Pathology review identifies frequent misdiagnoses in recurrent classic Hodgkin lymphoma in a nationwide cohort: implications for clinical and epidemiological studies.

Patients treated for classic Hodgkin lymphoma (CHL) have a reported 13-fold increased risk of developing subsequent non-Hodgkin lymphoma (NHL). In light of the growing awareness of CHL mimickers, this study re-assesses this risk based on an in-depth pathology review of a nationwide cohort of patients diagnosed with CHL in the Netherlands (2006-2013) and explores the spectrum of CHL mimickers. Among 2,669 patients with biopsy-proven CHL, 54 were registered with secondary NHL. On review, CHL was confirmed in 25/54 patients. In six of these, the subsequent lymphoma was a primary mediastinal B-cell lymphoma/mediastinal gray zone lymphoma, biologically related to CHL and 19/25 were apparently unrelated B-cell NHL. In 29/54 patients, CHL was reclassified as NHL, including T-cell lymphomas with secondary Hodgkin-like B-blasts (n=15), Epstein Barr virus-positive diffuse large B-cell lymphoma (n=8), CD30+ T-cell lymphoma (n=3) and indolent B-cell proliferations (n=3). Higher age, disseminated disease at presentation, extensive B-cell marker expression and association with Epstein-Barr virus were identified as markers to alert for CHL mimickers. Based on these data, the risk of developing NHL after CHL treatment was re-calculated to 3.6-fold (standardized incidence ratio 3.61; confidence interval: 2.29-5.42). In addition, this study highlights the clinicopathological pitfalls leading to misinterpretation of CHL and consequences for the care of individual patients, interpretation of trials and epidemiological assessments.

Prognostic and predictive biomarkers in lung cancer. A review.

In lung cancer, clinically relevant prognostic information is provided by staging. Staging forms the basis for the treatment options and this is briefly summarized in the introduction. Epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase are biomarkers used for prediction of chemotherapy and prediction of targeted treatment. Other driver biomarkers in lung cancer (point mutations and rearrangements in specific genes including Her2, BRAF, NUT, MET, ROS1, DDR2, FGFR1, KRAS, and PTEN) might potentially provide additional information for clinical decision making. Owing to the low prevalence of mutations in predictive markers, patient numbers in studies are usually small, with the exception of EGFR. These mutations increase our understanding of the biology of lung cancer. Mutation analysis as a basis for treatment choice can have an impressive clinical impact with dramatic responses. However, as yet the impact of these approaches to overall survival is less striking.