HIV-1 infection kinetics, drug resistance, and long-term safety of pre-exposure prophylaxis with emtricitabine plus tenofovir alafenamide (DISCOVER): week 144 open-label extension of a randomised, controlled, phase 3 trial.

BACKGROUND: Data characterising the long-term use and safety of emtricitabine plus tenofovir disoproxil fumarate as daily oral pre-exposure prophylaxis (PrEP) are scarce and there are uncertainties regarding the value of routine HIV-1 RNA testing during oral PrEP follow-up. METHODS: The DISCOVER trial was a randomised, controlled, phase 3 trial in which cisgender men and transgender women aged 18 years and older with a high likelihood of acquiring HIV were recruited from 94 clinics in Europe and North America and randomly assigned to receive either emtricitabine plus tenofovir disoproxil fumarate (200/25 mg) tablets daily, with matched placebo tablets, or emtricitabine plus tenofovir alafenamide (200/300 mg) tablets daily, with matched placebo tablets, for at least 96 weeks. After completion of the trial, participants were offered enrolment in this 48-week open-label extension study of emtricitabine plus tenofovir alafenamide. In participants diagnosed with HIV during the randomised and open-label phases of the study, we characterised HIV-1 test results and measured HIV-1 RNA viral load retrospectively when available. Adherence based on tenofovir diphosphate concentrations in dried blood spots and genotypic resistance were assessed in participants diagnosed with HIV. Safety assessments included adverse events, laboratory parameters, and, in a subset of participants, bone mineral density. HIV-1 incidence in participants initially randomly assigned to receive emtricitabine plus tenofovir alafenamide was estimated using a Poisson distribution. Changes from baseline in safety endpoints were described in participants assigned to received emtricitabine plus tenofovir alafenamide and in those who switched from emtricitabine plus tenofovir disoproxil fumarate during the open-label phase. This trial is registered with ClinicalTrials.gov, NCT02842086, and is ongoing. FINDINGS: Between Sept 13, 2016, and June 30, 2017, 5399 participants were enrolled and randomly assigned in DISCOVER. 2699 were assigned to receive emtricitabine plus tenofovir disoproxil fumarate and 2700 were assigned to receive emtricitabine plus tenofovir alafenamide, of whom 2693 and 2694, respectively, received at least one dose of study drug. 2115 (79%) assigned to emtricitabine plus tenofovir disoproxil fumarate switched to emtricitabine plus tenofovir alafenamide in the open-label phase, and 2070 (77%) continued with emtricitabine plus tenofovir alafenamide in the open-label phase. As of data cutoff (Dec 10, 2020), after 15 817 person-years of follow-up, 27 new HIV-1 diagnoses were observed across the total study period, with three occurring during the open-label phase. In participants who were initially assigned to emtricitabine plus tenofovir alafenamide, the incidence was 0·13 per 100 person-years (95% CI 0·061-0·23; ten of 2670). Stored plasma samples were available for 23 of 27 participants, including 22 with incident infection. In four (17%) of 23 participants, retrospective testing detected HIV-1 RNA before serological HIV-1 test positivity; one was a suspected baseline infection. Of the three incident cases, all three were non-adherent to PrEP and none developed drug resistance. Among participants taking emtricitabine plus tenofovir alafenamide for up to 144 weeks, markers of glomerular filtration and proximal renal tubule dysfunction (ß2-microglobulin to creatinine ratio and retinol-binding protein to creatinine ratio) improved or remained stable at 144 weeks compared with baseline, bone mineral density in hip and lumbar spine increased or remained stable from baseline to week 144 (n=191), cholesterol and glucose concentrations remained stable, and median bodyweight increased by less than 1 kg per year. In participants who switched from emtricitabine plus tenofovir disoproxil fumarate during the open-label phase (2115 [79%] of 2693), markers of glomerular filtration and proximal renal tubule dysfunction improved or remained stable, bone mineral density increased, cholesterol concentrations increased, glucose concentrations were similar, and median bodyweight increased more compared with those who remained on emtricitabine and tenofovir alafenamide. INTERPRETATION: Routine HIV-1 RNA testing for follow-up of individuals on daily oral PrEP provides modest additional clinical benefit. Long-term use of emtricitabine and tenofovir alafenamide as daily oral PrEP is safe and well tolerated and can be an especially appropriate choice for people with bone or renal morbidities. FUNDING: Gilead Sciences.

Real-World Safety of Niraparib for Maintenance Treatment of Ovarian Cancer in Canada.

Niraparib was recently funded in Canada for the maintenance treatment of ovarian cancer following platinum-based chemotherapy. However, the drug's safety profile in the real world remains uncertain. We conducted a cohort study to describe the patient population using niraparib and the proportion that experienced adverse events between June 2019 and December 2022 in four Canadian provinces (Ontario, Alberta, British Columbia [BC], and Quebec). We used administrative data and electronic medical records from Ontario Health, Alberta Health Services, and BC Cancer, and registry data from Exactis Innovation. We summarized baseline characteristics using descriptive statistics and reported safety outcomes using cumulative incidence. We identified 514 patients receiving niraparib. Mean age was 67 years and most were initiated on a daily dose of 100 or 200 mg/day. Grade 3/4 anemia, neutropenia, and thrombocytopenia occurred in 11-16% of the cohort. In Ontario, the three-month cumulative incidence of grade 3/4 thrombocytopenia was 11.6% (95% CI, 8.3-15.4%), neutropenia was 7.1% (95% CI, 4.6-10.4%), and anemia was 11.3% (95% CI, 8.0-15.2%). Cumulative incidences in the remaining provinces were similar. Initial daily dose and proportions of hematological adverse events were low in the real world and may be related to cautious prescribing and close monitoring by clinicians.

Performance of Large Language Models on Medical Oncology Examination Questions.

Importance: Large language models (LLMs) recently developed an unprecedented ability to answer questions. Studies of LLMs from other fields may not generalize to medical oncology, a high-stakes clinical setting requiring rapid integration of new information. Objective: To evaluate the accuracy and safety of LLM answers on medical oncology examination questions. Design, Setting, and Participants: This cross-sectional study was conducted between May 28 and October 11, 2023. The American Society of Clinical Oncology (ASCO) Oncology Self-Assessment Series on ASCO Connection, the European Society of Medical Oncology (ESMO) Examination Trial questions, and an original set of board-style medical oncology multiple-choice questions were presented to 8 LLMs. Main Outcomes and Measures: The primary outcome was the percentage of correct answers. Medical oncologists evaluated the explanations provided by the best LLM for accuracy, classified the types of errors, and estimated the likelihood and extent of potential clinical harm. Results: Proprietary LLM 2 correctly answered 125 of 147 questions (85.0%; 95% CI, 78.2%-90.4%; P < .001 vs random answering). Proprietary LLM 2 outperformed an earlier version, proprietary LLM 1, which correctly answered 89 of 147 questions (60.5%; 95% CI, 52.2%-68.5%; P < .001), and the best open-source LLM, Mixtral-8x7B-v0.1, which correctly answered 87 of 147 questions (59.2%; 95% CI, 50.0%-66.4%; P < .001). The explanations provided by proprietary LLM 2 contained no or minor errors for 138 of 147 questions (93.9%; 95% CI, 88.7%-97.2%). Incorrect responses were most commonly associated with errors in information retrieval, particularly with recent publications, followed by erroneous reasoning and reading comprehension. If acted upon in clinical practice, 18 of 22 incorrect answers (81.8%; 95% CI, 59.7%-94.8%) would have a medium or high likelihood of moderate to severe harm. Conclusions and Relevance: In this cross-sectional study of the performance of LLMs on medical oncology examination questions, the best LLM answered questions with remarkable performance, although errors raised safety concerns. These results demonstrated an opportunity to develop and evaluate LLMs to improve health care clinician experiences and patient care, considering the potential impact on capabilities and safety.

Electronic malignant bowel obstruction symptom monitoring smartphone application for patients with gynecologic cancers.

OBJECTIVES: Implementation of an interprofessional program at Princess Margaret Cancer Centre, including nurse-led proactive calls to support patients with gynecologic cancers with malignant bowel obstruction, demonstrated improved outcomes compared with historical controls. The aim of the study was to convert the proactive calls into an electronic monitoring program to assess it's feasibility and scalability in patients with gynecologic cancers with or at risk of malignant bowel obstruction. METHODS: 'My Bowels on Track' smartphone application included weekly/biweekly electronic patient-reported outcomes (PROs), educational materials, and a secure messaging system. Based on PRO answers, an alerting system flagged patients with symptoms or uncompleted PROs. Nurses tracked and called patients on receiving clinical or compliance alerts. The primary objective was to assess adherence (≥70% PRO completion per patient considered an adherent patient) in the first 2 months on the program. A secondary objective was to assess the positive predictive value (PPV) of the alerts to trigger recommendations. RESULTS: Forty patients were enrolled between August 2021 and September 2022. Median age was 64.5 years (range 29-79 years). Primary diagnosis was ovarian (75%), endometrial (17.5%), or cervical (7.5%) cancer, and 92.5% of patients were receiving systemic therapy. Median duration on the program was 55 days (range 8-121 days). The 2-month adherence was 65% (95% CI 50% to 80%) and the overall adherence was 60% (95% CI 43% to 75%). Sixty-five symptom-related alerts (75% severe, 25% moderate) were reported in 60% (24/40) of patients. There were 59 recommendations triggered by the alerts. The PPV of the alerts to trigger actions was 72% (95% CI 58% to 82%). CONCLUSIONS: This pilot electronic malignant bowel obstruction monitoring program with real-time PRO assessment was feasible, and 65% of participants were adherent during the first 2 months on the program. The PRO response-based alerting system flagged concerning symptoms in 60% of participants, with a PPV of 72% to trigger nurse-led actions and/or management recommendations. TRIAL REGISTRATION NUMBER: NCT03260647.

Use of Deep Learning to Evaluate Tumor Microenvironmental Features for Prediction of Colon Cancer Recurrence.

Deep learning may detect biologically important signals embedded in tumor morphologic features that confer distinct prognoses. Tumor morphologic features were quantified to enhance patient risk stratification within DNA mismatch repair (MMR) groups using deep learning. Using a quantitative segmentation algorithm (QuantCRC) that identifies 15 distinct morphologic features, we analyzed 402 resected stage III colon carcinomas [191 deficient (d)-MMR; 189 proficient (p)-MMR] from participants in a phase III trial of FOLFOX-based adjuvant chemotherapy. Results were validated in an independent cohort (176 d-MMR; 1,094 p-MMR). Association of morphologic features with clinicopathologic variables, MMR, KRAS, BRAFV600E, and time-to-recurrence (TTR) was determined. Multivariable Cox proportional hazards models were developed to predict TTR. Tumor morphologic features differed significantly by MMR status. Cancers with p-MMR had more immature desmoplastic stroma. Tumors with d-MMR had increased inflammatory stroma, epithelial tumor-infiltrating lymphocytes (TIL), high-grade histology, mucin, and signet ring cells. Stromal subtype did not differ by BRAFV600E or KRAS status. In p-MMR tumors, multivariable analysis identified tumor-stroma ratio (TSR) as the strongest feature associated with TTR [HRadj 2.02; 95% confidence interval (CI), 1.14-3.57; P = 0.018; 3-year recurrence: 40.2% vs. 20.4%; Q1 vs. Q2-4]. Among d-MMR tumors, extent of inflammatory stroma (continuous HRadj 0.98; 95% CI, 0.96-0.99; P = 0.028; 3-year recurrence: 13.3% vs. 33.4%, Q4 vs. Q1) and N stage were the most robust prognostically. Association of TSR with TTR was independently validated. In conclusion, QuantCRC can quantify morphologic differences within MMR groups in routine tumor sections to determine their relative contributions to patient prognosis, and may elucidate relevant pathophysiologic mechanisms driving prognosis. SIGNIFICANCE: A deep learning algorithm can quantify tumor morphologic features that may reflect underlying mechanisms driving prognosis within MMR groups. TSR was the most robust morphologic feature associated with TTR in p-MMR colon cancers. Extent of inflammatory stroma and N stage were the strongest prognostic features in d-MMR tumors. TIL density was not independently prognostic in either MMR group.

Bayesian Meta-Analysis of Health State Utility Values: A Tutorial with a Practical Application in Heart Failure.

Researchers incorporate health state utility values as inputs to inform economic models. However, for a particular health state or condition, multiple utility values derived from different studies typically exist and a single study is often insufficient to represent the best available source of utility needed to inform policy decisions. The purpose of this paper is to provide an introductory guidance for conducting Bayesian meta-analysis of health state utility values to generate a single parameter input for economic evaluation, using R. The tutorial is illustrated using data from a systematic review of health state utilities of patients with heart failure, with 21 studies that reported utilities measured using the EuroQol-5D (EQ-5D). Explanations, key considerations and suggested readings are provided for each step of the tutorial, adhering to a clear workflow for conducting Bayesian meta-analysis: (1) setting-up the data; (2) employing methods to impute missing standard deviations; (3) defining the priors; (4) fitting the model; (5) diagnosing model convergence; (6) interpreting the results; and (7) performing sensitivity analyses. The posterior distributions for the pooled effect size (i.e. mean health state utility) and between-study heterogeneity are discussed and interpreted in light of the data, priors and models used. We hope that this tutorial will foster interest in Bayesian methods and their applications in the meta-analysis of utilities.

The immune-evasive proline-283 substitution in influenza nucleoprotein increases aggregation propensity without altering the native structure.

Nucleoprotein (NP) is a key structural protein of influenza ribonucleoprotein complexes and is central to viral RNA packing and trafficking. NP also determines the sensitivity of influenza to myxovirus resistance protein 1 (MxA), an innate immunity factor that restricts influenza replication. A few critical MxA-resistant mutations have been identified in NP, including the highly conserved proline-283 substitution. This essential proline-283 substitution impairs influenza growth, a fitness defect that becomes particularly prominent at febrile temperature (39°C) when host chaperones are depleted. Here, we biophysically characterize proline-283 NP and serine-283 NP to test whether the fitness defect is caused by the proline-283 substitution introducing folding defects. We show that the proline-283 substitution changes the folding pathway of NP, making NP more aggregation prone during folding, but does not alter the native structure of the protein. These findings suggest that influenza has evolved to hijack host chaperones to promote the folding of otherwise biophysically incompetent viral proteins that enable innate immune system escape.

HIV-1 Incidence, Adherence, and Drug Resistance in Individuals Taking Daily Emtricitabine/Tenofovir Disoproxil Fumarate for HIV-1 Pre-Exposure Prophylaxis: Pooled Analysis From 72 Global Studies.

BACKGROUND: Oral pre-exposure prophylaxis (PrEP) with emtricitabine/tenofovir disoproxil fumarate (F/TDF) has high efficacy against HIV-1 acquisition. Seventy-two prospective studies of daily oral F/TDF PrEP were conducted to evaluate HIV-1 incidence, drug resistance, adherence, and bone and renal safety in diverse settings. METHODS: HIV-1 incidence was calculated from incident HIV-1 diagnoses after PrEP initiation and within 60 days of discontinuation. Tenofovir concentration in dried blood spots (DBS), drug resistance, and bone/renal safety indicators were evaluated in a subset of studies. RESULTS: Among 17,274 participants, there were 101 cases with new HIV-1 diagnosis (0.77 per 100 person-years; 95% CI 0.63-0.94). In 78 cases with resistance data, 18 (23%) had M184I or V, one (1.3%) had K65R, and three (3.8%) had both mutations. In 54 cases with tenofovir concentration data from DBS, 45 (83.3%), 2 (3.7%), 6 (11.1%), and 1 (1.9%) had average adherence of <2, 2-3, 4-6, and ≥7 doses/week, respectively, and the corresponding incidence was 3.9 (95% CI 2.9-5.3), 0.24 (0.060-0.95), 0.27 (0.12-0.60), and 0.054 (0.008-0.38) per 100 person-years. Adherence was low in younger participants, Hispanic/Latinx and Black participants, cisgender women, and transgender women. Bone and renal adverse event incidence rates were 0.69 and 11.8 per 100 person-years, respectively, consistent with previous reports. CONCLUSIONS: Leveraging the largest pooled analysis of global PrEP studies to date, we demonstrate that F/TDF is safe and highly effective, even with less than daily dosing, in diverse clinical settings, geographies, populations, and routes of HIV-1 exposure.

High grade adverse event reporting and enrolment in gynecologic oncology clinical trials.

OBJECTIVE: The primary objective is to assess factors associated with treatment related high grade (CTCAE grade ≥ 3) adverse event (AE) reporting among participants in gynecologic oncology clinical trials. METHODS: All AEs recorded in the Princess Margaret Clinical Trial adverse event database between 01/2016 and 12/2018 were evaluated. Gynecologic oncology clinical trials assessing systemic therapy were included. Inferential statistics on risk factors of related grade ≥ 3 adverse event reporting and GEE logistic models with Odds Ratios (OR) were performed. Multivariable analysis adjusting for age, clinical trial phase, sponsor, and therapy type. RESULTS: The gynecology cancer clinical trials accrued 317 unique patients (359 nested on trials) in 42 systemic therapy trials. In the period, 17,175 related AEs were reported in the gynecological cancer trials, 7.4% were grade ≥ 3. On multivariable analysis, no odds differences of grade ≥ 3 related AEs were detected according to study phase. Patients in immunotherapy clinical trials had lower odds of related grade ≥ 3 AEs than patients on targeted or other therapy (adjusted OR [aOR] 0.43; 95% CI 0.24-0.75). There was greater odds of related grade ≥ 3 AEs in clinical trials assessing combination vs single therapeutics (aOR 2.26, 95% CI 1.34-3.80). Patients aged ≥65 (aOR 1.77; 95% CI 1.08-2.89) had greater odds of related grade ≥ 3 AEs than patients aged 50 to 65 years. When compared to other disease sites, the odds of having a grade  ≥ 3 related AE reported in gynecology clinical trials was no different. CONCLUSIONS: In this cohort, factors influencing the odds of related grade ≥ 3 AE reporting in gynecologic trials included type of therapy and age. The study phase did not correlate with odds of high-grade AE reporting.

Bayesian approach for meta-analyses in biomedical research: a scoping review protocol.

OBJECTIVE: The overarching aim of this scoping review is to describe and analyze the scope of use and reporting of Bayesian methods in meta-analyses in biomedical research. INTRODUCTION: The Bayesian approach provides a powerful and flexible framework for meta-analysis, particularly suited for dealing with complex, sparse, or heterogeneous data. Due to these advantages and its appeal, Bayesian methods have been increasingly used in many areas of biomedical research; however, their use in meta-analysis remains scarce. INCLUSION CRITERIA: This review will include studies that used Bayesian methods for meta-analysis of primary studies in biomedical research. METHODS: The proposed review will be conducted in accordance with the JBI methodology for scoping reviews. PubMed, Embase, CINAHL, and the Cochrane Database of Systematic Reviews will be searched to identify relevant full-text papers published since 2016 in English. No geographical restriction will be applied. Two reviewers will screen the articles and extract the data using a tool that will be pilot-tested and revised, as necessary. Analysis will involve frequency counts, narrative synthesis, and mapping concepts to propose an appropriate workflow. The details of the scoping review will be reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guideline. REVIEW REGISTRATION: Open Science Framework https://osf.io/jenp4/.

Machine Learning to Allocate Palliative Care Consultations During Cancer Treatment.

PURPOSE: For patients with advanced cancer, early consultations with palliative care (PC) specialists reduce costs, improve quality of life, and prolong survival. However, capacity limitations prevent all patients from receiving PC shortly after diagnosis. We evaluated whether a prognostic machine learning system could promote early PC, given existing capacity. METHODS: Using population-level administrative data in Ontario, Canada, we assembled a cohort of patients with incurable cancer who received palliative-intent systemic therapy between July 1, 2014, and December 30, 2019. We developed a machine learning system that predicted death within 1 year of each treatment using demographics, cancer characteristics, treatments, symptoms, laboratory values, and history of acute care admissions. We trained the system in patients who started treatment before July 1, 2017, and evaluated the potential impact of the system on PC in subsequent patients. RESULTS: Among 560,210 treatments received by 54,628 patients, death occurred within 1 year of 45.2% of treatments. The machine learning system recommended the same number of PC consultations observed with usual care at the 60.0% 1-year risk of death, with a first-alarm positive predictive value of 69.7% and an outcome-level sensitivity of 74.9%. Compared with usual care, system-guided care could increase early PC by 8.5% overall (95% CI, 7.5 to 9.5; P < .001) and by 15.3% (95% CI, 13.9 to 16.6; P < .001) among patients who live 6 months beyond their first treatment, without requiring more PC consultations in total or substantially increasing PC among patients with a prognosis exceeding 2 years. CONCLUSION: Prognostic machine learning systems could increase early PC despite existing resource constraints. These results demonstrate an urgent need to deploy and evaluate prognostic systems in real-time clinical practice to increase access to early PC.

Knowledge-guided machine learning can improve carbon cycle quantification in agroecosystems.

Accurate and cost-effective quantification of the carbon cycle for agroecosystems at decision-relevant scales is critical to mitigating climate change and ensuring sustainable food production. However, conventional process-based or data-driven modeling approaches alone have large prediction uncertainties due to the complex biogeochemical processes to model and the lack of observations to constrain many key state and flux variables. Here we propose a Knowledge-Guided Machine Learning (KGML) framework that addresses the above challenges by integrating knowledge embedded in a process-based model, high-resolution remote sensing observations, and machine learning (ML) techniques. Using the U.S. Corn Belt as a testbed, we demonstrate that KGML can outperform conventional process-based and black-box ML models in quantifying carbon cycle dynamics. Our high-resolution approach quantitatively reveals 86% more spatial detail of soil organic carbon changes than conventional coarse-resolution approaches. Moreover, we outline a protocol for improving KGML via various paths, which can be generalized to develop hybrid models to better predict complex earth system dynamics.

Liver transplantation for intrahepatic cholangiocarcinoma: who, when and how.

PURPOSE OF REVIEW: Using transplant oncology principles, selected patients with intrahepatic cholangiocarcinoma (iCCA) may achieve long-term survival after liver transplantation. Strategies for identifying and managing these patients are discussed in this review. RECENT FINDINGS: Unlike initial reports, several modern series have reported positive outcomes after liver transplantation for iCCA. The main challenges are in identifying the appropriate candidates and graft scarcity. Tumor burden and response to neoadjuvant therapies have been successfully used to identify favorable biology in unresectable cases. New molecular biomarkers will probably predict this response in the future. Also, new technologies and better strategies have been used to increase graft availability for these patients without affecting the liver waitlist. SUMMARY: Liver transplantation for the management of patients with unresectable iCCA is currently a reality under strict research protocols. Who is a candidate for transplantation, when to use neoadjuvant and locoregional therapies, and how to increase graft availability are the main topics of this review.

Circulating Oncometabolite 2-hydroxyglutarate as a Potential Biomarker for Isocitrate Dehydrogenase (IDH1/2) Mutant Cholangiocarcinoma.

Isocitrate dehydrogenase (IDH) enzymes catalyze the decarboxylation of isocitrate to alpha-ketoglutarate (αKG). IDH1/2 mutations preferentially convert αKG to R-2-hydroxyglutarate (R2HG), resulting in R2HG accumulation in tumor tissues. We investigated circulating 2-hydroxyglutate (2HG) as potential biomarkers for patients with IDH-mutant (IDHmt) cholangiocarcinoma (CCA). R2HG and S-2-hydroxyglutarate (S2HG) levels in blood and tumor tissues were analyzed in a discovery cohort of patients with IDHmt glioma and CCA. Results were validated in cohorts of patients with CCA and clear-cell renal cell carcinoma. The R2HG/S2HG ratio (rRS) was significantly elevated in tumor tissues, but not in blood for patients with IDHmt glioma, while circulating rRS was elevated in patients with IDHmt CCA. There were overlap distributions of circulating R2HG and total 2HG in patients with both IDHmt and wild-type (IDHwt) CCA, while there was minimal overlap in rRS values between patients with IDHmt and IDHwt CCA. Using the rRS cut-off value of 1.5, the sensitivity of rRS was 90% and specificity was 96.8%. Circulating rRS is significantly increased in patients with IDHmt CCA compare with patients with IDHwt CCA. Circulating rRS is a sensitive and specific surrogate biomarker for IDH1/2 mutations in CCA. It can potentially be used as a tool for monitoring IDH-targeted therapy.

Causal relationships between risk of venous thromboembolism and 18 cancers: a bidirectional Mendelian randomization analysis.

BACKGROUND: People with cancer experience high rates of venous thromboembolism (VTE). Risk of subsequent cancer is also increased in people experiencing their first VTE. The causal mechanisms underlying this association are not completely understood, and it is unknown whether VTE is itself a risk factor for cancer. METHODS: We used data from large genome-wide association study meta-analyses to perform bidirectional Mendelian randomization analyses to estimate causal associations between genetic liability to VTE and risk of 18 different cancers. RESULTS: We found no conclusive evidence that genetic liability to VTE was causally associated with an increased incidence of cancer, or vice versa. We observed an association between liability to VTE and pancreatic cancer risk [odds ratio for pancreatic cancer: 1.23 (95% confidence interval: 1.08-1.40) per log-odds increase in VTE risk, P = 0.002]. However, sensitivity analyses revealed this association was predominantly driven by a variant proxying non-O blood group, with inadequate evidence to suggest a causal relationship. CONCLUSIONS: These findings do not support the hypothesis that genetic liability to VTE is a cause of cancer. Existing observational epidemiological associations between VTE and cancer are therefore more likely to be driven by pathophysiological changes which occur in the setting of active cancer and anti-cancer treatments. Further work is required to explore and synthesize evidence for these mechanisms.

First impressions: A prospective evaluation of patient-physician concordance and satisfaction following the initial medical oncology consultation.

BACKGROUND: An especially significant event in the patient-oncologist relationship is the initial consultation, where many complex topics-diagnosis, treatment intent, and often, prognosis-are discussed in a relatively short period of time. This study aimed to measure patients' understanding of the information discussed during their first medical oncology visit and their satisfaction with the communication from medical oncologists. METHODS: Between January and August 2021, patients without prior systemic treatment of their gastrointestinal malignancy (GI) attending the Princess Margaret Cancer Centre (PMCC) were approached within 24 h of their initial consultation to complete a paper-based questionnaire assessing understanding of their disease (diagnosis, treatment plan/intent, and prognosis) and satisfaction with the consultation. Medical oncology physicians simultaneously completed a similar questionnaire about the information discussed at the initial visit. Matched patient-physician responses were compared to assess the degree of concordance. RESULTS: A total of 184 matched patient-physician surveys were completed. The concordance rates for understanding of diagnosis, treatment plan, treatment intent, and prognosis were 92.9%, 59.2%, 66.8%, and 59.8%, respectively. After adjusting for patient and physician variables, patients who reported treatment intent to be unclear at the time of the consultation were independently associated with lower satisfaction scores (global p = 0.014). There was no statistically significant association between patient satisfaction and whether prognosis was disclosed (p = 0.08). CONCLUSION: An in-depth conversation as to what treatment intent and prognosis means is reasonable during the initial medical oncology consultation to ensure patients and caregivers have a better understanding about their cancer.

Adjuvant and neoadjuvant therapies for hepatocellular carcinoma.

Immune-oncology-based regimens have shown efficacy in advanced HCC and have been implemented as standard of care as first-line therapy. Their efficacy, including high response rates, and safety justify their evaluation in earlier disease stages. Following negative results for adjuvant sorafenib in the global STORM trial in 2015, 4 global phase 3 trials, featuring different immune checkpoint inhibitor combinations, entered in parallel the race in the adjuvant setting. The IMbrave050 trial, comparing adjuvant atezolizumab in combination with bevacizumab to active surveillance following curative-intent resection or ablation, was the first to report, fast-tracking the results of the first interim analysis and demonstrating an improvement in recurrence-free survival. The trial has provoked a discussion on the horizon of expectations from adjuvant treatment and the clinical relevance of efficacy endpoints. Moreover, major pathological responses reported from early phase 2 data in the neoadjuvant setting provide a strong rationale for the evaluation of these concepts in phase 3 trials. In this review, we summarize current evidence and outline future directions for systemic therapies in early-stage HCC.

Machine Learning-Based Early Warning Systems for Acute Care Utilization During Systemic Therapy for Cancer.

BACKGROUND: Emergency department visits and hospitalizations frequently occur during systemic therapy for cancer. We developed and evaluated a longitudinal warning system for acute care use. METHODS: Using a retrospective population-based cohort of patients who started intravenous systemic therapy for nonhematologic cancers between July 1, 2014, and June 30, 2020, we randomly separated patients into cohorts for model training, hyperparameter tuning and model selection, and system testing. Predictive features included static features, such as demographics, cancer type, and treatment regimens, and dynamic features, such as patient-reported symptoms and laboratory values. The longitudinal warning system predicted the probability of acute care utilization within 30 days after each treatment session. Machine learning systems were developed in the training and tuning cohorts and evaluated in the testing cohort. Sensitivity analyses considered feature importance, other acute care endpoints, and performance within subgroups. RESULTS: The cohort included 105,129 patients who received 1,216,385 treatment sessions. Acute care followed 182,444 (15.0%) treatments within 30 days. The ensemble model achieved an area under the receiver operating characteristic curve of 0.742 (95% CI, 0.739-0.745) and was well calibrated in the test cohort. Important predictive features included prior acute care use, treatment regimen, and laboratory tests. If the system was set to alarm approximately once every 15 treatments, 25.5% of acute care events would be preceded by an alarm, and 47.4% of patients would experience acute care after an alarm. The system underestimated risk for some treatment regimens and potentially underserved populations such as females and non-English speakers. CONCLUSIONS: Machine learning warning systems can detect patients at risk for acute care utilization, which can aid in preventive intervention and facilitate tailored treatment. Future research should address potential biases and prospectively evaluate impact after system deployment.

The Immune-Evasive Proline 283 Substitution in Influenza Nucleoprotein Increases Aggregation Propensity Without Altering the Native Structure.

Nucleoprotein (NP) is a key structural protein of influenza ribonucleoprotein complexes and is central to viral RNA packing and trafficking. In human cells, the interferon induced Myxovirus resistance protein 1 (MxA) binds to NP and restricts influenza replication. This selection pressure has caused NP to evolve a few critical MxA-resistant mutations, particularly the highly conserved Pro283 substitution. Previous work showed that this essential Pro283 substitution impairs influenza growth, and the fitness defect becomes particularly prominent at febrile temperature (39 °C) when host chaperones are depleted. Here, we biophysically characterize Pro283 NP and Ser283 NP to test if the fitness defect is owing to Pro283 substitution introducing folding defects. We show that the Pro283 substitution changes the folding pathway of NP without altering the native structure, making NP more aggregation prone during folding. These findings suggest that influenza has evolved to hijack host chaperones to promote the folding of otherwise biophysically incompetent viral proteins that enable innate immune system escape. Teaser: Pro283 substitution in flu nucleoprotein introduces folding defects, and makes influenza uniquely dependent on host chaperones.