Development of a Multilevel Model to Identify Patients at Risk for Delay in Starting Cancer Treatment.

Importance: Delays in starting cancer treatment disproportionately affect vulnerable populations and can influence patients' experience and outcomes. Machine learning algorithms incorporating electronic health record (EHR) data and neighborhood-level social determinants of health (SDOH) measures may identify at-risk patients. Objective: To develop and validate a machine learning model for estimating the probability of a treatment delay using multilevel data sources. Design, Setting, and Participants: This cohort study evaluated 4 different machine learning approaches for estimating the likelihood of a treatment delay greater than 60 days (group least absolute shrinkage and selection operator [LASSO], bayesian additive regression tree, gradient boosting, and random forest). Criteria for selecting between approaches were discrimination, calibration, and interpretability/simplicity. The multilevel data set included clinical, demographic, and neighborhood-level census data derived from the EHR, cancer registry, and American Community Survey. Patients with invasive breast, lung, colorectal, bladder, or kidney cancer diagnosed from 2013 to 2019 and treated at a comprehensive cancer center were included. Data analysis was performed from January 2022 to June 2023. Exposures: Variables included demographics, cancer characteristics, comorbidities, laboratory values, imaging orders, and neighborhood variables. Main Outcomes and Measures: The outcome estimated by machine learning models was likelihood of a delay greater than 60 days between cancer diagnosis and treatment initiation. The primary metric used to evaluate model performance was area under the receiver operating characteristic curve (AUC-ROC). Results: A total of 6409 patients were included (mean [SD] age, 62.8 [12.5] years; 4321 [67.4%] female; 2576 [40.2%] with breast cancer, 1738 [27.1%] with lung cancer, and 1059 [16.5%] with kidney cancer). A total of 1621 (25.3%) experienced a delay greater than 60 days. The selected group LASSO model had an AUC-ROC of 0.713 (95% CI, 0.679-0.745). Lower likelihood of delay was seen with diagnosis at the treating institution; first malignant neoplasm; Asian or Pacific Islander or White race; private insurance; and lacking comorbidities. Greater likelihood of delay was seen at the extremes of neighborhood deprivation. Model performance (AUC-ROC) was lower in Black patients, patients with race and ethnicity other than non-Hispanic White, and those living in the most disadvantaged neighborhoods. Though the model selected neighborhood SDOH variables as contributing variables, performance was similar when fit with and without these variables. Conclusions and Relevance: In this cohort study, a machine learning model incorporating EHR and SDOH data was able to estimate the likelihood of delays in starting cancer therapy. Future work should focus on additional ways to incorporate SDOH data to improve model performance, particularly in vulnerable populations.

Adverse Events Reported by Patients With Cancer After Administration of a 2-Dose mRNA COVID-19 Vaccine.

BACKGROUND: Most safety and efficacy trials of the SARS-CoV-2 vaccines excluded patients with cancer, yet these patients are more likely than healthy individuals to contract SARS-CoV-2 and more likely to become seriously ill after infection. Our objective was to record short-term adverse reactions to the COVID-19 vaccine in patients with cancer, to compare the magnitude and duration of these reactions with those of patients without cancer, and to determine whether adverse reactions are related to active cancer therapy. PATIENTS AND METHODS: A prospective, single-institution observational study was performed at an NCI-designated Comprehensive Cancer Center. All study participants received 2 doses of the Pfizer BNT162b2 vaccine separated by approximately 3 weeks. A report of adverse reactions to dose 1 of the vaccine was completed upon return to the clinic for dose 2. Participants completed an identical survey either online or by telephone 2 weeks after the second vaccine dose. RESULTS: The cohort of 1,753 patients included 67.5% who had a history of cancer and 12.0% who were receiving active cancer treatment. Local pain at the injection site was the most frequently reported symptom for all respondents and did not distinguish patients with cancer from those without cancer after either dose 1 (39.3% vs 43.9%; P=.07) or dose 2 (42.5% vs 40.3%; P=.45). Among patients with cancer, those receiving active treatment were less likely to report pain at the injection site after dose 1 compared with those not receiving active treatment (30.0% vs 41.4%; P=.002). The onset and duration of adverse events was otherwise unrelated to active cancer treatment. CONCLUSIONS: When patients with cancer were compared with those without cancer, few differences in reported adverse events were noted. Active cancer treatment had little impact on adverse event profiles.

Psychological distress in patients with metastatic cancer enrolling on phase I clinical trials.

PURPOSE: Psychological distress is common in patients with cancer and is associated with lower quality-of-life (QOL). Although distress among oncology outpatients undergoing standard therapy has been widely studied, few studies have evaluated distress among patients enrolling on Phase I therapeutic clinical trials. Thus, we aimed to characterize levels of distress and types of stressors in patients enrolling on Phase I clinical trials. METHODS: Participants completed the National Comprehensive Cancer Network Distress Thermometer (NCCN DT) and Problem list and measures of anxiety and depression at the time of Phase I clinical trial initiation. RESULTS: We enrolled 87 patients (95% with metastatic/incurable disease) who were initiating a Phase I clinical trial. Analyses revealed a high prevalence of distress (51%) and anxiety (28%). There were significant correlations between overall distress and practical problems (r = 0.31, p = 0.016), family problems (r = 0.35, p = 0.006), and emotional problems (r = 0.64, p < 0.001), but not physical problems (r = 0.17, p = 0.206). CONCLUSIONS: Patients may be better prepared to manage physical stressors but not practical, emotional, or family stressors at the time of Phase I trial enrollment. IMPLICATIONS FOR CANCER SURVIVORS: Phase I trial patients experience high levels of distress which may be due to the rigors of previous therapies therapy and related emotional and social stressors related to the poor prognosis of their advanced cancer diagnosis. Distress may go unidentified without screening which is not standard practice at the time of Phase I trial consideration. Future studies should evaluate strategies to routinely identify and intervene upon addressable stressors in patients participating in Phase I clinical trials.

A multimodal intervention for patients with secondary progressive multiple sclerosis: feasibility and effect on fatigue.

BACKGROUND: Multiple sclerosis is an autoimmune disease influenced by environmental factors. OBJECTIVES: The feasibility of a multimodal intervention and its effect on perceived fatigue in patients with secondary progressive multiple sclerosis were assessed. DESIGN/SETTING: This was a single-arm, open-label intervention study in an outpatient setting. INTERVENTIONS: A multimodal intervention including a modified paleolithic diet with supplements, stretching, strengthening exercises with electrical stimulation of trunk and lower limb muscles, meditation, and massage was used. OUTCOME MEASURES: Adherence to each component of the intervention was calculated using daily logs. Side-effects were assessed from a monthly questionnaire and blood analyses. Fatigue was assessed using the Fatigue Severity Scale (FSS). Data were collected at baseline and months 1, 2, 3, 6, 9, and 12. RESULTS: Ten (10) of 13 subjects who were enrolled in a 2-week run-in phase were eligible to continue in the 12-month main study. Of those 10 subjects, 8 completed the study and 6 subjects fully adhered to the study intervention for 12 months. Over a 12-month period, average adherence to diet exceeded 90% of days, and to exercise/muscle stimulation exceeded 75% of days. Nutritional supplements intake varied among and within subjects. Group daily average duration of meditation was 13.3 minutes and of massage was 7.2 minutes. No adverse side-effects were reported. Group average FSS scores decreased from 5.7 at baseline to 3.32 (p=0.0008) at 12 months. CONCLUSIONS: In this small, uncontrolled pilot study, there was a significant improvement in fatigue in those who completed the study. Given the small sample size and completer rate, further evaluation of this multimodal therapy is warranted.

Amanita phalloides poisoning and treatment with silibinin in the Australian Capital Territory and New South Wales.

OBJECTIVES: To report the frequency and clinical outcomes of Amanita phalloides poisoning in the Australian Capital Territory and New South Wales, and the treatments used (including silibinin). DESIGN, SETTING AND PATIENTS: Retrospective case series of patients admitted to public hospitals in Canberra and Sydney for suspected A. phalloides poisoning between 1999 and 2012 (identified from hospital records and calls to the New South Wales Poisons Information Centre). MAIN OUTCOME MEASURES: Frequency of poisoning and the clinical outcomes. RESULTS: Twelve patients presented with a history suggesting A. phalloides poisoning, 10 with probable poisoning and two with possible poisoning. Eight of those with probable poisoning developed significant hepatotoxicity and four died. Silibinin was administered to nine of those with probable poisoning (the other presented before 2005). Maintaining silibinin supply became a challenge during two clusters of poisoning. Eight of the patients with probable poisoning were not long-term residents of the ACT, and six were immigrants from Asia. CONCLUSIONS: The mortality rate due to A. phalloides poisoning in this case series was high despite treatment according to current standards, including use of silibinin, and the frequency of hepatotoxicity was more than double that for the previous decade. Ongoing public health campaigns are required.

Gemcitabine plus sorafenib in patients with advanced pancreatic cancer: a phase II trial of the University of Chicago Phase II Consortium.

BACKGROUND: Sorafenib, an inhibitor of B-raf, VEGFR2, and PDGFR-ß, has activity against pancreatic cancer in preclinical models. In a phase I trial of gemcitabine plus sorafenib, 57% of pancreatic cancer patients achieved stable disease. PATIENTS AND METHODS: We conducted a multi-center phase II trial of sorafenib plus gemcitabine in chemo-naïve patients with histologically-confirmed, advanced pancreatic cancer. Patients received sorafenib 400 mg twice daily and gemcitabine 1,000 mg/m(2) on days 1, 8 and 15 of a 28 day cycle. RESULTS: Seventeen patients enrolled at 4 centers; 13 were evaluable for response. There were no objective responses; 18% had stable disease. Median overall survival was 4.0 months (95% CI: 3.4, 5.9); median progression-free survival was 3.2 months (95% CI: 1.6, 3.6). Grade 3/4 toxicities included thrombosis in 18% of patients, dehydration or hand-foot syndrome in 12%, and hypertension or gastrointestinal bleeding in 6%. CONCLUSION: Gemcitabine plus sorafenib is inactive in advanced pancreatic cancer.

B,O-chelated azadipyrromethenes as near-IR probes.

Complementary synthetic routes to a new class of near-IR fluorophores are described. These allow facile access (four synthetic steps) to the core fluorophore and substituted derivatives with emissions between 740 and 780 nm in good quantum yields.