Assessment of intrathoracic lymph nodes by FDG PET/CT in patients with asbestos-related lung cancer

How I treat refractory/relapsed diffuse large B-cell lymphomas with CD19-directed chimeric antigen receptor T cells

Chimeric antigen receptor (CAR) T cells targeting CD19 represent a promising salvage immunotherapy for relapsed/refractory diffuse large B-cell lymphoma (R/R DLBCL), offering ~40% of long-term responses. In everyday clinical practice, haematologists involved in CAR T cell treatment of patients with R/R DLBCL have to deal with diagnostically complex cases and difficult therapeutic choices. The availability of novel immunotherapeutic agents for R/R DLBCL and recent advances in understanding CAR T-cell failure mechanisms demand a rational approach to identify the best choice for bridging therapy and managing post-CAR T-cell therapy relapses. Moreover, positron emission tomography/computerised tomography may result in false-positive interpretation, highlighting the importance of post-treatment biopsy. In this review, we discuss all above issues, presenting four instructive cases, with the aim to provide criteria and new perspectives for CAR T-cell treatment of DLBCL.

Development and validation of nomograms based on clinical characteristics and CT reports for the preoperative prediction of precise lymph node dissection in lung cancer

OBJECTIVE

To develop and validate nomograms for preoperative prediction of precision lymph node (LN) dissection in lung cancer.

PATIENTS AND METHODS

The prediction models of each group LNs (LNx) were developed in a primary cohort that consisted of 1380 patients with clinicopathologically confirmed lung cancer. Clinical characteristics and CT reports were extracted. Patients with LNx dissection were divided into training cohort and testing cohort. Nomograms were built through univariate and multivariate regression analysis in the training cohort and internally verified in the testing cohort. The accuracy of the models was verified by constructing survival analysis in patients without LNx dissection.

RESULTS

Due to the lack of sufficient patients for LN1, 8, 13, a total of 10 nomograms were constructed in this study, including LN-2 ∼ 7, 9 ∼ 12. According to the nomogram of each group LN, the most common independent risk factors predicting LN status were CT-reported lymphadenectasis, tumor diameter and location, and the others include age, gender, and whether there were multiple nodules, etc. All models showed good discrimination, with the average C-index of 0.738 in the training cohort and 0.707 in the testing cohort. Survival analysis in patients without LNx dissection all showed the high accuracy of each nomogram to predict LN metastasis status and TNM staging.

CONCLUSION

We constructed nomograms to predict the metastasis status of each group of lymph nodes based on clinical characteristics and CT reports. Surgeons can accurately determine the extent of lymph node dissection in patients with lung cancer based on our nomogram models before surgery.