An Open-Source R Package for Detection of Adverse Events Under-Reporting in Clinical Trials: Implementation and Validation by the IMPALA (Inter coMPany quALity Analytics) Consortium.

Accurate and timely reporting of adverse events (AEs) in clinical trials is crucial to ensuring data integrity and patient safety. However, AE under-reporting remains a challenge, often highlighted in Good Clinical Practice (GCP) audits and inspections. Traditional detection methods, such as on-site investigator audits via manual source data verification (SDV), have limitations. Addressing this, the open-source R package {simaerep} was developed to facilitate rapid, comprehensive, and near-real-time detection of AE under-reporting at each clinical trial site. This package leverages patient-level AE and visit data for its analyses. To validate its efficacy, three member companies from the Inter coMPany quALity Analytics (IMPALA) consortium independently assessed the package. Results showed that {simaerep} consistently and effectively identified AE under-reporting across all three companies, particularly when there were significant differences in AE rates between compliant and non-compliant sites. Furthermore, {simaerep}'s detection rates surpassed heuristic methods, and it identified 50% of all detectable sites as early as 25% into the designated study duration. The open-source package can be embedded into audits to enable fast, holistic, and repeatable quality oversight of clinical trials.

Frequency of chromosome 17 polysomy in relation to CEP17 copy number in a large breast cancer cohort.

Eligibility to anti-HER2 therapy for breast tumors strictly depends on demonstrating HER2 overexpression (by immunohistochemistry) or HER2 gene amplification by in situ hybridization (ISH), usually defined by the ratio of HER2 gene to chromosome 17 centromere (CEP17) copies. However, the CEP17 copy number increase (CNI) has been proven responsible for misleading HER2 FISH results and recent small cohort studies suggest that chromosome 17 polysomy is actually very rare. Here we investigated by FISH the frequency of true chromosome 17 polysomy in a consecutive cohort of 5,477 invasive breast cancer patients. We evaluated and selected the LSI 17p11.2 probe for chromosome 17 enumeration on a training cohort of 67 breast cancer samples (CEP17 ≥ 2.5). LSI 17p11.2 was used in the 297/5,477 patients from the validation cohort displaying CEP17 CNI (CEP17 ≥ 3.0). Using HER2/17p11.2 scoring criteria, 37.3%/1.5% patients initially classified as equivocal/non-amplified were reclassified as amplified. For a more accurate assessment of chromosome 17 and ploidy in the samples, we tested six markers located on chromosome 17 and centromeric regions of chromosome 8 (CEP8) and 11 (CEP11) in 67 patients with CEP17 and LSI 17p11.2 CNI. True polysomy (hyperdiploidy) according to these markers was found in 0.48% of cases (24/5,020). CEP8 and CEP11 CNI (≥3.0) was more frequent in the hyperdiploid than CEP17 non-polysomic group (55.6% vs. 6.1% and 25% vs. 2.3%, respectively). Our results suggest that chromosome 17 polysomy is a rare event found in <1% breast cancer cases and that polysomy of other chromosomes frequently occurs with chromosome 17 polysomy.

Total and High Molecular Weight Adiponectin Levels and Prediction of Cardiovascular Risk in Diabetic Patients.

The study aimed at assessing the potential use of lower total and HMW adiponectin levels for predicting cardiovascular risk in patients with type 2 diabetes mellitus (T2DM). Concentrations of total adiponectin or high molecular weight (HMW) adiponectin decrease in association with the development of metabolic dysfunction such as obesity, insulin resistance, or T2DM. Increased adiponectin levels are associated with a lower risk for coronary heart disease. A total of 551 individuals were assessed. The first group comprised metabolically healthy participants (143 females, and 126 males) and the second group were T2DM patients (164 females, and 118 males). Both total adiponectin and HMW adiponectin in diabetic patients were significantly lower when compared with the group of metabolically healthy individuals. There was a weak monotonic correlation between HMW adiponectin levels and triglycerides levels. Binary logistic regression analysis, gender adjusted, showed a higher cardiovascular risk in diabetic persons when both total adiponectin (OR = 1.700) and HMW adiponectin (OR = 2.785) levels were decreased. A decrease in total adiponectin levels as well as a decrease in its HMW adiponectin is associated with a higher cardiovascular risk in individuals with T2DM. This association suggests that adiponectin levels may be potentially used as an epidemiological marker for cardiovascular risk in diabetic patients.