Statistical learning methodology for the prognosis of B-chronic lymphocytic leukemia (B-CLL) using flow cytometry data

B-Chronic Lymphocytic Leukemia (B-CLL) is known to be the most common type of leukemia in the Western world. Its prognosis remains one of the most interesting decision problems in clinical research and practice. Various clinical and laboratory factors are known to be associated with the evolution of the disease. However, for the parameters obtained by flow cytometry analysis that are traditionally utilized as the cornerstone during the diagnosis procedure of the disease, whether they offer additional prognostic information is an open issue. In this dissertation, we propose a decision support system to the hematologists, that provides multiparametric B-CLL patients’ prognosis, combining the usage of diverse heterogeneous factors (clinical, laboratory and flow cytometry) associated with the disease. B-CLL diagnosis is primarily derived from the study of the antigenic phenotype of the patients’ blood cells, which is held with flow cytometry analysis. Despite the fact that the method of the analysis is well defined, the process traditionally followed by the laboratory experts is characterized by amounts of inexactness and subjectivity. As flow cytometry technology advances rapidly, the need for adequate automated (computer-assisted) analysis methodologies on the data it produces is accordingly increasing. In this context, we present a useful paradigm of automated analysis of flow cytometry data that does not require the direct supervision of the expert, for B-CLL patients’ diagnosis. The values of the flow cytometry characteristic parameters extracted by applying the proposed methodology are afterward incorporated to the prognostic system for B-CLL mentioned above. By reducing the B-CLL prognosis problem to an instance of the pattern classification problem, as well as by simulating each step of the B-CLL diagnosis procedure with an instance of the data classification problem, we proceeded with applying statistical learning techniques. We focused on Bayesian network methodologies and utilized the naïve-Bayes model for both cases, in its supervised and unsupervised version, respectively. The characteristics of the data (especially of the flow cytometry ones) generated by a pathological underlying mechanism, like the disease’s one, did not encourage the direct use of the above model. Therefore, we combined the naïve-Bayes model with a set of suitable heuristic algorithmic procedures to obtain better results, not only with respect to some commonly used algorithmic optimality metrics, but also by considering the experts’ opinion. Due to their ability of incorporating the expert knowledge as a priori initial information to their learning methods, Bayesian methodologies are considered as the most appropriate ones to make use of in such types of applications.Η Β-χρόνια λεμφογενής λευχαιμία (Β-ΧΛΛ) αποτελεί τον πιο κοινό τύπο λευχαιμίας στο Δυτικό κόσμο. Η πρόγνωσή της θεωρείται ως ένα από τα πιο ενδιαφέροντα προβλήματα απόφασης στην κλινική έρευνα και πρακτική. Για διάφορους κλινικούς και εργαστηριακούς δείκτες είναι γνωστό ότι σχετίζονται με την εξέλιξη της νόσου. Για τις παραμέτρους, όμως, που εξάγονται με ανάλυση κυτταρομετρίας ροής, οι οποίες αποτελούν τον ακρογωνιαίο λίθο της διαδικασίας διάγνωσης της νόσου, το αν προσφέρουν επιπρόσθετη προγνωστική πληροφορία αποτελεί ανοιχτό πρόβλημα. Στη διατριβή αυτή προτείνουμε ένα σύστημα υποβοήθησης για τις αποφάσεις των ειδικών του πεδίου, το οποίο πραγματοποιεί πολυπαραμετρική πρόγνωση ασθενών με Β-ΧΛΛ, συνδυάζοντας τη χρήση ποικίλων ετερογενών προγνωστικών δεικτών (κλινικών, εργαστηριακών και κυτταρομετρίας ροής) που σχετίζονται με τη νόσο. Η διάγνωση της Β-ΧΛΛ βασίζεται κυρίως στη μελέτη του αντιγονικού φαινότυπου των κυττάρων των ασθενών, η οποία διενεργείται με κυτταρομετρία ροής. Αν και η διαδικασία που ακολουθείται κατά την ανάλυση αυτή είναι σαφώς ορισμένη, ο τρόπος με τον οποίο οι εργαστηριακοί υπεύθυνοι την πραγματοποιούν παραδοσιακά χαρακτηρίζεται από ανακρίβεια και υποκειμενικότητα. Καθώς η τεχνολογία της κυτταρομετρίας ροής εξελίσσεται ραγδαία, γίνεται όλο και πιο επιτακτική η ανάγκη για την ανάπτυξη αυτοματοποιημένων μεθόδων ανάλυσης των δεδομένων που παράγει. Σε αυτά τα πλαίσια, παρουσιάζουμε ένα χρήσιμο παράδειγμα αυτοματοποιημένης ανάλυσης κυτταρομετρικών δεδομένων, η οποία δεν απαιτεί την άμεση επίβλεψη των ειδικών, για τη διάγνωση ασθενών με Β-ΧΛΛ. Οι τιμές των χαρακτηριστικών παραμέτρων που εξάγονται με εφαρμογή της προτεινόμενης μεθοδολογίας, ενσωματώνονται κατόπιν στο προαναφερθέν προγνωστικό σύστημα. Ανάγοντας το πρόβλημα της πρόγνωσης της Β-ΧΛΛ σε ένα στιγμιότυπο ταξινόμησης προτύπων, καθώς και προσομοιώνοντας κάθε ένα από τα βήματα της διαδικασίας της διάγνωσης της νόσου με ένα στιγμιότυπο συσταδοποίησης δεδομένων, αντιμετωπίσαμε τα δύο προβλήματα εφαρμόζοντας τεχνικές στατιστικής μάθησης. Εστιάσαμε σε μεθοδολογίες δικτύων πεποίθησης, χρησιμοποιώντας συγκεκριμένα το naïve-Bayes μοντέλο και για τις δύο περιπτώσεις, στην επιβλεπόμενη και στη μη επιβλεπόμενη εκδοχή του, αντίστοιχα. Τα χαρακτηριστικά και η φύση των δεδομένων (κυρίως των κυτταρομετρικών) που παράγονται από έναν παθολογικό υποκείμενο μηχανισμό, όπως αυτός της νόσου, δεν ευνοούν την απευθείας εφαρμογή του παραπάνω μοντέλου στο εκάστοτε στιγμιότυπο. Για το λόγο αυτό, συνδυάσαμε την εφαρμογή του naïve-Bayes μοντέλου με κατάλληλες ευρετικές αλγοριθμικές διαδικασίες, για την επίτευξη καλύτερων αποτελεσμάτων, με κριτήριο βέλτιστου όχι μόνο κάποιες συχνά χρησιμοποιούμενες μετρικές αποτίμησης αλγόριθμων, αλλά και τη γνώμη των αιματολόγων. Χάρη στην ιδιότητά τους να ενσωματώνουν την έμπειρη γνώση των ειδικών ως εκ των προτέρων πληροφορία αρχικοποίησης των μεθόδων μάθησής τους, οι Bayesian μεθοδολογίες κρίνονται ως οι πλέον κατάλληλες για την εφαρμογή τους σε τέτοιου τύπου προβλήματα

Long-Term Results of Combination Treatment with Single-Dose Ranibizumab plus Photodynamic Therapy for Retinal Angiomatous Proliferation

Purpose: To present functional and anatomic outcomes of combination therapy with ranibizumab and photodynamic therapy (PDT) in a series of retinal angiomatous proliferation (RAP) cases. Methods: A total of 17 eyes of 17 patients with RAP were included. Thirteen eyes were treatment naive and 4 were already on ranibizumab monotherapy. Combined treatment with single-dose ranibizumab and PDT was performed on all treatment-naive cases. Follow-up was performed every month for 6-38 months, using optical coherence tomography and indocyanine green angiography when necessary. Results: Overall, 6 out of 7 treatment-naive cases with stage I or II disease manifested complete angiographic resolution of the hot spot with a single injection of ranibizumab plus PDT. In stage III disease, 7 out of 10 eyes showed persistent leakage immediately after the combined treatment. The rate of hot spot occlusion was found to correlate with the stage of disease (p = 0.05). There was a significant improvement in posttreatment BCVA for all patients regardless of disease stage (p = 0.02), which was more evident in the earlier stages. Improvement was also greater for treatment-naive patients (p = 0.03). The posttreatment improvement in BCVA was strongly correlated with hot spot occlusion (p < 0.001). Conclusions: Single-dose modified anti-VEGF treatment in combination with PDT may provide long-term regression at the initial stages of RAP

The role of late gadolinium enhancement in predicting arrhythmic events in cardiac sarcoidosis patients – a mini-review

Sarcoidosis is a multisystem inflammatory disorder with an unknown origin. Symptomatic cardiac involvement is rare and occurs in about 5% of patients with sarcoidosis. Fatal ventricular arrhythmias are the most severe clinical presentation of the disease. Cardiac magnetic resonance (CMR) is a useful non-invasive tool for the risk stratification of ventricular arrhythmias and sudden cardiac death (SCD) in patients with cardiac sarcoidosis (CS). More specifically, late gadolinium enhancement (LGE), a CMR tool for scar detection, has been found to be significantly associated with arrhythmic events in CS patients. This review aims to present the existing evidence regarding the association of LGE with adverse events and especially with fatal ventricular arrhythmias

The role of late gadolinium enhancement in predicting arrhythmic events in cardiac sarcoidosis patients – A mini-review

Sarcoidosis is a multisystem inflammatory disorder with an unknown origin. Symptomatic cardiac involvement is rare and occurs in about 5% of patients with sarcoidosis. Fatal ventricular arrhythmias are the most severe clinical presentation of the disease. Cardiac magnetic resonance (CMR) is a useful non-invasive tool for the risk stratification of ventricular arrhythmias and sudden cardiac death (SCD) in patients with cardiac sarcoidosis (CS). More specifically, late gadolinium enhancement (LGE), a CMR tool for scar detection, has been found to be significantly associated with arrhythmic events in CS patients. This review aims to present the existing evidence regarding the association of LGE with adverse events and especially with fatal ventricular arrhythmias

Dietary Factors May Delay Tolerance Acquisition in Food Protein-Induced Allergic Proctocolitis

Background: Dietary and environmental factors may influence tolerance acquisition in food protein-induced allergic proctocolitis (FPIAP). This retrospective observational study explored the role of maternal diet during pregnancy and breastfeeding in tolerance acquisition in infantile FPIAP. Methods: Breastfed infants with FPIAP from six diverse regions in Greece were divided into two groups, based on development of tolerance to the trigger food: Group A (n = 43), before, and Group B (n = 53), after, the 6th month of age. Maternal diet during pregnancy and breastfeeding was elicited using the Mediterranean Diet Score Questionnaire and the Mediterranean Oriented Culture Specific Semi-Quantitative Food Frequency Questionnaire. Results: Mean age at diagnosis of FPIAP (1.5 months) and weaning (5.5 months) were the same in both groups. The main trigger was cow’s milk. Group A received infant milk formula earlier than Group B. Group B had a higher incidence of asthma/wheeze, siblings with milk allergy, maternal smoking and rural residence. On multivariate analysis, earlier resolution of FPIAP was associated with higher maternal education and with salt intake and consumption of goat/sheep cheese during pregnancy and olive oil during breastfeeding. Consumption of multivitamins during pregnancy and meat, winter fruits, green vegetables, butter, salt, “ready-to-eat” meals and pastries during breastfeeding were correlated with longer duration of symptoms. Conclusions: Mothers of children with FPIAP to cow’s milk protein can be advised to eat more yogurt, cheese and olive oil during subsequent pregnancies, and avoid multivitamins, grilled food, “ready-to-eat” meals, pastries, meat and alcohol during breastfeeding, to reduce the duration of FPIAP presenting in future infants