S24 Assessment of histopathological and resection margin data in post-operative non-small cell lung cancer patients

Autor: J. Rao, H.V. Gleeson, D. Hopkinson, John G. Edwards, H. George, Laura Socci, S. Tenconi
Rok vydání: 2019
Předmět:
Zdroj: An update in screening for lung cancer.
Popis: Background Surgery remains the mainstay treatment modality in patients with Non-Small Cell Lung Cancer (NSCLC), however the benefits of surgery when resectability becomes borderline is contentious. Resection status (R-Status) reflects how effective the surgery is, which consequently impacts prognosis and potentially, further treatment. Methods Patients who underwent curative resection for NSCLC during 07/04/2005 to 30/03/2017 were eligible for this study, forming a cohort of 1,804 patients, once exclusion criteria were applied. Electronic medical records and histopathology data was retrospectively reviewed which formed the database. The IASLC proposed R-Status criteria was evaluated and consisted of: Number of N2 stations explored; Systematic or Lobe- Specific Lymph Node Dissection: Status of the highest station; Extracapsular Extension; and Bronchial Carcinoma In-Situ. Patients were then re-assigned R-Status based on these criteria and the revised categories of R0, R(Un), R1 and R2 were analysed to establish their prognostic and survival impact. Results Initially, there were 1642 R0, 155 R1 and 5 R2 cases. After reassignment according to the IASLC proposed definition, there were 673 R0, 959 R(un), 167 R1 and 5 R2. Less than Systematic or Lobe-Specific Lymph Node dissection was the primary reason for reassignment to R(Un) in 90.3% of cases. There was significant evidence of an association between proposed R-Status and T-Category, (p Conclusion These data confirm that R descriptors have prognostic relevance and the proposed uncertain resection stratifies between R0 and R1. The 26-month difference in survival between R0 and R(Un) in node positive cases, demonstrates the importance of these proposals and the need for further prospective data collection to validate these findings. Therefore, R(un) status should be considered for inclusion in the RCPath Minimum Dataset and the National Lung Cancer Audit as a quality outcome measure.
Databáze: OpenAIRE