Beta spending function based on conditional power in group sequential design.

Conditional power (CP) serves as a widely utilized approach for futility monitoring in group sequential designs. However, adopting the CP methods may lead to inadequate control of the type II error rate at the desired level. In this study, we introduce a flexible beta spending function tailored to regulate the type II error rate while employing CP based on a predetermined standardized effect size for futility monitoring (a so-called CP-beta spending function). This function delineates the expenditure of type II error rate across the entirety of the trial. Unlike other existing beta spending functions, the CP-beta spending function seamlessly incorporates beta spending concept into the CP framework, facilitating precise stagewise control of the type II error rate during futility monitoring. In addition, the stopping boundaries derived from the CP-beta spending function can be calculated via integration akin to other traditional beta spending function methods. Furthermore, the proposed CP-beta spending function accommodates various thresholds on the CP-scale at different stages of the trial, ensuring its adaptability across different information time scenarios. These attributes render the CP-beta spending function competitive among other forms of beta spending functions, making it applicable to any trials in group sequential designs with straightforward implementation. Both simulation study and example from an acute ischemic stroke trial demonstrate that the proposed method accurately captures expected power, even when the initially determined sample size does not consider futility stopping, and exhibits a good performance in maintaining overall type I error rates for evident futility.

Optimal futility stopping boundaries for binary endpoints.

BACKGROUND: Group sequential designs incorporating the option to stop for futility at the time point of an interim analysis can save time and resources. Thereby, the choice of the futility boundary importantly impacts the design's resulting performance characteristics, including the power and probability to correctly or wrongly stop for futility. Several authors contributed to the topic of selecting good futility boundaries. For binary endpoints, Simon's designs (Control Clin Trials 10:1-10, 1989) are commonly used two-stage designs for single-arm phase II studies incorporating futility stopping. However, Simon's optimal design frequently yields an undesirably high probability of falsely declaring futility after the first stage, and in Simon's minimax design often a high proportion of the planned sample size is already evaluated at the interim analysis leaving only limited benefit in case of an early stop. METHODS: This work focuses on the optimality criteria introduced by Schüler et al. (BMC Med Res Methodol 17:119, 2017) and extends their approach to binary endpoints in single-arm phase II studies. An algorithm for deriving optimized futility boundaries is introduced, and the performance of study designs implementing this concept of optimal futility boundaries is compared to the common Simon's minimax and optimal designs, as well as modified versions of these designs by Kim et al. (Oncotarget 10:4255-61, 2019). RESULTS: The introduced optimized futility boundaries aim to maximize the probability of correctly stopping for futility in case of small or opposite effects while also setting constraints on the time point of the interim analysis, the power loss, and the probability of stopping the study wrongly, i.e. stopping the study even though the treatment effect shows promise. Overall, the operating characteristics, such as maximum sample size and expected sample size, are comparable to those of the classical and modified Simon's designs and sometimes better. Unlike Simon's designs, which have binding stopping rules, the optimized futility boundaries proposed here are not adjusted to exhaust the full targeted nominal significance level and are thus still valid for non-binding applications. CONCLUSIONS: The choice of the futility boundary and the time point of the interim analysis have a major impact on the properties of the study design. Therefore, they should be thoroughly investigated at the planning stage. The introduced method of selecting optimal futility boundaries provides a more flexible alternative to Simon's designs with non-binding stopping rules. The probability of wrongly stopping for futility is minimized and the optimized futility boundaries don't exhibit the unfavorable properties of an undesirably high probability of falsely declaring futility or a high proportion of the planned sample evaluated at the interim time point.

Portuguese Advance Directives-a twist against futility? A cross sectional study.

BACKGROUND: Advance Directive documents allow citizens to choose the treatments they want for end-of-life care without considering therapeutic futility. OBJECTIVES: To analyze patients' and caregivers' answers to Advance Directives and understand their expectations regarding their decisions. DESIGN AND SETTING: This study analyzed participants' answers to a previously published trial, conceived to test the document's efficacy as a communication tool. METHODS: Sixty palliative patients and 60 caregivers (n = 120) registered their preferences in the Advance Directive document and expressed their expectations regarding whether to receive the chosen treatments. RESULTS: In the patient and caregiver groups, 30% and 23.3% wanted to receive cardiorespiratory resuscitation; 23.3% and 25% wanted to receive artificial organ support; and 40% and 35% chose to receive artificial feeding and hydration, respectively. The participants ignored the concept of therapeutic futility and expected to receive invasive treatments. The concept of therapeutic futility should be addressed and discussed with both the patients and caregivers. Legal Advanced Directive documents should be made clear to reduce misinterpretations and potential legal conflicts. CONCLUSION: The authors suggest that all citizens should be clarified regarding the futility concept before filling out the Advance Directives and propose a grammatical change in the document, replacing the phrase "Health Care to Receive / Not to Receive" with the sentence "Health Care to Accept / Refuse" so that patients cannot demand treatments, but instead accept or refuse the proposed therapeutic plans. TRIAL REGISTRATION: ClinicalTrials.gov ID NCT05090072. URL: https://clinicaltrials.gov/ct2/show/NCT05090072.

Nutrición parenteral domiciliaria en pacientes con obstrucción intestinal maligna / Consideraciones éticas Home parenteral nutrition in patients with malignant bowel obstruction. Ethical considerations

Introducción: los pacientes con cáncer constituyen uno de los principales grupos de pacientes dentro de los programas de nutrición parenteraldomiciliaria (NPD). Existe un grupo de pacientes con obstrucción intestinal maligna (OIM) en quienes el uso de la NPD es controvertido. Desdeel Grupo de ética de la SENPE se revisan las cuestiones éticas detrás de la decisión de iniciar la NPD en un paciente con OIM y se propone unapropuesta de acción.Método: se procedió a hacer una revisión crítica de la literatura, tras la cual se diseñaron las preguntas que este documento pretendía responder:¿Está indicado el uso de la NPD en pacientes con OIM? ¿En qué situaciones? Quedarían otros aspectos que también merecen una reflexión:¿Cualquier oncólogo puede enviar a un paciente a su domicilio con NPD? ¿Debe ser el programa de formación de los cuidados en la NPD igualque el referente a los pacientes con fracaso intestinal de causa benigna? ¿Se debe suspender la NPD en algún momento?Resultados: la NPD en pacientes con OIM consigue mejores resultados en aquellos con una buena situación funcional (índice de Karnofsky≥ 50 o ECOG ≤ 2), con un pronóstico vital superior a 2-3 meses e, idealmente, con niveles de marcadores inflamatorios bajos. En los escasostrabajos publicados en los que se valoran las ventajas sobre la calidad de vida, se concluye que la NPD permite a los pacientes disponer de untiempo valioso en su domicilio pero a costa de una carga significativa para ellos mismos y sus familias.Propuesta de acción: una vez considerado como candidato a la NPD, se debe tener una conversación abierta con el paciente y sus familiaresen la que se aborden los beneficios potenciales, las implicaciones prácticas y los riesgos. En esa conversación inicial debe también plantearse enqué momento considerar la retirada de la NPD. El responsable de la NPD es el equipo de soporte domiciliario en colaboración con el de nutriciónclínica.(AU)

Background: patients with cancer are one of the main group of patients on home parenteral nutrition (HPN). Patients with malignant bowelobstruction (MBO) represent a challenging group when considering HPN. At the Ethics Working Group of SENPE ethical considerations on thissubject were reviewed and a guidelines proposal was made.Methods: a literature search was done and a full set of questions arose: When, if ever, is HPN indicated for patients with MBO? How shouldthe training program be? When withdrawal of HPN should be considered? Other questions should be also taken into consideration. May anyOncologist send home a patient with HPN? The educational program could be shortened? When considering to withdraw parenteral nutrition?Results: HPN in MBO has better outcomes when patients have a good functional status (Karnofsky ≥ 50 or ECOG ≤ 2), expected survival > 2-3months, and low inflammatory markers. Very few data have been reported on quality of life, but HPN allows a valuable time at home albeit witha considerable burden for both patients and their families.Proposal: once a patient is considered for HPN, there is a need for a deep talk on the benefits, complications and risks. In this initial talk, whenHNP should be stopped needs to be included. The palliative care team with the help of the nutrition support team should follow the patient, whoseclinical status must be assessed regularly. HPN should be withdrawn when no additional benefits are achieved.Conclusion: HPN may be considered an option in patients with MBO when they have a fair or good functional status and a desire to spendtheir last days at home.(AU)

Design and monitoring of clinical trials with an interim analysis and a negative binomial endpoint.

There are very rich publications devoted to group sequential design, adaptive design and trial monitoring for continuous, binary and time to event endpoints. Many authors also discuss fixed design, blinded sample size re-estimation design and group sequential design for studies with a negative binomial outcome. Nonetheless, literature is sparse in adaptive design for a trial with a negative binomial endpoint. The features of such an endpoint in a flexible trial design setting remains inadequately understood. In this research, we seek to bridge this knowledge gap by offering a thorough examination of utilizing data components from a two-stage adaptive design for unblinded conditional power calculation and corresponding sample size re-estimation. We also provide expression for calculating the probability of meeting the futility criterion to determine the appropriate timing for the interim analysis. To evaluate the performance of the design, we conduct simulations to assess its operation characteristics. Finally, we provide a helpful and illustrative example to demonstrate the practical applications of the methods.

Futile treatment - when is enough, enough?

Objective This paper examines two aspects of treatment decision making: withdrawal of treatment decisions made by a patient; and decisions to not proceed with treatment by a health professional. The paper aims to provide an overview of the law relating to the provision of treatment, then highlight the uncertainty as to the meaning of and costs associated with futile treatment. Methods The paper reviews the current legal and medical literature on futile treatment. Results Continuing treatment which is futile is not in the patient's best interests. Futility may be understood in both quantitative and qualitative terms. Recent legal cases have expanded the definition of futility to focus not on the nature of the treatment itself, but also on the health of the patient to whom treatment is provided. Conclusions As Australia's population ages, there is likely to be an increased focus on the allocation of scarce health resources. This will, inevitably, place constraints on the number and variety of treatments offered to patients. The level of constraint will be felt acutely where a proposed treatment offers little clinical efficacy. It is time to try to understand and agree on a workable definition of futility.

Seamless phase 2/3 design for trials with multiple co-primary endpoints using Bayesian predictive power.

Seamless phase 2/3 design has become increasingly popular in clinical trials with a single endpoint. Trials that define success based on the achievement of all co-primary endpoints (CPEs) encounter the challenge of inflated type 2 error rates, often leading to an overly large sample size. To tackle this challenge, we introduced a seamless phase 2/3 design strategy that employs Bayesian predictive power (BPP) for futility monitoring and sample size re-estimation at interim analysis. The correlations among multiple CPEs are incorporated using a Dirichlet-multinomial distribution. An alternative approach based on conditional power (CP) was also discussed for comparison. A seamless phase 2/3 vaccine trial employing four binary endpoints under the non-inferior hypothesis serves as an example. Our results spotlight that, in scenarios with relatively small phase 2 sample sizes (e.g., 50 or 100 subjects), the BPP approach either outperforms or matches the CP approach in terms of overall power. Particularly, with n1 = 50 and ρ = 0, BPP showcases an overall power advantage over CP by as much as 8.54%. Furthermore, when the phase 2 stage enrolled more subjects (e.g., 150 or 200), especially with a phase 2 sample size of 200 and ρ = 0, the BPP approach evidences a peak difference of 5.76% in early stop probability over the CP approach, emphasizing its better efficiency in terminating futile trials. It's noteworthy that both BPP and CP methodologies maintained type 1 error rates under 2.5%. In conclusion, the integration of the Dirichlet-Multinominal model with the BPP approach offers improvement in certain scenarios over the CP approach for seamless phase 2/3 trials with multiple CPEs.

Futility and poor outcomes are not the same thing: A clinical perspective of refined outcomes definitions in liver transplantation.

The term "futility" in liver transplantation is used inappropriately and inaccurately, as it is frequently applied to patient populations with suboptimal outcomes that are often not truly "futile." The term "futile" is used interchangeably with poor outcomes. Not all poor outcomes fulfill a definition of futility when considering all viewpoints. Definitions of "futility" are variable throughout the medical literature. We review futility in the context of liver transplantation, encompassing various viewpoints, with a goal to propose focused outcome definitions, including futility, that encompass broader viewpoints, and improve the utilization of "futility" to truly futile situations, and improve communication between providers and patients/families. Focused, appropriate definitions will help the transplant community develop better models to more accurately predict and avoid futile transplants, and better predict an individual patient's posttransplant outcome.

Bayesian hierarchical modeling in interim futility analysis for two parallel clinical trials.

Incorporating interim analysis into a trial design is gaining popularity in the field of confirmatory clinical trials, where two studies may be conducted in parallel (ie, twin studies) in order to provide substantial evidence per the requirement of FDA guidance. Interim futility analysis provides a chance to check for the "disaster" scenario when the treatment has a high probability to be not more efficacious than the control. Therefore, it is an efficient tool to mitigate risk of running a complete and expansive trial under such scenario. There is no agreement among trial designers that interim analysis should be based on individual study data or pooled data under the twin study scenario. In fact, it is a dilemma for most scientists when specifying the interim analysis strategy at the design stage as the true treatment effects of the twin studies are unknown no matter how similar they are intended to be. To address the issue, we developed a Bayesian hierarchical modeling method to allow dynamic data borrowing between twin studies and demonstrated a favorable characteristic of the new method over the separate and pooled analyses. We evaluated a wide spectrum of the heterogeneity hyperparameters and visualized its critical impact on the Bayesian model's characteristic. Based on the evaluation, we made a suggestion on the heterogeneity hyperparameter selection independent of any a priori knowledge. We also applied our method to a case study where predictive powers of different methods are compared.

Predicting futility of upfront surgery in perihilar cholangiocarcinoma: Machine learning analytics model to optimize treatment allocation.

BACKGROUND: While resection remains the only curative option for perihilar cholangiocarcinoma, it is well known that such surgery is associated with a high risk of morbidity and mortality. Nevertheless, beyond facing life-threatening complications, patients may also develop early disease recurrence, defining a "futile" outcome in perihilar cholangiocarcinoma surgery. The aim of this study is to predict the high-risk category (futile group) where surgical benefits are reversed and alternative treatments may be considered. METHODS: The study cohort included prospectively maintained data from 27 Western tertiary referral centers: the population was divided into a development and a validation cohort. The Framingham Heart Study methodology was used to develop a preoperative scoring system predicting the "futile" outcome. RESULTS: A total of 2271 cases were analyzed: among them, 309 were classified within the "futile group" (13.6%). American Society of Anesthesiology (ASA) score ≥ 3 (OR 1.60; p = 0.005), bilirubin at diagnosis ≥50 mmol/L (OR 1.50; p = 0.025), Ca 19-9 ≥ 100 U/mL (OR 1.73; p = 0.013), preoperative cholangitis (OR 1.75; p = 0.002), portal vein involvement (OR 1.61; p = 0.020), tumor diameter ≥3 cm (OR 1.76; p < 0.001), and left-sided resection (OR 2.00; p < 0.001) were identified as independent predictors of futility. The point system developed, defined three (ie, low, intermediate, and high) risk classes, which showed good accuracy (AUC 0.755) when tested on the validation cohort. CONCLUSIONS: The possibility to accurately estimate, through a point system, the risk of severe postoperative morbidity and early recurrence, could be helpful in defining the best management strategy (surgery vs. nonsurgical treatments) according to preoperative features.

Group sequential designs for cancer immunotherapy trial with delayed treatment effect.

Cancer immunotherapy trials are frequently characterized by delayed treatment effects such that the proportional hazards assumption is violated and the log-rank test suffers a substantial loss of statistical power. To increase the efficacy of the trial design, a variety of weighted log-rank tests have been proposed for fixed sample and group sequential trial designs. However, in such a group sequential design, it is often not recommended for futility interim monitoring due to possible delayed treatment effect which could result a high false-negative rate. To resolve this problem, we propose a group sequential design using a piecewise weighted log-rank test which provides an event-driven approach based on number of events after the delayed time. That is, the interim looks will not be conducted until the planned number of events observed after the delay time. Thus, it avoids the possibility of false-negative rate due to the delayed treatment effect. Furthermore, with an event-driven approach, the proposed group sequential design is robust against the underlying survival, accrual and censoring distributions. The group sequential designs using Fleming-Harrington-(ρ,γ) weighted log-rank test and a new weighted log-rank test are also discussed.

Transfusion futility thresholds and mortality in geriatric trauma: Does frailty matter?

BACKGROUND: Data on massive transfusion (MT) in geriatric trauma patients is lacking. This study aims to determine geriatric transfusion futility thresholds (TT) and TT variations based on frailty. METHODS: Patients from 2013 to 2018 TQIP database receiving MT were stratified by age and frailty. TTs and outcomes were compared between geriatric and younger adults and among geriatric adults based on frailty status. RESULTS: The TT was lower for geriatric than younger adults (34 vs 39 units; p â€‹= â€‹0.03). There was no difference in TT between the non-frail, frail, and severely frail geriatric adults (37, 30 and 25 units, respectively, p â€‹> â€‹0.05). Geriatric adults had higher mortality than younger adults (63.1% vs 45.8%, p < 0.01). Non-frail geriatric adults had the highest mortality (69.4% vs 56.5% vs 56.2%, p < 0.01). CONCLUSIONS: Geriatric patients have a lower TT than younger adults, irrespective of frailty. This may help improve outcomes and optimize MT utilization.