Response Prediction in Chronic Hepatitis C by Assessment of IP-10 and IL28B-Related Single Nucleotide Polymorphisms.

BACKGROUND: High baseline levels of IP-10 predict a slower first phase decline in HCV RNA and a poor outcome following interferon/ribavirin therapy in patients with chronic hepatitis C. Several recent studies report that single nucleotide polymorphisms (SNPs) adjacent to IL28B predict spontaneous resolution of HCV infection and outcome of treatment among HCV genotype 1 infected patients. METHODS AND FINDINGS: In the present study, we correlated the occurrence of variants at three such SNPs (rs12979860, rs12980275, and rs8099917) with pretreatment plasma IP-10 and HCV RNA throughout therapy within a phase III treatment trial (HCV-DITTO) involving 253 Caucasian patients. The favorable SNP variants (CC, AA, and TT, respectively) were associated with lower baseline IP-10 (P = 0.02, P = 0.01, P = 0.04) and were less common among HCV genotype 1 infected patients than genotype 2/3 (P<0.0001, P<0.0001, and P = 0.01). Patients carrying favorable SNP genotypes had higher baseline viral load than those carrying unfavorable variants (P = 0.0013, P = 0.029, P = 0.0004 respectively). Among HCV genotype 1 infected carriers of the favorable C, A, or T alleles, IP-10 below 150 pg/mL significantly predicted a more pronounced reduction of HCV RNA from day 0 to 4 (first phase decline), which translated into increased rates of RVR (62%, 53%, and 39%) and SVR (85%, 76%, and 75% respectively) among homozygous carriers with baseline IP-10 below 150 pg/mL. In multivariate analyses of genotype 1-infected patients, baseline IP-10 and C genotype at rs12979860 independently predicted the first phase viral decline and RVR, which in turn independently predicted SVR. CONCLUSIONS: Concomitant assessment of pretreatment IP-10 and IL28B-related SNPs augments the prediction of the first phase decline in HCV RNA, RVR, and final therapeutic outcome.

A new ovarian response prediction index (ORPI): implications for individualised controlled ovarian stimulation

Background: The objective was to present a new ovarian response prediction index (ORPI), which was based on anti-Mullerian hormone (AMH) levels, antral follicle count (AFC) and age, and to verify whether it could be a reliable predictor of the ovarian stimulation response.Methods: A total of 101 patients enrolled in the ICSI programme were included. The ORPI values were calculated by multiplying the AMH level (ng/ml) by the number of antral follicles (2-9 mm), and the result was divided by the age (years) of the patient (ORPI=(AMH x AFC)/Patient age).Results: The regression analysis demonstrated significant (P<0.0001) positive correlations between the ORPI and the total number of oocytes and of MII oocytes collected. The logistic regression revealed that the ORPI values were significantly associated with the likelihood of pregnancy (odds ratio (OR): 1.86; P=0.006) and collecting greater than or equal to 4 oocytes (OR: 49.25; P<0.0001), greater than or equal to 4 MII oocytes (OR: 6.26; P<0.0001) and greater than or equal to 15 oocytes (OR: 6.10; P<0.0001). Regarding the probability of collecting greater than or equal to 4 oocytes according to the ORPI value, the ROC curve showed an area under the curve (AUC) of 0.91 and an efficacy of 88% at a cut-off of 0.2. In relation to the probability of collecting greater than or equal to 4 MII oocytes according to the ORPI value, the ROC curve had an AUC of 0.84 and an efficacy of 81% at a cut-off of 0.3. The ROC curve for the probability of collecting greater than or equal to 15 oocytes resulted in an AUC of 0.89 and an efficacy of 82% at a cut-off of 0.9. Finally, regarding the probability of pregnancy occurrence according to the ORPI value, the ROC curve showed an AUC of 0.74 and an efficacy of 62% at a cut-off of 0.3.Conclusions: The ORPI exhibited an excellent ability to predict a low ovarian response and a good ability to predict a collection of greater than or equal to 4 MII oocytes, an excessive ovarian response and the occurrence of pregnancy in infertile women. The ORPI might be used to improve the cost-benefit ratio of ovarian stimulation regimens by guiding the selection of medications and by modulating the doses and regimens according to the actual needs of the patients.

Cluster analysis and artificial neural network on the superovulatory response prediction in mice

Complex biological systems require sophisticated approach for analysis, once there are variables with distinct measure levels to be analyzed at the same time in them. The mouse assisted reproduction, e.g. superovulation and viable embryos production, demand a multidisciplinary control of the environment, endocrinologic and physiologic status of the animals, of the stressing factors and the conditions which are favorable to their copulation and subsequently oocyte fertilization. In the past, analyses with a simplified approach of these variables were not well succeeded to predict the situations that viable embryos were obtained in mice. Thereby, we suggest a more complex approach with association of the Cluster Analysis and the Artificial Neural Network to predict embryo production in superovulated mice. A robust prediction could avoid the useless death of animals and would allow an ethic management of them in experiments requiring mouse embryo.

Pushover analysis for the seismic response prediction of cable-stayed bridges under multi-directional excitation

Cable-stayed bridges represent nowadays key points in transport networks and their seismic behavior needs to be fully understood, even beyond the elastic range of materials. Both nonlinear dynamic (NL-RHA) and static (pushover) procedures are currently available to face this challenge, each with intrinsic advantages and disadvantages, and their applicability in the study of the nonlinear seismic behavior of cable-stayed bridges is discussed here. The seismic response of a large number of finite element models with different span lengths, tower shapes and class of foundation soil is obtained with different procedures and compared. Several features of the original Modal Pushover Analysis (MPA) are modified in light of cable-stayed bridge characteristics, furthermore, an extension of MPA and a new coupled pushover analysis (CNSP) are suggested to estimate the complex inelastic response of such outstanding structures subjected to multi-axial strong ground motions.

The Comparative Effectiveness of EEG Biomarkers in Antidepressant Response and Illness Prediction in Major Depressive Disorder

Background: There is growing evidence that individual EEG differences may aid in classifying patients with major depressive disorder (MDD) and also help predict clinical response to antidepressant treatment. This study aims to compare the effectiveness of EEG frequency band power, alpha asymmetry and prefrontal theta cordance towards escitalopram response prediction and MDD diagnosis, in a multi-site initiative. Methods: Resting EEG (eyes open and closed) was recorded from 64 electrodes in 44 depressed patients and 20 healthy controls at baseline, 2 weeks post-treatment and 8 weeks post-treatment. Clinical response was measured as change from baseline MADRS of 50% or more. EEG measures were analyzed (1) at baseline (2) at 2 weeks post-treatment and (3) as an ‘‘early change” variable defined as change in EEG from baseline to 2 weeks post-treatment. Results: At baseline, responders exhibited greater absolute alpha power in the left hemisphere versus the right while non-responders showed the opposite. Responders further exhibited a cortical asymmetry of greater right relative to left activity in parietal areas. Groups also differed in baseline relative delta power with responders showing greater power in the right hemisphere versus the left while non-responders showed the opposite. At 2 weeks post-treatment, responders exhibited greater absolute beta power in the left hemisphere relative to right and the opposite was noted for non-responders. The opposite pattern was noted for absolute and relative delta power at 2 weeks post-treatment. Responders exhibited early reduction in relative alpha power and early increments in relative theta power. Non-responders showed a significant early increase in prefrontal theta cordance. Absolute delta power helped distinguish MDD patients from healthy controls. Conclusions: Hemispheric asymmetries in the alpha and delta bands at pre-treatment baseline and at 2 weeks post-treatment have moderate to moderately strong predictive utility towards antidepressant treatment response. These findings have significant potential for improving clinical practice in psychiatry by eventually guiding clinical choice of treatments. This would greatly benefit patients awaiting relief from depressive symptoms as treatment optimization would help overcome problems associated with delayed recovery. Our results also indicate that resting EEG activity may have clinical utility in predicting MDD diagnosis.

The Comparative Effectiveness of EEG Biomarkers in Antidepressant Response and Illness Prediction in Major Depressive Disorder

Thesis (Ph.D, Neuroscience Studies) -- Queen's University, 2016-08-27 00:55:35.782

Prediction in Multilevel Logistic Regression

The purpose of this article is to present a new method to predict the response variable of an observation in a new cluster for a multilevel logistic regression. The central idea is based on the empirical best estimator for the random effect. Two estimation methods for multilevel model are compared: penalized quasi-likelihood and Gauss-Hermite quadrature. The performance measures for the prediction of the probability for a new cluster observation of the multilevel logistic model in comparison with the usual logistic model are examined through simulations and an application.

IMPROVING QUANTITATIVE TREATMENT RESPONSE MONITORING WITH DEFORMABLE IMAGE REGISTRATION

Quantitative imaging with 18F-FDG PET/CT has the potential to provide an in vivo assessment of response to radiotherapy (RT). However, comparing tissue tracer uptake in longitudinal studies is often confounded by variations in patient setup and potential treatment induced gross anatomic changes. These variations make true response monitoring for the same anatomic volume a challenge, not only for tumors, but also for normal organs-at-risk (OAR). The central hypothesis of this study is that more accurate image registration will lead to improved quantitation of tissue response to RT with 18F-FDG PET/CT. Employing an in-house developed “demons” based deformable image registration algorithm, pre-RT tumor and parotid gland volumes can be more accurately mapped to serial functional images. To test the hypothesis, specific aim 1 was designed to analyze whether deformably mapping tumor volumes rather than aligning to bony structures leads to superior tumor response assessment. We found that deformable mapping of the most metabolically avid regions improved response prediction (P<0.05). The positive predictive power for residual disease was 63% compared to 50% for contrast enhanced post-RT CT. Specific aim 2 was designed to use parotid gland standardized uptake value (SUV) as an objective imaging biomarker for salivary toxicity. We found that relative change in parotid gland SUV correlated strongly with salivary toxicity as defined by the RTOG/EORTC late effects analytic scale (Spearman’s ρ = -0.96, P<0.01). Finally, the goal of specific aim 3 was to create a phenomenological dose-SUV response model for the human parotid glands. Utilizing only baseline metabolic function and the planned dose distribution, predicting parotid SUV change or salivary toxicity, based upon specific aim 2, became possible. We found that the predicted and observed parotid SUV relative changes were significantly correlated (Spearman’s ρ = 0.94, P<0.01). The application of deformable image registration to quantitative treatment response monitoring with 18F-FDG PET/CT could have a profound impact on patient management. Accurate and early identification of residual disease may allow for more timely intervention, while the ability to quantify and predict toxicity of normal OAR might permit individualized refinement of radiation treatment plan designs.

Índice preditor de reserva ovariana (ORPI) para controle de estimulação ovariana individualizado

Objective: to expand the evaluation of a new ovarian response prediction index (ORPI), which was based on the AMH, AFC and age, and to verify its reability as a predictor of ovarian response to stimulation in assisted reproductive technology (ART) cycles. Methods: A total of 129 patients enrolled in the ICSI programme were included. The ORPI values were calculated by multiplying the AMH level (ng/ml) by the number of antral follicles (2-9 mm), and the result was divided by the age (years) of the patient (ORPI=(AMH × AFC)/Patient age). Results: Spearman's test revealed significant correlations (P<0.0001) between the ORPI and the number of oocytes collected and the number of follicles. Logistic regression revealed that ORPI values were significantly associated with the likelihood of collecting ≥4 oocytes (OR=45.56), ≥4 MII oocytes (OR=6.01) and ≥15 oocytes (OR=6.15; P<0.0001). Based on the ROC curves, the ORPI accurately predicted a low ovarian response (<4 oocytes retrieved; area under the curve (AUC):0.91), collection of ≥4 MII oocytes (AUC:0.85) and an excessive ovarian response (≥15 oocytes retrieved; AUC:0.89). Conclusions: The ORPI exhibited an excellent ability to predict a low ovarian response and a good ability to predict a collection of ≥ 4 MII oocytes, an excessive ovarian response. The ORPI might be used to improve the cost-benefit ratio of ovarian stimulation regimens by guiding the selection of medications and by modulating the doses and regimens according to the actual needs of the patients. © Todos os direitos reservados a SBRA - Sociedade Brasileira de Reprodução Assistida.

Optimierung der Pharmakotherapie schizophrener Patienten durch objektive Symptomerfassung und Therapeutisches Drug Monitoring

Der Erfolg einer Schizophrenie-Behandlung ist zum größten Teil abhängig vom Ansprechen des Patienten auf seine antipsychotische Medikation. Welches Medikament und welche Dosis bei einem individuellen Patienten wirksam sind, kann derzeit erst nach mehrwöchiger Behandlung beurteilt werden. Ein Grund für variierendes Therapieansprechen sind variable Plasmakonzentrationen der Antipsychotika. Ziel dieser Arbeit war es, zu untersuchen, in wieweit der Therapieerfolg zu einem frühen Zeitpunkt der Behandlung durch objektive Symptomerfassung vorhersagbar ist und welche Faktoren die hohe Variabilität der Antipsychotikaspiegel im Blut beeinflussen. rnEine 18-monatige naturalistische klinische Studie an schizophrenen Patienten wurde durchgeführt, um folgende Fragen zu beantworten: Kann man das Therapieansprechen prädizieren und welche Instrumente sind dafür geeignet? Die Psychopathologie wurde anhand zweier Messskalen (Brief Psychiatric Rating Scale, BPRS und Clinical Global Impressions, CGI) wöchentlich ermittelt, um die Besserung der Krankheitssymptome im Verlauf von 8 Wochen zu bewerten. Therapiebegleitend wurden noch die Serum-Konzentrationen der Antipsychotika gemessen. Objektive Symptomerfassung durch BPRS oder CGI waren als Messinstrumente geeignet, Therapieansprechen vorherzusagen. Bezogen auf den Behandlungsbeginn war eine Verminderung der Symptome hoch prädiktiv für späteres Therapieversagen oder -ansprechen. Eine Verminderung um mehr als 36,5% auf der BPRS Skala in Woche 2 wurde als signifikanter Schwellenwert für Nichtansprechen ermittelt. Patienten, deren Symptombesserung unterhalb des Schwellenwertes lag, hatten eine 11,2-fach höhere Wahrscheinlichkeit, am Ende der Studie nicht auf ihre medikamentöse Therapie anzusprechen als die Patienten, die sich um mindestens 36,5% verbesserten. Andere Faktoren, wie Alter, Geschlecht, Dauer der Erkrankung oder Anzahl der stationären Aufenthalte hatten keinen Einfluss auf die Prädiktion des Therapieansprechens. Therapeutische Antipsychotika-Spiegel übten einen positiven Einfluss auf die Ansprechrate aus. Bei Patienten mit therapeutischen Spiegeln war das Ansprechen rascher und die Ansprechrate größer als unter denjenigen deren Spiegel außerhalb der therapeutisch üblichen Bereiche lag. rnEine wichtige Voraussetzung für den Einsatz von TDM ist das Vorhandensein einer präzisen, reproduzierbaren, zeit- und kostensparenden analytischen Methode zur quantitativen Bestimmung der untersuchten Substanzen. Die Entwicklung und Validierung einer solchen geeigneten Methode wurde für den Nachweis von Haloperidol vorgenommen. Eine HPLC-Methode mit Säulenschaltung erwies sich für TDM geeignet. rnBasierend auf den Ergebnissen der eigenen klinischen Studie zur Response Prädiktion wurde untersucht, welche Faktoren die Variabilität der Pharmakokinetik von Antipsychotika beeinflussen. Die Variabilität der Pharmakokinetik ist ein Grund für fehlendes oder unzureichendes Ansprechen. Es wurde zum einen der Einfluss der galenischen Formulierung auf die Freisetzung und zum anderen der Einfluss von entzündlichen Prozessen auf die Metabolisierung eines Antipsychotikums untersucht. Dazu wurden Patientendaten retrospektiv ausgewertet.rnDie Analyse von 247 Serumspiegeln von Patienten, die mit Paliperidon in OROS®Formulierung, einer neu eingeführten Retardform, behandelt wurden, zeigte, dass die intraindividuelle Variabilität der Talspiegel (Vk) von Paliperidon 35% betrug. Er war damit vergleichbar wie für nicht retardiertes Risperidon 32% (p=n.s.). Die Retardierung hatte demnach keinen Varianz mindernden Effekt auf die Talspiegel des Antipsychotikums. Der Wirkstoff-Konzentrations-Bereich lag bei 21-55 ng/ml und entsprach ebenfalls nahezu dem therapeutischen Bereich von Risperidon (20-60 ng/ml). rnEntzündliche Prozesse können die Metabolisierung von Medikamenten verändern. Dies wurde bisher für Medikamente nachgewiesen, die über CYP1A2 abgebaut werden. Durch die eigene Analyse von 84 Patienten-Serumspiegeln konnte festgestellt werden, dass die Metabolisierung von Quetiapin während eines entzündlichen Prozesses beeinträchtigt war, wahrscheinlich durch Hemmung von CYP3A4. Dies sprach dafür, dass auch Wirkstoffe, die über CYP3A4 abgebaut werden, während eines entzündlichen Prozesses im Körper in ihrer Pharmakokinetik beeinträchtigt sein können. Aus diesem Grund sollte während einer Infektion unter der Therapie mit Quetiapin besonders auf die Nebenwirkungen geachtet werden und der Serumspiegel sollte in dieser Zeit überwacht werden, um den Patienten vor eventuellen Nebenwirkungen oder sogar Intoxikationen zu schützen. rnDie Befunde dieser Arbeit zeigen, dass bei einer Behandlung schizophrener Patienten mit Antipsychotika die Messung der Psychopathologie zur Vorhersage des Therapieansprechens und die Messung der Blutspiegel zur Identifizierung von Faktoren, die die pharmakokinetische Variabilität bedingen, geeignet sind. Objektive Symptomerfassung und Therapeutisches Drug Monitoring sind demnach Instrumente, die für die Steuerung der antipsychotischen Pharmakotherapie genutzt werden sollten.rn

Tumor regression grade of urothelial bladder cancer after neoadjuvant chemotherapy: a novel and successful strategy to predict survival.

Histopathologic tumor regression grades (TRGs) after neoadjuvant chemotherapy predict survival in different cancers. In bladder cancer, corresponding studies have not been conducted. Fifty-six patients with advanced invasive urothelial bladder cancer received neoadjuvant chemotherapy before cystectomy and lymphadenectomy. TRGs were defined as follows: TRG1: complete tumor regression; TRG2: >50% tumor regression; TRG3: 50% or less tumor regression. Separate TRGs were assigned for primary tumors and corresponding lymph nodes. The prognostic impact of these 2 TRGs, the highest (dominant) TRG per patient, and competing tumor features reflecting tumor regression (ypT/ypN stage, maximum diameter of the residual tumor) were determined. Tumor characteristics in initial transurethral resection of the bladder specimens were tested for response prediction. The frequency of TRGs 1, 2, and 3 in the primary tumors were n=16, n=19, and n=21; corresponding data from the lymph nodes were n=31, n=9, and n=16. Interobserver agreement in determination of the TRG was strong (κ=0.8). Univariately, all evaluated parameters were significantly (P≤0.001) related to overall survival; however, the segregation of the Kaplan-Meier curves was best for the dominant TRG. In multivariate analysis, only dominant TRG predicted overall survival independently (P=0.035). In transurethral resection specimens of the chemotherapy-naive bladder cancer, the only tumor feature with significant (P<0.03) predictive value for therapy response was a high proliferation rate. In conclusion, among all parameters reflecting tumor regression, the dominant TRG was the only independent risk factor. A favorable chemotherapy response is associated with a high proliferation rate in the initial chemotherapy-naive bladder cancer. This feature might help personalize neoadjuvant chemotherapy.