Publications by authors named "Tomasz Burzykowski"

115 Publications

Status of the alveolar bone after autotransplantation of developing premolars to the anterior maxilla assessed by CBCT measurements.

Dent Traumatol 2021 May 4. Epub 2021 May 4.

Department of Orthodontics, Faculty of Dentistry, Medical University of Warsaw, Warszawa, Poland.

Background/aims: Autotransplantation of developing premolars is an established treatment to replace missing teeth in the anterior maxilla in growing patients with a reported success rate of over 90%. The normal shape of the alveolus is observed after transplantation, but data on the presence and amount of alveolar bone after healing has not been previously reported. The aim of this study was to look for potential differences in alveolar bone dimensions between sites where autotransplanted premolars replaced missing incisors and control sites of contralateral incisors.

Material/methods: There were 11 patients aged between 10 and 12 years five months (mean age: 10 years and 7 months) who underwent autotransplantation of a premolar to replace a central incisor. Cone Beam Computed Tomography (CBCT) performed at least 1 year after transplantation served to evaluate bone at sites of autotransplanted premolars and controls (contralateral maxillary central incisor). The thickness of the labial bone, plus the height and width of the alveolar process were measured on scans and compared at transplant and control sites.

Results: Mean thicknesses of the labial bone at the transplant and control sites were 0.78 mm and 0.82 mm respectively. Mean alveolar bone height was 15.15 mm at the transplant sites and 15.12 mm at the control sites. The mean marginal thickness of the alveolus was 7.75 mm at the transplant sites and 7.98 mm at the control sites. Mean thicknesses of the alveolus for half of its vertical dimension at the transplant and control sites were 7.54 mm and 8.03 mm, respectively.

Conclusion: The mean values of bone thickness, width and height of the alveolar process at sites of transplanted premolars were comparable to the mean values for the control incisors. Successful autotransplantation of developing premolars to replace missing central incisors allowed preservation of alveolar bone in the anterior maxilla.
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http://dx.doi.org/10.1111/edt.12680DOI Listing
May 2021

Unbiasedness and efficiency of non-parametric and UMVUE estimators of the probabilistic index and related statistics.

Stat Methods Med Res 2021 Mar 1;30(3):747-768. Epub 2020 Dec 1.

Data Science Institute (DSI), Interuniversity Institute for Biostatistics and statistical Bioinformatics (I-BioStat), Hasselt University, Hasselt, Belgium.

In reliability theory, diagnostic accuracy, and clinical trials, the quantity , also known as the Probabilistic Index (PI), is a common treatment effect measure when comparing two groups of observations. The quantity , a linear transformation of PI known as the net benefit, has also been advocated as an intuitively appealing treatment effect measure. Parametric estimation of PI has received a lot of attention in the past 40 years, with the formulation of the Uniformly Minimum-Variance Unbiased Estimator (UMVUE) for many distributions. However, the non-parametric Mann-Whitney estimator of the PI is also known to be UMVUE in some situations. To understand this seeming contradiction, in this paper a systematic comparison is performed between the non-parametric estimator for the PI and parametric UMVUE estimators in various settings. We show that the Mann-Whitney estimator is always an unbiased estimator of the PI with univariate, completely observed data, while the parametric UMVUE is not when the distribution is misspecified. Additionally, the Mann-Whitney estimator is the UMVUE when observations belong to an unrestricted family. When observations come from a more restrictive family of distributions, the loss in efficiency for the non-parametric estimator is limited in realistic clinical scenarios. In conclusion, the Mann-Whitney estimator is simple to use and is a reliable estimator for the PI and net benefit in realistic clinical scenarios.
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http://dx.doi.org/10.1177/0962280220966629DOI Listing
March 2021

Bayesian biomarker-driven outcome-adaptive randomization with an imperfect biomarker assay.

Clin Trials 2021 Apr 24;18(2):137-146. Epub 2020 Nov 24.

I-BioStat, Hasselt University, Diepenbeek, Belgium.

Objective: We investigate the impact of biomarker assay's accuracy on the operating characteristics of a Bayesian biomarker-driven outcome-adaptive randomization design.

Methods: In a simulation study, we assume a trial with two treatments, two biomarker-based strata, and a binary clinical outcome (response). denotes the probability of response for treatment ( = 0 or 1) in biomarker stratum ( = 0 or 1). Four different scenarios in terms of true underlying response probabilities are considered: a null ( = = 0.25, = = 0.25) and consistent ( = = 0.25, = 0.5) treatment effect scenario, as well as a quantitative ( = = = 0.25, = 0.5) and a qualitative ( = = 0.5, = = 0.25) stratum-treatment interaction. For each scenario, we compare the case of a perfect with the case of an imperfect biomarker assay with sensitivity and specificity of 0.8 and 0.7, respectively. In addition, biomarker-positive prevalence values ( = 1) = 0.2 and 0.5 are investigated.

Results: Results show that the use of an imperfect assay affects the operational characteristics of the Bayesian biomarker-based outcome-adaptive randomization design. In particular, the misclassification causes a substantial reduction in power accompanied by a considerable increase in the type-I error probability. The magnitude of these effects depends on the sensitivity and specificity of the assay, as well as on the distribution of the biomarker in the patient population.

Conclusion: With an imperfect biomarker assay, the decision to apply a biomarker-based outcome-adaptive randomization design may require careful reflection.
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http://dx.doi.org/10.1177/1740774520964202DOI Listing
April 2021

A "Refined Hydrogen Rule" and a "Refined Hydrogen and Halogen Rule" for Organic Molecules.

J Am Soc Mass Spectrom 2020 Jan 21;31(1):132-136. Epub 2019 Nov 21.

I-BioStat, Data Science Institute, Hasselt University, Hasselt, Belgium.

Deriving chemical formulas of organic molecules, based on spectral information, with heuristic rules is a commonly recurring task. The computational effort and the potentially extensive list of candidate formulas put a strain on the downstream analysis. In this paper, we introduce a set of redefined heuristics based on the hydrogen and halogen rules that reduce the computational burden and the number of candidate formulas for organic molecules, such as peptides and lipids.
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http://dx.doi.org/10.1021/jasms.9b00064DOI Listing
January 2020

A Conceptual Framework for Abundance Estimation of Genomic Targets in the Presence of Ambiguous Short Sequencing Reads.

J Comput Biol 2020 08 31;27(8):1232-1247. Epub 2019 Dec 31.

Interuniversity Institute for Biostatistics and statistical Bioinformatics, Hasselt University, Diepenbeek, Belgium.

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http://dx.doi.org/10.1089/cmb.2019.0272DOI Listing
August 2020

The (generalized) hydrogen rule for organic molecules.

J Mass Spectrom 2020 Mar 27;55(3):e4485. Epub 2019 Dec 27.

I-BioStat, Data Science Institute, Hasselt University, Hasselt, Belgium.

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http://dx.doi.org/10.1002/jms.4485DOI Listing
March 2020

Visualizing the agreement of peptide assignments between different search engines.

J Mass Spectrom 2020 Aug 3;55(8):e4471. Epub 2019 Dec 3.

Interuniversity Institute of Biostatistics and Statistical Bioinformatics, Hasselt University, Hasselt, Belgium.

There is a trend in the analysis of shotgun proteomics data that aims to combine information from multiple search engines to increase the number of peptide annotations in an experiment. Typically, the degree of search engine complementarity and search engine agreement is visually illustrated by means of Venn diagrams that present the findings of a database search on the level of the nonredundant peptide annotations. We argue this practice to be not fit-for-purpose since the diagrams do not take into account and often conceal the information on complementarity and agreement at the level of the spectrum identification. We promote a new type of visualization that provides insight on the peptide sequence agreement at the level of the peptide-spectrum match (PSM) as a measure of consensus between two search engines with nominal outcomes. We applied the visualizations and percentage sequence agreement to an in-house data set of our benchmark organism, Caenorhabditis elegans, and illustrated that when assessing the agreement between search engine, one should disentangle the notion of PSM confidence and PSM identity. The visualizations presented in this manuscript provide a more informative assessment of pairs of search engines and are made available as an R function in the Supporting Information.
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http://dx.doi.org/10.1002/jms.4471DOI Listing
August 2020

Evaluation of Continuous Tumor-Size-Based End Points as Surrogates for Overall Survival in Randomized Clinical Trials in Metastatic Colorectal Cancer.

JAMA Netw Open 2019 09 4;2(9):e1911750. Epub 2019 Sep 4.

Hasselt University, Diepenbeek, Belgium.

Importance: Tumor measurements can be used to estimate time to nadir and depth of nadir as potential surrogates for overall survival (OS).

Objective: To assess time to nadir and depth of nadir as surrogates for OS in metastatic colorectal cancer.

Design, Setting, And Participants: Pooled analysis of 20 randomized clinical trials within the Aide et Recherche en Cancerologie Digestive database, which contains academic and industry-sponsored trials, was conducted. Three sets of comparisons were performed: chemotherapy alone, antiangiogenic agents, and anti-epidermal growth factor receptor agents in first-line treatment for patients with metastatic colorectal cancer.

Main Outcomes And Measures: Surrogacy of time to nadir and depth of nadir was assessed at the trial level based on joint modeling of relative tumor-size change vs baseline and OS. Treatment effects on time to nadir and on depth of nadir were defined in terms of between-arm differences in time to nadir and in depth of nadir, and both were assessed in linear regressions for their correlation with treatment effects (hazard ratios) on OS within each set. The strengths of association were quantified using sample-size-weighted coefficients of determination (R2), with values closer to 1.00 indicating stronger association. At the patient level, the correlation was assessed between modeled relative tumor-size change and OS.

Results: For 14 chemotherapy comparisons in 4289 patients, the R2 value was 0.63 (95% CI, 0.30-0.96) for the association between treatment effects on time to nadir and OS and 0.08 (95% CI, 0-0.37) for depth of nadir and OS. For 11 antiangiogenic agent comparisons (4854 patients), corresponding values of R2 were 0.25 (95% CI, 0-0.72) and 0.06 (95% CI, 0-0.35). For 8 anti-epidermal growth factor receptor comparisons (2684 patients), corresponding values of R2 were 0.24 (95% CI, 0-0.83) and 0.21 (95% CI, 0-0.78).

Conclusions And Relevance: In contrast with early reports favoring depth of response as a surrogate, these results suggest that neither time to nadir nor depth of nadir is an acceptable surrogate for OS in the first-line treatment of metastatic colorectal cancer.
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http://dx.doi.org/10.1001/jamanetworkopen.2019.11750DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6755539PMC
September 2019

Detection of atypical data in multicenter clinical trials using unsupervised statistical monitoring.

Clin Trials 2019 10 23;16(5):512-522. Epub 2019 Jul 23.

Department of Biostatistics, The University of Tokyo, Tokyo, Japan.

Background/aims: A risk-based approach to clinical research may include a central statistical assessment of data quality. We investigated the operating characteristics of unsupervised statistical monitoring aimed at detecting atypical data in multicenter experiments. The approach is premised on the assumption that, save for random fluctuations and natural variations, data coming from all centers should be comparable and statistically consistent. Unsupervised statistical monitoring consists of performing as many statistical tests as possible on all trial data, in order to detect centers whose data are inconsistent with data from other centers.

Methods: We conducted simulations using data from a large multicenter trial conducted in Japan for patients with advanced gastric cancer. The actual trial data were contaminated in computer simulations for varying percentages of centers, percentages of patients modified within each center and numbers and types of modified variables. The unsupervised statistical monitoring software was run by a blinded team on the contaminated data sets, with the purpose of detecting the centers with contaminated data. The operating characteristics (sensitivity, specificity and Youden's J-index) were calculated for three detection methods: one using the -values of individual statistical tests after adjustment for multiplicity, one using a summary of all -values for a given center, called the Data Inconsistency Score, and one using both of these methods.

Results: The operating characteristics of the three methods were satisfactory in situations of data contamination likely to occur in practice, specifically when a single or a few centers were contaminated. As expected, the sensitivity increased for increasing proportions of patients and increasing numbers of variables contaminated. The three methods showed a specificity better than 93% in all scenarios of contamination. The method based on the Data Inconsistency Score and individual -values adjusted for multiplicity generally had slightly higher sensitivity at the expense of a slightly lower specificity.

Conclusions: The use of brute force (a computer-intensive approach that generates large numbers of statistical tests) is an effective way to check data quality in multicenter clinical trials. It can provide a cost-effective complement to other data-management and monitoring techniques.
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http://dx.doi.org/10.1177/1740774519862564DOI Listing
October 2019

A Multivariate Negative-Binomial Model with Random Effects for Differential Gene-Expression Analysis of Correlated mRNA Sequencing Data.

J Comput Biol 2019 12 17;26(12):1339-1348. Epub 2019 Jul 17.

Interuniversity Institute for Biostatistics and statistical Bioinformatics, Hasselt University, Diepenbeek, Belgium.

Experimental designs such as matched-pair or longitudinal studies yield mRNA sequencing (mRNA-Seq) counts that are correlated across samples. Most of the approaches for the analysis of correlated mRNA-Seq data are restricted to a specific design and/or balanced data only (with the same number of samples in each group). We propose a model that is applicable to the analysis of correlated mRNA-Seq data of different types: paired, clustered, longitudinal, or others. Any combination of explanatory variables, as well as unbalanced data, can be processed within the proposed modeling framework. The model assumes that exon counts of a particular gene of an individual sample jointly follow a multivariate negative-binomial distribution. Additional correlation between exon counts obtained for, for example, individual samples within the same pair or cluster, is taken into account by including into the model a cluster-level normally distributed random effect. An interesting feature of the model is that it provides explicit expression for marginal correlation between exon counts at different levels. The performance of the model is evaluated by using a simulation study and an analysis of two real-life data sets: a paired mRNA-Seq experiment for 24 patients with clear-cell renal-cell carcinoma and a longitudinal mRNA-Seq experiment for 29 patients with Lyme disease.
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http://dx.doi.org/10.1089/cmb.2019.0168DOI Listing
December 2019

Chronological Trends in Progression-Free, Overall, and Post-Progression Survival in First-Line Therapy for Advanced NSCLC.

J Thorac Oncol 2019 09 1;14(9):1619-1627. Epub 2019 Jun 1.

Medical University of Gdańsk, Gdańsk, Poland. Electronic address:

Background: There is a debate about the merits of progression-free survival (PFS) versus overall survival (OS) as primary endpoints in NSCLC. It has been postulated that post-progression therapy may influence OS in both arms. To investigate this issue, we analyzed chronological trends in PFS and OS in advanced NSCLC using restricted mean survival times (RMSTs).

Methods: We digitized survival curves from first-line phase III trials published between 1998 and 2015 in 13 leading journals to compute RMSTs for PFS and OS at three truncation landmarks (5, 12, and 18 months).

Results: Among the 161 trials identified, RMSTs could be computed for both endpoints in 102, 97, and 82 trials for the 5-, 12-, and 18-month truncation landmarks, respectively. Post-progression survival in the control arm, quantified as mean OS minus mean PFS truncated at 18 months, was on average 3.3 months between 1998 and 2003, 4.4 months between 2004 and 2009, and 5.4 months between 2010 and 2015. This increase was due to increasing RMST for OS over time, with no increase in RMST for PFS. The average within-trial difference in RMSTs between experimental and control arm was close to 0 for OS and less than 1 month for PFS.

Conclusions: There is a progressive increase in post-progression survival in NSCLC trials, likely from salvage therapy. These results question both PFS and OS as sensitive endpoints in first-line trials, but suggest that the outlook for patients is improving regardless of within-trial gains.
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http://dx.doi.org/10.1016/j.jtho.2019.05.030DOI Listing
September 2019

De novo prediction of the elemental composition of peptides and proteins based on a single mass.

J Mass Spectrom 2020 Aug 13;55(8):e4367. Epub 2019 Aug 13.

I-BioStat, Hasselt University, Hasselt, Belgium.

Identification of peptides and proteins is a common task in mass spectrometry-based proteomics but often fails to deliver a comprehensive list of identifications. Downstream analysis, quantitative or qualitative, depends on the outcome of this process. Despite continuous improvement of computational methods, a large fraction of the screened peptides and/or proteins remains unidentified. We introduce here pacMASS, a method that de novo predicts the elemental composition of peptides and small proteins based on a single accurate mass, ie, the observed monoisotopic or average mass. This novel approach returns in a fast and memory efficient manner a limited number of elemental compositions per queried peptide or protein.
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http://dx.doi.org/10.1002/jms.4367DOI Listing
August 2020

Experimental Design in Quantitative Proteomics.

Methods Mol Biol 2019 ;1977:181-197

I-BioStat, Hasselt University, Diepenbeek, Belgium.

Metabolites and proteins are potential biomarkers. They can be identified with the help of mass spectrometry (MS). However, measurements obtained by using MS are prone to various random and systematic errors. The sensitivity of the technology to the errors poses practical challenges, including concerns about reproducibility of the MS-based assays and the possibility of false findings. Given the sensitivity, the proper design of MS-based experiments becomes of utmost importance. In this chapter, we review the basic experimental-design tools that can be used to prevent occurrence of errors that might cause misleading findings in MS-based experiments. We also present results of an experiment aimed at investigating variability of the intensity measurements produced by a MALDI-TOF mass spectrometer. The knowledge about the potential sources of systematic and random errors is fundamental in order to properly design an MS experiment.
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http://dx.doi.org/10.1007/978-1-4939-9232-4_12DOI Listing
August 2019

A multivariate linear model for investigating the association between gene-module co-expression and a continuous covariate.

Stat Appl Genet Mol Biol 2019 03 15;18(2). Epub 2019 Mar 15.

Hasselt University, I-BioStat, Diepenbeek, Belgium.

A way to enhance our understanding of the development and progression of complex diseases is to investigate the influence of cellular environments on gene co-expression (i.e. gene-pair correlations). Often, changes in gene co-expression are investigated across two or more biological conditions defined by categorizing a continuous covariate. However, the selection of arbitrary cut-off points may have an influence on the results of an analysis. To address this issue, we use a general linear model (GLM) for correlated data to study the relationship between gene-module co-expression and a covariate like metabolite concentration. The GLM specifies the gene-pair correlations as a function of the continuous covariate. The use of the GLM allows for investigating different (linear and non-linear) patterns of co-expression. Furthermore, the modeling approach offers a formal framework for testing hypotheses about possible patterns of co-expression. In our paper, a simulation study is used to assess the performance of the GLM. The performance is compared with that of a previously proposed GLM that utilizes categorized covariates. The versatility of the model is illustrated by using a real-life example. We discuss the theoretical issues related to the construction of the test statistics and the computational challenges related to fitting of the proposed model.
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http://dx.doi.org/10.1515/sagmb-2018-0008DOI Listing
March 2019

The impact of the method of extracting metabolic signal from 1H-NMR data on the classification of samples: A case study of binning and BATMAN in lung cancer.

PLoS One 2019 6;14(2):e0211854. Epub 2019 Feb 6.

I-BioStat, Hasselt University, Diepenbeek, Belgium.

Nuclear magnetic resonance (NMR) spectroscopy is a principal analytical technique in metabolomics. Extracting metabolic information from NMR spectra is complex due to the fact that an immense amount of detail on the chemical composition of a biological sample is expressed through a single spectrum. The simplest approach to quantify the signal is through spectral binning which involves subdividing the spectra into regions along the chemical shift axis and integrating the peaks within each region. However, due to overlapping resonance signals, the integration values do not always correspond to the concentrations of specific metabolites. An alternate, more advanced statistical approach is spectral deconvolution. BATMAN (Bayesian AuTomated Metabolite Analyser for NMR data) performs spectral deconvolution using prior information on the spectral signatures of metabolites. In this way, BATMAN estimates relative metabolic concentrations. In this study, both spectral binning and spectral deconvolution using BATMAN were applied to 400 MHz and 900 MHz NMR spectra of blood plasma samples from lung cancer patients and control subjects. The relative concentrations estimated by BATMAN were compared with the binning integration values in terms of their ability to discriminate between lung cancer patients and controls. For the 400 MHz data, the spectral binning approach provided greater discriminatory power. However, for the 900 MHz data, the relative metabolic concentrations obtained by using BATMAN provided greater predictive power. While spectral binning is computationally advantageous and less laborious, complementary models developed using BATMAN-estimated features can add complementary information regarding the biological interpretation of the data and therefore are clinically useful.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0211854PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6364941PMC
November 2019

Disease-free survival as a surrogate for overall survival in patients with HER2-positive, early breast cancer in trials of adjuvant trastuzumab for up to 1 year: a systematic review and meta-analysis.

Lancet Oncol 2019 03 29;20(3):361-370. Epub 2019 Jan 29.

Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Hasselt University, Diepenbeek, Belgium; International Drug Development Institute, San Francisco, CA, USA.

Background: Although frequently used as a primary endpoint, disease-free survival has not been validated as a surrogate for overall survival in early breast cancer. We investigated this surrogacy in the adjuvant setting of treatment with anti-HER2 antibodies.

Methods: In a systematic review and meta-analysis, we identified published and non-published randomised controlled trials with completed accrual and available disease-free survival and overall survival results for the intention-to-treat population as of September 2016. Bibliographic databases (MEDLINE, Embase, and Cochrane Central Register of Controlled Trials), clinical trial registries (Clinicaltrials.gov, EU Clinical Trials Register, WHO International Clinical Trials Registry Platform, and PharmNet.Bund), and trial registries from relevant pharmaceutical companies were searched. Eligibility for treatment of HER2-positive early breast cancer required at least one group to have an anti-HER antibody treatment (ie, trastuzumab, pertuzumab, or trastuzumab emtansine) planned for 12 months, and at least one control arm with chemotherapy without the antibody, a lower total dose or duration of the antibody, or observation alone. Units of analysis were contrasts: two-group trials gave rise to one contrast, whereas trials with more than two groups gave rise to more than one contrast. We excluded trials enrolling patients with recurrent, metastatic, or non-invasive disease, and those testing neoadjuvant therapy exclusively. Our primary objective was to estimate patient-level and trial-level correlations between disease-free survival and overall survival. We measured the association between disease-free survival and overall survival using Spearman's correlation coefficient (r), and the association between hazard ratios (HRs) for disease-free survival and overall survival using R. We computed the surrogate threshold effect, the maximum HR for disease-free survival that statistically predicts an HR for overall survival less than 1·00 in a future trial.

Findings: Eight trials (n=21 480 patients) gave rise to a full set (12 contrasts). Patient-level associations between disease-free and overall survival were strong (r=0·90 [95% CI 0·89-0·90]). Trial-level associations gave rise to values of R of 0·75 (95% CI 0·50-1·00) for the full set. Subgroups defined by nodal status and hormone receptor status yielded qualitatively similar results. Depending on the expected number of deaths in a future trial, the surrogate threshold effects ranged from 0·56 to 0·81, based on the full set.

Interpretation: These findings suggest that it is appropriate to continue to use disease-free survival as a surrogate for overall survival in trials in HER-2-positive, early breast cancer. The key limitation of this study is the dependence of its results on the trials included and on the existence of an outlying trial.

Funding: Roche Pharma AG.
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http://dx.doi.org/10.1016/S1470-2045(18)30750-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7050571PMC
March 2019

Re-induction using whole cell melanoma vaccine genetically modified to melanoma stem cells-like beyond recurrence extends long term survival of high risk resected patients - updated results.

J Immunother Cancer 2018 11 29;6(1):134. Epub 2018 Nov 29.

Chair of Medical Biotechnology, University of Medical Sciences, 15 Garbary street, 61-866, Poznan, Poland.

Background: AGI-101H is an allogeneic gene modified whole cell therapeutic melanoma vaccine, evaluated in over 400 melanoma patients in the adjuvant and therapeutic settings. We present updated long-term survival results from two single-arm, phase II adjuvant trials (Trial 3 and Trial 5) with the focus on treatment beyond recurrence of the disease.

Methods: Patients with resected high-risk melanoma (stage IIIB-IV) were enrolled to Trial 3 (n = 99) and Trial 5 (n = 97). The primary endpoint was disease-free survival (DFS), and the secondary was overall survival (OS). In the induction phase, the vaccine was administered every 2 weeks (eight times), followed by the maintenance phase every month until progression. At progression, maintenance was continued or re-induction was applied with or without surgery.

Results: In Trial 3, the 10-year DFS was equal to 33.0% overall and to 52.4, 25.0, and 8.7% for stage IIIB, IIIC, and stage IV patients, respectively. In Trial 5, the overall 10-year DFS was equal to 24.2%, and to 37.5, 18.0, and 17.6% for stage IIIB, IIIC, and stage IV patients, respectively. In Trial 3, the 10-year OS was equal to 42.3% overall, and to 59.5, 37.5, and 17.4% for stage IIIB, IIIC, and stage IV patients, respectively. In Trial 5, the 10-year OS was equal to 34.3% overall and to 46.9, 28.0, and 29.4% for stage IIIB, IIIC, and stage IV patients, respectively. Among the 65 patients of Trial 3 who developed progression, 43 received re-induction with (n = 22) or without (n = 21) surgery. Two patients received surgery without re-induction. All the 22 progressing patients, who did not receive re-induction, died. Among the 75 patients of Trial 5 who experienced progression, 39 received re-induction with (n = 21) or without (n = 18) surgery. Among the 36 progressing patients who did not receive the re-induction, 35 died. Surgery and re-induction reduced (independently) the increase of mortality after progression in both trials, with the effect of re-induction reaching statistical significance in Trial 5.

Conclusions: Vaccination beyond recurrence of the disease with additional re-induction combined with surgery or alone increased long term survival of melanoma patients. However, further studies on larger patient cohorts are required.

Trial Registration: Central Evidence of Clinical Trials (EudraCT Number 2008-003373-40 ).
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http://dx.doi.org/10.1186/s40425-018-0456-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6264600PMC
November 2018

Surrogate endpoints in advanced sarcoma trials: a meta-analysis.

Oncotarget 2018 Oct 2;9(77):34617-34627. Epub 2018 Oct 2.

Clinical and Epidemiological Research Unit, Institut Bergonié, Comprehensive Cancer Center, Bordeaux cedex 33076, France.

Background: Alternative endpoints to overall survival (OS) are frequently used to assess treatment efficacy in randomized controlled trials (RCT). Their properties in terms of surrogate outcomes for OS need to be assessed. We evaluated the surrogate properties of progression-free survival (PFS), time-to-progression (TTP) and time-to-treatment failure (TTF) in advanced soft tissue sarcomas (STS).

Results: A total of 21 trials originally met the selection criteria and 14 RCTs ( = 2846) were included in the analysis. Individual-level associations were moderate (highest for 12-month PFS: Spearman's rho = 0.66; 95% CI [0.63; 0.68]). Trial-level associations were ranked as low for the three endpoints as per the IQWiG criterion.

Materials And Methods: We performed a meta-analysis using individual-patient data (IPD). Phase II/III RCTs evaluating therapies for adults with advanced STS were eligible. We estimated the individual- and the trial-level associations between then candidate surrogates and OS. Statistical methods included weighted linear regression and the two-stage model introduced by Buyse and Burzykowski. The strength of the trial-level association was ranked according to the German Institute for Quality and Efficiency in Health Care (IQWiG) guidelines.

Conclusions: Our results do not support strong surrogate properties of PFS, TTP and TTF for OS in advanced STS.
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http://dx.doi.org/10.18632/oncotarget.26166DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6195375PMC
October 2018

The retrospective study of 93 patients with transmigration of mandibular canine and a comparative analysis with a control group.

Eur J Orthod 2019 Aug;41(4):390-396

Department of Oral Surgery, Medical University of Warsaw, Poland.

Objectives: The aim of this study was to evaluate characteristics of patients with unilateral transmigration of a mandibular canine in the largest study group presented until now.

Materials And Methods: The study group consisted of 93 patients with unilateral transmigration of mandibular canine; the control group included 85 non-affected patients. Type of transmigration, status of deciduous and permanent canines, prevalence of missing teeth, class of occlusion, and space conditions were assessed to draw comparisons between groups.

Results: In this study, 64.5 per cent patients presented type 1 of transmigration; types 2, 3, 4, and 5 were present in, respectively, 23.7, 5.4, 4.3, and 2.1 per cent patients. There was a clear, statistically significant difference (P < 0.0001) between the mean crown and apex migration and angulation for the three groups of canines (transmigrated, contralateral, and control), whereas no differences were observed for the total number of permanent teeth present. In the study group, 73.1 per cent patients retained their primary canine on the affected side and 18.3 per cent on the contralateral side; in the control group, 22.3 per cent subjects had at least one primary canine. There was a statistically significant difference in the distribution of types of malocclusion between the study and the control groups.

Conclusions: Transmigration of mandibular canine was associated with the presence of retained primary canine on the affected side, higher mesial tilting of contralateral mandibular canine when compared to the canines in the control group. Additionally, higher prevalence of Angle's Class I occlusion in patients with canine transmigration was recorded.
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http://dx.doi.org/10.1093/ejo/cjy067DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6686080PMC
August 2019

The search for surrogate endpoints for immunotherapy trials.

Ann Transl Med 2018 Jun;6(11):231

International Drug Development Institute, Louvain-la-Neuve, Belgium.

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http://dx.doi.org/10.21037/atm.2018.05.16DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6035998PMC
June 2018

Understanding and Communicating Measures of Treatment Effect on Survival: Can We Do Better?

J Natl Cancer Inst 2018 03;110(3):232-240

Interuniversity Institute for Biostatistics and statistical Bioinformatics (I-BioStat), Hasselt University, Diepenbeek, Belgium.

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.
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http://dx.doi.org/10.1093/jnci/djx179DOI Listing
March 2018

Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation.

Cell 2018 04;173(2):338-354.e15

Poznań University of Medical Sciences, 61701 Poznań, Poland; Greater Poland Cancer Center, 61866 Poznań, Poland; International Institute for Molecular Oncology, 60203 Poznań, Poland. Electronic address:

Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation.
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http://dx.doi.org/10.1016/j.cell.2018.03.034DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5902191PMC
April 2018

A Poisson approach to the validation of failure time surrogate endpoints in individual patient data meta-analyses.

Stat Methods Med Res 2019 01 6;28(1):170-183. Epub 2017 Jul 6.

1 Service de Biostatistique et d'Épidémiologie, Institut Gustave Roussy, Université Paris-Saclay, Villejuif, France.

Surrogate endpoints are often used in clinical trials instead of well-established hard endpoints for practical convenience. The meta-analytic approach relies on two measures of surrogacy: one at the individual level and one at the trial level. In the survival data setting, a two-step model based on copulas is commonly used. We present a new approach which employs a bivariate survival model with an individual random effect shared between the two endpoints and correlated treatment-by-trial interactions. We fit this model using auxiliary mixed Poisson models. We study via simulations the operating characteristics of this mixed Poisson approach as compared to the two-step copula approach. We illustrate the application of the methods on two individual patient data meta-analyses in gastric cancer, in the advanced setting (4069 patients from 20 randomized trials) and in the adjuvant setting (3288 patients from 14 randomized trials).
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http://dx.doi.org/10.1177/0962280217718582DOI Listing
January 2019

Precision medicine needs randomized clinical trials.

Nat Rev Clin Oncol 2017 05 7;14(5):317-323. Epub 2017 Feb 7.

I-BioStat, Hasselt University, Martelarenlaan 42, 3500 Hasselt, Belgium; and at the IDDI, 185 Alewife Brook Parkway, Suite 410, Cambridge, Massachusetts 02138, USA.

The advent of precision medicine has prompted profound changes in clinical cancer research, and the rising numbers of new therapeutic agents pose challenges in terms of the most appropriate trial designs and effects on the drug-approval process. In the past 5 years, some remarkably efficacious drugs have been approved based on evidence from uncontrolled phase I trials. We challenge the view that the expected benefits from new drugs are generally sufficient to forgo a randomized trial with patients assigned to a control arm (a regimen other than the experimental treatment). Relying on efficacy results from uncontrolled clinical trials can result in expedited drug approval, but the disadvantages of this practice must be taken into account. For example, the apparent improvements in outcomes observed in an early single-arm trial of a new therapy might reflect the prognostic nature of the target, rather than a true treatment effect. Moreover, the predictive role of biomarkers cannot be definitively ascertained without randomly assigning patients to a control arm. We discuss the need for such randomization to a true control in all phases of drug development and the role of companion biomarker testing. We propose that an increased use of randomization will facilitate a seamless transition between phases of drug and/or biomarker development.
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http://dx.doi.org/10.1038/nrclinonc.2017.8DOI Listing
May 2017

An open label phase II study evaluating first-line EGFR tyrosine kinase inhibitor erlotinib in non-small cell lung cancer patients with tumors showing high EGFR gene copy number.

Oncotarget 2017 Mar;8(10):17270-17278

Department of Oncology and Radiotherapy, Medical University of Gdańsk, Poland.

Background: First-line treatment with epidermal growth factor receptor (EGFR) inhibitors in NSCLC is effective in patients with activating EGFR mutations. The activity of erlotinib in patients harboring high EGFR gene copy number has been considered debatable.

Patients And Methods: A multicenter, open-label, single-arm phase II clinical trial was performed to test the efficacy of erlotinib in the first-line treatment of NSCLC patients harboring high EGFR gene copy number defined as ≥4 copies in ≥40% of cells.

Findings: Between December 2007 and April 2011, tumor samples from 149 subjects were screened for EGFR gene copy number by fluorescence in-situ hybridization (FISH), Out of 49 patients with positive EGFR FISH test, 45 were treated with erlotinib. Median PFS in the intent-to-treat population was 3.3 months (95%CI: 1.8-3.9 months), and median overall survival was 7.9 months (95% CI: 5.1-12.6 months). Toxicity profile of erlotinib was consistent with its known safety profile. The trial was stopped prematurely at 63% of originally planned sample size due to accumulating evidence that EGFR gene copy number should not be used to select NSCLC patients to first-line therapy with EGFR TKI. Data on erlotinib efficacy according to EGFR, KRAS and BRAF mutations are additionally presented.

Interpretation: This trial argues against using high gene copy number for selection of NSCLC patients to first-line therapy with EGFR TKIs. The study adds to the discussion on efficacy of other targeted agents in patients with target gene amplified tumors.
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http://dx.doi.org/10.18632/oncotarget.13793DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5370039PMC
March 2017

Adoption of Pathologic Complete Response as a Surrogate End Point in Neoadjuvant Trials in HER2-Positive Breast Cancer Still an Open Question.

JAMA Oncol 2017 03;3(3):416

Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Hasselt University, Belgium4International Drug Development Institute, San Francisco, California.

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http://dx.doi.org/10.1001/jamaoncol.2016.3941DOI Listing
March 2017

Adaptive Randomization of Neratinib in Early Breast Cancer.

N Engl J Med 2016 10;375(16):1591-2

International Drug Development Institute, Louvain-la-Neuve, Belgium

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http://dx.doi.org/10.1056/NEJMc1609993DOI Listing
October 2016

Computational methods and challenges in hydrogen/deuterium exchange mass spectrometry.

Mass Spectrom Rev 2017 09 7;36(5):649-667. Epub 2016 Sep 7.

I-BioStat, Hasselt University, Campus Diepenbeek, Agoralaan Gebouw D, Diepenbeek 3590, Belgium.

Hydrogen/Deuterium exchange (HDX) has been applied, since the 1930s, as an analytical tool to study the structure and dynamics of (small) biomolecules. The popularity of using HDX to study proteins increased drastically in the last two decades due to the successful combination with mass spectrometry (MS). Together with this growth in popularity, several technological advances have been made, such as improved quenching and fragmentation. As a consequence of these experimental improvements and the increased use of protein-HDXMS, large amounts of complex data are generated, which require appropriate analysis. Computational analysis of HDXMS requires several steps. A typical workflow for proteins consists of identification of (non-)deuterated peptides or fragments of the protein under study (local analysis), or identification of the deuterated protein as a whole (global analysis); determination of the deuteration level; estimation of the protection extent or exchange rates of the labile backbone amide hydrogen atoms; and a statistically sound interpretation of the estimated protection extent or exchange rates. Several algorithms, specifically designed for HDX analysis, have been proposed. They range from procedures that focus on one specific step in the analysis of HDX data to complete HDX workflow analysis tools. In this review, we provide an overview of the computational methods and discuss outstanding challenges. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 36:649-667, 2017.
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http://dx.doi.org/10.1002/mas.21519DOI Listing
September 2017

Estimation of diagnostic accuracy of a combination of continuous biomarkers allowing for conditional dependence between the biomarkers and the imperfect reference-test.

Biometrics 2017 06 6;73(2):646-655. Epub 2016 Sep 6.

Hasselt University, I-BioStat, Agoralaan, B-3590 Diepenbeek, Belgium.

Estimating biomarker-index accuracy when only imperfect reference-test information is available is usually performed under the assumption of conditional independence between the biomarker and imperfect reference-test values. We propose to define a latent normally-distributed tolerance-variable underlying the observed dichotomous imperfect reference-test results. Subsequently, we construct a Bayesian latent-class model based on the joint multivariate normal distribution of the latent tolerance and biomarker values, conditional on latent true disease status, which allows accounting for conditional dependence. The accuracy of the continuous biomarker-index is quantified by the AUC of the optimal linear biomarker-combination. Model performance is evaluated by using a simulation study and two sets of data of Alzheimer's disease patients (one from the memory-clinic-based Amsterdam Dementia Cohort and one from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database). Simulation results indicate adequate model performance and bias in estimates of the diagnostic-accuracy measures when the assumption of conditional independence is used when, in fact, it is incorrect. In the considered case studies, conditional dependence between some of the biomarkers and the imperfect reference-test is detected. However, making the conditional independence assumption does not lead to any marked differences in the estimates of diagnostic accuracy.
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http://dx.doi.org/10.1111/biom.12583DOI Listing
June 2017

Normalisation of brain spectroscopy findings in Niemann-Pick disease type C patients treated with miglustat.

J Neurol 2016 May 16;263(5):927-936. Epub 2016 Mar 16.

Department of Neuroradiology, Pierre and Marie Curie University, Paris, France.

Niemann-Pick disease type C (NP-C) is a fatal progressive neurolipidosis involving neuronal storage of cholesterol and gangliosides. Miglustat, an inhibitor of glycosphingolipid synthesis, has been approved to treat neurological manifestations in adults and children with NP-C. This open-label observational study in adults with confirmed NP-C evaluated the efficacy of miglustat (200 mg t.i.d.) based on composite functional disability (CFD) scores and brain proton magnetic resonance spectroscopy (H-MRS) measurement of choline (Cho)/N-acetyl aspartate (NAA) ratio in the centrum ovale. Overall, 16 patients were included and received miglustat for a mean period of 30.6 months: 12 continued on miglustat throughout follow up, and 4 discontinued miglustat because of adverse effects (n = 2) or perceived lack of efficacy (n = 2). In the 'continued' subgroup, the mean (SD) annual progression of CFD scores decreased from 0.75 (0.94) before treatment to 0.29 (1.29) during the period between miglustat initiation and last follow-up. In the discontinued subgroup, CFD progression increased from 0.48 (0.44) pre-treatment to 1.49 (1.31) at last follow up (off treatment). Mean (SD) Cho/NAA ratio [normal level 0.48 (0.076)] decreased during miglustat treatment in the continued subgroup: 0.64 (0.12) at baseline (miglustat initiation), 0.59 (0.17) at 12-month follow up, and 0.48 (0.09) at 24-month follow up. Cho/NAA ratio remained relatively stable in the discontinued subgroup: 0.57 (0.15), 0.53 (0.04) and 0.55 (0.09), respectively. In conclusion, H-MRS Cho/NAA ratio might serve as an objective, quantitative neurological marker of brain dysfunction in NP-C, allowing longitudinal analysis of the therapeutic effect of miglustat.
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http://dx.doi.org/10.1007/s00415-016-8051-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4859844PMC
May 2016