57 research outputs found

    Association of cetuximab with adverse pulmonary events in cancer patients: a comprehensive review

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    Compounds derived from biologic sources, or biologicals, are increasingly utilized as therapeutic agents in malignancy. Development of anti-cancer targeted therapies from biologics is increasingly being utilized. Cetuximab, a chimeric monoclonal antibody, is one such anti-cancer targeted therapeutic that has shown efficacy in quelling the rate of patient decline in colorectal, head/neck, and non-small cell lung cancer. However, due to the relatively recent addition of biologic compounds to the therapeutic arsenal, information related to adverse reactions is less well known than those seen in traditional chemotherapeutics. Dermatologic reactions have been demonstrated as the most frequent side effect cited during cetuximab therapy for malignancy; however, other effects may lead to greater morbidity. In general, pulmonary complications of therapeutics can lead to significant morbidity and mortality. The purpose of this review is to compile the various pulmonary side effects seen in patients treated with cetuximab for various malignancies, and to compare the incidence of these adverse reactions to standard therapies

    Letter To The Editor

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    Choosing the Function of Baseline Run-In Data for Use as a Covariate in the Analysis of Treatment Data from Phase III Clinical Trials in Hypertension

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    In this work, we simulated (1000 replications) diastolic blood pressure (DBP) data to model a Phase III clinical trial in newly diagnosed hypertensive patients that had 8 consecutive days of baseline run-in data followed by six months of double-blind, randomized treatment with either a drug or placebo. We considered six different patterns (3 linear, 3 non-linear) of baseline run-in DBP data, prior to randomizing patients to treatment with a drug or placebo in balanced fashion (50 per group). We defined 11 functions of the baseline run-in data for use as covariates. Comparative statistical analyses were performed using both repeated measures linear ANCOVA models and longitudinal data analysis models—with or without treatment-by-time interaction and with or without the covariates. Further we assumed the DBP data followed a truncated Normal distribution on the interval (80; 120] mmHg with covariance structure specified as either AR (1) or compound symmetry (CS) with correlation coefficients of 0.1, 0.5 and 0.9. Our objective was to determine the best function of the baseline run-in data to use as a covariate in the comparative statistical analysis of the monthly treatment period data
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