The ARIA trial protocol: a randomised controlled trial to assess the clinical, technical, and cost-effectiveness of a cloud-based, ARtificially Intelligent image fusion system in comparison to standard treatment to guide endovascular Aortic aneurysm repair.

BACKGROUND: Endovascular repair of aortic aneurysmal disease is established due to perceived advantages in patient survival, reduced postoperative complications, and shorter hospital lengths of stay. High spatial and contrast resolution 3D CT angiography images are used to plan the procedures and inform device selection and manufacture, but in standard care, the surgery is performed using image-guidance from 2D X-ray fluoroscopy with injection of nephrotoxic contrast material to visualise the blood vessels. This study aims to assess the benefit to patients, practitioners, and the health service of a novel image fusion medical device (Cydar EV), which allows this high-resolution 3D information to be available to operators at the time of surgery. METHODS: The trial is a multi-centre, open label, two-armed randomised controlled clinical trial of 340 patient, randomised 1:1 to either standard treatment in endovascular aneurysm repair or treatment using Cydar EV, a CE-marked medical device comprising of cloud computing, augmented intelligence, and computer vision. The primary outcome is procedural time, with secondary outcomes of procedural efficiency, technical effectiveness, patient outcomes, and cost-effectiveness. Patients with a clinical diagnosis of AAA or TAAA suitable for endovascular repair and able to provide written informed consent will be invited to participate. DISCUSSION: This trial is the first randomised controlled trial evaluating advanced image fusion technology in endovascular aortic surgery and is well placed to evaluate the effect of this technology on patient outcomes and cost to the NHS. TRIAL REGISTRATION: ISRCTN13832085. Dec. 3, 2021.

Cost-effectiveness of nivolumab versus surveillance for the adjuvant treatment of patients with urothelial carcinoma who are at high risk of recurrence: a US payer perspective.

AIM: To evaluate the cost-effectiveness of adjuvant nivolumab compared with surveillance for the treatment of patients with high-risk muscle-invasive urothelial carcinoma (MIUC) after radical resection from a US healthcare payer perspective and to investigate the impact of alternative modeling approaches on the cost-effectiveness results. MATERIAL AND METHODS: A four-state, semi-Markov model consisting of disease free, local recurrence, distant recurrence, and death health states was developed to investigate the cost-effectiveness of nivolumab compared with surveillance over a 30-year time horizon. The model used data from the randomized CheckMate 274 trial (NCT02632409) and published literature to inform transitions among health states, and inputs on cost, utility, adverse event, and disease management. Scenario analyses were conducted to investigate the impact of model structure and key assumptions on the results. One-way deterministic and probabilistic sensitivity analysis were conducted to investigate the robustness of the results. RESULTS: Total expected costs were higher with nivolumab ($162,278) compared with surveillance ($63,027). Nivolumab was associated with improved survival (1.61 life-years gained compared with surveillance) and an incremental gain of 0.98 quality-adjusted life-years (QALYs). Although total treatment costs were higher for nivolumab, cost offsets were observed because of delayed or avoided recurrences and deaths experienced with nivolumab compared with observation. The incremental cost-effectiveness and cost-utility ratios were $61,462/life-year and $100,930/QALY. LIMITATIONS: At the time of analysis, CheckMate 274 had limited follow-up on disease-free survival and no overall survival data. The limited evidence necessitated assumptions on modeling survival after each type of recurrence. CONCLUSIONS: Nivolumab is estimated to be a life-extending and cost-effective option for adjuvant treatment of MIUC for patients who are at high risk of recurrence after undergoing radical resection in the United States. Using a threshold of $150,000/QALY, the cost-effectiveness conclusions remained consistent across the scenario and sensitivity analyses conducted.

Challenges, considerations, and approaches for developing a cost-effectiveness model for the adjuvant treatment of muscle-invasive urothelial carcinoma: with a spotlight on nivolumab versus placebo.

AIMS: To present alternative approaches related to both structural assumptions and data sources for the development of a decision analytic model for evaluating the cost-effectiveness of adjuvant nivolumab compared with surveillance in patients with high-risk muscle-invasive urothelial carcinoma (MIUC) after radical resection. METHODS AND RESULTS: Alternative approaches related to both structural assumptions and data sources are presented to address challenges and data gaps, as well as discussion of strengths and limitations of each approach. Specifically, challenges and considerations related to the following are presented: (1) selection of a modeling approach (partitioned survival model or state transition model) given the available evidence, (2) choice of health state structure (three- or four-state) to model disease progression and subsequent therapy, (3) modeling of outcomes from subsequent therapy using tunnel states to account for time-dependent transition probabilities or absorbing health states with one-off costs and outcomes applied, and (4) methods for modeling health-state transitions in a setting where treatment has curative intent and available survival data are immature. CONCLUSIONS: Multiple considerations must be taken into account when developing an economic model for new, emerging oncology treatments in early lines of therapy, all of which can affect the model's overall ability to estimate (quality-adjusted) survival benefits over a lifetime horizon. This paper identifies a series of key structural and analytic considerations regarding modeling of nivolumab treatment in the adjuvant MIUC setting. Several alternative approaches with regard to structure and data have been included in a flexible cost-effectiveness model so the impact of the alternative approaches on model results can be explored. The impact of these alternative approaches on cost-effectiveness results are presented in a companion article. Our findings may also help inform the development of future models for other treatments and settings in early-stage cancer.

Surrogacy and the Valuation of ATMPs: Taking Our Place in the Evidence Generation/Assessment Continuum.

Medical technology is advancing rapidly, but established methods for health technology assessment are struggling to keep up. This challenge is particularly stark for the assessment of advanced therapy medicinal products-therapies often launched on the basis of single-arm studies powered to a surrogate primary endpoint. The most robust surrogacy methods investigate trial-level correlations between the treatment effect on the surrogate and the outcome of ultimate interest. However, these methods are often impossible with the evidence usually available for advanced therapy medicinal products at the time of the launch (randomized controlled trials are necessary for these advanced methods). Additionally, these surrogacy relationships are usually considered to be technology specific, adding uncertainty for any approach that primarily relies on historic data to estimate the surrogacy relationship for novel interventions such as advanced therapy medicinal products. The literature has already highlighted the need for early dialogue, staged assessment processes, and pricing arrangements that responsibly share the risk between the manufacturer and payer. However, it is our view that in addition to these critical developments, the modeling methods employed could also improve. Currently, health technology assessment practitioners typically either ignore the surrogate and simply extrapolate the endpoint of greatest patient relevance irrespective of the degree of maturity or assume historic surrogate relationships apply to the novel technology. In this opinion piece, we outline an additional avenue. By drawing on the understanding of the mechanism of action and insights generated earlier in the evidence generation/assessment continuum, cost-effectiveness modelers can make better use of the wider data available. These efforts are expected to reduce uncertainty at the time of the initial launch of pharmaceutical products and increase the value of subsequent data collection efforts.

Oral follicle-stimulating hormone receptor agonist affects granulosa cells differently than recombinant human FSH.

OBJECTIVE: To determine whether TOP5300, a novel oral follicle-stimulating hormone (FSH) receptor (FSHR) allosteric agonist, elicits a different cellular response than recombinant human FSH (rh-FSH) in human granulosa cells from patients undergoing in vitro fertilization. DESIGN: Basic science research with a preclinical allosteric FSHR agonist. SETTING: University hospital. PATIENT(S): Patients with infertility at a single academic fertility clinic were recruited under an Institutional Review Board-approved protocol. Primary granulosa cell cultures were established for 41 patients, of whom 8 had normal ovarian reserve (NOR), 17 were of advanced reproductive age (ARA), 12 had a diagnosis of polycystic ovary syndrome (PCOS), and 4 had a combination of diagnoses, such as ARA and PCOS. INTERVENTION(S): Primary granulosa-lutein (GL) cell cultures were treated with rh-FSH, TOP5300, or vehicle. MAIN OUTCOME MEASURE(S): Estradiol (E2) production using enzyme-linked immunosorbent assay, steroid pathway gene expression of StAR and aromatase using quantitative polymerase chain reaction, and FSHR membrane localization using immunofluorescence were measured in human GL cells. RESULT(S): TOP5300 consistently stimulated E2 production among patients with NOR, ARA, and PCOS. Recombinant FSH was the more potent ligand in GL cells from patients with NOR but was ineffective in cells from patients with ARA or PCOS. The lowest level of FSHR plasma membrane localization was seen in patients with ARA, although FSHR localization was more abundant in cells from patients with PCOS; the highest levels were present in cells from patients with NOR. The localization of FSHR was not affected by TOP5300 relative to rh-FSH in any patient group. TOP5300 stimulated greater expression of StAR and CYP19A1 across cells from all patients with NOR, ARA, and PCOS combined, although rh-FSH was unable to stimulate StAR and aromatase (CYP19A1) expression in cells from patients with PCOS. TOP5300-induced expression of StAR and CYP19A1 mRNA among patients with ARA and NOR was consistently lower than that observed in cells from patients with PCOS. CONCLUSION(S): TOP5300 appears to stimulate E2 production and steroidogenic gene expression from GL cells more than rh-FSH in PCOS, relative to patients with ARA and NOR. It does not appear that localization of FSHR at cell membranes is a limiting step for TOP5300 or rh-FSH stimulation of steroidogenic gene expression and E2 production.

Extrapolation of Survival Data Using a Bayesian Approach: A Case Study Leveraging External Data from Cilta-Cel Therapy in Multiple Myeloma.

INTRODUCTION: Extrapolating long-term overall survival (OS) from shorter-term clinical trial data is key to health technology assessment in oncology. However, extrapolation using conventional methods is often subject to uncertainty. Using ciltacabtagene autoleucel (cilta-cel), a chimeric antigen receptor T-cell therapy for multiple myeloma, we used a flexible Bayesian approach to demonstrate use of external longer-term data to reduce the uncertainty in long-term extrapolation. METHODS: The pivotal CARTITUDE-1 trial (NCT03548207) provided the primary efficacy data for cilta-cel, including a 12-month median follow-up snapshot of OS. Longer-term (48-month median follow-up) survival data from the phase I LEGEND-2 study (NCT03090659) were also available. Twelve-month CARTITUDE-1 OS data were extrapolated in two ways: (1) conventional survival models with standard parametric distributions (uninformed), and (2) Bayesian survival models whose shape prior was informed from 48-month LEGEND-2 data. For validation, extrapolations from 12-month CARTITUDE-1 data were compared with observed 28-month CARTITUDE-1 data. RESULTS: Extrapolations of the 12-month CARTITUDE-1 data using conventional uninformed parametric models were highly variable. Using informative priors from the 48-month LEGEND-2 dataset, the ranges of projected OS at different timepoints were consistently narrower. Area differences between the extrapolation curves and the 28-month CARTITUDE-1 data were generally lower in informed Bayesian models, except for the uninformed log-normal model, which had the lowest difference. CONCLUSIONS: Informed Bayesian survival models reduced variation of long-term projections and provided similar projections as the uninformed log-normal model. Bayesian models generated a narrower and more plausible range of OS projections from 12-month data that aligned with observed 28-month data. TRIAL REGISTRATION: CARTITUDE-1 ClinicalTrials.gov identifier, NCT03548207. LEGEND-2 ClinicalTrials.gov identifier, NCT03090659, registered retrospectively on 27 March 2017, and ChiCTR-ONH-17012285.

Discovery of Highly Potent and BMPR2-Selective Kinase Inhibitors Using DNA-Encoded Chemical Library Screening.

The discovery of monokinase-selective inhibitors for patients is challenging because the 500+ kinases encoded by the human genome share highly conserved catalytic domains. Until now, no selective inhibitors unique for a single transforming growth factor ß (TGFß) family transmembrane receptor kinase, including bone morphogenetic protein receptor type 2 (BMPR2), have been reported. This dearth of receptor-specific kinase inhibitors hinders therapeutic options for skeletal defects and cancer as a result of an overactivated BMP signaling pathway. By screening 4.17 billion "unbiased" and "kinase-biased" DNA-encoded chemical library molecules, we identified hits CDD-1115 and CDD-1431, respectively, that were low-nanomolar selective kinase inhibitors of BMPR2. Structure-activity relationship studies addressed metabolic lability and high-molecular-weight issues, resulting in potent and BMPR2-selective inhibitor analogs CDD-1281 (IC50 = 1.2 nM) and CDD-1653 (IC50 = 2.8 nM), respectively. Our work demonstrates that DNA-encoded chemistry technology (DEC-Tec) is reliable for identifying novel first-in-class, highly potent, and selective kinase inhibitors.

Routine cerebral embolic protection in transcatheter aortic valve implantation: rationale and design of the randomised British Heart Foundation PROTECT-TAVI trial.

Transcatheter aortic valve implantation (TAVI) is an established treatment for aortic stenosis. Cerebral embolic protection (CEP) devices may impact periprocedural stroke by capturing debris destined for the brain. However, there is a lack of high-quality randomised trial evidence supporting the use of CEP during TAVI. The British Heart Foundation (BHF) PROTECT-TAVI trial will address whether the routine use of CEP reduces the incidence of stroke in patients undergoing TAVI. BHF PROTECT-TAVI is a prospective, open-label, outcome-adjudicated, multicentre randomised controlled trial. The trial is open to all adult patients scheduled for TAVI at participating specialist cardiac centres across the United Kingdom who are able to receive the CEP device. The trial will recruit 7,730 participants. Participants will be randomised in a 1:1 ratio to undergo TAVI with CEP or TAVI without CEP (standard of care). The primary outcome is the incidence of stroke at 72 hours post-TAVI. Key secondary outcomes include the incidence of stroke and all-cause mortality up to 12 months post-TAVI, disability and cognitive outcomes, stroke severity, access site complications and a health economics analysis. The sample size of 7,730 participants has 80% power to detect a 33% relative risk reduction from a 3% incidence of the primary outcome in the controls. Trial recruitment commenced in October 2020. As of October 2022, 3,068 patients have been enrolled. BHF PROTECT-TAVI is designed to provide definitive evidence on the clinical efficacy and cost-effectiveness of using routine CEP with the SENTINEL device to reduce stroke in TAVI.

A Guide to Selecting Flexible Survival Models to Inform Economic Evaluations of Cancer Immunotherapies.

OBJECTIVES: Parametric models are routinely used to estimate the benefit of cancer drugs beyond trial follow-up. The advent of immune checkpoint inhibitors has challenged this paradigm, and emerging evidence suggests that more flexible survival models, which can better capture the shapes of complex hazard functions, might be needed for these interventions. Nevertheless, there is a need for an algorithm to help analysts decide whether flexible models are required and, if so, which should be chosen for testing. This position article has been produced to bridge this gap. METHODS: A virtual advisory board comprising 7 international experts with in-depth knowledge of survival analysis and health technology assessment was held in summer 2021. The experts discussed 24 questions across 6 topics: the current survival model selection procedure, data maturity, heterogeneity of treatment effect, cure and mortality, external evidence, and additions to existing guidelines. Their responses culminated in an algorithm to inform selection of flexible survival models. RESULTS: The algorithm consists of 8 steps and 4 questions. Key elements include the systematic identification of relevant external data, using clinical expert input at multiple points in the selection process, considering the future and the observed hazard functions, assessing the potential for long-term survivorship, and presenting results from all plausible models. CONCLUSIONS: This algorithm provides a systematic, evidence-based approach to justify the selection of survival extrapolation models for cancer immunotherapies. If followed, it should reduce the risk of selecting inappropriate models, partially addressing a key area of uncertainty in the economic evaluation of these agents.

EarlyCDT Lung blood test for risk classification of solid pulmonary nodules: systematic review and economic evaluation.

BACKGROUND: EarlyCDT Lung (Oncimmune Holdings plc, Nottingham, UK) is a blood test to assess malignancy risk in people with solid pulmonary nodules. It measures the presence of seven lung cancer-associated autoantibodies. Elevated levels of these autoantibodies may indicate malignant disease. The results of the test might be used to modify the risk of malignancy estimated by existing risk calculators, including the Brock and Herder models. OBJECTIVES: The objectives were to determine the diagnostic accuracy, clinical effectiveness and cost-effectiveness of EarlyCDT Lung; and to develop a conceptual model and identify evidence requirements for a robust cost-effectiveness analysis. DATA SOURCES: MEDLINE (including Epub Ahead of Print, In-Process & Other Non-Indexed Citations, Ovid MEDLINE Daily and Ovid MEDLINE), EMBASE, Cochrane Central Register of Controlled Trials, Science Citation Index, EconLit, Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, Health Technology Assessment database, NHS Economic Evaluation Database ( NHS EED ) and the international Health Technology Assessment database were searched on 8 March 2021. REVIEW METHODS: A systematic review was performed of evidence on EarlyCDT Lung, including diagnostic accuracy, clinical effectiveness and cost-effectiveness. Study quality was assessed with the quality assessment of diagnostic accuracy studies-2 tool. Evidence on other components of the pulmonary nodule diagnostic pathway (computerised tomography surveillance, Brock risk, Herder risk, positron emission tomography-computerised tomography and biopsy) was also reviewed. When feasible, bivariate meta-analyses of diagnostic accuracy were performed. Clinical outcomes were synthesised narratively. A simulation study investigated the clinical impact of using EarlyCDT Lung. Additional reviews of cost-effectiveness studies evaluated (1) other diagnostic strategies for lung cancer and (2) screening approaches for lung cancer. A conceptual model was developed. RESULTS: A total of 47 clinical publications on EarlyCDT Lung were identified, but only five cohorts (695 patients) reported diagnostic accuracy data on patients with pulmonary nodules. All cohorts were small or at high risk of bias. EarlyCDT Lung on its own was found to have poor diagnostic accuracy, with a summary sensitivity of 20.2% (95% confidence interval 10.5% to 35.5%) and specificity of 92.2% (95% confidence interval 86.2% to 95.8%). This sensitivity was substantially lower than that estimated by the manufacturer (41.3%). No evidence on the clinical impact of EarlyCDT Lung was identified. The simulation study suggested that EarlyCDT Lung might potentially have some benefit when considering intermediate risk nodules (10-70% risk) after Herder risk analysis. Two cost-effectiveness studies on EarlyCDT Lung for pulmonary nodules were identified; none was considered suitable to inform the current decision problem. The conceptualisation process identified three core components for a future cost-effectiveness assessment of EarlyCDT Lung: (1) the features of the subpopulations and relevant heterogeneity, (2) the way EarlyCDT Lung test results affect subsequent clinical management decisions and (3) how changes in these decisions can affect outcomes. All reviewed studies linked earlier diagnosis to stage progression and stage shift to final outcomes, but evidence on these components was sparse. LIMITATIONS: The evidence on EarlyCDT Lung among patients with pulmonary nodules was very limited, preventing meta-analyses and economic analyses. CONCLUSIONS: The evidence on EarlyCDT Lung among patients with pulmonary nodules is insufficient to draw any firm conclusions as to its diagnostic accuracy or clinical or economic value. FUTURE WORK: Prospective cohort studies, in which EarlyCDT Lung is used among patients with identified pulmonary nodules, are required to support a future assessment of the clinical and economic value of this test. Studies should investigate the diagnostic accuracy and clinical impact of EarlyCDT Lung in combination with Brock and Herder risk assessments. A well-designed cost-effectiveness study is also required, integrating emerging relevant evidence with the recommendations in this report. STUDY REGISTRATION: This study is registered as PROSPERO CRD42021242248. FUNDING: This project was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 26, No. 49. See the NIHR Journals Library website for further project information.

People at risk of lung cancer sometimes undergo computerised tomography ( CT ) scans of their lungs. These scans may identify lung nodules that could be cancerous. Currently, CT scans of the lung nodules, or sometimes further positron emission tomography­computerised tomography ( PET-CT ) scans, are used to predict the risk that a nodule is cancerous. EarlyCDT Lung is a blood test that detects substances, called autoantibodies, associated with having cancer. If the autoantibodies are detected, the chance of a lung nodule being cancerous may be substantially increased. This test could help doctors make decisions about whether to treat immediately, carry out further tests or monitor the nodule over time to see if it grows or changes shape. This project examined the evidence on the clinical value of the EarlyCDT Lung test. We reviewed all published studies of EarlyCDT Lung and reanalysed the reported data. We found that there has been little research on EarlyCDT Lung among people with lung nodules (only five studies comprising 695 patients). This makes it difficult to draw any firm conclusions. The evidence suggests that EarlyCDT Lung may not be particularly effective at determining which lung nodules are cancerous, and may not improve diagnosis when compared with using CT and PET - CT scans. However, this is uncertain because the evidence is so limited. This project also looked for evidence on the value for money of the EarlyCDT Lung test in detecting lung cancer, and found no relevant evidence. This means that the value for money of EarlyCDT Lung is largely unknown, and there is currently no good evidence to support further analyses on this. We therefore sought to summarise the information and analyses that would be needed to support a future assessment of the value for money of EarlyCDT Lung.

Intensive behavioural interventions based on applied behaviour analysis (ABA) for young children with autism: A cost-effectiveness analysis.

BACKGROUND: The economic and social costs of autism are significant. This study evaluates the cost-effectiveness of early intensive Applied Behaviour Analysis (ABA)-based interventions for autistic pre-school children in the UK. METHODS: A de novo economic analysis was developed in Microsoft Excel comparing early intensive ABA-based interventions compared with treatment as usual (TAU). The analysis used 15.5-year time horizon, with costs and benefits discounted a 3.5%. The model structure was based on cohort structure to capture changes in adaptive behaviour and cognitive ability over time. The analysis was informed by an individual patient data (IPD) meta-analysis of available evidence. RESULTS: Adopting a public sector perspective, early intensive ABA-based therapies were associated with greater incremental costs and greater benefits. When pessimistic assumptions were made regarding the long-term effects of treatment incremental costs were £46,103 and incremental quality-adjusted life years (QALYs) were 0.24, resulting in an incremental cost-effectiveness ratio (ICER) of £189,122 per quality-adjusted life year (QALY). When optimistic assumptions were made about long-term effects, incremental costs were £39,233 with incremental benefits of 0.84 QALYs. The resulting ICER was £46,768 per QALY. Scenario analyses emphasised the importance of assumptions made regarding adult outcomes and type of school attended, both of which significantly affect the results of the analysis. CONCLUSIONS: The results of this economic analysis suggest that early intensive ABA-based interventions are unlikely to represent value for money, based on a £20,000 to £30,000 per QALY threshold typically adopted to inform UK healthcare funding decisions. However, important gaps in the available evidence, limit the strength of the conclusions that can be drawn from the presented analysis. Further research, focusing on the trajectory of autistic children following intervention is likely to be highly beneficial to resolving some of these uncertainties.

Discovery of potent BET bromodomain 1 stereoselective inhibitors using DNA-encoded chemical library selections.

BRDT, BRD2, BRD3, and BRD4 comprise the bromodomain and extraterminal (BET) subfamily which contain two similar tandem bromodomains (BD1 and BD2). Selective BD1 inhibition phenocopies effects of tandem BET BD inhibition both in cancer models and, as we and others have reported of BRDT, in the testes. To find novel BET BD1 binders, we screened >4.5 billion molecules from our DNA-encoded chemical libraries with BRDT-BD1 or BRDT-BD2 proteins in parallel. A compound series enriched only by BRDT-BD1 was resynthesized off-DNA, uncovering a potent chiral compound, CDD-724, with >2,000-fold selectivity for inhibiting BRDT-BD1 over BRDT-BD2. CDD-724 stereoisomers exhibited remarkable differences in inhibiting BRDT-BD1, with the R-enantiomer (CDD-787) being 50-fold more potent than the S-enantiomer (CDD-786). From structure­activity relationship studies, we produced CDD-956, which maintained picomolar BET BD1 binding potency and high selectivity over BET BD2 proteins and had improved stability in human liver microsomes over CDD-787. BROMOscan profiling confirmed the excellent pan-BET BD1 affinity and selectivity of CDD-787 and CDD-956 on BD1 versus BD2 and all other BD-containing proteins. A cocrystal structure of BRDT-BD1 bound with CDD-956 was determined at 1.82 Å and revealed BRDT-BD1­specific contacts with the αZ and αC helices that explain the high affinity and selectivity for BET BD1 versus BD2. CDD-787 and CDD-956 maintain cellular BD1-selectivity in NanoBRET assays and show potent antileukemic activity in acute myeloid leukemia cell lines. These BET BD1-specific and highly potent compounds are structurally unique and provide insight into the importance of chirality to achieve BET specificity.

Estimating and Extrapolating Survival Using a State-Transition Modeling Approach: A Practical Application in Multiple Myeloma.

OBJECTIVES: State-transition models (STMs) applied in oncology have given limited considerations to modeling postprogression survival data. This study presents an application of an STM focusing on methods to evaluate the postprogression transition and its impact on survival predictions. METHODS: Data from the lenalidomide plus dexamethasone arm of the ASPIRE trial was used to estimate transition rates for an STM. The model accounted for the competing risk between the progression and preprogression death events and included an explicit structural link between the time to progression and subsequent death. The modeled transition rates were used to simulate individual disease trajectories in a discrete event simulation framework, based on which progression-free survival and overall survival over a 30-year time horizon were estimated. Survival predictions were compared with the observed trial data, matched external data, and estimates obtained from a more conventional partitioned survival analysis approach. RESULTS: The rates of progression and preprogression death were modeled using piecewise exponential functions. The rate of postprogression mortality was modeled using an exponential function accounting for the nonlinear effect of the time to progression. The STM provided survival estimates that closely fitted the trial data and gave more plausible long-term survival predictions than the best-fitting Weibull model applied in a partitioned survival analysis. CONCLUSIONS: The fit of the STM suggested that the modeled transition rates accurately captured the underlying disease process over the modeled time horizon. The considerations of this study may apply to other settings and facilitate a wider use of STMs in oncology.

Modeling Benefits, Costs, and Affordability of a Novel Gene Therapy in Hemophilia A.

The objective was to undertake an early cost-effectiveness assessment of valoctocogene roxaparvovec (valrox; Roctavian) compared to factor (F)VIII prophylaxis or emicizumab (Hemlibra; Roche HQ, Bazel, Switzerland) in patients with severe Hemophilia A (HA) without FVIII-antibodies. We also aimed to incorporate and quantify novel measures of value such as treatment durability, maximum value-based price (MVBP) and break-even time (ie, time until benefits begin to offset upfront payment). We constructed a Markov model to model bleeds over time which were linked to costs and quality-of-life decrements. In the valrox arm, FVIII over time was estimated combining initial effect and treatment waning and then linked to bleeds. In FVIII and emicizumab arms, bleeds were based on trial evidence. Evidence and assumptions were validated using expert elicitation. Model robustness was tested via sensitivity analyses. A Dutch societal perspective was applied with a 10-year time horizon. Valrox in comparison to FVIII, and emicizumab showed small increases in quality-adjusted life years at lower costs, and were therefore dominant. Valrox' base case MVBP was estimated at €2.65 million/treatment compared to FVIII and €3.5 million/treatment versus emicizumab. Mean break-even time was 8.03 years compared to FVIII and 5.68 years to emicizumab. Early modeling of patients with HA in The Netherlands treated with valrox resulted in estimated improved health and lower cost compared to prophylactic FVIII and emicizumab. We also demonstrated feasibility of incorporation of treatment durability and novel outcomes such as value-based pricing scenarios and break-even time. Future work should aim to better characterize uncertainties and increase translation of early modeling to direct research efforts.

Metabolism of a Selective Serotonin and Norepinephrine Reuptake Inhibitor Duloxetine in Liver Microsomes and Mice.

Duloxetine (DLX) is a dual serotonin and norepinephrine reuptake inhibitor, widely used for the treatment of major depressive disorder. Although DLX has shown good efficacy and safety, serious adverse effects (e.g., liver injury) have been reported. The mechanisms associated with DLX-induced toxicity remain elusive. Drug metabolism plays critical roles in drug safety and efficacy. However, the metabolic profile of DLX in mice is not available, although mice serve as commonly used animal models for mechanistic studies of drug-induced adverse effects. Our study revealed 39 DLX metabolites in human/mouse liver microsomes and mice. Of note, 13 metabolites are novel, including five N-acetyl cysteine adducts and one reduced glutathione (GSH) adduct associated with DLX. Additionally, the species differences of certain metabolites were observed between human and mouse liver microsomes. CYP1A2 and CYP2D6 are primary enzymes responsible for the formation of DLX metabolites in liver microsomes, including DLX-GSH adducts. In summary, a total of 39 DLX metabolites were identified, and species differences were noticed in vitro. The roles of CYP450s in DLX metabolite formation were also verified using human recombinant cytochrome P450 (P450) enzymes and corresponding chemical inhibitors. Further studies are warranted to address the exact role of DLX metabolism in its adverse effects in vitro (e.g., human primary hepatocytes) and in vivo (e.g., Cyp1a2-null mice). SIGNIFICANCE STATEMENT: This current study systematically investigated Duloxetine (DLX) metabolism and bioactivation in liver microsomes and mice. This study provided a global view of DLX metabolism and bioactivation in liver microsomes and mice, which are very valuable to further elucidate the mechanistic study of DLX-related adverse effects and drug-drug interaction from metabolic aspects.

Prospecting and informed dispersal: Understanding and predicting their joint eco-evolutionary dynamics.

The ability of individuals to leave a current breeding area and select a future one is important, because such decisions can have multiple consequences for individual fitness, but also for metapopulation dynamics, structure, and long-term persistence through non-random dispersal patterns. In the wild, many colonial and territorial animal species display informed dispersal strategies, where individuals use information, such as conspecific breeding success gathered during prospecting, to decide whether and where to disperse. Understanding informed dispersal strategies is essential for relating individual behavior to subsequent movements and then determining how emigration and settlement decisions affect individual fitness and demography. Although numerous theoretical studies have explored the eco-evolutionary dynamics of dispersal, very few have integrated prospecting and public information use in both emigration and settlement phases. Here, we develop an individual-based model that fills this gap and use it to explore the eco-evolutionary dynamics of informed dispersal. In a first experiment, in which only prospecting evolves, we demonstrate that selection always favors informed dispersal based on a low number of prospected patches relative to random dispersal or fully informed dispersal, except when individuals fail to discriminate better patches from worse ones. In a second experiment, which allows the concomitant evolution of both emigration probability and prospecting, we show the same prospecting strategy evolving. However, a plastic emigration strategy evolves, where individuals that breed successfully are always philopatric, while failed breeders are more likely to emigrate, especially when conspecific breeding success is low. Embedding information use and prospecting behavior in eco-evolutionary models will provide new fundamental understanding of informed dispersal and its consequences for spatial population dynamics.

Pharmacological Characterization of Low Molecular Weight Biased Agonists at the Follicle Stimulating Hormone Receptor.

Follicle-stimulating hormone receptor (FSHR) plays a key role in reproduction through the activation of multiple signaling pathways. Low molecular weight (LMW) ligands composed of biased agonist properties are highly valuable tools to decipher complex signaling mechanisms as they allow selective activation of discrete signaling cascades. However, available LMW FSHR ligands have not been fully characterized yet. In this context, we explored the pharmacological diversity of three benzamide and two thiazolidinone derivatives compared to FSH. Concentration/activity curves were generated for Gαs, Gαq, Gαi, ß-arrestin 2 recruitment, and cAMP production, using BRET assays in living cells. ERK phosphorylation was analyzed by Western blotting, and CRE-dependent transcription was assessed using a luciferase reporter assay. All assays were done in either wild-type, Gαs or ß-arrestin 1/2 CRISPR knockout HEK293 cells. Bias factors were calculated for each pair of read-outs by using the operational model. Our results show that each ligand presented a discrete pharmacological efficacy compared to FSH, ranging from super-agonist for ß-arrestin 2 recruitment to pure Gαs bias. Interestingly, LMW ligands generated kinetic profiles distinct from FSH (i.e., faster, slower or transient, depending on the ligand) and correlated with CRE-dependent transcription. In addition, clear system biases were observed in cells depleted of either Gαs or ß-arrestin genes. Such LMW properties are useful pharmacological tools to better dissect the multiple signaling pathways activated by FSHR and assess their relative contributions at the cellular and physio-pathological levels.

Cost-effectiveness of point-of-care creatinine testing to assess kidney function prior to contrast-enhanced computed tomography imaging.

BACKGROUND: Patients undergoing contrast-enhanced computed tomography (CECT) imaging in a non-emergency outpatient setting often lack a recent estimated Glomerular Filtration Rate measurement. This may lead to inefficiencies in the CECT pathway. The use of point-of-care (POC) creatinine tests to evaluate kidney function in these patients may provide a safe and cost-effective alternative to current practice, as these can provide results within the same CECT appointment. METHODS: A decision tree model was developed to characterise the diagnostic pathway and patient management (e.g., intravenous hydration) and link these to adverse renal events associated with intravenous contrast media. Twelve diagnostic strategies including three POC devices (i-STAT, ABL800 Flex and StatSensor), risk factor screening and laboratory testing were compared with current practice. The diagnostic accuracy of POC devices was derived from a systematic review and meta-analysis; relevant literature sources and databases informed other parameters. The cost-effective strategy from a health care perspective was identified based on highest net health benefit (NHB) which were expressed in quality-adjusted life years (QALYs) at £20,000/QALY. RESULTS: The cost-effective strategy, with a NHB of 9.98 QALYs and a probability of being cost-effective of 79.3%, was identified in our analysis to be a testing sequence involving screening all individuals for risk factors, POC testing (with i-STAT) on those screening positive, and performing a confirmatory laboratory test for individuals with a positive POC result. The incremental NHB of this strategy compared to current practice, confirmatory laboratory test, is 0.004 QALYs. Results were generally robust to scenario analysis. CONCLUSIONS: A testing sequence combining a risk factor questionnaire, POC test and confirmatory laboratory testing appears to be cost-effective compared to current practice. The cost-effectiveness of POC testing appears to be driven by reduced delays within the CECT pathway. The contribution of intravenous contrast media to acute kidney injury, and the benefits and harms of intravenous hydration remain uncertain.

DNA-encoded chemistry technology yields expedient access to SARS-CoV-2 Mpro inhibitors.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has killed more than 4 million humans globally, but there is no bona fide Food and Drug Administration-approved drug-like molecule to impede the COVID-19 pandemic. The sluggish pace of traditional therapeutic discovery is poorly suited to producing targeted treatments against rapidly evolving viruses. Here, we used an affinity-based screen of 4 billion DNA-encoded molecules en masse to identify a potent class of virus-specific inhibitors of the SARS-CoV-2 main protease (Mpro) without extensive and time-consuming medicinal chemistry. CDD-1714, the initial three-building-block screening hit (molecular weight [MW] = 542.5 g/mol), was a potent inhibitor (inhibition constant [Ki] = 20 nM). CDD-1713, a smaller two-building-block analog (MW = 353.3 g/mol) of CDD-1714, is a reversible covalent inhibitor of Mpro (Ki = 45 nM) that binds in the protease pocket, has specificity over human proteases, and shows in vitro efficacy in a SARS-CoV-2 infectivity model. Subsequently, key regions of CDD-1713 that were necessary for inhibitory activity were identified and a potent (Ki = 37 nM), smaller (MW = 323.4 g/mol), and metabolically more stable analog (CDD-1976) was generated. Thus, screening of DNA-encoded chemical libraries can accelerate the discovery of efficacious drug-like inhibitors of emerging viral disease targets.