Prognostic Value of Genetic Mutations in Thyroid Cancer: A Meta-Analysis

Abstract

Background:

Genetic mutations have been found to be associated with thyroid cancer. Previous studies have been focused on the relation between genetic mutations and thyroid cancer. We sought to evaluate the prognostic value of the three most common genetic mutations (BRAF, RAS, and RET) in patients with thyroid cancer.

Methods:

Sources from MEDLINE (inception to December 2013) and EMBASE (inception to December 2013) were searched. Studies of thyroid cancer with results of genetic mutations and studies that reported survival data were included and two authors performed the data extraction independently. Any discrepancies were resolved by a consensus.

Results:

Fourteen studies assessing BRAF mutations, 6 RAS mutations, 4 RET mutations, and 1 with analysis of both BRAF and RAS mutations were included in this meta-analysis. Patients with papillary thyroid cancer with BRAF mutations showed a 1.59-fold higher risk of events or a 2.66-fold higher risk of death than patients with papillary thyroid cancer without a BRAF mutation. Also, patients with RAS mutations showed a 2.90-fold higher risk of death by thyroid cancer than patients without a RAS mutation. In addition, patients with medullary thyroid cancer with RET mutations showed a 5.82-fold higher risk of death by the disease than without a RET mutation.

Conclusions:

Genetic mutations should be considered as a poor prognostic marker in thyroid cancer and may lead to better management of individual patients. However, the use of genetic mutations as prognostic markers should not be generalized, but individualized in the specific clinic setting.

Introduction

Thyroid cancer is the most common endocrine cancer, and its incidence has increased continuously over the last three decades worldwide, including in Korea (1,2). Although thyroid cancer is perceived to have a high survival rate, the sustained increase in thyroid carcinoma incidence worldwide has recently attracted considerable attention. Despite the good prognosis, a minority of patients show recurrence and distant metastasis (3). Therefore, thyroid cancer care places an inevitable demand on social health care resources, as well as an economic burden. Therefore, identifying the tumors that pose the greatest risk to patients is a high priority.

Thyroid carcinomas commonly contain one of a small number of recurrent genetic mutations (4). Previous studies revealed the pathogenetic, diagnostic, prognostic, and therapeutic roles of these mutations in thyroid tumors. These mutations have emerged as promising prognostic factors for thyroid cancer. Much effort has focused on identifying the association between genetic mutations and the outcome of thyroid cancer. However, the clinical significance of mutations as potential prognostic markers in papillary thyroid cancer (PTC) remains controversial, and scientific debate is ongoing (5). Previous meta-analyses (6 –8) revealed an association between BRAF mutations and the clinical outcome of PTC. However, these studies have several limitations, and no studies regarding the prognostic value of RAS and RET mutations have been performed. Therefore, we performed a meta-analysis to assess the prognostic value of the three most common genetic mutations (BRAF, RAS, and RET) in patients with thyroid cancer.

Materials and Methods

Data search and study selection

We performed a systematic search of MEDLINE (from inception to December 2013) and EMBASE (from inception to December 2013) for English-language publications using the keywords “thyroid,” “BRAF,” “RAS,” “RET,” and “prognosis.” All searches were limited to human studies. The inclusion criteria were studies of thyroid cancer that reported the results of genetic mutations and survival data. Reviews, abstracts, and editorial materials were excluded, and duplicate data were removed. If there was more than one study from the same center, the report with the information most relevant to this study was included. Two authors performed the searches and screening independently, and discrepancies were resolved by consensus.

Data extraction and statistical analysis

Data were extracted from the publications independently by two reviewers, and the following information was recorded: first author, year of publication, country, genetic mutation analyzed, number of patients, staging, mutation rate, and end points. The primary outcome was event-free survival (EFS). Data regarding disease-free survival (DFS), recurrence-free survival (RFS), disease-free interval (DFI), and progression-free survival (PFS) were obtained from the included studies, and were redefined as EFS, which was measured from the date of initiation of therapy to the date of recurrence or metastasis (9). The secondary end point was disease-specific survival (DSS), which included tumor-specific survival (TSS), cause-specific survival (CSS), papillary thyroid cancer-related mortality (PRM), survival from cancer (SFC), death from thyroid cancer (DFT), and tumor-related death (TRD). Only deaths from disease were included in DSS. The tertiary outcome was overall survival (OS), which was defined as the time from the initiation of therapy until death from any cause.

The effects of genetic mutations on survival were assessed using hazard ratios (HRs). Survival data were extracted following a methodology suggested previously (10). A univariate HR estimate and 95% confidence intervals (CIs) were extracted directly from each study, if provided by the authors. Otherwise, p values of the log-rank tests, 95% confidence intervals, numbers of events, and numbers of patients at risk were extracted to estimate the HR indirectly. Survival rates calculated from Kaplan-Meier curves were read using Engauge Digitizer version 3.0 (http://digitizer.sourceforge.net) to reconstruct the HR estimate and its variance, assuming that patients were censored at a constant rate during follow-up. An HR>1 implied worse survival for patients with genetic mutations, whereas an HR<1 implied a survival benefit for patients with genetic mutations. Heterogeneity among studies was assessed using χ² tests and I² statistics, as described previously (11). Funnel plots were used to assess publication bias (12). p values<0.05 were considered to be statistically significant. The data from each study were analyzed using Review Manager (RevMan, Version 5.2, Copenhagen: The Nordic Cochrane Centre, The Cochrane Collaboration, 2012).

Results

Study characteristics

The electronic search identified 2,128 articles. Non-English–language articles (n=172), conference abstracts (n=687), and 846 studies that did not meet the inclusion criteria based on their title and abstract were excluded. After reviewing the full text of 102 articles, 25 studies including 5,854 patients were eligible for inclusion in the study. The detailed procedure is shown in Figure 1.

FIG. 1.

Flowchart of the study selection process.

Fourteen studies assessing BRAF mutations (13 –26) six with RAS mutations (27 –32), four analyzing somatic RET mutations (33 –36), and one reporting both BRAF and RAS mutations (37) were included in the meta-analysis. The prognostic value of BRAF mutations was assessed by analyzing DSS in 2,913 patients and EFS in 2,264. The prognostic potential of RAS mutations was analyzed according to DSS, EFS, and OS in 294, 173, and 131 patients, respectively. The prognostic value of RET mutations was assessed according to DSS in 300 individuals. The percentage of patients with the mutation in each study ranged from 36.7–73.4 for BRAF, 14.3–56.9 for RAS, and 16.0–61.8 for RET. All studies of BRAF mutations included patients with PTC (13 –26,37). Patients with MTC were included in three of four studies analyzing RET mutations (33,34,36). Visual inspection of the funnel plot suggested no evidence of publication bias. The study characteristics are summarized in Table 1.

Table 1.

Studies Included in Meta-Analysis

First author	Year of publication	Country	Genetic alterations	No. of patients	Stage	Mutation (%)	PTC (%)	Follow-up (months)	End points
Kim TY (13)	2006	Korea	BRAF	203	I–IV	73.4	100	87.6^a	DFS
Abubaker J (14)	2008	Saudi Arabia	BRAF	296	I–IV	51.7	100	—	DFS
Costa AM (37)	2008	Spain	BRAF	48	I–IV	56.3	100	131^b	RFS, DSS
			RAS	48	I–IV	14.6	100	131^b	RFS
Ito Y (20)	2009	Japan	BRAF	624	I–IV	61.5	100	83^a	DFS
Czarniecka A (16)	2010	Poland	BRAF	88	—	43.2	100	48^a	DFS
O'Neill CJ (23)	2010	Australia	BRAF	95	I–IV	57.9	100	106^a	DFS
Guerra A (18)	2012	Italy	BRAF	168	I–IV	36.9	100	61.2^a	DFS
Prescott JD (24)	2012	USA	BRAF	205	I–IV	53.6	100	—	RFS
Ulisse S (25)	2012	Italy	BRAF	75	I–IV	46.7	100	19^a	DFI
Alzahrani AS (15)	2013	USA	BRAF	115	I–IV	40.9	100	35^a	RFS
Fernandez IJ (17)	2013	Italy	BRAF	297	I–IV	58.2	100	49.8^a	RFS
McKelvie PA (21)	2013	Australia	BRAF	50	I–IV	66.0	100	100^a	PFS
Musholt TJ (22)	2010	Germany	BRAF	280	I–IV	42.1	100	66^a	TSS
Ito Y (19)	2013	Japan	BRAF	736	I–IV	36.7	100	130^b	CSS
Xing M (26)	2013	USA	BRAF	1,849	I–III	45.7	100	33^a	PRM
Hara H (30)	1994	USA	RAS	91	I–IV	14.3	100	169.2^b	SFC
Akslen LA (27)	1995	Norway	RAS	125	—	52.8	100	137^a	RFS, DFT
Garcia-Rostan G (29)	2003	USA	RAS	78	I–IV	25.6	56.4	84^a	DSS
Pinto AE (31)	2008	Portugal	RAS	20	IV	15.0	0 (PDTC and ATC 100)	10^a	OS
Volante M (32)	2009	Italy	RAS	53	—	26.4	0 (PDTC 100)	52^b	OS
Fukahori M (28)	2012	Japan	RAS	58	—	56.9	0 (FTC 100)	96^a	OS
Musholt TG (35)	2000	Germany	RET	106	—	16.0	100	68.4^b	TRD
Schilling T (36)	2001	Germany	RET	34	II–IV	61.8	0 (MTC 100)	—	DSS
Elisei R (33)	2008	Italy	RET	100	I–IV	43.0	0 (MTC 100)	10^a	DSS
Mian C (34)	2011	Italy	RET	60	I–IV	38.3	0 (MTC 100)	39^a	DSS

Follow-up; ^amedian, ^bmean.

PRM, papillary thyroid cancer-related mortality; TSS, tumor-specific survival; CSS, cause-specific survival; PFS, progression free survival; DFI, disease-free interval; DSS, disease-specific survival; DSD, disease-specific death; SFC, survival from cancer; DFT, death from thyroid cancer; TRD, tumor-related death; PDTC, poorly differentiated thyroid cancer; ATC, anaplastic thyroid cancer; MTC, medullary thyroid cancer.

BRAF mutations

All patients included in the meta-analysis of BRAF mutations had PTC. EFS was analyzed based on 12 studies (13 –18,20,21,23 –25,37). The pooled HR for adverse events was 1.59 (95% confidence interval [CI] 1.24–2.04, p=0.0002), and the test for heterogeneity gave no significant results (χ²=14.49, p=0.21; I²=24%). Subgroup meta-analyses were assessed according to region (European, Korea/Japan, United States, and others), number of patients (<100, ≥100, <200, and ≥200), patient age (<45 and ≥45 years), the prevalence of BRAF mutations (<50 and ≥50%), and follow-up period (<60 and ≥60 months) (Table 2). Studies with a BRAF mutation rate <50% had a HR of 1.81 (1.12–2.93, p=0.02), whereas those with a BRAF mutation rate ≥50% had a HR of 1.52 (1.14–2.03, p=0.004). The effect sizes of HRs were similar among the subgroups analyzed. DSS was analyzed based on four studies (19,22,26,37), and the combined HR for deaths from thyroid cancer was 2.66 (1.34–5.27, p=0.005). The forest plots for EFS and DSS are shown in Figure 2.

FIG. 2.

Forest plots of the hazard ratios for events (A) and deaths (B) in patients with the BRAF mutation.

Table 2.

Subgroup Analyses: BRAF Mutation–EFS

Factor	No. of studies	HR	95% CI of HR	Heterogeneity I² (%)	Model used
Country
Europe	5	1.77	1.15–2.70	38	Fixed effect
Korea/Japan	2	1.47	0.69–3.13	56	Random effects
USA	2	2.41	1.40–4.15	0	Fixed effect
Others	3	1.01	0.59–1.72	0	Fixed effect
No. of patients
<100	5	1.22	0.73–2.04	2	Fixed effect
≥100, <200	2	1.71	1.05–2.79	0	Fixed effect
≥200	5	1.83	1.12–3.01	50.2	Random effects
Age (years)
<45	6	1.83	1.31–2.57	0	Fixed effect
≥45	6	1.36	0.95–1.94	43	Fixed effect
BRAF mutation rate (%)
<50	3	1.81	1.12–2.93	16	Fixed effect
≥50	9	1.52	1.14–2.03	32	Fixed effect
Follow-up (months)
<60	4	2.22	1.35–3.66	45	Fixed effect
≥60	6	1.35	0.96–1.88	0	Fixed effect

EFS, event-free survival; HR, hazard ratio; CI, confidence interval.

RAS mutations

Two studies (27,37) analyzed EFS in 173 patients, and three studies (28,31,32) containing 131 patients that reported OS were included to calculate the combined HRs. However, RAS mutations were not associated with an increased risk of events (HR 1.80; 0.95–3.43, p=0.07) or a higher risk of death from any cause (HR 2.18; 0.45–10.64, p=0.33). To measure the HR of DSS, three studies containing 294 patients were included (27,29,30). The combined HR of deaths from thyroid cancer was 2.90 (1.66–5.07, p=0.0002). The forest plots for EFS, OS, and DSS are shown in Figure 3.

FIG. 3.

Forest plots of hazard ratios for events (A), deaths by any cause (B), and deaths from thyroid cancer (C) in patients with RAS mutations.

RET mutations

DSS was analyzed based on four studies including 300 patients (33 –36). After excluding one study of patients with PTC (35), three studies analyzing MTC showed a combined HR of 5.82 (2.53–13.38, p<0.0001). The forest plot for DSS is presented in Figure 4.

FIG. 4.

Forest plots of the hazard ratio for death from thyroid cancer in patients with RET mutations.

Discussion

This meta-analysis evaluated the prognostic value of genetic mutations in patients with thyroid cancer. In combined results, PTC patients with BRAF mutations had a 1.59-fold higher risk of events and a 2.66-fold higher risk of death than those without BRAF mutations. In addition, patients with RAS mutations had a 2.90-fold higher risk of thyroid cancer-related death than those without a RAS mutation. Finally, MTC patients with RET mutations had a 5.82-fold higher risk of death due to the disease compared with patients without RET mutations.

The present study is consistent with recent meta-analyses reporting that BRAF mutations are closely related to the presence of high-risk clinicopathologic factors and poorer outcome in patients with PTC (6 –8). Our results are compatible with a clinical study reporting that preoperative knowledge of BRAF mutations might alter the initial PTC surgical management strategy, and also prevent the increased rate of morbidity that has been associated with preoperative neck exploration (38). An explanation for the role of BRAF mutations in PTC-related mortality lies in the molecular mechanisms by which BRAF mutations promote the aggressive pathogenesis of thyroid cancer. For example, BRAF mutations cause the dedifferentiation of PTC, resulting in the loss of expression of the thyroidal genes that regulate thyroid iodide concentration and hence the failure of radioiodine treatment (7,39). BRAF mutations also strongly upregulate several classic angiogenic and tumor-promoting molecules, and are associated with the hypermethylation and inactivation of tumor suppressor genes (7,39). It is likely that, through these unique molecular mechanisms, BRAF mutations promote aggressive tumor behavior such as lymph node metastasis (LNM), tumor invasion, distant metastasis, silencing of thyroidal genes involved in iodide handling thereby rendering tumors resistant to radioiodine treatment, and expedite tumor progression. In combination, these effects increase the risk of PTC-related mortality. However, the presence of a BRAF mutation cannot be interpreted independent of tumor behaviors that can affect patient mortality. In fact, when Xing et al. (26) adjusted for these tumor behaviors, the association of outcomes with the presence of a BRAF mutation was no longer statistically significant. These results from Xing et al. (26) are consistent with another study (20) demonstrating that the presence of a BRAF mutation has a significant impact on PTC-related deaths in high-risk categories.

The current study also reveals that patients with RAS mutations had a 2.90-fold higher risk of death due to thyroid cancer. Constitutively activating RAS mutations are probably the most common mutations in cancer biology (4). Previous studies revealed correlations between RAS mutations and bone metastases, increased aggressiveness, and higher mortality in all types of thyroid cancer (27,29,30,40). A retrospective study also found that RAS mutations are overrepresented in differentiated thyroid carcinomas in patients with radioiodine-avid pulmonary metastases (41). Radioiodine-avid lung metastases are rarely cured by radioiodine therapy, resulting in a impaired prognosis. PTCs usually contain an activating mutation in the RAS/MAPK cascade: most commonly in BRAF, and less frequently in RAS. A recent study (42) reported that the rapid increase in thyroid cancer incidence over the last four decades was accompanied by an increased frequency of BRAF mutations and a marked increase in RAS mutations. Consistent with this finding, we confirm the prognostic value of BRAF and RAS mutations in patients with PTC. The current study is the first meta-analysis of the prognostic value of RAS mutations in thyroid carcinoma. The association of BRAF and RAS in thyroid cancer combined with the diverse effects of BRAF/RAS presents many potential therapeutic targets.

The current meta-analysis also found that MTC patients with RET mutations had a 5.82-fold higher risk of death. RET is a cell–surface receptor tyrosine kinase that transmits environmental cues to RAS and the downstream MAPK pathway. RET itself is not expressed in normal thyroid follicular cells, but the juxtaposition of the two kinase domains of RET and its promoter leads to the expression of a fusion oncoprotein and aberrant kinase activity (4). The biologic behavior of MTC is much less favorable compared with other well-differentiated thyroid carcinomas (43). Currently, the only effective clinical tools for gauging the progressive or stable nature of an MTC tumor are the calcitonin and carcinoembryonic antigen doubling times during follow-up (43). Previous studies demonstrated that RET gene mutations, which are present in approximately 40–50% of MTC tumors, are a poor prognostic factor for the outcome of MTC patients (33,34,36). However, this observation was not confirmed by several other reports (44,45). These analyses were performed in small MTC series with short-term follow-ups. In addition, the data were not always homogeneous in terms of the frequency, type, and site of the somatic RET gene mutation, or their association with clinical and pathologic features. Our data confirm that somatic RET mutations are molecular markers of more aggressive MTC subtypes. This might facilitate the planning of appropriate surgical interventions, determination of the extent of surgery, and tailored patient follow-up from the beginning of treatment.

The major strength of this study consists in the fact that it is the largest meta-analysis performed to date that includes the most recent studies. We analyzed the association of the three most common genetic mutations and with the prognosis (EFS, DSS, and OS) of thyroid cancer patients, but not with clinico-pathological features. Six previous meta-analyses were identified by searching the electronic MEDLINE and EMBASE databases (Table 3). Each study analyzed the effect size of risk ratios (RRs) or odds ratios (ORs). However, because RRs or ORs are measured at a single point in time, they are not recommended as surrogate methods for analyzing time-to-event outcomes (46); instead, HR is the most appropriate measurement. Therefore, we calculated HRs as the effect size in the current study. Nevertheless, this study also has several limitations. Because we were unable to access individual patient data, there is a risk of bias. Studies with different treatments, follow-up periods, and surveillance protocols were included in this study, which is a weakness for meta-analysis. Although funnel plots did not reveal clear evidence of publication bias, it could not be excluded. In addition, even though two reviewers read survival curves independently, this strategy could not ensure complete accuracy of the extracted data. Finally, although we included studies of RAS mutations, we were unable to subanalyze these according to RAS isoforms due to the insufficient number of studies.

Table 3.

Previous Meta-Analyses

								Results
First author	Year of publication	Country	Histology	Genetic mutations	No. of studies	No. of patients	Mutation (%)	Associated with	Not associated with	Effect size
Tufano RP (4)	2012	USA	PTC	BRAF	14	2,470	45.3	Recurrence, LN metastasis, EE, advanced stage	Distant metastasis	risk ratio
Xing M (39)	2007	USA	PTC	BRAF	28	3,028	50	Recurrence, LN metastasis, EE, advanced stage		odds ratio
Li C (6)	2012	USA	PTC	BRAF	32	6,372	50.9	LN metastasis, EE, advanced stage, tumor size, sex, multifocality, absence of capsule, histologic subtype	Age, vascular invasion	odds ratio
Lee JH (1)	2007	Korea	PTC	BRAF	12	1,168	48.8	EE, advanced stage, histologic subtype,	Age, sex, race, tumor size	odds ratio
Liu X (39)	2014	China	PTC	BRAF	69	14,170	56.3	Recurrence, LN metastasis, EE, advanced stage, multifocality	Age, distant metastasis	odds ratio
Kim TH (7)	2012	Korea	PTC	BRAF	27	5,655	49.4	Recurrence, EE, LN metastasis, advanced stage		odds ratio, risk ratio

PTC, papillary thyroid cancer; LN, lymph node; EE, extrathyroidal extension.

Cancer is a disease of accumulated DNA damage the progression of which is in part driven by the acquisition of additional genetic abnormalities. Understanding how these changes contribute to the disease process is essential for the development of novel prognostic and therapeutic strategies. Targeting these recurrent mutations singly can result in transient relief from disease progression. Combination therapies that address a more comprehensive catalogue of driving mutations might achieve more durable responses, and perhaps cures. Finally, the epigenetic control of the tumor genome is also an attractive target for reversal of disease progression. In conclusion, genetic mutations should be considered to be poor prognostic markers in thyroid cancer; such knowledge might improve the management of individual patients. However, the use of a BRAF mutation or other mutations as prognostic markers should not be generalized, but individualized in the specific clinic setting. Further studies of risk assessment establishing strategies for aggressive postoperative therapies and follow-up are needed.

Footnotes

Author Disclosure Statement

The authors declare no conflict of interest.

References

Lee

, Lee

, Kim

. 2007. Clinicopathologic significance of BRAF V600E mutation in papillary carcinomas of the thyroid: a meta-analysis. Cancer, 110:38–46.

Ciampi

, Mian

, Fugazzola

, Cosci

, Romei

, Barollo

, Cirello

, Bottici

, Marconcini

, Rosa

, Borrello

, Basolo

, Ugolini

, Materazzi

, Pinchera

, Elisei

. 2013. Evidence of a low prevalence of RAS mutations in a large medullary thyroid cancer series. Thyroid, 23:50–57.

Schlumberger

. 1998. Papillary and follicular thyroid carcinoma. N Engl J Med, 338:297–306.

Tufano

, Teixeira

, Bishop

, Carson

, Xing

. 2012. BRAF mutation in papillary thyroid cancer and its value in tailoring initial treatment: a systematic review and meta-analysis. Medicine (Baltimore), 91:274–286.

Melloni

, Gajate

, Sestini

, Gallivanone

, Bandiera

, Landoni

, Muriana

, Gianolli

, Zannini

. 2013. New positron emission tomography derived parameters as predictive factors for recurrence in resected stage I non-small cell lung cancer. Eur J Surg Oncol, 39:1254–1261.

, Lee

, Schneider

, Zeiger

. 2012. BRAF V600E mutation and its association with clinicopathological features of papillary thyroid cancer: a meta-analysis. J Clin Endocrinol Metab, 97:4559–4570.

Kim

, Park

, Lim

, Ahn

, Lee

, Kim

, Hahn

, Youn

, Kim

, Cho

, Park do

. 2012. The association of the BRAF(V600E) mutation with prognostic factors and poor clinical outcome in papillary thyroid cancer: a meta-analysis. Cancer, 118:1764–1773.

Liu

, Yan

, Lin

, Zhao

, An

, Wang

, Liu

. 2014. The association between BRAF mutation and pathological features in PTC. Eur Arch Otorhinolaryngol, 271:3041–3052.

Zhao

, Feng

, Mao

, Qie

. 2013. Prognostic value of fluorine-18-fluorodeoxyglucose positron emission tomography or PET-computed tomography in cervical cancer: a meta-analysis. Int J Gynecol Cancer, 23:1184–1190.

10.

Parmar

, Torri

, Stewart

. 1998. Extracting summary statistics to perform meta-analyses of the published literature for survival endpoints. Stat Med, 17:2815–2834.

11.

Higgins

, Thompson

, Deeks

, Altman

. 2003. Measuring inconsistency in meta-analyses. BMJ, 327:557–560.

12.

Egger

, Davey Smith

, Schneider

, Minder

. 1997. Bias in meta-analysis detected by a simple, graphical test. BMJ, 315:629–634.

13.

Kim

, Kim

, Rhee

, Song

, Kim

, Gong

, Lee

, Kim

, Hong

, Shong

. 2006. The BRAF mutation is useful for prediction of clinical recurrence in low-risk patients with conventional papillary thyroid carcinoma. Clin Endocrinol, 65:364–368.

14.

Abubaker

, Jehan

, Bavi

, Sultana

, Al-Harbi

, Ibrahim

, Al-Nuaim

, Ahmed

, Amin

, Al-Fehaily

, Al-Sanea

, Al-Dayel

, Uddin

, Al-Kuraya

. 2008. Clinicopathological analysis of papillary thyroid cancer with PIK3CA alterations in a Middle Eastern population. J Clin Endocrinol Metab, 93:611–618.

15.

Alzahrani

, Xing

. 2013. Impact of lymph node metastases identified on central neck dissection (CND) on the recurrence of papillary thyroid cancer: potential role of BRAFV600E mutation in defining CND. Endocr Relat Cancer, 20:13–22.

16.

Czarniecka

, Rusinek

, Stobiecka

, Krajewska

, Kowal

, Kropinska

, Zebracka

, Kowalska

, Wloch

, Maciejewski

, Handkiewicz-Junak

. 2010. Occurrence of BRAF mutations in a Polish cohort of PTC patients—preliminary results. Endokrynol Pol, 61:462–466.

17.

Fernandez

, Piccin

, Sciascia

, Cavicchi

, Repaci

, Vicennati

, Fiorentino

. 2013. Clinical significance of BRAF mutation in thyroid papillary cancer. Otolaryngol Head Neck Surg, 148:919–925.

18.

Guerra

, Fugazzola

, Marotta

, Cirillo

, Rossi

, Cirello

, Forno

, Moccia

, Budillon

, Vitale

. 2012. A high percentage of BRAFV600E alleles in papillary thyroid carcinoma predicts a poorer outcome. The Journal of clinical endocrinology and metabolism, 97:2333–2340.

19.

Ito

, Yoshida

, Kihara

, Kobayashi

, Miya

, Miyauchi

. 2013. BRAF mutation analysis in papillary thyroid carcinoma: is it useful for all patients?. World J Surg, 38:679–687.

20.

Ito

, Yoshida

, Maruo

, Morita

, Takano

, Hirokawa

, Yabuta

, Fukushima

, Inoue

, Tomoda

, Kihara

, Uruno

, Higashiyama

, Takamura

, Miya

, Kobayashi

, Matsuzuka

, Miyauchi

. 2009. BRAF mutation in papillary thyroid carcinoma in a Japanese population: its lack of correlation with high-risk clinicopathological features and disease-free survival of patients. Endocr J, 56:89–97.

21.

McKelvie

, Chan

, Yu

, Waring

, Gresshoff

, Farrell

, Williams

. 2013. The prognostic significance of the BRAF V600E mutation in papillary thyroid carcinoma detected by mutation-specific immunohistochemistry. Pathology, 45:637–644.

22.

Musholt

, Schonefeld

, Schwarz

, Watzka

, Musholt

, Fottner

, Weber

, Springer

, Schad

. 2010. Impact of pathognomonic genetic alterations on the prognosis of papillary thyroid carcinoma. ESES vienna presentation. Langenbecks Arch Surg, 395:877–883.

23.

O'Neill

, Bullock

, Chou

, Sidhu

, Delbridge

, Robinson

, Gill

, Learoyd

, Clifton-Bligh

, Sywak

. 2010. BRAF(V600E) mutation is associated with an increased risk of nodal recurrence requiring reoperative surgery in patients with papillary thyroid cancer. Surgery, 148:1139–1145; discussion 1145–1136.

24.

Prescott

, Sadow

, Hodin

, Le

, Gaz

, Randolph

, Stephen

, Parangi

, Daniels

, Lubitz

. 2012. BRAF V600E status adds incremental value to current risk classification systems in predicting papillary thyroid carcinoma recurrence. Surgery, 152:984–990.

25.

Ulisse

, Baldini

, Sorrenti

, Barollo

, Prinzi

, Catania

, Nesca

, Gnessi

, Pelizzo

, Mian

, De Vito

, Calvanese

, Palermo

, Persechino

, De Antoni

, D'Armiento

. 2012. In papillary thyroid carcinoma BRAFV600E is associated with increased expression of the urokinase plasminogen activator and its cognate receptor, but not with disease-free interval. Clin Endocrinol, 77:780–786.

26.

Xing

, Alzahrani

, Carson

, Viola

, Elisei

, Bendlova

, Yip

, Mian

, Vianello

, Tuttle

, Robenshtok

, Fagin

, Puxeddu

, Fugazzola

, Czarniecka

, Jarzab

, O'Neill

, Sywak

, Lam

, Riesco-Eizaguirre

, Santisteban

, Nakayama

, Tufano

, Pai

, Zeiger

, Westra

, Clark

, Clifton-Bligh

, Sidransky

, Ladenson

, Sykorova

. 2013. Association between BRAF V600E mutation and mortality in patients with papillary thyroid cancer. JAMA, 309:1493–1501.

27.

Akslen

, Varhaug

. 1995. Oncoproteins and tumor progression in papillary thyroid carcinoma: presence of epidermal growth factor receptor, c-erbB-2 protein, estrogen receptor related protein, p21-ras protein, and proliferation indicators in relation to tumor recurrences and patient survival. Cancer, 76:1643–1654.

28.

Fukahori

, Yoshida

, Hayashi

, Yoshihara

, Matsukuma

, Sakuma

, Koizume

, Okamoto

, Kondo

, Masuda

, Miyagi

. 2012. The associations between RAS mutations and clinical characteristics in follicular thyroid tumors: new insights from a single center and a large patient cohort. Thyroid, 22:683–689.

29.

Garcia-Rostan

, Zhao

, Camp

, Pollan

, Herrero

, Pardo

, Wu

, Carcangiu

, Costa

, Tallini

. 2003. ras mutations are associated with aggressive tumor phenotypes and poor prognosis in thyroid cancer. J Clin Oncol, 21:3226–3235.

30.

Hara

, Fulton

, Yashiro

, Ito

, DeGroot

, Kaplan

. 1994. N-ras mutation: an independent prognostic factor for aggressiveness of papillary thyroid carcinoma. Surgery, 116:1010–1016.

31.

Pinto

, Silva

, Banito

, Leite

, Soares

. 2008. Aneuploidy and high S-phase as biomarkers of poor clinical outcome in poorly differentiated and anaplastic thyroid carcinoma. Oncology reports, 20:913–919.

32.

Volante

, Rapa

, Gandhi

, Bussolati

, Giachino

, Papotti

, Nikiforov

. 2009. RAS mutations are the predominant molecular alteration in poorly differentiated thyroid carcinomas and bear prognostic impact. J Clin Endocrinol Metab, 94:4735–4741.

33.

Elisei

, Cosci

, Romei

, Bottici

, Renzini

, Molinaro

, Agate

, Vivaldi

, Faviana

, Basolo

, Miccoli

, Berti

, Pacini

, Pinchera

. 2008. Prognostic significance of somatic RET oncogene mutations in sporadic medullary thyroid cancer: a 10-year follow-up study. J Clin Endocrinol Metab, 93:682–687.

34.

Mian

, Pennelli

, Barollo

, Cavedon

, Nacamulli

, Vianello

, Negro

, Pozza

, Boschin

, Pelizzo

, Rugge

, Mantero

, Girelli

, Opocher

. 2011. Combined RET and Ki-67 assessment in sporadic medullary thyroid carcinoma: a useful tool for patient risk stratification. Eur J Endocrinol, 164:971–976.

35.

Musholt

, Musholt

, Khaladj

, Schulz

, Scheumann

, Klempnauer

. 2000. Prognostic significance of RET and NTRK1 rearrangements in sporadic papillary thyroid carcinoma. Surgery, 128:984–993.

36.

Schilling

, Burck

, Sinn

, Clemens

, Otto

, Hoppner

, Herfarth

, Ziegler

, Schwab

, Raue

. 2001. Prognostic value of codon 918 (ATG–>ACG) RET proto-oncogene mutations in sporadic medullary thyroid carcinoma. Int J Cancer, 95:62–66.

37.

Costa

, Herrero

, Fresno

, Heymann

, Alvarez

, Cameselle-Teijeiro

, Garcia-Rostan

. 2008. BRAF mutation associated with other genetic events identifies a subset of aggressive papillary thyroid carcinoma. Clin Endocrinol, 68:618–634.

38.

Yip

, Nikiforova

, Carty

, Yim

, Stang

, Tublin

, Lebeau

, Hodak

, Ogilvie

, Nikiforov

. 2009. Optimizing surgical treatment of papillary thyroid carcinoma associated with BRAF mutation. Surgery, 146:1215–1223.

39.

Xing

. 2007. BRAF mutation in papillary thyroid cancer: pathogenic role, molecular bases, and clinical implications. Endocr Rev, 28:742–762.

40.

Davison

, Mercier

, Russo

, Subramaniam

. 2013. PET-based primary tumor volumetric parameters and survival of patients with non-small cell lung carcinoma. AJR Am J Roentgenol, 200:635–640.

41.

Sabra

, Dominguez

, Grewal

, Larson

, Ghossein

, Tuttle

, Fagin

. 2013. Clinical outcomes and molecular profile of differentiated thyroid cancers with radioiodine-avid distant metastases. J Clin Endocrinol Metab, 98:E829–836.

42.

Hyun

, Ahn

, Kim

, Ahn

, Park

, Ahn

, Kim

, Shim

, Choi

. 2014. Volume-based assessment by (18)F-FDG PET/CT predicts survival in patients with stage III non-small-cell lung cancer. Eur J Nucl Med Mol Imag, 41:50–58.

43.

American Thyroid Association Guidelines Task F, Kloos

, Eng

, Evans

, Francis

, Gagel

, Gharib

, Moley

, Pacini

, Ringel

, Schlumberger

, Wells

Jr . 2009. Medullary thyroid cancer: management guidelines of the American Thyroid Association. Thyroid, 19:565–612.

44.

Dvorakova

, Vaclavikova

, Sykorova

, Vcelak

, Novak

, Duskova

, Ryska

, Laco

, Cap

, Kodetova

, Kodet

, Krskova

, Vlcek

, Astl

, Vesely

, Bendlova

. 2008. Somatic mutations in the RET proto-oncogene in sporadic medullary thyroid carcinomas. Mol Cell Endocrinol, 284:21–27.

45.

Uchino

, Noguchi

, Adachi

, Sato

, Yamashita

, Watanabe

, Murakami

, Toda

, Murakami

, Yamashita

. 1998. Novel point mutations and allele loss at the RET locus in sporadic medullary thyroid carcinomas. Jpn J Cancer Res, 89:411–418.

46.

Michiels

, Piedbois

, Burdett

, Syz

, Stewart

, Pignon

. 2005. Meta-analysis when only the median survival times are known: a comparison with individual patient data results. Int J Technol Assess Health Care, 21:119–125.