutation status. Four panels labeled A through D arranged in a two by two grid. A legend in panel A maps gray triangles to All, orange circles to Female, and blue squares to Male. Panel A title: Mortality for wild-type B R A F and T E R T p. Horizontal axis labeled Age, y with categories less than 25, 25 to 34, 35 to 44, 45 to 54, 55 to 64, 65 to 74, and greater than or equal to 75. Vertical axis labeled Mortality rate, percent, ranging from 0 to 40. Three lines remain near zero through age 45 to 54, rise to about 2 to 3 percent at 55 to 64, peak around 5 to 7 percent at 65 to 74, then decline at greater than or equal to 75 to about 2 to 4 percent for All and Female and about 0 percent for Male. Panel B title: Accumulated mortality for wild-type B R A F and T E R T p. Horizontal axis labeled Age, y with categories less than 25, less than 35, less than 45, less than 55, less than 65, less than 75, and All. Vertical axis labeled Accumulated mortality rate, percent, from 0 to 40. All three series increase gradually from near 0 to about 1 percent by less than 75 and around 1 percent at All. Panel C title: Mortality for B R A F V 600 E and T E R T p mutations. Axes match panel A. Values are 0 at less than 25 and 25 to 34. At 35 to 44, Male about 22 percent, Female about 8 percent, All about 14 percent. At 45 to 54, Male about 31 percent, Female about 6 percent, All about 19 percent. At 55 to 64, Male about 19 percent, Female about 9 percent, All about 13 percent. At 65 to 74, Male about 25 percent, Female about 10 percent, All about 15 percent. At greater than or equal to 75, Male about 20 percent, Female about 26 percent, All about 24 percent. Panel D title: Accumulated mortality for B R A F V 600 E and T E R T p mutations. Axes match panel B with vertical range 0 to 40. Male rises to about 17 percent at less than 45 and about 26 percent at less than 55, then stays near 22 to 24 percent through less than 75 and All; small letters a appear near the Male line at less than 55, less than 65, and All, and letter b near less than 75. All rises to about 10 percent at less than 45 and about 15 to 16 percent by less than 55, remaining near 14 to 16 percent through All. Female rises to about 6 percent at less than 45, about 6 percent at less than 55, about 8 percent at less than 65, about 9 percent at less than 75, and about 12 percent at All. — ^aP for sex difference < .05.

^bP for sex difference < .01.

Cox regression analysis showed no association between male sex and mortality in the groups other than male patients 45 years and older with dual mutations when the cohort was divided according to age and genotypes (Table 2). In this latter patient population, male sex was associated with increased mortality in both univariable and multivariable analyses, particularly prominent in the latter (unadjusted HR, 1.85; 95% CI, 1.00-3.42; P = .049; adjusted HR, 3.07; 95% CI, 1.35-6.97; P = .007) (Table 2). This special population of male patients ages 45 years and older with dual mutations had the highest mortality (37.07 per 1000 person-years), which was 86-fold higher than that of female patients younger than 45 years with dual wild-type genes (0.43 per 1000 person-years), yielding the most significant HR among all groups (Table 2; eTable 5 in Supplement 1). A synergistic interaction between male sex and age was observed among patients ages 45 years and older with dual mutations in affecting mortality risk (SI, 1.81; 95% CI, 1.02-3.16) (eTable 6 in Supplement 1). Among other groups, male patients younger than 45 years old with dual mutations, female patients ages 45 years and older with dual mutations, and both male and female patients at least 45 years old with TERTp mutation alone had a moderate mortality risk (eTable 5 in Supplement 1).

Table 2. Papillary Thyroid Cancer (PTC)-Specific Mortality and Hazard Ratios (HRs) for Male vs Female Sex by BRAF and TERT Promoter (TERTp) Status and Age.

Characteristics	Mortality rate, No./Total No. (%)		P value	Deaths per 1000 person-years (95% CI)		HR (95% CI)	P value	Adjusted HR (95% CI)^a	P value
Characteristics	Female patients	Male patients	P value	Female patients	Male patients	HR (95% CI)	P value	Adjusted HR (95% CI)^a	P value
Age <45 y
BRAF-negative/TERTp-negative	2/613 (0.3)	1/138 (0.7)	.46	0.43 (0.05-1.55)	1.03 (0.03-5.74)	2.89 (0.26-21.74)^b	.34	2.92 (0.27-22.04)^b	.33
BRAF-positive/TERTp-negative	1/847 (0.1)	1/268 (0.4)	.42	0.22 (0.01-1.20)	0.80 (0.02-4.47)	9.38 (0.50-1369.12)^b^,^c	.13	9.45 (0.50-1379.02)^b^,^c	.13
BRAF-negative/TERTp-positive	0/36	0/14	NA^d	0 (0-4.64)	0 (0-25.19)	NA^d	NA^d	NA^d	NA^d
BRAF-positive/TERTp-positive	1/17 (5.9)	2/12 (16.7)	.55	7.43 (0.19-41.42)	17.90 (2.17-64.67)	0.22 (0.002-4.17)^b	.32	0.20 (0.001-3.87)^b	.29
Age ≥45 y
BRAF-negative/TERTp-negative	14/613 (2.3)	4/201 (2.0)	>.99	3.16 (1.73-5.31)	2.72 (0.74-6.96)	0.86 (0.28-2.60)	.78	0.62 (0.15-2.53)	.51
BRAF-positive/TERTp-negative	12/1194 (1.0)	6/370 (1.6)	.40	2.17 (1.12-3.79)	3.81 (1.40-8.29)	2.12 (0.77-5.85)	.15	0.91 (0.26-3.15)	.88
BRAF-negative/TERTp-positive	10/63 (15.9)	5/24 (20.8)	.75	22.11 (10.60-40.66)	23.74 (7.71-55.41)	1.10 (0.37-3.23)	.86	4.67 (0.64-34.14)	.13
BRAF-positive/TERTp-positive	20/160 (12.5)	21/89 (23.6)	.03	19.80 (12.09-30.57)	37.07 (22.95-56.67)	1.85 (1.00-3.42)	.049	3.07 (1.35-6.97)	.007

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Abbreviation: NA, not applicable.

^{^a}

For the subgroup aged 45 years and older, HRs were adjusted for all 5 covariates: vascular invasion, extrathyroidal extension, lymph node metastasis, distant metastasis, and radioiodine-131 treatment; for the younger than 45 years subgroup, the HRs were adjusted for distant metastasis only, as adjustment for all other specified covariates (vascular invasion, extrathyroidal extension, lymph node metastasis, and radioiodine-131 treatment) would have resulted in zero events in the analysis cohort, rendering multivariable Cox regression nonestimable.

^{^b}

Given the small number of events (<5), the Firth penalized maximum likelihood method was implemented in Cox regression analyses to mitigate finite-sample bias.

^{^c}

Wide CI was due to low event numbers (1 per group).

^{^d}

NA values indicate statistical nonestimability for Cox regression due to the absence of mortality events in both groups (BRAF-negative/TERTp-positive, age <45 years).

Combination of Patient Sex, Age, and Genetic Duet and Association With Patient Survival in PTC

We next examined how the interactions of sex, age, and genetics were associated with patient survival in PTC. This large cohort analysis confirmed the previous finding of BRAF V600E-dependent separation of the survival curves between male and female patients⁸ (eFigure 1 in Supplement 1). Similarly, when dividing the cohort into 2 TERTp groups, the Kaplan-Meier survival curves for male and female patients differed in the TERTp-mutation group, but not the wild-type TERTp group (eFigure 2 in Supplement 1). When dividing the cohort into 4 genotypes, there were no sex differences in survival in the dual wild-type gene group or the wild-type BRAF and TERTp mutation group (eFigure 3 in Supplement 1). In the BRAF V600E and wild-type TERTp group, male patients had a slightly lesser survival than female patients. In the dual-mutation group, the survival curve showed a sharper, albeit marginally nonsignificant, decline in male patients compared with female patients.

We took a further look at this issue by separating the patients according to the age point of 45 years. Consistent with the lack of sex difference in mortality in patients younger than 45 years in various genotypes, no sex difference was observed in survival in any of the 4 genotype groups in this youngest group (eFigure 4 in Supplement 1). In patients ages 45 years and older, there was no sex difference in survival with dual wild-type genes, BRAF V600E and wild-type TERTp, or wild-type BRAF and TERTp mutation (Figure 3). In contrast, the survival curve for patients ages 45 years and older with dual BRAF V600E and TERTp mutations showed a sharper decline in male than female patients (log-rank P = .046) (Figure 3D). Thus, this sex difference in survival was observed exclusively in patients ages 45 years and older with dual mutations, which was consistent with the similar effects of male sex on mortality (Figure 2; Table 2).

Four Kaplan-Meier panels of survival probability versus time by sex and genotype. Four-panel Kaplan-Meier figure arranged two by two, panels A through D, each with vertical axis labeled Survival probability, percent, from 0 to 100, and horizontal axis labeled Time, y, from 0 to 25. Two step curves per panel: blue labeled Male and orange labeled Female, with multiple plus-sign censoring marks along each curve. Panel A, title Wild-type B R A F and T E R T p: both curves remain near 100 percent with small step decreases; Male label near the upper portion, Female label slightly lower; log-rank P equals .78 printed at lower right. Below the x axis, No. at risk table lists Female 613, 371, 176, 41, 12, 2 and Male 201, 123, 58, 13, 5, 2 at successive time points aligned with the axis ticks. Panel B, title B R A F V 600 E mutation, wild-type T E R T p: blue Male curve declines modestly to the high 80s by about 15 to 20 years; orange Female curve stays near the mid to high 90s until a late sharp drop near about 23 to 25 years, reaching near 0 at 25 years; log-rank P equals .14. No. at risk: Female 1194, 388, 159, 20, 4, 1 and Male 370, 106, 44, 7, 1, 0. Panel C, title Wild-type B R A F, T E R T p mutation: both curves drop from near 100 to about 80 to 85 percent by roughly 5 to 10 years; later, the orange Female curve steps down to about the mid 60s around 14 to 15 years, while the blue Male curve remains around the mid 70s to high 70s through about 20 years; log-rank P equals .86. No. at risk: Female 63, 39, 16, 4, 0, 0 and Male 24, 18, 8, 2, 1, 0. Panel D, title Dual B R A F V 600 E and T E R T p mutations: both curves decline steadily; blue Male falls more steeply after about 8 to 12 years, reaching roughly 20 percent by about 18 to 20 years; orange Female remains higher, around 70 percent near 15 years and about 30 percent near 18 years; log-rank P equals .05. No. at risk: Female 160, 90, 31, 7, 0, 0 and Male 89, 50, 19, 4, 1, 0.

We examined the 278 cases of dual-mutation patients (101 male and 177 female) and found no significant difference between male and female patients in clinicopathologic characteristics that may be associated with main disease progression at the initial surgery, including AJCC 8th stage distribution (eg, stage IV, 14.9% vs 14.7%; P = .73), distant metastasis (19.2% vs 14.4%; P = .30), extrathyroidal invasion (64.9% vs 64.2%; P = .90), vascular invasion (34.5% vs 26.6%; P = .21), radioiodine treatments (87.4% vs 85.7%; P = .71), and follow-up duration (median, 70.0 [37.0-116.5] vs 72.0 [34.1-112.0] months; P = .80). The mortality rates in male vs female patients in such settings were 22.8% vs 11.9% (P = .02) (Table 1; Figure 2C and 2D).

We also used the propensity score-matched sensitivity approach to identify a pair of male and female patient groups, consisting of 906 and 2214 patients, respectively, matching their clinicopathologic characteristics of patient age, tumor size, AJCC 8th stage, extrathyroidal extension, vascular invasion, lymph node metastasis, distant metastasis, and data source at the initial surgery. With this match of similar initial disease severity in the 2 groups, the dual BRAF V600E and TERTp mutation rate and mortality rate remained significantly higher in the male group than the female group, being 8.3% vs 4.4% (OR, 1.95; 95% CI, 1.42-2.66; P < .001) and 2.9% vs 1.6% (HR, 2.05; 95% CI, 1.24-3.41; P = .005), respectively.

Discussion

Previous studies on the role of patient sex in mortality risk in thyroid cancer have yielded conflicting results, limiting its prognostic use in clinical practice.^{6,7,8,9,10,11,12,13,14,15,16,17} Our previous studies have demonstrated an association between male sex and mortality in PTC in a BRAF V600E mutation-dependent manner.⁸ Likewise, the prognostic value of patient age in PTC is also contingent upon the BRAF V600E status,³¹ although patient age is genetically nondiscriminatively integrated into the mortality risk stratification in the AJCC system for thyroid cancer.^4,5 Here we demonstrate that the 3 basic biological factors of patient sex, age, and tumor genetics, particularly with a coexisting BRAF V600E and TERTp mutation, uniquely intertwine in drastically shaping the mortality risk of PTC.

Specifically, male sex and older patient age cooperatively exert adverse effects on PTC-specific mortality, driven by their interdependent ability to favor the tumor’s acquisition of BRAF V600E and TERTp mutations and their concurrence. The effect of patient age in this interplay begins to be prominent around 45 years, which is precisely the age when the occurrence of dual BRAF V600E and TERTp mutations begins to be robust, particularly in male patients, with a sharp early age shift compared with female patients. This identifies male patients aged 45 years and older with dual mutations having the worst prognosis. Interestingly, this age point of 45 years coincides with the cutoff age of 45 years previously used to separate mortality risk of thyroid cancer in the AJCC system.⁴ Thus, early thyroid cancer experts have already wisely observed that clinically the emergence of thyroid cancer aggressiveness begins at the patient age of 45 years. However, they failed to recognize the contribution of patient sex and tumor genetics to this long-standing clinical observation.

The present study has clinical implications beyond amending the conventional wisdom. For example, a male PTC patient who is 45 years or older should be prioritized for genetic testing of BRAF and TERTp and be managed with correspondingly vigorous measures if dual mutations are identified. This also raises a question on whether the sex-indiscriminate use of the cut-off age of 55 years in the current AJCC 8 is an optimal choice or whether the AJCC system should be designed with male and female sexes separated, with a cut-off age of 45 years reserved for male patients.

The intertwining association of patient sex, age, and tumor genetics with clinical outcomes of PTC is complex. The rising rates of the BRAF V600E and TERTp mutations and, especially, their concurrence with increasing age play a fundamental role in the association of male sex with high mortality. One phenomenon of particular note was that even in male patients with dual BRAF V600E and TERTp mutations, mortality only began to rise prominently around age of 45 years. This suggests that it is not just genetics that adversely affects the prognostic outcomes of PTC, but it is the interdependent cooperation among male sex, older patient age, and tumor genetics. The role of male sex in this interplay in patients ages 45 years and older was robust as suggested by the multivariable adjustment analysis showing that in patients with dual BRAF V600E/TERTp mutations, the association of male sex with mortality was independent of clinicopathologic characteristics. The biological mechanism underlying the role of male sex and age in tumor aggressiveness of PTC may speculatively involve the actions of male hormones or their receptor signaling and their interactions with aging-related biological processes in affecting the occurrence or action of dual mutations, oncogenesis, and tumor aggressiveness. It is likely that the previous inconsistent observations on the prognostic value of sex arose from the heterogeneity in patient age and thyroid tumor genetics in different studies.

It is worth noting that the initial clinicopathologic characteristics between dual-mutation male and female patients were of no significant difference, but male patients had a higher mortality; when the initial clinicopathologic characteristics were matched between male and female patients, the dual mutation and mortality rates were also still higher in the former. These results all support an intrinsic effect of male sex on the occurrence of dual mutations and mortality in PTC, but not delayed disease diagnosis that, if occurring, could result in more severe disease in male patients.

Limitations

This study had several limitations. There could be an apparent heterogeneity concern in this study given the large number of medical centers and countries with different ethnic backgrounds. Nevertheless, previous vigorous quality assessment of this specific patient cohort has demonstrated its solid quality in various aspects.³⁰ For example, there was no heterogeneity in the associations of genetics with patient mortality and no significant variation in the association between mutations and patient mortality among the medical centers. The ethnic, geographical, and genetic diversity of the study population in fact represents a strength of the study as it supports the global generalizability of the findings.³⁰ Other less common aggressive genetic alterations, such as TP53 mutations, were not examined.

Conclusions

In this large multicenter cohort study of patients with PTC, we demonstrated male sex as a prominent risk for PTC-specific mortality, which was patient age- and tumor genetic-dependent and arose from their intertwining factors. Our study especially identified male patients with PTC who were age 45 years or older with dual BRAF V600E and TERTp mutations as a special population with the highest mortality risk. This study reconciled previous inconsistent findings on the prognostic value of patient sex in thyroid cancer and supported its formal integration as a cardinal component, in conjunction with patient age and tumor genetics, into the risk stratification systems for PTC. These new findings could accelerate translating the currently developing concept of genetic-based risk stratification of thyroid cancer into specific clinical practicality.

Supplement 1.

eAppendix. Statement on patient and public involvement

eTable 1. Centers, countries, and patients participating in the study

eTable 2. Effects of patient sex on clinicopathologic characteristics of PTC

eTable 3. Effects of patient sex on clinicopathologic characteristics of PTC by BRAF status

eTable 4. Spearman analysis of the correlation between age and TERTp mutation rates by the BRAF status

eTable 5. Mortality hazard ratios for BRAF/TERT-age-sex stratified subgroups vs. overall cohort

eTable 6. Synergistic interaction of male sex and age ≥45 years in mortality by 4 genotypes of BRAF and TERTp

eFigure 1. PTC-specific Kaplan-Meier survival curves by sex and BRAF mutation status

eFigure 2. PTC-specific Kaplan-Meier survival curves by sex and TERTp mutation status

eFigure 3. PTC-specific Kaplan-Meier survival curves by sex and 4 genotypes of BRAF and TERTp

eFigure 4. PTC-specific Kaplan-Meier survival curves by sex and 4 genotypes of BRAF and TERTp in patients <45 years of age

jamanetwopen-e2635582-s001.pdf^{(1.3MB, pdf)}

Supplement 2.

Data sharing statement

jamanetwopen-e2635582-s002.pdf^{(15.7KB, pdf)}

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