In renal transplant patients, there is an established relationship between mycophenolate area under the curve and clinical outcome. The authors have developed and validated a limited sampling strategy to estimate mycophenolic acid area under the curve to 12 hours (MPA AUC0-12) in a stable renal transplant Indian population prescribed a formulation of mycophenolate mofetil (Mofilet) along with prednisolone and tacrolimus. Intensive pharmacokinetic sampling was performed in 29 patients to measure mycophenolate concentration from trough to 12 hours postdose. Subsets of different timed concentrations against total measured 12-hour area under the curve were analyzed by linear regression. Three models were identified and linear regression analysis done. After all subset regression analysis, three, four, and five time point limited sampling strategies (LSS) were developed having correlation coefficients above 0.92. Validation of the models was performed using the jackknife method and their predictive performances were tested. After validation, the correlation coefficients for all three models were above 0.901. The five-point LSS had the best predictive performance with a bias (95% confidence interval) of 0.67% (-3.45 to 4.79) and mean precision 7.73%. In all patients except one, the five-point LSS estimation for total area under the curve was within +/- 20% of the total measured AUC0-12. Trough concentration had a significant correlation with AUC0-12 (r = 0.69). However, if dosing in routine clinical practice was adjusted based only on trough concentration, 41% of our patients would require a different dose compared with monitoring using AUC0-12. The five-point LSS uses half-hourly samples from trough to 1.5 hour postdose with an additional sample at 3 hours. Ninety-three percent of our patients had a Cmax within 1.5 hour and inclusion of all the time points up to1.5 hour gave a better estimate of AUC0-12. This model simplifies area under the curve measurement with high precision in stable adult renal transplant patients.
Enteric-coated mycophenolate sodium (EC-MPS) is widely used in renal transplantation. With a delayed absorption profile, it has not been possible to develop limited sampling strategies to estimate area under the curve (mycophenolic acid [MPA] AUC₀₋₁₂), which have limited time points and are completed in 2 hours. We developed and validated simplified strategies to estimate MPA AUC₀₋₁₂ in an Indian renal transplant population prescribed EC-MPS together with prednisolone and tacrolimus. Intensive pharmacokinetic sampling (17 samples each) was performed in 18 patients to measure MPA AUC₀₋₁₂. The profiles at 1 month were used to develop the simplified strategies and those at 5.5 months used for validation. We followed two approaches. In one, the AUC was calculated using the trapezoidal rule with fewer time points followed by an extrapolation. In the second approach, by stepwise multiple regression analysis, models with different time points were identified and linear regression analysis performed. Using the trapezoidal rule, two equations were developed with six time points and sampling to 6 or 8 hours (8hrAUC[₀₋₁₂exp]) after the EC-MPS dose. On validation, the 8hrAUC(₀₋₁₂exp) compared with total measured AUC₀₋₁₂ had a coefficient of correlation (r²) of 0.872 with a bias and precision (95% confidence interval) of 0.54% (-6.07-7.15) and 9.73% (5.37-14.09), respectively. Second, limited sampling strategies were developed with four, five, six, seven, and eight time points and completion within 2 hours, 4 hours, 6 hours, and 8 hours after the EC-MPS dose. On validation, six, seven, and eight time point equations, all with sampling to 8 hours, had an acceptable r with the total measured MPA AUC₀₋₁₂ (0.817-0.927). In the six, seven, and eight time points, the bias (95% confidence interval) was 3.00% (-4.59 to 10.59), 0.29% (-5.4 to 5.97), and -0.72% (-5.34 to 3.89) and the precision (95% confidence interval) was 10.59% (5.06-16.13), 8.33% (4.55-12.1), and 6.92% (3.94-9.90), respectively. Of the eight simplified approaches, inclusion of seven or eight time points improved the accuracy of the predicted AUC compared with the actual and can be advocated based on the priority of the user.
Aims:There are few studies on the pathology of warty carcinoma (WC) of the penis and these have been from South America. Penile cancers are not uncommon in India. We reviewed the frequency of subtypes of penile squamous carcinoma (SC) and the pathological features and outcome of WC when compared to squamous carcinoma-not otherwise specified (SC-NOS). We also compared the clinicopathological features of WC in our series with those published earlier.Materials and Methods:We studied 103 cases of penile cancers over 6 years. Cases were classified into different subtypes according to established histologic criteria. Clinicopathologic features were studied in detail and compared among the different subtypes, especially between WC and SC-NOS. The patients were followed-up and disease free survival in months was noted.Results:SC-NOS constituted 75.7% of all penile cancer cases in our series. The frequency of other subtypes was WC: 9.7%, verrucous: 3.9%, basaloid type and papillary type: 0.97% each, and mixed types 8.7%. The average tumor size and depth of invasion did not differ significantly between the two subtypes. Frequency of lymphovascular emboli and percentage of lymph node metastasis in WC (30 and 10%) were lesser than in SC-NOS (49.37 and 26.58%), respectively. There were no recurrences after partial penectomy in the WC subtype. In the SC-NOS type, three cases had recurrence after partial/total penectomy.Conclusion:Warty carcinoma constitutes nearly 10% of all penile squamous cell cancers. These patients seem to have a less aggressive behavior than SC-NOS.
The aim of the study was to determine the reliability of estimating area under the curve from 0 to 6 hours (AUC0-6) of mycophenolic acid (MPA) by pooling the blood samples from different sampling time points. Eighty 6-hour concentration-time profiles were obtained from 68 patients on mycophenolate mofetil and the MPA AUC0-6 was calculated. In the pooled strategy, each of the equally spaced time point samples was pooled into two samples. Two rectangles were created instead of multiple trapezoids and the sum of their areas equal to the MPA AUC0-6. The linear correlation (r), intraclass correlation, bias, and precision were calculated between the pooled MPA AUC0-6 and the MPA AUC0-6 derived from measurements at different time points. Pharmacokinetic profiles of an additional 20 patients were obtained to study the possibility of using fewer time points to create a single pooled sample to obtain MPA AUC0-6. The linear correlation (r) and intraclass correlation between pooled and measured MPA AUC0-6 was 0.982 and 0.979, respectively. There was a highly significant correlation (r) of 0.978 between the pooled versus measured for both MPA AUC0-3 and MPA AUC3-6. The mean bias and precision (95% confidence interval) for pooled with total measured MPA AUC0-6 was -6.4% (-7.8% to -4.94%) and 7.37% (6.21%-8.54%), respectively. The pooled sample approach using only five time points to estimate MPA AUC0-6 had an unacceptable bias and precision. Pooling 10 samples to a set of two samples gave a highly accurate measure of MPA AUC0-6. The advantages for a central laboratory are the high throughput of samples and the transportation of only two specimens from other centers, all of which leads to a reduction in cost. This approach is extremely useful for studies aimed at examining the bioavailability of mycophenolate mofetil in different ethnic populations within India.
In this paper, a single element antenna is presented for 5G millimeter wave (mm Wave) applications and using single element can be made for MIMO, array of antenna. The bandwidth value of the presented antenna is 11.1 GHz (from 25.1 GHz to 36.2 GHz) and overall size is only 11.5 × 12.5 mm2. It shows that very good candidate for 5G applications. Future wireless communications services require high data rates as technology is progressing. Multi-input multi-output (MIMO) technology for emerging and future wireless communications systems is seen as a fundamental requirement. Technologies like data rate improvements, transmission speed, channel capacity and throughput increase the performance of wireless communication systems substantially. On the side of the transmitter and the receiver, MIMO antennas are several. The design of effective MIMO antennas with a high rate of data and large capacity presents various obstacles.
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