Models for change in tumour size, appearance of new lesions and survival probability in patients with advanced epithelial ovarian cancer.

Aims: The aims of this study were (i) to develop a modelling framework linking change in tumour size during treatment to survival probability in metastatic ovarian cancer; and (ii) to model the appearance of new lesions and investigate their relationship with survival and disease characteristics.

Methods: Data from a randomized Phase III clinical trial comparing carboplatin monotherapy to gemcitabine plus carboplatin combotherapy in 336 patients with metastatic ovarian cancer were used. A population model describing change in tumour size based on drug treatment information was established and its relationship with time to appearance of new lesions and survival were investigated with time to event models.

Phase 1/2 study of ocaratuzumab, an Fc-engineered humanized anti-CD20 monoclonal antibody, in low-affinity FcγRIIIa patients with previously treated follicular lymphoma.

This phase 2 study assessed the safety and efficacy of ocaratuzumab, a humanized anti-CD20 monoclonal antibody. Fifty patients with previously treated follicular lymphoma (FL) and a low-affinity genotype of FcγRIIIa received ocaratuzumab 375 mg/m(2) weekly for 4 weeks. Grade 3/4/5 adverse events (AEs) were reported in 11/1/1 patients, respectively.

Randomization by minimization for unbalanced treatment allocation.

Minimization is a dynamic randomization technique that has been widely used in clinical trials for achieving a balance of prognostic factors across treatment groups, but most often it has been used in the setting of equal treatment allocations. Although unequal treatment allocation is frequently encountered in clinical trials, an appropriate minimization procedure for such trials has not been published. The purpose of this paper is to present novel strategies for applying minimization methodology to such clinical trials.