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Purpose: Use of artificial intelligence (AI) in cancer care is increasing. What remains unclear is how best to design patient-facing systems that communicate AI output. With oncologist input, we designed an interface that presents patient-specific, machine learning-based 6-month survival prognosis information designed to aid oncology providers in preparing for and discussing prognosis with patients with advanced solid tumors and their caregivers. The primary purpose of this study was to assess patient and caregiver perceptions and identify enhancements of the interface for communicating 6-month survival and other prognosis information when making treatment decisions concerning anticancer and supportive therapy., Methods: This qualitative study included interviews and focus groups conducted between November and December 2022. Purposive sampling was used to recruit former patients with cancer and/or former caregivers of patients with cancer who had participated in cancer treatment decisions from Utah or elsewhere in the United States. Categories and themes related to perceptions of the interface were identified., Results: We received feedback from 20 participants during eight individual interviews and two focus groups, including four cancer survivors, 13 caregivers, and three representing both. Overall, most participants expressed positive perceptions about the tool and identified its value for supporting decision making, feeling less alone, and supporting communication among oncologists, patients, and their caregivers. Participants identified areas for improvement and implementation considerations, particularly that oncologists should share the tool and guide discussions about prognosis with patients who want to receive the information., Conclusion: This study revealed important patient and caregiver perceptions of and enhancements for the proposed interface. Originally designed with input from oncology providers, patient and caregiver participants identified additional interface design recommendations and implementation considerations to support communication about prognosis.

Objectives: To design an interface to support communication of machine learning (ML)-based prognosis for patients with advanced solid tumors, incorporating oncologists' needs and feedback throughout design., Materials and Methods: Using an interdisciplinary user-centered design approach, we performed 5 rounds of iterative design to refine an interface, involving expert review based on usability heuristics, input from a color-blind adult, and 13 individual semi-structured interviews with oncologists. Individual interviews included patient vignettes and a series of interfaces populated with representative patient data and predicted survival for each treatment decision point when a new line of therapy (LoT) was being considered. Ongoing feedback informed design decisions, and directed qualitative content analysis of interview transcripts was used to evaluate usability and identify enhancement requirements., Results: Design processes resulted in an interface with 7 sections, each addressing user-focused questions, supporting oncologists to "tell a story" as they discuss prognosis during a clinical encounter. The iteratively enhanced interface both triggered and reflected design decisions relevant when attempting to communicate ML-based prognosis, and exposed misassumptions. Clinicians requested enhancements that emphasized interpretability over explainability. Qualitative findings confirmed that previously identified issues were resolved and clarified necessary enhancements (eg, use months not days) and concerns about usability and trust (eg, address LoT received elsewhere). Appropriate use should be in the context of a conversation with an oncologist., Conclusion: User-centered design, ongoing clinical input, and a visualization to communicate ML-related outcomes are important elements for designing any decision support tool enabled by artificial intelligence, particularly when communicating prognosis risk., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Purpose: Belinostat is an inhibitor of histone deacetylase enzymes, resulting in DNA repair inhibition and apoptosis. Present data are lacking to provide dosing recommendations in renal insufficiency. The purpose of this trial was to assess the pharmacokinetics (PK) of belinostat and belinostat metabolites in plasma and urine., Methods: This was a phase I, single-center, open-label, two-part study. In Part I, patients received single-agent belinostat 1000 mg/m 2 . Blood and urine samples were collected at pre-specified time points to determine PK of belinostat and metabolites and their elimination in urine. In Part II, patients were permitted to continue belinostat in 21-day cycles on Days 1 through 5 until disease progression, unacceptable toxicity, or according to patient preference., Results: A total of nine patients with advanced solid tumors were treated. Median t max for belinostat was observed 10 min after the start of infusion. Concentrations of belinostat rapidly declined with a t 1/2 of 2.9 h. The mean fraction of belinostat excreted unchanged in urine was 0.926 %. The metabolites belinostat glucuronide and 3-ASBA represented the largest fractions of belinostat dose excreted in urine (30.5 and 4.61 %, respectively), while renal excretion appeared to be a minor route of elimination for the parent belinostat (<1 %). The most common adverse events were nausea, fatigue, and diarrhea. One Grade 3 adverse event (constipation) was thought to be treatment related., Conclusions: Urinary elimination of parent belinostat was minimal, although a combined 36.7 % of belinostat metabolites were excreted in urine. Since these metabolites are primarily inactive, belinostat may not require dosage adjustment in renal dysfunction.

Purpose: Belinostat is a potent small molecule inhibitor that exerts its antitumor effect through inhibition of histone deacetylase. The purpose of this study was to evaluate the pharmacokinetics and pharmacodynamics of warfarin (as a reference drug metabolized by CYP2C9) in the presence and absence of belinostat., Methods: We conducted a phase I, single-center, open-label, drug-drug interaction study between belinostat and warfarin. In part I, patients were given warfarin 5 mg orally (day-14 and 3) and belinostat 1000 mg/m(2) (days 1 through 5). Patients receiving benefit continued belinostat on days 1 through 5 every 21 days until disease progression, unacceptable toxicity, or per patient preference., Results: A total of 18 patients were treated. With belinostat, the least-squared means for maximum concentration (C max), area under the curve0-∞, and area under the curve0-t of R-warfarin were slightly increased. However, for the more potent S-warfarin isomer, the same parameters were primarily contained within the pre-specified equivalence limits of 0.80 and 1.25, indicating there was no statistically significant interaction between S-warfarin and belinostat. The most common adverse events were nausea, vomiting, and fatigue. Three grade 3 adverse events (diarrhea 5.6 %, nausea 5.6 %, and vomiting 5.6 %) were thought to be treatment related. Progression-free survival ranged from 0.2 to 13.8 months in all patients., Conclusions: Belinostat did not significantly affect the pharmacokinetics and pharmacodynamics of warfarin, indicating no clinically relevant effect on the enzymatic activity of CYP2C9.

Mus81-Eme1 endonuclease has been implicated in the rescue of stalled replication forks and the resolution of meiotic recombination intermediates in yeast. We used gene targeting to study the physiological requirements of Mus81 in mammals. Mus81-/- mice are viable and fertile, which indicates that mammalian Mus81 is not essential for recombination processes associated with meiosis. Mus81-deficient mice and cells were hypersensitive to the DNA cross-linking agent mitomycin C but not to gamma-irradiation. Remarkably, both homozygous Mus81-/- and heterozygous Mus81+/- mice exhibited a similar susceptibility to spontaneous chromosomal damage and a profound and equivalent predisposition to lymphomas and other cancers. These studies demonstrate a critical role for the proper biallelic expression of the mammalian Mus81 in the maintenance of genomic integrity and tumor suppression.