by
Stacy Cooper Bailey;
Guisselle A. Wismer;
Ruth M Parker;
Surrey M. Walton;
Alastair J.J. Wood;
Amisha Wallia;
Samantha A. Brokenshire;
Alexandra C. Infanzon;
Laura M. Curtis;
Mary J. Kwasny;
Michael S. Wolf
Background Patients with chronic conditions are often responsible for self-managing complex, multi-drug regimens with minimal professional clinical support. While numerous interventions to promote and support medication adherence have been tested, most have had limited success or have been too resource-intensive for real-world implementation. Objective To compare the effectiveness of multiple low-cost, technology-enabled strategies, alone and in combination, for promoting medication regimen adherence among older adults. Methods Older, English or Spanish-speaking patients on complex drug regimens (N = 1505) will be recruited from a community health system in Chicago, IL. Enrolled patients will be randomized to one of four study arms, receiving either: 1) enhanced usual care alone; 2) daily medication reminders via SMS text messages; 3) medication monitoring via a patient portal-based assessment; or 4) both SMS text message reminders and portal-based medication monitoring. The primary outcome of the study is medication adherence, which will be assessed via multiple measures at baseline, 2 months, and 6 months. The effect of intervention strategies on clinical markers (hemoglobin A1c, blood pressure, cholesterol level), as well as intervention fidelity and the barriers and costs of implementation will also be evaluated. Conclusions This randomized controlled trial will evaluate the impact of various low-cost intervention strategies on adherence to complex medication regimens and will explore barriers to implementation. If the studied intervention strategies are shown to be effective, then these approaches could be effectively deployed across a diverse range of clinical settings and patient populations. Clinical Trial Registration: This trial is registered on clinicaltrials.govNCT02820753.
To save valuable time and resources in new drug development, Phase I/II clinical trials with toxicity control and drug efficacy as dual primary endpoints have become increasingly popular. Escalation with over-dose control (the EWOC) is a Bayesian adaptive Phase I clinical trial design that can accurately estimate the maximum tolerated dose (MTD) level and control the probability of overdosing patients during the dose allocation phase. In this paper, we extend EWOC to Phase I/II clinical trials by controlling for under-dosing with a Gumbel Copula model to provide patients with at least minimum drug efficacy. We propose a utility function to measure the composite effect of toxicity and efficacy and select the optimal dose. To deal with the common issue that the efficacy endpoint often cannot be quickly ascertained, we employ Bayesian data augmentation to handle delayed efficacy and allow for flexible patient accrual without a waiting period. Extensive simulations demonstrate that the proposed new design not only provides better therapeutic effect by reducing the probability of treating patients at under-dose levels while protecting patients from being overdosed, but also improves trial efficiency and increases the accuracy of dose recommendation for subsequent clinical trials. We apply the proposed design to a Phase I/II solid tumor trial.
by
William Whang;
Matthew M. Burg;
Robert M. Carney;
Kenneth E. Freedland;
J. Thomas Bigger;
Diane Catellier;
Susan Czajkowski;
Nancy Frasure-Smith;
Donald C. Haas;
Allan S. Jaffe;
Francois Lesperance;
Vivian Medina;
Joan Duer-Hefele;
Gabrielle A. Osorio;
Faith Parsons;
Peter A. Shapiro;
David S. Sheps;
Viola Vaccarino;
Karina W. Davidson
In almost all current Phase I designs, toxicity response is treated coarsely as a binary indicator of dose limiting toxicity (DLT) and a lot of useful toxicity information is discarded. We are the first to establish a novel toxicity scoring system to treat toxicity response as a quasi-continuous variable and utilize all toxicities in Phase I trial. The generally accepted and objective parts, such as a logistic function, grade and type of toxicity, and whether the toxicity is DLT, are used so that the toxicity scoring system is relatively objective. Our toxicity scoring system has been successfully applied to an isotonic design (ID) to develop an extended isotonic design (EID). Simulation study and application of EID to the data of a real Phase I trial demonstrate that EID can always estimate a more accurate maximum tolerated dose (MTD) according to the exact toxicity profile under any toxicity profiles without additional cost or length of the trial. These cannot be accomplished in designs using a binary indicator of DLT, such as Standard 3+3 design, ID, and continual reassessment method (CRM). Moreover, our EID is relatively objective, model free, and simple to use. Our toxicity scoring system can also be applied to other designs, such as CRM and escalation with overdose control (EWOC), to improve their efficiency and accuracy in MTD estimation by utilizing all toxicities. Our novel toxicity scoring system and EID may help to begin a new era in which toxicity response is treated as a continuous variable.