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OSNA in lung cancer

In non-small cell lung cancer (NSCLC), surgery remains the best chance of cure for early stage patients. However, up to 30% of those patients experience recurrences after surgery [1]. This is in part due to occult metastases in the lymph nodes that are missed by standard histology, which analyses only a small portion of the node [2]. This is a major concern since nodal status determines patient survival and guides intra- and post-operative treatment decisions. Furthermore, the clinical trend is moving toward de-escalation of surgical treatment with the aim to improve patient quality of life and to reduce comorbidities, such as poor pulmonary and cardiac function.

Unlike histopathological methods, OSNA (one-step nucleic acid amplification) enables a fast, molecular whole-node analysis. It provides nodal staging and prognosis accuracy as well as an improved basis for personalised fully-informed treatment decisions in the most common subtypes [3] of lung cancer. Thanks to a fast and accurate intra-operative staging, OSNA can enable pioneer thoracic surgeons and pathologists who have already implemented marginal or sentinel lymph node biopsy in lung cancer to reduce excision radicality (lung tissue and lymph nodes) in node-negative cases.

OSNA offers a molecular analysis by quantifying the expression of CK19 mRNA, reflecting the metastatic burden in the LN. Among various markers with high expression in lung cancer, CK19 reported the best performance to detect LN metastases [4]. OSNA has been compared to conventional histology and resulted in high concordance (96.2%) and sensitivity (100%)[5-6]. By detecting more LN metastases than histology, OSNA led to a higher pTNM stage in 22% of patients[7].

OSNA – superior diagnostic information

  • Confidence for the pathologists to not overlook metastases
  • Enables immediate and fully-informed decisions already during surgery
  • Offers an improved basis for personalised treatment decisions
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22848 Norderstedt

Germany

+49 (40) 527 26 0

+49 (40) 527 26 100

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