Historical Trials Research Articles

Surrogate endpoint meta-regression: Useful statistics for regulators and trialists

ObjectivesThe main purpose of using a surrogate endpoint is to estimate the treatment effect on the true endpoint sooner than with a true endpoint. Based on a meta-regression of historical randomized trials with surrogate and true endpoints, we discuss statistics for applying and evaluating surrogate endpoints. MethodsWe computed statistics from two types of linear meta-regressions for trial-level data: simple random effects and novel random effects with correlations among estimated treatment effects in trials with more than 2 arms. A key statistic is the estimated intercept of the meta-regression line. An intercept that is small or not statistically significant increases confidence when extrapolating to a new treatment because of consistency with a single causal pathway and invariance to labeling of treatments as controls. For a regulator applying the meta-regression to a new treatment, a useful statistic is the 95% prediction interval. For a clinical trialist planning a trial of a new treatment, useful statistics are the surrogate threshold effect proportion, the sample size multiplier adjusted for dropouts, and the novel true endpoint advantage. ResultsWe illustrate these statistics with surrogate endpoint meta-regressions involving anti-hypertension treatment, breast cancer screening, and colorectal cancer treatment. ConclusionRegulators and trialists should consider using these statistics when applying and evaluating surrogate endpoints.

A causal inference framework for leveraging external controls in hybrid trials.

We consider the challenges associated with causal inference in settings where data from a randomized trial are augmented with control data from an external source to improve efficiency in estimating the average treatment effect (ATE). This question is motivated by the SUNFISH trial, which investigated the effect of risdiplam on motor function in patients with spinal muscular atrophy. While the original analysis used only data generated by the trial, we explore an alternative analysis incorporating external controls from the placebo arm of a historical trial. We cast the setting into a formal causal inference framework and show how these designs are characterized by a lack of full randomization to treatment and heightened dependency on modeling. To address this, we outline sufficient causal assumptions about the exchangeability between the internal and external controls to identify the ATE and establish a connection with novel graphical criteria. Furthermore, we propose estimators, review efficiency bounds, develop an approach for efficient doubly robust estimation even when unknown nuisance models are estimated with flexible machine learning methods, suggest model diagnostics, and demonstrate finite-sample performance of the methods through a simulation study. The ideas and methods are illustrated through their application to the SUNFISH trial, where we find that external controls can increase the efficiency of treatment effect estimation.

WITHDRAWN: A smart agriculture information system delivering research data for adoption by the Australian grains industry

Online Farm Trials (OFT) is a bespoke online information system providing current and historical grains trials research data and information in Australia. It represents a technology that supports smart agriculture by enabling discoveries in the data. Its impact on users has been established, supporting industry knowledge and decision making and leading to improved work practices. The aim of this research is to identify the contribution of OFT, as a tool that supports smart agriculture, and to explore current adoption, barriers and the opportunities for expansion of the system in the Australian grains industry, as perceived by industry experts. In-depth, semi-structured interviews were conducted with leaders and innovators from the agriculture industry (N = 16). Thematic analysis of the qualitative data reveals widespread value of OFT as an important resource for accessing industry-dedicated, current and historical research trials data. Barriers to adoption were identified which included incomplete data, and a lack of industry-wide awareness. Opportunities to consolidate and expand the data, together with improved industry awareness, are essential to improving industry-wide adoption. Key learnings were identified in the research that has benefit for the industry, and consideration for the adoption of technology in smart agriculture. This includes functionality, audience, completeness of information/data, consideration of new technologies and the promotion of the system supported by real world examples to encourage industry adoption. Recommendations to support the design and development of digital platforms in agriculture, in the future, are also offered.

Рецензия на монографию «Адамчевский П., Войтковяк Я., Мамулиа Г. Воспоминания Изма-эль-бека (Юзефа) Петруцина-Петрушевского как источник по истории февральской рево-люции и войны на Кавказе. 1917–1919 гг. – Варшава: Институт политических исследований польской академии наук, 2022. – 332 с. (на русском языке, перевод с польского)

The review examines the publication of “Memoirs” by Jozef Petrucina-Petrushevsky, who was in the Caucasus in 1917-1920 and became a participant and witness of many historical events in the region. The review acknowledges the good archeographic preparation of the publication and con-siders the text itself as an addition to the rich heritage of Polish narratives about the Caucasus. The extraordinary personality of the author gives the originality of the “Memories”. The Russian officer and Polish patriot became a devoted soldier of the Caucasus, sharing the fate of its peoples during the hard years of historical trials of the period of revolutions and civil war. The review draws attention to the key aspects of “Memoirs” related to the history of the Mountain Republic, the author’s military activities, and his meetings with Caucasian leaders at that time. The conclu-sion is substantiated that “Memoirs” are a valuable source of the history of the Caucasus at the beginning of the last century.

Inadequate staging and excessive surveillance imaging: Evaluating the magnitude of benefit of targeted therapies in lung cancer

Several phase III trials have altered the management of oncogenic driven non-small cell lung cancer (NSCLC) including those harboring EGFR and ALK mutations. However, several of these pivotal trials deviated from standard-of-care practices for either baseline imaging or surveillance imaging. This occurred despite sponsor acknowledgement in a clinical trial protocol that historical trials utilized imaging modalities that potentially under-staged patients. Inadequate baseline imaging for adjuvant trials instead of PET/CT may not identify individuals with metastatic disease, and thereby subject such individuals with metastatic disease to inferior treatment if randomized to the control arm. Similarly, more frequent surveillance imaging than what is considered standard-of-care may identify disease progression earlier than what is expected in real-world clinical practice and therefore embellish the magnitude of benefit between a targeted therapy and the control arm. While targeted therapies have provided clinical benefit for individuals with oncogenic driven NSCLC, physicians and patients must be cognizant that clinical trial deviations from standard-of-care imaging practices may have embellished the magnitude of benefit for several of these therapies.

Ruptured AAA: bridging the gap between international guidelines and local clinical realities

BackgroundTreatment of asymptomatic Abdominal Aortic Aneurysms (AAA) presents a clinical challenge, requiring a delicate balance between rupture risk, patient comorbidities, and intervention-related complications. International guidelines recommend intervention for specific AAA size thresholds, but these are based on historical trials with limited female representation. We aimed to analyse disease characteristics, AAA size at rupture, and intervention outcomes in patients with ruptured AAA from 2009 to 2023 to investigate the gap between guidelines and local realities.MethodsThis single-centre retrospective cohort study analysed electronic health records of patients treated for a ruptured AAA, excluding those who were managed palliatively. The study assessed patients’ demographics, risk factors, comorbidities, clinical presentation, radiological characteristics, and outcomes.ResultsOf 164 patients (41 females, 123 males, median age 73.5), 93.3% presented with abdominal or back pain. The median AAA size at rupture was 8.0 cm in males and 7.6 cm in females. No significant correlations were found between demographic characteristics, risk factors, AAA size, repair modality, and outcomes. Trends show a decline in AAA prevalence and rupture rates, aligning with global health initiatives. Post-intervention survival rates at 30 days were 70.7% (67.5% in males and 80.0% in females), and at 2 years were 65.85% (61.7% in males and 70.0% in females).ConclusionEvolving AAA trends and improved post-intervention survival rates warrant a critical reassessment of existing intervention recommendations. Adjusting intervention thresholds to larger sizes may be justified to optimise the risk-benefit ratio.

Enhancing Study Power in Pediatric Research through Bayesian Extrapolation

Pediatric populations, comprising individuals aged 18 or younger, and rare disease populations pose significant challenges in clinical trial design due to limited participant numbers, patient sensitivity, and insufficient natural history data. Addressing these challenges often involves data extrapolation, leveraging existing data from adults to inform pediatric trials. Bayesian hierarchical modeling is increasingly recognized as a valuable tool for combining information across disparate sources, such as adult and pediatric datasets. This manuscript introduces an extension of an existing statistical model to enhance the efficiency of borrowing strength from multiple historical trials under consistent assumptions. A quantitative method is developed to improve the borrowing of historical information. The methods are illustrated with a simulation study motivated by real case study in pediatric clinical trial, and practical considerations are provided regarding the selection of prior distributions. This work aims to provide comprehensive insights and practical guidance for leveraging historical data effectively in clinical trial design.

2025 update on clinical trials in immune thrombocytopenia.

Although the development and regulatory approval of the thrombopoietin receptor agonists revolutionized aspects of the immune thrombocytopenia (ITP) treatment landscape over the past two decades, there remain many areas of high unmet need. Therefore, a number of investigational and repurposed agents are currently undergoing clinical development in ITP. In a departure from historical trials, which largely focused on the indefinite treatment of persistent or chronic ITP, ongoing trials run the gamut of disease phases, and include novel agents being evaluated in early phases of the disease to attempt to modify the disease course. Many agents in development target disease pathophysiologic mechanisms not previously targeted by agents in current use, including platelet autoantibody recycling, B-cell maturation and differentiation, long-lived plasma cells, and the complement system, among others. These agents represent promising treatment options for patients with otherwise refractory disease or who are intolerant of currently available therapies. Additionally, with our increasing understanding of the diverse immune mechanisms at play in ITP, the expansion of the therapeutic armamentarium to include agents targeting diverse pathophysiologic mechanisms may allow a more personalized therapeutic selection in the future. This manuscript provides an up-to-date, in-depth overview of recently completed and ongoing clinical trials in ITP.

Modern approaches for evaluating treatment effect heterogeneity from clinical trials and observational data.

In this paper, we review recent advances in statistical methods for the evaluation of the heterogeneity of treatment effects (HTE), including subgroup identification and estimation of individualized treatment regimens, from randomized clinical trials and observational studies. We identify several types of approaches using the features introduced in Lipkovich et al (Stat Med 2017;36: 136-196) that distinguish the recommended principled methods from basic methods for HTE evaluation that typically rely on rules of thumb and general guidelines (the methods are often referred to as common practices). We discuss the advantages and disadvantages of various principled methods as well as common measures for evaluating their performance. We use simulated data and a case study based on a historical clinical trial to illustrate several new approaches to HTE evaluation.

Evaluating the robustness of an AI pathfinder application on eligibility criteria in multiple myeloma trials using real-world data and historical trials.

Background: Eligibility criteria are pivotal in achieving clinical trial success, enabling targeted patient enrollment while ensuring the trial safety. However, overly restrictive criteria hinder enrollment and study result generalizability. Broadening eligibility criteria enhances the trial inclusivity, diversity and enrollment pace. Liu et al.proposed an AI pathfinder method leveraging real-world data to broaden criteria without compromising efficacy and safety outcomes, demonstrating promise in non-small cell lung cancer trials. Aim: To assess the robustness of the methodology, considering diverse qualities of real-world data and to promote its application. Materials/Methods: We revised the AI pathfinder method, applied it to relapsed and refractory multiple myeloma trials and compared it using two real-world data sources. We modified the assessment and considered a bootstrap confidence interval of the AI pathfinder to enhance the decision robustness. Results & conclusion: Our findings confirmed the AI pathfinder's potential in identifying certain eligibility criteria, in other words, prior complications and laboratory tests for relaxation or removal. However, a robust quantitative assessment, accounting for trial variability and real-world data quality, is crucial for confident decision-making and prioritizing safety alongside efficacy.

Statistical approaches for the integration of external controls in a cystic fibrosis clinical trial: a simulation and an application.

Development of new therapeutics for a rare disease such as cystic fibrosis (CF) is hindered by challenges in accruing enough patients for clinical trials. Using external controls from well-matched historical trials can reduce prospective trial sizes, and this approach has supported regulatory approval of new interventions for other rare diseases. We consider three statistical methods that incorporate external controls into a hypothetical clinical trial of a new treatment to reduce pulmonary exacerbations in CF patients: 1) inverse probability weighting, 2) Bayesian modeling with propensity score-based power priors, and 3) hierarchical Bayesian modeling with commensurate priors. We compare the methods via simulation study and in a real clinical trial data setting. Simulations showed that bias in the treatment effect was <4% using any of the methods, with type 1 error (or in the Bayesian cases, posterior probability of the null hypothesis) usually <5%. Inverse probability weighting was sensitive to similarity in prevalence of the covariates between historical and prospective trial populations. The commensurate prior method performed best with real clinical trial data. Using external controls to reduce trial size in future clinical trials holds promise and can advance the therapeutic pipeline for rare diseases.

Impact of Subspecialty Pediatric Palliative Care on Children with Heart Disease; A Systematic Review and Meta-analysis.

While many experts in pediatric cardiology have emphasized the importance of palliative care involvement, very few studies have assessed the influence of specialty pediatric palliative care (SPPC) involvement for children with heart disease. We conducted a systematic review using keywords related to palliative care, quality of life and care-satisfaction, and heart disease. We searched PubMed, EMBASE, CINAHL, CENTRAL and Web of Science in December 2023. Screening, data extraction and methodology followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) recommendations. Pairs of trained reviewers independently evaluated each article. All full texts excluded from the review were hand-screened for eligible references including systematic reviews in general pediatric populations. Two reviewers independently extracted: (1) study design; (2) methodology; (2) setting; (3) population; (4) intervention/exposure and control definition; (5) outcome measures; and (6) results. Of 4059 studies screened, 9 met inclusion criteria including two with overlapping patient data. Study designs were heterogenous, including only one randomized control and two historical control trials with SPPC as a prospective intervention. Overall, there was moderate to high risk of bias. Seven were single centers studies. In combined estimates, patients who received SPPC were more likely to have advance care planning documented (RR 2.7, [95%CI 1.6, 4.7], p < 0.001)and resuscitation limits (RR 4.0, [2.0, 8.1], p < 0.001), while half as likely to have active resuscitation at end-of-life ([0.3, 0.9], p = 0.032). For parental stress, receipt of SPPC improved scores by almost half a standard deviation (RR 0.48, 95%CI 0.10, 0.86) more than controls. Ultimately, we identified a paucity of high-quality data studying the influence of SPPC; however, findings correlate with literature in other pediatric populations. Findings suggest benefits of SPPC integration for patients with heart disease and their families.

EPEN-05. SURGERY FOR CHILDHOOD EPENDYMOMA: THE EPENDYMOMA MULTIDISCIPLINARY ADVISORY GROUP (EMAG) CLINICAL TRIAL EXPERIENCE

Abstract INTRODUCTION The National Ependymoma Multidisciplinary Advisory Group (EMAG) is the central review mechanism for the SIOP Ependymoma II clinical trial in the UK. EMAG is a multiprofessional group which meets weekly to support decision making. We report detailed surgical outcomes for children with confirmed intracranial ependymoma, discussed through EMAG between January 2020 and November 2022. METHODS Data was collected on resection status, surgical outcomes, reasons for not achieving Gross Total Resection (GTR), number of surgeries and adjuvant therapies. Data was analysed descriptively. RESULTS After first surgery, GTR or near total resection (NTR) rate was 69/105 (66%) rising to 83/105 (79%) following repeated surgeries. 17 patients underwent second-look surgery prior to further therapy, whilst 9 underwent second-look surgery after chemotherapy but before radiotherapy. Eight (17%) posterior fossa (PF) surgeries were not completed due to factors including patient instability and tumour attachments. Most post-operative problems were seen in PF tumours with 26/60 (43%) bulbar palsy, 13/60 (22%) focal weakness and 12/60 (20%) cerebellar mutism. Incomplete PF resections were associated with increased bulbar palsy risk (p=0.02, Chi-Square test). 73% of PF patients required hydrocephalus management with external ventricular drainage, endoscopic third ventriculostomy (ETV) or shunt. Longer term hydrocephalus management with ETV or shunt was required in 29% and was more common in those with subtotal resection (R3-RX, 8/16, 50%) compared to GTR or NTR (R0-R2, 9/43, 21%, p=0.03). 27/60 (45%) received post-op NG feeding and 2/60 (3%) needed tracheostomies. Second surgery was associated with lower complication rates. DISCUSSION Our National MDT approach supports collaborative surgical decision making without a need for centralisation of the surgery itself. There was no evidence of increased complication rates compared to historical trials despite a more aggressive surgical approach. We argue for continued centralisation of EPN evaluation to support optimal care for children with this devastating disease.

Brain metastases in clinical trial participants with KRAS-mutated advanced non-small cell lung cancer receiving docetaxel: Pooled data analysis

ObjectivesLimited data are available on central nervous system (CNS) efficacy with standard-of-care therapies for KRAS-mutated (KRASmut) advanced non-small cell lung cancer (NSCLC). The objective of this study was to investigate the incidence and progression of brain metastases in KRASmut advanced NSCLC treated with docetaxel using pooled data from historical clinical trials. Materials and MethodsData from phase 2/3 trials of docetaxel-containing regimens in advanced NSCLC were sourced from the Medidata platform. Analysis was restricted to stage IIIB-IV KRASmut NSCLC with disease progression after ≥ 1 systemic anticancer therapy. Participants with asymptomatic, treated, and stable brain metastases were included. Endpoints included 12-month CNS disease control rate (CNS-DCR) and CNS progression per Response Evaluation Criteria in Solid Tumors; progression-free survival (PFS); and overall survival (OS). Data were pooled and analyses stratified by baseline brain metastases status. ResultsA total of 595 participants were included in the analysis (62 [10%] with baseline brain metastases and 533 [90 %] without). Among participants with brain metastases, 17 (27.4 %) had CNS progression during docetaxel treatment and 12-month CNS-DCR was 75.8 %; 45 (8.4 %) participants without baseline brain metastases developed brain metastases during treatment. In an analysis restricted to patients with metastatic disease, outcomes with and without baseline brain metastases included: median PFS, 3.3 and 4.9 months (p < 0.005); 12-month PFS, 5 % and 16 %; median OS, 6.9 and 10.4 months (p < 0.005); and 12-month OS, 20 % and 44 %, respectively. ConclusionThese findings establish CNS progression rates with docetaxel in previously treated KRASmut advanced NSCLC and facilitate interpretation of data from ongoing randomized clinical trials of novel KRAS-targeted therapeutic strategies vs. docetaxel.

Prediction of therapeutic response and cancer outcomes in solid tumours via in silico clinical trials.

e13603 Background: Oncology therapeutic development has high failure rates with substantial costs. Advances in technology, including molecular characterisations of cancer and computational power, provide the opportunity to better model therapeutic response for existing and emerging therapies. Methods: Concr adapted Bayesian statistical principles used by astrophysicists to effectively integrate multi-dimensional data (genomic &amp; transcriptomic) for accurate modelling of cancer biology. Our proprietary computational framework was applied to predict clinical response and survival through construction of digital twins and in silico simulations of clinical trials. Predicted log odds ratios (LOR) were generated for drug response and compared to published data from 8 suitable historical clinical trials. Three distinct models underpin this framework: Drug Efficacy, Treatment Response &amp; Overall Survival (OS). Three publicly available datasets were used for training: Cancer Therapeutic Response Portal ( in vitro dose-response data), Cancer Cell Line Encyclopaedia and TCGA. Results: For all 8 clinical studies, the digital twin model accurately simulated both trial arms, compared drug efficacy across arms and predicted which treatment was most active. Unblinded evaluation: Our model accurately predicted gemcitabine would have greater clinical benefit than 5-FU (LOR -0.10, P &lt;0.0001) in metastatic pancreatic cancer. In advanced breast cancer, the model predicted docetaxel had a higher response rate than doxorubicin, and carboplatin response rates were similar to docetaxel in BRCA wild-type patients. In platinum-sensitive recurrent ovarian cancer, the model predicted cisplatin-based combination had a higher response rate than paclitaxel. Blinded evaluation: Using data for paclitaxel, the model correctly predicted that nab-paclitaxel+gemcitabine response rates were higher than gemcitabine in metastatic pancreatic cancer (predicted LOR -0.090, p = &lt;0.001). In all 3 early breast cancer studies, predictions mirrored clinical trial results, adjuvant ECF &gt; CMF, adjuvant TC &gt; AC and adjuvant tamoxifen was superior to capecitabine. The underlying pan-tumour Overall Survival model used a Random Survival Forest approach, trained on 23 cancers with predictive accuracy of 0.78 AUC ROC and C-index 0.71. To enable cohort enrichment for drug response, the model segmented patient cohorts into treatment responder and non-responder. Using this approach, the log odds increased for drug response rate for 16 of the 19 different cancers and 14 of the different 17 drugs. Conclusions: Our digital twin model represents transformative technology for clinical trial simulation with strong potential for accelerating and de-risking clinical drug development, and utility for synthetic control arms.

Q&A: Methods for estimating genetic gain in sub-Saharan Africa and achieving improved gains.

Regular measurement of realized genetic gain allows plant breeders to assess and review the effectiveness of their strategies, allocate resources efficiently, and make informed decisions throughout the breeding process. Realized genetic gain estimation requires separating genetic trends from nongenetic trends using the linear mixed model (LMM) on historical multi-environment trial data. The LMM, accounting for the year effect, experimental designs, and heterogeneous residual variances, estimates best linear unbiased estimators of genotypes and regresses them on their years of origin. An illustrative example of estimating realized genetic gain was provided by analyzing historical data on fresh cassava (Manihot esculenta Crantz) yield in West Africa (https://github.com/Biometrics-IITA/Estimating-Realized-Genetic-Gain). This approach can serve as a model applicable to other crops and regions. Modernization of breeding programs is necessary to maximize the rate of genetic gain. This can be achieved by adopting genomics to enable faster breeding, accurate selection, and improved traits through genomic selection and gene editing. Tracking operational costs, establishing robust, digitalized data management and analytics systems, and developing effective varietal selection processes based on customer insights are also crucial for success. Capacity building and collaboration of breeding programs and institutions also play a significant role in accelerating genetic gains.

Outcomes of patients with peritoneal carcinomatosis treated with HIPEC and chemotherapy or HIPEC alone: A single center community experience.

e15578 Background: Peritoneal carcinomatosis is a common presentation of intraperitoneal malignancies. The optimal management of peritoneal carcinomatosis is currently unknown but can contain a combination of HIPEC and chemotherapy. Optimal timing and order of these interventions is controversial. HIPEC surgery alone can provide a cure rate of approximately 16% with macroscopically complete resection. The PRODIGE 7 trial demonstrated no difference in overall survival between HIPEC plus cytoreduction versus cytoreduction alone with six months of systemic chemotherapy. Which patients should receive HIPEC, chemotherapy and HIPEC or chemotherapy alone remains unknown. Methods: This is a single center, retrospective chart review assessing all patients age 18 and above who received HIPEC surgery with and without the administration of chemotherapy at Ascension Saint John Hospital. Results: We found that there was no significant difference in overall survival and progression free survival between the HIPEC and HIPEC with chemotherapy group with a OS of 57.2 months and 52.5 months; and PFS of 33.6 and 34.4 months respectively. We found that patients with a PCI score between 0 and 13, overall survival favored the HIPEC alone group versus the HIPEC with chemotherapy with a p value of 0.043. There was no difference in progression free survival and overall survival in all other groups when stratified by PCI. When stratified by disease subtype, we no differences between PFS and OS for both appendiceal and colon cancer. Conclusions: The primary objective of this study was to investigate the difference in overall survival and progression free survival among patients with peritoneal carcinomatosis when treated with either HIPEC with systemic chemotherapy versus HIPEC alone. This analysis among 100 patients showed no statistically significant differences in OS or PFS for patients receiving a combination of HIPEC with systemic chemotherapy versus HIPEC alone. The only exception to this was with respect to OS in patients with a PCI score between 0-13. In this group, 0 patients in the HIPEC along group experienced disease progression where 5 progressed in the HIPEC and chemotherapy group. Our data suggests that HIPEC alone may be a reasonable treatment approach for patients with a low PCI score. Important conclusions can be drawn from the data when compared to historical trials. The PROTEGE 7 study found that the median overall survival was approximately 41.7 months for the HIPEC and cytoreductive surgery group and 41.2 months versus cytoreductive surgery alone. The overall survival for the HIPEC alone group was 57.2 months and 52.5 months for the HIPEC plus chemotherapy group. This data suggests that the combination of HIPEC and chemotherapy is a reasonable approach to patients with peritoneal carcinomatosis.

Outcomes of patients aged ≥26 years with relapsed or refractory B-cell acute lymphoblastic leukemia in ZUMA-3 and historical trials

Brexucabtagene autoleucel (brexu-cel) is an autologous anti-CD19 CAR T-cell therapy approved in the USA and European Union (EU) for adults with relapsed or refractory B-cell acute lymphoblastic leukemia (R/R B-ALL; aged ≥26 years in EU). Here, outcomes for patients with R/R B-ALL aged ≥26 years in ZUMA-3 treated with brexu-cel were compared with historical standard-of-care (SOC) therapy. After median follow-up of 26.8 months, the overall complete remission (CR) rate among patients treated with brexu-cel in Phase 2 (N = 43) was 72% and median overall survival (OS) was 25.4 months (95% CI, 15.9-NE). Median OS was improved in Phase 2 patients versus matched historical SOC-treated patients. Compared with aggregate historical trial data, Phase 1 and 2 patients had improved OS versus blinatumomab, inotuzumab, and chemotherapy in a matching-adjusted indirect comparison (MAIC) study. These data demonstrate clinical benefit of brexu-cel relative to SOC in patients ≥26 years with R/R B-ALL.

Genetic progress in cowpea [Vigna unguiculata (L.) Walp.] stemming from breeding modernization efforts at the International Institute of Tropical Agriculture.

Genetic gain has been proposed as a quantifiable key performance indicator that can be used to monitor breeding programs' effectiveness. The cowpea breeding program at the International Institute of Tropical Agriculture (IITA) has developed and released improved varieties in 70 countries globally. To quantify the genetic changes to grain yield and related traits, we exploited IITA cowpea historical multi-environment trials (METs) advanced yield trial (AYT) data from 2010 to 2022. The genetic gain assessment targeted short duration (SD), medium duration (MD), and late duration (LD) breeding pipelines. A linear mixed model was used to calculate the best linear unbiased estimates (BLUE). Regressed BLUE of grain yield by year of genotype origin depicted realized genetic gain of 22.75 kg/ha/year (2.65%), 7.91 kg/ha/year (0.85%), and 22.82 kg/ha/year (2.51%) for SD, MD, and LD, respectively. No significant gain was realized in 100-seed weight (Hsdwt). We predicted, based on 2022 MET data, that recycling the best genotypes at AYT stage would result in grain yield gain of 37.28 kg/ha/year (SD), 28.00 kg/ha/year (MD), and 34.85 kg/ha/year (LD), and Hsdwt gain of 0.48g/year (SD), 0.68g/year (MD), and 0.55g/year (LD). These results demonstrated a positive genetic gain trend for cowpea, indicating that a yield plateau has not yet been reached and that accelerated gain is expected with the recent integration of genomics in the breeding program. Advances in genomics include the development of the reference genome, genotyping platforms, quantitative trait loci mapping of key traits, and active implementation of molecular breeding.

Hierarchical modelling of variance components makes analysis of resolvable incomplete block designs more efficient

The standard approach to variance component estimation in linear mixed models for alpha designs is the residual maximum likelihood (REML) method. One drawback of the REML method in the context of incomplete block designs is that the block variance may be estimated as zero, which can compromise the recovery of inter-block information and hence reduce the accuracy of treatment effects estimation. Due to the development of statistical and computational methods, there is an increasing interest in adopting hierarchical approaches to analysis. In order to increase the precision of the analysis of individual trials laid out as alpha designs, we here make a proposal to create an objectively informed prior distribution for variance components for replicates, blocks and plots, based on the results of previous (historical) trials. We propose different modelling approaches for the prior distributions and evaluate the effectiveness of the hierarchical approach compared to the REML method, which is classically used for analysing individual trials in two-stage approaches for multi-environment trials.