Clinical Characteristics and Prognostic Markers of Aggressive Subtypes of Thyroid Cancer: A Retrospective Chart Review Study

Clinical Characteristics and Prognostic Markers of Aggressive Subtypes of Thyroid Cancer: A Retrospective Chart Review Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Clinical Characteristics and Prognostic Markers of Aggressive Subtypes of Thyroid Cancer: A Retrospective Chart Review Study Suhaib Adel Radi, Mazin Al-Maghrabi, Saleh Binmahfooz, Miguel Franco, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4087685/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Importance : The prevalence of thyroid cancer has increased significantly. Aggressive subtypes of papillary thyroid cancer (AG-PTC) and poorly differentiated thyroid cancer (PDTC) are malignancies that lie between well-differentiated and undifferentiated cancers. The management of well-differentiated cancers has been established in the literature; however, that of AG-PTC and PDTC needs to be clarified. Objective : To describe the clinicopathological characteristics and genomic landscape of AG-PTC and PDTC and to assess their prognostic value. We primarily aimed to determine the association between persistent or recurrent thyroid cancer and clinicopathological prognostic markers Design : A retrospective chart review of patients with thyroid cancer over the last 10 years Setting : Single center Participants : Patients with AG-PTC or high-grade follicular cell-derived malignancies (HGFM) were included in the analysis. HGFM comprised of patients with PDTC & differentiated high-grade thyroid carcinoma. The clinical presentation, pathological characteristics, molecular markers, specific treatments, and clinical outcomes were compared between the groups. Exposure(s): Main Outcome(s) and Measure(s): Results : Of the 3,244 thyroid cancer charts reviewed, 136 met the criteria for AG-PTC and HGFM. The mean age at diagnosis was 49 years, with a predominance of women. The median follow-up duration was 3 years. The rate of persistent or recurrent disease was 40.3% in the AG-PTC group and 29.3% in the HGFM group, 4.5% died in the AG-PTC group, and 1.8% died in the HGFM group. The presence of vascular, lymphovascular invasion and extrathyroidal extension were associated with a higher incidence of persistent or recurrent disease (Hazard ratio: 2.5, 3.8, and 4.2, respectively; p < 0.05). When the Ki-67 index was divided into five groups, the recurrence rate was higher in the ≥ 20% Ki-67 group compared to lower Ki67 (P-value of 0.017). Although there was a numerical increase in the rate of persistent/recurrent disease among BRAF-mutated patients, it didn’t reach statistical significance. No difference was observed in recurrence based on percentage of aggressive/poorly differentiated tumor involvement. Conclusions and Relevance : Possible prognostic markers for predicting recurrent and persistent thyroid cancers and guiding therapy for AG-PTC and HGFM include vascular/lymphovascular invasion, extrathyroidal extension, and the proliferative index Ki-67. Thyroid cancer Ki-67 BRAF genetic mutation aggressive variant of papillary thyroid cancer poorly differentiated thyroid cancer prognostic marker Figures Figure 1 Figure 2 Key Points Question: What characteristics and factors can affect the prognosis of patients with high-grade follicular cell-derived malignancies (aggressive papillary thyroid cancer [AG-PTC] and high-grade follicular cell-derived malignancies [HGFM]). Findings: Of 75 patients followed up for >1 year, 42.7% had either a persistent or recurrent disease (52.6% in the AG-PTC group and 32.4% in the HGFM group), 4.5% died of AG-PTC, and 1.8% died in the HGFM group. The presence of vascular or lymphovascular invasion and extrathyroidal extension was associated with a higher incidence of persistent or recurrent disease (Hazard ratio: 2.5, 3.8, and 4.2, respectively; p <0.05) Meaning: Rates of persistent and recurrent disease are high in patients with HGFM and AG-PTC. Certain pathological features can predict worse prognosis in these patients. Close follow up and aggressive management is warranted in this group. Background Thyroid cancer is the most prevalent endocrine tumor, and its prevalence has increased significantly over the last 20 years owing primarily to the increased detection of thyroid microcarcinomas. 1 It’s estimated that thyroid cancer constitutes around 2% of all malignancies worldwide. 1 Follicular cell-derived thyroid cancer includes different histologic types: papillary thyroid cancer (PTC), follicular thyroid cancer (FTC), poorly differentiated thyroid cancer (PDTC), and anaplastic thyroid cancer (ATC). PTC and FTC are usually well differentiated and have good prognoses. In contrast, PDTC and ATC are rarer, dedifferentiated, and have worse outcomes. PTC accounts for approximately 80% of thyroid cancer cases. 2 , 3 The aggressive subtypes of PTC (AG-PTC) and PDTC are malignancies that lie between well-differentiated and undifferentiated anaplastic cancers. The features and management of well-differentiated cancers have been established in the literature; however, AG-PTC and PDTC need to be clarified further because they have characteristics different from those of their more benign counterparts. 4 The prevalence of AG-PTC and PDTC is relatively low; however, the incidence of persistent or recurrent disease at 1 year after primary therapy is high compared with that of the more well-differentiated tumors. 5 Furthermore, AG-PTC subtypes possess distinct clinical, pathological, and molecular features that distinguish it from well-differentiated PTC with a higher rate of metastasis and lower avidity to radioactive iodine (RAI). 6 The 5-year survival rate for thyroid cancer varies according to histotype. A recent epidemiological study in Denmark based on a national cancer registry reported that the 5-year survival rate was 91.1%, 79.9%, and 63.6% for PTC, FTC, and PDTC, respectively. 7 PTC has a good prognosis; however, there are aggressive subtypes with clinicopathological and genomic backgrounds different from those of the classical PTC. 8 The development of molecular techniques has led us to identify clinically significant biomarkers useful in the diagnosis and prognosis of PTC. 9 Knowing the features and markers that predict a worse prognosis can help treat and monitor patients after primary therapy. The BRAF -encoded BRAF protein sends signals to direct cell proliferation. 10 BRAF mutations are associated with more invasive disease and a higher risk of recurrence in patients with thyroid cancer compared to those without BRAF mutations. 11 However, whether BRAF mutations are associated with PDTC remains unclear. 12 The Ki-67 index is a widely used biomarker for assessing the cell proliferation rate of certain cancers, such as breast cancer and neuroendocrine neoplasia. 13 , 14 Ki-67 expression and its role in thyroid cancer have been debated; however, it has potential implications for differentiating between benign and malignant tumors. 15 Ito et al. found that the proliferative index Ki-67 is an independent prognostic factor for disease-free survival in patients with PTC. 16 Furthermore, a high Ki-67 index in patients with PTC is associated with higher recurrence rates and poor survival. 16 , 17 In the present study, we aimed to analyze and characterize the clinical, pathological, and genotypic aspects of AG-PTC and PDTC and their prognostic significance in this patient cohort. We primarily aimed to determine the association of the Ki-67 index and BRAF mutations with recurrent or persistent thyroid cancer, with a secondary aim to determine the association between persistent or recurrent thyroid cancer and other clinicopathological prognostic markers. This may contribute to directing surveillance and individualizing the therapeutic strategies in such patients. Methodology Study design, setting, and population After obtaining ethics approval from the Institutional Research Board (IRB), project number 2020 − 1902, this retrospective chart review of adult patients of both sexes, aged ≥ 18 years, with thyroid cancer over the last 10 years, between 2010 and 2019 at the Jewish General Hospital in Montreal, Canada, affiliated with McGill University, was conducted. A total of 3,324 medical records were reviewed, and patients with AG-PTC or PDTC were included. Patients with other types of thyroid cancer were excluded, leaving 136 patients who met the diagnostic criteria. Of the total cohort, 124 patients were followed up for ≥ 1 year. Definitions of AG-PTC and PDTC According to the World Health Organization (WHO) criteria, AG-PTC is defined as the presence of one of the following histologic patterns: tall cell, clear cell, diffuse sclerosing, columnar cell, or hobnail. The presence of one or more of these patterns at ≥ 30% is considered a subtype; otherwise, it would be called “features.” The recently released 2022 WHO report distinguishes the two types of high-grade follicular cell-derived malignancies (HGFM): PDTC and differentiated high-grade thyroid carcinoma (DHGTC). PDTC was defined using the Turin criteria as the presence of a solid/trabecular pattern, an insular growth pattern, and one of three high-grade features—mitosis (> 3/10 high-power field), necrosis, or convoluted nuclei. DHGTC was defined based on high mitotic activity and tumor necrosis, regardless of histological differentiation. Both types were grouped together in the present study under HGFM, considering similar biologic behaviours. 18 Outcomes Persistent disease was defined as an incomplete response, either structural or biochemical. 19 Recurrence was defined as evidence of disease confirmed using either structural or functional imaging or biopsy after 6 months of being disease-free. Disease-free survival was defined as the duration during which a patient remains free of any signs or symptoms of a specific disease after completing a treatment, indicating the absence of disease recurrence or progression during that period. Ki-67 index and BRAF mutations, determined using immunohistochemistry, were included in only some of the medical records reviewed because they were routinely analyzed more frequently in all aggressive types recently and much less frequently in older specimens. Statistical analysis The characteristics of patients and tumors were compared between those with and without evidence of persistent disease, recurrence, or death using the Pearson x 2 test. Univariate and multivariate analyses were performed using the log-rank test and the Cox proportional hazards method, respectively. Statistical significance was set at P < 0.05. Statistical analysis was performed using SPSS version 26.0 (IBM). Results In total, out of the 3,324 patients screened, 136 patients were included in this study: 74 in the AG-PTC group and 62 in the HGFM group. This constitutes a prevalence of AG-PTC of 2.2% and HGFM of 1.9%. Furthermore, most patients were females in the AG-PTC (70.30% [n = 52/74]) and HGFM (59.7% [n = 37/62]) groups. The mean age was 44 (+/- 18.7) and 54 (+/- 14.5) years in the AG-PTC and HGFM groups, respectively (P = 0.0005; Table 1 ). Table 1 Baseline Characteristics AG-PTC (n = 74) HGFM (n = 62) P-value Mean age in years 44 54 0.0005 Female 70.3% 59.7% 0.03 Mean f/u in years 4.52 +/- 5.04 4.89 +/- 5.12 0.07 Hobnail features 12 5 NA Diffuse sclerosing features 26 1 Columnar features 3 3 Tall cell features 41 4 Clear cell features 2 1 Insular features 0 7 Mitosis 0 5 necrosis 0 10 Solid features 0 38 Trabecular features 0 27 Convoluted nuclei features 0 1 >= 30% involvement 44.6% 62.9% 0.06 Mean tumor size in cm 2.71 3.58 0.0133 T3/T4 stage 54.8% 37.1% 0.03 Extrathyroidal extension 51.4% 21% 0.0039 Vascular invasion 23% 21% 0.591 Lymphovascular invasion 71.6% 40.3% 0.000087 Positive margins 40.5% 29% 0.514 pN1 stage 75.3% 29% < 0.005 pM1 stage 8.3% 12.9% 0.231 Biochemical response • Complete • Partial • Indeterminate Out of 65 49.2% 32.3% 18.5% Out of 54 72% 22.2% 5.6% 0.022 Structural response • Complete • Partial • Indeterminate Out of 66 60.6% 19.7% 19.7% Out of 53 66% 17% 17% 0.83 Mean Ki67 5.42 12.23 0.0033 Ki67 groups • = 10 Out of 24 75% 25% Out of 35 45.7% 54.3% 0.024 BRAF positive 84.6% (out of 26) 16.7% (out of 24) < 0.005 Abbreviations: AG-PTC: aggressive-papillary thyroid cancer; HGFM: high-grade follicular cell-derived malignancies The most prominent subtype in the AG-PTC group was tall-cell (55.4%, n = 41/74), followed by diffuse sclerosing (35.1%, n = 26/74) and hobnail (16.2%, n = 12/74). The most common growth pattern in the HGFM group was solid (61.3%, n = 38/62), followed by trabecular (43.6%, n = 27/62). The mean tumor size was 2.71 cm (+/- 1.60) and 3.58 cm (+/- 2.25) in the AG-PTC and HGFM groups, respectively (p = 0.0133). Furthermore, more patients had advanced disease (stages T3 and T4) in the AG-PTC group than in the HGFM group (54.8% vs. 37.1%, p = 0.03). Extrathyroidal extension occurred in more patients in the AG-PTC group than in the HGFM group (51.4% vs. 21%, p = 0.0039). Similarly, more patients had lymphovascular invasion (71.6%) in the AG-PTC group than in the HGFM group (40.3%) (p < 0.005). Six patients had metastasis on presentation in the AG-PTC group, whereas eight had metastasis in the HGFM group. Of the eight patients with pM1 on presentation (four biopsy-proven, three to the lungs, and five to the bones) in the HGFM group, five were RAI-avid and two were flurodeoxyglucose (FDG)-avid. Of the six patients with pM1 on presentation (four biopsy-proven, three to the lungs, and three to the bones and lungs) in the AG-PTC group, five were RAI-avid and one was FDG-avid. Furthermore, 89.2% of patients received RAI treatment in the AG-PTC group, whereas 74.19% received it in the HGFM group. Two patients underwent radiotherapy in the AG-PTC group, whereas one underwent radiotherapy in the HGFM group. Central neck dissection was performed in 61.81% and 68% of patients in the AG-PTC and HGFM groups, respectively. Furthermore, 32.43% and 11.29% of patients underwent central and lateral neck dissections in the AG-PTC and HGFM groups, respectively. Lobectomy only was performed in 4% and 16.13% of patients in the AG-PTC and HGFM groups, respectively. The reason for performing lobectomy in most cases was the aggressive nature of the disease, which made total thyroidectomy unfeasible. Notably, more patients achieved complete biochemical response in the HGFM group than in the AG-PTC group (72% [n = 39/54] vs. 49.2% [n = 32/65]), p = 0.022). The complete structural responses of both groups were similar (AG-PTC: 60.6% [n = 40/66], HGFM: 66% [n = 35/53]). In the AG-PTC group, 19.4% of patients had persistent disease, whereas 29.9% had recurrent disease. In the HGFM group, 15.5% of patients had persistent disease, whereas 22.4% had recurrent disease. The combined persistent or recurrent disease rate was numerically higher in the AG-PTC group than in the HGFM group (40.3% vs. 29.3%, p = 0.137). Of 13 patients with recurrent HGFM, 11 had locoregional disease. In contrast, all 20 patients with recurrent AG-PTC had locoregional disease (p = 0.148). Eight of the 13 patients with recurrent HGFM had distant metastasis, whereas seven of the 20 patients with recurrent AG-PTC had distant metastasis (p = 0.128). Four patients died during the follow-up period: three in the AG-PTC group and one in the HGFM group (Table 2 ). Table 2 Prognosis of AG-PTC and HGFM According to Recurrence, Persistence, and Mortality Rates Outcomes AG-PTC (n = 74) HGFM (n = 62) P-value Persistent disease 19.4% (out of 67) 15.5% (out of 58) 0.371 Recurrent disease 29.9% (out of 67) 22.4% (out of 58) 0.231 Persistent/recurrent disease 40.3% (out of 67) 29.3% (out of 58) 0.137 Mean time till recurrence in years 2.71 +/- 3.05 4.23 +/- 3.81 0.2395 Mean number of recurrences 1.6 +/- 0.75 1.62 +/- 0.96 0.9615 Death 4.5% (3 out of 67) 1.8% (1 out of 56) 0.38 Mean duration till death (in years) 4 +/- 3 2 Abbreviations: AG-PTC: aggressive-papillary thyroid cancer; HGFM: high-grade follicular cell-derived malignancies Although there was a numerical increase in the rate of persistent/recurrent disease among BRAF-mutated patients, it didn’t reach statistical significance. Also, there was no difference between high (≥ 10%) and low (< 10%) Ki-67 groups. Similarly, no statistically significant difference was observed between patients with ≥ 30% involvement of their aggressive or poorly differentiated features and those with less involvement. When the Ki-67 index was divided into five groups, the recurrence rate was higher in the ≥ 20% Ki-67 group (P-value of 0.017), as shown in Table 3 . Table 3 Number of patients with AG-PTC or HGFM and Number of Recurrences in the Total Cohort Based on Ki-67 Groups Ki67 in % AG-PTC HGFM Recurrence No recurrence < 5 14 4 7 6 5 - <10 4 12 1 13 10 - <15 4 9 5 6 15 - =20 0 7 5 1 p-value 0.002 0.017 Abbreviations: AG-PTC: aggressive-papillary thyroid cancer; HGFM: high-grade follicular cell-derived malignancies In the present cohort, the 5-year disease-free survival was 59.4% and 44.7% in the HGFM and AG-PTC groups, respectively (Fig. 1 ). HR for univariate analysis was 0.53 (p = 0.073), whereas HR for multivariate analysis was 0.47 (p = 0.031), both of which were in favor of HGFM (Table 4 ). In other words, patients with HGFM were 53% less likely to have persistent or recurrent disease compared to those with AG-PTC. Table 4 Univariate and Multivariate Analyses of Disease-free Survival Univariate Multivariate HR CI p HR CI p HGFM 0.53 0.265–1.061 0.073 0.471 0.234–0.945 0.031 Age > = 55 2.761 1.369–5.571 0.005 2.768 1.362–5.625 0.005 Male 2.213 1.125–4.355 0.021 2.236 1.128–4.432 0.021 Ki > = 10% 1.487 0.597–3.669 .394 1.833 0.728–4.619 0.199 BRAF + 1.606 0.649–3.97 0.305 2.168 0.854–5.508 0.104 Percent > = 30% 1.4 0.668–2.931 0.372 1.641 0.757–3.56 0.21 VI 2.53 1.241–5.157 0.011 2.532 1.239–5.176 0.011 Partial biochemical 3.174 1.482-6.8 0.003 2.228 0.995–4.985 0.051 Partial structural 2.255 1.094–4.467 0.028 1.898 0.844–4.271 0.121 Tumor size > 3 cm 3.727 1.641–7.606 < 0.001 3.413 1.495–7.050 0.002 LVI 3.707 1.662–8.969 0.002 3.774 1.763–8.789 0.002 ETE 4.171 1.709–10.18 0.002 4.238 1.721–10.437 0.002 Solid 0.375 0.126–1.013 0.053 0.413 0.145–1.178 0.098 Tall cell 1.899 0.894–3.617 0.073 1.868 0.873–3.733 0.091 Abbreviations: AG-PTC: aggressive-papillary thyroid cancer; HGFM: high-grade follicular cell-derived malignancies; VI: vascular invasion; LVI: lymphovascular invasion; ETE: extrathyroidal extension In the multivariate cox regression analysis, the recurrence rate was 2-fold higher in males than in females (HR: 2.236, confidence interval [CI] = 1.13–4.43, P-value 0.021). The risk of recurrence was 2.8-fold higher in patients aged ≥ 55 years than in younger patients (HR: 2.77, CI = 1.4–5.6, P-value 0.005; Fig. 2 ). In addition, recurrence rates were significantly higher among patients with invasive histological features on surgical pathology, including vascular invasion (HR = 2.5, P-value 0.011), tumor size > 3 cm (HR = 3.4, P-value 0.002), lymphovascular invasion (HR = 3.8, P-value 0.002), and extrathyroidal extension (HR = 4.2, P-value 0.002) (Table 4 ). Discussion In this study, the prevalence of AG-PTC and HGFM in the cohort was low at 2.2% and 1.9%, respectively. These are close to the rates reported in the literature for PDTC but lower than the rates reported for AG-PTC. 20 – 22 After a mean follow-up period of 4.52 +/- 5.04 and 4.89 +/- 4.89 years for AG-PTC and HGFM, respectively, the rates of recurrent disease were found to be 29.9% (AG-PTC) and 22.4% (HGFM), whereas the rates of persistent disease were 19.4% (AG-PTC) and 15.5% (HGFM). These rates are significantly higher than those for well-differentiated thyroid cancers. Ibrahimpasic et al. reported a recurrence rate of 18% in patients with PDTC, and 26% of patients had persistent disease. 5 The tall-cell subtype in the present cohort was associated with a higher rate of recurrent/persistent disease; however, this association did not reach statistical significance. Coca-Pelaz reported that the tall-cell subtype is associated with more aggressive disease, and 20% of the tall cells are refractory to RAI. 6 Consistent with that in the present study, more aggressive tumors and worse prognoses have been associated with older age, larger tumors, and gross extrathyroidal extension. 5 , 6 In the present study, certain features of invasiveness (T3/T4 stage, ETE, LVI, and N1) were more common in the AG-PTC group than in the HGFM group. These factors might account for the lower disease-free survival rate among patients with AG-PTC. Shannon et al. examined a cohort of 365 individuals diagnosed with PTC with tall-cell, discerning that positive surgical margins, nodal metastases, and a primary tumor dimension exceeding 3 cm serve as independent predictors for locoregional recurrence-free survival. 23 The investigation by Kunte et al. into PDTC demonstrated that elevated tumor and nodal stages correlate with significantly worse outcomes, irrespective of the therapeutic methods applied. 24 Furthermore, Ki-67 index is a prognostic marker in many types of tumors. 14 , 23 , 24 Volante et al. revealed that tumor necrosis and mitotic count in cases of solid/trabecular/insular carcinoma are the most relevant indicators for prognosis, 25 which was consistent with the literature on the Ki-67 index. 16 , 26 , 27 Tang reported a linear correlation between tumor size and Ki-67 index with a cutoff value > 2.5%, predicting more recurrence and mortality rates. 17 Additionally, the univariate analysis by Hescot et al. identified that possessing a mitotic count greater than 5 per 2 mm^2 was a factor associated with an increased risk of disease recurrence in thyroid cancer patients. 30 In the present study, an increase in recurrence rates with a Ki-67 index > 10% was observed; however, this did not reach statistical significance. This could be because of the small number of patients with documented Ki-67 data or the low tested cutoff value. If a higher cutoff value had been used, positive results would probably have been achieved. Subgroup analysis revealed that patients with a Ki-67 index ≥ 20% had a significantly higher rate of recurrent disease than those with a Ki-67 index < 20%. BRAF V600E mutation positivity was found in 16.7% of patients in the HGFM group, which is close to the rate reported earlier. 28 However, the positivity rate was much higher in the AG-PTC cohort (84.6%) of the present study, as expected with the papillary nuclear atypia. Jin et al identified that aggressive subtypes of Papillary Thyroid Carcinoma showed a higher incidence of BRAF mutations (89%) and a lower incidence of RAS mutations (3%). 32 A previous study reported that BRAF V600E mutation is associated with aggressive disease and must be investigated in patients with small papillary thyroid carcinoma (< 1.5 cm) or papillary microcarcinoma (< 1 cm) to help identify high-risk groups and initiate ideal treatment. 29 The present study did not show a relationship between the presence of BRAF mutation and the recurrence rate, possibly owing to the small number of patients with reported BRAF genetic testing because it was not routinely performed in all patients until recently. Despite the lack of statistical significance, there was a numerical increase in rates of persistent/recurrent disease among BRAF positive patients. This indicates that BRAF mutation is a promising prognostic marker for AG-PTC. Furthermore, more genetic testing must be performed in a larger population of patients with advanced thyroid cancer to discover possible biomarkers associated with disease progression, evaluate prognosis accurately, and initiate better treatment plans. Higher recurrence rates among patients with ≥ 30% tumor involvement were observed; however, this did not reach statistical significance, supporting recent studies reporting that even tumor involvement of > 10% can cause adverse outcomes. The mortality rate in the HGFM group of our cohort was relatively low at 1.8% compared with that in the large trial of patients with PDTC conducted by Ibrahimpasic et al., who reported a mortality rate of approximately 30%. 5 However, considering the relatively high rate of distant metastasis at presentation in the HGFM group, higher long-term mortality rate is expected in this cohort of patients. This study has some limitations. First, the retrospective nature of this study inevitably resulted in missing data. In addition, BRAF and Ki-67 data were documented in a relatively small number of patients because genetic testing was not routinely performed on all pathology slides at our center until recently. Evidence suggests that other late mutations, such as TP53 30 and TERT mutations, 29 , 31 in combination with those in BRAF , contribute more to an aggressive tumor type, and these mutations were minimally assessed in the present cohort. Further studies should investigate these mutations. Finally, the short follow-up period might have underestimated the recurrence and mortality rates. Further studies with longer follow-up periods should compare patients with consistent findings and results reported. Conclusion AG-PTC and HGFM are aggressive thyroid tumors with high recurrence and persistence rates. Possible prognostic markers for predicting recurrent and persistent thyroid cancers and guiding therapy include tumor size > 3 cm, lymphovascular invasion, vascular invasion, extrathyroidal extension, response to primary therapy, and the proliferative index Ki-67. AG-PTC and HGFM should be recognized and followed up more closely with intense treatment strategies based on prognostic markers. Declarations Acknowledgments Not applicable Authors’ contributions SR wrote the proposal, collected the data, wrote the manuscript, MT originated the idea, supervised the process, revised the manuscript, MA wrote and reviewed the manuscript, SB and MF performed the analysis, RP originated the idea, supervised the process. Funding No sources of funding to declare. Availability of data and materials All data generated or analyzed during the study are included in the article. Ethics approval and consent to participate This study was approved by the Medical-Bioethics Research Ethics Committee (REC) of the Integrated Health and Social Services Network for West-Central Montreal. Consent from participants was not required as this was a retrospective study. Consent for publication Not applicable Competing interests No competing financial or non-financial interests exist. References Kitahara CM, Sosa JA. The changing incidence of thyroid cancer. Nat Rev Endocrinol. 2016;12(11):646-653. Enewold L, Zhu K, Ron E, et al. Rising thyroid cancer incidence in the United States by demographic and tumor characteristics, 1980-2005. Cancer Epidemiol Biomarkers Prev. 2009;18(3):784-791. Zhu X, Yao J, Tian W. Microarray technology to investigate genes associated with papillary thyroid carcinoma. Mol Med Rep. 2015;11(5):3729-3733. Miftari R, Topçiu V, Nura A, Haxhibeqiri V. Management of the patient with aggressive and resistant papillary thyroid carcinoma. 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Diagn Pathol. 2011;6(1):126. Ito Y, Miyauchi A, Kakudo K, Hirokawa M, Kobayashi K, Miya A. Prognostic significance of Ki-67 labeling index in papillary thyroid carcinoma. World J Surg. 2010;34(12):3015-3021. Tang J, Gui C, Qiu S, Wang M. The clinicopathological significance of Ki67 in papillary thyroid carcinoma: a suitable indicator? World J Surg Oncol. 2018;16(1):100. Baloch ZW, Asa SL, Barletta JA, et al. Overview of the 2022 WHO classification of thyroid neoplasms. Endocr Pathol. 2022;33(1):27-63. Haugen BR, Alexander EK, Bible KC, et al. 2015 American Thyroid Association management guidelines for adult patients with thyroid nodules and differentiated thyroid cancer: the American Thyroid Association guidelines task force on thyroid nodules and differentiated thyroid cancer. Thyroid 2016;26(1):1-133. Tong J, Ruan M, Jin Y, et al. Poorly differentiated thyroid carcinoma: a clinician’s perspective. Eur Thyroid J. 2022;11(2). Choi SW, Lee JH, Kim YY, et al. Poorly differentiated thyroid carcinoma: an institutional experience. Korean J Clin Oncol. 2020;16(1):25-32. Ho AS, Luu M, Barrios L, et al. Incidence and mortality risk spectrum across aggressive variants of papillary thyroid carcinoma. JAMA Oncol. 2020;6(5):706-713. Wu SS, Joshi N, Sharrett J, Rao S, Shah A, Scharpf J, et al. Risk Factors Associated With Recurrence and Death in Patients With Tall Cell Papillary Thyroid Cancer: A Single-Institution Cohort Study With Predictive Nomogram. JAMA Otolaryngol Head Neck Surg. 2023;149(1):79-86. Kunte S, Sharett J, Wei W, Nasr C, Prendes B, Lamarre E, et al. Poorly Differentiated Thyroid Carcinoma: Single Institution Series of Outcomes. Anticancer Res. 2022;42(5):2531-9. Luporsi E, André F, Spyratos F, et al. Ki-67: level of evidence and methodological considerations for its role in the clinical management of breast cancer: analytical and critical review. Breast Cancer Res Treat. 2012;132(3):895-915. Berney DM, Gopalan A, Kudahetti S, et al. Ki-67 and outcome in clinically localised prostate cancer: analysis of conservatively treated prostate cancer patients from the Trans-Atlantic Prostate Group study. Br J Cancer. 2009;100(6):888-893. Volante M, Landolfi S, Chiusa L, et al. Poorly differentiated carcinomas of the thyroid with trabecular, insular, and solid patterns: a clinicopathologic study of 183 patients. Cancer. 2004;100(5):950-957. Gnemmi V, Renaud F, Do Cao C, et al. Poorly differentiated thyroid carcinomas: application of the Turin proposal provides prognostic results similar to those from the assessment of high-grade features. Histopathology. 2014;64(2):263-273. Gerdes J, Li L, Schlueter C, et al. Immunobiochemical and molecular biologic characterization of the cell proliferation-associated nuclear antigen that is defined by monoclonal antibody Ki-67. Am J Pathol. 1991;138(4):867-873. Hescot S, Al Ghuzlan A, Henry T, Sheikh-Alard H, Lamartina L, Borget I, et al. Prognostic of recurrence and survival in poorly differentiated thyroid cancer. Endocr Relat Cancer. 2022;29(11):625-34. Romei C, Tacito A, Molinaro E, et al. Clinical, pathological and genetic features of anaplastic and poorly differentiated thyroid cancer: A single institute experience. Oncol Lett. 2018;15(6):9174-9182. Jin M, Song DE, Ahn J, Song E, Lee YM, Sung TY, et al. Genetic Profiles of Aggressive Variants of Papillary Thyroid Carcinomas. Cancers (Basel). 2021;13(4). Silver JA, Bogatchenko M, Pusztaszeri M, et al. BRAF V600E mutation is associated with aggressive features in papillary thyroid carcinomas ≤ 1.5 cm. J Otolaryngol Head Neck Surg. 2021;50(1):63. Kjellman P, Wallin G, Höög A, Auer G, Larsson C, Zedenius J. MIB-1 index in thyroid tumors: a predictor of the clinical course in papillary thyroid carcinoma. Thyroid. 2003;13(4):371-380. Miyauchi A, Kudo T, Hirokawa M, et al. Ki-67 labeling index is a predictor of postoperative persistent disease and cancer growth and a prognostic indicator in papillary thyroid carcinoma. Eur Thyroid J. 2013;2(1):57-64. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4087685","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":280851781,"identity":"1e51a07b-87f2-495b-ae2c-27c8455f4d09","order_by":0,"name":"Suhaib Adel Radi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2UlEQVRIiWNgGAWjYHACgwMMDDYMDBJgDjPRWtJI1ALEh0nQYt5+eOPBn23n8+Sjmx8w3aiwZpBvP4Bfi8yZtILDvG23iw3vHDNgzjmTzmBwJgG/FgmGHIPDjG23EzfOSDBgzm07DHQnIS38bwyADjsH1JL+gTn332EG+f4HBLRI5Bgc4G07kDgfyGDObQCGww1Ctkg8KzjMcy45cYNETsHhnGPpPAY3CNnCn7z5448yu8T5M9I3Ps6psZaT7ydgCxyAIhSIGHiIVA8E8g3Eqx0Fo2AUjIIRBgCYUEeGEQROhQAAAABJRU5ErkJggg==","orcid":"","institution":"King Saud bin Abdulaziz University for Health Sciences","correspondingAuthor":true,"prefix":"","firstName":"Suhaib","middleName":"Adel","lastName":"Radi","suffix":""},{"id":280851782,"identity":"34b89c42-4048-46c8-8547-d829eba3a9da","order_by":1,"name":"Mazin Al-Maghrabi","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Mazin","middleName":"","lastName":"Al-Maghrabi","suffix":""},{"id":280851783,"identity":"2e5ce393-77ad-40ae-8d0d-f0b98a8da922","order_by":2,"name":"Saleh Binmahfooz","email":"","orcid":"","institution":"King Abdulaziz University","correspondingAuthor":false,"prefix":"","firstName":"Saleh","middleName":"","lastName":"Binmahfooz","suffix":""},{"id":280851784,"identity":"9cc385e5-9b8b-4a1b-ad72-3c8fd7f3d869","order_by":3,"name":"Miguel Franco","email":"","orcid":"","institution":"Autonomous University of Nayarit","correspondingAuthor":false,"prefix":"","firstName":"Miguel","middleName":"","lastName":"Franco","suffix":""},{"id":280851785,"identity":"ceaf6ee3-c552-4c57-b86c-ab4cd1f36ddf","order_by":4,"name":"Richard Payne","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Richard","middleName":"","lastName":"Payne","suffix":""},{"id":280851786,"identity":"a00ddfcc-c999-4069-96fa-828df4487141","order_by":5,"name":"Michael Tamilia","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"","lastName":"Tamilia","suffix":""}],"badges":[],"createdAt":"2024-03-12 21:35:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4087685/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4087685/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53184090,"identity":"1f3ccbc3-1b70-4efd-9c40-044b20b00711","added_by":"auto","created_at":"2024-03-21 16:04:13","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":103481,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier curve for disease-free survival in the AG-PTC and HGFM groups.\u003c/p\u003e\n\u003cp\u003eAbbreviations: AG-PTC: aggressive-papillary thyroid cancer; HGFM: high-grade follicular cell-derived malignancies\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4087685/v1/f63cc1965d1e00410a5ae9d6.png"},{"id":53184091,"identity":"27c38699-d378-4121-8659-61ced5c8ffd8","added_by":"auto","created_at":"2024-03-21 16:04:13","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":96384,"visible":true,"origin":"","legend":"\u003cp\u003eRecurrence probability according to age.\u003c/p\u003e\n\u003cp\u003eHR: 2.77, p = 0.005\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4087685/v1/826cdb186008ef05b1f5390f.png"},{"id":57618649,"identity":"14878c49-a864-4fbd-83f2-2c16078f3de6","added_by":"auto","created_at":"2024-06-03 12:21:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":862419,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4087685/v1/50a66594-dadf-4ef0-9b49-466ea52c8cb9.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Clinical Characteristics and Prognostic Markers of Aggressive Subtypes of Thyroid Cancer: A Retrospective Chart Review Study","fulltext":[{"header":"Key Points","content":"\u003cp\u003e\u003cstrong\u003eQuestion:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWhat characteristics and factors can affect the prognosis of patients with\u0026nbsp;high-grade follicular cell-derived malignancies (aggressive papillary thyroid cancer [AG-PTC] and\u0026nbsp;high-grade follicular cell-derived malignancies [HGFM]).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eFindings:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOf 75 patients followed up for \u0026gt;1 year, 42.7% had either a persistent or recurrent disease (52.6% in the AG-PTC group and 32.4% in the HGFM group), 4.5% died of AG-PTC, and 1.8% died in the HGFM group. The presence of vascular or lymphovascular invasion and extrathyroidal extension was associated with a higher incidence of persistent or recurrent disease (Hazard ratio: 2.5, 3.8, and 4.2, respectively; p \u0026lt;0.05)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eMeaning:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRates of persistent and recurrent disease are high in patients with HGFM and AG-PTC. Certain pathological features can predict worse prognosis in these patients. Close follow up and aggressive management is warranted in this group.\u0026nbsp;\u003c/p\u003e"},{"header":"Background","content":"\u003cp\u003eThyroid cancer is the most prevalent endocrine tumor, and its prevalence has increased significantly over the last 20 years owing primarily to the increased detection of thyroid microcarcinomas.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e It\u0026rsquo;s estimated that thyroid cancer constitutes around 2% of all malignancies worldwide.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e Follicular cell-derived thyroid cancer includes different histologic types: papillary thyroid cancer (PTC), follicular thyroid cancer (FTC), poorly differentiated thyroid cancer (PDTC), and anaplastic thyroid cancer (ATC). PTC and FTC are usually well differentiated and have good prognoses. In contrast, PDTC and ATC are rarer, dedifferentiated, and have worse outcomes. PTC accounts for approximately 80% of thyroid cancer cases.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe aggressive subtypes of PTC (AG-PTC) and PDTC are malignancies that lie between well-differentiated and undifferentiated anaplastic cancers. The features and management of well-differentiated cancers have been established in the literature; however, AG-PTC and PDTC need to be clarified further because they have characteristics different from those of their more benign counterparts.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e The prevalence of AG-PTC and PDTC is relatively low; however, the incidence of persistent or recurrent disease at 1 year after primary therapy is high compared with that of the more well-differentiated tumors.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e Furthermore, AG-PTC subtypes possess distinct clinical, pathological, and molecular features that distinguish it from well-differentiated PTC with a higher rate of metastasis and lower avidity to radioactive iodine (RAI).\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe 5-year survival rate for thyroid cancer varies according to histotype. A recent epidemiological study in Denmark based on a national cancer registry reported that the 5-year survival rate was 91.1%, 79.9%, and 63.6% for PTC, FTC, and PDTC, respectively.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e PTC has a good prognosis; however, there are aggressive subtypes with clinicopathological and genomic backgrounds different from those of the classical PTC.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe development of molecular techniques has led us to identify clinically significant biomarkers useful in the diagnosis and prognosis of PTC.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e Knowing the features and markers that predict a worse prognosis can help treat and monitor patients after primary therapy. The \u003cem\u003eBRAF\u003c/em\u003e-encoded BRAF protein sends signals to direct cell proliferation.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e BRAF mutations are associated with more invasive disease and a higher risk of recurrence in patients with thyroid cancer compared to those without BRAF mutations.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e However, whether BRAF mutations are associated with PDTC remains unclear.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe Ki-67 index is a widely used biomarker for assessing the cell proliferation rate of certain cancers, such as breast cancer and neuroendocrine neoplasia.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e Ki-67 expression and its role in thyroid cancer have been debated; however, it has potential implications for differentiating between benign and malignant tumors.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e Ito et al. found that the proliferative index Ki-67 is an independent prognostic factor for disease-free survival in patients with PTC.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Furthermore, a high Ki-67 index in patients with PTC is associated with higher recurrence rates and poor survival.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn the present study, we aimed to analyze and characterize the clinical, pathological, and genotypic aspects of AG-PTC and PDTC and their prognostic significance in this patient cohort. We primarily aimed to determine the association of the Ki-67 index and \u003cem\u003eBRAF\u003c/em\u003e mutations with recurrent or persistent thyroid cancer, with a secondary aim to determine the association between persistent or recurrent thyroid cancer and other clinicopathological prognostic markers. This may contribute to directing surveillance and individualizing the therapeutic strategies in such patients.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design, setting, and population\u003c/h2\u003e \u003cp\u003e After obtaining ethics approval from the Institutional Research Board (IRB), project number 2020\u0026thinsp;\u0026minus;\u0026thinsp;1902, this retrospective chart review of adult patients of both sexes, aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years, with thyroid cancer over the last 10 years, between 2010 and 2019 at the Jewish General Hospital in Montreal, Canada, affiliated with McGill University, was conducted. A total of 3,324 medical records were reviewed, and patients with AG-PTC or PDTC were included. Patients with other types of thyroid cancer were excluded, leaving 136 patients who met the diagnostic criteria. Of the total cohort, 124 patients were followed up for \u0026ge;\u0026thinsp;1 year.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eDefinitions of AG-PTC and PDTC\u003c/h2\u003e \u003cp\u003eAccording to the World Health Organization (WHO) criteria, AG-PTC is defined as the presence of one of the following histologic patterns: tall cell, clear cell, diffuse sclerosing, columnar cell, or hobnail. The presence of one or more of these patterns at \u0026ge;\u0026thinsp;30% is considered a subtype; otherwise, it would be called \u0026ldquo;features.\u0026rdquo; The recently released 2022 WHO report distinguishes the two types of high-grade follicular cell-derived malignancies (HGFM): PDTC and differentiated high-grade thyroid carcinoma (DHGTC). PDTC was defined using the Turin criteria as the presence of a solid/trabecular pattern, an insular growth pattern, and one of three high-grade features\u0026mdash;mitosis (\u0026gt;\u0026thinsp;3/10 high-power field), necrosis, or convoluted nuclei. DHGTC was defined based on high mitotic activity and tumor necrosis, regardless of histological differentiation. Both types were grouped together in the present study under HGFM, considering similar biologic behaviours.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eOutcomes\u003c/h2\u003e \u003cp\u003ePersistent disease was defined as an incomplete response, either structural or biochemical.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e Recurrence was defined as evidence of disease confirmed using either structural or functional imaging or biopsy after 6 months of being disease-free. Disease-free survival was defined as the duration during which a patient remains free of any signs or symptoms of a specific disease after completing a treatment, indicating the absence of disease recurrence or progression during that period. Ki-67 index and BRAF mutations, determined using immunohistochemistry, were included in only some of the medical records reviewed because they were routinely analyzed more frequently in all aggressive types recently and much less frequently in older specimens.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe characteristics of patients and tumors were compared between those with and without evidence of persistent disease, recurrence, or death using the Pearson x\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e test. Univariate and multivariate analyses were performed using the log-rank test and the Cox proportional hazards method, respectively. Statistical significance was set at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Statistical analysis was performed using SPSS version 26.0 (IBM).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eIn total, out of the 3,324 patients screened, 136 patients were included in this study: 74 in the AG-PTC group and 62 in the HGFM group. This constitutes a prevalence of AG-PTC of 2.2% and HGFM of 1.9%. Furthermore, most patients were females in the AG-PTC (70.30% [n\u0026thinsp;=\u0026thinsp;52/74]) and HGFM (59.7% [n\u0026thinsp;=\u0026thinsp;37/62]) groups. The mean age was 44 (+/- 18.7) and 54 (+/- 14.5) years in the AG-PTC and HGFM groups, respectively (P\u0026thinsp;=\u0026thinsp;0.0005; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline Characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAG-PTC (n\u0026thinsp;=\u0026thinsp;74)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHGFM (n\u0026thinsp;=\u0026thinsp;62)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean age in years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean f/u in years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.52 +/- 5.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.89 +/- 5.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHobnail features\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"10\" rowspan=\"11\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiffuse sclerosing features\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eColumnar features\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTall cell features\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClear cell features\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsular features\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMitosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003enecrosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSolid features\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrabecular features\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConvoluted nuclei features\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;= 30% involvement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean tumor size in cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0133\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT3/T4 stage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExtrathyroidal extension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0039\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVascular invasion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.591\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphovascular invasion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000087\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive margins\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.514\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epN1 stage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epM1 stage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.231\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBiochemical response\u003c/p\u003e \u003cp\u003e\u0026bull; Complete\u003c/p\u003e \u003cp\u003e\u0026bull; Partial\u003c/p\u003e \u003cp\u003e\u0026bull; Indeterminate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOut of 65\u003c/p\u003e \u003cp\u003e49.2%\u003c/p\u003e \u003cp\u003e32.3%\u003c/p\u003e \u003cp\u003e18.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOut of 54\u003c/p\u003e \u003cp\u003e72%\u003c/p\u003e \u003cp\u003e22.2%\u003c/p\u003e \u003cp\u003e5.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStructural response\u003c/p\u003e \u003cp\u003e\u0026bull; Complete\u003c/p\u003e \u003cp\u003e\u0026bull; Partial\u003c/p\u003e \u003cp\u003e\u0026bull; Indeterminate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOut of 66\u003c/p\u003e \u003cp\u003e60.6%\u003c/p\u003e \u003cp\u003e19.7%\u003c/p\u003e \u003cp\u003e19.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOut of 53\u003c/p\u003e \u003cp\u003e66%\u003c/p\u003e \u003cp\u003e17%\u003c/p\u003e \u003cp\u003e17%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean Ki67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0033\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKi67 groups\u003c/p\u003e \u003cp\u003e\u0026bull; \u0026lt;\u0026thinsp;10\u003c/p\u003e \u003cp\u003e\u0026bull; \u0026gt;= 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOut of 24\u003c/p\u003e \u003cp\u003e75%\u003c/p\u003e \u003cp\u003e25%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOut of 35\u003c/p\u003e \u003cp\u003e45.7%\u003c/p\u003e \u003cp\u003e54.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBRAF positive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84.6% (out of 26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.7% (out of 24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eAbbreviations: AG-PTC: aggressive-papillary thyroid cancer; HGFM: high-grade follicular cell-derived malignancies\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe most prominent subtype in the AG-PTC group was tall-cell (55.4%, n\u0026thinsp;=\u0026thinsp;41/74), followed by diffuse sclerosing (35.1%, n\u0026thinsp;=\u0026thinsp;26/74) and hobnail (16.2%, n\u0026thinsp;=\u0026thinsp;12/74). The most common growth pattern in the HGFM group was solid (61.3%, n\u0026thinsp;=\u0026thinsp;38/62), followed by trabecular (43.6%, n\u0026thinsp;=\u0026thinsp;27/62). The mean tumor size was 2.71 cm (+/- 1.60) and 3.58 cm (+/- 2.25) in the AG-PTC and HGFM groups, respectively (p\u0026thinsp;=\u0026thinsp;0.0133). Furthermore, more patients had advanced disease (stages T3 and T4) in the AG-PTC group than in the HGFM group (54.8% vs. 37.1%, p\u0026thinsp;=\u0026thinsp;0.03). Extrathyroidal extension occurred in more patients in the AG-PTC group than in the HGFM group (51.4% vs. 21%, p\u0026thinsp;=\u0026thinsp;0.0039). Similarly, more patients had lymphovascular invasion (71.6%) in the AG-PTC group than in the HGFM group (40.3%) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.005).\u003c/p\u003e \u003cp\u003eSix patients had metastasis on presentation in the AG-PTC group, whereas eight had metastasis in the HGFM group. Of the eight patients with pM1 on presentation (four biopsy-proven, three to the lungs, and five to the bones) in the HGFM group, five were RAI-avid and two were flurodeoxyglucose (FDG)-avid. Of the six patients with pM1 on presentation (four biopsy-proven, three to the lungs, and three to the bones and lungs) in the AG-PTC group, five were RAI-avid and one was FDG-avid.\u003c/p\u003e \u003cp\u003eFurthermore, 89.2% of patients received RAI treatment in the AG-PTC group, whereas 74.19% received it in the HGFM group. Two patients underwent radiotherapy in the AG-PTC group, whereas one underwent radiotherapy in the HGFM group. Central neck dissection was performed in 61.81% and 68% of patients in the AG-PTC and HGFM groups, respectively. Furthermore, 32.43% and 11.29% of patients underwent central and lateral neck dissections in the AG-PTC and HGFM groups, respectively. Lobectomy only was performed in 4% and 16.13% of patients in the AG-PTC and HGFM groups, respectively. The reason for performing lobectomy in most cases was the aggressive nature of the disease, which made total thyroidectomy unfeasible.\u003c/p\u003e \u003cp\u003eNotably, more patients achieved complete biochemical response in the HGFM group than in the AG-PTC group (72% [n\u0026thinsp;=\u0026thinsp;39/54] vs. 49.2% [n\u0026thinsp;=\u0026thinsp;32/65]), p\u0026thinsp;=\u0026thinsp;0.022). The complete structural responses of both groups were similar (AG-PTC: 60.6% [n\u0026thinsp;=\u0026thinsp;40/66], HGFM: 66% [n\u0026thinsp;=\u0026thinsp;35/53]).\u003c/p\u003e \u003cp\u003eIn the AG-PTC group, 19.4% of patients had persistent disease, whereas 29.9% had recurrent disease. In the HGFM group, 15.5% of patients had persistent disease, whereas 22.4% had recurrent disease. The combined persistent or recurrent disease rate was numerically higher in the AG-PTC group than in the HGFM group (40.3% vs. 29.3%, p\u0026thinsp;=\u0026thinsp;0.137).\u003c/p\u003e \u003cp\u003eOf 13 patients with recurrent HGFM, 11 had locoregional disease. In contrast, all 20 patients with recurrent AG-PTC had locoregional disease (p\u0026thinsp;=\u0026thinsp;0.148). Eight of the 13 patients with recurrent HGFM had distant metastasis, whereas seven of the 20 patients with recurrent AG-PTC had distant metastasis (p\u0026thinsp;=\u0026thinsp;0.128). Four patients died during the follow-up period: three in the AG-PTC group and one in the HGFM group (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrognosis of AG-PTC and HGFM According to Recurrence, Persistence, and Mortality Rates\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcomes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAG-PTC (n\u0026thinsp;=\u0026thinsp;74)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHGFM (n\u0026thinsp;=\u0026thinsp;62)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePersistent disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.4% (out of 67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.5% (out of 58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.371\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRecurrent disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29.9% (out of 67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.4% (out of 58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.231\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePersistent/recurrent disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40.3% (out of 67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.3% (out of 58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.137\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean time till recurrence in years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.71 +/- 3.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.23 +/- 3.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2395\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean number of recurrences\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.6 +/- 0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.62 +/- 0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9615\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeath\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.5% (3 out of 67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.8% (1 out of 56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean duration till death (in years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 +/- 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eAbbreviations: AG-PTC: aggressive-papillary thyroid cancer; HGFM: high-grade follicular cell-derived malignancies\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAlthough there was a numerical increase in the rate of persistent/recurrent disease among BRAF-mutated patients, it didn\u0026rsquo;t reach statistical significance. Also, there was no difference between high (\u0026ge;\u0026thinsp;10%) and low (\u0026lt;\u0026thinsp;10%) Ki-67 groups. Similarly, no statistically significant difference was observed between patients with \u0026ge;\u0026thinsp;30% involvement of their aggressive or poorly differentiated features and those with less involvement. When the Ki-67 index was divided into five groups, the recurrence rate was higher in the \u0026ge;\u0026thinsp;20% Ki-67 group (P-value of 0.017), as shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNumber of patients with AG-PTC or HGFM and Number of Recurrences in the Total Cohort Based on Ki-67 Groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKi67 in %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAG-PTC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHGFM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRecurrence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo recurrence\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5 - \u0026lt;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10 - \u0026lt;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15 - \u0026lt;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;=20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eAbbreviations: AG-PTC: aggressive-papillary thyroid cancer; HGFM: high-grade follicular cell-derived malignancies\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the present cohort, the 5-year disease-free survival was 59.4% and 44.7% in the HGFM and AG-PTC groups, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). HR for univariate analysis was 0.53 (p\u0026thinsp;=\u0026thinsp;0.073), whereas HR for multivariate analysis was 0.47 (p\u0026thinsp;=\u0026thinsp;0.031), both of which were in favor of HGFM (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). In other words, patients with HGFM were 53% less likely to have persistent or recurrent disease compared to those with AG-PTC.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate and Multivariate Analyses of Disease-free Survival\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUnivariate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMultivariate\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHGFM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.265\u0026ndash;1.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.471\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.234\u0026ndash;0.945\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u0026thinsp;\u0026gt;\u0026thinsp;=\u0026thinsp;55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.761\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.369\u0026ndash;5.571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.768\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.362\u0026ndash;5.625\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.125\u0026ndash;4.355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.128\u0026ndash;4.432\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKi\u0026thinsp;\u0026gt;\u0026thinsp;=\u0026thinsp;10%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.487\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.597\u0026ndash;3.669\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.394\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.833\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.728\u0026ndash;4.619\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.199\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBRAF +\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.649\u0026ndash;3.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.854\u0026ndash;5.508\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.104\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePercent\u0026thinsp;\u0026gt;\u0026thinsp;=\u0026thinsp;30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.668\u0026ndash;2.931\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.641\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.757\u0026ndash;3.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.241\u0026ndash;5.157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.239\u0026ndash;5.176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePartial biochemical\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.482-6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.995\u0026ndash;4.985\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePartial structural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.094\u0026ndash;4.467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.898\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.844\u0026ndash;4.271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.121\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumor size\u0026thinsp;\u0026gt;\u0026thinsp;3 cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.727\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.641\u0026ndash;7.606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.413\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.495\u0026ndash;7.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLVI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.662\u0026ndash;8.969\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.774\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.763\u0026ndash;8.789\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eETE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.709\u0026ndash;10.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.721\u0026ndash;10.437\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSolid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.126\u0026ndash;1.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.413\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.145\u0026ndash;1.178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.098\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTall cell\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.899\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.894\u0026ndash;3.617\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.868\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.873\u0026ndash;3.733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.091\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eAbbreviations: AG-PTC: aggressive-papillary thyroid cancer; HGFM: high-grade follicular cell-derived malignancies; VI: vascular invasion; LVI: lymphovascular invasion; ETE: extrathyroidal extension\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the multivariate cox regression analysis, the recurrence rate was 2-fold higher in males than in females (HR: 2.236, confidence interval [CI]\u0026thinsp;=\u0026thinsp;1.13\u0026ndash;4.43, P-value 0.021). The risk of recurrence was 2.8-fold higher in patients aged\u0026thinsp;\u0026ge;\u0026thinsp;55 years than in younger patients (HR: 2.77, CI\u0026thinsp;=\u0026thinsp;1.4\u0026ndash;5.6, P-value 0.005; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In addition, recurrence rates were significantly higher among patients with invasive histological features on surgical pathology, including vascular invasion (HR\u0026thinsp;=\u0026thinsp;2.5, P-value 0.011), tumor size\u0026thinsp;\u0026gt;\u0026thinsp;3 cm (HR\u0026thinsp;=\u0026thinsp;3.4, P-value 0.002), lymphovascular invasion (HR\u0026thinsp;=\u0026thinsp;3.8, P-value 0.002), and extrathyroidal extension (HR\u0026thinsp;=\u0026thinsp;4.2, P-value 0.002) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, the prevalence of AG-PTC and HGFM in the cohort was low at 2.2% and 1.9%, respectively. These are close to the rates reported in the literature for PDTC but lower than the rates reported for AG-PTC.\u003csup\u003e\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e After a mean follow-up period of 4.52 +/- 5.04 and 4.89 +/- 4.89 years for AG-PTC and HGFM, respectively, the rates of recurrent disease were found to be 29.9% (AG-PTC) and 22.4% (HGFM), whereas the rates of persistent disease were 19.4% (AG-PTC) and 15.5% (HGFM). These rates are significantly higher than those for well-differentiated thyroid cancers. Ibrahimpasic et al. reported a recurrence rate of 18% in patients with PDTC, and 26% of patients had persistent disease.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e The tall-cell subtype in the present cohort was associated with a higher rate of recurrent/persistent disease; however, this association did not reach statistical significance. Coca-Pelaz reported that the tall-cell subtype is associated with more aggressive disease, and 20% of the tall cells are refractory to RAI.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e Consistent with that in the present study, more aggressive tumors and worse prognoses have been associated with older age, larger tumors, and gross extrathyroidal extension.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e In the present study, certain features of invasiveness (T3/T4 stage, ETE, LVI, and N1) were more common in the AG-PTC group than in the HGFM group. These factors might account for the lower disease-free survival rate among patients with AG-PTC. Shannon et al. examined a cohort of 365 individuals diagnosed with PTC with tall-cell, discerning that positive surgical margins, nodal metastases, and a primary tumor dimension exceeding 3 cm serve as independent predictors for locoregional recurrence-free survival. \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e The investigation by Kunte et al. into PDTC demonstrated that elevated tumor and nodal stages correlate with significantly worse outcomes, irrespective of the therapeutic methods applied. \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFurthermore, Ki-67 index is a prognostic marker in many types of tumors.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e Volante et al. revealed that tumor necrosis and mitotic count in cases of solid/trabecular/insular carcinoma are the most relevant indicators for prognosis,\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e which was consistent with the literature on the Ki-67 index.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e Tang reported a linear correlation between tumor size and Ki-67 index with a cutoff value\u0026thinsp;\u0026gt;\u0026thinsp;2.5%, predicting more recurrence and mortality rates.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e Additionally, the univariate analysis by Hescot et al. identified that possessing a mitotic count greater than 5 per 2 mm^2 was a factor associated with an increased risk of disease recurrence in thyroid cancer patients. \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e In the present study, an increase in recurrence rates with a Ki-67 index\u0026thinsp;\u0026gt;\u0026thinsp;10% was observed; however, this did not reach statistical significance. This could be because of the small number of patients with documented Ki-67 data or the low tested cutoff value. If a higher cutoff value had been used, positive results would probably have been achieved. Subgroup analysis revealed that patients with a Ki-67 index\u0026thinsp;\u0026ge;\u0026thinsp;20% had a significantly higher rate of recurrent disease than those with a Ki-67 index\u0026thinsp;\u0026lt;\u0026thinsp;20%.\u003c/p\u003e \u003cp\u003e \u003cem\u003eBRAF\u003c/em\u003e V600E mutation positivity was found in 16.7% of patients in the HGFM group, which is close to the rate reported earlier.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e However, the positivity rate was much higher in the AG-PTC cohort (84.6%) of the present study, as expected with the papillary nuclear atypia. Jin et al identified that aggressive subtypes of Papillary Thyroid Carcinoma showed a higher incidence of BRAF mutations (89%) and a lower incidence of RAS mutations (3%). \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e A previous study reported that \u003cem\u003eBRAF\u003c/em\u003e V600E mutation is associated with aggressive disease and must be investigated in patients with small papillary thyroid carcinoma (\u0026lt;\u0026thinsp;1.5 cm) or papillary microcarcinoma (\u0026lt;\u0026thinsp;1 cm) to help identify high-risk groups and initiate ideal treatment.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e The present study did not show a relationship between the presence of \u003cem\u003eBRAF\u003c/em\u003e mutation and the recurrence rate, possibly owing to the small number of patients with reported \u003cem\u003eBRAF\u003c/em\u003e genetic testing because it was not routinely performed in all patients until recently. Despite the lack of statistical significance, there was a numerical increase in rates of persistent/recurrent disease among BRAF positive patients. This indicates that \u003cem\u003eBRAF\u003c/em\u003e mutation is a promising prognostic marker for AG-PTC. Furthermore, more genetic testing must be performed in a larger population of patients with advanced thyroid cancer to discover possible biomarkers associated with disease progression, evaluate prognosis accurately, and initiate better treatment plans.\u003c/p\u003e \u003cp\u003eHigher recurrence rates among patients with \u0026ge;\u0026thinsp;30% tumor involvement were observed; however, this did not reach statistical significance, supporting recent studies reporting that even tumor involvement of \u0026gt;\u0026thinsp;10% can cause adverse outcomes. The mortality rate in the HGFM group of our cohort was relatively low at 1.8% compared with that in the large trial of patients with PDTC conducted by Ibrahimpasic et al., who reported a mortality rate of approximately 30%.\u003csup\u003e5\u003c/sup\u003e However, considering the relatively high rate of distant metastasis at presentation in the HGFM group, higher long-term mortality rate is expected in this cohort of patients.\u003c/p\u003e \u003cp\u003eThis study has some limitations. First, the retrospective nature of this study inevitably resulted in missing data. In addition, BRAF and Ki-67 data were documented in a relatively small number of patients because genetic testing was not routinely performed on all pathology slides at our center until recently. Evidence suggests that other late mutations, such as \u003cem\u003eTP53\u003c/em\u003e\u003csup\u003e30\u003c/sup\u003e and \u003cem\u003eTERT\u003c/em\u003e mutations,\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e in combination with those in \u003cem\u003eBRAF\u003c/em\u003e, contribute more to an aggressive tumor type, and these mutations were minimally assessed in the present cohort. Further studies should investigate these mutations. Finally, the short follow-up period might have underestimated the recurrence and mortality rates. Further studies with longer follow-up periods should compare patients with consistent findings and results reported.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eAG-PTC and HGFM are aggressive thyroid tumors with high recurrence and persistence rates. Possible prognostic markers for predicting recurrent and persistent thyroid cancers and guiding therapy include tumor size\u0026thinsp;\u0026gt;\u0026thinsp;3 cm, lymphovascular invasion, vascular invasion, extrathyroidal extension, response to primary therapy, and the proliferative index Ki-67. AG-PTC and HGFM should be recognized and followed up more closely with intense treatment strategies based on prognostic markers.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSR wrote the proposal, collected the data, wrote the manuscript, MT originated the idea, supervised the process, revised the manuscript, MA wrote and reviewed the manuscript, SB and MF performed the analysis, RP originated the idea, supervised the process.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo sources of funding to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during the study are included in the article.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Medical-Bioethics Research Ethics Committee (REC) of the Integrated Health and Social Services Network for West-Central Montreal.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eConsent from participants was not required as this was a retrospective study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo competing financial or non-financial interests exist.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKitahara CM, Sosa JA. 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Ki-67: level of evidence and methodological considerations for its role in the clinical management of breast cancer: analytical and critical review. \u003cem\u003eBreast Cancer Res Treat. \u003c/em\u003e2012;132(3):895-915. \u003c/li\u003e\n\u003cli\u003eBerney DM, Gopalan A, Kudahetti S, et al. Ki-67 and outcome in clinically localised prostate cancer: analysis of conservatively treated prostate cancer patients from the Trans-Atlantic Prostate Group study. \u003cem\u003eBr J Cancer. \u003c/em\u003e2009;100(6):888-893. \u003c/li\u003e\n\u003cli\u003eVolante M, Landolfi S, Chiusa L, et al. Poorly differentiated carcinomas of the thyroid with trabecular, insular, and solid patterns: a clinicopathologic study of 183 patients. \u003cem\u003eCancer. \u003c/em\u003e2004;100(5):950-957. \u003c/li\u003e\n\u003cli\u003eGnemmi V, Renaud F, Do Cao C, et al. 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Clinical, pathological and genetic features of anaplastic and poorly differentiated thyroid cancer: A single institute experience. \u003cem\u003eOncol Lett. \u003c/em\u003e2018;15(6):9174-9182. \u003c/li\u003e\n\u003cli\u003eJin M, Song DE, Ahn J, Song E, Lee YM, Sung TY, et al. Genetic Profiles of Aggressive Variants of Papillary Thyroid Carcinomas. Cancers (Basel). 2021;13(4). \u003c/li\u003e\n\u003cli\u003eSilver JA, Bogatchenko M, Pusztaszeri M, et al. BRAF V600E mutation is associated with aggressive features in papillary thyroid carcinomas \u0026le;\u0026thinsp;1.5 cm. \u003cem\u003eJ Otolaryngol Head Neck Surg. \u003c/em\u003e2021;50(1):63. \u003c/li\u003e\n\u003cli\u003eKjellman P, Wallin G, H\u0026ouml;\u0026ouml;g A, Auer G, Larsson C, Zedenius J. MIB-1 index in thyroid tumors: a predictor of the clinical course in papillary thyroid carcinoma. \u003cem\u003eThyroid. \u003c/em\u003e2003;13(4):371-380. \u003c/li\u003e\n\u003cli\u003eMiyauchi A, Kudo T, Hirokawa M, et al. Ki-67 labeling index is a predictor of postoperative persistent disease and cancer growth and a prognostic indicator in papillary thyroid carcinoma. \u003cem\u003eEur Thyroid J. \u003c/em\u003e2013;2(1):57-64.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Thyroid cancer, Ki-67, BRAF, genetic mutation, aggressive variant of papillary thyroid cancer, poorly differentiated thyroid cancer, prognostic marker","lastPublishedDoi":"10.21203/rs.3.rs-4087685/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4087685/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cb\u003eImportance\u003c/b\u003e: The prevalence of thyroid cancer has increased significantly. Aggressive subtypes of papillary thyroid cancer (AG-PTC) and poorly differentiated thyroid cancer (PDTC) are malignancies that lie between well-differentiated and undifferentiated cancers. The management of well-differentiated cancers has been established in the literature; however, that of AG-PTC and PDTC needs to be clarified.\u003c/p\u003e \u003cp\u003e \u003cb\u003eObjective\u003c/b\u003e: To describe the clinicopathological characteristics and genomic landscape of AG-PTC and PDTC and to assess their prognostic value. We primarily aimed to determine the association between persistent or recurrent thyroid cancer and clinicopathological prognostic markers\u003c/p\u003e \u003cp\u003e \u003cb\u003eDesign\u003c/b\u003e: A retrospective chart review of patients with thyroid cancer over the last 10 years\u003c/p\u003e \u003cp\u003e \u003cb\u003eSetting\u003c/b\u003e: Single center\u003c/p\u003e \u003cp\u003e \u003cb\u003eParticipants\u003c/b\u003e: Patients with AG-PTC or high-grade follicular cell-derived malignancies (HGFM) were included in the analysis. HGFM comprised of patients with PDTC \u0026amp; differentiated high-grade thyroid carcinoma. The clinical presentation, pathological characteristics, molecular markers, specific treatments, and clinical outcomes were compared between the groups.\u003c/p\u003e \u003cp\u003eExposure(s):\u003c/p\u003e \u003cp\u003eMain Outcome(s) and Measure(s):\u003c/p\u003e \u003cp\u003e \u003cb\u003eResults\u003c/b\u003e: Of the 3,244 thyroid cancer charts reviewed, 136 met the criteria for AG-PTC and HGFM. The mean age at diagnosis was 49 years, with a predominance of women. The median follow-up duration was 3 years. The rate of persistent or recurrent disease was 40.3% in the AG-PTC group and 29.3% in the HGFM group, 4.5% died in the AG-PTC group, and 1.8% died in the HGFM group. The presence of vascular, lymphovascular invasion and extrathyroidal extension were associated with a higher incidence of persistent or recurrent disease (Hazard ratio: 2.5, 3.8, and 4.2, respectively; p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). When the Ki-67 index was divided into five groups, the recurrence rate was higher in the \u0026ge;\u0026thinsp;20% Ki-67 group compared to lower Ki67 (P-value of 0.017). Although there was a numerical increase in the rate of persistent/recurrent disease among BRAF-mutated patients, it didn\u0026rsquo;t reach statistical significance. No difference was observed in recurrence based on percentage of aggressive/poorly differentiated tumor involvement.\u003c/p\u003e \u003cp\u003e \u003cb\u003eConclusions and Relevance\u003c/b\u003e: Possible prognostic markers for predicting recurrent and persistent thyroid cancers and guiding therapy for AG-PTC and HGFM include vascular/lymphovascular invasion, extrathyroidal extension, and the proliferative index Ki-67.\u003c/p\u003e","manuscriptTitle":"Clinical Characteristics and Prognostic Markers of Aggressive Subtypes of Thyroid Cancer: A Retrospective Chart Review Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-21 16:04:08","doi":"10.21203/rs.3.rs-4087685/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5d26be5a-00a3-4a07-8721-b891ec4cfb07","owner":[],"postedDate":"March 21st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-03T12:13:02+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-21 16:04:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4087685","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4087685","identity":"rs-4087685","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}