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HomeAmerican Journal of Clinical Pathologyindex/list_12094_8Quality of Anatomic Staging of Breast Carcinoma in Hospitals in the United...

Quality of Anatomic Staging of Breast Carcinoma in Hospitals in the United States, With Focus on Measurement of Tumor Dimension

Abstract and Introduction

Abstract

Objectives: We investigated the accuracy of clinical breast carcinoma anatomic staging and the greatest tumor dimension measurements.

Methods: We compared clinical stage and greatest dimension values with the pathologic reference standard values using 57,747 cases from the 2016 US National Cancer Institute Surveillance, Epidemiology, and End Results program who were treated by surgical resection without prior neoadjuvant therapy.

Results: Agreement for clinical vs pathologic anatomic TNM group stage, overall, is 74.3% ± 0.4%. Lymph node N staging overall agrees very well (85.1% ± 0.4%). Based on tumor dimension and location, T staging has an agreement of only 64.2% ± 0.4%, worsening to 55% without carcinoma in situ (Tis) cases. In approximately 25% of cases, pathologic T stage is higher than clinical T stage. The mean difference in the greatest dimension is 1.36 ± 9.59 mm with pathologic values being generally larger than clinical values; pathologic and clinical measurements correlate well. T-stage disagreement is associated with histology, tumor grade, tumor size, N stage, patient age, periodic biases in tumor size measurements, and overuse of family T-stage categories. Pathologic measurement biases include rounding and specimen-slicing intervals.

Conclusions: Clinical and pathologic T-staging values agree only moderately. Pathologists face challenges in increasing the precision of gross tumor measurements, with the goal of improving the accuracy of clinical T staging and measurement.

Introduction

Cancer stage describes the extent and severity of the disease, offers prognostic information, and informs treatment decisions, which require that stage evaluation be accurate. Breast carcinoma (BC) is a leading cancer for which the American Joint Committee on Cancer’s cancer stage now includes biomarkers along with the traditional anatomic stage, which together form a prognostic stage. Anatomic staging preserves a way to categorize patients with BC worldwide under the Union for International Cancer Control guidelines, which do not include biomarkers.[1,2] Accuracy of the prognostic stage is worse if its anatomic component is not accurate. Postsurgery pathologic staging and measurements are the reference standard to which corresponding radiologic clinical values aspire. However, before surgery, the clinical anatomic TNM stage (group stage) and tumor dimension (T stage) determine prognosis and impact treatment plans and patient monitoring.[3–10] The selection of neoadjuvant chemotherapy and radiotherapy and the prediction of their value are based partly on measurements for clinical anatomic stage.[10] Accurate clinical data are also critical to optimize radiology algorithms. However, there is a lack of studies analyzing the accuracy of clinical anatomic staging under hospital conditions to improve its accuracy.[11,12] The accuracy of clinical staging is determined by comparing clinical values with pathologic values.[13,14] Accordingly, the more precise pathologic staging is, the more it can promote improved clinical staging and measurement accuracy. For instance, if the reported pathologic tumor size is at a stage cutoff value, the assigned pathologic stage may create ambiguity by over- or underestimating predicted survival or affecting the optimization of software algorithms to delineate or characterize a tumor.

The T-stage component of TNM ideally measures the greatest dimension (“dimension” or “size”) of the invasive component of a primary tumor, and T-stage T4 subcategories include tumor location and inflammatory carcinomas.[3–6] N stage is the ipsilateral lymph node involvement. Patient workup and planned treatment can be different at major thresholds for the clinical stage category.[3–7,15] For example, patients whose BC is assessed as clinical T-stage (cT) T2 to T4 may receive neoadjuvant therapy. Patients with T0 to T1 and N0 disease may undergo partial mastectomy, wide local excision, or quadrant resection, whereas those with T2 to T3 and N0/N1 disease may have simple mastectomy and those with T4 or N2 may undergo modified radical mastectomy.

Increasing diagnostic accuracy has occurred hand in hand with increasing treatment precision. Breast cancer treatment has evolved from radical mastectomy to partial mastectomy with or without radiation therapy, depending on stage and histologic findings. Systemic therapy such as definitive chemotherapy may be administered without surgery, and there is no traditional postsurgery pathologic staging. Clinical staging may have no pathologic confirmation. With increased resolution, 3-dimensional images have been analyzed by radiologists or computer algorithms that detect, delineate, and measure breast tumors. Diagnostic radiography and biopsy results generate the cT and clinical N (cN) stages. Such evolution requires accurate and precise clinical staging measurements, along with precision data sets to calibrate the techniques and algorithms. Future therapy refinements depend on staging refinements; for example, subcategorizing T2 into T2a and T2b improves prognosis and guides adjuvant therapy.[16] Refining clinical tumor size measurement improves prognosis and validates other prognostic parameters related to dimension (eg, tumor volume approximately equivalent to dimension-cubed) when there is no pathologic counterpart.

The study objectives have been (1) to ascertain the accuracy of clinical BC anatomic staging at US hospitals by comparing the pathologic and clinical staging data; (2) to quantify agreement precisely but with user-friendly arithmetic techniques; (3) to note sources of disagreement that, to our knowledge, are not described in previous BC staging studies; (4) to investigate sources of unexpected measurement bias in the pathologic BC tumor dimension; and (5) to provide suggestions for future measurement practices and research.

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