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Background The recent progress in medical research generates an increasing interest in the use of longitudinal biomarkers for characterizing the occurrence of an outcome. The present work is motivated by a study, where the objective was to explore the potential of the long pentraxin 3 (PTX3) as a prognostic marker of Acute Graft- versus -Host Disease (GvHD) after haematopoietic stem cell transplantation. Time-varying covariate Cox model was commonly used, despite its limiting assumptions that marker values are constant in time and measured without error. A joint model has been developed as a viable alternative; however, the approach is computationally intensive and requires additional strong assumptions, in which the impacts of their misspecification were not sufficiently studied. Methods We conduct an extensive simulation to clarify relevant assumptions for the understanding of joint models and assessment of its robustness under key model misspecifications. Further, we characterize the extent of bias introduced by the limiting assumptions of the time-varying covariate Cox model and compare its performance with a joint model in various contexts. We then present results of the two approaches to evaluate the potential of PTX3 as a prognostic marker of GvHD after haematopoietic stem cell transplantation. Results Overall, we illustrate that a joint model provides an unbiased estimate of the association between a longitudinal marker and the hazard of an event in the presence of measurement error, showing improvement over the time-varying Cox model. However, a joint model is severely biased when the baseline hazard or the shape of the longitudinal trajectories are misspecified. Both the Cox model and the joint model correctly specified indicated PTX3 as a potential prognostic marker of GvHD, with the joint model providing a higher hazard ratio estimate. Conclusions Joint models are beneficial to investigate the capability of the longitudinal marker to characterize time-to-event endpoint. However, the benefits are strictly linked to the correct specification of the longitudinal marker trajectory and the baseline hazard function, indicating a careful consideration of assumptions to avoid biased estimates.

PurposeWe aimed to verify the predictiveness of dorsal sural nerve neurophysiological monitoring in obtaining risk stratification for oxaliplatin-induced peripheral neurotoxicity (OXAPN).MethodsWe conducted a secondary analysis on a cohort of 110 colorectal cancer patients who were evaluated clinically and neurophysiologically before chemotherapy, at mid-treatment and at discontinuation. We applied the classification tree analysis method to predict the end-of-treatment OXAPN neurophysiological diagnosis, using data recorded at mid-treatment. We then ascertained the correlation between the obtained classes and neurological impairment at the end of treatment (Fisher’s exact test).ResultsDorsal sural nerve monitoring enabled us to stratify oxaliplatin-treated patients into risk classes with an implemented approach to neurophysiology application in this setting. Neurological outcome at discontinuation was predicted by neurophysiological monitoring performed during chemotherapy administration.ConclusionsWe demonstrated the role that neurophysiology may play in clinical trials as an early surrogate marker that can predict OXAPN development at the end of treatment. Specifically, we propose abnormal dorsal sural sensory nerve testing as an early biomarker in identifying patients at high risk of eventually developing OXAPN.

-rearranged acute lymphoblastic leukemia (ALL) in infants is an aggressive disease with 3-year event-free survival below 40%. Most relapses occur during treatment, with two thirds occurring within 1 year and 90% within 2 years after diagnosis. Outcomes have not improved in recent decades despite intensification of chemotherapy. We studied the safety and efficacy of blinatumomab, a bispecific T-cell engager molecule targeting CD19, in infants with -rearranged ALL. Thirty patients younger than 1 year of age with newly diagnosed -rearranged ALL were given the chemotherapy used in the Interfant-06 trial with the addition of one postinduction course of blinatumomab (15 μg per square meter of body-surface area per day; 28-day continuous infusion). The primary end point was clinically relevant toxic effects, defined as any toxic effect that was possibly or definitely attributable to blinatumomab and resulted in permanent discontinuation of blinatumomab or death. Minimal residual disease (MRD) was measured by polymerase chain reaction. Data on adverse events were collected. Outcome data were compared with historical control data from the Interfant-06 trial. The median follow-up was 26.3 months (range, 3.9 to 48.2). All 30 patients received the full course of blinatumomab. No toxic effects meeting the definition of the primary end point occurred. Ten serious adverse events were reported (fever [4 events], infection [4], hypertension [1], and vomiting [1]). The toxic-effects profile was consistent with that reported in older patients. A total of 28 patients (93%) either were MRD-negative (16 patients) or had low levels of MRD (<5×10 [i.e., <5 leukemic cells per 10,000 normal cells], 12 patients) after the blinatumomab infusion. All the patients who continued chemotherapy became MRD-negative during further treatment. Two-year disease-free survival was 81.6% in our study (95% confidence interval [CI], 60.8 to 92.0), as compared with 49.4% (95% CI, 42.5 to 56.0) in the Interfant-06 trial; the corresponding values for overall survival were 93.3% (95% CI, 75.9 to 98.3) and 65.8% (95% CI, 58.9 to 71.8). Blinatumomab added to Interfant-06 chemotherapy appeared to be safe and had a high level of efficacy in infants with newly diagnosed -rearranged ALL as compared with historical controls from the Interfant-06 trial. (Funded by the Princess Máxima Center Foundation and others; EudraCT number, 2016-004674-17.).

During the peak of hospitalizations of patients with severe Covid-19 in Italy and Spain in March, a group of researchers in these and other countries obtained and analyzed samples, resulting in the identification of two chromosomal loci associated with the disorder.

Time-to-event endpoints are central to evaluating treatment efficacy across disease areas. In clinical trials with time-to-event endpoints, the information available for interim and final analyses is largely determined by the number of observed events rather than by the number of enrolled patients. Interim monitoring therefore requires assessing how many additional events are expected to accrue by scheduled future analysis dates. Quantifying uncertainty around these counts is essential for assessing whether planned information levels are likely to be reached, anticipating delays or event overrunning, and supporting operational decisions while the trial is ongoing. This is especially relevant in pediatric oncology trials, where event accrual is often uncertain. Although methods for predicting time to endpoint maturation are well established, interval prediction for event counts at fixed calendar times remains less developed. We propose a patient-level framework for constructing such intervals at interim analyses of time-to-event trials. Conditionally on the interim data, the future count follows a Poisson--binomial law with patient-specific event probabilities; we estimate this law using a conditional parametric bootstrap. Under standard regularity conditions, the bootstrap is consistent and yields asymptotically calibrated prediction intervals. The framework accommodates staggered entry, patient-level covariates, administrative censoring, random loss to follow-up, and possible dependence between entry dates and loss to follow-up before conditioning on the realised interim data. We study its operating characteristics in simulation studies and illustrate it using a real-world phase III trial in childhood acute lymphoblastic leukaemia.

Time-to-event endpoints are central to evaluate treatment efficacy across many disease areas. Many trial protocols include interim analyses within group-sequential designs that control type I error via spending functions or boundary methods, with operating characteristics determined by the number of looks and the information accrued. Planning interim analyses with time-to-event endpoints is challenging because statistical information depends on the number of observed events, so adequate follow-up to accrue the required events is critical and interim prediction of information at scheduled looks and at the final analysis becomes essential. While several methods have been developed to predict the calendar time required to reach a target number of events, to the best of our knowledge there is no established framework that addresses the prediction of the number of events at a future date with corresponding prediction intervals. Starting from prediction interval approach originally developed in reliability engineering for the number of future component failures, we reformulated and extended it to the context of interim monitoring in clinical trials. This adaptation yields a general framework for event-count prediction intervals in the clinical setting, taking the patient as the unit of analysis and accommodating a range of parametric survival models, patient-level covariates, stagged entry and possible dependence between entry dates and loss to follow-up. Prediction intervals are obtained in a frequentist framework from a bootstrap estimator of the conditional distribution of future events. The performance of the proposed approach is investigated via simulation studies and illustrated by analyzing a real-world phase III trial in childhood acute lymphoblastic leukaemia.

Trials of imatinib have provided evidence of activity in adults with Philadelphia-chromosome-positive acute lymphoblastic leukaemia (ALL), but the drug's role when given with multidrug chemotherapy to children is unknown. This study assesses the safety and efficacy of oral imatinib in association with a Berlin–Frankfurt–Munster intensive chemotherapy regimen and allogeneic stem-cell transplantation for paediatric patients with Philadelphia-chromosome-positive ALL. Patients aged 1–18 years recruited to national trials of front-line treatment for ALL were eligible if they had t(9;22)(q34;q11). Patients with abnormal renal or hepatic function, or an active systemic infection, were ineligible. Patients were enrolled by ten study groups between 2004 and 2009, and were classified as good risk or poor risk according to early response to induction treatment. Good-risk patients were randomly assigned by a web-based system with permuted blocks (size four) to receive post-induction imatinib with chemotherapy or chemotherapy only in a 1:1 ratio, while all poor-risk patients received post-induction imatinib with chemotherapy. Patients were stratified by study group. The chemotherapy regimen was modelled on a Berlin–Frankfurt–Munster high-risk backbone; all received four post-induction blocks of chemotherapy after which they became eligible for stem-cell transplantation. The primary endpoints were disease-free survival at 4 years in the good-risk group and event-free survival at 4 years in the poor-risk group, analysed by intention to treat and a secondary analysis of patients as treated. The trial is registered with EudraCT (2004-001647-30) and ClinicalTrials.gov, number NCT00287105. Between Jan 1, 2004, and Dec 31, 2009, we screened 229 patients and enrolled 178: 108 were good risk and 70 poor risk. 46 good-risk patients were assigned to receive imatinib and 44 to receive no imatinib. Median follow-up was 3·1 years (IQR 2·0–4·6). 4-year disease-free survival was 72·9% (95% CI 56·1–84·1) in the good-risk, imatinib group versus 61·7% (45·0–74·7) in the good-risk, no imatinib group (p=0·24). The hazard ratio (HR) for failure, adjusted for minimal residual disease, was 0·63 (0·28–1·41; p=0·26). The as-treated analysis showed 4-year disease-free survival was 75·2% (61·0–84·9) for good-risk patients receiving imatinib and 55·9% (36·1–71·7) for those who did not receive imatinib (p=0·06). 4-year event-free survival for poor-risk patients was 53·5% (40·4–65·0). Serious adverse events were much the same in the good-risk groups, with infections caused by myelosuppression the most common. 16 patients in the good-risk imatinib group versus ten in the good-risk, no imatinib group (p=0·64), and 24 in the poor-risk group, had a serious adverse event. Our results suggests that imatinib in conjunction with intensive chemotherapy is well tolerated and might be beneficial for treatment of children with Philadelphia-chromosome-positive ALL. Projet Hospitalier de Recherche Clinique-Cancer (France), Fondazione Tettamanti-De Marchi and Associazione Italiana per la Ricerca sul Cancro (Italy), Novartis Germany, Cancer Research UK, Leukaemia Lymphoma Research, and Central Manchester University Hospitals Foundation Trust.

Acute lymphoblastic leukaemia in infants younger than 1 year is rare, and infants with the disease have worse outcomes than do older children. We initiated an international study to investigate the effects of a new hybrid treatment protocol with elements designed to treat both acute lymphoblastic leukaemia and acute myeloid leukaemia, and to identify any prognostic factors for outcome in infants. We also did a randomised trial to establish the value of a late intensification course. Patients aged 0–12 months were enrolled by 17 study groups in 22 countries between 1999 and 2005. Eligible patients were stratified for risk according to their peripheral blood response to a 7-day prednisone prophase, and then given a hybrid regimen based on the standard protocol for acute lymphoblastic leukaemia, with some elements designed for treatment of acute myeloid leukaemia. Before the maintenance phase, a subset of patients in complete remission were randomly assigned to receive either standard treatment or a more intensive chemotherapy course with high-dose cytarabine and methotrexate. The primary outcomes were event-free survival (EFS) for the initial cohort of patients and disease-free survival (DFS) for the patients randomly assigned to a treatment group. Data were analysed on an intention-to-treat basis. This trial was registered with ClinicalTrials.gov, number NCT 00015873, and at controlled-trials.com, number ISRCTN24251487. In the 482 enrolled patients who underwent hybrid treatment, 260 (58%) were in complete remission at a median follow-up of 38 (range 1–78) months, and EFS at 4 years was 47·0% (SE 2·6, 95% CI 41·9–52·1). Of 445 patients in complete remission after 5 weeks of induction treatment, 191 were randomised: 95 patients to receive a late intensification course, and 96 to a control group. At a median follow-up of 42 (range 1–73) months, 60 patients in the treatment group and 57 controls were disease-free. DFS at 4 years did not differ between the two groups (60·9% [SE 5·2] for treatment group vs 57·0% [5·5] for controls; p=0·81). During the intensification phase, of 71 patients randomly assigned to the treatment group, and for whom toxicity data were available, 35 (49%) had infections, 21 (30%) patients had mucositis, 22 (31%) patients had toxic effects on the liver, and 2 (3%) had neurotoxicity. All types of rearrangements in the (mixed lineage leukaemia) MLL gene, very high white blood cell count, age of younger than 6 months, and a poor response to the prednisone prophase were independently associated with inferior outcomes. Patients treated with our hybrid protocol, and especially those who responded poorly to prednisone, had higher EFS than most reported outcomes for treatment of infant ALL. Delayed intensification of chemotherapy did not benefit patients.

Pancreatic cancer (PC) remains one of the most challenging malignancies to treat. Current therapeutic options are unsatisfactory, and there is an urgent need for more effective and less toxic drugs to improve the dismal prognosis of PC. In recent years, drug repurposing (DR) has emerged as an attractive strategy to identify novel treatments for PC by leveraging existing drugs approved for other indications. Through the use of electronic medical records, Artificial Intelligence, study of metabolic pathways, signalling pathways, and many other approaches, it has become much easier in recent years to identify potential novel uses for old drugs. Although policy, funding and research attention in this area are steadily growing, major challenges to efficient and effective patient-centric DR in PC need to be addressed. These include but are not limited to regulatory, financial and funding barriers and the lack of coordination and collaboration among several sectors and stakeholders. To explore the opportunities and challenges associated with DR in PC, a one-day multi-stakeholder meeting was held on 14 of November 2023 in Brussels, Belgium as part of the REMEDi4ALL project. This meeting provided a platform for researchers, clinicians, industry representatives, funders, regulatory experts, and patient advocates to discuss and propose actions to optimize and accelerate DR in PC. Insights from this meeting support the potential of DR to enhance PC treatment options while highlighting the importance of systemic and supportive changes in the regulatory, policy and funding landscapes, interdisciplinary collaboration, data sharing, and patient involvement in driving therapeutic innovation. This summary highlights key outcomes and recommendations from the meeting in informing future efforts to advance DR initiatives in the context of PC.