Clinical effectiveness and safety of cetirizine versus rupatadine in chronic spontaneous urticaria: a randomized, double-blind, 6-week trial.

BACKGROUND: Urticaria is a distressing condition associated with diverse clinical presentations. Chronic spontaneous urticaria (CsU) is characterized by wheals and angioedema. Its treatment requires an algorithmic approach to identify the optimum medication. OBJECTIVES: Cetirizine is commonly used in the treatment of urticaria. Rupatadine is a selective non-sedating H1 -antihistamine approved for the treatment of CsU. This trial was conducted to ascertain whether the properties of rupatadine offer advantages over cetirizine. METHODS: Seventy patients with CsU were enrolled. Parameters assessed included: (i) mean number of wheals (MNW); (ii) pruritus; (iii) mean total symptom score (MTSS); (iv) size of wheal; (v) interference of wheals with sleep; and (vi) sedation. Patients with CsU were divided randomly into two groups. Routine investigations were performed at baseline and at the end of the study. RESULTS: Evaluations of MTSS, MNW, and pruritus revealed statistically significant differences at week 3 compared with baseline in the cetirizine group. However, greater reductions in these parameters were obtained with rupatadine. In patients receiving rupatadine, reductions in the MNW, size of wheals, and intensity of erythema were also significant at six weeks (P < 0.001) and were significantly greater than those in the cetirizine group (P < 0.05). CONCLUSIONS: Improvements in MTSS, MNW, size of wheals, intensity of erythema, and differential eosinophil count imply that rupatadine is a particularly attractive therapeutic modality compared with cetirizine for the treatment of CsU.

Basic biostatistics for post-graduate students.

Statistical methods are important to draw valid conclusions from the obtained data. This article provides background information related to fundamental methods and techniques in biostatistics for the use of postgraduate students. Main focus is given to types of data, measurement of central variations and basic tests, which are useful for analysis of different types of observations. Few parameters like normal distribution, calculation of sample size, level of significance, null hypothesis, indices of variability, and different test are explained in detail by giving suitable examples. Using these guidelines, we are confident enough that postgraduate students will be able to classify distribution of data along with application of proper test. Information is also given regarding various free software programs and websites useful for calculations of statistics. Thus, postgraduate students will be benefitted in both ways whether they opt for academics or for industry.