VOLUME 27 䡠 NUMBER 11 䡠 APRIL 10 2009 JOURNAL OF CLINICAL ONCOLOGY O R I G I N A L R E P O R T Simplifying the TNM System for Clinical Use in Differentiated Thyroid Cancer Adedayo A. Onitilo, Jessica M. Engel, Catharina Ihre Lundgren, Per Hall, Lukman Thalib, and Suhail A.R. Doi From the Marshfield Clinic Weston Center, Weston, WI; Department of Molecular Medicine and Surgery, Karolinska University Hospital; Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden; and the Department of Community Medicine (Biostatistics), Kuwait University; Division of Endocrinology, Mubarak Al-Kabeer Teaching Hospital; and the Department of Medicine, Kuwait University, Kuwait. Submitted October 6, 2008; accepted November 25, 2008; published online ahead of print at www.jco.org on March 9, 2009. Authors’ disclosures of potential conflicts of interest and author contributions are found at the end of this article. Corresponding author: Suhail A.R. Doi, PhD, Department of Medicine, Kuwait University, PO Box 24923 Safat, 13110 Kuwait; e-mail: [email protected] The Appendix is included in the full-text version of this article, available online at www.jco.org. It is not included in the PDF version (via Adobe® Reader®). A B S T R A C T Purpose The TNM stratification has been found useful at stratifying patients with differentiated thyroid carcinoma (DTC) into prognostic risk groups. However, it is cumbersome to implement clinically given the large number of bins within this system and the complicated system of arriving at stage information. Patients and Methods We decided to quantify each variable in this system to arrive at a simplified quantitative alternative to the TNM system (QTNM) and compare this with the conventional system. We used our electronic record system to identify 614 cases of DTC managed at our institution from 1987 to 2006. Cancer-specific survival (CSS) and disease-free survival (DFS) were calculated by the Kaplan-Meier method, and a simplified QTNM score was devised using a Cox proportional hazards model. Results We were able to quantify the TNM system as follows: 4 points each for age older than 45 years and presence of neck nodal metastases while 6 points for tumor size larger than 4 cm or extrathyroidal extension and 1 point for nonpapillary DTC. A sum of 0 to 5 points was low risk, 6 to 10 points intermediate, and 11 to 15 points high risk. Comparison with the conventional TNM system and two other systems revealed similar or better discrimination with the QTNM and this discrimination was maintained when this risk stratification was applied to a unique validation set. Conclusion The QTNM system as opposed to the conventional TNM system seems to be a simple and effective method for risk stratification for both recurrence and cancer-specific mortality. J Clin Oncol 27:1872-1878. © 2009 by American Society of Clinical Oncology © 2009 by American Society of Clinical Oncology 0732-183X/09/2711-1872/$20.00 INTRODUCTION DOI: 10.1200/JCO.2008.20.2382 Nonmedullary differentiated thyroid carcinomas (DTC; papillary, follicular, follicular type of papillary, and Hurthle) have a favorable prognosis, but a proportion of patients will develop recurrences and eventually die of the disease indicating a lack of reliable prognosticators. For this reason, systems have been devised that can order patients by a decreasing probability of survival which can be used for selecting patients for therapy and for providing patients with an estimate of their prognosis. The TNM system has been widely used for this purpose and is in effect a “bin model” wherein the TNM prognostic factors are used to create a mutually exclusive and exhaustive partitioning of patients, so that every patient is in one and only one bin.1 This system uses the mean survival of the patients already in the bin to predict what will happen to a new patient placed in that bin. For example, if a new patient is placed in the 1872 (T1, N0, M0) bin, then that patient’s 5-year diseasespecific survival is predicted to be the same as the mean survival of all the patients who were placed in that bin 5 years ago.2 Although the TNM is based on the anatomic extent of disease, there are several problems. Distant metastases at diagnosis is in itself a sufficient criterion for aggressive management and effectively bypasses the selection process for therapy. It was realized as early as 1993 that there were sufficient data available to indicate the independent prognostic significance of additional nonanatomic variables.3 As the TNM system is updated, there has been an increase in the number of subgroups within the TNM criteria themselves. The problem faced with adding all these to the TNM system is that stratifying by additional prognostic variables or TNM subgroups (eg, splitting T4 into T4a and T4b or N1 into N1a and N1b) leads to a proliferation of bins.2 For example, if one adds to the TNM stages for © 2009 by American Society of Clinical Oncology Downloaded from jco.ascopubs.org on June 9, 2014. For personal use only. No other uses without permission. Copyright © 2009 American Society of Clinical Oncology. All rights reserved. Quantitative TNM in Thyroid Cancer Table 1. Results of Model Building Using Cox Proportional Hazard Regression Parameter A† Age, ⬎ 45 years Tumor, ⬎ 4 cm Node present Not papillary Valid observations, total No. Uncensored Censored Log likelihood Final solution Null model (all ß’s ⫽ 0) 2 (null model final solution) df P B‡ Age ⬎ 45 years Tumor, ⬎ 4 cm Node present Valid observations, total No. Uncensored Censored Log likelihood Final solution Null model (all ß’s ⫽ 0) 2 (null model final solution) df P C§ Age, ⬎ 45 years Tumor, ⬎ 4 cm Node present Metastasis present Valid observations, total No. Uncensored Censored Log likelihood Final solution Null model (all ß’s ⫽ 0) 2 (null model final solution) df P ␤ SE t Value ORⴱ Wald Statistic P 1.11 1.79 1.18 0.31 0.32 0.31 0.32 0.33 3.44 5.71 3.73 0.95 3.03 5.97 3.24 1.37 559 49; 8.77% 510; 91.23% 11.9 32.6 13.9 0.9 ⬍ .001 ⬍ .001 ⬍ .001 .34 12.98 35.02 13.36 ⬍ .001 ⬍ .001 ⬍ .001 7.2 28.6 9.3 1.9 .007 ⬍ .001 .002 .16 ⫺248.57 ⫺283.54 69.9 4 ⬍ .001 1.14 1.83 1.07 0.32 0.31 0.29 3.15 6.25 2.92 559 49; 8.8% 510; 91.2% ⫺249 ⫺283.5 69.1 3 ⬍ .001 0.88 1.77 0.96 0.76 0.33 0.33 0.32 0.55 2.4 5.9 2.6 2.1 403 43; 10.7% 360; 89.3% 208.7 ⫺236.2 54.9 4 ⬍ .001 Abbreviations: OR, odds ratio; DTC, differentiated thyroid carcinoma. ⴱ Indicates the odds that an individual in the group with that risk factor reaches the end point first (end point is DTC related recurrence or death). †Results of model building using Cox proportional hazard regression. ‡Results of model building using Cox proportional hazard regression but not forcing histopathology into the model. §Results of model building using Cox proportional hazard regression but not forcing histopathology into the model and including distant metastases. thyroid cancer age information (two groups: age ⬎ 45 years v others) and histologic type information (two groups: follicular v others), one would increase the number of bins from 36 bins (6 T ⫻ 3 N ⫻ 2 M ⫽ 36) to a number that will be 144 bins (36 ⫻ 2 age groups ⫻ 2 histologic types ⫽ 144). Because the primary utility of the TNM staging system is its simplicity as a “look-up” table in which one looks up the stage of disease, the organization and use of a system with 144 bins becomes an impractical task.2 This problem may be compounded by our future need to add newer nonanatomic prognostic markers to the current TNM system. Eventually, clinicians will make use of the bins by grouping them together into larger bins called stages for clinical use.2 The TNM www.jco.org system for thyroid cancer groups the bins into four stages, each associated with a specific prognosis. The problem with this system of risk stratification is that prognostic risk stratification is not an exact science, and combining 144 bins into four stages may not necessarily improve prognostic risk stratification over and above quantitative evaluation of risk factors defined at say two levels of each TNM factor and other important nonanatomic factors, such as age and histologic type for DTC. We therefore decided to evaluate a quantitative simplified TNM system for thyroid cancer against the standard TNM classification using information on disease-free survival (DFS) and cancer-specific survival (CSS) obtained via our comprehensive patient database. © 2009 by American Society of Clinical Oncology Downloaded from jco.ascopubs.org on June 9, 2014. For personal use only. No other uses without permission. Copyright © 2009 American Society of Clinical Oncology. All rights reserved. 1873 Onitilo et al PATIENTS AND METHODS Study Target Populations Patients diagnosed with well DTC were electronically extracted from the Marshfield Clinic (MC) combined medical record using ICD-9 diagnostic code 193, with a rule of two (same diagnosis on two separate service dates). The resulting cases were then run against the MC/Saint Joseph’s Hospital (SJH) Cancer Registry, which identified a total of 658 patients during the time-frame from January 1, 1987, through December 31, 2006. Further review and application of exclusions reduced the number of study patients from 658 to 614. Patients were excluded due to diagnoses of non-DTC (anaplastic or medullary thyroid cancer) and if there were missing data verified through manual abstraction. A validation cohort (separate from the cohort in the United States described earlier) was selected from the Swedish Cancer Registry (SCR), which was established in 1958. The SCR does not register tumors for which the sole source of information is the death certificate. Tumors detected incidentally at autopsy were excluded from the validation study. From 1958 to 1987, when Sweden had 8.4 million inhabitants, 7,906 thyroid cancers were reported to the SCR. After excluding 1,405 patients (17.8%) with anaplastic and medullary thyroid cancers and 947 with follicular thyroid adenomas (12.0%), 5,554 individuals with DTC remained, of whom 5,123 had survived for at least 1 year after diagnosis.4 Matching of these 5,123 patients with the Swedish Causes of Death Register for 1959 to 1999 identified 693 patients (potential cases) for whom thyroid cancer was reported as the cause of death. Treatment protocols for DTC are standard and as such were similar in both Sweden and the United States. However, this does not exclude possible minor differences between the practices of institutions this being a limitation of this study. Data Collection The MC/SJH Cancer Registry database was queried to provide the following data on each patient: age, sex, histologic type, tumor size, presence of distant metastases, nodal disease, pathologic diagnosis, recurrence, location of recurrence, cause of death, and length of survival. The majority of data was available electronically. Supplemental manual data abstraction as needed was performed by two of the investigators (A.A.O., J.M.E.). This study protocol was approved by the MC institutional review board. The setting was a large multispecialty group practice located in central Wisconsin. Data sources included the combined medical record of MC and affiliated hospitals and the MC/SJH Cancer Registry.5,6 For the validation study, data on histopathologic findings, growth patterns, tumor differentiation, surgical procedures, and findings at follow-up were abstracted from the case records of these 693 patients. A group of three specialists (a cardiologist, an oncologist, and an endocrine surgeon) independently evaluated the medical records to confirm DTC as the cause of death. Ninety-eight patients had to be excluded for various reasons,4 and 595 sets of patients and controls were generated by randomly sampling one control for each patient, matched for age at diagnosis (5-year age groups), sex, and 10-year calendar periods of diagnosis via incidence density sampling. Statistical Analysis Variables used in the TNM system, as well as sex and histopathologic type, were dichotomized and entered into a forward stepwise Cox proportional hazards model, the outcome being DFS, defined as time to first recurrence or to a cancer-specific death. These factors had all been documented when the diagnosis was made. Only age, tumor size/extension, and node status were selected. Sex, metastases at diagnosis, and histopathologic status were excluded from the model. The results of this multivariate analysis were then used to develop a clinical prediction model, after forcing histopathology into the model instead of distant metastases even though the latter and not the former is within the conventional TNM system (Table 1). This was done for two reasons: histopathologic status is widely recognized as a prognostic variable and was associated with CSS in our cohort and we decided not to force distant metastases into the final model given the fact that distant metastases at diagnosis must be treated aggressively regardless of ultimate prognosis. Nev1874 © 2009 by American Society of Clinical Oncology Table 2. QTNM Staging for Differentiated Thyroid Cancer Stage Risk Criteria by Score 10-Year DFS (%) 10-Year CSS (%) 1 2 3 Low Intermediate High 0-5 6-10 11-15 95 70 45 100 90 65 NOTE. The TNM factor distant metastases was substituted instead with histopathologic status. Quantitative alternative to the TNM system (QTNM) score is the sum of the following: histopathology ⫽ 1 (not papillary thyroid cancer) otherwise 0; age ⫽ 4 (age ⱖ 45 years) otherwise 0; nodes ⫽ 4 (regional lymph node metastasis) otherwise 0; tumor ⫽ 6 (tumor ⬎ 4 cm in greatest dimension limited to the thyroid or any tumor with extrathyroid extension) otherwise 0. Abbreviations: DFS, disease-free survival; CSS, cancer-specific survival. ertheless, for comparison, we analyzed models without forcing histopathology and after forcing distant metastases (Table 1). Each ␤ coefficient was multiplied by 3.3 and rounded to the nearest integer. The risk score for an individual patient was determined by assigning points for each factor present and summing. The resulting continuous distribution of total risk scores across all patients in the model (range, 0 to 15) was then stratified into three equal categories of points that grouped patients according to the level of risk (low, intermediate, and high risk) as presented in Table 2. The quantitative alternative to the TNM system (QTNM) score is the sum of the following: histopathology ⫽ 1 (not papillary thyroid cancer) otherwise 0; age ⫽ 4 (age ⱖ 45 years) otherwise 0; nodes ⫽ 4 (regional lymph node metastasis) otherwise 0; tumor ⫽ 6 (tumor ⬎ 4 cm in greatest dimension limited to the thyroid or any tumor with extrathyroid extension) otherwise 0. Table 3. Characteristics of the Population With Differentiated Thyroid Carcinoma in Terms of Difference in Survival Between Subgroups Characteristic Sex Female Male Age, years ⱕ 45 ⬎ 45 Histopathology Papillary Other Tumor size ⱕ 4 cm and no extrathyroid extension ⬎ 4 cm or having extrathyroid extension Nodal metastases N⫹ N⫺ Distant metastases M1 M0 Surgery Total thyroidectomy Less than total surgery Post surgery radioiodine ablation therapy No Yes No. of Patients Gehan’s Wilcoxon P DFS CSS .09 .2 ⬍ .001 ⬍ .001 .3 .05 ⬍ .0001 ⬍ .0001 ⬍ .0001 .03 ⬍ .001 ⬍ .0001 .1 ⬍ .0001 .5 ⬍ .001 457 154 305 306 419 192 425 145 168 414 12 398 503 102 158 449 Abbreviations: DFS, disease-free survival; CSS, cancer-specific survival. JOURNAL OF CLINICAL ONCOLOGY Downloaded from jco.ascopubs.org on June 9, 2014. For personal use only. No other uses without permission. Copyright © 2009 American Society of Clinical Oncology. All rights reserved. Quantitative TNM in Thyroid Cancer classification seems to be the currently most predictive system.10,11 We also did a comparison with the University of Alabama and M. D. Anderson Cancer Care (Houston, TX) system12 because its highest risk category is made up of patients with distant metastases at diagnosis, a variable that was dropped from the multivariate analysis in this study. Cumulative Survival (proportion) 1.0 0.9 0.8 0.7 RESULTS Group 1 Group 2 Group 3 Complete Censored 0.6 0.5 0.4 0.3 0 5 10 15 20 25 Time (years) Fig 1. Disease-free survival by quantitative alternative to the TNM system risk group. Group 1 is low risk, group 2 is intermediate risk, and group 3 is high risk. Although this stratification method resulted in relatively few patients in the highest risk group, it allowed for discrimination of this small subset of patients at high risk. The univariate relationships between survival and the staging groups were analyzed via the Kaplan-Meier method. The difference between two risk groups was compared with Gehan’s Wilcoxon test since this test gives more weight to recurrence or deaths at early time points. Statistical analyses were performed using the Statistica software (Statsoft, Tulsa, OK) for Windows 6.0 computer software ( StatSoft Inc). For the validation study, a conditional logistic regression model for the data set matched for 10-year calendar period, sex, and survival time in completed years was used to estimate odds ratios and their respective 95% CIs (PROC PHREG in SAS, version 9; SAS Institute Inc, Cary, NC). The odds ratio was used as an estimate of the relative risk. Comparisons With Other Systems Comparison with MACIS (Mayo Clinic’s metastasis, age, completeness, invasive, size score)7 was made since, after the TNM8,9 system, this staging We examined 614 DTC patients retrospectively to validate known prognostic factors that enable them to be recognized as having either a low or a high risk of death related to a recurrence of DTC, by reference to our new QTNM stage or the conventional TNM stage or the two other staging classifications (MACIS and M. D. Anderson classifications). Patient characteristics are presented in Table 3. Fifty-nine patients (9.6%) had local or distant recurrence, or died of a recurrence, with a 10-year recurrence free survival of 85%. The 10-year CSS was 93%. Sex, age, larger tumor size, extrathyroidal invasion, nodal and distant metastases were all related to a higher incidence of tumor recurrence. Cancer-specific death, however, was associated with all of these factors except sex and in addition with nonpapillary tumor type, extent of surgery, and postsurgical remnant ablation (Table 3). Survival by QTNM risk group is shown in Figure 1 and Appendix Fig A1 (online only) for DFS and CSS, respectively. Cox proportional hazards regression of each staging system revealed that the TNM stages I and II as well as MACIS groups 2 and 3 were not very discriminatory since the odds indicate that an individual in the baseline group is as likely to reach the end point first as an individual in the next group (Table 4). The validation results confirmed that the hazard ratios for DTC related mortality were significantly greater in the intermediate and high risk categories than in the low-risk group in patients from a different center (Table 5), and again the standard TNM staging groups were not very discriminatory even though there was a trend (Table 6). Finally a cross-tabulation of the 16 bins possible (from these four Table 4. Multivariate Cox Regression Analysis Classification MACIS score 0-5.99 6-6.99 7-7.99 8⫹ TNM stage I II III IV University of Alabama and M. D. Anderson stage 1 2 3 QTNM score (this study) 0-5 6-10 11-15 No. of Patients Odds of Recurrence 95% CI P 317 35 18 23 1 (ref) 2.1 5.9 11.7 0.7 to 6.3 2.2 to 16.1 5.7 to 23.9 .17 ⬍ .001 ⬍ .001 271 38 36 27 1 (ref) 1.4 3.5 16.9 0.4 to 4.8 1.3 to 9.1 8.1 to 35.3 .6 .01 ⬍ .001 258 140 12 1 (ref) 3.3 7.3 1.7 to 6.3 2.4 to 22 ⬍ .001 ⬍ .001 386 117 56 1 (ref) 5.1 14.3 2.5 to 10.6 6.9 to 29.7 ⬍ .001 ⬍ .001 NOTE. Odds that an individual in the group with the higher risk will reach the end point (recurrence of disease) first according to the various classification systems. Abbreviations: MACIS, Mayo Clinic’s metastasis, age, completeness, invasive, size score; QTNM, quantitative alternative to the TNM system. www.jco.org © 2009 by American Society of Clinical Oncology Downloaded from jco.ascopubs.org on June 9, 2014. For personal use only. No other uses without permission. Copyright © 2009 American Society of Clinical Oncology. All rights reserved. 1875 Onitilo et al Table 5. Validation of QTNM Staging for Differentiated Thyroid Cancer Mortality Using Conditional Logistic Regression on Matched Cases (died) and Controls (survived) Sampled Using Incidence Density Sampling Matching Variables Onlyⴱ No. Stage Risk Score Patient Control Odds Ratio 1 2 3 Low Intermediate High 0-5 6-10 11-15 297 176 122 441 114 37 Ref 1.64 2.02 Other Variables† 95% CI Odds Ratio 95% CI 1.14 to 2.37 1.22 to 3.32 Ref 1.58 1.96 1.09 to 2.28 1.19 to 3.22 NOTE. The hazard is the odds of being a patient. Quantitative alternative to the TNM system (QTNM) score is the sum of the following: histopathology ⫽ 1 (not papillary thyroid cancer) otherwise 0; age ⫽ 4 (age ⱖ 45 years) otherwise 0; nodes ⫽ 4 (regional lymph node metastasis) otherwise 0; tumor ⫽ 6 (tumor ⬎ 4 cm in greatest dimension limited to the thyroid or any tumor with extrathyroid extension) otherwise 0. ⴱ Odds ratio adjusted for matching variables (sex, survival time in completed years, and 10-year calendar periods of diagnosis). †Odds ratio adjusted for extent of surgery (total v other procedures) in addition to matching variables. dichotomous risk parameters) versus quantitative risk categories reveals that the three categories are fairly homogenous (Appendix Table A1, online only). DISCUSSION The QTNM results suggest that despite being a simple and easily applied quantitative score, it retains a similar prognostic significance to the TNM, MACIS, and M. D. Anderson classifications. At the same time it obviates the necessity to make use of the bins in the complicated fashion of grouping them together into larger bins called stages for clinical use as dictated by the TNM classification. We only pursued the four variables in the TNM system (age, neck lymph node involvement, tumor size/extrathyroidal invasion, and distant metastases at diagnosis) and two other commonly employed variables (histopathology and sex). It has been suggested that of these six, the most important prognostic variables are age (cutoff value, 45 to 50 years) and extracapsular invasion of the thyroid gland.13 These two factors have also been found previously to be associated with a poor clinical outcome in several commonly used staging systems.7,12,14-19 Similarly, we found that tumor size/extension was most significant, followed by age and node status, the latter two being equally important. Other risk factors have been proposed over the years such as tumor grading20, DNA ploidy,21 nuclear atypia,22 gross lymph node involvement,23 microscopic and macroscopic tumor multifocality,24 histologic papillary thyroid cancer variants,25 size of lymph node Table 6. Comparative Validation of TNM Staging for Differentiated Thyroid Cancer Mortality Using Conditional Logistic Regression on Matched Cases (died) and Controls (survived) Sampled Using Incidence Density Sampling Matching Variables Onlyⴱ No. Stage Patient Control Odds Ratio I II III IV 32 101 288 161 78 218 231 48 Ref 0.66 1.21 1.89 Other Variables† 95% CI Odds Ratio 95% CI 0.33 to 1.28 0.63 to 2.32 0.9 to 4.0 Ref 0.67 1.21 1.88 0.34 to 1.31 0.63 to 2.32 0.9 to 4.0 NOTE. The hazard is the odds of being a patient. ⴱ Odds ratio adjusted for only matching variables (sex, survival time in completed years, and 10-year calendar periods of diagnosis). †Odds ratio adjusted for extent of surgery (total v other procedures) in addition to matching variables. 1876 © 2009 by American Society of Clinical Oncology metastases,26 and tumor angioinvasion.27 However, due to lack of widespread acceptance they have not been utilized routinely in clinical practice. Sex and histopathologic status were found to be the weakest prognostic indicators. Indeed, in univariate analyses, sex retained only borderline association with recurrence while histopathologic status retained borderline association with death. In the multivariate model, histopathologic status carried the lowest weight and had to be forced into the DFS model. This could be because patients with follicular thyroid cancer present at a higher stage, and thus in the univariate analysis there was a significant difference but not in the adjusted model. Histopathologic status was retained nevertheless as a risk factor in the model because there is reasonable evidence for its use as a prognostic variable,28 and while confounding by presentation at a higher stage is an issue, the fact that this happens suggests that the two tumor types behave differently in terms of aggressiveness.29 Indeed, others suggest that after adjusting for TNM stage, patients with follicular thyroid cancer have a 40% higher risk of dying from DTC compared with those patients diagnosed with papillary thyroid cancer.28 Sex, however, was not included in our model. Even though thyroid disease is more common in women, sex has not been demonstrated to have direct implication in the overall outcome in patients with thyroid cancer.30,31 In this study, nodal metastases had a significant association with DFS and CSS. The prognostic impact of regional lymph node metastases is still a controversial issue,32,33 and according to the recent TNM classification, patients with a minimal extrathyroidal tumor extension and/or LN metastases belong to the same stage I group when age younger than 45 years and stage III or IV otherwise.9 However, the respective impact on prognosis of lymph node metastases and minimal extrathyroidal tumor extension has not been properly documented. A recent nested case-control study suggests that patients with locoregional spread are more likely to die of DTC while the number of lymph node metastases do not appear to influence survival.28 We found a stronger relationship with recurrence than with death, suggesting that while it is associated with both, the former is more significant. Distant metastases did have a significant association with both recurrence and death in this study, but was not included in the multivariate model. It is well known that thyroid cancer with distant metastases at the time of diagnosis has an adverse effect on survival.28,34 However, this may itself be related to other factors, such as age, which not only influence long-term survival in patients with existing distant JOURNAL OF CLINICAL ONCOLOGY Downloaded from jco.ascopubs.org on June 9, 2014. For personal use only. No other uses without permission. Copyright © 2009 American Society of Clinical Oncology. All rights reserved. Quantitative TNM in Thyroid Cancer metastases but also predict the development of such metastases.35 Indeed, when distant metastases was forced into the model, the significance of age decreased confirming what we already know from TNM—age influences the impact of distant metastases in DTC. Also, patients with distant metastases at diagnosis must be treated aggressively and as such a staging system may not be relevant if a patient has, for example, pulmonary metastases identified on the radioiodine scan after total thyroidectomy. Finally, as distant metastases at diagnosis is relatively uncommon and routinely treated aggressively, systems with or without this factor did not differ in terms of risk stratification. The MACIS staging classification has previously been reported to result in a risk category for the two intermediate groups to be too broad, and in the case of the TNM classification, stages I and II overlapped considerably in terms of risk definition.13 We also found a similar trend for DFS (Table 4) with both MACIS and the TNM system, again suggesting that three risk groups are possibly the optimum number when stratifying DFS risk for DTC. In the QTNM, quantitatively measured risk was divided into three equal groups based on the assumption that quantitative risk is a continuum and thus does not require binning where risk groups need to be chosen. In this respect, the QTNM, with three risk categories, seems more appropriate than these systems. When we compare DFS with CSS with our QTNM risk stratification system, low- and intermediate-risk groups come closer for CSS as compared with DFS. This is probably a reflection of the fact that prolonged survival is possible even after disease recurrence and hence does not confer a major survival disadvantage. Therefore, while three risk categories seem optimal for DFS, two might be more optimal for CSS. With the QTNM, predominantly high- and low-risk groups emerge for CSS (Fig A1), and this may be a REFERENCES 1. Burke HB, Henson DE: The American Joint Committee on Cancer: Criteria for prognostic factors and for an enhanced prognostic system. Cancer 72:3131-3135, 1993 2. Burke HB: Outcome prediction and the future of the TNM staging system. J Natl Cancer Inst 96:1408-1409, 2004 3. Hermanek P, Sobin LH, Wittekind C: How to improve the present TNM staging system. Cancer 86:2189-2191, 1999 4. Lundgren CI, Hall P, Dickman PW, Zedenius J: Influence of surgical and postoperative treatment on survival in differentiated thyroid cancer. Br J Surg 94:571-577, 2007 5. 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This interaction of treatment parameters with mortality as opposed to recurrence needs to be elucidated in future research. In conclusion, the QTNM is a simple and effective method of prognostic stratification for both recurrence and cancer-specific mortality. There is no loss of discrimination when compared with current systems, including its parent TNM staging system, despite being simpler and less complicated. Substantiation of this system in other settings is recommended. AUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST The author(s) indicated no potential conflicts of interest. AUTHOR CONTRIBUTIONS Conception and design: Adedayo Onitilo, Suhail Doi Administrative support: Adedayo Onitilo, Jessica Engel Provision of study materials or patients: Adedayo Onitilo, Jessica Engel, Catharina Ihre Lundgren, Per Hall Collection and assembly of data: Adedayo Onitilo, Jessica Engel, Catharina Ihre Lundgren, Per Hall Data analysis and interpretation: Lukman Thalib, Suhail Doi Manuscript writing: Adedayo Onitilo, Catharina Ihre Lundgren, Per Hall, Lukman Thalib, Suhail Doi Final approval of manuscript: Adedayo Onitilo, Jessica Engel, Catharina Ihre Lundgren, Per Hall, Lukman Thalib, Suhail Doi noma with extrathyroid extension. J Clin Endocrinol Metab 92:215-218, 2007 10. Passler C, Prager G, Scheuba C, et al: Application of staging systems for differentiated thyroid carcinoma in an endemic goiter region with iodine substitution. Ann Surg 237:227-234, 2003 11. Lang BH, Lo CY, Chan WF, et al: Staging systems for papillary thyroid carcinoma: A review and comparison. 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