Background & Aims-Photodynamic therapy (PDT) has been shown to be effective in the treatment of high-grade dysplasia (HGD)/mucosal carcinoma in Barrett's esophagus (BE). Substantial proportions of patients do not respond to PDT or progress to carcinoma despite PDT. The role of biomarkers in predicting response to PDT is unknown. We aimed to determine if biomarkers known to be associated with neoplasia in BE can predict loss of dysplasia in patients treated with ablative therapy for HGD/intramucosal cancer.
Objective The risk of developing adenocarcinoma in non-dysplastic Barrett's oesophagus is low and difficult to predict. Accurate tools for risk stratification are needed to increase the efficiency of surveillance. We aimed to develop a prediction model for progression using clinical variables and genetic markers. Methods In a prospective cohort of patients with non-dysplastic Barrett's oesophagus, we evaluated six molecular markers: p16, p53, Her-2/neu, 20q, MYC, and aneusomy by DNA fluorescence in situ hybridisation on brush cytology specimens. Primary study outcomes were the development of high-grade dysplasia or oesophageal adenocarcinoma. The most predictive clinical variables and markers were determined using Cox proportional-hazards models, receiver-operating-characteristic curves and a leave-one-out analysis. Results A total of 428 patients participated (345 men; median age 60 years) with a cumulative follow-up of 2019 patient-years (median 45 months per patient). Of these patients, 22 progressed; nine developed high-grade dysplasia and 13 oesophageal adenocarcinoma. The clinical variables, age and circumferential Barrett's length, and the markers, p16 loss, MYC gain, and aneusomy, were significantly associated with progression on univariate analysis. We defined an ‘Abnormal Marker Count’ that counted abnormalities in p16, MYC and aneusomy, which significantly improved risk prediction beyond using just age and Barrett's length. In multivariate analysis, these three factors identified a high-risk group with an 8.7-fold (95% CI, 2.6 to 29.8) increased hazard ratio compared with the low-risk group, with an area under the curve of 0.76 (95% CI, 0.66 to 0.86). Conclusion A prediction model based on age, Barrett's length, and the markers p16, MYC, and aneusomy determines progression risk in non-dysplastic Barrett's oesophagus.
Background Recommended dietary protein allowances for chronic peritoneal dialysis (PD) patients are approximately 60% higher than the dietary protein allowances for healthy adults. The relative contribution of dialysate protein and amino acid losses to these high protein requirements or total nitrogen losses is uncertain. Methods Following a peritoneal equilibration test, two 24-hour dialysate collections (24–1 and 24–2) were performed in 9 stable patients undergoing automated PD [4 males, 3 diabetics, age 43 ± 5 years (mean ± SEM), dialysis vintage 42 ± 6 months, dialysate-to-plasma ratio of creatinine 0.61 ± 0.04]. Dialysate effluent from nighttime cycling was collected separately from the daytime dwells. Results The measured 24-hour protein losses were 9.4 ± 0.6 (24-31) and 10.8 ± 0.8 (24-32) g/day. Even though day dwells accounted for 27% of daily dialysate volume, they accounted for 40% of daily protein and amino acid losses. The frequency of nighttime cycling and duration of dwell were significant predictors of peritoneal protein losses. Dialysate protein and amino acid losses constituted 24% ± 2% and 3.1% ± 0.3% of dialysate nitrogen and 14% ± 1% and 1.7% ± 0.1% of dietary nitrogen intake respectively. Conclusions Treatment with automated PD is associated with somewhat higher 24-hour dialysate protein losses compared to previous reports among continuous ambulatory PD patients. Dialysate protein and amino acid losses constitute a small, albeit significant, proportion of total nitrogen appearance and thus may contribute to the increased dietary protein requirements of chronic PD patients.
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