Trends and outcome of neoadjuvant treatment for rectal cancer: A retrospective analysis and critical assessment of a 10-year prospective national registry on behalf of the Spanish Rectal Cancer Project

Introduction: Preoperative treatment and adequate surgery increase local control in rectal cancer. However, modalities and indications for neoadjuvant treatment may be controversial. Aim of this study was to assess the trends of preoperative treatment and outcomes in patients with rectal cancer included in the Rectal Cancer Registry of the Spanish Associations of Surgeons. Method: This is a STROBE-compliant retrospective analysis of a prospective database. All patients operated on with curative intention included in the Rectal Cancer Registry were included. Analyses were performed to compare the use of neoadjuvant/adjuvant treatment in three timeframes: I)2006–2009; II)2010–2013; III)2014–2017. Survival analyses were run for 3-year survival in timeframes I-II. Results: Out of 14, 391 patients, 8871 (61.6%) received neoadjuvant treatment. Long-course chemo/radiotherapy was the most used approach (79.9%), followed by short-course radiotherapy ± chemotherapy (7.6%). The use of neoadjuvant treatment for cancer of the upper third (15-11 cm) increased over time (31.5%vs 34.5%vs 38.6%, p = 0.0018). The complete regression rate slightly increased over time (15.6% vs 16% vs 18.5%; p = 0.0093); the proportion of patients with involved circumferential resection margins (CRM) went down from 8.2% to 7.3%and 5.5% (p = 0.0004). Neoadjuvant treatment significantly decreased positive CRM in lower third tumors (OR 0.71, 0.59–0.87, Cochrane-Mantel-Haenszel P = 0.0008). Most ypN0 patients also received adjuvant therapy. In MR-defined stage III patients, preoperative treatment was associated with significantly longer local-recurrence-free survival (p < 0.0001), and cancer-specific survival (p < 0.0001). The survival benefit was smaller in upper third cancers. Conclusion: There was an increasing trend and a potential overuse of neoadjuvant treatment in cancer of the upper rectum. Most ypN0 patients received postoperative treatment. Involvement of CRM in lower third tumors was reduced after neoadjuvant treatment. Stage III and MRcN + benefited the most

A comparative study of multispectral image classifiers: Applications to classification problems with high-dimensional data and high-overlapping spectral signatures. Simulation of . . .

Classification of high-dimensional images is of the almost interest in Remote Sensing applications. Storage space, and specially the computational effort required for classifying this kind of images are the main drawbacks in practice. Moreover, it is well known that a number of spectral classifiers may not be useful-even not valid- in practice when the training sets are high-overlapping in the representation space. In this paper, we compare a large number of spectral classifiers for classifying high-dimensional images. We selected a number of different classifiers, both parametric and nonparametric classifiers, in order to made an in depth comparative study. We also propose the use of different spectral classifications as initial classifications to be used by a contextual classifier (ICM, in this case) in order to obtain some interesting combinations of spectral-contextual classifiers for Remote Sensing image classification with an acceptable trade-off between the accuracy of the final..

The Performance of Regularized Discriminant Analysis Versus Non-Parametric Classifiers Applied to High-Dimensional Image Classification.

Classification of very high dimensional images is of the almost interest in Remote Sensing applications. Storage space, and mainly the computational effort required for classifying this kind of images are the main drawbacks in practice. Moreover, it is well known that a number of spectral classifiers may not be useful-even not valid- in practice for classifying very high dimensional images. Even if they are valid, they do not provide high accuracy classifications when the training sets are high-overlapping in the representation space due to the shape of the decision boundaries they impose. In these cases, it is preferable to adopt a classifier that may adjust the decision boundaries in a better fashion. To do so, we compare classification based on regularized discriminant analysis (RDA) with a number of nonparametric classifiers. We shall use two synthetical image databases, consisting of high-dimensional images for testing test the performance of the classifiers. These datasets have b..

A Comparison of Multispectral Image Classifiers Using High-Dimensional Simulated Data Sets

Classification of very high dimensional images is of the almost interest in Remote Sensing applications. Storage space, and mainly the computational effort required for classifying this kind of images are the main drawbacks in practice. Classical spectral classifiers may not be useful-even not valid- in practice to be used for classifying very high dimensional images. In this paper, we perform a comparative study of a number of spectral classifiers for classifying very high dimensional images. Our study concentrates on two synthetical image databases, created from scratch by using a procedure proposed by the authors. Dimensionality and spatial resolution of the images in the databases were selected in order to evaluate the performance of the classifiers. Key Words : Classification, Learning, Multispectral images, Remote Sensing. 1 Introduction By using very high spectral resolution scanners, it is possible to sample a wide range of the electromagnetic spectrum. Now, discrimination be..

Efficacy and safety of universal (TCRKO) ARI-0001 CAR-T cells for the treatment of B-cell lymphoma.

Autologous T cells expressing the Chimeric Antigen Receptor (CAR) have been approved as advanced therapy medicinal products (ATMPs) against several hematological malignancies. However, the generation of patient-specific CAR-T products delays treatment and precludes standardization. Allogeneic off-the-shelf CAR-T cells are an alternative to simplify this complex and time-consuming process. Here we investigated safety and efficacy of knocking out the TCR molecule in ARI-0001 CAR-T cells, a second generation αCD19 CAR approved by the Spanish Agency of Medicines and Medical Devices (AEMPS) under the Hospital Exemption for treatment of patients older than 25 years with Relapsed/Refractory acute B cell lymphoblastic leukemia (B-ALL). We first analyzed the efficacy and safety issues that arise during disruption of the TCR gene using CRISPR/Cas9. We have shown that edition of TRAC locus in T cells using CRISPR as ribonuleorproteins allows a highly efficient TCR disruption (over 80%) without significant alterations on T cells phenotype and with an increased percentage of energetic mitochondria. However, we also found that efficient TCRKO can lead to on-target large and medium size deletions, indicating a potential safety risk of this procedure that needs monitoring. Importantly, TCR edition of ARI-0001 efficiently prevented allogeneic responses and did not detectably alter their phenotype, while maintaining a similar anti-tumor activity ex vivo and in vivo compared to unedited ARI-0001 CAR-T cells. In summary, we showed here that, although there are still some risks of genotoxicity due to genome editing, disruption of the TCR is a feasible strategy for the generation of functional allogeneic ARI-0001 CAR-T cells. We propose to further validate this protocol for the treatment of patients that do not fit the requirements for standard autologous CAR-T cells administration