Investigation toward the economic feasibility of personalized medicine for healthcare service providers: the case of bladder cancer.

In today's complex healthcare landscape, the pursuit of delivering optimal patient care while navigating intricate economic dynamics poses a significant challenge for healthcare service providers (HSPs). In this already complex dynamic, the emergence of clinically promising personalized medicine-based treatment aims to revolutionize medicine. While personalized medicine holds tremendous potential for enhancing therapeutic outcomes, its integration within resource-constrained HSPs presents formidable challenges. In this study, we investigate the economic feasibility of implementing personalized medicine. The central objective is to strike a balance between catering to individual patient needs and making economically viable decisions. Unlike conventional binary approaches to personalized treatment, we propose a more nuanced perspective by treating personalization as a spectrum. This approach allows for greater flexibility in decision-making and resource allocation. To this end, we propose a mathematical framework to investigate our proposal, focusing on Bladder Cancer (BC) as a case study. Our results show that while it is feasible to introduce personalized medicine, a highly efficient but highly expensive one would be short-lived relative to its less effective but cheaper alternative as the latter can be provided to a larger cohort of patients, optimizing the HSP's objective better.

Socio-demographic Predictors of Hospitalization Duration Among Patients with Borderline Personality Disorder.

Borderline personality disorder (BPD) is a complex psychopathology associated with high service utilization rates. In turn, the hospitalization of BPD patients is a controversial challenge for mental health professionals. Prior literature has identified certain socio-demographic factors as linked to an increased risk of BPD. In this study, we examined the possible connection between these socio-demographic factors and hospitalization duration. We analyzed 1077 hospitalization records of 200 BPD-diagnosed patients. Patients' gender, age, education level, employment and marital statuses, and living arrangement were statistically significantly linked with hospitalization duration. Specifically, female gender, age twenty or below, no high-school diploma (or, to a lesser extent, a diploma with no academic education), unemployment status and/or patients who live with parents are strongly associated with longer hospitalizations compared to male gender, older patients, more educated, married/divorced status and/or those who do not live with their parents. Additionally, the results point to a weak, albeit statistically significant, temporal pattern with more advanced hospitalizations generally aligning with the duration of their preceding ones, while being slightly shorter. In order to prevent potentially unnecessary prolonged and regressive hospitalizations, an estimation of the expected hospitalization duration should be explicitly considered when setting hospitalization goals and plans.

4a,4b-Dihydrophenanthrene → cis-stilbene photoconversion: TD-DFT/DFT study.

CONTEXT: DHP → CS photoconversion was analyzed in terms of electron density redistribution for the first time. The following explanation for the non-recovery of the C4a-C4b bond upon CS relaxation is proposed: during this process, the Coulomb repulsion energy between these pairs of atoms increases by almost one and a half times, and their bonding by an electron at LUMO is insufficient to recover the C4a-C4b bond. According to calculations, upon CS relaxation, the linker connecting the benzene rings undergoes significant structural changes. In this case, the distance between the C4a and C4b atoms increases from 3.00 Å to 3.28 Å. Calculations showed that the C4a-C4b vibration of the DHP bond has a very low intensity. Therefore, thermal motion does not contribute to the rupture of this bond. METHODS: All calculations were performed using the Gaussian16 software package at the B3LYP/6-311 + + G(d,p)/IEFPCM theory level. B3LYP was the only hybrid functional supported by Gaussian16, which ensured the cleavage of the C4a-C4b bond of DHP while optimizing its S1 excited state. A quantitative description of the redistribution of electron density in the studied conformers was carried out using the analysis of the NPA of atomic charges. Cyclohexane was used as an implicitly specified non-polar solvent. Visualization of molecular orbitals, and electron densities, as well as plotting of calculated IR spectra, were performed using the Gaussview6 software package.

Mathematical modeling of BCG-based bladder cancer treatment using socio-demographics.

Cancer is one of the most widespread diseases around the world with millions of new patients each year. Bladder cancer is one of the most prevalent types of cancer affecting all individuals alike with no obvious "prototypical patient". The current standard treatment for BC follows a routine weekly Bacillus Calmette-Guérin (BCG) immunotherapy-based therapy protocol which is applied to all patients alike. The clinical outcomes associated with BCG treatment vary significantly among patients due to the biological and clinical complexity of the interaction between the immune system, treatments, and cancer cells. In this study, we take advantage of the patient's socio-demographics to offer a personalized mathematical model that describes the clinical dynamics associated with BCG-based treatment. To this end, we adopt a well-established BCG treatment model and integrate a machine learning component to temporally adjust and reconfigure key parameters within the model thus promoting its personalization. Using real clinical data, we show that our personalized model favorably compares with the original one in predicting the number of cancer cells at the end of the treatment, with [Formula: see text] improvement, on average.