In any single-arm trial on novel treatments, assessment of toxicity plays an important role as occurrence of adverse events (AEs) is relevant for application in clinical practice. In the presence of ...a non-fatal time-to-event(s) efficacy endpoint, the analysis should be broadened to consider AEs occurrence in time. The AEs analysis could be tackled with two approaches, depending on the clinical question of interest. Approach 1 focuses on the occurrence of AE as first event. Treatment ability to protect from the efficacy endpoint event(s) has an impact on the chance of observing AEs due to competing risks action. Approach 2 considers how treatment affects the occurrence of AEs in the potential framework where the efficacy endpoint event(s) could not occur.
In the first part of the work we review the strategy of analysis for these two approaches. We identify theoretical quantities and estimators consistent with the following features: (a) estimators should address for the presence of right censoring; (b) theoretical quantities and estimators should be functions of time. In the second part of the work we propose the use of alternative methods (regression models, stratified Kaplan-Meier curves, inverse probability of censoring weighting) to relax the assumption of independence between the potential times to AE and to event(s) in the efficacy endpoint for addressing Approach 2.
We show through simulations that the proposed methods overcome the bias due to the dependence between the two potential times and related to the use of standard estimators.
We demonstrated through simulations that one can handle patients selection in the risk sets due to the competing event, and thus obtain conditional independence between the two potential times, adjusting for all the observed covariates that induce dependence.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Atypical chronic myeloid leukemia (aCML) shares clinical and laboratory features with CML, but it lacks the BCR-ABL1 fusion. We performed exome sequencing of eight aCMLs and identified somatic ...alterations of SETBP1 (encoding a p.Gly870Ser alteration) in two cases. Targeted resequencing of 70 aCMLs, 574 diverse hematological malignancies and 344 cancer cell lines identified SETBP1 mutations in 24 cases, including 17 of 70 aCMLs (24.3%; 95% confidence interval (CI) = 16-35%). Most mutations (92%) were located between codons 858 and 871 and were identical to changes seen in individuals with Schinzel-Giedion syndrome. Individuals with mutations had higher white blood cell counts (P = 0.008) and worse prognosis (P = 0.01). The p.Gly870Ser alteration abrogated a site for ubiquitination, and cells exogenously expressing this mutant exhibited higher amounts of SETBP1 and SET protein, lower PP2A activity and higher proliferation rates relative to those expressing the wild-type protein. In summary, mutated SETBP1 represents a newly discovered oncogene present in aCML and closely related diseases.
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DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Anaplastic lymphoma kinase (ALK)-positive lymphomas respond to chemotherapy, but relapses, which bear a poor prognosis, occur. Crizotinib inhibits ALK in vitro and in vivo and was administered as ...monotherapy to 11 ALK+ lymphoma patients who were resistant/refractory to cytotoxic therapy. The overall response rate was 10 of 11 (90.9%; 95% confidence interval CI = 58.7% to 99.8%). Disease status at the latest follow-up is as follows: four patients are in complete response (CR) (months >21, >30, >35, >40) under continuous crizotinib administration; 4 patients had progression of disease (months 1, 2, 2, 2); 1 patient obtained CR on crizotinib, received an allogeneic bone marrow transplant, and is in CR; 2 patients (treated before and/or after allogeneic bone marrow transplant) obtained and are still in CR but they have stopped crizotinib. Overall and progression-free survival rates at 2 years are 72.7% (95% CI = 39.1% to 94.0%) and 63.7% (95% CI = 30.8% to 89.1%), respectively. ALK mutations conferring resistance to crizotinib in vitro could be identified in relapsed patients. Crizotinib exerted a potent antitumor activity with durable responses in advanced, heavily pretreated ALK+ lymphoma patients, with a benign safety profile.
The recent progress in medical research generates an increasing interest in the use of longitudinal biomarkers for characterizing the occurrence of an outcome. The present work is motivated by a ...study, where the objective was to explore the potential of the long pentraxin 3 (PTX3) as a prognostic marker of Acute Graft-versus-Host Disease (GvHD) after haematopoietic stem cell transplantation. Time-varying covariate Cox model was commonly used, despite its limiting assumptions that marker values are constant in time and measured without error. A joint model has been developed as a viable alternative; however, the approach is computationally intensive and requires additional strong assumptions, in which the impacts of their misspecification were not sufficiently studied.
We conduct an extensive simulation to clarify relevant assumptions for the understanding of joint models and assessment of its robustness under key model misspecifications. Further, we characterize the extent of bias introduced by the limiting assumptions of the time-varying covariate Cox model and compare its performance with a joint model in various contexts. We then present results of the two approaches to evaluate the potential of PTX3 as a prognostic marker of GvHD after haematopoietic stem cell transplantation.
Overall, we illustrate that a joint model provides an unbiased estimate of the association between a longitudinal marker and the hazard of an event in the presence of measurement error, showing improvement over the time-varying Cox model. However, a joint model is severely biased when the baseline hazard or the shape of the longitudinal trajectories are misspecified. Both the Cox model and the joint model correctly specified indicated PTX3 as a potential prognostic marker of GvHD, with the joint model providing a higher hazard ratio estimate.
Joint models are beneficial to investigate the capability of the longitudinal marker to characterize time-to-event endpoint. However, the benefits are strictly linked to the correct specification of the longitudinal marker trajectory and the baseline hazard function, indicating a careful consideration of assumptions to avoid biased estimates.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Cut-point finding is a crucial step for clinical decision making when dealing with diagnostic (or prognostic) biomarkers. The extension of ROC-based cut-point finding methods to the case of censored ...failure time outcome is of interest when we are in the presence of a biomarker, measured at baseline, used to identify whether there will be the development, or not, of some disease condition within a given time point τ of clinical interest.
Three widely used cut-point finding methods, namely the Youden index, the concordance probability and the point closest to-(0,1) corner in the ROC plane, are extended to the case of censored failure time outcome resorting to non-parametric estimators of the sensitivity and specificity that account for censoring. The performance of these methods in finding the optimal cut-point is compared under Normal and Gamma distributions of the biomarker (in subjects developing or not the disease condition). Normality ensures that estimators point theoretically to the same cut-point. Two motivating examples are provided in the paper.
The point closest-to-(0,1) corner approach has the best performance from simulations in terms of mean square error and relative bias.
We discuss the use of the Youden index or concordance probability associated to the cut-point identified through the closest-to-(0,1) corner approach to ease interpretability of the classification performance of the dichotomized biomarker. In addition, the achieved performance of the dichotomized biomarker classification associated to the estimated cut-point can be represented through a confidence interval of the point on the ROC curve.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
In pediatric age the prevalence of obesity is high. Obese children who do not have other risk factors than excess weight have been defined as "metabolically healthy obese" (MHO).
The aim of this ...study is to evaluate, in a population of obese children, the prevalence of the MHO and "metabolically unhealthy obese" (MUO) phenotype. Furthermore, we evaluated the distribution of Uric Acid, HOMA index and Waist-Height ratio (W-Hr) in the MHO and MUO sub-groups and the impact of these non-traditional risk factors on the probability to be MUO.
In 1201 obese children and adolescents 54% males, age (±SD) 11.9 (±3.0) years weight, height, waist circumference, systolic (SBP) and diastolic (DBP) blood pressure, pubertal status, glucose, insulin, HDL cholesterol, triglycerides and Uric Acid serum values were assessed. MUO phenotype was defined as the presence of at least one of the following risk factors: SBP or DBP ≥ 90th percentile, glycaemia ≥ 100 mg/dl, HDL cholesterol <40 mg/dl, triglycerides ≥100 mg/dl (children <10 years) or ≥130 mg/dl (children ≥10 years). A multivariate logistic regression analysis was used to estimate the association between MUO phenotype and non-traditional cardiovascular risk factors.
The prevalence of the MUO status was high (61%). MUO subjects were more often male, older and pubertal (
< 0.001). The levels of the three non-traditional risk factors were significantly higher in MUO children compared to MHO children (
< 0.001) and all of them were independent predictors of the fact of being MUO OR 1.41 (95% CI 1.24-1.69); 1.15 (95% CI 1.06-1.23) and 1.03 (95% CI1.01-1.05) for Uric Acid, HOMA index and W-Hr, respectively. About 15% of MHO subjects had serum Uric Acid, HOMA index and W-Hr values within the highest quartile of the study population.
The prevalence of MUO subjects in a large pediatric population is high and serum Uric Acid, HOMA index and W-Hr values are independent predictors of the probability of being MUO. A non-negligible percentage of subjects MHO has high values of all three non-traditional risk factors.
We recently reported that activation of Trop-2 through its cleavage at R87-T88 by ADAM10 underlies Trop-2–driven progression of colon cancer. However, the mechanism of action and pathological impact ...of Trop-2 in metastatic diffusion remain unexplored. Through searches for molecular determinants of cancer metastasis, we identified TROP2 as unique in its up-regulation across independent colon cancer metastasis models. Overexpression of wild-type Trop-2 in KM12SM human colon cancer cells increased liver metastasis rates in vivo in immunosuppressed mice. Metastatic growth was further enhanced by a tail-less, activated ΔcytoTrop-2 mutant, indicating the Trop-2 tail as a pivotal inhibitory signaling element. In primary tumors and metastases, transcriptome analysis showed no down-regulation of CDH1 by transcription factors for epithelial-to-mesenchymal transition, thus suggesting that the pro-metastatic activity of Trop-2 is through alternative mechanisms. Trop-2 can tightly interact with ADAM10. Here, Trop-2 bound E-cadherin and stimulated ADAM10-mediated proteolytic cleavage of E-cadherin intracellular domain. This induced detachment of E-cadherin from β-actin, and loss of cell-cell adhesion, acquisition of invasive capability, and membrane-driven activation of β-catenin signaling, which were further enhanced by the ΔcytoTrop-2 mutant. This Trop-2/E-cadherin/β-catenin program led to anti-apoptotic signaling, increased cell migration, and enhanced cancer-cell survival. In patients with colon cancer, activation of this Trop-2–centered program led to significantly reduced relapse-free and overall survival, indicating a major impact on progression to metastatic disease. Recently, the anti-Trop-2 mAb Sacituzumab govitecan-hziy was shown to be active against metastatic breast cancer. Our findings define the key relevance of Trop-2 as a target in metastatic colon cancer.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Cardiometabolic risk factors are frequent in children and adolescents with excess weight. The aim of this study was to evaluate the effects of lifestyle modifications on alterations in lipid and ...glycemic profiles and uric acid values in a pediatric population at increased cardiovascular risk. The study involved 276 subjects with a mean age of 10.6 (2.3) years. Body mass index (BMI) z-score and biochemical parameters (serum low-density lipoprotein (LDL) cholesterol, triglycerides and uric acid and homeostasis model assessment to quantify insulin resistance (HOMA index)) were assessed at baseline and at the end of a median follow-up of 14.7 (12.4, 19.3) months. Throughout follow-up, all children received a non-pharmacological treatment based on increased physical activity, reduced sedentary activity and administration of a personalized, healthy and balanced diet. All children attended periodic quarterly control visits during follow-up. Multivariable statistical analyses showed that each BMI z-score point reduction at follow-up was associated with an 8.9 (95% CI −14.2; −3.6) mg/dL decrease in LDL cholesterol (p = 0.001), 20.4 (95% CI −30.0; −10.7) mg/dL in triglycerides (p < 0.001), 1.6 (95% CI −2.2; −1.0) in HOMA index (p < 0.001), and 0.42 (95% CI −0.66; −0.18) mg/dL in uric acid (p = 0.001) values. At each reduction of the BMI z-score by one point, the odds of presenting with insulin resistance and hyperuricemia at follow-up significantly decreased (OR 0.23, 95% CI 0.10−0.50, and OR 0.32, 95% CI 0.10−0.95, p < 0.001 and p < 0.05, respectively). Improvement of dietary habits and lifestyles may improve lipid and glycemic profiles and serum uric acid values in a pediatric population.
Hyperuricemia has been shown to be a strong correlate of hypertension in children. However, the complex interaction between serum uric acid (UA), systemic blood pressure (BP), and possibly ...confounding factors has been elucidated only in part.
We evaluated office BP as well as clinical and biohumoral parameters in a cross-sectional cohort of 501 children (280 boys and 221 girls) aged between 6 and 18 years (mean = 10.8 years) consecutively referred for cardiovascular risk assessment.
Overall, 156 (31.1%) were normotensive, 122 (24.4%) showed transient hypertension, 87 (17.4%) had prehypertension, and 136 (27.1%) had hypertension. Altogether 33.3% and 40.5% of the study group were overweight or obese, respectively. There was a trend toward greater weight and waist circumference and higher BMI, Homeostasis Model Assessment index, and UA levels as the BP categories rose. Moreover, the prevalence of pubertal children, obesity, and waist-to-height ratio above 0.50 progressively increased from lower to upper BP categories. After adjusting for puberty, gender, BMI (z-score), Homeostasis Model Assessment index, and renal function, UA was found to be directly related to systolic and diastolic BP values (P = .03). Using normotensive children for comparison, the risk of showing prehypertension or hypertension increased by at least 50% for each 1 mg/dL UA increase (P < .01), whereas it doubled for children in the top gender-specific UA quartile (P < .03).
Increased UA levels showed an independent predictive power for the presence of higher BP levels among a cohort of children at relatively high cardiovascular risk.
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