Patient and Caregiver Perceptions of an Interface Design to Communicate Artificial Intelligence-Based Prognosis for Patients With Advanced Solid Tumors.

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.

Lower frequencies of circulating suppressive regulatory T cells and higher frequencies of CD4+ naïve T cells at baseline are associated with severe immune-related adverse events in immune checkpoint inhibitor-treated melanoma.

BACKGROUND: Immune-related adverse events (irAEs) are major barriers of clinical management and further development of immune checkpoint inhibitors (ICIs) for cancer therapy. Therefore, biomarkers associated with the onset of severe irAEs are needed. In this study, we aimed to identify immune features detectable in peripheral blood and associated with the development of severe irAEs that required clinical intervention. METHODS: We used a 43-marker mass cytometry panel to characterize peripheral blood mononuclear cells from 28 unique patients with melanoma across 29 lines of ICI therapy before treatment (baseline), before the onset of irAEs (pre-irAE) and at the peak of irAEs (irAE-max). In the 29 lines of ICI therapy, 18 resulted in severe irAEs and 11 did not. RESULTS: Unsupervised and gated population analysis showed that patients with severe irAEs had a higher frequency of CD4+ naïve T cells and lower frequency of CD16+ natural killer (NK) cells at all time points. Gated population analysis additionally showed that patients with severe irAEs had fewer T cell immunoreceptor with Ig and ITIM domain (TIGIT+) regulatory T cells at baseline and more activated CD38+ CD4+ central memory T cells (TCM) and CD39+ and Human Leukocyte Antigen-DR Isotype (HLA-DR)+ CD8+ TCM at peak of irAEs. The differentiating immune features at baseline were predominantly seen in patients with gastrointestinal and cutaneous irAEs and type 1 diabetes. Higher frequencies of CD4+ naïve T cells and lower frequencies of CD16+ NK cells were also associated with clinical benefit to ICI therapy. CONCLUSIONS: This study demonstrates that high-dimensional immune profiling can reveal novel blood-based immune signatures associated with risk and mechanism of severe irAEs. Development of severe irAEs in melanoma could be the result of reduced immune inhibitory capacity pre-ICI treatment, resulting in more activated TCM cells after treatment.

A single center case series of immune checkpoint inhibitor-induced type 1 diabetes mellitus, patterns of disease onset and long-term clinical outcome.

Background: Type 1 diabetes mellitus (T1DM) is a rare, but serious immune-related adverse event (irAE) of immune checkpoint inhibitors (ICIs). Our goal was to characterize treatment outcomes associated with ICI-induced T1DM through analysis of clinical, immunological and proteomic data. Methods: This was a single-center case series of patients with solid tumors who received ICIs and subsequently had a new diagnosis of T1DM. ICD codes and C-peptide levels were used to identify patients for chart review to confirm ICI-induced T1DM. Baseline blood specimens were studied for proteomic and immunophenotypic changes. Results: Between 2011 and 2023, 18 of 3744 patients treated at Huntsman Cancer Institute with ICIs were confirmed to have ICI-induced T1DM (0.48%). Eleven of the 18 patients received anti-PD1 monotherapy, 4 received anti-PD1 plus chemotherapy or targeted therapy, and 3 received ipilimumab plus nivolumab. The mean time to onset was 218 days (range 22-418 days). Patients had sudden elevated serum glucose within 2-3 weeks prior to diagnosis. Sixteen (89%) presented with diabetic ketoacidosis. Three of 12 patients had positive T1DM-associated autoantibodies. All patients with T1DM became insulin-dependent through follow-up. At median follow-up of 21.9 months (range 8.4-82.4), no patients in the melanoma group had progressed or died from disease. In the melanoma group, best responses were 2 complete response and 2 partial response while on active treatment; none in the adjuvant group had disease recurrence. Proteomic analysis of baseline blood suggested low inflammatory (IL-6, OSMR) markers and high metabolic (GLO1, DXCR) markers in ICI-induced T1DM cohort. Conclusions: Our case series demonstrates rapid onset and irreversibility of ICI-induced T1DM. Melanoma patients with ICI-induced T1DM display excellent clinical response and survival. Limited proteomic data also suggested a unique proteomic profile. Our study helps clinicians to understand the unique clinical presentation and long-term outcomes of this rare irAE for best clinical management.

Design of an interface to communicate artificial intelligence-based prognosis for patients with advanced solid tumors: a user-centered approach.

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.

Evaluation of Oncology Hospital at Home: Unplanned Health Care Utilization and Costs in the Huntsman at Home Real-World Trial.

PURPOSE: Patients with cancer experience high rates of morbidity and unplanned health care utilization and may benefit from new models of care. We evaluated an adult oncology hospital at home program's rate of unplanned hospitalizations and health care costs and secondarily, emergency department (ED) use, length of hospital stays, and intensive care unit (ICU) admissions during the 30 days after enrollment. METHODS: We conducted a prospective, nonrandomized, real-world cohort comparison of 367 hospitalized patients with cancer-169 patients consecutively admitted after hospital discharge to Huntsman at Home (HH), a hospital-at-home program, compared with 198 usual care patients concurrently identified at hospital discharge. All patients met clinical criteria for HH admission, but those in usual care lived outside the HH service area. Primary outcomes were the number of unplanned hospitalizations and costs during the 30 days after enrollment. Secondary outcomes included length of hospital stays, ICU admissions, and ED visits during the 30 days after enrollment. RESULTS: Groups were comparable except that more women received HH care. In propensity-weighted analyses, the odds of unplanned hospitalizations was reduced in the HH group by 55% (odds ratio, 0.45, 95% CI, 0.29 to 0.70; P < .001) and health care costs were 47% lower (mean cost ratio, 0.53; 95% CI, 0.39 to 0.72; P < .001) over the 30-day period. Secondary outcomes also favored HH. Total hospital stay days were reduced by 1.1 days (P = .004) and ED visits were reduced by 45% (odds ratio, 0.55; 95% CI, 0.33 to 0.92; P = .022). There was no evidence of a difference in ICU admissions (P = .972). CONCLUSION: This oncology hospital at home program shows initial promise as a model for oncology care that may lower unplanned health care utilization and health care costs.

Real-world experience with elective discontinuation of PD-1 inhibitors at 1 year in patients with metastatic melanoma.

BACKGROUND: Randomized trials evaluating programmed cell death protein 1 (PD-1) inhibitors in metastatic melanoma either permitted treatment for 2 years (pembrolizumab) or more (nivolumab). The optimal duration of therapy is currently unknown due to limited data, and shorter therapies may be effective. METHODS: Data of patients with metastatic cutaneous melanoma treated with single-agent PD-1 inhibitors at Huntsman Cancer Institute from January 1, 2015, to December 31, 2018, was reviewed to identify a continuous series of patients who made the joint decision with their provider to electively discontinue therapy at 1 year (>6 months and <18 months) in the setting of ongoing treatment response or disease stability. Patients were excluded if they received PD-1 inhibitors with other systemic therapy, had prior exposure to PD-1 therapy, or discontinued treatment due to disease progression or immune-related adverse event. Best objective response (BOR) per RECIST V.1.1 at treatment discontinuation, progression-free survival (PFS), and retreatment characteristics was analyzed. RESULTS: Of 480 patients who received PD-1 inhibitors, 52 met the inclusion criteria. The median treatment duration from first to the last dose was 11.1 months (95% CI 10.5 to 11.4). BOR was complete response in 13 (25%), partial response in 28 (53.8%), and stable disease in 11 (21.2%) patients. After a median follow-up of 20.5 months (range 3-49.2) from treatment discontinuation, 39 (75%) patients remained without disease progression, while 13 (25%) had progression (median PFS 3.9 months; range 0.7-30.9). On multivariable analysis, younger age, history of brain metastasis, and higher lactate dehydrogenase at the time of anti-PD-1 discontinuation were associated with recurrence. Patients with recurrent melanoma were managed with localized treatment, anti-PD-1 therapies, and BRAF-MEK inhibitors. All patients except one were alive at data cutoff. CONCLUSION: In this large real-world, observational cohort study, the majority of patients with metastatic melanoma after 1 year of anti-PD-1 therapy remained without progression on long-term follow-up. The risk of disease progression even in patients with residual disease on imaging was low. After prospective validation, elective PD-1 discontinuation at 1 year may reduce financial and immunotherapy-related toxicity without sacrificing outcomes.

External Validation of a Machine Learning Model to Predict 6-Month Mortality for Patients With Advanced Solid Tumors.

This prognostic study performed external validation of a machine learning model to predict 6-month mortality among patients with advanced solid tumors.

Pralatrexate Monitoring Using a Commercially Available Methotrexate Assay to Avoid Potential Drug Interactions.

Pralatrexate (PDX) is a folate antagonist structurally similar to methotrexate (MTX). Unlike MTX, it is currently not known whether PDX exhibits delayed clearance and heightened toxicity in the setting of fluid overload. A specific serum assay for PDX is not commercially available. To our knowledge, we report the first case using an MTX serum assay as a surrogate for PDX concentrations to avoid a potential drug-drug interaction with pralatrexate. We describe a 76-year-old man with refractory cutaneous T-cell lymphoma who began therapy with weekly PDX 15 mg/m(2) intravenous infusions on days 1, 8, and 15 of a 28-day cycle. He subsequently developed mucositis, a moderate right-sided pleural effusion, and peripheral edema over the next 5 weeks. Aggressive diuresis with furosemide was initiated, which was then withheld the day before his next PDX dose to avoid a potential drug-drug interaction between PDX and furosemide. His baseline MTX/PDX concentration (measured prior to administration of the cycle 2, week 2 PDX dose) was less than 0.20 µmol/L (i.e., undetectable). After PDX administration, his 1-hour peak MTX/PDX concentration increased to 0.58 µmol/L. Aggressive diuresis was withheld until his MTX/PDX concentration was undetectable, 43.5 hours later. PDX is more potent than MTX and displays similar pharmacokinetic properties. PDX concentrations using the serum MTX assay reflect lower values than those reported from PDX-specific assays in clinical studies. Because PDX is approved by the U.S. Food and Drug Administration for the treatment of uncommon malignancies, it is unlikely that a specific assay will be commercially developed. We propose that the MTX serum assay has merit for use in determining when to reinstate possible interacting drug therapies such as loop diuretics.

A phase I study to determine the pharmacokinetics and urinary excretion of belinostat and metabolites in patients with advanced solid tumors.

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/m2. 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.

A phase I clinical trial of the effect of belinostat on the pharmacokinetics and pharmacodynamics of warfarin.

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.