Clinical trial monitoring effectiveness: Remote risk-based monitoring versus on-site monitoring with 100% source data verification.

BACKGROUND/AIMS: Traditional on-site monitoring of clinical trials via frequent site visits and 100% source data verification is cost-consuming, and it still cannot guarantee data quality effectively. Depending on the types and designs of clinical trials, an alternative would be combining several monitoring methods, such as risk-based monitoring and remote monitoring. However, there is insufficient evidence of its effectiveness. This research compared the effectiveness of risk-based monitoring with a remote monitoring system with that of traditional on-site monitoring. METHODS: With a cloud-based remote monitoring system called beagle View®, we created a remote risk-based monitoring methodology that focused only on critical data and processes. We selected a randomized controlled trial conducted at Tohoku University Hospital and randomly sampled 11 subjects whose case report forms had already been reviewed by data managers. Critical data and processes were verified retrospectively by remote risk-based monitoring; later, all data and processes were confirmed by on-site monitoring. We compared the ability of remote risk-based monitoring to detect critical data and process errors with that of on-site monitoring with 100% source data verification, including an examination of clinical trial staff workload and potential cost savings. RESULTS: Of the total data points (n = 5617), 19.7% (n = 1105, 95% confidence interval = 18.7-20.7) were identified as critical. The error rates of critical data detected by on-site monitoring, remote risk-based monitoring, and data review by data managers were 7.6% (n = 84, 95% CI = 6.2-9.3), 7.6% (n = 84, 95% confidence interval = 6.2-9.3), and 3.9% (n = 43, 95% confidence interval = 2.9-5.2), respectively. The total number of critical process errors detected by on-site monitoring was 14. Of these 14, 92.9% (n = 13, 95% confidence interval = 68.5-98.7) and 42.9% (n = 6, 95% confidence interval = 21.4-67.4) of critical process errors were detected by remote risk-based monitoring and data review by data managers, respectively. The mean time clinical trial staff spent dealing with remote risk-based monitoring was 9.9 ± 5.3 (mean ± SD) min per visit per subject. Our calculations show that remote risk-based monitoring saved between 9 and 41 on-site monitoring visits, corresponding to a cost of between US$13,500 and US$61,500 per trial site. CONCLUSION: Remote risk-based monitoring was able to detect critical data and process errors as well as on-site monitoring with 100% source data verification, saving travel time and monitoring costs. Remote risk-based monitoring offers an effective alternative to traditional on-site monitoring of clinical trials.

Reno-protective effects of oral alkalizing agents in chronic kidney disease with aciduria: protocol for a randomized cohort study.

BACKGROUND: Aciduria caused by urinary excretion of acidic metabolic wastes produced in daily life is known to be augmented in patients with chronic kidney disease (CKD). To evaluate the reno-protective effect of oral alkalizing agents for the improvement of metabolic acidosis and neutralization of intratubular pH in the patients with mild stages of CKD. Also, to identify reno-protective surrogate markers in the serum and urine that can closely associate the effect of urine alkalization. METHODS: In this single-centered, open-labeled, randomized cohort study, patients with CKD stages G2, G3a and G3b, who visited and were treated at Tohoku University Hospital during the enrollment period were registered. We administered sodium bicarbonate or sodium-potassium citrate as the oral alkalinizing agents. A total of 150 patients with CKD will be randomly allocated into the following three groups: sodium bicarbonate, sodium-potassium citrate and standard therapy group without any alkalinizing agents. The data of performance status, venous blood test, spot urine test, venous blood-gas test, electrocardiogram, renal arterial ultrasonography and chest X-ray will be collected at 0, 6, 12 and 24 weeks (short-term study) from starting the interventions. These data will be also collected at 1 and 2 years (long-term study). The samples of plasma and serum and early-morning urine at every visit will be acquired for the analysis of renal function and surrogate uremic biomarkers. The recruitment for this cohort study terminated in March, 2018, and the follow-up period for all the enrolled subjects will be terminated in December, 2020. The primary endpoint will be the development of originally-defined significant renal dysfunction or the occurrence of any cerebrovascular disease in the short-term study. The secondary endpoint will be the same endpoints as in the long-term study, or the patients with significant changes in the suggested the surrogate biomarkers. DISCUSSION: The findings of this study will address the importance of taking oral alkalizing agents in the patients with early stages of CKD, furthermore they could address any new surrogate biomarkers that can be useful from early stage CKD. TRIAL REGISTRATION: Registered Report Identifier: UMIN000010059 and jRCT021180043. The trial registration number; 150. Date of registration; 2013/02/26.

Application of Large Electronic Medical Database for Detecting Undiagnosed Patients in the General Population.

Clinical application of accumulated medical big data is a hot topic in medical informatics. Not only for suggesting possible diagnoses in each individual, large medical database can be possibly used for detecting undiagnosed patients in the general population. In this study, we tried to develop a computerized system of detecting overlooked undiagnosed patients with rare chronic diseases in the community population by utilizing the uniformed national medical insurance record database. A cumulative total of 489,823 hospital visits at one tertiary medical center were collected for this project. As the target disease, we selected esophagogastric junction outflow obstruction (EGJOO), including achalasia, which is known to be easily overlooked without performing a barium swallow test. Patient selection software automatically picked out 17,814 individuals with the given suspected diagnoses that could be misdiagnosed in patients with the target disease, from which the software further picked out 526 individuals who underwent upper endoscopy but did not undergo barium swallow test. Of them, the hospital medical records suggested that 39 people still suffered from prolonged symptoms lasting for more than 6 months after the first hospital visit. Among them, 16 individuals agreed to undergo the barium swallow test. One of them was confirmed to suffer from EGJOO, possibly based on some undiagnosed connective tissue diseases. An automated computerized detection system with uniform big medical data would realize more efficient and less expensive screening system for undiagnosed chronic diseases in the general population based on symptoms and previously performed examinations in each individual.