Association of CD38 antigen expression with other prognostic parameters in early stages of chronic lymphocytic leukemia.

The expression of the surface molecule CD38 on B cell chronic lymphocytic leukemia (B-CLL) cells has recently been described as a prognostic marker for patient survival. We have analyzed CD19/CD38 expression in 81 patients with predominantly early stages of B-CLL (69 Binet A, seven Binet B, five Binet C). Sixty-two patients (77%) had less than 30% CD38+/CD19+ cells, while 19 (23%) had > or = 30%. There was a significant association between Binet stages (A vs. B+C, p < 0.0001), Rai stages (0-II vs. III+IV, p < 0.001) and CD38 expression, confirming the published cut-off level of 30%. A particularly strong association between CD38 expression was found with soluble CD23 (sCD23) levels of > or = 2000 U/ml (p < 0.0001) and beta2-microglobulin (beta2 MG) serum levels of > or = 3 mg/l (p < 0.0001) indicating that CD38 is a marker of tumor mass as well as disease progression. A borderline association was found with lymphocyte doubling time (LDT) < 12 months (p = 0.05) due to low patient numbers, while there was no association with age, sex or immunoglobulin deficiency. Discordant results were obtained in a number of patients: 10 of 69 patients (14%) with Binet A had a CD38 > or = 30% while three of seven patients with Binet B had a CD38 < 30%. In these two subgroups CD38 and other prognostic factors gave discrepant results. Due to the early stage and short median observation time (12 months. range 1-24 months), calculations concerning patient survival were not performed. However, our data show a strong association between CD38 and other known prognostic factors. The results also suggest that this factor is not always reliable in Binet A patients.

Clinical relevance of the lung resistance protein in diffuse large B-cell lymphomas.

Drug resistance of non-Hodgkin's lymphomas may involve mechanisms of the multidrug resistance phenotype including the lung resistance protein (LRP) and the multidrug resistance protein (MRP1). To determine the clinical relevance of these multidrug resistance factors in previously untreated diffuse large B-cell lymphomas (n = 48), we studied LRP and MRP1 expression in lymphoma cells and their impact on clinical outcome. LRP and MRP1 expression were immunohistochemically assessed by means of the monoclonal antibodies LRP-56 and MRPr1, respectively. LRP was positive in 23% and MRP1 in 44% of the samples. LRP expression was associated with higher tumor stage (P = 0.03), elevated serum lactate dehydrogenase levels (P = 0.01), and the International Prognostic Index (P = 0.0001). LRP-positive patients had a lower complete response rate to polychemotherapy than LRP-negative patients (18 versus 65%; P = 0.006). Patients with LRP expression had a shorter overall survival than those without LRP expression (median of 0.9 years versus median not reached; P = 0.001). MRP1 expression was independent of clinical and laboratory parameters and had no impact on the outcome of chemotherapy or survival of the patients. These data suggest that LRP expression but not MRP1 expression is an important mechanism of drug resistance associated with worse clinical outcome in previously untreated diffuse large B-cell lymphomas. Thus, the reversal of LRP-mediated drug resistance may improve clinical outcome in diffuse large B-cell lymphoma in the future.

Knowledge-based interpretation of serologic tests for hepatitis on the World Wide Web.

HEPAXPERT is a knowledge-based system that interprets the results of routine serologic tests for infection with hepatitis A and B viruses. The following tests are included: hepatitis A virus antibodies, IgM antibodies to the hepatitis A virus, hepatitis A virus in stool, hepatitis B surface antigen and antibodies, antibodies to hepatitis B core antigen, and hepatitis B envelope antigen and antibodies. HEPAXPERT/WWW, an implementation of HEPAXPERT-III for the World Wide Web, can be reached by URL http://www.med-expert.co.at/hepax. After selecting HEPAXPERT/WWW, serologic test results can be entered and will be transferred as an E-mail message for subsequent interpretation, which is done off-line with HEPAXPERT-III. The textual interpretation is sent back via E-mail. Each qualitative test for hepatitis A and B antibodies and antigens may produce one of four possible results: positive, negative, borderline, and not tested. To cover the resulting 64 (A) and 57,344 (B) combinations of findings, the knowledge base of HEPAXPERT/WWW contains 16 rules of hepatitis A and 131 rules for hepatitis B serology interpretation. This basic knowledge is structured such that all possible combinations of findings can be interpreted, and there is no overlap in the premises underlying the rules. The reports that the system automatically generates include the transferred results of the tests; a detailed analysis of the results, including virus exposure, immunity, stage of illness, prognosis, infectiousness, and vaccination recommendation; and, as an option, an identification, to distinguish the origin of the interpretation requests.

A WWW-accessible knowledge base for the interpretation of hepatitis serologic tests.

HEPAXPERT is a knowledge-based system that interprets the results of routine serologic tests for infection with hepatitis A and B viruses. The following tests are included: hepatitis A virus anti-bodies (anti-HAV), IgM antibodies to the hepatitis A virus (IgM anti-HAV), hepatitis A virus (HAV in stool, hepatitis B surface antigen (HBsAg) and antibodies (qualitative anti-HBs, quantitative anti-HBs titre), antibodies to hepatitis B core antigen (anti-HBc and IgM anti-HBc), and hepatitis B envelope antigen (HBeAg) and antibodies (anti-HBe). HEPAXPERT/WWW--an implementation of HEPAXPERT-III for WWW--can be reached by URL http://www.swun.com/hepax of the World Wide Web. After selecting HEPAXPERT/WWW, serologic test results can be entered and will be transferred as an e-mail message for subsequent interpretation which is done off-line with HEPAXPERT-III. The textual interpretation is sent back via e-mail. Each qualitative test for hepatitis A and B antibodies and antigens may produce one of four possible results: positive, negative, borderline, and not tested. To cover the resulting 64 (A) and 57344 (B) combinations of findings, the knowledge base of HEPAXPERT/WWW contains 16 rules for hepatitis A and 131 rules for hepatitis B serology interpretation. This basic knowledge is structured such that all possible combinations of findings can be interpreted and there is no overlap in the premises underlying the rules. The reports that the system automatically generates include: (a) the transferred results of the tests; (b) a detailed analysis of the results, including virus exposure, immunity, stage of illness, prognosis, infectiousness, and vaccination recommendation; and (c) optional: an ID to distinguish the origin of the interpretation requests.

HEPAXPERT-III: knowledge-based interpretation of serologic tests for hepatitis A, B, C, and D.

1. The HEPAXPERT-III SYSTEM. HEPAXPERT-III--the successor of HEPAXPERT-I[1] and HEPAXPERT-II [2]--is a routinely-used, integrated medical database and knowledge-based system that stores and interprets the results of serologic tests for infection with hepatitis A, B, C, and D viruses. The following tests are included: Anti-HAV, IGM anti-HAV, and HAV in stool; HBsAg, anti-HBs, anti-HBc, IGM anti-HBc, HBeAg, anti-HBe, and anti-HBs titre; Anti-HCV, HCV-immunoblot, and HCV-PCR; Delta-Ag and anti-delta. HEPAXPERT-III provides the following functions: a) screen input of patient's personal data (patient ID, surname, first name, name at birth, date of birth, and sex), administrative data (department requiring the tests and date of specimen sample), and medical data (results of serologic tests); and/or b) automatic transfer of patient's personal, administrative, and medical data by connecting HEPAXPERT-III to a laboratory information system, a hospital information system, or an automated laboratory analyzer; and c) automatic generation of interpretive reports of the obtained serologic findings, including an analysis of possible virus exposition, immunity, disease stage, prognosis, and degree of infectiousness. HEPAXPERT-I and HEPAXPERT-II have been routinely used at the Vienna General Hospital, the teaching hospital of the University of Vienna Medical School. The interpretive reports are well-accepted and lead to several improvements in patient care [3]. HEPAXPERT-III will not only extend the scope of interpretation to hepatitis C and D serologic tests, but will also offer a state-of-the-art graphical user interface. 2. HARDWARE AND SOFTWARE. IBM-compatible personal computer (minimum 80386 SX processor), 8 MB RAM (OS/2) and 4 RM RAM (MS-Windows), resp., graphic adapter (minimum 640x480) and printer supported by OS/2 and MS-Windows 3.1, resp., IBM OS/2-2.1 or higher and MS-Windows 3.1 or higher, resp., and for the OS/2 version IBM Database 2 (DB2/2).

MONI: an intelligent database and monitoring system for surveillance of nosocomial infections.

Recording, recognition, and prevention of nosocomial infections are the primary responsibilities of the hospital infection control unit. To perform these tasks, this unit needs information from diverse sources--the patient's symptoms and signs, microbiological and virological test results, and information regarding antibiotics and treatment come from different levels of healthcare delivery. Because of the large amount of data (e.g., about 300 microbiological requests daily) a computer system is required to store this information and to provide a means for subsequent evaluation. MONI (Monitoring of nosocomial infections) is an intelligent database and monitoring system for surveillance and detection of nosocomial infections. Data can be entered into the system manually as well as transferred automatically from external information systems. The central feature of the system is the automatic detection of and calling attention to conditions that may be a detriment to patient recovery, such as possible hospital-acquired infections, risk factors, diseases to be reported, etc. By using this system, we seek to reduce the frequency of infection and the frequency of nosocomial deaths by improving the quality of patient treatment, shortening the length of stay in a hospital, and the use of fewer and/or cheaper antibiotics. MONI provides a means to access relevant medical data (names of infectious agents, antibiotics, department names, monitoring rules, etc.) from a library. This library can be updated or otherwise modified, even during use. An infection control team using this system can customize it to suit the demands of that particular unit. Automatic data transfer from external information systems is made possible by tables that translate between different code systems. The system also offers flexibility; the program can be configured to adapt it for use in other hospitals and institutions. The core element of MONI is the monitoring module, which is implemented as a layer between data input and the database. Upon data acquisition, the system checks the input against several monitoring tools and alerts the user to matches, which may indicate an infection risk. Processing of a rule may be deferred, depending on complexity of the rule and the actual and estimated workload of the system. Examples of the monitoring guidelines are: (1) suspicion of nosocomial infection; (2) infection at a normally sterile site; (3) infection due to bacteria with unusual antibiotic sensitivity patterns; (4) lab report indicates that patient is treated with ineffective antibiotic; (5) possible choice for less expensive antibiotic; (6) infection which is required to be reported to state and/or health authorities; (7) patients receiving prophylactic antibiotics longer than medically indicated; and (8) infections of two or more patients in different wards with the same bacteria (cf. Evans 85). The MONI system was developed at one of the largest hospitals in Europe, the Vienna General Hospital (2,200 beds). This facility serves as the teaching hospital of the University of Vienna Medical School. The size of the hospital and the large amount of data made it necessary to introduce such a system into clinical routine. MONI was programmed in C and C++ with a state-of-the-art graphical user interface (Presentation Manager, Workplace Shell) for OS/2. IBM Database 2 for OS/2 (dB 2/2) was used in constructing the database. The layer between the database and the monitoring application is driven by the multitasking and interprocess communication abilities of OS/2. A pen-based support system that assists in mobile data acquisition is currently under development.

[Resistance spectrum of staphylococci at the Vienna general hospital (July to December 1991)]. / Resistenzverhalten von Staphylokokken am Allgemeinen Krankenhaus der Stadt Wien (Juli bis Dezember 1991).

This study describes the antibiotic resistance of 1961 staphylococcal strains that were isolated at the University Hospital of Vienna from July to December 1991. Staphylococcus aureus (SA) represented 43.2%; coagulase-negative (CNS) staphylococci 56.8%, three quarters of which were Staphylococcus epidermidis. Excepting netilmicin, the proportion of resistant strains to all antibiotics was higher with CNS than SA. Methicillin resistance (M(r)) was found in 11.8% of SA and 30.3% of CNS. Borderline oxacillin resistance (BOR) was noted in 7.4% of SA and 32.5% of CNS. It is important to note that severe or generalized infections due to M(r) staphylococci should be treated with glycopeptide antibiotics such as vancomycin or teicoplanin from the very beginning, whereas chemotherapy of those with BOR strains may also be carried out with beta lactamase-stable beta lactam antibiotics. Comparing the results of this study with those of the first half of 1991, the respective proportion of M(r) staphylococci was significantly lower than 23.6% for SA and 47.6% for CNS recorded then. As compared with the foregoing period, however, these strains demonstrated increased resistance frequencies to gentamicin (from 81.3 to 90%), amikacin (from 35.4 to 69%), netilmicin (35.4 to 55%), and ciprofloxacin (56.2 to 64%). This is taken as an indication for the epidemic spread of a clone of resistant strains.