M. lentiflavum is an emerging pathogen producing NTM lymphadenitis in Madrid.

No abstract

Cáncer de mama; Cirugía mamaria; Mastectomía contralateral Resumen Introducción: No existe un consenso sobre las indicaciones de mastectomía contralateral en pacientes diagnosticadas de cáncer de mama unilateral sin mutación germinal en BRCA1/2. Estudios previos han identificado algunos factores que pueden influir en la toma de la decisión dependientes del tumor, como el tamaño o histología, de la paciente, como la edad, y de la cirugía como la posibilidad de realizar una reconstrucción inmediata o la experiencia del cirujano. Métodos: Estudio retrospectivo de una cohorte de 176 pacientes diagnosticadas de CM entre 2010 y 2016 a las que se les realizó cirugía mamaria. Se ha analizado la asociación de características del tumor y de la paciente con la toma de decisión de realizar mastectomía contralateral (MC) o no-MC. Asimismo, se han analizado los datos relacionados con la cirugía y la recurrencia por grupos mediante la curva de incidencia acumulada y el test de Gray. Resultados: El número de MC se ha incrementado en nuestro centro. No hemos encontrado diferencias significativas en el desarrollo de complicaciones posquirúrgicas entre los 2 grupos de pacientes, pero sí en la estancia hospitalaria, siendo superior para MC. También hemos observado diferencias entre ambas cohortes en edad y tipo de tumor, siendo la MC más frecuente en aquellas pacientes más jóvenes y subtipo luminal A. Hemos hallado diferencias en la incidencia acumulada de recidiva entre ambos subgrupos (p = 0,034).Abreviaturas: CAP, complejo areola-pezón; CM, cáncer de mama; CMC, cáncer de mama contralateral; MC, mastectomía contralateral.

e22502 Background: Inherited mutations in the CHEK2 gene have been associated with an increased lifetimerisk of develop breast cancer (BC). The main objective of the study is to identify in our population the prevalence of mutations in the CHEK2 gene in diagnosed BC patients, as well as to evaluate the phenotypic characteristics of the tumour and family history. Methods: A genetic study was performed in 396 patients diagnosed of BC at the University Hospital Lozano Blesa of Zaragoza (Spain). We selected 9 patients with genetic variants in the CHEK2 gene and performed a descriptive analysis of the clinical variables, a bibliographic review of the genetic variants and a co-segregation study. Results: We identified 2 pathogenic variants ( CHEK2 c.349 A>G and c.507delT) and 6 variants of uncertain significance (VUS). The genotypic characteristics of the VUS are summarized in the table. In all cases there was a family history of BC in first and /or second degree relatives. The variant cosegregated with the disease in one of the families. Conclusions: The pathogenic missense variant c.349A>G was found in two families. This is a rare missense variant. Studies have shown that this variant had a significant impact on the protein based on in silico prediction and has been associated with BC. In our study, this variant was found in a patient with renal carcinoma and was identified in a proband with a strong family history of pancreatic and ovarian cancer (OC). However, there aren’t exist data about the risk of developing other cancer, different of BC, with this specific mutation. The other pathogenic variant detected was CHEK2 c.507delT in a family with history of BC and OC. This variant is a frameshift mutation, predicted to cause loss of normal protein function. CHEK2 507delT was reported in one of 12 BC families in one series and is possible its relation with OC. With regard to the VUS the cosegregation analysis in selected families may help understand if a variant could have played a role in developing cancer. In conclusion, CHEK2 mutations have been associated with increased risk for BC. However, the frequency of carriers may vary depending on the population, and different mutations may be associated with different cancer risks. More studies are needed to establish a complete range of risks associated with CHEK2 mutations. [Table: see text]

e16537 Background: Renal cell carcinoma (RCC) have low prevalence but it incidence is increasing. For a correct therapeutic approach, it is important to carry out a correct prognostic stratification. Several prognostication systems have been proposed. One of the most commonly used is the one developed by Heng. It is based on IMDC database. This classification includes six prognostic factors (hemoglobin, neutrohils, platelets, serum calcium, Karnosky Performance Status and time from diagnosis to initiaton treatment) to divide patients into three gorups. The relevance of IMDC prognostic criterio, in the era of immunotherapy, remains to be established. In the absence of alternative criteria, these prognostication system continue to be used. A great prognostic disparity has been observed in the intermediate prognosis group. This raises the need to divide this group into two. Thus, patients included in it would be better selected. Methods: Observational, single-center, retrospective study, based on a cohort of 107 patients with advanced RCC, recruited from January 2006 to December 2019. Main objective: Evaluate whether survival of patients with intermediate prognosis (treated with antiangiogenic in first-line) is different depending on the presence of one or two prognostic factors. Descriptive and survival analysis (OS and PFS) were performed. In addition, the influence of prognostic factors on OS and PFS were compared using the log-rank test and Cox regression. Results: In the overall population, median overall survival (OS) was 26.86 months (95% CI: 21.09-32.63) and median PFS was 18.41 months (95% CI: 14.02-22.79). Median OS were, in favorable-risk 42.24 months (95% CI: 29.62-54.62), in intermediate-risk 27,24 (95% CI: 19.44-35-03) and in poor-risk 8.00 (95% CI: 4.54-11.45). Median PFS were in favorable-risk 30.53 months (95% CI:20.92-40.13), in intermediate-risk 17,16 (95% CI:11.54-22.78) and poor-risk 6.13 (95% CI:3.02-9.25). Median OS and PFS, in patients with intermediate-risk, with a single risk factor were 33.79 (95% CI 23.17-44.41) and 20.97 months (95% CI 13.35-28.59), compared to 14.88 (95% CI 8.80-20.95) and 10.59 months (95% CI 4.87-16.32) in those with two risk factors. The results were statistically significant in OS (p = 0.01) and PFS (p = 0.037). Conclusions: The differences in median OS and PFS, within the intermediate prognosis group (1 or 2 RF), confirm the existence of two subgroups of patients. Patients with 1 RF are similar to those with favorable-risk. These results are important since, the presence of 1 or 2 RF, would condition the choice of TKIs as part of the first-line treatment combination. More studies are needed to better subclassify the intermediate risk group when optimizing the best treatments for each patient.