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(Chest. 2000;117:1247-1255.)
© 2000 American College of Chest Physicians

Prognostic Value of Stage Grouping and TNM Descriptors in Lung Cancer*

Gianfranco Buccheri, MD and Domenico Ferrigno, MD

* From the Cuneo Lung Cancer Study Group at the "S. Croce and Carle" General Hospital, Cuneo, Italy.

Correspondence to: Gianfranco Buccheri, MD, Divisione di Pneumologia, Ospedale "S. Croce e Carle," Cuneo I-12100, Italy; e-mail: buccheri{at}culcasg.org


   Abstract
TOP
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Study objectives: The International Staging System for Lung Cancer (ISSLC) was revised in 1997. Validation studies are numerous but include only selected surgical patients. This study aims to verify the following: (1) the reliability of the ISSLC in an unselected lung cancer population; (2) the likely improvement in prognostic capability of the new classification; and (3) the possibilities for further improvements.

Design: Analysis of a single institution database over a 16-year period from 1983 to 1998.

Setting: Community-based hospital and second referral level institution for a province of 500,000 people.

Patients: The study included 1,296 consecutive patients (1,117 men), with pathologically documented lung cancer (46% with squamous cell cancer), staged both clinically (77%) and pathologically (23%), and treated, for the most part, with chemotherapy (52%).

Interventions: Anthropometric, clinical, and laboratory data were recorded prospectively. Survival analysis was performed by the Kaplan-Meier method and Cox multivariate regression analysis.

Measurement and results: The 1997 revised ISSLC classification fit well with the cohort studied. Each stage and substage significantly differed from each other, except for stage IIA. In this stratum, there were only 13 patients. Comparing the 1986 and the 1997 classifications, no substantial differences were observed (log-rank statistics, 295 vs 293, respectively; p < 0.0001). Independent of the classification used, the Cox models were always highly predictive of the outcome. The only way to increase their efficiency was to replace the variable stage with the original TNM descriptors.

Conclusions: Since grouping different TNM subsets into one stage is not really helpful, we might choose to use TNM descriptors in clinical practice and in research.

Key Words: classification • lung neoplasm • multivariate analysis • neoplasm staging • non-small cell lung cancer • prognosis


   Introduction
TOP
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
The staging of lung cancer is crucial in everyday practice and in clinical research. It helps in the evaluation of the prognosis, serves as a basis for exchanging information among clinicians and researchers, and guides the choice of the most appropriate treatment. The International Staging System for Lung Cancer (ISSLC), adopted by the Union Internationale Contre le Cancer and the American Joint Committee on Cancer, provides a common alphabet for lung cancer specialists in any part of the world.1 2 3 4 5 The current version was introduced in 1997 by Mountain,6 and it replaced his prior 1986 classification.7 The next revision is foreseen for the year 2007,8 and, for that time, new reports will be helpful to improve further an already excellent system.

Starting from this premise, we undertook the current data analysis to respond to three main questions. The first question is how the 1997 staging system works when applied to an unselected population of lung cancer patients. Such patients are often inoperable at presentation and, thus, are clinically staged. About 20% of these patients may undergo an intervention, but the surgical exploration may not be as accurate as it was in the 5,319 patients who formed the basis for the new staging evaluation.6 To what extent can we generalize from the information that was validated in the surgical wards of highly qualified and hyperselective cancer centers? The second question is whether the new 1997 staging system has improved the overall prognostic capability, as compared with the 1986 classification. Apart from moving "satellite" tumor nodules found within the lobe of the primary tumor into the T4 category, the 1997 staging system regards almost exclusively a more complex grouping of the TNM descriptors.6 Survival rates may differ significantly between stages,9 but the overall improvement in prognostic capability of the new staging classification might be modest or even null. Finally, we were interested in exploring other ways of considering TNM descriptors that might ensure a better prognostic assessment.


   Materials and Methods
TOP
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Recruitment of Patients
In 1983, a group of chest physicians decided to devote their professional interest to the study of lung cancer. The group, who later became known as the Cuneo Lung Cancer Study Group (referred to as "the group"), is still active at the A. Carle Hospital of Chest Diseases, in the city of Cuneo, Italy. The A. Carle hospital, currently named S. Croce and Carle Hospital, then was designated as a Hospital of National Importance and serves the whole Cuneo Province as a second referral institution. Among the prime acts of the group is the creation of a clinical database for patients with carcinoma of the lung. All lung cancer patients who were referred to a physician in the group were managed uniformly. A minimum set of 44 variables, including TNM descriptors and a computer-derived stage of disease, was available for each new patient with a cytologically or pathologically documented diagnosis. Small cell lung cancers (SCLCs) were treated in the same way as non-small cell lung cancers (NSCLCs). In fact, as also suggested by Clifton F. Mountain in introducing the new revised stage classification,6 the TNM staging is more informative than the classic division in limited/extensive diseases. Every 4 to 5 years, the structure of the database is modified and upgraded to newer, more powerful software; the number of variables recorded has progressively increased to include hundreds of variables at the present time. However, the core variables of the early database remained unchanged, allowing careful analyses and time-related comparisons. At the end of December 1998, 1,296 patients with lung cancer were seen, and they form the basis for this report (Table 1 ).


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  		Table 1.. Anthropometric and Clinical Characteristics of the Cohort*

 
Diagnostic Techniques, Therapeutic Management, and Documentation
Diagnostic and staging techniques varied considerably during the 16 years of recorded data, although the frequent coexistence of an experimental protocol that was aimed at optimizing diagnostic and staging procedures ensured an overall assessment that was performed well. As shown in Table 2 , a thoracic CT was performed in almost all patients. In addition to that, an abdomen and brain CT were requested in 877 patients. A bone scan was performed in 32% of the entire cohort for a variety of reasons, including clinical demand, SCLC diagnosis, presurgical evaluation, and investigative diagnostic protocols. Such clinical evaluation, which also included physical examination, routine laboratory tests, and the measurement of serum tumor markers,10 11 was supplemented by many nonroutine studies, including 104 67Ga scans 12 and 142 anti-carcinoembryonic antigen (CEA) monoclonal antibody scintigraphies.13 14 In contrast with several carefully staged patients, there were others for whom performing the baseline three-organ CT was impossible or unreasonable. Also, a small but significant number of patients refused to undergo what they considered a distressing test. As a result, in 5% of the 1,296 patients (Table 1) Go , the quality of the staging was rather poor and was based only on conventional radiology. On the other hand, the staging evaluation was confirmed either by thoracotomy or by a biopsy of distant metastases in 23% of the cohort.


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  		Table 2.. Investigations for Staging Evaluation

 

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  		Table 1A.. Continued*

 
As expected, only a relatively small fraction of patients was operable (19% of the cohort). Patients operated on locally did not undergo complete lymph node sampling on a routine basis. A few operable patients were directed to the thoracic surgeons at the Genoa Medical School (Professor G. Motta, head surgeon), either because the interventions required specific competence or simply on the patient’s demand. Chemotherapy was the most frequent treatment, which is consistent with our earlier recognition of its potential benefit.15 As shown in Table 1 , 671 patients (52%) received chemotherapy, either alone or in combination with other therapy. According to our experimental protocols, the regimens used did not vary remarkably during the last 16 years (Table 3 ). No patients, except those with SCLC, received second-line treatment.


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  		Table 3.. Chemotherapy Regimens Adopted During the 16-Year Study*

 
At the end of the diagnostic evaluation, a physician in the group reviewed clinical charts, including the description of the operation and the pathologic reports. He directly recorded the codified data that described the clinical status of and treatment plan for a patient on a computer. He recorded also the TNM descriptors, using the definitions that were in effect at that time. Then the computer, using an algorithm that was valid for the time, automatically generated the stage of disease. Since 1983, TNM definitions have changed, radically in 1986 and minimally in 1997, because of two consecutive revisions to the ISSLC.6 7 Therefore, to allow for homogeneous comparisons, we had to review the patients’ charts and upgrade their TNM variables. This work was done as soon as both Union Internationale Contre le Cancer and the American Joint Committee on Cancer formalized the revision of the ISSLC. Finally, diverse stage classifications, based on various ISSLC definitions or on a preliminary exploration of the data, were recalculated at the time of the statistical analysis. Three in situ lesions were incorporated into the T1 group. For this study, we decided to analyze only the 15 variables listed in Table 1 .

Statistical Analysis
Statistical analysis was performed using computer software (SPSS for Windows, version 8.0; SPSS Inc; Chicago, IL). Survival curves were generated with the Kaplan-Meier method 16 and were compared by means of the log-rank test.17 Multivariate survival analyses were made using the Cox regression model and were stratified by tumor cell type.18 Survival times were recorded from the time of the first visit for a suspected lung cancer to death or to May 1999, when a check on the status of patients believed to be alive was made. Since no reliable data about the causes of deaths were available, all the deaths were attributed to cancer. All statistical tests were two sided.


   Results
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
Descriptive Statistics
Table 1 summarizes the anthropometric and clinical characteristics of our sample, which included 1,296 patients (90% men) whose median age was 65 years. This information, along with cell type, stage-related variables, and treatment plans, was available for the whole population. In 16 patients, we did not record the Karnofsky performance status (KPS) score,19 which ranged from 20 to 100 in the remaining 1,280 patients and was quite poor (<= 60) in 18% of them. Nearly half of the 1,243 assessed patients complained of weight loss at their first evaluation. CEA and tissue polypeptide antigen (TPA) tests were performed in 1,136 and 1,115 patients, respectively (86 to 88% of patients, respectively). Despite this partial data deficiency, we decided to keep tumor markers in all multivariate models because of their intrinsic prognostic value.10 11 The median TPA serum level increased moderately, as would be expected for a mixed population containing different prognostic strata.11

Univariate Analyses of Survival
At the time of the survival analysis, 1,063 patients had already died, while 233 were still alive.

Figures 1 and 2 , complemented by Table 4 , show how well both the 1986 and 1997 stage classifications were able to discriminate between patients with similar prognoses. In addition, Table 4 shows the results of the same analysis limited to pathologically staged patients. Survival curves are displayed in logarithmic scale to emphasize differences between strata that would have been insufficiently appreciable otherwise.



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  		Figure 1.. Kaplan-Meier survival estimate for the whole cohort (1,296 patients) by stage of disease (1986 classification7 ).

 

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  		Table 4.. Results of Kaplan-Meier Analysis*

 
As shown, both stage groupings were highly predictive of survival both in the population as a whole and in the surgical subgroup. There was no difference as far as the cell type was concerned; in both SCLC and NSCLC, stage groupings were equally well correlated with the outcome. Of course, the clinical evaluation underestimated the real stage of disease, which explained why, in the earliest stages, survival times were shorter for all patients than for those in the surgical subgroup. However, the error was the same in both stage groupings and did not influence the comparison.

Differences between stages were highly significant (p < 0.0001) in both the 1986 and 1997 versions of the ISSLC. The log-rank statistics, which measure the equality of the survival distributions, were very similar between the 1986 and 1997 versions (ie, 295 and 293, respectively). Pairwise comparisons between adjacent stages were highly significant within the 1986 grouping (Fig 1) but were not always so significant in the 1997 version of the ISSCL (Fig 2) . For example, there were no differences between stages IB and IIA or between stages IIA and IIB, mainly due to the scarcity of patients in stage IIa (only 13 patients). Essentially, both stage groupings were highly and equally predictive. However, since the prognostic content of the 1997 grouping was split into more strata, each of them shared a lower prognostic capability.



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  		Figure 2.. Kaplan-Meier survival estimate for the whole cohort (1,296 patients) by stage of disease (1997 stage grouping6 ).

 
Taking into account our survival data (Table 4) , the simplest way to avoid the scarcity of patients in stage IIA would be by eliminating stage IB and by including the T2N0M0 tumor subset into stage IIA. Stage IIA, therefore, would be composed of both the T2N0M0 and T1N1M0 tumor subgroups, while stage IA would remain the only substage in stage I with T1N0M0 tumors. We explored such an alternative stage grouping (1997-modified stage), which, unfortunately, was completely useless, leading to an overall log-rank statistic of 292.

Multivariate Analyses of Survival
In a first run, the Cox proportional hazards regression analyses included only stage groupings to verify further the similarity of their prognostic significance (Table 5 ). The overall {chi}2 values were 281, 270, and 262, respectively, for the 1986, 1997, and 1997-modified groupings. Similarly, in the pathologically staged subgroup, the {chi}2 values were 91, 85, and 87, respectively, for each of the above groupings. All these values were highly significant (p < 0.0001).


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  		Table 5.. Summary of Cox Regression Analysis*

 
Then, six more co-factors (ie, age, sex, KPS score, weight loss, CEA level, and TPA level) were added to the model, increasing remarkably its prognostic capability. Such models were similar to the previous ones (same numbers of patients and variables), except for the stage grouping, which was, therefore, the cause of any possible differences. Again, the model constructed using the 1986 stage groupings was slightly better than its 1997 counterpart (Table 5) .

An alternative approach for stage groupings would be the use of TNM descriptors as they are, without grouping them into one derived variable. This implies handling three variables rather than one, with 32 potential combinations rather than the 7 in the last version of the ISSLC. However, the use of TNM descriptors would be simpler in clinical practice because it would not require the grouping of descriptors into one stage, and it could be even more helpful in clinical research, providing more details on tumor extension. Actually, when we replaced the stage of disease with the TNM descriptors, we found that the overall {chi}2 value increased to 422. This value increased further when the number and the sites of metastases were inserted into the equation (Table 5) .

Table 6 shows the model that best fit the data without excessively increasing the number of stage-related cofactors.


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  		Table 6.. Best Model (Predictability and Simplicity) by Cox Regression Analysis*

 

   Discussion
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
When we planned this study, we did not want to put the current stage grouping into question.7 As already mentioned, the last revision of the ISSLC has been approved by the major world cancer organizations 7 and is the basis for a common language among the oncologists of all nations. We believe that to have universally accepted rules for tumor classification is so important that it would be in our common interest to use them, even if they are not perfect. However, while using them, it is always possible to provide new raw material for the next revision.

We had the following three main purposes in planning this study: (1) to verify the validity of the last revision of the ISSLC in an unselected general population of lung cancer patients; (2) to compare the latest revision with the prior one; and (3) to explore the possibility of using better ways to accomplish the same objectives. We believe that our study has confirmed that the 1997 revision of the ISSLC is valid (with the possible exception of stage IIA) and generally applicable. Excluding perhaps the new biological factors,20 21 the stage of disease remains the best predictor of survival, 22 and this has been demonstrated once again. However, we saw no global improvement using the new staging classification, and, therefore, the answer to the second question we posed at the beginning of this article should be "no improvement." At least with respect to the prognosis, the new version of the ISSLC was no better than the previous one. Finally, our data have shown that, to improve our prognostic capability further, TNM factors should be used as they are, without grouping them into a stage of disease.

Many investigators have tested the new ISSLC by trying to fit their survival data,5 8 23 24 25 26 and many commentators already have discussed the merits and demerits of the introduced changes.2 3 4 8 9 27 Others have posed specific questions, including the opportunity of splitting stage I into two stages,5 moving T3N0M0 disease into stage IIB,5 25 assessing the role of satellite nodules,24 and reconsidering the need for a stage IIA.26 28

Inoue and colleagues 5 investigated the prognosis of 1,310 patients who underwent resection for NSCLC. These authors found significant differences in survival rates among patients with T1N0M0 and T2N0M0 tumors and no differences among patients with T2N1M0 and T3N0M0 tumors. They, like others,9 concluded that splitting stage I into stages IA and IA or putting T3N0M0 tumors into stage IIB was a sound decision. Mizushima and collaborators25 studied the appropriateness of the new ISSLC with special emphasis on the T3N0M0 tumor group.6 They analyzed 119 patients with NSCLC who had undergone pneumonectomy. Stage IIB included 14 patients with T3N0M0 tumors. In this group, the authors reported a 5-year survival rate of 69.6%, which was superior even to the 55.7% found in the T1N1M0 and T2N1M0 subsets. Mizushima et al25 also concluded that down-staging the T3N0M0 tumor group was appropriate. Our data are in fair agreement with these reports. In our group of nonsurgical patients, the division of stage I into stages IA and IB was capable of separating two strata with different prognoses. In addition, our patients with a T3N0M0 disease seemed to enjoy a relatively good outcome. In surgical patients, this was indirectly proved by the 91-week difference in median survival times that was observed between stages IIB and IIIA, from the new system, compared with the 32-week difference for stages II and IIIA, from the old system. However, TN status had to be confirmed pathologically, since, otherwise, the clinical underestimation of the real extent of disease hides (or even inverts) the effect. This is the reason why the above differences showed an opposite trend when all 1,296 patients were taken into account.

Yano and coworkers24 conducted a validation of the new ISSLC, concentrating on the inclusion of satellite nodes into the T4 category. They reviewed the clinical records of 352 patients with T2 to T4 resected lung cancers. No satellite nodules were found in 305 patients, one satellite nodule in the same lobe of the primary tumor was found in 39 patients, and a satellite nodule in another ipsilateral lobe was found in 8 patients. The authors reported no statistically significant differences in survival rates between patients without satellite nodules and patients with nodules within the ipsilateral primary lobe when the primary tumor was not advanced. For patients with tumors classified as T4, independent of the presence or absence of satellite nodules, the 5-year survival rate was 0% in the group without satellite nodes, 33.3% in the group with nodules within the primary lobe, and 0% in the group with nodules in nonprimary tumor lobes. The authors concluded that patients with satellite nodes in the primary tumor lobe might even elevate the survival rate of patients classified as having T4 tumors. We have no personal data to add, since we saw only four patients with pathologically documented satellite nodules of the primary ipsilateral tumor lobe and no other distant metastasis. According to our policy, they were soon reclassified as having T4M0 tumors. However, the debate clearly has scarce relevance for an unselected nonsurgical series.

However, the major limitation of the new ISSLC may be something different. In our cohort, there were very few patients classified as having T1N1M0 tumors or as having stage IIA disease, accounting for 13 (only 8 of whom had pathologic confirmation) of 1,296 patients (1% of the total population). Such low occurrence is the probable cause of the nonsignificant differences observed between the survival distributions of stages IIA and IB and of stages IIA and IIB. This observation is not new.26 28

There are multiple goals for the use of a cancer staging system. Using the words of Leong and colleagues,9 the goals are the following: (1) to standardize the description of disease; (2) to reflect prognosis; (3) to direct treatment; and (4) to facilitate research and the comparison of results. With this study, we have addressed the prognostic value of the refining of the ISSLC.6 We believe that the other purposes of a staging system are consequential, since the ability of a staging system to identify patients with similar prognoses is the premise for its use both in research and in clinical practice. A better characterization of the different prognostic strata was, indeed, the main objective of the revision of the ISSLC,6 which was pursued by splitting stages into substages and by reorganizing the TNM descriptors. However, this rearrangement seems to have failed in its goal of increasing the overall prognostic capability of the staging system, which ultimately depends on how accurately the TNM descriptors portray the disease. Because a derived variable cannot be more informative than the parental variables, it should be impossible to go beyond the TNM factors with any of their possible combinations. As acutely observed by Margolis,29 we do not need to group multiple and different TNM subsets into a unique stage. One might simply denote the TNM subsets that are being dealt with and calculate the stage at a later time, if necessary. This would be more responsive to the changes in clinical and research environments. It would avoid additional, nonessential classifications and would offer the greatest potential for a prognostic assessment and the best specificity for the individuation of groups at similar risk. In conclusion, there is a message from this study that we would like to emphasize. The message is that there is no need to place the various TNM subsets into stage groups. The next committee for the revision of the ISSLC might like to consider the pros and the cons of maintaining such a classification.


   Acknowledgements
 
The authors thank Lorena Gribaudo and Anna Merlo, nurses in the outpatients unit, for the invaluable help and support. The authors also thank Mr. Loren Parfitt for English editing.


   Footnotes
 
Abbreviations: CEA = carcinoembryonic antigen; ISSLC = International Staging System for Lung Cancer; KPS = Karnofsky performance status; NSCLC = non-small cell lung cancer; SCLC = small cell lung cancer; TPA = tissue polypeptide antigen

Received for publication July 1, 1999. Accepted for publication January 12, 2000.


   References
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

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 Eur Respir JHome page
G. Buccheri and D. Ferrigno
Lung cancer: clinical presentation and specialist referral time
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A. Lopez-Encuentra, J. L. Duque-Medina, R. Rami-Porta, A. G. de la Camara, and P. Ferrando
Staging in Lung Cancer: Is 3 cm a Prognostic Threshold in Pathologic Stage I Non-small Cell Lung Cancer? : A Multicenter Study of 1,020 Patients
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 Ann. Thorac. Surg.Home page
T. Naruke, R. Tsuchiya, H. Kondo, and H. Asamura
Prognosis and survival after resection for bronchogenic carcinoma based on the 1997 TNM-staging classification: the Japanese experience
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