Reference Interval Estimation from Mixed Distributions using Truncation Points and the Kolmogorov-Smirnov Distance (kosmic)

Appropriate reference intervals are essential when using laboratory test results to guide medical decisions. Conventional approaches for the establishment of reference intervals rely on large samples from healthy and homogenous reference populations. However, this approach is associated with substantial financial and logistic challenges, subject to ethical restrictions in children, and limited in older individuals due to the high prevalence of chronic morbidities and medication. We implemented an indirect method for reference interval estimation, which uses mixed physiological and abnormal test results from clinical information systems, to overcome these restrictions. The algorithm minimizes the difference between an estimated parametrical distribution and a truncated part of the observed distribution, specifically, the Kolmogorov-Smirnov-distance between a hypothetical Gaussian distribution and the observed distribution of test results after Box-Cox-transformation. Simulations of common laboratory tests with increasing proportions of abnormal test results show reliable reference interval estimations even in challenging simulation scenarios, when <20% test results are abnormal. Additionally, reference intervals generated using samples from a university hospital’s laboratory information system, with a gradually increasing proportion of abnormal test results remained stable, even if samples from units with a substantial prevalence of pathologies were included. A high-performance open-source C++ implementation is available at https://gitlab.miracum.org/kosmic

Latent class distributional regression for the estimation of non-linear reference limits from contaminated data sources

Background Medical decision making based on quantitative test results depends on reliable reference intervals, which represent the range of physiological test results in a healthy population. Current methods for the estimation of reference limits focus either on modelling the age-dependent dynamics of different analytes directly in a prospective setting or the extraction of independent distributions from contaminated data sources, e.g. data with latent heterogeneity due to unlabeled pathologic cases. In this article, we propose a new method to estimate indirect reference limits with non-linear dependencies on covariates from contaminated datasets by combining the framework of mixture models and distributional regression. Results Simulation results based on mixtures of Gaussian and gamma distributions suggest accurate approximation of the true quantiles that improves with increasing sample size and decreasing overlap between the mixture components. Due to the high flexibility of the framework, initialization of the algorithm requires careful considerations regarding appropriate starting weights. Estimated quantiles from the extracted distribution of healthy hemoglobin concentration in boys and girls provide clinically useful pediatric reference limits similar to solutions obtained using different approaches which require more samples and are computationally more expensive. Conclusions Latent class distributional regression models represent the first method to estimate indirect non-linear reference limits from a single model fit, but the general scope of applications can be extended to other scenarios with latent heterogeneity

Mixture density networks for the indirect estimation of reference intervals

Background Reference intervals represent the expected range of physiological test results in a healthy population and are essential to support medical decision making. Particularly in the context of pediatric reference intervals, where recruitment regulations make prospective studies challenging to conduct, indirect estimation strategies are becoming increasingly important. Established indirect methods enable robust identification of the distribution of “healthy” samples from laboratory databases, which include unlabeled pathologic cases, but are currently severely limited when adjusting for essential patient characteristics such as age. Here, we propose the use of mixture density networks (MDN) to overcome this problem and model all parameters of the mixture distribution in a single step. Results Estimated reference intervals from varying settings with simulated data demonstrate the ability to accurately estimate latent distributions from unlabeled data using different implementations of MDNs. Comparing the performance with alternative estimation approaches further highlights the importance of modeling the mixture component weights as a function of the input in order to avoid biased estimates for all other parameters and the resulting reference intervals. We also provide a strategy to generate partially customized starting weights to improve proper identification of the latent components. Finally, the application on real-world hemoglobin samples provides results in line with current gold standard approaches, but also suggests further investigations with respect to adequate regularization strategies in order to prevent overfitting the data. Conclusions Mixture density networks provide a promising approach capable of extracting the distribution of healthy samples from unlabeled laboratory databases while simultaneously and explicitly estimating all parameters and component weights as non-linear functions of the covariate(s), thereby allowing the estimation of age-dependent reference intervals in a single step. Further studies on model regularization and asymmetric component distributions are warranted to consolidate our findings and expand the scope of applications

Imatinib treatment and longitudinal growth in pediatric patients with chronic myeloid leukemia: Influence of demographic, pharmacological, and genetic factors in the German CML-PAED cohort

In children and adolescents, impaired growth due to tyrosine kinase inhibitor therapy remains an insufficiently studied adverse effect. This study examines demographic, pharmacological, and genetic factors associated with impaired longitudinal growth in a uniform pediatric cohort treated with imatinib. We analyzed 94 pediatric patients with chronic myeloid leukemia (CML) diagnosed in the chronic phase and treated with imatinib for >12 months who participated in the Germany-wide CML-PAEDII study between February 2006 and February 2021. During imatinib treatment, significant height reduction occurred, with medians of -0.35 standard deviation score (SDS) at 12 months and -0.76 SDS at 24 months. Cumulative height SDS change (Δheight SDS) showed a more pronounced effect in prepubertal patients during the first year but were similar between prepubertal and pubertal subgroups by the second year (-0.55 vs. -0.50). From months 12 to 18 on imatinib, only 18% patients achieved individually longitudinal growth adequate to the growth standard (Δheight SDS≥0). When patients were divided into two subgroups based on median Δheight SDS (classifier Δheight SDS > or ≤-0.37) after one year on imatinib therapy, cohort 1 (Δheight SDS extending -0.37) showed younger age at diagnosis, a higher proportion of prepubertal children, but also better treatment response and higher imatinib serum levels. Exploring the association of growth parameters with pharmacokinetically relevant single nucleotide polymorphisms, known for affecting imatinib response, showed no correlation. This retrospective study provides new insights into imatinib-related growth impairment. We emphasize the importance of optimizing treatment strategies for pediatric patients to realize their maximum growth potential

Assessment of an application on a detoxification process of groundnut press cake for aflatoxins by ammoniation

12 p.-2 fig.-2 tab.Following a request from the European Commission, the EFSA Panel on Contaminants in the Food Chain (CONTAM) provided a scientific opinion on an application for a detoxification process of groundnut press cake for aflatoxins by ammoniation. Specifically, it is required that the feed decontamination process is compliant with the acceptability criteria specified in the Commission Regulation (EU) 2015/786 of 19 May 2015. The CONTAM Panel assessed the data provided by the feed business operator with respect to the efficacy of the process to remove the contaminant from groundnut press cake batches and on information demonstrating that the process does not adversely affect the characteristics and the nature of the product. Although according to the literature the process may be able to reduce aflatoxin levels below the legal limits, the Panel concluded that the proposed decontamination process, on the basis of the experimental data submitted by the feed business operator, cannot be confirmed for compliance with the acceptability criteria provided for in Commission Regulation (EU) 2015/786 of 19 May 2015. The Panel recommended sufficient sample testing before and after the process, under the selected conditions, to ensure that the process is reproducible and reliable and to demonstrate that the detoxification is not reversible. In addition, genotoxicity testing of extracts of the treated feedingstuff and of the identified degradation products would be necessary. Finally, information on the transfer rate of AFB1 to AFM1 excretion in milk for animals fed the ammoniated product, in comparison to the starting material and on the ammoniation process changes of the nutritional values of the feed material should be provided.The Panel wishes to thank Federico Cruciani and Carina Wenger for the support provided to this scientific output, and the hearing expert Professor Dr Wayne L Bryden, for the overview on aflatoxin inactivation by ammoniation.Peer reviewe

Assessment of a decontamination process for hydrocyanic acid in linseed intended for use in animal feed

Adopted: 19 September 2017Peer reviewedPublisher PD

Appropriateness to set a group health based guidance value for nivalenol and its modified forms

The Panel wishes to thank the members of the Working Group on HBGV for mycotoxins and their modified forms: Jan Alexander, Chiara Dall'Asta, Arno Gutleb, Manfred Metzler, Isabelle P Oswald and Dominique Parent‐Massin for the preparatory work on this scientific output, and the EFSA staff members: Marco Binaglia and Hans Steinkellner for the support provided to this scientific output. Adopted: 15 March 2017Peer reviewedPublisher PD

Assessment of a decontamination process for dioxins and dioxin‐like PCBs in fish oil by physical filtration with activated carbon

Adopted: 4 July 2017Peer reviewedPublisher PD