ABSTRACT
Hematopoietic stem cell transplant (HCT) recipients have a substantial risk of developing secondary solid cancers, particularly beyond 5 years after HCT and without reaching a plateau overtime. A working group was established through the Center for International Blood and Marrow Transplant Research and the European Group for Blood and Marrow Transplantation with the goal to facilitate implementation of cancer screening appropriate to HCT recipients. The working group reviewed guidelines and methods for cancer screening applicable to the general population and reviewed the incidence and risk factors for secondary cancers after HCT. A consensus approach was used to establish recommendations for individual secondary cancers. The most common sites include oral cavity, skin, breast and thyroid. Risks of cancers are increased after HCT compared with the general population in skin, thyroid, oral cavity, esophagus, liver, nervous system, bone and connective tissues. Myeloablative TBI, young age at HCT, chronic GVHD and prolonged immunosuppressive treatment beyond 24 months were well-documented risk factors for many types of secondary cancers. All HCT recipients should be advised of the risks of secondary cancers annually and encouraged to undergo recommended screening based on their predisposition. Here we propose guidelines to help clinicians in providing screening and preventive care for secondary cancers among HCT recipients.
Subject(s)
Hematopoietic Stem Cell Transplantation/adverse effects , Mass Screening , Neoplasms, Second Primary/diagnosis , Female , Humans , Male , Neoplasms, Second Primary/epidemiology , Organ Specificity , Risk FactorsABSTRACT
This article describes a computer procedure for the examination and analysis of cerebral electrical activity (CEA). Changes in CEA generate random electrical activity and may include transitory events, such as burst episodes. As yet, there are no standard techniques for evaluating the statistical process of the CEA. This article proposes a computerized method of analyzing the stochastic character of CEA using a computer algorithm. Using a real-time wave-by-wave technique, the algorithm characterizes CEA by the frequency and amplitude of each CEA waveform. This algorithm produces digital packets of information that describe individual CEA waveforms.
