Bayesian Federated Inference for Statistical Models

Identifying predictive factors via multivariable statistical analysis is for rare diseases often impossible because the data sets available are too small. Combining data from different medical centers into a single (larger) database would alleviate this problem, but is in practice challenging due to regulatory and logistic problems. Federated Learning (FL) is a machine learning approach that aims to construct from local inferences in separate data centers what would have been inferred had the data sets been merged. It seeks to harvest the statistical power of larger data sets without actually creating them. The FL strategy is not always feasible for small data sets. Therefore, in this paper we refine and implement an alternative Bayesian Federated Inference (BFI) framework for multi center data with the same aim as FL. The BFI framework is designed to cope with small data sets by inferring locally not only the optimal parameter values, but also additional features of the posterior parameter distribution, capturing information beyond that is used in FL. BFI has the additional benefit that a single inference cycle across the centers is sufficient, whereas FL needs multiple cycles. We quantify the performance of the proposed methodology on simulated and real life data.Comment: 19 pages, 3 figures, 4 table

Testing for association between RNA-Seq and high-dimensional data

Background: Testing for association between RNA-Seq and other genomic data is challenging due to high variability of the former and high dimensionality of the latter. Results: Using the negative binomial distribution and a random-effects model, we develop an omnibus test that overcomes both difficulties. It may be conceptualised as a test of overall significance in regression analysis, where the response variable is overdispersed and the number of explanatory variables exceeds the sample size. Conclusions: The proposed test can detect genetic and epigenetic alterations that affect gene expression. It can examine complex regulatory mechanisms of gene expression. The R package globalSeq is available from Bioconductor

Flexible modelling of risk factors on the incidence of pneumonia in young children in South Africa using piece-wise exponential additive mixed modelling

Introduction Recurrent episodes of pneumonia are frequently modeled using extensions of the Cox proportional hazards model with the underlying assumption of time-constant relative risks measured by the hazard ratio. We aim to relax this assumption in a study on the effect of factors on the evolution of pneumonia incidence over time based on data from a South African birth cohort study, the Drakenstein child health study. Methods We describe and apply two models: a time-constant and a time-varying relative effects model in a piece-wise exponential additive mixed model’s framework for recurrent events. A more complex model that fits in the same framework is applied to study the continuously measured seasonal effects. Results We find that several risk factors (male sex, preterm birth, low birthweight, lower socioeconomic status, lower maternal education and maternal cigarette smoking) have strong relative effects that are persistent across time. When time-varying effects are allowed in the model, HIV exposure status (HIV exposed & uninfected versus HIV unexposed) shows a strong relative effect for younger children, but this effect weakens as children grow older, with a null effect reached from about 15 months. Weight-for-length at birth shows a time increasing relative effect. We also find that children born in the summer have a much higher risk of pneumonia in the 3-to-8-month age period compared with children born in winter. Conclusion This work highlights the usefulness of flexible modelling tools in recurrent events models. It avoids stringent assumptions and allows estimation and visualization of absolute and relative risks over time of key factors associated with incidence of pneumonia in young children, providing new perspectives on the role of risk factors such HIV exposure

Sparse classification with paired covariates

Funder: Department of Epidemiology and Biostatistics, Amsterdam UMC, VU University AmsterdamAbstractThis paper introduces the paired lasso: a generalisation of the lasso for paired covariate settings. Our aim is to predict a single response from two high-dimensional covariate sets. We assume a one-to-one correspondence between the covariate sets, with each covariate in one set forming a pair with a covariate in the other set. Paired covariates arise, for example, when two transformations of the same data are available. It is often unknown which of the two covariate sets leads to better predictions, or whether the two covariate sets complement each other. The paired lasso addresses this problem by weighting the covariates to improve the selection from the covariate sets and the covariate pairs. It thereby combines information from both covariate sets and accounts for the paired structure. We tested the paired lasso on more than 2000 classification problems with experimental genomics data, and found that for estimating sparse but predictive models, the paired lasso outperforms the standard and the adaptive lasso. The R package is available from cran.</jats:p

Mutational spectrum and dynamics of clonal hematopoiesis in anemia of older individuals

Anemia is a major and currently poorly understood clinical manifestation of hematopoietic aging. Upon aging, hematopoietic clones harboring acquired leukemia-associated mutations expand and become detectable, now referred to as clonal hematopoiesis (CH). To investigate the relationship between CH and anemia of the elderly, we explored the landscape and dynamics of CH in older individuals with anemia. From the prospective, population-based Lifelines cohort (n = 167 729), we selected all individuals at least 60 years old who have anemia according to World Health Organization criteria (n = 676) and 1:1 matched control participants. Peripheral blood of 1298 individuals was analyzed for acquired mutations at a variant allele frequency (VAF) of 1% or higher in 27 driver genes. To track clonal evolution over time, we included all available follow-up samples (n = 943). CH was more frequently detected in individuals with anemia (46.6%) compared with control individuals (39.1%; P = .007). Although no differences were observed regarding commonly detected DTA mutations (DNMT3A, TET2, ASXL1) in individuals with anemia compared with control individuals, other mutations were enriched in the anemia cohort, including TP53 and SF3B1. Unlike individuals with nutrient deficiency (P = .84), individuals with anemia of chronic inflammation and unexplained anemia revealed a higher prevalence of CH (P = .035 and P = .017, respectively) compared with their matched control individuals. Follow-up analyses revealed that clones may expand and decline, generally showing only a subtle increase in VAF (mean, 0.56%) over the course of 44 months, irrespective of the presence of anemia. Specific mutations were associated with different growth rates and propensities to acquire an additional hit. In contrast to smaller clones (<5% VAF), which did not affect overall survival, larger clones were associated with increased risk for death

Excessive toxicity of cabozantinib in a phase II study in patients with recurrent and/or metastatic salivary gland cancer

AIM: Because the tyrosine kinases c-MET and vascular endothelial growth factor receptors (VEGFR) are often overexpressed in salivary gland cancer (SGC), this study evaluated the efficacy and safety of cabozantinib in patients with recurrent/metastatic (R/M) SGC. PATIENTS AND METHODS: A single-centre phase II study was conducted. Patients with immunohistochemical c-MET-positive R/M SGC were included in three cohorts: adenoid cystic carcinoma (ACC); salivary duct carcinoma (SDC) and other miscellaneous SGCs. No prior systemic treatments were required. Patients started cabozantinib 60 mg once daily. The primary outcome was the objective response rate (ORR). Secondary outcomes included survival, safety and quality of life. Per Simon-two-stage design, depending on efficacy, a maximum of 43 patients would be included. RESULTS: In total, 25 patients were included until premature closure owing to severe toxicity. Six patients (24%) had grade 3-5 wound complications, occurring at a median of 7.1 months on cabozantinib treatment (range 2.1-12.6). Remarkably, four of these six patients developed this complication in the area prior exposed to high-dose radiotherapy. Other grade ≥3 adverse events in >1 patient were hypertension (20%), diarrhoea (8%) and dehydration (8%). Twenty-one patients were evaluable for response; 1/15 ACC (ORR: 7%); 1/4 SDC and 0/2 patients with other miscellaneous SGC responded. Median progression-free survival was 9.4 months (95% confidence interval [CI] 7.4-11.4 months), 7.2 months (95%CI 0.0-15.1) and 6.9 months (95%CI 0.0-15.1), respectively. CONCLUSION: This study showed too many severe cabozantinib-associated wound complications in patients with SGC, especially in prior irradiated areas. Therefore, the study closed prematurely. The efficacy in the limited number of evaluable patients was low to moderate. TRIAL REGISTRATION: This trial was registered on ClinicalTrials.gov: NCT03729297

Exploring immune status in peripheral blood and tumor tissue in association with survival in patients with multi-organ metastatic colorectal cancer

Colorectal cancer (CRC) raises considerable clinical challenges, including a high mortality rate once the tumor spreads to distant sites. At this advanced stage, more accurate prediction of prognosis and treatment outcome is urgently needed. The role of cancer immunity in metastatic CRC (mCRC) is poorly understood. Here, we explore cellular immune cell status in patients with multi-organ mCRC. We analyzed T cell infiltration in primary tumor sections, surveyed the lymphocytic landscape of liver metastases, and assessed circulating mononuclear immune cells. Besides asking whether immune cells are associated with survival at this stage of the disease, we investigated correlations between the different tissue types; as this could indicate a dominant immune phenotype. Taken together, our analyses corroborate previous observations that higher levels of CD8+ T lymphocytes link to better survival outcomes. Our findings therefore extend evidence from earlier stages of CRC to indicate an important role for cancer immunity in disease control even after metastatic spreading to multiple organs. This finding may help to improve predicting outcome of patients with mCRC and suggests a future role for immunotherapeutic strategies.</p

Update to a randomized controlled trial of lutetium-177-PSMA in Oligo-metastatic hormone-sensitive prostate cancer:the BULLSEYE trial

Background: The BULLSEYE trial is a multicenter, open-label, randomized controlled trial to test the hypothesis if 177Lu-PSMA is an effective treatment in oligometastatic hormone-sensitive prostate cancer (oHSPC) to prolong the progression-free survival (PFS) and postpone the need for androgen deprivation therapy (ADT). The original study protocol was published in 2020. Here, we report amendments that have been made to the study protocol since the commencement of the trial. Changes in methods and materials: Two important changes were made to the original protocol: (1) the study will now use 177Lu-PSMA-617 instead of 177Lu-PSMA-I&T and (2) responding patients with residual disease on 18F-PSMA PET after the first two cycles are eligible to receive additional two cycles of 7.4 GBq 177Lu-PSMA in weeks 12 and 18, summing up to a maximum of 4 cycles if indicated. Therefore, patients receiving 177Lu-PSMA-617 will also receive an interim 18F-PSMA PET scan in week 4 after cycle 2. The title of this study was modified to; “Lutetium-177-PSMA in Oligo-metastatic Hormone Sensitive Prostate Cancer” and is now partly supported by Advanced Accelerator Applications, a Novartis Company. Conclusions: We present an update of the original study protocol prior to the completion of the study. Treatment arm patients that were included and received 177Lu-PSMA-I&T under the previous protocol will be replaced. Trial registration: ClinicalTrials.gov NCT04443062. First posted: June 23, 2020