A phase II clinical trial does not show that high dose simvastatin has beneficial effect on markers of bone turnover in multiple myeloma.

Several studies have evaluated the impact of low dose statin (20-80 mg/day) on bone metabolism with inconclusive results despite promising data of preclinical studies. In this study, we investigated the effect of high dose simvastatin (HD-Sim) on biochemical markers of bone turnover and disease activity in six heavily pretreated patients with multiple myeloma (MM). These patients were treated with simvastatin (15 mg/kg/day) for 7 days followed by a rest period of 21 days in two 4-week cycles. Endpoints were changes in the level of biochemical markers of (i) osteoclast activity (tartrate resistant acid phosphatase, TRACP); (ii) bone resorption (collagen fragments CTX and NTX); (iii) bone formation (osteocalcin and aminoterminal propeptide of type I collagen PINP); (iv) cholesterol; (v) regulators of bone metabolism [osteoprotegerin (OPG) and Dickkopf-1 (DKK-1)] and (vi) disease activity (monoclonal proteins or free light chains in serum). TRACP activity in serum and levels of collagen fragments (NTX) in urine increased for all patients temporarily during the 7 days of treatment with HD-Sim indicating that osteoclasts may have been stimulated rather than inhibited. The other markers of bone metabolism showed no change. None of the patients showed any reduction in free monoclonal light chains or monoclonal proteins in serum during treatment with HD-Sim. In spite of the fact that bone turn over effects of HD-Sim may have been blunted by concomitant treatment of patients with other drugs we observed a transient increase in markers of osteoclast activity. This sign of a transient stimulation of osteoclast activity suggests that HD-Sim may be harmful rather than beneficial for MM patients. For this reason and because of gastro-intestinal side effects the study was stopped prematurely.

Strengths and resources used by Australian and Danish adult patients and their family caregivers during treatment for cancer.

PURPOSE: Family plays an essential role in supporting the patient with cancer, however, relatively little attention has been given to understanding the strengths and resources of the family unit across different settings and countries. This study aims to investigate the strengths and resources of patients and family members in Australia and Denmark. METHODS: Using a descriptive, cross-sectional design, 232 patient and family participants from inpatient and outpatient oncology services in Australia and Denmark completed paper based surveys that included the Family Hardiness Index (FHI) and Family Crisis Orientated Personal Evaluation Scales (F-COPES), together with demographic and health information. RESULTS: The family's appraisal of the cancer and ways the family worked together predicted the level of external resources used to manage their circumstances. CONCLUSION: After a cancer diagnosis patients and family respond in different ways related to their family functioning. There is a need for nurses to work closely with the family to understand their strengths and resources, and tailor support and information for family to promote optimal patient outcomes.

Therapeutic options for cefotaxime in the management of bacterial infections.

Clinical studies of cefotaxime administered every 8 and 12 h have demonstrated comparable clinical and microbiologic success when compared to traditional 6-h regimens. This phenomena may be explained, in part, by the pharmacokinetic and pharmacodynamic properties of cefotaxime and the antimicrobially active metabolite desacetyl-cefotaxime. Although cefotaxime levels cannot be maintained above the bacterial minimum inhibitory concentration (MIC) for all infecting pathogens with extended dosing intervals, concentrations of desacetyl-cefotaxime remain above the effective concentration for a variety of organisms throughout the extended interval. Cefotaxime dosage adjustment may be accomplished in nonimmunocompromised patients with infections outside the central nervous system including uncomplicated urinary tract and lower respiratory infections. Infections caused by bacteria with MIC90 values < or = 1 microgram/ml usually respond to 8- or 12-h dosage intervals. Less susceptible organisms with MIC90 values between 2 and 8 micrograms/ml, such as Serratia marcescens, may initially require cefotaxime administered every 6 or 8 h. Extended intervals should be avoided or used cautiously in patients that are neutropenic, immunocompromised, or hypermetabolic. Upon evidence of clinical and microbiologic response, therapy may be continued with alternative stepdown therapy.

Combination beta-lactam and beta-lactamase-inhibitor products: antimicrobial activity and efficiency of enzyme inhibition.

Classification schemes for gram-negative beta-lactamases are presented, mechanisms by which beta-lactamases inactivate beta-lactam antibiotics are reviewed, and methods for assessing the efficiency of beta-lactamase inhibitors are evaluated. Beta-lactamases are commonly produced by Staphylococcus species, the Enterobacteriaceae, Pseudomonas aeruginosa, Acinetobacter species, and some anaerobes. Currently available beta-lactamase inhibitors are thought to be "suicide inhibitors" that form stable complexes between the bacterial beta-lactamase and the beta-lactamase inhibitor in a multistep chemical reaction. Each step can be quantitated; however, the overall process is difficult to measure. Thus, a comparative evaluation of commercially available beta-lactamase inhibitors is extremely difficult and must be done under standardized test conditions. In general, sulbactam, clavulanate, and tazobactam are all potent inhibitors of staphylococcal penicillinase; chromosomal beta-lactamases produced by Bacteroides species, Proteus vulgaris, Haemophilus influenzae, Neisseria gonorrhoeae; and type IV enzymes of Klebsiella species. Although sulbactam possesses activity against TEM-1 and TEM-2 beta-lactamases, it does not have reliable activity against SHV-1 beta-lactamases. Clavulanate and tazobactam are potent inhibitors of both TEM and SHV-1 beta-lactamases. P. aeruginosa and some Enterobacteriaceae produce an inducible, extremely potent, broad-spectrum enzyme (type I beta-lactamase). Tazobactam is the only currently available. beta-lactamase inhibitor with activity against type I beta-lactamases; however, some enzymes are not inhibited by tazobactam.

Batch accuracy of on-line fat determination.

A new method for determination of the fat content of large meat batches without sampling is presented. It is based on dual-energy X-ray (DXR) scanning of meat trimmings prior to mixing, in order to determine the exact fat content of the resulting meat batch. Twenty-seven samples of three types of pork trimmings with a fat content ranging from 24 to 63% were collected and combined into batch sizes of 27-241 kg. At small batch sizes (27 kg) the nature of the measurement error is mainly random, resulting in a prediction error (root mean square error of prediction) of 0.57% against the reference method. At a batch size of 241 kg the error was reduced to 0.34%. The DXR method determines the fat content of all meat in a batch without any sampling required, thus reducing the sampling error to a minimum. This is essential, as the results show that the sampling error is large: when 27-kg samples were homogenized and measured by the reference method, the standard deviation of high-fat samples was 4.7%.

Twenty-four-hour area under the concentration-time curve/MIC ratio as a generic predictor of fluoroquinolone antimicrobial effect by using three strains of Pseudomonas aeruginosa and an in vitro pharmacodynamic model.

Several investigators have suggested that the 24-h area under the concentration-time curve (AUC)/MIC ratio (AUC/MIC24 or AUIC24) can be used to make comparisons of antimicrobial activity between fluoroquinolone antibiotics. Limited data exist regarding the generic predictive ability of AUC/MIC24 for the antimicrobial effects of fluoroquinolones. The purposes of the present investigation were to determine if the AUC/MIC24 can be used as a generic outcome predictor of fluoroquinolone antibacterial activity and to determine if a similar AUC/MIC24 breakpoint can be established for different fluoroquinolones. Using an in vitro pharmacodynamic model, 29 duplicate concentration time-kill curve experiments simulated AUC/MIC24s ranging from 52 to 508 SIT-1.h (inverse serum inhibitory titer integrated over time) with ciprofloxacin or ofloxacin against three strains of Pseudomonas aeruginosa. Each 24-h experiment was performed in cation-supplemented Mueller-Hinton broth with a starting inoculum of 10(6) CFU/ml. At timed intervals cation-supplemented Mueller-Hinton broth samples were collected for CFU and fluoroquinolone concentration determinations. Transformation of bacterial counts into the cumulative bacterial effect parameter of the 24-h area under the effect curve (AUEC24) was performed for each concentration time-kill curve. Multivariate regression analysis was used to compare pharmacodynamic predictors (AUC/MIC24, 24-h AUC, peak concentration [Cmax] to MIC ratios [Cmax:MIC], etc.) with ln AUEC24. To identify threshold breakpoint AUC/MIC24s, AUEC24s were stratified by the magnitude of AUC/MIC24 into subgroups, which were analyzed for differences in antibacterial effect. The Kruskal-Wallis test and subsequent Tukey's multiple comparison test were used to determine which AUC/MIC subgroups were significantly different. Multiple regression analysis revealed that only AUC/MIC24 (r2 = 0.65) and MIC (r2 = 0.03) were significantly correlated with antibacterial effect. At similar AUC/MIC24s, yet different MICs, Cmaxs, or elimination half-lives, the AUEC24s were similar for both fluoroquinolones. The relationship between AUC/MIC24 and ln AUEC24 was best described by a sigmoidal maximal antimicrobial effect (Emax) model (r2 = 0.72; Emax = 9.1; AUC/MIC50 = 119 SIT-1.h; S = 2.01 [S is an exponent that reflects the degree of sigmoidicity]). Ciprofloxacin-bacteria AUC/MIC24 values of < 100 SIT-1.h were significantly different (P < 0.05) from the AUC/MIC24 values of > 100 SIT-1.h. An ofloxacin AUC/MIC24 of > 100 SIT-1.h and an AUC/MIC24 of < 100 SIT-1.h exhibited a trend toward a significant difference (P > 0.05 but < 0.1). The inverse relationship between drug exposure and MIC increase postexposure was described by a sigmoidal fixed Emax model (AUC/MIC24, r2 = 0.40; AUC/MIC50 = 95 SIT-1.h; S = 1.97; Cmax:MIC, r2 = 0.41; Cmax:MIC50 = 7.3; S = 2.01). These data suggest that AUC/MIC24 may be the most descriptive measurement of fluoroquinolone antimicrobial activity against P. aeruginosa, that ofloxacin and ciprofloxacin have similar AUC/MIC24 threshold breakpoints at approximately 100 SIT-1.h, that the concentration-dependent selection of resistant organisms may parallel the threshold breakpoint of the antimicrobial effect, and that AUC/MIC24 generically describes the antibacterial effects of different fluoroquinolones.