Differentiated thyroid cancer: Clinicopathologic staging

INTRODUCTION — Clinicopathologic staging of patients with cancer is valuable for many reasons, including the following [1]:

●To estimate risk of recurrence and disease-specific mortality for an individual patient

●To tailor decisions regarding postoperative adjunctive therapy (such as the need for radioiodine [RAI] ablation and degree of thyroid-stimulating hormone [TSH] suppression) to the patient's risk for disease recurrence and mortality

●To make decisions regarding the frequency, modality, and intensity of follow-up based upon an individual patient's risk of recurrence and mortality

●To enable accurate communication regarding a patient among health care professionals

●To allow evaluation of differing therapeutic strategies applied to comparable groups of patients in clinical studies

●To provide "a method of conveying clinical experience to others without ambiguity" [2]

The clinicopathologic staging of differentiated thyroid cancer will be discussed here. The management of differentiated thyroid cancer is reviewed separately. (See "Differentiated thyroid cancer: Overview of management".)

STAGING FOR DIFFERENTIATED THYROID CANCER

●Initial postoperative staging – In our practice, we use the tumor, node, metastasis (TNM) (table 1) or Metastases, Age, Completeness of Resection, Invasion, Size (MACIS) staging systems to estimate disease-specific mortality and then an additional clinicopathologic staging system, such as the American Thyroid Association (ATA) system, to estimate the risk of recurrence (table 2) [3-5].

●Restaging during follow-up – These initial risk assessments are then actively modified based upon data obtained during follow-up that reflect the individualized patient's response to therapy [4,6]. This dynamic risk assessment approach allows for more accurate risk assessments than either a static estimate of risk based on the TNM staging system or the ATA risk of recurrence classification system [4].

The ATA recommends the TNM staging system (table 1) for all patients with differentiated thyroid cancer and any of the postoperative clinicopathologic staging systems to achieve more accurate risk factor stratification [5]. It should be recognized, however, that no staging system reliably predicts outcome in individual patients; as a result, clinicians should use individual clinicopathologic characteristics to determine the specific treatment for a given patient.

It is important to note that the initial stage assigned to a patient is based upon information available in the first few weeks to months after diagnosis. The eighth edition of the American Joint Committee on Cancer (AJCC)/TNM staging system specifically allows all data collected within the first four months after surgery to be used as part of the initial AJCC staging for each patient [7]. In practical terms, this initial stage assignment does not change over time. In contrast, the estimates of the risk of recurrence and death usually do change over time depending upon how well the patient responds to initial therapy (surgery with or without radioiodine [RAI] ablation). As an example, patients who have had an excellent response to initial therapies would be considered to be at much lower risk for recurrence and death from disease than may have been predicted based on initial staging. Conversely, patients with an incomplete response to therapy may be at a higher risk of clinically significant disease recurrence or death than would have been predicted based on initial staging factors. Thus, we restratify patients on each follow-up visit using a reclassification system that emphasizes the response to therapy for each individual patient. (See 'Dynamic risk stratification' below.)

Staging systems for predicting disease-specific mortality — Given their relative ease of use and widespread acceptance, we prefer the TNM or MACIS staging systems to estimate disease-specific mortality. (See 'TNM system' below and 'MACIS system' below.)

In differentiated thyroid cancer, there are several staging systems for estimating disease-specific mortality (table 3). Each of the staging systems tend to use a core set of data that usually includes age at diagnosis, size of the primary tumor, extent of local extrathyroidal extension, and the presence/absence of distant metastases. The estimated mortality rates reflect both the predictive accuracy of the staging system and the variations in therapy at different institutions. There are sufficient differences among the staging systems such that practitioners using different schema cannot be assured that they are classifying patients in a similar fashion.

Application of several different staging systems to 1225 patients with differentiated thyroid cancer treated with total thyroidectomy and radioiodine (131-I) therapy revealed that the TNM system was best for separating groups of patients with distinctly different survival curves [8]. Even so, none of the static initial staging systems were able to explain more than a small proportion of the variance in mortality in the patient population, while the dynamic risk staging systems that incorporate response to therapy variables into an active ongoing risk stratification system account for a much higher proportion of variance. (See 'Dynamic risk stratification' below.)

The more commonly used staging systems for predicting disease-specific mortality are reviewed below.

TNM system — The Union for International Cancer Control (UICC) and the AJCC have adopted the eighth (2017) tumor, node, metastasis (TNM) classification system, which took effect globally on January 1, 2018 (table 1) [2]. The TNM system is optimized to predict survival in patients with thyroid cancer, based primarily on pathologic findings accumulated preoperatively, intraoperatively, and during the first four months after thyroid surgery [9].

The updated 2017 TNM staging system is notable for the following changes [9,10]:

●The age at diagnosis cutoff for prognostic staging was raised from 45 to 55 years of age. Mortality from thyroid cancer increases progressively with advancing age starting at approximately age 35 years. While previous editions of the TNM staging system used 45 years of age as a discrete point to differentiate patients at higher risk for dying from thyroid cancer from lower risk patients, the 2017 TNM staging system increased the age cutoff to 55 years.

●Regional lymph node metastases and microscopic extrathyroidal extension were removed from the definition of T3 disease.

●T3a is a new category for tumors >4 cm confined to the thyroid gland.

●T3b is a new category for tumors of any size demonstrating gross extrathyroidal extension into strap muscles.

●Level VII lymph nodes, previously classified as lateral neck lymph nodes (N1b) were reclassified as central neck lymph nodes (N1a) to be more anatomically consistent and to facilitate uniform coding for tumor registrars, clinicians, and researchers.

●The presence of distant metastases in older patients is classified as IVB, rather than IVC disease.

Compared with the seventh edition, the changes implemented in the eighth edition downstage many patients into lower stages, more accurately reflecting their lower risk of thyroid cancer mortality [11-13]. The updated system classifies fewer patients as having stage III or IV disease but conveys a poorer prognosis for those who do. The expected 10-year, disease-specific survival for patients <55 years old with stage I or II disease is 98 to 100 and 85 to 95 percent, respectively. For patients ≥55 years of age, the expected 10-year, disease-specific survival for stages I, II, III, and IV disease is 98 to 100, 85 to 95, 60 to 70, and <50 percent, respectively [9].

While the AJCC eighth edition performs well when analyzed across large cohorts of patients, it is important to note that as many as 6 percent of AJCC stage I patients less than 55 years old at diagnosis will have high-risk features (eg, gross extrathyroidal extension or incomplete tumor resection). These patients have a poorer prognosis than predicted for the entire cohort of stage I patients but can easily be identified by being classified as ATA high risk (see 'ATA risk stratification' below), even though they are classified as having AJCC eighth edition stage I disease [1].

MACIS system — The Metastases, Age, Completeness of Resection, Invasion, Size (MACIS) system was introduced to eliminate the need for histologic grading of the tumor [14,15]. The MACIS score is calculated as follows:

●3.1 (for patients less than 40 years old at diagnosis) or 0.08 x age (if 40 or more years old) plus

●0.3 x tumor size (in cm) plus

●1 if tumor incompletely resected plus

●1 if tumor locally invasive plus

●3 if distant metastases present

Using this system in patients with papillary cancer, the 20-year, disease-specific mortality for patients with a MACIS score less than 6 was 1 percent; with a MACIS score between 6.0 and 6.99, 11 percent; with a MACIS score between 7.0 and 7.99, 44 percent; and with a MACIS score of 8.0 or more, 76 percent.

National Thyroid Cancer Treatment Cooperative Study — The National Thyroid Cancer Treatment Cooperative Study (NTCTCS) created a staging approach that was applied prospectively to a registry of patients drawn from 14 cooperating institutions [16]. Clinicopathologic staging was based upon patient age at diagnosis, tumor histology, tumor size, intrathyroidal multifocality, extraglandular invasion, metastases, and tumor differentiation. Between 1987 and 1995, 1607 patients were registered; 43 percent were classified as having stage I disease, 24 percent stage II, 24 percent stage III, and 9 percent stage IV. Patients with follicular cancer were more likely to have stage III or IV disease than those with papillary cancer. Of 1562 patients for whom censored follow-up was available (median follow-up 40 months), 78 died from thyroid cancer or complications of treatment. Five-year, product-limit, disease-specific survival was 99.8 percent for stage I, 100 percent for stage II, 91.9 percent for stage III, and 48.9 percent for stage IV. The frequency of remaining disease free also significantly declined with increasing stage (94.3 percent for stage I, 93.1 percent for stage II, 77.8 percent for stage III, and 24.6 percent for stage IV) (table 4).

Staging systems used to predict initial risk of recurrence — In our practice, we use one of the popular staging systems to provide initial estimates of disease-specific mortality (usually TNM or MACIS) and then an additional clinicopathologic staging system, such as the ATA system (table 2), to provide initial estimates of risk of recurrence [3-5]. During follow-up, these initial risk estimates are continually refined as new data are used to assess response to therapy. (See 'Dynamic risk stratification' below.)

All of the popular staging systems reliably predict disease-specific mortality; however, they usually are not designed to adequately predict recurrence for individual patients. As an example, in a study comparing recurrence-free survival in patients with successfully treated differentiated thyroid carcinoma (undetectable stimulated thyroglobulin [Tg] and negative whole-body iodine scan), there was no difference in recurrence-free survival in patients initially classified as high or low risk based upon TNM stage at diagnosis [17]. Because of this limitation in current staging systems, the ATA proposed a novel clinicopathologic staging system designed to risk stratify patients as having either a low (papillary thyroid cancer confined to the thyroid), intermediate (regional metastases, worrisome histologies, extrathyroidal extension, or vascular invasion), or high (gross extrathyroidal extension or distant metastases) risk of recurrence (table 2) [5].

ATA risk stratification — The 2009 American Thyroid Association (ATA) guidelines for the management of thyroid cancer proposed a system to estimate the risk of recurrence in differentiated thyroid cancer based upon selected clinicopathologic features (table 2) [18]. Several retrospective studies have demonstrated that the 2009 ATA clinicopathology staging system accurately predicted the risk of disease recurrence and can be used to guide initial follow-up recommendations [19-22]. As an example, in a retrospective review of 588 patients with differentiated thyroid cancer followed at Memorial-Sloan Kettering Cancer Center (MSKCC) in New York, the ATA risk of recurrence staging system effectively predicted the risk of either recurrence or persistent structural disease, which occurred in 3, 21, and 68 percent of patients in the low-, intermediate-, and high-risk groups [4].

In the 2015 ATA guidelines, the ATA low-risk group was extended to include patients with small-volume lymph node metastases (≤5 micrometastases smaller than 0.2 cm), intrathyroidal encapsulated follicular variants of papillary thyroid cancer, intrathyroidal follicular thyroid cancer with no more than minimal vascular invasion, and intrathyroidal papillary microcarcinomas even if V600E BRAF mutation is present (table 2) [5]. Furthermore, the ATA high-risk category was extended to include patients with large-volume cervical metastases (≥3 cm) and follicular thyroid cancer with extensive vascular invasion. While still formally endorsing the three-tiered risk stratification systems, the ATA recognizes that risk of recurrence follows a continuum across the three discrete risk categories (low, intermediate, and high).

Dynamic risk stratification — While initial staging systems can be used to guide initial therapeutic and diagnostic follow-up strategy decisions, it is important to recognize that initial risk estimates may need to change as new data are accumulated during follow-up monitoring [23]. We typically restratify patients on each follow-up visit using a reclassification system that emphasizes the response to therapy for each individual patient. As originally conceived, these clinical outcomes described the best response to initial therapy during the first two years of follow-up [4,23] but are now being used to describe the clinical status at any point during follow-up. At each follow-up visit, patients are classified as having one of the following clinical outcomes [4,5,21]:

●Excellent response – No clinical, biochemical, or structural evidence of disease.

●Biochemical incomplete response – Abnormal Tg or rising Tg antibody values in the absence of localizable disease.

●Structural incomplete response – Persistent or newly identified locoregional or distant metastases.

●Indeterminate response – Nonspecific biochemical or structural findings that cannot be confidently classified as either benign or malignant. This includes patients with stable or declining anti-Tg antibody levels without definitive structural evidence of disease.

The precise definition of excellent response and biochemical incomplete response is dependent on the extent of initial therapy (table 5) [24]. As an example, we define an excellent response in each group as follows:

●Total thyroidectomy and RAI remnant ablation – A stimulated Tg value <1 ng/mL (or highly sensitive, nonstimulated Tg <0.2 ng/mL) with negative cross-sectional imaging (most commonly a normal postoperative neck ultrasound).

●Total thyroidectomy without RAI ablation – A stimulated Tg value <2 ng/mL (or highly sensitive, nonstimulated Tg <0.2 ng/mL) with negative cross-sectional imaging (most commonly a normal postoperative neck ultrasound).

●Less than total thyroidectomy (eg, lobectomy or lobectomy with isthmusectomy) – A nonstimulated Tg value <30 ng/mL (approximately 50 percent of the Tg expected from an intact normal thyroid) and negative imaging.

There are limited data to define the utility of monitoring Tg levels following lobectomy or lobectomy with isthmectomy [25]. While a nonstimulated Tg <30 ng/mL was originally used to define an excellent response in these patients, serum Tg levels obtained in this setting have low sensitivity and specificity for detection of persistent/recurrent thyroid disease and need to be interpreted in the light of current TSH values, ultrasound imaging findings in the contralateral lobe, and the magnitude of Tg elevation [25-28].

Very high Tg levels would not be expected in the setting of a contralateral thyroid lobe that is normal or demonstrating small thyroid nodules. Tg produced by the residual normal thyroid tissue usually far exceeds Tg coming from small-volume structural disease, except in the setting of clinically significant distant metastasis. Additionally, trends in Tg are difficult to interpret as the Tg values can vary with changes in TSH over time and can rise with the development of benign nodules in the contralateral lobe that may not be apparent on ultrasound imaging. Thus, a rising Tg over time could be related to either benign or malignant thyroid conditions.

Reclassification at each follow-up visit allows the clinician to tailor ongoing management recommendations to the current clinical status (rather than the initial risk stratification estimates). (See "Differentiated thyroid cancer: Overview of management", section on 'Monitoring response to therapy'.)

Two studies have demonstrated the importance of adjusting risk estimates during follow-up based on the response to initial therapy [4,6]. Restratification during the first two years of follow-up in a cohort of 588 patients reduced the likelihood of finding persistent structural disease or disease recurrence to 2 percent in the low-risk, 2 percent in the intermediate-risk, and 14 percent in the high-risk patients that achieved an excellent response to therapy (stimulated Tg less than 1 ng/mL and no evidence of structural disease on cross-sectional imaging). Conversely, an incomplete response to therapy (suppressed Tg >1 ng/mL, stimulated Tg >10 ng/mL, or structural evidence of persistent/recurrent disease within the first two years of follow-up) increased the subsequent risk of recurrence to 13 percent in low-risk, 41 percent in intermediate-risk, and 79 percent in high-risk patients [4].

Similar findings were reported in a study of 548 patients followed in Italy; the risk of recurrence decreased to 2 percent in low-risk and 5 percent in high-risk patients who demonstrated an excellent response to therapy [6]. In both of these dynamic risk stratification systems, the proportion of variance explained by these dynamic staging systems (84 and 62 percent, respectively) is significantly better than any of the static staging systems that rely only on initial clinicopathologic data to predict final outcomes.

Following these two initial validation studies [4,6], multiple studies have demonstrated the clinical utility of dynamic risk stratification [24].

OTHER PROGNOSTIC FACTORS — In addition to the clinical and histopathologic factors included in most thyroid cancer staging systems (age at diagnosis, size of the primary tumor, extent of local extrathyroidal extension, and the presence/absence of distance metastases), several other factors have been described that also appear to have prognostic significance. However, it is unclear how much these various factors improve one's ability to accurately risk stratify an individual patient beyond that achieved with the previously described staging systems.

Multifocality — Although not included in the tumor, node, metastasis (TNM) or Metastases, Age, Completeness of Resection, Invasion, Size (MACIS) staging systems, many, but not all, analyses suggest that multifocality is a predictor of recurrence. For example, in a study of 2095 patients with papillary cancer, both multifocality (odds ratio [OR] 1.45, 95% CI 1.01-2.10) and the number of tumors (OR 1.75, 95% CI 1.04-2.97) were significantly associated with disease recurrence [29].

Lymphocytic infiltration — Although not usually considered in staging systems, the presence of lymphocytic thyroiditis in the thyroid glands of patients with differentiated thyroid cancer appears to affect prognosis. In a retrospective study of 631 patients with this type of thyroid cancer who were followed for an average of 11 years, the recurrence rate (6 versus 24 percent; p<0.001) and the mortality rate (1 versus 8 percent; p<0.001) were lower in the 128 patients with thyroiditis [30].

PET-positive tumors — Also not presently considered in any staging system, thyroid cancers initially detected by fluorodeoxyglucose positron emission tomography (PET) are more likely to be more aggressive variants of thyroid cancer [31].

Histologic subtypes — While the Age, Grade, Extent, Size (AGES) and Memorial Sloan-Kettering Cancer Center (MSKCC) staging systems incorporate "tumor grade" into their staging systems (table 3), the other staging systems treat all papillary thyroid cancers the same regardless of the specific histologic subtype. Several studies have demonstrated a poorer prognosis for specific subtypes of papillary thyroid cancers, including tall cell variants [32] and poorly differentiated tumors [33].

Molecular characteristics — Multiple studies suggest that specific molecular profiles may be used to predict risk of extrathyroidal extension, lymph node metastases, and even distant metastases. Molecular testing results can be used to determine molecular risk group categories (low, intermediate, high) that provide clinically meaningful risk stratification information for disease recurrence, recurrence-free survival, overall survival, incomplete response to initial therapy, and probability of distant metastasis [34-36]:

●Low risk – RAS and RAS-like alterations

●Intermediate risk – BRAF V600E and other BRAF-like mutations and copy number alterations

●High risk – Driver mutation plus a second mutation such as TERT, TP53, AKT1, or PIK3CA

In a cohort study, the molecular risk group category (which can be known preoperatively) provided risk stratification very similar to the gold standard American Thyroid Association (ATA) risk stratification system (which can only be defined in the postoperative setting), indicating a potential role for preoperative molecular risk group classification to further individualize initial management decisions regarding extent of initial surgery [36]. While these observations need further validation, it is likely that molecular risk group classification systems, as well as specific mutational profiles, will be incorporated into staging systems in the near future. (See "Oncogenes and tumor suppressor genes in thyroid nodules and nonmedullary thyroid cancer".)

SOCIETY GUIDELINE LINKS — Links to society and government-sponsored guidelines from selected countries and regions around the world are provided separately. (See "Society guideline links: Thyroid nodules and cancer".)

SUMMARY AND RECOMMENDATIONS

●Staging systems for estimating disease-specific mortality – In differentiated thyroid cancer, several classification and staging systems are available (table 3), all of which reliably predict disease-specific mortality. In our practice, we use tumor, node, metastasis (TNM) (table 1) or Metastases, Age, Completeness of Resection, Invasion, Size (MACIS) staging systems to estimate disease-specific mortality. (See 'Staging systems for predicting disease-specific mortality' above.)

●Staging systems to predict risk of recurrence – Staging systems for estimating disease-specific mortality are not designed to adequately predict recurrence for individual patients. In addition, the estimates of the risk of recurrence and death usually do change over time depending upon how well the patient responds to initial therapy. Therefore, we use an additional clinicopathologic staging system, such as the American Thyroid Association (ATA) three-tiered risk stratification system, to estimate the risk of recurrence (table 2). The risk of recurrence, however, follows a continuum across the three discrete risk categories (low, intermediate, and high). (See 'Staging systems used to predict initial risk of recurrence' above.)

●Dynamic risk stratification – Initial risk assessments are actively modified based on data obtained during follow-up that reflect the individualized patient's response to therapy (table 5). This dynamic risk assessment approach allows for more accurate risk assessments than either a static estimate of risk based on the TNM staging system or the ATA risk of recurrence classification system. (See 'Dynamic risk stratification' above.)

It should be recognized, however, that no staging system predicts outcome in individual patients with 100 percent accuracy; as a result, clinicians should use individual clinicopathologic characteristics to determine the specific treatment for a given patient.

●Other prognostic factors – In addition to the clinical and histopathologic factors included in most thyroid cancer staging systems (age at diagnosis, size of the primary tumor, extent of local extrathyroidal extension, and the presence/absence of distance metastases), several other factors have been described that also appear to have prognostic significance, including multifocality, histologic subtypes, and molecular characteristics. (See 'Other prognostic factors' above.)