23 research outputs found
Combined cetuximab and trastuzumab are superior to gemcitabine in the treatment of human pancreatic carcinoma xenografts
Background: Pancreatic carcinoma remains a treatment-refractory cancer with a poor prognosis. Here, we compared anti-epidermal growth factor receptor (EGFR) and anti-HER2 monoclonal antibodies (2mAbs) injections with standard gemcitabine treatment on human pancreatic carcinoma xenografts. Materials and methods: Nude mice, bearing human pancreatic carcinoma xenografts, were treated with either combined anti-EGFR (cetuximab) and anti-HER2 (trastuzumab) or gemcitabine, and tumor growth was observed. Results and conclusion: In first-line therapy, mice survival was significantly longer in the 2mAbs group compared with gemcitabine (P < 0.0001 for BxPC-3, P = 0.0679 for MiaPaCa-2 and P = 0.0019 for Capan-1) and with controls (P < 0.0001). In second-line therapy, tumor regressions were observed after replacing gemcitabine by 2mAbs treatment, resulting in significantly longer animal survival compared with mice receiving continuous gemcitabine injections (P = 0.008 for BxPC-3, P = 0.05 for MiaPaCa-2 and P < 0.001 for Capan-1). Therapeutic benefit of 2mAbs was observed despite K-Ras mutation. Interestingly, concerning the mechanism of action, coinjection of F(abâČ)2 fragments from 2mAbs induced significant tumor growth inhibition, compared with controls (P = 0.001), indicating that the 2mAbs had an Fc fragment-independent direct action on tumor cells. This preclinical study demonstrated a significant improvement of survival and tumor regression in mice treated with anti-EGFR/anti-HER2 2mAbs in first- and second-line treatments, compared with gemcitabine, independently of the K-Ras statu
Application of Two-Part Statistics for Comparison of Sequence Variant Counts
Investigation of microbial communities, particularly human associated communities, is significantly enhanced by the vast amounts of sequence data produced by high throughput sequencing technologies. However, these data create high-dimensional complex data sets that consist of a large proportion of zeros, non-negative skewed counts, and frequently, limited number of samples. These features distinguish sequence data from other forms of high-dimensional data, and are not adequately addressed by statistical approaches in common use. Ultimately, medical studies may identify targeted interventions or treatments, but lack of analytic tools for feature selection and identification of taxa responsible for differences between groups, is hindering advancement. The objective of this paper is to examine the application of a two-part statistic to identify taxa that differ between two groups. The advantages of the two-part statistic over common statistical tests applied to sequence count datasets are discussed. Results from the t-test, the Wilcoxon test, and the two-part test are compared using sequence counts from microbial ecology studies in cystic fibrosis and from cenote samples. We show superior performance of the two-part statistic for analysis of sequence data. The improved performance in microbial ecology studies was independent of study type and sequence technology used
Random effect Models for Quality of Life Analysis in Oncology
International audienceIn Oncology, the Health-related Quality of Life (QoL) has become an essential criterion in clinical trials. However, the longitudinal analysis of this criterion is complex and non-standardized. Indeed, the observations are obtained through self-questionnaires (Patient-Reported Outcomes) and there are both multiple responses, repeated and ordinal ones.From a statistical standpoint, QoL is not directly measurable and is considered as a latent trait which is accessible through responses to items.To evaluate QoL in most cancer clinical trials, the QLQ-C30 questionnaire has been used. Nowadays, the statistical analysis is done on a score from the EORTC recommendations, corresponding to the average of item responses. Longitudinal competing models are exploitedsuch as a linear mixed model (LMM) classically used for score modelling and generalized linear mixed models (GLMM)employedfor ordinal categorical data. The latter model familybuilds on the Item Response Theory (IRT) and allows considering raw data (item responses). Regarding the longitudinal analysis, the IRT models are proposed as an alternative to LMMandextended to take into account the clinical covariates and data characteristics. These presented models were compared through the analysis of a dataset from a clinical trial and then a simulation studywas performed. The IRT model for polytomous data is quitecomplex and fastidious to estimate the regression coefficients and topredict the random effects. Finally, a less complex approach of linearization advanced by Schall in 1991 is proposed to estimate these GLMM in order to complete the simulation study
RĂšgles d\u27arrĂȘt prĂ©coce dans les essais cliniques basĂ©es sur une surveillance sĂ©quentielle des Ă©vĂ©nements indĂ©sirables graves
Comput Methods Programs Biomed
BACKGROUND AND OBJECTIVE: Health-related quality of life (HRQoL) has become one relevant and available alternative endpoint of clinical trials in cancer research to evaluate efficiency of care both for the patient and health system. HRQoL in oncology is mainly assessed using the 30-item European Organisation for Research and Treatment of Cancer Quality of Life-Questionnaire Core 30 (EORTC QLQ-C30). The EORTC QLQ-C30 questionnaire is usually assessed at different times along the clinical trials in order to analyze the kinetics of HRQoL evolution and to fully assess the impact of the treatment on the patient's HRQoL level. In this perspective, the realization of a longitudinal HRQoL analysis is essential and the time to HRQoL score deterioration approach is a method which is more and more used in clinical trials. METHOD: Using the Stata software, we developed a QLQ-C30 specific command, qlqc30_TTD, which implements longitudinal strategies based on the time to event methods by considering the time to HRQoL score deterioration. This user-written command providing automatic execution of the Time To Deterioration (TTD) and Time Until Definitive Deterioration (TUDD) methods. RESULT: The program implements all published definitions and provides the Kaplan-Meier curves for each dimension (by group) and a table with the Hazard Ratio and Log-Rank test. CONCLUSION: The longitudinal analysis of HRQoL data in cancer clinical trials remains complex with only few programs like ours computed. This program will be of great help and will allow a more systematic and quicker analysis of the HRQoL data in clinical trials in oncology
Méthodes de détermination de la différence minimale cliniquement importante pour les questionnaires de qualité de vie relative à la santé en cancérologie
La qualite de vie relative a la sante (QdV) est un critere de jugement majeur dans les essais cliniques en cancerologie afin de pouvoir mesurer le benefice clinique de nouvelles strategies therapeutiques pour le patient. Lâinterpretation des resultats doit se faire dâun point de vue statistique mais egalement dâun point de vue clinique pour le patient. En effet, la significativite statistique etant fortement influencee par la taille de lâechantillon, une petite difference de score de QdV peut etre statistiquement significative sans pour autant avoir de sens clinique pour le patient. La difference minimale cliniquement importante (DMCI) a ainsi ete definie comme la plus petite difference dâun score de QdV percue comme cliniquement importante pour le patient. Lâobjectif de ce travail est de repertorier lâensemble des methodes existantes pour la determination de la DMCI et de realiser une revue de la litterature en cancerologie. Methodes Les methodes existantes pour determiner la DMCI sont generalement classees en deux categories : (1) celles basees sur lâancre, i.e. sur un critere externe permettant de qualifier le changement observe (petite, moyenne, ou importante amelioration/deterioration vs. stabilite) et (2) celles basees sur la distribution des scores de QdV. Differents articles en cancerologie portant sur la determination de la DMCI pour un questionnaire du groupe EORTC ont ete selectionnes par une recherche dans PUBMED avec algorithme de selection. Des informations ont ete recueillies telles que la methode de determination de la DMCI utilisee, le choix de lâancre et des distributions reportees, et la taille de lâechantillon consideree. Resultats Une premiere recherche PUBMED a permis dâidentifier 54 articles dont 11 articles (20 %) portant sur des questionnaires EORTC. Les premiers resultats obtenus specifiquement pour les articles EORTC sont reportes ici. Les methodes basees sur lâancre et la distribution ont ete utilisees conjointement dans chaque etude. Lâancre utilisee correspondait a lâitem de QdV global du questionnaire QLQ-C30 ou QLQ-C15PAL pour quatre etudes, la question de transition de Jaeschke pour quatre etudes, et des mesures cliniques telles que le « performance status » pour trois etudes. La correlation entre lâancre et les scores de QdV a lâinclusion a ete verifiee pour huit etudes. Les distributions generalement reportes etaient 20, 30 et 50 % de lâecart-type a lâinclusion. Dans seulement une etude, la taille de lâechantillon a ete determinee specifiquement pour lâanalyse de la DMCI. Les methodes basees sur lâancre necessitent la collecte dâun critere externe supplementaire. Une limite souvent observee est le faible echantillon par categorie dâancre conduisant a des resultats peu fiables, avec un minimum de sept patients observes pour determiner la DMCI pour lâamelioration. Dans deux articles lâimpact de lâoccurrence de lâeffet « response shift » (RS) sur la determination de la DMCI a ete etudie. Il a ete montre dans ces etudes que lâeffet RS impactait majoritairement les resultats de la DMCI chez les patients pour lesquels une deterioration etait observee. Dans deux etudes la stabilite de la DMCI au cours du temps a ete exploree. Conclusion La revue systematique de la litterature est en cours et les resultats de cette revue completeront ces premieres donnees. Des recommandations pourront ainsi etre proposees pour les futures etudes ayant pour objectif de determiner la DMCI
Méthodes de détermination de la différence minimale cliniquement importante pour les questionnaires de qualité de vie relative à la santé en cancérologie
La qualite de vie relative a la sante (QdV) est un critere de jugement majeur dans les essais cliniques en cancerologie afin de pouvoir mesurer le benefice clinique de nouvelles strategies therapeutiques pour le patient. Lâinterpretation des resultats doit se faire dâun point de vue statistique mais egalement dâun point de vue clinique pour le patient. En effet, la significativite statistique etant fortement influencee par la taille de lâechantillon, une petite difference de score de QdV peut etre statistiquement significative sans pour autant avoir de sens clinique pour le patient. La difference minimale cliniquement importante (DMCI) a ainsi ete definie comme la plus petite difference dâun score de QdV percue comme cliniquement importante pour le patient. Lâobjectif de ce travail est de repertorier lâensemble des methodes existantes pour la determination de la DMCI et de realiser une revue de la litterature en cancerologie. Methodes Les methodes existantes pour determiner la DMCI sont generalement classees en deux categories : (1) celles basees sur lâancre, i.e. sur un critere externe permettant de qualifier le changement observe (petite, moyenne, ou importante amelioration/deterioration vs. stabilite) et (2) celles basees sur la distribution des scores de QdV. Differents articles en cancerologie portant sur la determination de la DMCI pour un questionnaire du groupe EORTC ont ete selectionnes par une recherche dans PUBMED avec algorithme de selection. Des informations ont ete recueillies telles que la methode de determination de la DMCI utilisee, le choix de lâancre et des distributions reportees, et la taille de lâechantillon consideree. Resultats Une premiere recherche PUBMED a permis dâidentifier 54 articles dont 11 articles (20 %) portant sur des questionnaires EORTC. Les premiers resultats obtenus specifiquement pour les articles EORTC sont reportes ici. Les methodes basees sur lâancre et la distribution ont ete utilisees conjointement dans chaque etude. Lâancre utilisee correspondait a lâitem de QdV global du questionnaire QLQ-C30 ou QLQ-C15PAL pour quatre etudes, la question de transition de Jaeschke pour quatre etudes, et des mesures cliniques telles que le « performance status » pour trois etudes. La correlation entre lâancre et les scores de QdV a lâinclusion a ete verifiee pour huit etudes. Les distributions generalement reportes etaient 20, 30 et 50 % de lâecart-type a lâinclusion. Dans seulement une etude, la taille de lâechantillon a ete determinee specifiquement pour lâanalyse de la DMCI. Les methodes basees sur lâancre necessitent la collecte dâun critere externe supplementaire. Une limite souvent observee est le faible echantillon par categorie dâancre conduisant a des resultats peu fiables, avec un minimum de sept patients observes pour determiner la DMCI pour lâamelioration. Dans deux articles lâimpact de lâoccurrence de lâeffet « response shift » (RS) sur la determination de la DMCI a ete etudie. Il a ete montre dans ces etudes que lâeffet RS impactait majoritairement les resultats de la DMCI chez les patients pour lesquels une deterioration etait observee. Dans deux etudes la stabilite de la DMCI au cours du temps a ete exploree. Conclusion La revue systematique de la litterature est en cours et les resultats de cette revue completeront ces premieres donnees. Des recommandations pourront ainsi etre proposees pour les futures etudes ayant pour objectif de determiner la DMCI
%TTD and %TUDD: New SAS macro programs to calculate the survival data of the time to deterioration for patient-reported outcomes data in oncology
International audienceBackground and objective: Longitudinal analysis of patient-reported outcome (PRO) data remains challenging, as no standardization of statistical methods has been proposed, making comparison of PRO results between clinical trials difficult. In this context, the time to deterioration approach has recently been proposed and is regularly used as a modality of longitudinal PRO analysis in oncology.Methods: Two new SAS macro programs were developed, %TTD and %TUDD, which implement longitudinal analysis of PRO data according to the time to deterioration approach. These programs implement the recommended deterioration definitions. We described the programs with their different functionalities.Results: The %TTD macro calculates the time to first or transient deterioration, and the %TUDD macro calculates the time until definitive deterioration. These macros allow to obtain the survival variables from the time to deterioration approach. We illustrate our programs by presenting different applications on the randomized phase II AFUGEM GERCOR clinical trial.Conclusion: The implementation of the deterioration definitions in SAS software allows the dissemination of this approach, in order to move toward the goal of standardization of longitudinal PRO analysis in oncology clinical trials
In pancreatic carcinoma, dual EGFR/HER2 targeting with cetuximab/trastuzumab is more effective than treatment with trastuzumab/erlotinib or lapatinib alone: implication of receptors' down-regulation and dimers' disruption.
We previously demonstrated the synergistic therapeutic effect of the cetuximab (anti-epidermal growth factor receptor [EGFR] monoclonal antibody, mAb)-trastuzumab (anti-HER2 mAb) combination (2mAbs therapy) in HER2(low) human pancreatic carcinoma xenografts. Here, we compared the 2mAbs therapy, the erlotinib (EGFR tyrosine kinase inhibitor [TKI])-trastuzumab combination and lapatinib alone (dual HER2/EGFR TKI) and explored their possible mechanisms of action. The effects on tumor growth and animal survival of the three therapies were assessed in nude mice xenografted with the human pancreatic carcinoma cell lines Capan-1 and BxPC-3. After therapy, EGFR and HER2 expression and AKT phosphorylation in tumor cells were analyzed by Western blot analysis. EGFR/HER2 heterodimerization was quantified in BxPC-3 cells by time-resolved FRET. In K-ras-mutated Capan-1 xenografts, the 2mAbs therapy gave significantly higher inhibition of tumor growth than the erlotinib/trastuzumab combination, whereas in BxPC-3 (wild-type K-ras) xenografts, the erlotinib/trastuzumab combination showed similar growth inhibition but fewer tumor-free mice. Lapatinib showed no antitumor effect in both types of xenografts. The efficacy of the 2mAbs therapy was partly Fc-independent because F(ab')(2) fragments of the two mAbs significantly inhibited BxPC-3 growth, although with a time-limited therapeutic effect. The 2mAbs therapy was associated with a reduction of EGFR and HER2 expression and AKT phosphorylation. BxPC-3 cells preincubated with the two mAbs showed 50% less EGFR/HER2 heterodimers than controls. In pancreatic carcinoma xenografts, the 2mAbs therapy is more effective than treatments involving dual EGFR/HER2 TKIs. The mechanism of action may involve decreased AKT phosphorylation and/or disruption of EGFR/HER2 heterodimerization
Time to deterioration in cancer randomized clinical trials for patient-reported outcomes data: a systematic review
International audienc