CIGB-552 is a synthetic peptide that interacts with COMMD1 and upregulates its protein levels. The objectives of this phase I study were safety, pharmacokinetic profile, evaluation of the lymphocytes CD4+ and CD8+ and preliminary activity in patients with advanced tumors. A 3 + 3 dose-escalation design with seven dose levels was implemented. Patients were included until a grade 3 related adverse event occurred and the maximum tolerated dose was reached. The patients received subcutaneous administration of CIGB-552 three times per week for 2 weeks. Single-dose plasma pharmacokinetics was characterized at two dose levels, and tumor responses were classified by RECIST 1.1. Twenty-four patients received CIGB-552. Doselimiting toxicity was associated with a transient grade 3 pruritic maculopapular rash at a dose of 7.0 mg. The maximum tolerated dose was defined as 4.7 mg. Ten patients were assessable for immunological status. Seven patients had significant changes in the ratio CD4/CD8 in response to CIGB-552 treatment; three patients did not modify the immunological status. Stable disease was observed in five patients, including two metastatic soft sarcomas. We conclude that CIGB-552 at dose 4.7 mg was well tolerated with no significant adverse events and appeared to provide some clinical benefits.
The present work provides a set of macros performed over SAS (Statistical Analysis System) for Windows, capable to fit conditional models under the problematic scenario of intermittent missingness in longitudinal data. Model fitting is based on the Missing Completely At Random (MCAR) or Missing At Random (MAR) assumptions, and the separability condition. The problem translates to maximization of the marginal observed data density only, which for Gaussian data is again Gaussian, meaning that likelihood can be expressed in terms of the mean and covariance matrix of the observed data vector, thus allowing implementation by means of a matrix oriented language like IML (Interactive Matrix Language) of SAS. A practical application is also given, where a convenient conditional model is fitted to the data from a clinical trial that assessed the effect of a Cuban product on a disease of the respiratory system. A parsimonious transition model of order seven with six parameters is obtained. A strong dependence is detected of the actual value of the primary endpoint, oxygenation index, on previous values reached one hour, three hours and seven hours before. Time distinguishes as a significant covariate: it is possible to say that oxygenation index tends to raise its values with time. This conclusion conveys a gradual improvement of patients, at least during the three days of treatment.
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