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Introduction: GYNOCARE, the European Network for Gynaecological Rare Cancer Research, set out to evaluate the current status of biobanks with access to rare gynaecological tumours, with a view to harmonising sample and data collection and associated consent, to facilitate collaborative cross-border research, enabling clinical trials and translational research.

Methods: Two digital surveys were formulated, one covering clinical and scientific parameters and one exploring ethical and regulatory issues around informed consent.

Results: Data were analysed for 20 common responses, from 7 European countries. Tissue was the main sample type biobanked with 63 % also banking blood. Documentation of clinical data, treatment regimens and classification systems varied. Eighty percent collected pathological information. Most biobanks were linked to medical records but only one fifth with national registries. The Information Sheet covered governance, benefits/risks, sharing (mainly for non-profit research), return of results and data protection safeguards. Only 37 % informed patients about sample and data storage, although about half stored samples for an indefinite time. Pseudonymisation and Data Protection Officer approval were the prime data safeguards. Less than half explained the difference between anonymisation and pseudonymisation. Broad consent was the norm (84 %) and 95 % granted the right to withdraw consent. Three countries have Biobank legislation.

Conclusion: These surveys provide a snapshot of the current state of biobanks and highlight divergences in the consent process and data management. More work is needed to understand what parameters are being gathered across more EU countries and thus harmonise the sample and data collection processes to facilitate cross-border research.

Ovarian cancer in children and adolescents is rare, presenting unique diagnostic and management challenges distinct from adult cases. This paper provides a comprehensive overview of this disease, focusing on the importance of a multidisciplinary approach to care. We discuss the common presentation of ovarian malignant masses in young patients, highlighting the role of imaging and tumor markers in diagnosis. The paper delves into the surgical management of these tumors, emphasizing the importance of fertility-sparing techniques whenever possible. We explore the role of adjuvant chemotherapy, considering histological subtypes and disease stage. Furthermore, we address the good prognosis associated with early diagnosis and treatment, with survival rates exceeding 90 % in many cases. Finally, the need for long-term follow-up to monitor for potential recurrence is underscored and the long-term treatment-related effects are addressed. This review aims to guide clinicians in providing optimal care for this unique patient population, emphasizing the importance of balancing oncological control with the preservation of future fertility and quality of life.

Endometrial cancer (EC) is increasing incidence among women, and it constitutes a health problem for women globally. An important aspect of EC management involves the use of protein biomarkers for early detection and monitoring. Protein biomarkers allow the identification of high-risk patients, the detection of the disease in its early stages, and the assessment of treatment responses. Mass spectrometry (MS)-based proteomics offers robust analytical techniques and a comprehensive understanding of proteins. Proteomics methods allow scientists to investigate both the quantities and functions of proteins. Thus, it provides valuable insights into how proteins are altered under different conditions. This review summarizes recent advances in MS-based proteomic biomarker discovery for EC, focusing on different sample types and MS-based techniques used in clinical studies. The review emphasized in detail the most commonly used key sources such as blood, urine, vaginal fluids and tissue. Furthermore, MS-based proteomics techniques such as untargeted, targeted, sequential window acquisition of all theoretical mass spectra (SWATH-MS) and mass spectrometry imaging used in the discovery and validation/validation phases were evaluated. This review highlights the importance of biomarker discovery and clinical translation to improve diagnostic and therapeutic outcomes in EC. It aims to provide a comprehensive overview of MS-based proteomics in EC, guiding future research and clinical applications.

Aim: Gastric cancer is one of the leading causes of cancer-related mortalities worldwide. According to the pathological TNM classification, T3N0M0, Stage IIA gastric cancer has been excluded from the S-1 adjuvant chemotherapy trials. Thus, the clinical impact of S-1 adjuvant chemotherapy in patients with pathological T3N0M0 cancer and the associated prognostic factors have not been elucidated. Consequently, we determined the prognostic factors in patients with pathological T3N0M0 gastric cancer and the efficacy of adjuvant chemotherapy.

Methods: From 2007 to 2018, 205 patients diagnosed with pathological T3N0M0 gastric cancer were enrolled at seven institutions. Recurrence-free and overall survival rates were evaluated. Univariate and multivariate survival analyses for recurrence-free and overall survival were performed, using the Cox proportional hazards model.

Results: The 5-year recurrence-free and overall survival rates were 84.7 % and 81.4 %, respectively. Although there was no difference in overall survival, multivariate analysis identified positive venous invasion as an independent risk factor for recurrence (p = 0.007, hazard ratio = 3.851). Adjuvant chemotherapy had no impact on both recurrence free and overall survival. However, the 5-year overall survival rates in the sub-cohort that completed adjuvant chemotherapy with S-1 were higher than those in the sub-cohort that did not complete the treatment (p = 0.019).

Conclusion: The prognosis of patients with pathological T3N0M0 gastric cancer was relatively favorable. However, adjuvant chemotherapy was not identified as an independent risk factor and patients with venous invasion were at a high risk of recurrence. Therefore, a large-scale multi-institutional prospective study evaluating the efficacy of adjuvant chemotherapy for high risk pT3N0M0 is required.

Background: Post-hepatectomy liver failure (PHLF) can significantly compromise outcomes, especially in cirrhotic patients. The identification of accurate and non-invasive pre-operative predictors is of paramount importance to appropriately stratify patients according to their estimated risk and select the best treatment strategy.

Materials and methods: Consecutive patients undergoing liver resection for HCC on cirrhosis between 1-2015 and 12-2020 at 10 international Institutions were enrolled and their pre-operative CT scans were evaluated for the presence of spontaneous portosystemic shunts (SPSS) to identify predictors of PHLF and develop a nomogram.

Results: The analysis of the CT scans identified SPSS in 74 patients (17.4 %). PHLF was developed in 27 out of 425 cases (6.4 %), with grades B/C observed in 17 patients (4 %). At the multivariable analysis, the presence of SPSS resulted an independent risk factor for all-grades PHLF (OR 6.83, 95%CI 2.39-19.51, p < 0.001) and clinically significant PHLF development (OR 7.92, 95%CI 2.03-30.85, p = 0.003) alongside a patient's age ≥74 years, a pre-operative platelets count <106x10³/μL, a multiple-segments liver resection, and an intraoperative blood loss ≥1200 mL. The 30- and 90-days mortality in patients with and without SPSS resulted 2.7 % vs 0.3 % (p = 0.024) and 5.4 % vs 1.1 % (p = 0.014). The accuracy of SPSS in predicting PHLF development was 0.847 (95%n CI 0.809-0.880). The internally validated nomogram showed excellent performance in predicting grades B/C PHLF (c-statistic = 0.933 (95%CI 0.888-0.979)).

Conclusion: The pre-operative presence of SPSS assessed on the pre-operative imaging proved to be a valuable radiological biomarker able to predict PHLF development in patients undergoing liver resection for HCC.

Introduction: Neoadjuvant chemotherapy is becoming routine for colorectal liver metastasis (CRLM) in patients with high risks of recurrence or in whom resection is difficult. This retrospective study aimed to establish a modified survival prediction model for patients with CRLM who underwent hepatectomy after neoadjuvant chemotherapy.

Materials and methods: A total of 619 patients who received neoadjuvant chemotherapy followed by hepatectomy between 2006 and 2021 were included and divided into training and validation groups at a ratio of 2:1. The model was established in training group and validated in validation group. Chemotherapy response was integrated into the genetic and morphological evaluation (GAME) score as a new NeoGAME model, with assigned points based on the hazard ratio in the multivariate Cox regression. The NeoGAME score grouping cutoff was divided using X-tile, and the predictive power was compared with that of traditional models.

Results: The 5-year overall survival were significantly different in the NeoGAME low-risk (0-2 points), medium-risk (3-4 points) and high-risk (≥5 points) groups (training group, P < 0.001; validation group, P = 0.0012). The area under the curve in predicting 5-year survival was 0.67 and 0.66 for the training and validation groups, respectively. Time-dependent receiver operating characteristic curve showed better discrimination ability of NeoGAME than the GAME score in predicting 5-year survival.

Conclusions: The newly established NeoGAME score can predict survival more precisely for patients with CRLM receiving neoadjuvant chemotherapy. Moreover, the model offers a useful tool for assessing tumor behavior and selecting a benefiting population for liver resection.