Toward trustworthy medical device in silico clinical trials: a hierarchical framework for establishing credibility and strategies for overcoming key challenges.

Computational models of patients and medical devices can be combined to perform an in silico clinical trial (ISCT) to investigate questions related to device safety and/or effectiveness across the total product life cycle. ISCTs can potentially accelerate product development by more quickly informing device design and testing or they could be used to refine, reduce, or in some cases to completely replace human subjects in a clinical trial. There are numerous potential benefits of ISCTs. An important caveat, however, is that an ISCT is a virtual representation of the real world that has to be shown to be credible before being relied upon to make decisions that have the potential to cause patient harm. There are many challenges to establishing ISCT credibility. ISCTs can integrate many different submodels that potentially use different modeling types (e.g., physics-based, data-driven, rule-based) that necessitate different strategies and approaches for generating credibility evidence. ISCT submodels can include those for the medical device, the patient, the interaction of the device and patient, generating virtual patients, clinical decision making and simulating an intervention (e.g., device implantation), and translating acute physics-based simulation outputs to health-related clinical outcomes (e.g., device safety and/or effectiveness endpoints). Establishing the credibility of each ISCT submodel is challenging, but is nonetheless important because inaccurate output from a single submodel could potentially compromise the credibility of the entire ISCT. The objective of this study is to begin addressing some of these challenges and to identify general strategies for establishing ISCT credibility. Most notably, we propose a hierarchical approach for assessing the credibility of an ISCT that involves systematically gathering credibility evidence for each ISCT submodel in isolation before demonstrating credibility of the full ISCT. Also, following FDA Guidance for assessing computational model credibility, we provide suggestions for ways to clearly describe each of the ISCT submodels and the full ISCT, discuss considerations for performing an ISCT model risk assessment, identify common challenges to demonstrating ISCT credibility, and present strategies for addressing these challenges using our proposed hierarchical approach. Finally, in the Appendix we illustrate the many concepts described here using a hypothetical ISCT example.

Antibiotic selection for the treatment of infectious complications of implant-based breast reconstruction.

BACKGROUND: Infection requiring explantation remains the most devastating complication associated with implant-based breast reconstruction. There are many treatment algorithms to prevent reconstructive failure in face of infection using both oral and intravenous antibiotics. In the absence of patient-specific culture data, antibiotic selection is generally directed toward broad-spectrum coverage based on historical data. We hypothesize that reviewing our institution's microbiology data obtained from explanted implant-based breast reconstructions would provide a rational basis for antibiotic selection in the future. METHODS: A retrospective review of 902 consecutive immediate implant-based breast reconstructions at a single institution from November 2007 to May 2011 was conducted. Implant reconstructions requiring explantation or drainage by interventional radiology were identified. Patient demographics, implant characteristics, presence of skin necrosis, microbiological data, and outcomes were reviewed. RESULTS: Forty-three (4.76%) implant reconstructions requiring explantation or drainage by interventional radiology met the inclusion criteria for this study. Five patients (11.6%) had round, smooth silicone implants, and 36 (88.4%) had textured tissue expanders. Twenty-six implants were explanted because of infection; 3, because of exposure from skin necrosis; and 11, because of the combination of flap necrosis and infection; and 1, secondarily because of cancer invasion into the skin. Reconstruction was salvaged in 21 breasts (51.2%): 12 (57.1%) by implant reconstruction, 5 (23.8%) by pedicled latissimus dorsi flaps, and 4 (19.1%) with a microvascular free flap. Thirty explants had microbiology data available. The most common organism isolated was Staphylococcus epidermidis (10), followed by methicillin-sensitive Staphylococcus aureus (5), Serratia marcescens (5), Pseudomonas aeruginosa (4), enterococcus (3), Escherichia coli (2), Enterobacter (2), group B streptococcus (1), and Morganella morganii (1). Forty percent of the organisms were resistant to cefazolin; however, 86% were sensitive to gentamicin, 80% were sensitive to Levaquin, and 63% were sensitive to ciprofloxacin. CONCLUSIONS: Infection associated with implant-based breast reconstructions continues to threaten explantation and reconstructive failure. Based on our microbiological data, initial cellulitis amenable to oral antibiotics should be treated with oral fluoroquinolones as a first-line treatment. If this regimen fails, intravenous imipenem or gentamicin and vancomycin should be initiated. Obviously, clinical judgment regarding specific patient risk factors and compliance should play a role in decision making, but these data provide an evidence-based rationale for first-line oral antibiotic selection.