Multi-arm covariate adjusted response adaptive designs for ordinal outcome clinical trials.

Covariate adjusted response adaptive designs are developed with ordinal categorical responses for phase III clinical trial involving multiple treatments. Stochastic ordering principle is used to order the treatments according to effectiveness and consequently allocation functions are developed by combining the cumulative odds ratios suitably. The performance of the proposed designs is investigated through relevant exact as well as large sample measures. To investigate the performance in a real situation, a real clinical trial involving lung cancer patients is further redesigned using the proposed allocation design.

A novel SAR reduction technique for implantable antenna using conformal absorber metasurface.

In this paper, a conformal absorber metasurface has been designed and used for reducing the specific absorption rate (SAR) of an implantable antenna. SAR reduction of implantable antennas is one of the significant design aspects to be considered for their use in modern-day healthcare applications. The introduction of the absorber metasurface restricts the back radiation of the antenna to control the SAR value. This technique decreases the maximum SAR value by 24% and also reduces the average SAR distribution significantly without affecting the desired antenna gain. A reduction in SAR value indicates the decrease in radiation absorption by human tissue, and thus, decreases the possibility of health hazards due to EM radiation. Later, this antenna-absorber system is designed as a capsule module for increased mobility and less-invasiveness. The redundancy of invasive surgery increases acceptance of the capsule module designs of implantable antennas and devices for various biomedical usages. In vitro testing of the fabricated prototype has been carried out inside a multi-layer porcine slab to verify the effectiveness of this unique SAR reduction technique.

An optimal multiarmed response adaptive design for survival outcome with independent censoring.

Compromising ethics and precision in the context of a multiarmed clinical trial, an optimal order adjusted response adaptive design is proposed for survival outcomes subject to independent random censoring. The operating characteristics of the proposed design and the follow-up inference are studied both theoretically as well as empirically and are compared with those of the competitors. Applicability of the developed design is further illustrated through redesigning a real clinical trial with survival responses.

An optimal response adaptive design for multi-treatment clinical trials with ordinal categorical outcomes.

In clinical trials, fixed randomizations in a prefixed proportion (e.g. 1:1 or 2:1 for two treatment trials) may be adopted to allocate the entering patients among the competing treatments. However, such an allocation procedure ignores the knowledge obtained from the accrued information on the performance of the treatments until that point. However, while allocating, a fixed randomization may favor the most and the least effective treatments in a prefixed manner, and hence becomes instrumental to induce a conflict with the "individual ethics" requirement. Adaptive allocation designs are considered instead, for their ability to dynamically settle the issue of running randomization towards the treatment doing better - all using the available data but with a scope to compromise in statistical precision. Although most of the developments are pertinent to binary, continuous and survival responses, ordinal categorical responses are natural outcomes in many disciplines of clinical trials like Orthopedics and Ophthalmology. Therefore, to balance between ethics and precision in the context of a multi-treatment clinical trial producing ordinal categorical responses, an optimal response adaptive design is derived by minimizing a measure of "precision" subject to constrained number of "failures" ensuring higher number of assignments to the "best" treatment. Related design and inference-based characteristics are extensively studied - both theoretically and empirically. Further, the practical applicability of the developed design is envisaged through re-designing of a real clinical trial, where the responses are immediate and are measured in ordinal categorical scale.

A multi-treatment response adaptive design for ordinal categorical responses.

A multi-treatment response adaptive procedure is developed considering "comparison with the best" philosophy of multiple comparison procedures for clinical trials with ordinal categorical responses, when there is no shared control. For each response category, we arbitrarily create two outcome groups; one by combining the categories more favorable to it and the other by merging the categories at most as favorable to it and hence define the odds (i.e. cumulative odds). Pairwise ratios of such odds (i.e. cumulative odds ratios) based on pairs of treatments are combined conveniently to derive a measure of relative superiority and hence the allocation probability functions. For practical implementation, we suggest response-adaptive randomization (RAR), that is, update the allocation probabilities dynamically using the available allocation and response information to favor the treatment doing better. Empirical as well as large sample properties following the randomization are investigated in detail. Moreover, a real clinical trial with trauma patients is redesigned using the proposed RAR to envisage practical applicability.

A response adaptive design for ordinal categorical responses.

A two treatment response adaptive design is developed for phase III clinical trials with ordinal categorical treatment outcome using Goodman-Kruskal measure of association. Properties of the proposed design are studied both empirically and theoretically and the acceptability is further illustrated using two real data-sets; one from a clinical trial with trauma patients and the other from a trial with patients having rheumatoid arthritis.