Predictors of individual response to placebo or tadalafil 5mg among men with lower urinary tract symptoms secondary to benign prostatic hyperplasia: An integrated clinical data mining analysis

Background: A significant percentage of patients with lower urinary tract symptoms (LUTS) secondary to benign prostatic hyperplasia (BPH) achieve clinically meaningful improvement when receiving placebo or tadalafil 5mg once daily. However, individual patient characteristics associated with treatment response are unknown. Methods: This integrated clinical data mining analysis was designed to identify factors associated with a clinically meaningful response to placebo or tadalafil 5mg once daily in an individual patient with LUTS-BPH. Analyses were performed on pooled data from four randomized, placebo-controlled, double-blind, clinical studies, including about 1,500 patients, from which 107 baseline characteristics were selected and 8 response criteria. The split set evaluation method (1,000 repeats) was used to estimate prediction accuracy, with the database randomly split into training and test subsets. Logistic Regression (LR), Decision Tree (DT), Support Vector Machine (SVM) and Random Forest (RF) models were then generated on the training subset and used to predict response in the test subset. Prediction models were generated for placebo and tadalafil 5mg once daily Receiver Operating Curve (ROC) analysis was used to select optimal prediction models lying on the ROC surface. Findings: International Prostate Symptom Score (IPSS) baseline group (mild/moderate vs. severe) for active treatment and placebo achieved the highest combined sensitivity and specificity of 70% and ∼50%for all analyses, respectively. This was below the sensitivity and specificity threshold of 80% that would enable reliable allocation of an individual patient to either the responder or non-responder group Conclusions: This extensive clinical data mining study in LUTS-BPH did not identify baseline clinical or demographic characteristics that were sufficiently predictive of an individual patient response to placebo or once daily tadalafil 5mg. However, the study reaffirms the efficacy of tadalalfil 5mg once daily in the treatment of LUTS-BPH in the majority of patients and the importance of evaluating individual patient need in selecting the most appropriate treatment. Copyright

Comparison of ixekizumab with ustekinumab in moderate-to-severe psoriasis: 24-week results from IXORA-S, a phase III study

Background It has been shown that the interleukin (IL)-23/IL-17 axis is critical in the pathogenesis of psoriasis. Objectives To present the primary end point (week 12) and safety and efficacy data up to week 24 from a head-to-head trial (IXORA-S) of the IL-17A inhibitor ixekizumab (IXE) vs. the IL-12/23 inhibitor ustekinumab (UST). Methods Randomized patients received IXE (160-mg starting dose, then 80 mg every 2 weeks for 12 weeks, then 80 mg every 4 weeks, n = 136) or UST (45 mg or 90 mg weight-based dosing per label, n = 166). The primary end point was the proportion of patients reaching ≥ 90% Psoriasis Area and Severity Index improvement (PASI 90). Hommel-adjusted key secondary end points at week 12 included PASI 75, PASI 100, static Physician's Global Assessment (sPGA) score of 0 or 1, sPGA score of 0, Dermatology Life Quality Index (DLQI) score of 0 or 1, ≥ 4-point reduction on the itch numerical rating scale (NRS) and changes in itch NRS and skin pain visual analogue scale. Results At week 12, IXE (n = 99, 72 8%) was superior to UST (n = 70, 42 2%) in PASI 90 response (response difference 32 1%, 97 5% confidence interval 19 8 44 5%, P < 0 001). Response rates for PASI 75, PASI 100 and sPGA (0,1) were significantly higher for IXE than for UST (adjusted P < 0 05). At week 24, IXEtreated patients had significantly higher response rates than UST-treated patients for PASI, sPGA and DLQI (unadjusted P < 0 05). No deaths were reported, and the treatments did not differ with regard to overall incidences of adverse events (P = 0 299). Conclusions The superior efficacy of IXE demonstrated at week 12 persisted up to week 24. The safety profiles were consistent with those previously reported for both treatments. peerReviewe

Predicting DNA-Binding Specificities of Eukaryotic Transcription Factors

Today, annotated amino acid sequences of more and more transcription factors (TFs) are readily available. Quantitative information about their DNA-binding specificities, however, are hard to obtain. Position frequency matrices (PFMs), the most widely used models to represent binding specificities, are experimentally characterized only for a small fraction of all TFs. Even for some of the most intensively studied eukaryotic organisms (i.e., human, rat and mouse), roughly one-sixth of all proteins with annotated DNA-binding domain have been characterized experimentally. Here, we present a new method based on support vector regression for predicting quantitative DNA-binding specificities of TFs in different eukaryotic species. This approach estimates a quantitative measure for the PFM similarity of two proteins, based on various features derived from their protein sequences. The method is trained and tested on a dataset containing 1 239 TFs with known DNA-binding specificity, and used to predict specific DNA target motifs for 645 TFs with high accuracy