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To study the reproductive system of the putative autogamous species Anthyllis vulneraria in Belgian calcareous grasslands, eight polymorphic microsatellite loci were developed using the sequence-tagged microsatellite profiling technique and 35 plants were typed for all loci. No linkage disequilibrium was found between any pair of loci. Over the loci, the number of alleles ranged from two to five. Observed and expected heterozygosities ranged from 0.053 to 0.688 and from 0.053 to 0.631, respectively. The estimated FIS values ( FIS = 0.031 and 0.122) are not in accordance with a predominantly selfing reproductive system. [ABSTRACT FROM AUTHOR]

Background: Evidence suggests that ctDNA may be a reliable biomarker to monitor metastatic colorectal cancer (CRC) evolution. Nevertheless, evidence on the potential of liquid biopsy in this setting is still low quality, mostly consisting of retrospective studies., Methods: COPERNIC is an international, multicenter clinical trial. The pilot study aims to confirm the predictive potential of early on-treatment ctDNA dynamics, and inform the design of a larger ctDNA-driven trial. Advanced CRC patients who are candidates for ≥3rd lines of systemic therapy undergo longitudinal blood sample collection during treatment (day 1, 15 and 29 for 2- or 4-weekly treatment regimens; day 1, 22 and 43 for 3-weekly treatment regimens) and at each imaging assessment. ctDNA analyses are carried out with the FoundationOne Liquid CDx and FoundationOneMonitor assays, and ctDNA changes during treatment are correlated with radiologic response (as assessed every 8-12 weeks by RECIST v1.1). The primary objective is to select the optimal timepoint and cut-off value for early ctDNA changes (at day 15/22) to predict progressive disease as best radiological response with a high positive predictive value. The cut-off value for ctDNA will be defined based on nonparametric ROC-curves with bootstrapping. Based on the expected rate of progressive disease and statistical assumptions, 109 patients are needed to be screened to have 87 assessable patients. COPERNIC is sponsored by the Institut Jules Bordet, and supported by Roche and Foundation Medicine. Recruitment is open in 13 centres across Belgium and France. The study is registered with clinicaltrials.gov (NCT05487248)., Competing Interests: Disclosure Giacomo Bregni: Support for travel/accomodation from Amgen. Marc Buyse: Stock ownership in International Drug Development Institute (IDDI), Louvain-la-Neuve, Belgium. Benoist Chibaudel: Consultancy, advisory roles, honoraria from Amgen, Bayer, Beigine, Biocartis, Lilly, Merck, MSD, Pfizer, Pierre Fabre, Roche, SeqOne, Sanofi, Servier, Takeda. Karen Geboes: Consultancy, advisory roles, honoraria from Amgen, BMS, Ipsen, MSD, Merck, Pierre Fabre, Servier. Research funding (institutional) from Merck, Ipsen, Servier. Support for travel/accomodation from Ipsen, Servier. Timon Vandamme: Consultancy, advisory roles, honoraria from AstraZeneca, Bayer, Bristol Myers Squibb, Eisai, Elmedix, Ipsen, Novartis, Roche, Sirtex. Research funding (institutional) from Ipsen and Novartis. Support for travel/accomodation from Ipsen and Servier. Alain Hendlisz: Consultancy, advisory roles, honoraria from Amgen, Bayer, Eli Lilly, Merck, Pierre Fabre, Servier, Sirtex. Research funding (institutional) from Amgen, Astra Zeneca, Ipsen, Leo Pharma, Merck, Roche, Sanofi, Teva Pharma. Support for travel/accomodation from Merck, Roche, Sirtex. Francesco Sclafani: Consultancy, advisory roles, honoraria from AMAL Therapeutics, Amgen, Bayer, BMS, Dragonfly Therapeutics, GSK, Merck, Nordic Pharma, Roche, Servier. Research funding (institutional) from Amgen, Astellas, Astra Zeneca, Bayer, BMS, Merck, MSD, Pierre-Fabre, Roche, Sanofi. Support for travel/accomodation from Amgen, Astra Zeneca, Bayer, Lilly, Merck, Roche, Servier. Leadership role: Secretary of the EORTC Gastrointestinal Tract Cancer Group., (Copyright © 2024 Elsevier Inc. All rights reserved.)

In randomized trials, comparability of the treatment groups is ensured through allocation of treatments using a mechanism that involves some random element, thus controlling for confounding of the treatment effect. Completely random allocation ensures comparability between the treatment groups for all known and unknown prognostic factors. For a specific trial, however, imbalances in prognostic factors among the treatment groups may occur. Although accidental bias can be avoided in the presence of such imbalances by stratifying the analysis, most trialists, regulatory agencies, and other stakeholders prefer a balanced distribution of prognostic factors across the treatment groups. Some procedures attempt to achieve balance in baseline covariates, by stratifying the allocation for these covariates, or by dynamically adapting the allocation using covariate information during the trial (covariate-adaptive procedures). In this Tutorial, the performance of minimization, a popular covariate-adaptive procedure, is compared with two other commonly used procedures, completely random allocation and stratified blocked designs. Using individual patient data of 2 clinical trials (in advanced ovarian cancer and age-related macular degeneration), the procedures are compared in terms of operating characteristics (using asymptotic and randomization tests), predictability of treatment allocation, and achieved balance. Fifty actual trials of various sizes that applied minimization for treatment allocation are used to investigate the achieved balance. Implementation issues of minimization are described. Minimization procedures are useful in all trials but especially when (1) many major prognostic factors are known, (2) many centers of different sizes accrue patients, or (3) the trial sample size is moderate., (© 2023 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.)

Immunotherapy with checkpoint inhibitors (CPIs) and cell-based products has revolutionized the treatment of various solid tumors and hematologic malignancies. These agents have shown unprecedented response rates and long-term benefits in various settings. These clinical advances have also pointed to the need for new or adapted approaches to trial design and assessment of efficacy and safety, both in the early and late phases of drug development. Some of the conventional statistical methods and endpoints used in other areas of oncology appear to be less appropriate in immuno-oncology. Conversely, other methods and endpoints have emerged as alternatives. In this article, we discuss issues related to trial design in the early and late phases of drug development in immuno-oncology, with a focus on CPIs. For early trials, we review the most salient issues related to dose escalation, use and limitations of tumor response and progression criteria for immunotherapy, the role of duration of response as an endpoint in and of itself, and the need to conduct randomized trials as early as possible in the development of new therapies. For late phases, we discuss the choice of primary endpoints for randomized trials, review the current status of surrogate endpoints, and discuss specific statistical issues related to immunotherapy, including non-proportional hazards in the assessment of time-to-event endpoints, alternatives to the Cox model in these settings, and the method of generalized pairwise comparisons, which can provide a patient-centric assessment of clinical benefit and be used to design randomized trials.

The human epidermal growth factor receptor 2 (HER2)-enriched intrinsic subtype represents up to 75% of all HER2-positive hormone receptor (HR)-negative breast cancer (BC). Optimizing HER2-targeting therapy in this population might allow the omission of anthracycline-based chemotherapy, which is associated with potentially severe toxicities. DECRESCENDO (NCT04675827) is a large, multicenter, single-arm phase II trial in patients with HR-negative, HER2-positive, node-negative early BC evaluating a neoadjuvant pertuzumab and trastuzumab fixed-dose combination administered subcutaneously plus taxane-based chemotherapy followed by adjuvant treatment, adapted according to response to neoadjuvant therapy. The primary end point is the 3-year recurrence-free survival rate in patients with 'HER2-enriched' tumors and a pathological complete response. This flexible care substudy offers adjuvant treatment administration outside the hospital to some patients.

Background: Missing data may lead to loss of statistical power and introduce bias in clinical trials. The Covid-19 pandemic has had a profound impact on patient health care and on the conduct of cancer clinical trials. Although several endpoints may be affected, progression-free survival (PFS) is of major concern, given its frequent use as primary endpoint in advanced cancer and the fact that missed radiographic assessments are to be expected. The recent introduction of the estimand framework creates an opportunity to define more precisely the target of estimation and ensure alignment between the scientific question and the statistical analysis., Methods: We used simulations to investigate the impact of two basic approaches for handling missing tumor scans due to the pandemic: a "treatment policy" strategy, which consisted in ascribing events to the time they are observed, and a "hypothetical" approach of censoring patients with events during the shutdown period at the last assessment prior to that period. We computed the power of the logrank test, estimated hazard ratios (HR) using Cox models, and estimated median PFS times without and with a hypothetical 6-month shutdown period with no patient enrollment or tumor scans being performed, varying the shutdown starting times., Results: Compared with the results in the absence of shutdown, the "treatment policy" strategy slightly overestimated median PFS proportionally to the timing of the shutdown period, but power was not affected. Except for one specific scenario, there was no impact on the estimated HR. In general, the pandemic had a greater impact on the analyses using the "hypothetical" strategy, which led to decreased power and overestimated median PFS times to a greater extent than the "treatment policy" strategy., Conclusion: As a rule, we suggest that the treatment policy approach, which conforms with the intent-to-treat principle, should be the primary analysis to avoid unnecessary loss of power and minimize bias in median PFS estimates., (© 2022. The Author(s).)

Meta-analysis based on individual participant data (IPD) is a powerful methodology for synthesizing evidence by combining information drawn from multiple trials. Hitherto, its principal application has been in questions of clinical management, but an increasingly important use is in clarifying trials methodology, for instance in the selection of endpoints, as discussed in this review. In oncology, the Aide et Recherche en Cancérologie Digestive (ARCAD) Metastatic Colorectal Cancer Database is a leader in the use of IPD-based meta-analysis in methodological research. The ARCAD database contains IPD from more than 38 000 patients enrolled in 46 studies and continues to collect phase III trial data. Here, we review the principal findings of the ARCAD project in respect of endpoint selection and examine their implications for cancer trials. Analysis of the database has confirmed that progression-free survival (PFS) is no longer a valid surrogate endpoint predictive of overall survival in the first-line treatment of colorectal cancer. Nonetheless, PFS remains an endpoint of choice for most first-line trials in metastatic colorectal cancer and other solid tumors. Only substantial PFS effects are likely to translate into clinically meaningful benefits, and accordingly, we advocate an oncology research model designed to identify highly effective treatments in carefully defined patient groups. We also review the use of the ARCAD database in assessing clinical response including novel response metrics and prognostic markers. These studies demonstrate the value of IPD as a tool for methodological studies and provide a reference point for the expansion of this approach within clinical cancer research., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Mitochondrial fusion and fission proteins have been nominated as druggable targets in cancer. Whether their inhibition is efficacious in triple negative breast cancer (TNBC) that almost invariably develops chemoresistance is unknown., Methods: We used a combination of bioinformatics analyses of cancer genomic databases, genetic and pharmacological Optic Atrophy 1 (OPA1) inhibition, mitochondrial function and morphology measurements, micro-RNA (miRNA) profiling and formal epistatic analyses to address the role of OPA1 in TNBC proliferation, migration, and invasion in vitro and in vivo., Results: We identified a signature of OPA1 upregulation in breast cancer that correlates with worse prognosis. Accordingly, OPA1 inhibition could reduce breast cancer cells proliferation, migration, and invasion in vitro and in vivo. Mechanistically, while OPA1 silencing did not reduce mitochondrial respiration, it increased levels of miRNAs of the 148/152 family known to inhibit tumor growth and invasiveness. Indeed, these miRNAs were epistatic to OPA1 in the regulation of TNBC cells growth and invasiveness., Conclusions: Our data show that targeted inhibition of the mitochondrial fusion protein OPA1 curtails TNBC growth and nominate OPA1 as a druggable target in TNBC., (© 2022. The Author(s).)

Introduction: Recent changes in the adjuvant treatment of melanoma have raised interest in confirming relapse-free survival (RFS) as a surrogate for overall survival (OS)., Methods: We explore this issue with the meta-analytic framework, using individual patient data from the European Organisation for Research and Treatment of Cancer (EORTC) 18071 trial of ipilimumab and published results from other adjuvant trials., Results: The individual patient data analysis results at a median follow-up of 5.3 years showed a strong association between RFS and OS at the patient level (ρ = 0.84; 95% confidence interval [CI]: 0.82-0.87) and a moderate association at the trial level (R 2  = 0.59; 95% CI: 0.08-1.00)., Conclusions: The trial-level association previously observed in interferon-based trials appeared to be maintained when the EORTC 18071 results were added to a regression analysis using published results from other trials. More data from adjuvant trials are required to confirm the strength of association between RFS and OS in this setting., Competing Interests: Conflict of interest statement M.B. reports receiving personal fees and other from funds from IDDI, outside of the submitted work. G.de.S. and S.S. report receiving Bristol-Myers Squibb Grant to the EORTC HQ. A.E.reports receiving personal fees from Biocad, BioInvent, BMS, Ellipses, GSK, ISA Pharmaceuticals, IO Bioteck, Merk&Co/MSD, Nektar, Novartis, Sanofi, Sellas and SkylineDx; personal fees from Biocad, MSD, Novartis, GSK, Novartis and Pfizer and other fees from BMS, outside the submitted work. A.M. and S.K. are employees of and hold stock/stock options in Bristol Myers Squibb. E.C, E.D.S. and P.S. report receiving employer IDDI and consultancy fees from BMS during the conduct of the study. J.S.W. reports receiving grants from BMS, Merck and Novartis, outside the submitted work; In addition, J.S.W. has been named on a PD-1 biomarker patent by Biodesix and on a CTLA4 biomarker patent by Moffitt Cancer Center., (Copyright © 2020. Published by Elsevier Ltd.)

Time-to-event end points are the most frequent primary end points in phase III oncology trials, both in the adjuvant and advanced settings. The evaluation of these end points is important to inform clinical practice. However, although different measures can be used to describe the effect of treatment on these end points, we believe that any treatment benefit in a given trial is best reported using various absolute and relative measures. Our goal is to help clinicians understand the strengths and limitations of the traditional and novel measures used to denote the effect of treatment in randomized trials. Although none of these measures can reliably predict the outcome of individual patients, some measures could be added to the commonly used hazard ratio to provide a more patient-oriented assessment of treatment benefit. In particular, the difference of mean survival times quantifies the average survival benefit for a patient receiving a new treatment compared with a patient treated with standard of care, whereas the net benefit quantifies the probability of a patient receiving the new treatment to live longer by at least m months (for any number of months m of interest) than a patient receiving the standard treatment. We encourage statisticians and clinical scientists to include various measures of treatment benefit in the reports of phase III trials, acknowledging that different clinical situations may call for different measures of treatment effect. By using the various available measures, we may better inform ourselves and communicate results to our patients.