PubMed · 11627202
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P Soetaert. 1973. [Not Available].. https://pubmed.ncbi.nlm.nih.gov/11627202/
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PURPOSE: Precision medicine, also known as personalized medicine, enables the provision of tailored health services to patients. In the prevention, early detection, and treatment of cancers, precision medicine is highly promising, given the increasing use of genomic profiling for diagnosis and adapting therapies in several tumor types. Artificial Intelligence (AI) can support this process by analyzing vast amounts of relevant data. However, high-quality data and financial investments in the health system are essential for the implementation of precision medicine and AI solutions in routine cancer care. DESIGN/METHODOLOGY/APPROACH: Building on the quantitative outcomes of a foresight exercise published in another study, this article collects qualitative data to gain more detailed insights into the future of precision oncology in Belgium and discusses the role of AI in this field. It reports the results of a series of expert workshops, focusing on four hypothetical future scenarios that are centered around technological and economic issues that must be overcome for the widespread use of precision oncology in Belgium. FINDINGS: The study concludes that all four scenarios discussed in the workshops would require supportive policy measures in Belgium, which should go beyond mere technological and economic considerations, such as involving patient associations and the public in policy design or creating multi-disciplinary expert groups for precision medicine. ORIGINALITY/VALUE: To the best of our knowledge, this is the first study to employ foresight methodology to illustrate possible future scenarios, scrutinize feasible approaches for implementing precision oncology in Belgium, and discuss the use of AI in this context.
Before an active compound can be registered as a drug, it needs to be demonstrated that it does not cause particular unwanted compound specific side effects. Demonstrating non-inferiority of an active drug with placebo with respect to an unwanted side effect is often based on pharmacodynamic 3 x 3 cross-over trials, with the third treatment arm consisting of a positive control. The main comparison then is the pairwise comparison between active drug and placebo. In this paper, two different non-parametric methods with adjustment for period effect are compared with the non-parametric non-adjusted test and the parametric period-adjusted test with respect to size and power. The non-parametric test with period adjustment based on rank alignment has generally the largest power, but its size exceeds the nominal significance level. The non-parametric test with period adjustment based on stratification has low power for trials with a small number of subjects. The non-parametric test without period adjustment is a valid alternative in such cases, but its power decreases substantially in the presence of period effects. In the case of unbalanced designs, however, only the non-parametric test with period adjustment based on stratification can be used.
Flow cytometry is an accurate but expensive method to determine absolute CD4 cell counts. We compared different methods to measure absolute CD4 counts in blood samples from HIV-infected and uninfected subjects using a research/clinical flow cytometer (FACScan); a dedicated clinical instrument (FACSCount); and a volumetric, mobile, open-system flow cytometer equipped with 3 fluorescence and 2 light scatter detectors (Cyflow SL blue). The FACScan and Cyflow were used as single-platform instruments, but they differ in running cost, which is a central factor for resource-poor settings. Direct volumetric and bead-based CD4 measurements on the Cyflow were compared with 2 bead-based single-platform CD4 measurements on the FACSCount and on FACScan (TruCount) in "Le Dantec" Hospital, Dakar, Senegal, using whole blood samples from 102 HIV+ and 28 HIV- subjects. The agreement between the various measurement methods was evaluated by Bland-Altman analysis. Volumetric CD4 measurements on the Cyflow using a no-lyse-no-wash (NLNW) procedure and a lyse-no-wash (LNW) procedure correlated well with each other (R2 = 0.98) and with CD4 measurements on the FACSCount (R2 = 0.97) and FACScan (R2 = 0.97), respectively. Red blood cell lysis had no negative effect on the accuracy of absolute CD4 counting on the Cyflow. An excellent correlation was observed between bead-based CD4 measurements on the Cyflow and CD4 measurements on the FACSCount (R2 = 0.99) and FACScan (R2 = 0.99). Rigid internal and external quality control monitoring and adequate training of technicians were considered essential to generate accurate volumetric CD4 measurements on the Cyflow.