Clinical Profile and Response to Treatment with Pegylated Interferon α 2b and Ribavirin in Chronic Hepatitis C-A Reappraisal from a Tertiary Care Center in Northern India.

AIM: To assess the clinical profile of 80 chronic hepatitis C patients in a tertiary health care center in Northern India and also to study the efficacy and tolerability of pegylated interferon (Peg-IFN) α 2b and ribavirin therapy in a cohort of chronic hepatitis C patients. METHODS: Thirty subjects with chronic hepatitis C (CH-C) with genotypes 2 and 3 received Peg-IFN α 2b 1.5 µg/kg subcutaneously weekly plus daily ribavirin 800 mg for 24 weeks .Subjects with genotype 1 infection received therapy for 48 weeks with ribavirin 1000 mg/day and Peg-IFN α 2b dose remained the same. The primary end point was the sustained viral response (SVR). Drug dosage was modified or temporarily discontinued if anemia or bone marrow suppression developed. RESULTS: The clinical profile of chronic hepatitis C infected patients showed decompensated cirrhosis in the more elderly patients. Genotype 3 was the commonest genotype and was seen in 21 (70%) patients. The mean baseline HCV RNA was high. SVR was achieved less commonly with genotype 1 than with genotype 2/3. Patients who became negative for HCV RNA at 4-weeks (rapid virological response or RVR) and 12 weeks (early virological response or EVR) of treatment showed significantly higher sustained virological response (SVR) rates. Similarly, patients who showed normalization of ALT level at 4-weeks and 12-weeks of treatment showed significant high rate of SVR. Overall treatment was well tolerated. CONCLUSION: In our region, CHC subjects have high viral load and genotype 3 being the most common. Treatment with Peg-IFN α 2b and ribavirin is effective and well tolerated. Genotype 1 was more resistant to the treatment. Patients who achieved RVR and EVR are more likely to achieve SVR. Although the numbers of patients in this study was small, considering the paucity of data of treatment from India, the data is relevant.

Mohr-Claussen syndrome or oro-facial-digital syndrome (OFDS) type-II.

The Mohr-Claussen syndrome or oro-facial-digital syndrome type II (OFD-II)] is characterised by tongue lobulation, midline cleft lip, high arched or cleft palate, broad nasal root with wide bifid nasal tip, hypertelorism, micrognathia, brachydactyly, syndactyly and polydactyly, bilateral reduplicated hallux, conductive hearing loss and normal intelligence. In view of the different modes of inheritance and the different prognoses of the two oro-facio-digital syndromes, type 1 and type 2, it is important to establish a correct diagnosis in these patients. A neonate with features of oro-facio-digital syndrome, type-II is being reported and the distinguishing clinicoradiological features with type-I are compared.

Extending the modified bayesian information criterion (mBIC) to dense markers and multiple interval mapping.

SUMMARY: The modified version of Bayesian Information Criterion (mBIC) is a relatively simple model selection procedure that can be used when locating multiple interacting quantitative trait loci (QTL). Our earlier work demonstrated the statistical properties of mBIC for situations where the average genetic map interval is at least 5 cM. In this work mBIC is adapted to genome searches based on a dense map and, more importantly, to the situation where consecutive QTL and interactions are located by multiple interval mapping. Easy to use formulas for the extended mBIC are given. A simulation study, as well as the analysis of real data, confirm the good properties of the extended mBIC.

Modifying the Schwarz Bayesian information criterion to locate multiple interacting quantitative trait loci.

The problem of locating multiple interacting quantitative trait loci (QTL) can be addressed as a multiple regression problem, with marker genotypes being the regressor variables. An important and difficult part in fitting such a regression model is the estimation of the QTL number and respective interactions. Among the many model selection criteria that can be used to estimate the number of regressor variables, none are used to estimate the number of interactions. Our simulations demonstrate that epistatic terms appearing in a model without the related main effects cause the standard model selection criteria to have a strong tendency to overestimate the number of interactions, and so the QTL number. With this as our motivation we investigate the behavior of the Schwarz Bayesian information criterion (BIC) by explaining the phenomenon of the overestimation and proposing a novel modification of BIC that allows the detection of main effects and pairwise interactions in a backcross population. Results of an extensive simulation study demonstrate that our modified version of BIC performs very well in practice. Our methodology can be extended to general populations and higher-order interactions.