Fludarabine, cytarabine, and idarubicin with or without venetoclax in patients with relapsed/refractory acute myeloid leukemia.

Treatment options for relapsed and refractory acute myeloid leukemia patients (R/R AML) are limited. This retrospective cohort study compares safety and efficacy of fludarabine, cytarabine, and idarubicin (FLA-IDA) without or with venetoclax (FLAVIDA) in patients with R/R AML. Thirty-seven and 81 patients received one course FLA-IDA with or without a 7-day course of venetoclax, respectively. The overall response rate (ORR) was significantly higher in FLAVIDA compared to FLAIDA- treated patients (78% vs. 47%; P=0.001), while measurable residual disease was negative at a similar proportion in responding patients (50% vs. 57%), respectively. Eighty-one percent and 79% of patients proceeded to allogeneic hematopoietic cell transplantation or donor lymphocyte infusion after FLAVIDA and FLA-IDA, respectively. Event-free and overall survival were similar in FLAVIDA- and FLA-IDA-treated patients. Refractory patients could be salvaged more successfully after FLA-IDA compared to FLAVIDA pretreatment. Neutrophil and platelet recovery times were similar in the venetoclax and the control group. In conclusion, short-term venetoclax in combination with FLA-IDA represents an effective treatment regimen in R/R AML identifying chemosensitive patients rapidly and inducing measurable residual disease-negative remission in a high proportion of R/R AML patients.

Statistical plasmode simulations-Potentials, challenges and recommendations.

Statistical data simulation is essential in the development of statistical models and methods as well as in their performance evaluation. To capture complex data structures, in particular for high-dimensional data, a variety of simulation approaches have been introduced including parametric and the so-called plasmode simulations. While there are concerns about the realism of parametrically simulated data, it is widely claimed that plasmodes come very close to reality with some aspects of the "truth" known. However, there are no explicit guidelines or state-of-the-art on how to perform plasmode data simulations. In the present paper, we first review existing literature and introduce the concept of statistical plasmode simulation. We then discuss advantages and challenges of statistical plasmodes and provide a step-wise procedure for their generation, including key steps to their implementation and reporting. Finally, we illustrate the concept of statistical plasmodes as well as the proposed plasmode generation procedure by means of a public real RNA data set on breast carcinoma patients.

Effect of empagliflozin on circulating proteomics in heart failure: mechanistic insights into the EMPEROR programme.

AIMS: Sodium-glucose co-transporter 2 (SGLT2) inhibitors improve cardiovascular outcomes in diverse patient populations, but their mechanism of action requires further study. The aim is to explore the effect of empagliflozin on the circulating levels of intracellular proteins in patients with heart failure, using large-scale proteomics. METHODS AND RESULTS: Over 1250 circulating proteins were measured at baseline, Week 12, and Week 52 in 1134 patients from EMPEROR-Reduced and EMPEROR-Preserved, using the Olink® Explore 1536 platform. Statistical and bioinformatical analyses identified differentially expressed proteins (empagliflozin vs. placebo), which were then linked to demonstrated biological actions in the heart and kidneys. At Week 12, 32 of 1283 proteins fulfilled our threshold for being differentially expressed, i.e. their levels were changed by ≥10% with a false discovery rate <1% (empagliflozin vs. placebo). Among these, nine proteins demonstrated the largest treatment effect of empagliflozin: insulin-like growth factor-binding protein 1, transferrin receptor protein 1, carbonic anhydrase 2, erythropoietin, protein-glutamine gamma-glutamyltransferase 2, thymosin beta-10, U-type mitochondrial creatine kinase, insulin-like growth factor-binding protein 4, and adipocyte fatty acid-binding protein 4. The changes of the proteins from baseline to Week 52 were generally concordant with the changes from the baseline to Week 12, except empagliflozin reduced levels of kidney injury molecule-1 by ≥10% at Week 52, but not at Week 12. The most common biological action of differentially expressed proteins appeared to be the promotion of autophagic flux in the heart, kidney or endothelium, a feature of 6 proteins. Other effects of differentially expressed proteins on the heart included the reduction of oxidative stress, inhibition of inflammation and fibrosis, and the enhancement of mitochondrial health and energy, repair, and regenerative capacity. The actions of differentially expressed proteins in the kidney involved promotion of autophagy, integrity and regeneration, suppression of renal inflammation and fibrosis, and modulation of renal tubular sodium reabsorption. CONCLUSIONS: Changes in circulating protein levels in patients with heart failure are consistent with the findings of experimental studies that have shown that the effects of SGLT2 inhibitors are likely related to actions on the heart and kidney to promote autophagic flux, nutrient deprivation signalling and transmembrane sodium transport.

Telomerase activation by genomic rearrangements in high-risk neuroblastoma.

Neuroblastoma is a malignant paediatric tumour of the sympathetic nervous system. Roughly half of these tumours regress spontaneously or are cured by limited therapy. By contrast, high-risk neuroblastomas have an unfavourable clinical course despite intensive multimodal treatment, and their molecular basis has remained largely elusive. Here we have performed whole-genome sequencing of 56 neuroblastomas (high-risk, n = 39; low-risk, n = 17) and discovered recurrent genomic rearrangements affecting a chromosomal region at 5p15.33 proximal of the telomerase reverse transcriptase gene (TERT). These rearrangements occurred only in high-risk neuroblastomas (12/39, 31%) in a mutually exclusive fashion with MYCN amplifications and ATRX mutations, which are known genetic events in this tumour type. In an extended case series (n = 217), TERT rearrangements defined a subgroup of high-risk tumours with particularly poor outcome. Despite a large structural diversity of these rearrangements, they all induced massive transcriptional upregulation of TERT. In the remaining high-risk tumours, TERT expression was also elevated in MYCN-amplified tumours, whereas alternative lengthening of telomeres was present in neuroblastomas without TERT or MYCN alterations, suggesting that telomere lengthening represents a central mechanism defining this subtype. The 5p15.33 rearrangements juxtapose the TERT coding sequence to strong enhancer elements, resulting in massive chromatin remodelling and DNA methylation of the affected region. Supporting a functional role of TERT, neuroblastoma cell lines bearing rearrangements or amplified MYCN exhibited both upregulated TERT expression and enzymatic telomerase activity. In summary, our findings show that remodelling of the genomic context abrogates transcriptional silencing of TERT in high-risk neuroblastoma and places telomerase activation in the centre of transformation in a large fraction of these tumours.

Marginal variable screening for survival endpoints.

When performing survival analysis in very high dimensions, it is often required to reduce the number of covariates using preliminary screening. During the last years, a large number of variable screening methods for the survival context have been developed. However, guidance is missing for choosing an appropriate method in practice. The aim of this work is to provide an overview of marginal variable screening methods for survival and develop recommendations for their use. For this purpose, a literature review is given, offering a comprehensive and structured introduction to the topic. In addition, a novel screening procedure based on distance correlation and martingale residuals is proposed, which is particularly useful in detecting nonmonotone associations. For evaluating the performance of the discussed approaches, a simulation study is conducted, comparing the true positive rates of competing variable screening methods in different settings. A real data example on mantle cell lymphoma is provided.

Prediction accuracy and variable selection for penalized cause-specific hazards models.

We consider modeling competing risks data in high dimensions using a penalized cause-specific hazards (CSHs) approach. CSHs have conceptual advantages that are useful for analyzing molecular data. First, working on hazards level can further understanding of the underlying biological mechanisms that drive transition hazards. Second, CSH models can be used to extend the multistate framework for high-dimensional data. The CSH approach is implemented by fitting separate proportional hazards models for each event type (iCS). In the high-dimensional setting, this might seem too complex and possibly prone to overfitting. Therefore, we consider an extension, namely "linking" the separate models by choosing penalty tuning parameters that in combination yield best prediction of the incidence of the event of interest (penCR). We investigate whether this extension is useful with respect to prediction accuracy and variable selection. The two approaches are compared to the subdistribution hazards (SDH) model, which is an established method that naturally achieves "linking" by working on incidence level, but loses interpretability of the covariate effects. Our simulation studies indicate that in many aspects, iCS is competitive to penCR and the SDH approach. There are some instances that speak in favor of linking the CSH models, for example, in the presence of opposing effects on the CSHs. We conclude that penalized CSH models are a viable solution for competing risks models in high dimensions. Linking the CSHs can be useful in some particular cases; however, simple models using separately penalized CSH are often justified.

Analysis of prognostic factors in patients with newly diagnosed diffuse large B-cell lymphoma and skeletal involvement.

BACKGROUND: Skeletal involvement (SI) is observed at low prevalence in patients with diffuse large B-cell lymphoma (DLBCL). Due to the rareness of this particular condition, prospective trials for these patients are scarce. METHODS: We analyzed clinical characteristics and outcome of 75 patients with DLBCL and SI in order to identify factors with prognostic impact towards progression-free survival (PFS) and overall survival (OS). RESULTS: Limited stage disease (Ann Arbor stage IE-IIE) was present in 34 patients (45%), 41 patients (55%) had advanced stage disease (Ann Arbor stage IIIE-IVE). Outcome was generally favorable for patients with DLBCL and SI with 3-year OS of 83%. The international prognostic index (IPI) was able to distinguish between different risk groups within this specific entity. Additionally, hypercalcemia showed to be a factor significantly associated with inferior survival. In regard to first-line treatment modalities, consolidative radiotherapy was positively associated with prolonged PFS and OS while intensification of chemotherapy had no significant impact. CONCLUSIONS: In our cohort of patients with DLBCL and SI, high-risk IPI as well as presence of hypercalcemia were associated with inferior outcome. Consolidative radiotherapy had a positive impact on survival.

p19-INK4d inhibits neuroblastoma cell growth, induces differentiation and is hypermethylated and downregulated in MYCN-amplified neuroblastomas.

Uncontrolled cell cycle entry, resulting from deregulated CDK-RB1-E2F pathway activity, is a crucial determinant of neuroblastoma cell malignancy. Here we identify neuroblastoma-suppressive functions of the p19-INK4d CDK inhibitor and uncover mechanisms of its repression in high-risk neuroblastomas. Reduced p19-INK4d expression was associated with poor event-free and overall survival and neuroblastoma risk factors including amplified MYCN in a set of 478 primary neuroblastomas. High MYCN expression repressed p19-INK4d mRNA and protein levels in different neuroblastoma cell models with conditional MYCN expression. MassARRAY and 450K methylation analyses of 105 primary neuroblastomas uncovered a differentially methylated region within p19-INK4d. Hypermethylation of this region was associated with reduced p19-INK4d expression. In accordance, p19-INK4d expression was activated upon treatment with the demethylating agent, 2'-deoxy-5-azacytidine, in neuroblastoma cell lines. Ectopic p19-INK4d expression decreased viability, clonogenicity and the capacity for anchorage-independent growth of neuroblastoma cells, and shifted the cell cycle towards the G1/0 phase. p19-INK4d also induced neurite-like processes and markers of neuronal differentiation. Moreover, neuroblastoma cell differentiation, induced by all-trans retinoic acid or NGF-NTRK1-signaling, activated p19-INK4d expression. Our findings pinpoint p19-INK4d as a neuroblastoma suppressor and provide evidence for MYCN-mediated repression and for epigenetic silencing of p19-INK4d by DNA hypermethylation in high-risk neuroblastomas.

Applying stability selection to consistently estimate sparse principal components in high-dimensional molecular data.

MOTIVATION: Principal component analysis (PCA) is a basic tool often used in bioinformatics for visualization and dimension reduction. However, it is known that PCA may not consistently estimate the true direction of maximal variability in high-dimensional, low sample size settings, which are typical for molecular data. Assuming that the underlying signal is sparse, i.e. that only a fraction of features contribute to a principal component (PC), this estimation consistency can be retained. Most existing sparse PCA methods use L1-penalization, i.e. the lasso, to perform feature selection. But, the lasso is known to lack variable selection consistency in high dimensions and therefore a subsequent interpretation of selected features can give misleading results. RESULTS: We present S4VDPCA, a sparse PCA method that incorporates a subsampling approach, namely stability selection. S4VDPCA can consistently select the truly relevant variables contributing to a sparse PC while also consistently estimate the direction of maximal variability. The performance of the S4VDPCA is assessed in a simulation study and compared to other PCA approaches, as well as to a hypothetical oracle PCA that 'knows' the truly relevant features in advance and thus finds optimal, unbiased sparse PCs. S4VDPCA is computationally efficient and performs best in simulations regarding parameter estimation consistency and feature selection consistency. Furthermore, S4VDPCA is applied to a publicly available gene expression data set of medulloblastoma brain tumors. Features contributing to the first two estimated sparse PCs represent genes significantly over-represented in pathways typically deregulated between molecular subgroups of medulloblastoma. AVAILABILITY AND IMPLEMENTATION: Software is available at https://github.com/mwsill/s4vdpca. CONTACT: m.sill@dkfz.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Nonidentical twins: Comparison of frequentist and Bayesian lasso for Cox models.

One important task in translational cancer research is the search for new prognostic biomarkers to improve survival prognosis for patients. The use of high-throughput technologies allows simultaneous measurement of genome-wide gene expression or other genomic data for all patients in a clinical trial. Penalized likelihood methods such as lasso regression can be applied to such high-dimensional data, where the number of (genomic) covariables is usually much larger than the sample size. There is a connection between the lasso and the Bayesian regression model with independent Laplace priors on the regression parameters, and understanding this connection has been useful for understanding the properties of lasso estimates in linear models (e.g. Park and Casella, 2008). In this paper, we study the lasso in the frequentist and Bayesian frameworks in the context of Cox models. For the Bayesian lasso we extend the approach by Lee et al. (2011). In particular, we impose the lasso penalty only on the genome features, but not on relevant clinical covariates, to allow the mandatory inclusion of important established factors. We investigate the models in high- and low-dimensional simulation settings and in an application to chronic lymphocytic leukemia.

Statistical challenges of high-dimensional methylation data.

With the fast growing field of epigenetics comes the need to better understand the intricacies of DNA methylation data analysis. High-throughput profiling using techniques, such as Illumina's BeadArray assay, enable the quantitative assessment of methylation. Challenges arise from the fact that resulting methylation levels (so-called beta values) are proportions between 0 and 1, often from an asymmetric, bimodal distribution with peaks close to 0 and 1. Therefore, the majority of standard statistical approaches do not apply. The logit transformation into so-called M-values is a common approach to circumvent this problem and aims to allow the use of common statistical methods. However, it can be observed that the transformation from beta to M-values does not necessarily result in an approximately homoscedastic distribution. Often, bimodality, asymmetry and heteroscedasticity are conserved even after transformation. We give an overview and discussion of methods suggested in the recent years that attempt to address the characteristics of methylation data in univariate screening settings. In order to identify 'differential' methylation with respect to covariates of interest while adjusting for confounders, we compare parametric methods, such as linear and beta regression, and nonparametric methods, such as rank-based regression. Our goal is to sensitise researchers to the challenges and issues that arise from this type of data as well as to present possible solutions.

Simulation study to evaluate when Plasmode simulation is superior to parametric simulation in estimating the mean squared error of the least squares estimator in linear regression.

Simulation is a crucial tool for the evaluation and comparison of statistical methods. How to design fair and neutral simulation studies is therefore of great interest for both researchers developing new methods and practitioners confronted with the choice of the most suitable method. The term simulation usually refers to parametric simulation, that is, computer experiments using artificial data made up of pseudo-random numbers. Plasmode simulation, that is, computer experiments using the combination of resampling feature data from a real-life dataset and generating the target variable with a known user-selected outcome-generating model, is an alternative that is often claimed to produce more realistic data. We compare parametric and Plasmode simulation for the example of estimating the mean squared error (MSE) of the least squares estimator (LSE) in linear regression. If the true underlying data-generating process (DGP) and the outcome-generating model (OGM) were known, parametric simulation would obviously be the best choice in terms of estimating the MSE well. However, in reality, both are usually unknown, so researchers have to make assumptions: in Plasmode simulation studies for the OGM, in parametric simulation for both DGP and OGM. Most likely, these assumptions do not exactly reflect the truth. Here, we aim to find out how assumptions deviating from the true DGP and the true OGM affect the performance of parametric and Plasmode simulations in the context of MSE estimation for the LSE and in which situations which simulation type is preferable. Our results suggest that the preferable simulation method depends on many factors, including the number of features, and on how and to what extent the assumptions of a parametric simulation differ from the true DGP. Also, the resampling strategy used for Plasmode influences the results. In particular, subsampling with a small sampling proportion can be recommended.

Neurologic Complications of the Central Nervous System after Allogeneic Stem Cell Transplantation: The Role of Transplantation-Associated Thrombotic Microangiopathy as a Potential Underreported Cause.

Neurologic complications (NCs), especially those of the central nervous system (CNS), represent a severe complication after allogeneic stem cell transplantation (allo-HSCT) and are associated with relevant morbidity and mortality. We aimed to characterize the potential risk factors for the development of CNS-NC, with a special focus on the role of calcineurin inhibitors (CNIs) as a predisposing factor. For this purpose, we compared cyclosporin A (CsA) versus tacrolimus (TAC) with respect to their influence on the incidence and type of CNS-NC after allo-HSCT. We retrospectively analyzed the incidence, risk factors, and impact on outcomes of CNS-NC diagnosed during the post-transplantation follow-up in patients with different high-risk hematologic malignancies who underwent allo-HSCT at our institution over a 20-year period. All patients included in the analysis received CNI (CsA or TAC) as graft-versus-host disease (GVHD) prophylaxis. We evaluated a total of 739 consecutive patients who underwent transplantation between December 1999 and April 2019. During a median follow-up of 6.8 years, we observed a CNS-NC incidence of 17%. The development of CNS-NC was associated with decreased overall survival (OS) and increased transplantation-related mortality (TRM). The most frequent CNS-NCs were infections (30%) and neurologic adverse events related to the administration of CNI, TAC, or CsA as GVHD prophylaxis (42%). In the multivariable analysis, age, total body irradiation (TBI), and severe acute GVHD and chronic GVHD were significant risk factors in the development of CNS-NCs. TAC compared with CsA emerged as an independent predisposing factor for CNS-NCs. The TAC-associated risk of CNS-NCs was related mostly to the occurrence of transplantation-associated thrombotic microangiopathy (TA-TMA) with neurologic manifestations (neuro-TA-TMA), although the general TA-TMA incidence was comparable in the 2 CNI subgroups. CNS-NCs are associated with poor prognosis after allo-HSCT, with TAC emerging as a potential yet insufficiently characterized predisposing factor.

Clinical impact of the genomic landscape and leukemogenic trajectories in non-intensively treated elderly acute myeloid leukemia patients.

To characterize the genomic landscape and leukemogenic pathways of older, newly diagnosed, non-intensively treated patients with AML and to study the clinical implications, comprehensive genetics analyses were performed including targeted DNA sequencing of 263 genes in 604 patients treated in a prospective Phase III clinical trial. Leukemic trajectories were delineated using oncogenetic tree modeling and hierarchical clustering, and prognostic groups were derived from multivariable Cox regression models. Clonal hematopoiesis-related genes (ASXL1, TET2, SRSF2, DNMT3A) were most frequently mutated. The oncogenetic modeling algorithm produced a tree with five branches with ASXL1, DDX41, DNMT3A, TET2, and TP53 emanating from the root suggesting leukemia-initiating events which gave rise to further subbranches with distinct subclones. Unsupervised clustering mirrored the genetic groups identified by the tree model. Multivariable analysis identified FLT3 internal tandem duplications (ITD), SRSF2, and TP53 mutations as poor prognostic factors, while DDX41 mutations exerted an exceptionally favorable effect. Subsequent backwards elimination based on the Akaike information criterion delineated three genetic risk groups: DDX41 mutations (favorable-risk), DDX41wildtype/FLT3-ITDneg/TP53wildtype (intermediate-risk), and FLT3-ITD or TP53 mutations (high-risk). Our data identified distinct trajectories of leukemia development in older AML patients and provide a basis for a clinically meaningful genetic outcome stratification for patients receiving less intensive therapies.

Risk factors and characteristics influencing humoral response to COVID-19 vaccination in patients after allogeneic stem cell transplantation.

Introduction: Vaccination against severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) is approved and recommended for immunocompromised patients such as patients after allogeneic stem cell transplantation (allo-SCT). Since infections represent a relevant cause of transplant related mortality we analyzed the advent of immunization to SARS-CoV-2 vaccination in a bicentric population of allogeneic transplanted patients. Methods: We retrospectively analyzed data of allo-SCT recipients in two German transplantation centers for safety and serologic response after two and three SARS-CoV-2 vaccinations. Patients received mRNA vaccines or vector-based vaccines. All patients were monitored for antibodies against SARS-CoV2-spike protein (anti-S-IgG) with an IgG ELISA assay or an EIA Assay after two and three doses of vaccination. Results: A total of 243 allo-SCT patients underwent SARS-CoV-2 vaccination. The median age was 59 years (range 22-81). While 85% of patients received two doses of mRNA vaccines, 10% had vector-based vaccines and 5% received a mixed vaccination. The two vaccine doses were well tolerated with only 3% patients developing a reactivation of graft versus host disease (GvHD). Overall, 72% of patients showed a humoral response after two vaccinations. In the multivariate analysis age at time of allo-SCT (p=0.0065), ongoing immunosuppressive therapy (p= 0.029) and lack of immune reconstitution (CD4-T-cell counts <200/µl, p< 0.001) were associated with no response. Sex, intensity of conditioning and the use of ATG showed no influence on seroconversion. Finally, 44 out of 69 patients that did not respond after the second dose received a booster and 57% (25/44) showed a seroconversion. Discussion: We showed in our bicentric allo-SCT patient cohort, that a humoral response could be achieve after the regular approved schedule, especially for those patients who underwent immune reconstitution and were free from immunosuppressive drugs. In over 50% of the initial non-responders after 2-dose vaccination, a seroconversion can be achieved by boostering with a third dose.

Intensive chemotherapy with or without gemtuzumab ozogamicin in patients with NPM1-mutated acute myeloid leukaemia (AMLSG 09-09): a randomised, open-label, multicentre, phase 3 trial.

BACKGROUND: Acute myeloid leukaemia with mutated NPM1 is associated with high CD33 expression and intermediate-risk cytogenetics. The aim of this study was to evaluate intensive chemotherapy with or without the anti-CD33 antibody-drug conjugate gemtuzumab ozogamicin in participants with newly diagnosed, NPM1-mutated acute myeloid leukaemia. METHODS: This open-label, phase 3 trial was conducted at 56 hospitals in Germany and Austria. Eligible participants were 18 years or older and had newly diagnosed NPM1-mutated acute myeloid leukaemia and an Eastern Cooperative Oncology Group performance status of 0-2. Participants were randomly assigned, using age as a stratification factor (18-60 years vs >60 years), 1:1 to the two treatment groups using allocation concealment; there was no masking of participants and investigators to treatment groups. Participants received two cycles of induction therapy (idarubicin, cytarabine, and etoposide) plus all-trans retinoic acid (ATRA) followed by three consolidation cycles of high-dose cytarabine (or an intermediate dose for those older than 60 years) and ATRA, without or with gemtuzumab ozogamicin (3 mg/m2 administered intravenously on day 1 of induction cycles 1 and 2, and consolidation cycle 1). The primary endpoints were short-term event-free survival and overall survival in the intention-to-treat population (overall survival was added as a co-primary endpoint after amendment four of the protocol on Oct 13, 2013). The secondary endpoints were event-free survival with long-term follow-up, rates of complete remission, complete remission with partial haematological recovery (CRh), and complete remission with incomplete haematological recovery (CRi), cumulative incidences of relapse and death, and number of days in hospital. This trial is registered with ClinicalTrials.gov (NCT00893399) and has been completed. FINDINGS: Between May 12, 2010, and Sept 1, 2017, 600 participants were enrolled, of which 588 (315 women and 273 men) were randomly assigned (296 to the standard group and 292 to the gemtuzumab ozogamicin group). No difference was found in short-term event-free survival (short-term event-free survival at 6-month follow-up, 53% [95% CI 47-59] in the standard group and 58% [53-64] in the gemtuzumab ozogamicin group; hazard ratio [HR] 0·83; 95% CI 0·65-1·04; p=0·10) and overall survival between treatment groups (2-year overall survival, 69% [63-74] in the standard group and 73% [68-78] in the gemtuzumab ozogamicin group; 0·90; 0·70-1·16; p=0·43). There was no difference in complete remission or CRi rates (n=267 [90%] in the standard group vs n=251 [86%] in the gemtuzumab ozogamicin group; odds ratio [OR] 0·67; 95% CI 0·40-1·11; p=0·15) and complete remission or CRh rates (n=214 [72%] vs n=195 [67%]; OR 0·77; 0·54-1·10; p=0·18), whereas the complete remission rate was lower with gemtuzumab ozogamicin (n=172 [58%] vs n=136 [47%]; OR 0·63; 0·45-0·80; p=0·0068). Cumulative incidence of relapse was significantly reduced by gemtuzumab ozogamicin (2-year cumulative incidence of relapse, 37% [95% CI 31-43] in the standard group and 25% [20-30] in the gemtuzumab ozogamicin group; cause-specific HR 0·65; 0·49-0·86; p=0·0028), and there was no difference in the cumulative incidence of death (2-year cumulative incidence of death 6% [4-10] in the standard group and 7% [5-11] in the gemtuzumab ozogamicin group; HR 1·03; 0·59-1·81; p=0·91). There were no differences in the number of days in hospital across all cycles between treatment groups. The most common treatment-related grade 3-4 adverse events were febrile neutropenia (n=135 [47%] in the gemtuzumab ozogamicin group vs n=122 [41%] in the standard group), thrombocytopenia (n=261 [90%] vs n=265 [90%]), pneumonia (n=71 [25%] vs n=64 [22%]), sepsis (n=85 [29%] vs n=73 [25%]). Treatment-related deaths were documented in 25 participants (4%; n=8 [3%] in the standard group and n=17 [6%] in the gemtuzumab ozogamicin group), mostly due to sepsis and infections. INTERPRETATION: The primary endpoints of the trial of event-free survival and overall survival were not met. However, an anti-leukaemic efficacy of gemtuzumab ozogamicin in participants with NPM1-mutated acute myeloid leukaemia is shown by a significantly lower cumulative incidence of relapse rate, suggesting that the addition of gemtuzumab ozogamicin might reduce the need for salvage therapy in these participants. The results from this study provide further evidence that gemtuzumab ozogamicin should be added in the standard of care treatment in adults with NPM1-mutated acute myeloid leukaemia. FUNDING: Pfizer and Amgen.

Genomic landscape of patients with FLT3-mutated acute myeloid leukemia (AML) treated within the CALGB 10603/RATIFY trial.

The aim of this study was to characterize the mutational landscape of patients with FLT3-mutated acute myeloid leukemia (AML) treated within the randomized CALGB 10603/RATIFY trial evaluating intensive chemotherapy plus the multi-kinase inhibitor midostaurin versus placebo. We performed sequencing of 262 genes in 475 patients: mutations occurring concurrently with the FLT3-mutation were most frequent in NPM1 (61%), DNMT3A (39%), WT1 (21%), TET2 (12%), NRAS (11%), RUNX1 (11%), PTPN11 (10%), and ASXL1 (8%) genes. To assess effects of clinical and genetic features and their possible interactions, we fitted random survival forests and interpreted the resulting variable importance. Highest prognostic impact was found for WT1 and NPM1 mutations, followed by white blood cell count, FLT3 mutation type (internal tandem duplications vs. tyrosine kinase domain mutations), treatment (midostaurin vs. placebo), ASXL1 mutation, and ECOG performance status. When evaluating two-fold variable combinations the most striking effects were found for WT1:NPM1 (with NPM1 mutation abrogating the negative effect of WT1 mutation), and for WT1:treatment (with midostaurin exerting a beneficial effect in WT1-mutated AML). This targeted gene sequencing study provides important, novel insights into the genomic background of FLT3-mutated AML including the prognostic impact of co-mutations, specific gene-gene interactions, and possible treatment effects of midostaurin.

Midostaurin plus intensive chemotherapy for younger and older patients with AML and FLT3 internal tandem duplications.

We conducted a single-arm, phase 2 trial (German-Austrian Acute Myeloid Leukemia Study Group [AMLSG] 16-10) to evaluate midostaurin with intensive chemotherapy followed by allogeneic hematopoietic-cell transplantation (HCT) and a 1-year midosta urin maintenance therapy in adult patients with acute myeloid leukemia (AML) and fms-related tyrosine kinase 3 (FLT3) internal tandem duplication (ITD). Patients 18 to 70 years of age with newly diagnosed FLT3-ITD-positive AML were eligible. Primary and key secondary endpoints were event-free survival (EFS) and overall survival (OS). Results were compared with a historical cohort of 415 patients treated on 5 prior AMLSG trials; statistical analysis was performed using a double-robust adjustment with propensity score weighting and covariate adjustment. Results were also compared with patients (18-59 years) treated on the placebo arm of the Cancer and Leukemia Group B (CALGB) 10603/RATIFY trial. The trial accrued 440 patients (18-60 years, n = 312; 61-70 years, n = 128). In multivariate analysis, EFS was significantly in favor of patients treated within the AMLSG 16-10 trial compared with the AMLSG control (hazard ratio [HR], 0.55; P < .001); both in younger (HR, 0.59; P < .001) and older patients (HR, 0.42; P < .001). Multivariate analysis also showed a significant beneficial effect on OS compared with the AMLSG control (HR, 0.57; P < .001) as well as to the CALGB 10603/RATIFY trial (HR, 0.71; P = .005). The treatment effect of midostaurin remained significant in sensitivity analysis including allogeneic HCT as a time-dependent covariate. Addition of midostaurin to chemotherapy was safe in younger and older patients. In comparison with historical controls, the addition of midostaurin to intensive therapy led to a significant improvement in outcome in younger and older patients with AML and FLT3-ITD. This trial is registered at clinicaltrialsregistry.eu as Eudra-CT number 2011-003168-63 and at clinicaltrials.gov as NCT01477606.

A global test for competing risks survival analysis.

Standard tests for the Cox model, such as the likelihood ratio test or the Wald test, do not perform well in situations, where the number of covariates is substantially higher than the number of observed events. This issue is perpetuated in competing risks settings, where the number of observed occurrences for each event type is usually rather small. Yet, appropriate testing methodology for competing risks survival analysis with few events per variable is missing. In this article, we show how to extend the global test for survival by Goeman et al. to competing risks and multistate models[Per journal style, abstracts should not have reference citations. Therefore, can you kindly delete this reference citation.]. Conducting detailed simulation studies, we show that both for type I error control and for power, the novel test outperforms the likelihood ratio test and the Wald test based on the cause-specific hazards model in settings where the number of events is small compared to the number of covariates. The benefit of the global tests for competing risks survival analysis and multistate models is further demonstrated in real data examples of cancer patients from the European Society for Blood and Marrow Transplantation.