ORIGINAL ARTICLE
TNM-BASED STAGE GROUPINGS IN HEAD AND NECK
CANCER: APPLICATION IN CANCER OF THE HYPOPHARYNX
Stephen F. Hall, MSc, MD, FRCSC,1,2Patti A. Groome, PhD,2 Jonathan Irish, MSc, MD, FRCSC,3Brian O’Sullivan, MB, FRCPC4 1
Department of Otolaryngology, Queen’s University, Kingston, Ontario, Canada. E-mail: sfh@queensu.ca
2Division of Cancer Care and Epidemiology, Queen’s Cancer Research Institute,
Queen’s University, Kingston, Ontario, Canada
3Department of Surgical Oncology, Princess Margaret Hospital, Toronto, Ontario, Canada 4
Department of Radiation Oncology, Princess Margaret Hospital, Toronto, Ontario, Canada
Accepted 19 May 2008
Published online 20 November 2008 in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/hed.20917
Abstract: Background. The purpose of this study was to test the Union Internationale Contre le Cancer (UICC)/TNM cate-gory–based head and neck cancer stage grouping systems pro-posed in the literature for their ability to create clinically relevant prognostic groups of like-patients with cancer of the hypopharynx.
Methods. Population-based retrospective survival study of 595 patients with squamous cell carcinoma of the hypopharynx across Ontario, Canada, from January 1990 to January 2000. The grouping systems of UICC/TNM, T and N Integer Score (TANIS), Hart, Berg, Snyderman, Kiricuta, and Hall were tested and compared for prognostic ability using hazard consistency, hazard discrimination, percent variance explained, outcome prediction, and balance.
Results. All 8 systems predicted disease-specific survival. The system proposed by Snyderman performed the best, and UICC/TNM sixth edition did not perform as well as most.
Conclusion. The UICC/TNM stage group classification, although successful in creating statistically distinct groups, did not perform as well as other stage grouping systems, continuing a theme that has been reported previously. VVC2008 Wiley Peri-odicals, Inc. Head Neck 31: 1–8, 2009
Keywords: stage group; hypopharynx cancer; prognosis
T
he TNM classification was conceived to aid treatment planning, indicate prognosis, assist treatment evaluation, and facilitate exchange of information between oncologists. It is based on the concept that the natural history of a cancer in a patient is an orderly progression of events including enlargement, invasion, regional lym-phatic spread, and metastases. The process of ‘‘staging’’ a patient using TNM consists of 2 parts with different objectives. First, the anatomic extent of the cancer is assessed and described using the categories of T, N, and M related to the size or extent of the tumor. These categories were designed to create a common language among oncologists that would be simple, reproducible, and unambiguous. The TNM anatomic extent of cancer is recognized as both the strongest predic-tor of survival1and an essential step in treatment planning.2Stage grouping is an attempt to assem-ble patients with different combinations of T, N, and M but similar prognosis in order toprognosti-Correspondence to: S. F. Hall
Contract grant sponsor: Canadian Institutes of Health Research (CIHR); Contract grant number: MOP # 62781.
V
cate, plan, and evaluate treatments. To be a valid useful predictor of survival, the stage groups have to be made up of patients with similar survival yet different between-group survival.
The relative strengths of the TNM classifica-tion for head and neck cancers have been reviewed by Piccirillo3and Lydiatt et al,4who noted simplic-ity, universal acceptance, longevsimplic-ity, user-friendli-ness, and cost-effectiveness. Numerous authors have presented assessments of the performance the TNM stage grouping system as predictors of survival for the head and neck cancer sites (oral cavity,5–7 larynx,8,9 oropharynx,10–14 all sites15–18); although all concluded that the TNM stage created groups that were statistically suc-cessful predictors of survival, all reported that 1 or more stage grouping systems were better pre-dictors. Many authors have proposed changes to both TNM categories and the stage groups for the head and neck sites, but no substantial changes to stage groups have been forthcoming.
In an editorial in this journal, Lydiatt et al4 summarized the controversy of TNM stage groups and identified 4 central issues. First was the im-portance of ease of use and simplicity. Second was the need to balance consistency of staging over time to allow retrospective comparisons. Third was the need to determine the types of evidence that would be required to precipitate a change. To generate statistically sound evidence, the authors recommended the methodology reported by Groome et al,6,9,13 which described 5 criteria for assessment of prognostic group performance (hazard consistency, hazard discrimination, per-cent variance explained [PVE], outcome predic-tion, and balance). The fourth issue asked if the classification should be site specific or all inclusive as is the case in head and neck oncology.
The first objective of this study was to use a large cohort of unselected patients with squamous cell carcinoma of the hypopharynx to test the vari-ous head and neck stage grouping systems pro-posed in the literature for their ability to create clinically relevant prognostic groups of like-patients following the methodology of Groome et al. The prognostic validity of TNM for the hypo-pharynx site has not been reported, and this will complete the TNM prognostic validity for the mu-cosal squamous cell carcinomas of the upper aero-digestive tract using Groome’s methodology. The hypopharynx site is ideal to test the grouping sys-tems as there is a wide range of survival plus a high incidence of regional nodal disease compared with other head and neck sites.
The second objective was to compile the results on the assessment of TNM stage groupings for all head and neck sites that used the methodology described by Groome et al to investigate patterns of performance.
MATERIALS AND METHODS
Data Collection. The study population included patients with squamous cell carcinoma of the hypopharynx from the Province of Ontario, Can-ada, from 1990 to 2000. The cohort was specifi-cally chosen to reduce the potential biases created by treatment effects and/or treatment selection because chemoradiotherapy was not used exten-sively in Ontario until after 2000 and the stand-ard of investigation had not switched from CT to MRI. The patients were treated at 9 Cancer Care Ontario cancer treatment centers across the prov-ince, and the treatment varied from center to cen-ter consistent with the confusion in the licen-terature on the best or ideal treatment. The overall treat-ments were surgery 6 radiotherapy (19.7%), radiotherapy 6 chemotherapy 6 surgical salvage for residual disease (64.6%), palliative radiother-apy (5.9%), and no active treatment (9.7%).
The Ontario Cancer Registry (OCR) is a popu-lation-based tumor registry operated by Cancer Care Ontario. It consists of linked data on all patients with cancer, including demographic in-formation from the cancer centers, all pathology reports of cancer from all hospitals and laborato-ries, all hospital separations from the Canadian Institute of Health Information (CIHI) when a di-agnosis of cancer included, and death information from the Ontario Registrar General.
There were 891 cases of squamous cell carci-noma of the hypopharynx identified in the OCR across Ontario, diagnosed from January 1, 1990, to December 31, 1999. Of the 891 cases, there were 35 duplicate cases, leaving 856 patients. Spe-cific clinical information was requested and received from all Cancer Care Ontario treatment centers and the Princess Margaret Hospital for the variables to describe patients, tumors, treat-ments, and clinical course including cause of death for the 856 patients. Eleven identified patients who were not seen at a regional cancer center were also included based on requested hos-pital records. The charts of 50% (random) of the patients from the largest center (126 were not reviewed) and the charts of all patients from the other 8 cancer treatment centers were abstracted
(total 595). Twelve percent of the original patients coded as cancer of the hypopharynx in the OCR were rejected for errors of site (supraglottic larynx [47], oropharynx [35], unknown primary [14], other [7]). Eight patients were excluded due to insufficient information (extent of disease, comor-bid illness, treatment, lack of follow-up), and 24 patients who did not meet criteria of the study (no biopsy report, non-squamous cell carcinoma his-tology, treatment out of province) were excluded. The principle investigator (S.H.) reviewed all clin-ical staging, all surgclin-ical treatments, and cause of death. Missing data such as CT reports and opera-tive notes were requested and obtained on 57% of cases through hospitals and physicians.
We could not use T, N, or M categories as stated on the charts because they were frequently miss-ing, outdated, or inconsistent. To establish ana-tomic stage, the referring letters, consultation let-ters, operative biopsy reports, and imaging were used. The elements of anatomic stage were based on clinical examination and imaging only. For this study, with the known poor reliability of clinical examination of neck masses, imaging was used when available for N category. N2B category was used for multiple nodes regardless of size, and N3 category was used for individual nodes over 6 cm. A record by an otolaryngologist/head and neck sur-geon or an experienced head and neck radiation oncologist stating any vocal cord dysfunction or imaging reporting vocal cord fixation was used to identify vocal cord paralysis. In keeping with the SEER Program Code Manual for ambiguous terms on extent of disease (third edition),19we identified cartilage invasion by the specific terms (invasion to, onto, appears to, and compatible with invasion), and any cartilage invasion was recorded as posi-tive. The T and N categories were then generated based on the TNM manual sixth edition20noting specific rules such as cartilage invasion in pyriform cancers. TNM site assignment was based on the location of at least 60% of tumor, and category assignment followed TNM general rules such as using the less-advanced stage when there was doubt about the correct assignment.
Using the chart information, requested further information, and recorded cause of death based on the Ontario Death Registry, we assigned cause of death as either ‘‘dead of hypopharyngeal cancer’’ or ‘‘dead of another cause.’’ Patients who died with active progressing disease were assigned ‘‘dead of cancer’’ regardless of actual cause (eg, aspiration pneumonia, pulmonary embolus), and patients who died within a month of treatment were assigned
the actual cause of death secondary to the hypo-pharyngeal cancer. Patients who were cancer free but subsequently died with no clinical information on cause were assigned ‘‘dead of another cause— cause not determined’’ (n 5 51) and patients lost to follow-up with no information on vital status were assigned ‘‘status missing’’ (n 5 2). Mean follow-up time for those alive or lost to follow-up was 75.4 months (min, 15.4; max, 150.4 months).
Data Analysis. We tested the prognostic stage group classifications of TNM sixth edition20with the alternative classifications including T and N Integer Scores (TANIS),17 Snyderman and Wagner,7Hart et al,21Berg,11Kiricuta,22and Hall et al.15The methodologies and study populations used to create each of these classifications were very different and have been reviewed.13,15 An overview of the T and N category combinations and distributions within each of these schemes is found on Figure 1. We refer to a subgroup as the patients with a specific combination of T and N categories and a group as the combination of sub-groups within a classification system. The terms classification, scheme, and system are used inter-changeably.
Survival was assessed using the Kaplan– Meier method, log rank tests, and hazard ratios (using the Cox Proportional Hazards Regression modeling). The time zero was date of diagnosis, and the outcome of interest was disease-specific sur-vival. Disease-specific survival was chosen for test-ing the prognostic ability of stage as it reflects the response of the tumor to treatment and is not as influenced as overall survival by other prognostic factors such as comorbidity, age, and performance status. Disease-specific survival was assessed for each TNM subgroup (T1N1, T2N3, etc.) and for each stage group within each classification.
Evaluation of the classifications followed the methodology of Groome et al, acknowledged to be the standard for the testing and reporting of prog-nostic classifications in head and neck oncology,4 which recommended 4 criteria plus an overall summary score that are summarized briefly. First, ‘‘hazard consistency’’ addresses the question of the homogeneity of the patients within each sub-group for all the sub-groups. Hazard consistency is an assessment of the average of the survival differen-ces between the subgroups that make up the groups and the groups themselves. The percent is the average survival rate difference between the subgroups. Lower scores indicate less difference in between-group survival. Second, ‘‘hazard
dis-crimination’’ addresses the question of the hetero-geneity of patients between each adjacent group. Hazard discrimination assesses how well the sur-vival curves groups are spaced apart given the span of survival they each represent. The percent is the average of difference in survival between the highest and lowest curves across time. The score for hazard discrimination ranges from 0 to 1.0 with a higher score indicating better discrimina-tion between curves. The third criteria ‘‘outcome prediction’’ is assessed in 2 ways. PVE23is the per-cent of the overall variance in survival that is explained by the grouping scheme. The second assessment of outcome prediction is referred to as ‘‘slope.’’ Slope assesses the accuracy of the predic-tions of survival and death. These 2 complemen-tary methods assess how well the groups predict the outcome of survival. Finally, ‘‘balance’’ refers to the balance of patient numbers in each group and has a range of possible values from 0 to 1. The
actual score for each of the four tests (criteria) for each of the classifications is reported followed by a normalized score and the rank of the classification within that test. A ‘‘summary score’’ is then calcu-lated, which is a weighted sum of the component scores and puts equal importance on criteria 1 to 4 with less on balance as it is of more statistical than clinical relevance. A more prognostic staging system has a lower summary score. Finally, stag-ing systems are ranked within the summary scores with the lowest summary score ranking first. These concepts and the derivation of the scores including the summary score are described in more detail in the work of Groome et al.6
RESULTS
The case mix variables describing the patients and their tumors are presented in Tables 1 and 2. The mean age was 66.1 years, and the tumors were advanced, with 57.4% stage 4.
The overall and disease-specific survival for all patients is presented in Figure 2.
The causes of death are found in Table 3. Of patients who died, almost 2 of 3 succumbed to their hypopharyngeal cancer.
Table 4 presents the hazard risks of disease-specific survival for each of the 20 combinations (subgroups) of the T and N categories with the T1N0 subgroup as the baseline group. The num-ber of patients in each subgroup is in brackets and the statically significant hazard risks are high-lighted (p < .05). In most cells, except N3 where the numbers are quite small, the prognostic use-fulness of the T and the N categories is demon-strated, as there is a progressive increase in the hazard risks with increasing severity of both.
Table 5 presents the hazard risks for each stage group of each system and demonstrates the progression in risk for the groups within each, noting that each system has a different number of groups. For example TNM has five groups (I, II, III, IVa, IVb). The highlighted values were statis-tically significant (p < .05). All classifications were successful in creating groups with increas-ing risk for increasincreas-ing severity although some not statistically successful.
Table 6 presents the overall results including hazard consistency, hazard discrimination, prog-nostic ability, balance, and overall scores for the 8 classification systems. Each test is reported as a score, a normalized score, and the rank of the score across the 8 systems.
Hazard Consistency. The homogeneity within groups is assessed by hazard consistency, with a lower score indicating better homogeneity with the subgroups. The TANIS-7 and the Hall tions had the best scores, and the Berg classifica-tions had the poorest. The TNM/Union Internatio-nale Contre le Cancer (UICC) sixth edition did place similar risk patients into the same subgroups.
Hazard Discrimination. The heterogeneity between groups is assessed by hazard discrimination, with lower scores indicating better patient grouping. The classifications of Kiricuta and Hart had the best scores while TANIS-7 was the poorest along Table 1. Case mix: patient variables.
Variable Category No. of patients %
Age <50 28 4.7 51–60 155 26.2 61–70 229 38.4 >70 182 30.7 Sex Male 483 81.2 Female 112 18.8
Table 2. Case mix: tumor variables.
Variable Category No. of patients %
T category T1 75 12.8 T2 204 34.2 T3 173 29.0 T4a 121 20.3 T4b 22 3.7 N category N0 213 35.9 N1 114 19.1 N2a 46 7.7 N2b 143 24.0 N2c 49 8.2 N3 30 5.0 M category M0 575 96.1 M1 20 3.4 TNM stage group I 23 4.0 II 76 12.8 III 152 25.5 IV 344 57.7
FIGURE 2. Overall survival and disease-specified survival curves. Reprinted with permission from Hall SF et al. The natu-ral history of patients with squamous cell carcinoma of the hypopharynx. Laryngoscope 2008;118:1362–1371, Lippincott Williams & Wilkens. [Color figure can be viewed in the online issue, which is available at www.interscience.wiley.com.]
Table 3. Causes of death.
Cause of death Category
No. of patients % Hypopharyngeal cancer 337 64.7 Other disease 178 34.0 Cancers 45 25.3 Cardiac 19 10.7
Central nervous system 5 2.8
Respiratory 7 3.9
Other 10 5.6
Not determined 51 24.4
with the Hall classification. The TNM/UICC sixth edition did not create different groups of patients with different risk as well as others.
Outcome Prediction. For the prognostic ability the systems as measured by percent variance explained, TANIS-7 had the best score and explained 11.2% of the variance in disease specific survival. For prognostic ability using the slope methodology that measures the accuracy of predic-tion of survival and death within each group, UICC/TNM sixth and the Hall classification had the highest scores. The UICC/TNM sixth created groups that predicted outcome.
Balance. Balance is the balance of patient num-bers within each group and had a very wide range of scores due to small numbers of patients within certain TNM subgroups. The Snyderman classifi-cation created the best balance and UICC/TNM the poorest.
Summary Scores and Summary Ranking Scores. The overall weighted scores of the eight classifications created three clusters. The Snydermann and the Kiricuta were the best performers and the Berg classification was the poorest. The remaining five (UICC, TANIS-3, TANIS-7, Hart, Hall) had simi-lar mid-range scores. The UICC/TNM ranked 5th of 8 overall.
Table 7 presents an overall rank for each of the stage groupings systems for each of the head and
neck cancer sites from the literature6,9,13 includ-ing this study. The average of all the rankinclud-ing scores for each site is calculated for each grouping system as an assessment of overall performance. The Snyderman proposal7 had the best overall performance (ie, the lowest average ranking). The UICC/TNM system was the poorest overall with the highest overall ranking.
DISCUSSION
The first objective of this study was to compare the various TNM category–based stage grouping systems for the hypopharynx patient population. We found over 4 tests that the UICC TNM sixth edition stage grouping system, when compared with the 7 other classification systems, created groups that predicted death from the cancer but did not create homogeneous subgroups, heteroge-neous groups, or explain survival variance as well as others. It was the best system at predicting outcome of survival vs death and did predict 11.0% of the variance in disease-specific survival; however, for the important tests of Hazard Consis-tency and Hazard Discrimination, it was a poor performer.
The best performing classifications were those by Snyderman and Kiricuta. Snyderman and Wagner7 modified the TANIS-717 to create 4 groups based on the disease-free survival analysis of 186 patients with oral cavity cancer. The TANIS as proposed by Jones et al17added the T and N cat-egory scores to create a single number. They tested the scoring system as a prognostic index on 83 patients with advanced squamous cell cancer of the head and neck in a chemoradiotherapy pro-tocol. The 7 combinations of the T and N categories created TANIS-7, and the authors reduced the groups to 3 to maximize group size. The Kiricuta model22was a small, but important, change to the system proposed by Hart et al,21which was based on multiple variable analysis of the disease-spe-cific survival of 640 patients with oropharyngeal Table 4. Disease-specific survival: hazard ratios for
each combination of T and N.
T1 T2 T3 T4 N0 1.00 (23) 0.91 (78) 1.56 (64) 4.58 (47) N1 1.56 (16) 2.20 (45) 2.80 (27) 3.78 (26) N2a 1.16 (8) 1.51 (17) 5.78 (15) 24.34 (6) N2bc 3.79 (22) 3.26 (56) 3.99 (67) 4.39 (47) N3 6.05 (7) 3.74 (6) 11.91 (5) 11.71 (11)
Note: Hazard ratios shown in bold are statistically different compared with the reference group (T1N0).
Table 5. Disease-specific survival: hazard risks for each stage grouping scheme.
UICC/AJCC (6e) TNM4 TANIS-7 TANIS-3 Snyderman Hart Berg Kiricuta Hall
Group 1 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 Group 2 0.91 0.91 1.01 2.19 2.00 2.07 1.29 2.45 1.02 Group 3 1.92 1.92 2.01 3.11 3.29 3.26 2.49 4.63 2.11 Group 4 3.61 3.98 3.31 4.66 4.43 4.16 6.18 3.93 Group 5 8.54 4.12 5.05 Group 6 5.13 Group 7 11.38
Abbreviations: UICC, Union Internationale Contre le Cancer; AJCC, American Joint Committee on Cancer; TANIS, T and N Integer Score. Note: Hazard ratios shown in bold are statistically different compared with the reference group 1.
cancer from multiple centers. The Berg scheme was based on 470 patients with oropharynx can-cer, and the Hall scheme was based on 637 patients with cancers from all sites.
The second objective was to compile the results of similar studies on stage group testing for all the mucosal squamous cell carcinoma sites. Table 7 demonstrates that overall the Sny-derman system, with TANIS-7 that it was derived from, were consistently the best per-formers across all sites and tests. The UICC/ TNM stage grouping system did not perform well compared with others. It is important to note that the studies on oral, laryngeal, and oropha-ryngeal cancers were based on the fourth edition, whereas we have reported the results based on the sixth edition. When our data were analyzed based on the rules of the fourth edition, the results were almost the same with the noteable improvement in percent variance explained with the sixth edition.
The strength of this study on hypopharyngeal cancer is that we used a large unbiased multicen-ter patient population with a range of treatments that is ideal for the analysis of prognostic factors as all patients are included and selection bias is part of the design.
There are 3 potential limitations to this study and our findings. First is the reliability of the clin-ical variable assignments for specific patients, a li-mitation common to all retrospective research based on chart abstraction. Assignment, based on a priori rules, is dependent on the availability of records, the quality of records, the completeness of investigations, and the quality of the various examinations. One example is the N category assignment, as we based N category on the pre-treatment CT report when available. Another example is our assignment of cartilage invasion based on the rules used by tumor registrars and not the TNM rule of ‘‘through cartilage’’ for T4. Almost all of the centers performed CT on at least
Table 7. Ranking scores for each stage group system for 5 head and neck sites based on the literature and this study.
UICC* TANIS-7 TANIS-3 Snyderman Hart Berg Kiricuta Hall
Oral cavity (Ref. 6) 8 4 1 3 7 2 6 5
Tonsil (Ref. 13) 8 4 7 1 3 6 2 5
Larynx – glottic (Ref. 9) 4 2 7 5 3 1 6
Larynx – supraglottic (Ref. 9) 7 2 3 4 1 6 5
Hypopharynx 5 3 6 1 5 8 2 7
Mean 6.4 3 4.8 2.8 3.6 4.6 4.2 5.7
Abbreviations: UICC, Union Internationale Contre le Cancer; TANIS, T and N Integer Score.
Note: The classification with the best prognostic performance has the lowest ranking score for each site. *UICC fourth or sixth edition.
Table 6. Consistency, discrimination, percent variance explained, outcome prediction, and balance for each stage grouping scheme.
UICC/AJCC (6e) TANIS-7 TANIS-3 Snyderman Hart Berg Kiricuta Hall
Hazard consistency, % 5.8 5.2 7.7 5.8 8.1 9.6 5.6 5.1 Score 0.31 0.04 1.16 0.31 1.33 2 0.22 0 Rank 4.5 2 6 4.5 7 8 3 1 Hazard discrimination 0.42 0.39 0.59 0.63 0.64 0.51 0.66 0.40 Score 1.78 2 1.52 0.22 0.15 1.11 0 1.93 Rank 6 8 4 3 2 5 1 7 Outcome prediction, % PVE 11.0 11.2 9.8 10.7 9.8 7.7 11.1 10.3 Score 0.06 0 0.4 0.14 0.4 1 0.03 0.28 Rank 3 1 6.5 4 6.5 8 2 5 Slope 19.4 18.8 11.2 18.5 13.3 12.1 18.6 19.0 Score 0 0.07 1 0.11 0.74 0.89 0.10 0.05 Rank 1 3 8 5 6 7 4 2 Balance 70.7 53.8 19.2 14.1 35.9 54.4 42.6 58.3 Score 1 0.70 0.09 0 0.39 0.71 0.50 0.78 Rank 8 5 2 1 3 6 4 7
Overall weighted score 3.15 2.81 3.17 0.78 3.01 5.71 0.85 3.04
Overall rank 5 3 6 1 4 8 2 7
70% of the patients, although 1 center only scanned 30% of patients. Barbera et al24reported the differences in the rates of CT scans by treat-ment center across Ontario for laryngeal cancer patients and found that 20.2% of patients had stag-ing assignments changed from the clinical stage assignment with the use of CT. They also reported that most of the changes were increases in stage se-verity, especially into the T4 group. It is likely, espe-cially with the high incidence of extensive disease in hypopharyngeal cancer, that some patients will be ‘‘understaged,’’ but the impact of these errors may not be significant because the overall T and N category distribution did not differ significantly among centers (T category, p 5 .24; N category, p 5 .54) and Barbera et al did not find that the predic-tive value of clinically based stage assignment improved with CT assignment. Finally, the impact of these potential errors would extend across all staging classifications, likely without bias.
The second limitation of this study is the small number of patients in some subgroups and groups despite being the largest reported study (n 5 596) on the stage distribution of patients with hypo-pharyngeal cancer. A larger study might find some of these cells to be of more prognostic signifi-cance. The small numbers of patients in uncom-mon combinations of T and N categories and stage groups is a weakness of the TNM-based system in general and of all stage grouping systems.
The third potential limitation is the coding of cancer of the hypopharynx by the OCR. Because of problems of site assignment with confusing ad-jacent anatomical sites, some true cases, miscoded as supraglottic or oropharyngeal cancers, would have been missed.
CONCLUSION
If patients are not optimally grouped based on prog-nosis, the true treatment effectiveness may be hidden. The UICC/TNN stage group classification, although successful in creating statistically dis-tinct groups, did not perform as well as other stage grouping systems, continuing a theme that has been reported previously. Researchers are encour-aged to publish other data sets with similar analy-sis to encourage the UICC/TNM organization to consider improvement of the stage group system for head and neck cancers.
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