Search

Background Dopaminergic symptoms may be extremely pronounced in some migraine patients during the attack, representing a major source of disability. Objectives We aimed to carefully characterize the clinical picture of migraine patients with dopaminergic symptoms in a large patients’ population as a putative migraine endophenotype, allowing more precise disease management, treatment and outcome prediction. Methods We screened 1148 consecutive tertiary care episodic and chronic migraine patients with face-to-face interviews collecting thorough data on lifestyle, socio-demographic factors, and clinical migraine features. Results We identified 374 patients with migraine with dopaminergic symptoms (32.6%). The most frequent dopaminergic symptom was yawning followed by somnolence, nausea, vomiting, fatigue, mood changes and diuresis. Migraine patients with dopaminergic symptoms had longer attack duration (OR: 1.82; 95% CI: 1.41–2.36, p Conclusions Migraine patients with dopaminergic symptoms are characterized by a full-blown, more disabling migraine. Dopaminergic system modulation should be carefully considered in individuals with migraine with dopaminergic symptoms for both acute and preventative treatments in future ad hoc designed studies.

Aristotelia chilensis (Mol.) Stuntz, commonly called “maqui” is a native tree of Chile considered sacred for the Mapuche people. The fruits are sweet blackberries with a high concentration of polyphenols which stain the hands and mouth when eaten. The Mapuche people use it for creating "chicha" an alcoholic beverage, while leaves are used to treat infected wounds, inflammation and ulcers. In this review, we will give an overview of the pharmacology reported for the plant and molecules isolated from leaves and fruits, with the scope of giving a better understanding of the potential of this tree.

Dopamine-beta-hydroxylase (DBH) enzyme activity is modulated at the genetic level by the presence of several polymorphisms. Among these, the 19-bp insertion/deletion (I/D) polymorphism (rs72393728/rs141116007) was investigated in several genetic association studies for its correlation with the susceptibility to develop episodic migraine, but conflicting results were achieved. In the present study we analyzed this genetic variant in a carefully characterized population of migraineurs encompassing both episodic and chronic migraine (with and without medication overuse) with the aim to perform a replication study and verify any possible correlation with migraine endophenotypes. Genotyping of the DBH 19-bp I/D polymorphism was performed on 400 migraine patients and 204 healthy individuals. The associations between genotypic frequencies and the clinical and sociodemographic features of migraineurs were then investigated. The DBH 19-bp I/D polymorphism did not correlate with migraine susceptibility or most clinical variables, with the exception of a statistically significant correlation within the subgroup of patients affected by chronic migraine were the individuals carrying the deleted (D) allele were significantly more prone to abuse in analgesics. As a result of this finding, the DBH 19-bp I/D polymorphism does not influence migraine susceptibility, but it might contribute to the development of medication overuse in patient with chronic migraine.

White matter hyperintensities (WMHs) in migraine could be related to inflammatory and antioxidant events. The aim of this study is to verify whether migraine patients with WMHs carry a genetic pro-inflammatory/pro-oxidative status. To test this hypothesis, we analyzed lymphotoxin alpha (LTA; rs2071590T and rs2844482G) and superoxide dismutase 1 (SOD1; rs2234694C) and 2 (SOD2; rs4880T) gene polymorphisms (SNPs) in 370 consecutive patients affected by episodic (EM; n = 251) and chronic (CM; n = 119) migraine and in unrelated healthy controls (n = 100). Brain magnetic resonance was available in 183/370 patients. The results obtained show that genotypes and allele frequencies for all tested SNPs did not differ between patients and controls. No association was found between single SNPs or haplotypes and sex, migraine type, cardiovascular risk factors or disorders. Conversely, the LTA rs2071590T (OR = 2.2) and the SOD1 rs2234694C (OR = 4.9) alleles were both associated with WMHs. A four-loci haplotype (TGCT haplotype: rs2071590T/rs2844482G/rs2234694C/rs4880T) was significantly more frequent in migraineurs with WMHs (7 of 38) compared to those without WMHs (4 of 134; OR = 8.7). We may, therefore, conclude by suggesting that that an imbalance between pro-inflammatory/pro-oxidative and antioxidant events in genetically predisposed individuals may influence the development of WMHs.

Artificial Intelligence is providing astonishing results, with medicine being one of its favourite playgrounds. Machine Learning and, in particular, Deep Neural Networks are behind this revolution. Among the most challenging targets of interest in medicine are cancer diagnosis and therapies but, to start this revolution, software tools need to be adapted to cover the new requirements. In this sense, learning tools are becoming a commodity but, to be able to assist doctors on a daily basis, it is essential to fully understand how models can be interpreted. In this survey, we analyse current machine learning models and other in-silico tools as applied to medicine—specifically, to cancer research—and we discuss their interpretability, performance and the input data they are fed with. Artificial neural networks (ANN), logistic regression (LR) and support vector machines (SVM) have been observed to be the preferred models. In addition, convolutional neural networks (CNNs), supported by the rapid development of graphic processing units (GPUs) and high-performance computing (HPC) infrastructures, are gaining importance when image processing is feasible. However, the interpretability of machine learning predictions so that doctors can understand them, trust them and gain useful insights for the clinical practice is still rarely considered, which is a factor that needs to be improved to enhance doctors’ predictive capacity and achieve individualised therapies in the near future.

Tailored treatments for metastatic colorectal cancer (mCRC) have not yet completely evolved due to the variety in response to drugs. Therefore, artificial intelligence has been recently used to develop prognostic and predictive models of treatment response (either activity/efficacy or toxicity) to aid in clinical decision making. In this systematic review, we have examined the ability of learning methods to predict response to chemotherapy alone or combined with targeted therapy in mCRC patients by targeting specific narrative publications in Medline up to April 2022 to identify appropriate original scientific articles. After the literature search, 26 original articles met inclusion and exclusion criteria and were included in the study. Our results show that all investigations conducted on this field have provided generally promising results in predicting the response to therapy or toxic side-effects. By a meta-analytic approach we found that the overall weighted means of the area under the receiver operating characteristic (ROC) curve (AUC) were 0.90, 95% C.I. 0.80–0.95 and 0.83, 95% C.I. 0.74–0.89 in training and validation sets, respectively, indicating a good classification performance in discriminating response vs. non-response. The calculation of overall HR indicates that learning models have strong ability to predict improved survival. Lastly, the delta-radiomics and the 74 gene signatures were able to discriminate response vs. non-response by correctly identifying up to 99% of mCRC patients who were responders and up to 100% of patients who were non-responders. Specifically, when we evaluated the predictive models with tests reaching 80% sensitivity (SE) and 90% specificity (SP), the delta radiomics showed an SE of 99% and an SP of 94% in the training set and an SE of 85% and SP of 92 in the test set, whereas for the 74 gene signatures the SE was 97.6% and the SP 100% in the training set.

Background: Tumor tissue (T) mutational analysis represents the standard for metastatic colorectal cancer (mCRC), however, circulating tumor DNA (ctDNA) detected by liquid biopsy in plasma (PL) can better represent tumor heterogeneity. Methods: mCRC patients undergoing standard first-line chemotherapy with known T-KRAS/NRAS/BRAF status were enrolled in the present prospective study. PL mutations were assessed within 2 weeks before chemotherapy start with real time PCR and correlated with T status and Progression free survival (PFS). Clinical and biochemical variables including also total number of tumor lesions (TNL) and the sum of maximum diameter (SMD) of all lesions were assessed as potential predictors of T/PL discordance. RESULTS: Among 45 enrolled patients, all BRAF mutations were concordant between T and PL and there were 20% of patients RAS discordant: 9% wild type in T and mutated in PL and 11% mutated in T and wild type in PL. T mutations were significantly associated to median PFS (mPFS of 4.5, 8.3 and 22.9 months for T-BRAF mutated, T-RAS mutated, and T-wild type patients, respectively, p for trend 0.00014). PL mutations further refined prognosis: RAS wild type in T and mutated in PL had significantly shorter PFS than concordant RAS wild type in T and PL: mPFS 9.6 vs. 23.3 months, respectively, p = 0.02. Patients RAS mutated in T and wild type in PL had longer PFS than concordant RAS mutated in T and PL: 24.4 vs. 7.8 months, respectively, p = 0.008. At a multivariate cox regression analysis for PFS, PL mutations were independent prognostic factor superior to T analysis (HR 0.13, p = 0.0008). At multivariate logistic regression analysis TNL and SMD were significant predictors of discordant cases. Conclusions: PL mutational analysis allows a better prognostication than T analysis alone and could help in mCRC treatment management.

Objectives: The aim of the present review is to discuss the potential link between RAS, BRAF and microsatellite instability (MSI) mutational patterns and chemotherapeutic agent efficacy [Irinotecan (IRI) vs. Oxaliplatin (OXA)], and how this can potentially influence the choice of the chemotherapy backbone. Methods: Following a review of the research literature, all pertinent articles published in the core journals were selected for the study. The inclusion criteria regarded relevant clinical and pre-clinical studies on the topic of interest (Relationship of OXA and IRI to KRAS/BRAF mutations and MSI). Results: Excision repair cross complementation group 1 (ERCC1) expression is inhibited by KRAS mutation, making tumor cells more sensitive to OXA. Results from OPUS, COIN and PRIME trials support that no conclusive data are available for BRAF mutant population because of the small number of patients. Enhanced IRI cytotoxicity to MSI cell lines is due to the participation of some of the mismatch repair (MMR) components in various DNA repair processes and their role in the maintenance of the pro-apoptotic effect of IRI and G2/M cell arrest. Conclusions: OXA and IRI are indispensable drugs for mCRC treatment and their selection must be as careful as that of targeted agents. We suggest taking into consideration the interaction between known genomic alterations and OXA and IRI activity to personalize chemotherapy in mCRC patients.

Simultaneous care represents the ideal integration between early supportive and palliative care in cancer patients under active antineoplastic treatment. Cancer patients require a composite clinical, social and psychological management that can be effective only if care continuity from hospital to home is guaranteed and if such a care takes place early in the course of the disease, combining standard oncology care and palliative care. In these settings, venous thromboembolism (VTE) represents a difficult medical challenge, for the requirement of acute treatments and for the strong impact on anticancer therapies that might be delayed or, even, totally discontinued. Moreover, cancer patients not only display high rates of VTE occurrence/recurrence but are also more prone to bleeding and this forces clinicians to optimize treatment strategies, balancing between hemorrhages and thrombus formation. VTE prevention is, therefore, regarded as a double-edged sword. Indeed, while on one hand the appropriate use of antithrombotic agents can reduce VTE occurrence, on the other it significantly increases the bleeding risk, especially in the frail patients who present with multiple co-morbidities and poly-therapy that can interact with anticoagulant drugs. For these reasons, thromboprophylaxis should start while active cancer treatment is ongoing, according to a simultaneous care model in a patient-centered perspective.

Venous thromboembolism (VTE) is a compelling challenge across all phases of cancer care as it may result in treatment delays, impaired quality of life (QoL), and increased mortality [...]

The hypothesis that increased oxidative stress in breast cancer (BC) patients could induce enhanced lipid peroxidation, which, in turn, would contribute to platelet activation and poor clinical outcome is attractive. To address this issue, we investigated pre-surgical urinary 8-iso-prostaglandin (PG)F2α (marker of in vivo oxidative stress) and 11-dehydro-thromboxane (TX)B2 (marker of in vivo platelet activation) levels in patients with primary BC (n = 115) compared with control women paired for comorbidities and their association with patients' metabolic profile and clinical prognostic factors. The results obtained showed that presurgical urinary excretion of both biomarkers was enhanced in BC patients compared to controls and was associated with patients' estrogen receptor (ER) expression, but not HER2 status or Ki67 proliferation index. Accordingly, both urinary biomarkers were increased in patients with luminal-like BC molecular subtypes compared with triple negative or HER2-enriched tumors. ER status was an independent predictor of 8-iso-PGF2α urinary levels, which, in turn, significantly predicted 11-dehydro-TXB2 urinary levels together with disease stage and ER status. The prognostic value of 11-dehydro-TXB2 was then evaluated showing a significant correlation with BC pathological response to neoadjuvant treatment. Furthermore, among relapsing patients, those with elevated urinary biomarker levels were more likely to develop distant metastasis rather than local recurrence. In conclusion, we may speculate that enhanced oxidative stress due to estrogen-related mechanisms might cause a condition of persistent platelet activation capable of sustaining BC growth and progression through the release of bioactive stored molecules, ultimately contributing to tumor invasiveness. Further studies specifically addressing this hypothesis are presently needed.

Background and objective Community-acquired pneumonia (CAP) is associated with an increased risk of arterial and venous thrombosis but the underlying pathophysiological mechanisms are still unclear. We investigated if, in patients with CAP, a pro-thrombotic state does exist and its relationship with serum levels of endotoxins. Methods A total of 104 consecutive patients with CAP were prospectively recruited and followed up until discharge. At admission and at discharge, serum endotoxins, systemic markers of clotting activation and zonulin, a marker of gut permeability, were analysed. Hospitalized patients matched for gender, age and comorbidities but without infections were used as control. Results At admission, CAP patients showed higher plasma levels of F1 +2, a marker of thrombin generation (P = 0.023), and lower levels of protein C (PC; P

Risk prediction of chemotherapy-associated venous thromboembolism (VTE) is a compelling challenge in contemporary oncology, as VTE may result in treatment delays, impaired quality of life, and increased mortality. Current guidelines do not recommend thromboprophylaxis for primary prevention, but assessment of the patient’s individual risk of VTE prior to chemotherapy is generally advocated. In recent years, efforts have been devoted to building accurate predictive tools for VTE risk assessment in cancer patients. This review focuses on candidate biomarkers and prediction models currently under investigation, considering their advantages and disadvantages, and discussing their diagnostic performance and potential pitfalls.

Machine learning (ML) has been recently introduced to develop prognostic classification models that can be used to predict outcomes in individual cancer patients. Here, we report the significance of an ML-based decision support system (DSS), combined with random optimization (RO), to extract prognostic information from routinely collected demographic, clinical and biochemical data of breast cancer (BC) patients. A DSS model was developed in a training set (n = 318), whose performance analysis in the testing set (n = 136) resulted in a C-index for progression-free survival of 0.84, with an accuracy of 86%. Furthermore, the model was capable of stratifying the testing set into two groups of patients with low- or high-risk of progression with a hazard ratio (HR) of 10.9 (p < 0.0001). Validation in multicenter prospective studies and appropriate management of privacy issues in relation to digital electronic health records (EHR) data are presently needed. Nonetheless, we may conclude that the implementation of ML algorithms and RO models into EHR data might help to achieve prognostic information, and has the potential to revolutionize the practice of personalized medicine.

Migraine is a common multifactorial and polygenic neurological disabling disorder characterized by a genetic background and associated to environmental, hormonal and food stimulations. A large series of evidence suggest a strong correlation between nutrition and migraine and indicates several commonly foods, food additives and beverages that may be involved in the mechanisms triggering the headache attack in migraine-susceptible persons. There are foods and drinks, or ingredients of the same, that can trigger the migraine crisis as well as some foods play a protective function depending on the specific genetic sensitivity of the subject. The recent biotechnological advances have enhanced the identification of some genetic factors involved in onset diseases and the identification of sequence variants of genes responsible for the individual sensitivity to migraine trigger-foods. Therefore many studies are aimed at the analysis of polymorphisms of genes coding for the enzymes involved in the metabolism of food factors in order to clarify the different ways in which people respond to foods based on their genetic constitution. This review discusses the latest knowledge and scientific evidence of the role of gene variants and nutrients, food additives and nutraceuticals interactions in migraine.

SummaryAmong the possible genetic contributors to cancer-related venous thromboembolism (VTE), vascular endothelial growth factor (VEGFA) could play an important role, as an imbalance of the VEGFA system (either disease-related or drug-induced) may result in a disturbance of vascular homeostasis. Thus, this study was designed to investigate the predictive role of eight different VEGFA gene promoter single nucleotide polymorphisms (SNPs) for a first VTE episode in cancer out-patients undergoing chemotherapy. To this purpose, VEGFA gene promoter polymorphisms were analysed in 297 cancer patients using polymerase chain reaction amplification and direct DNA sequencing analysis. One hundred forty unrelated healthy subjects from the same geographical area were also analysed in order to evaluate and compare genotype/haplotype frequencies in our ethnicity. VTE occurred in 26 (9 %) of cancer patients with a median time-to-event of 3.4 months. Association analyses showed that –1154G/A polymorphism was significantly associated with the risk of chemotherapy-triggered VTE, with the A allele exerting a protective role both in the overall population (hazard ratio [HR]: 0.21; 95 % confidence interval [CI]: 0.07–0.58) or in bevacizumab-treated metastatic patients (HR: 0.09, 95 %CI: 0.01–0.86) in whom VEGFA –1154AA genotype also conferred a reduced risk of early progression (HR: 0.58, 95 %CI: 0.34–0.98). These results suggest that VEGFA may represent a candidate gene contributing to VTE development in chemotherapy treated cancer patients and that –1154G/A SNP might provide useful clinical information on the efficacy and toxicity of bevacizumab in metastatic patients. Validation studies are needed for translation into clinical practice.Note: This study has been presented in part at the Congress on Controversies in Thrombosis & Haemostasis, Berlin, Germany, October 30-November 1, 2014.

Background: Migraine is the most common neurological disorder and the second most disabling human condition, whose pathogenesis is favored by a combination of genetic, epigenetic, and environmental factors. In recent years, several efforts have been made to identify reliable biomarker(s) useful to monitor disease activity and/or ascertain the response to a specific treatment. Objective: To review the current evidence on the potential biological markers associated with migraine. Methods: A structured search of peer-reviewed research literature was performed by searching major publications databases up to December 2017. Results: Several circulating biomarkers have been proposed as diagnostic or therapeutic tools in migraine, mostly related to migraine’s inflammatory pathophysiological aspects. Nonetheless, their detection is still a challenge for the scientific community, reflecting, at least in part, disease complexity and clinical diagnostic limitations. At the present time, calcitonin generelated peptide (CGRP) represents probably the most promising candidate as a diagnostic and/or therapeutic biomarker, as its plasma levels are elevated during migraine attack and decrease during successful treatment. Other molecules (including some neuropeptides, cytokines, adipokines, or vascular activation markers) despite promising, do not possess the sufficient prerequisites to be considered as migraine biomarkers. Conclusion: The characterization of migraine-specific biomarkers would be fundamental in a perspective of precision medicine, enabling risk assessment and tailored treatments. However, speculating on the clinical validity of migraine biomarkers may be premature and controlled clinical trials are presently needed to investigate both the diagnostic and therapeutic value of these biomarkers in migraine.

Background/aim To investigate whether neutrophil-to-lymphocyte ratio (NLR) might represent an additional biological criterion able to identify patients with worse prognosis within the 8th edition TNM prognostic staging system for breast cancer (BC). Patients and methods Pre-treatment NLR was retrospectively analyzed in 475 BC women prospectively followed for a mean time of 3.8 years. The optimal NLR cutoff, identified by ROC analysis, was set at 2. Results Elevated pre-treatment NLR was associated with worse disease-free survival (DFS) (HR=2.28) and overall survival (OS) (HR=3.39). The prognostic value of NLR was mostly evident in stage I BC (HR for DFS=2.89; HR for OS=1.30), in whom NLR significantly stratified patients who developed distant metastasis (HR= 4.62), but not local recurrence. Conclusion NLR might provide important information in risk stratification, especially in stage I BC patients in whom the presence of a high NLR might raise the question as to whether they should be more aggressively managed.

Migraine represents the third most prevalent and the seventh most disabling human disorder. Approximately 30% of migraine patients experience transient, fully reversible, focal neurological symptoms (aura) preceding the attack. Recent Advances: Awareness of the hypothesis that migraine actually embodies a spectrum of illnesses-ranging from episodic to chronic forms-is progressively increasing and poses novel challenges for clarifying the underlying pathophysiological mechanisms of migraine as well as for the development of novel therapeutic interventions. Several theories have evolved to the current concept that a combination of genetic, epigenetic, and environmental factors may play a role in migraine pathogenesis, although their relative importance is still being debated.One critical issue that deserves a particular attention is the role of oxidative stress in migraine. Indeed, potentially harmful oxidative events occur during the migraine attack and long-lasting or frequent migraine episodes may increase brain exposure to oxidative events that can lead to chronic transformation. Moreover, a wide variety of dietary, environmental, physiological, behavioral, and pharmacological migraine triggers may act through oxidative stress, with clear implications for migraine treatment and prophylaxis. Interestingly, almost all current prophylactic migraine agents exert antioxidant effects.Increasing awareness of the role of oxidative stress and/or decreased antioxidant defenses in migraine pathogenesis and progression to a chronic condition lays the foundations for the design of novel prophylactic approaches, which, by reducing brain oxidative phenomena, could favorably modify the clinical course of migraine. Antioxid. Redox Signal. 28, 1144-1183.

Venous thromboembolism (VTE) is a commonly diagnosed multifactorial condition with significant morbidity and mortality, occurring in up to 20% of cancer patients. Indeed, patients with cancer are in a higher pro-thrombotic state due to alterations in their haemostatic-coagulative system, stasis and blood flow slowdown, endothelial dysfunction, vascular inflammation and platelet activation. Moreover, several cancer-dependent factors can sum up to trigger a first episode of VTE or to cause its recurrence in the course of anticoagulant treatment. Such a pro-thrombotic condition is further worsened by additional favoring risks such as immobilization, infection, surgery, or insertion of a central venous catheter, and anti-cancer therapy. Furthermore, in the secondary prevention setting, the anticoagulant therapy is accompanied by a high incidence of bleeding complications. Given the above, understanding and identifying the factors associated with the incidence and clinical outcome of VTE in cancer patients might be of great value in the prevention and management of VTE-attributable complications, including death. Differences associated to gender on cancer-related VTEs are not yet fully defined; many of the studies that addressed the question have been biased by erroneous/non homogeneous inclusion criteria. In the present review, we analyzed the potential differences in VTEs occurrence in cancer patients, by reporting the most significant findings in the recent literature. The identification of a differential clinical approach according to patient sex, might prompt the design of personalized treatment options tailored and optimized according to algorithms for oncological VTE prevention.

Neutrophil/lymphocyte (NLR) and platelet/lymphocyte (PLR) ratios might represent a yet unrecognized risk factor for venous thromboembolism (VTE) in cancer out-patients receiving chemotherapy. Accordingly, this study was aimed at analyzing the significance of these novel markers in the risk prediction of a first VTE episode in a population representative of a general practice cohort. To this purpose, a mono-institutional cohort study was conducted to retrospectively analyze NLR and PLR in 810 consecutive cancer out-patients with primary or relapsing solid cancer at the start of a new chemotherapy regimen. Over a median follow-up of 9.2 months, VTE occurred in 6.7% of patients. Incidental VTE was diagnosed at time of restaging in 47% of cases. Median pre-chemotherapy NLR (p = 0.015) and PLR (p = 0.040) were significantly higher in patients with intermediate risk class who developed symptomatic VTE with a twofold increased VTE risk for both inflammation-based markers (NLR: p = 0.022; PLR: p = 0.037) and a worst 1-year VTE-free survival for patients with high NLR or PLR. However, only PLR (HR = 2.4, p = 0.027) confirmed to be an independent predictor of future VTE in patients in the intermediate risk class in multivariate analysis, together with ECOG performance status (HR = 3.4, p = 0.0002) and bevacizumab use (HR = 4.7, p = 0.012). We may, thus, conclude that PLR, but to a lesser extent NLR, could represent useful clinical predictors of VTE, especially in selected categories of patients such as those in the intermediate risk class in whom the assessment of PLR could allow a better risk stratification of VTE without additional costs to the national health systems.

Background. Reduced estimated glomerular filtration rate (eGFR) has been associated with increased venous thromboembolism (VTE) risk in the general population. VTE incidence significantly increases in cancer patients, especially those undergoing chemotherapy. Despite the evidence that a substantial number of cancer patients have unrecognized renal impairment, as indicated by reduced eGFR in the presence of serum creatinine levels within the reference value, chemotherapy dosage is routinely adjusted for serum creatinine values. Among chemotherapies, platinum-based regimens are associated with the highest rates of VTE. A cohort study was designed to assess the value of pretreatment eGFR in the risk prediction of a first VTE episode in cancer outpatients without previous history of VTE who were scheduled for platinum-based chemotherapy. Methods. Serum creatinine and eGFR were evaluated before the start of standard platinum-based chemotherapy in a cohort of 322 consecutive patients with primary or relapsing/recurrent solid cancers, representative of a general practice population. Results. Patients who experienced a first VTE episode in the course of chemotherapy had lower mean eGFR values compared with patients who remained VTE free. Multivariate Cox analysis demonstrated that eGFR had an independent value for risk prediction of a first VTE episode during treatment, with a 3.15 hazard ratio. Indeed, 14% of patients with reduced eGFR had VTE over 1-year follow-up compared with 6% of patients with normal eGFR values. Conclusion. The results suggest that reductions in eGFR, even in the presence of normal serum creatinine, are associated with an increased VTE risk in cancer outpatients undergoing platinum-based chemotherapy regimens. Determining eGFR before chemotherapy could represent a simple predictor of VTE, at no additional cost to health care systems.

Aim: In the present case–control study, we investigated the correlation between the common ACE insertion/deletion (I/D) polymorphism and migraine. Materials & methods: Genotyping of the ACE I/D variant was performed in 502 Caucasian patients with migraine and 323 age-, sex- and race/ethnicity-matched healthy controls. We investigated associations between ACE genetic variants and sociodemographic and/or clinical features of migraineurs. Results: We found a significant association between ACE insertion/insertion (I/I) polymorphism and lower use of pharmacological prophylaxis in migraine patients with aura and in those with chronic migraine. Moreover, ACE I/I polymorphism was significantly more common in migraine patients with aura who had a negative family history of migraine. Conclusion: Our data suggest that although the ACE I/D polymorphism is not a direct risk factor for migraine, the ACE I/I genotype may influence the clinical feature of this disease being associated with reduced use of prophylactic agents in patients with migraine with aura and in those with chronic migraine. Original submitted 5 June 2013; Revision submitted 16 September 2013

Data on the relationship between aging, chemotherapy, and risk for venous thromboembolism (VTE) are controversial. We sought to evaluate the risk of chemotherapy-associated VTE in young to middle-aged (YMA) and elderly cancer patients and to analyze the VTE-free survival time in both groups. Patients with histologically confirmed diagnosis of solid malignancy receiving any type of systemic chemotherapy, no clinical diagnosis of VTE before chemotherapy initiation, and Eastern Cooperative Oncology Group (ECOG) performance status (PS) ≤2 were enrolled in this study. Of the 486 consecutive patients included in the study, 380 (78%) were classified as YMA (≤70 years of age) and 106 (22%) as elderly (>70 years of age). At a median follow-up of 1 year, the incidence of VTE events was almost two-fold greater in elderly than in YMA (11% vs. 6%). Age (≤70 years vs. >70 years (hazard ratio [HR], 2.42; 95% confidence interval [CI] 1.15-5.06; p=0.020), ECOG-PS (HR, 6.54; 95% CI 3.10-13.8; p

Thiazolidinediones (TZDs) represent a class of peroxisome proliferator-activated receptor (PPAR)γ agonists widely used as insulin-sensitizers in the treatment of type 2 diabetes mellitus (T2DM). The beneficial effects of hypoglycemic drugs, including TZDs, on the hemostatic abnormalities associated to T2DM have been formerly related to improved metabolic control, rather than to direct effects. However, in recent years the pleiotropic effects of PPARγ agonists on hemostatic function have become evident. In particular, the role of platelets as a pivotal player in diabetes complications by stimulating and sustaining inflammation has been lately acknowledged. Upon activation platelets synthesize and release many bioactive substances such as thromboxane A2 (TXA2) or pro-inflammatory mediators including CD40 ligand (CD40L) that exert autocrine and paracrine activation processes in vascular inflammation leading to cardiovascular disease (CVD). Although PPARγ is a nuclear hormone receptor, anucleate platelets also highly express this receptor and treatment with synthetic PPARγ ligands dampens the release of soluble(s)CD40L and TXA2 in thrombin-activated platelets. Moreover, PPARγ through Sirtuin1 pathway has been implicated in modulating inflammatory and atherosclerotic processes in patients with T2DM. Therefore, in T2DM, where platelet activation contributes to the pathogenesis of CVD, TZDs may have an enhanced therapeutic role, despite some potentially serious adverse side effects. This review will discuss the pleiotropic effects of PPARγ treatment on the hemostatic abnormalities associated with T2DM, with particular focus on platelet activation.

Chemotherapy has been associated with an increased risk of venous thromboembolism (VTE). However, the prevalence of coagulation abnormalities or VTE occurrence as a consequence of different anti-cancer agents or treatment schemes is largely uncharacterized. Thus, this study was aimed at analyzing the impact of different anticancer drugs on the prothrombotic status of cancer out-patients scheduled for chemotherapy. To this purpose, a mono-institutional study was prospectively conducted to monitor serial changes of activated protein C (APC) function in 505 consecutive cancer out-patients with primary or relapsing solid cancer at the start of a new chemotherapy regimen. The results obtained showed that age >65 years (p = 0.01), ECOG performance status (p = 0.01), platinum-based (p = 0.035) and fluoropyrimidine-based regimens (p = 0.008) were independent predictors of an acquired APC resistance during the first chemotherapy cycle. Multivariate model of Cox proportional hazards survival analysis demonstrated that a decline in APC functionality (HR = 2.4; p = 0.013) and platinum-based regimens (HR = 2.2; p = 0.042) were both capable of predicting the occurrence of a first VTE episode during chemotherapy. Indeed, 14% of patients with platinum-associated APC impairment had VTE over a 1-year follow-up, compared to 3% of patients treated with other regimens and in whom APC functionality remained stable (HR = 1.5; p = 0.003). We may, thus, conclude that use of platinum-based regimens is responsible for induction of an acquired thrombophilic condition and represents a predictor for VTE even after adjustment for other risk factors.

Evaluating disease progression risk is a key issue in medicine that has been revolutionized by the advent of machine learning approaches and the wide availability of medical data in electronic form. It is time to provide physicians with near-to-the-clinical-practice and effective tools to spread this important technological innovation. In this paper, we describe RISK, a web service that implements a multiple kernel learning approach for predicting breast cancer disease progression. We report on the experience of the BIBIOFAR project where RISK Web Predictor has been developed and tested. Results of our system demonstrate that this kind of approaches can effectively support physicians in the evaluation of risk.

Migraine has been associated with an increased risk for stroke, especially in young women.1 Among the pathophysiologic mechanisms linking migraine and stroke, coagulation abnormalities have been regarded as a logical link.2

Using kernel machine learning (ML) and random optimization (RO) techniques, we recently developed a set of venous thromboembolism (VTE) risk predictors, which could be useful to devise a web interface for VTE risk stratification in chemotherapy-treated cancer patients. This study was designed to validate a model incorporating the two best predictors and to compare their combined performance with that of the currently recommended Khorana score (KS). Age, sex, tumor site/stage, hematological attributes, blood lipids, glycemic indexes, liver and kidney function, BMI, performance status, and supportive and anticancer drugs of 608 cancer outpatients were all entered in the model, with numerical attributes analyzed as continuous values. VTE rate was 7.1%. The VTE risk prediction performance of the combined model resulted in 2.30 positive likelihood ratio (+LR), 0.46 negative LR (−LR), and 4.88 HR (95% CI: 2.54–9.37), with a significant improvement over the KS [HR 1.73 (95% CI: 0.47–6.37)]. These results confirm that a ML approach might be of clinical value for VTE risk stratification in chemotherapy-treated cancer outpatients and suggest that the ML-RO model proposed could be useful to design a web service able to provide physicians with a graphical interface helping in the critical phase of decision making.

The development of Biobanks and recent advances in molecular biology have enhanced the possibility to accelerate translational research studies. The Interinstitutional Multidisciplinary BioBank (BioBIM) is organized in a large healthy donors collection and pathology-based biobanks with the aim to provide a service for development of interdisciplinary studies. A new pathology-based biobank has been organized to specifically collect biospecimen from patients affected by migraine, with the final goal to centralize data, collect blood, plasma, serum, DNA and RNA of patients with this disease. The BioBIM is fully equipped for the automation of sampling/processing, storage and tracking of biospecimens. Standard Operating Procedures have been developed for processing and storage phases as well as archive of clinical data. The availability of biospecimens and clinical data will constitute a resource for various research projects.

BACKGROUND: High Neutrophil/Lymphocyte ratio (NLR), as a measure of enhanced inflammatory response, has been negatively associated with prognosis in patients with localized pancreatic ductal adenocarcinoma (PDA). OBJECTIVE: In the present study, we aimed at investigating the prognostic value of NLR in two homogeneous groups of chemotherapy-na've metastatic PDA patients. Patients were treated with either gemcitabine (GEM) or gemcitabine/ oxaliplatin (GEMOXA). We also assessed whether NLR could identify patients benefiting from the use of oxaliplatin. METHODS: Consecutive PDA patients treated at the Medical Oncology Unit of Tor Vergata University Hospital of Rome with either GEM or GEMOXA were included (n = 103). NLR was assessed before and during chemotherapy and correlated with outcome together with common clinical and biochemical variables. RESULTS: Among 17 analyzed variables NLR, Karhofsky Perfomance Status (KPS), d-dimer and erythrocyte sedimentation rate were found to be significantly associated with median Overall Survival (mOS) at the univariate analysis. Only NLR and KPS were independent prognosticator at multivariate analysis, with NLR displaying the highest statistical significance. NLR was also predictive of oxaliplatin activity, as only patients with NLR > 2.5 (cutoff determined upon ROC analysis) derived benefit from GEMOXA over GEM. CONCLUSIONS: NLR is both an independent prognostic and predictive factor in metastatic PDA, since only patients with high NLR seem to benefit from the addition of oxaliplatin. NLR may help select patients for whom a particularly poor prognosis might justify more intensive, yet less tolerable, combination regimens.

To design a precision medicine approach aimed at exploiting significant patterns in data, in order to produce venous thromboembolism (VTE) risk predictors for cancer outpatients that might be of advantage over the currently recommended model (Khorana score).Multiple kernel learning (MKL) based on support vector machines and random optimization (RO) models were used to produce VTE risk predictors (referred to as machine learning [ML]-RO) yielding the best classification performance over a training (3-fold cross-validation) and testing set.Attributes of the patient data set ( n = 1179) were clustered into 9 groups according to clinical significance. Our analysis produced 6 ML-RO models in the training set, which yielded better likelihood ratios (LRs) than baseline models. Of interest, the most significant LRs were observed in 2 ML-RO approaches not including the Khorana score (ML-RO-2: positive likelihood ratio [+LR] = 1.68, negative likelihood ratio [-LR] = 0.24; ML-RO-3: +LR = 1.64, -LR = 0.37). The enhanced performance of ML-RO approaches over the Khorana score was further confirmed by the analysis of the areas under the Precision-Recall curve (AUCPR), and the approaches were superior in the ML-RO approaches (best performances: ML-RO-2: AUCPR = 0.212; ML-RO-3-K: AUCPR = 0.146) compared with the Khorana score (AUCPR = 0.096). Of interest, the best-fitting model was ML-RO-2, in which blood lipids and body mass index/performance status retained the strongest weights, with a weaker association with tumor site/stage and drugs.Although the monocentric validation of the presented predictors might represent a limitation, these results demonstrate that a model based on MKL and RO may represent a novel methodological approach to derive VTE risk classifiers. Moreover, this study highlights the advantages of optimizing the relative importance of groups of clinical attributes in the selection of VTE risk predictors.