Risk-Adapted, Combined-Modality Therapy for Unfavorable Pediatric Hodgkin Lymphom

Background and Objectives: Risk-adapted therapy for children with HL is directed toward high survival, minimal toxicity and optimal quality of life, with long term follow up. We assess the impact of prognostic factors associated with local treatment failure of pediatric HL patients with unfavorable criteria treated with combined modality: Alternating ABVD (Doxorubicin, Bleomycin, Vinblastine and Decarbazine) and COEP (Cyclophosphamide, Oncovin, Etoposide and Prednisone) chemotherapy and response-based, involved-field radiation for newly diagnosed unfavorable pediatric HL patients, also will detect toxicities and long-term complications observed in the patients. Methods: This prospective study was carried out from January 2010 to January 2018, with a median follow up of 74 months (range 8 - 103 months). 54 patients were eligible for this study stratified into two groups: intermediate risk (IR) and high-risk group (HR). Patients were treated with (4 - 6 cycles) and (6 - 8 cycles) respectively of alternating ABVD/COEP chemotherapy followed by involved-field radiation therapy (IFRT): 15 Gy for patients achieved complete response, and 25.5 Gy for those achieved a partial response. Results: 27 patients were IR and 27 patients were HR. There were 16 treatment failures;5 patients had progressive disease;and 11 patients had a relapse. 9 patients died from their disease progression. The 5-year overall survival (OS) and event-free survival (EFS) rates (±SE) were 81.8% ± 5.7% and 71.8% ± 6.2% respectively. Multivariate analysis revealed that the only independent factor for inferior OS was radiotherapy. Conclusion: Treatment results of unfavourable HL patients in our study are satisfactory for with IR group but not for HR group who needs intensification of therapy. Radiotherapy is considered as a cornerstone in the treatment of the patients with unfavourable criteria with better assessment of early responders needed by PET-CT to identify patients at risk for relapse.

Treatment options in stage I seminoma

Seminomas are most commonly diagnosed in clinical stage I(CSI).After orchiectomy,approximately 15%of patients in this stage have subclinical metastases.Adjuvant radiotherapy(ART)delivered to the retroperitoneum and ipsilateral pelvic lymph nodes has been the mainstay of treatment for many years.Although highly efficient,with long-term cancer-specific survival(CSS)rates approaching almost 100%,ART is associated with considerable long-term consequences,particularly cardiovascular toxicity and increased risk of secondary malignancies(SMN).Therefore,active surveillance(AS)and adjuvant chemotherapy(ACT)were developed as alternative treatment options.While AS prevents patient overtreatment,it is associated with strict follow-up regimens and increased radiation exposure due to repeated imaging.Due to equivalent CSS rates to ART,and lower toxicity,one course of adjuvant carboplatin presents the cornerstone of chemotherapy for CSI patients.CSS is almost 100%for patients with CSI seminoma,regardless of the chosen treatment option.Therefore,a personalized approach in treatment selection is preferred.Currently,routine radiotherapy for CSI seminoma patients is no longer recommended.Instead,it should be reserved for patients who are unfit or unwilling for AS or ACT.Identification of prognostic factors for disease relapse allowed for the development of risk-adapted treatment strategy and stratification of patients in low-risk and high-risk groups.Although risk-adapted policy needs further validation,surveillance is currently recommended in low-risk patients,while ACT is reserved for patients with a higher risk of relapse.

Identifying high-risk over-entitlement in access control policies using fuzzy logic

Analysing access control policies is an essential process for ensuring over-prescribed permissions are identified and removed. This is a time-consuming and knowledge-intensive process, largely because there is a wealth of policy information that needs to be manually examined. Furthermore, there is no standard definition of what constitutes an over-entitled permission within an organisation’s access control policy, making it not possible to develop automated rule-based approaches. It is often the case that over-entitled permissions are subjective to an organisation’s role-based structure, where access is be divided and managed based on different employee needs. In this context, an irregular permission could be one where an employee has frequently changed roles, thus accumulating a wide-ranging set of permissions. There is no one size fits all approach to identifying permissions where an employee is receiving more permission than is necessary, and it is necessary to examine them in the context of the organisation to establish their individual risk. Risk is not a binary measure and, in this work, an approach is built using Fuzzy Logic to determine an overall risk rating, which can then be used to make a more informed decision as to whether a user is over-entitled and presenting risk to the organisation. This requires the exploratory use of establishing resource sensitivity and user trust as measures to determine a risk rating. The paper presents a generic solution, which has been implemented to perform experimental analysis on Microsoft’s New Technology File System to show how this works in practice. A simulation using expert knowledge for comparison is then performed to demonstrate how effective it is at helping the user identify potential irregular permissions.

Gene expression profiling as a prognostic tool in multiple myeloma

Multiple myeloma(MM)is an aggressive plasma cell malignancy with high degrees of variability in outcome,some patients experience long remissions,whilst others survive less than two years from diagnosis.Therapy refractoriness and relapse remain challenges in MM management,and there is a need for improved prognostication and targeted therapies to improve overall survival(OS).The past decade has seen a surge in gene expression profiling(GEP)studies which have elucidated the molecular landscape of MM and led to the identification of novel gene signatures that predict OS and outperform current clinical predictors.In this review,we discuss the limitations of current prognostic tools and the emerging role of GEP in diagnostics and in the development of personalised medicine approaches to combat drug resistance.