The tumor/node/metastasis (TNM) staging system collaboratively developed and maintained by the American Joint Committee on Cancer and the International Union for Cancer Control plays a critical role in the evaluation and management of patients diagnosed with a range of different types of cancers [1]. Accurate staging based on assessment of the extent of anatomic spread of cancer at the time of diagnosis helps to determine prognosis based on correlated survival rates. Staging also helps to guide the planning of treatment, facilitates communication between providers working in different disciplines, and serves as the basis for identifying patients who may be eligible for enrollment in clinical trials [2].

Criteria for stage assignments have been established for 47 different types of cancers. Determination of a patient’s stage is based on the classification of three principal components that may be assessed at the point of diagnosis to determine a clinical stage, or after definitive surgery to determine a pathologic stage. Assignment of a tumor (T) classification ranging from T0-T4(a-d) is based on assessment of the size and extent of contiguous spread of the primary tumor. Assignment of a node (N) classification ranging from N0-N3(a-c) is based on assessment of the extent of spread of tumor to regional draining lymph nodes. Assignment of a metastasis (M) classification ranging from M0-M1(a-b) is based on assessment of the presence or absence of distant metastases (Table 1).

Additional prognostic factors that have proven to be significant in the staging of specific types of cancers include tumor grade, tumor location, mitotic rate, risk factors, histologic scores, and biochemical tumor marker levels. Compiled groupings of T, N, M, and prognostic factor classifications are sorted into tabular arrays that are stratified to define stages characterized as anatomic stages or prognostic groups ranging from 0-IV(A-C) in order of declining prognosis (Table 2).

The conventional approach to staging involves (1) selecting appropriate T, N, M, and prognostic factor classifications, (2) combining these classifications to generate a TNM grouping, and (3) locating this TNM grouping in the array of possible combinations to determine a corresponding stage. This combinatorial approach is inherently inefficient due to the fact that successive tumor and node classifications for different types of cancers are not always graded or mutually exclusive. Assignment of a T1 classification may be based on measurement of the diameter of the primary tumor, while assignment of a T2 classification may be based on identification of a pattern of local invasion. Assignment of an N2 classification may be based on confirmation of spread of tumor to a specific group of regional draining lymph nodes, while assignment of an N3 classification may be based on tabulation of the number of involved lymph nodes. As a result, accurate staging relies on scrupulous review of the criteria for each T, N, and prognostic factor classification to ensure that correct assignments are made.

An alternative approach to staging that seeks to optimize the efficiency of the process is predicated on the notion that unambiguous selection or exclusion of a T, N, M, or prognostic factor classification may serve to constrain the number of subsequent classifications that need to be reviewed to identify a correct TNM grouping. If a specific T, N, M, or prognostic factor classification can be selected based on review of its criteria, then any TNM groupings that do not include that classification can be excluded from further consideration. Alternatively, if a specific classification can be excluded without reservation, then any TNM groupings that include that classification can be excluded from further consideration. The set of TNM groupings that remain as viable options after a specific classification has been selected or excluded will most often encompass a restricted subset of classifications. In its elaboration, this exclusionary approach may effectively serve to minimize the number of classifications that need to be reviewed to accurately determine a patient’s stage.

A Web-based app configured to demonstrate this approach to staging was developed as an instructional aid for trainees. A version coded in ActionScript 3.0 was iteratively adapted to incorporate the following key features [3]:

Users are prompted to select a tumor type to begin a staging exercise. Some tumor types require selection of secondary options which may include identification of a tumor subtype, anatomic location, age limit, or phase of staging (clinical vs pathologic). Selection of a tumor type shifts to a display that includes a grid of anatomic stage listings and a prompted yes/no question corresponding to the first ranked T, N, M, or prognostic factor classification (Figure 1).

Clicking a Yes or No button to answer the question will select or exclude the classification. If a specific classification is known at the point of entry, it can be directly selected by clicking on a corresponding entry in the grid of anatomic stage listings. Selection or exclusion of a classification triggers fading of nullified TNM groupings and cycling of the exclusionary algorithm. Subsequent prompted yes/no questions will appear in sequence until the set of TNM groupings has been narrowed to delimit a single TNM grouping and/or a specific anatomic stage. If a specific anatomic stage has been delimited with multiple TNM groupings that persist as viable options, a “Complete” button can be clicked to prompt further selection and exclusion. When a single TNM grouping has been identified, a terminal display lists the anatomic stage and T, N, M, and prognostic factor classifications with their corresponding criteria. Forward and back arrows can be clicked to scroll through the sequence of classifications with highlighting of selected answers and concordant enhancement and fading of associated TNM groupings.

All 30 of the enrolled subjects completed the entire survey. Subjects expressed a high level of agreement with each of the 12 statements. No “Strongly disagree” responses were registered. The median level of agreement was “Agree” for 7 of 12 statements and “Strongly agree” for the remainder with minimal dispersion (Table 4).

The median overall usefulness rating was 9 (25-75 interquartile range 8-9.75). Eighteen subjects elected to enter free text comments that ranged from general impressions of the app to specific criticisms of its navigability and functionality. While most of the general impressions were favorable (“Great application”, “Very useful clinically”), a few subjects expressed reservations about the limited scope of the app (eg, “It would be nice to have links to the appropriate staging guidelines or references”, “It would be great to see some of the hematologic malignancies like myeloma and lymphoma added”). The majority of the specific criticisms focused on problems that subjects experienced when trying to use the browser back button to navigate between screens. This problem is commonly encountered with the first use of platform-independent apps that run in browser plug-ins [4]. Internal navigation controls were moved to more intuitive locations in subsequent iterations as a result. A few of the subjects found staging exercises that began with prompted questions about the presence of distant metastases to be disconcerting at first, but on reflection they expressed an understanding of the logic of this approach.