Quality-adjusted-life-years (QALYs) are used to concurrently quantify morbidity and mortality within a single parameter. For this reason, QALYs can facilitate the discussion of risks and benefits during patient counseling regarding treatment options. QALYs are often calculated using partitioned-survival modelling. Alternatively, QALYs can be calculated using more flexible and informative state-transition models populated with transition rates estimated using multistate modelling (MSM) techniques. Unfortunately the latter approach is considered not possible when only progression-free survival (PFS) and overall survival (OS) analyses are reported. We have developed a method that can be used to estimate approximate transition rates from published PFS and OS analyses (we will refer to transition rates estimated using full multistate methods as true transition rates). The approximation method is more accurate for estimating the transition rates out of health than the transition rate out of illness. The method tends to under-estimate true transition rates as censoring increases. In this article we present the basis for and use of the transition rate approximation method. We then apply the method to a case study and evaluate the method in a simulation study.

Background: As of May 2022, Ontario has seen more than 1.3 million cases of COVID-19. While the majority of individuals will recover from infection within 4 weeks, a significant subset experience persistent and often debilitating symptoms, known as “post-COVID syndrome” or “Long COVID.” Those with Long COVID experience a wide array of symptoms, with variable severity, including fatigue, cognitive impairment, and shortness of breath. Further, the prevalence and duration of Long COVID is not clear, nor is there evidence on the best course of rehabilitation for individuals to return to their desired level of function. Previous work with chronic conditions has suggested that the addition of electronic case management (ECM) may help to improve outcomes. These platforms provide enhanced connection with care providers, detailed symptom tracking and goal setting, and access to relevant resources. In this study, our primary aim is to determine if the addition of ECM with health coaching improves Long COVID outcomes at 3 months compared to health coaching alone. Methods: The trial is an open-label, single-site, randomized controlled trial of ECM with health coaching (ECM+) compared to health coaching alone (HC). Both groups will continue to receive usual care. Participants will be randomized equally to receive health coaching (± ECM) for a period of 8 weeks and a 12-week follow-up. Our primary outcome is the WHO Disability Assessment Scale (WHODAS), 36-item self-report total score. Participants will also complete measures of cognition, fatigue, breathlessness, and mental health. Participants and care providers will be asked to complete a brief qualitative interview at the end of the study to evaluate acceptability and implementation of the intervention. Discussion: There is currently little evidence about the optimal treatment of Long COVID patients or the use of digital health platforms in this population. The results of this trial could result in rapid, scalable, and personalized care for people with Long COVID which will decrease morbidity after an acute infection. Results from this study will also inform decision making in Long COVID and treatment guidelines at provincial and national levels. Trial registration: ClinicalTrials.gov NCT05019963. Registered on 25 August 2021.

Surgical planning for complex orthopaedic oncology cases requires thorough understanding of anatomy and relationships to critical structures. Current imaging regimens include 2D planar CT and MRI, multiplanar reformations, 3D surface enhanced series and 3D printed models. However, Virtual Reality (VR) visualization and planning is a dynamic, immersive experience offering enhanced understanding of complex anatomical relationships, the ability manipulate and layer 3D models and images in real time and allows for multiple participants to engage simultaneously across remote sites. This pilot describes our initial experience with a novel VR planning system. Six patients with complex anatomic tumors were reviewed preoperatively by a multidisciplinary team of orthopaedic oncology surgeons, neurosurgeons, thoracic surgeons, spine surgeons along with a musculoskeletal radiologist. Interactive, on demand modelling of anatomical structures was performed in real time with input from all team members. Three cases involved the chest wall and spine and three cases arose from the pelvis. Pathology included Ewings sarcoma, neuroblastoma, and chondrosarcoma. Three-dimensional models of relevant bony and soft tissue anatomy were derived directly from diagnostic CT and MR imaging using 3D modeling tools in the virtual environment while noting the length of time and cost to prepare cases. The VR system was also validated for model and measurement accuracy via direct comparisons of with a reference system, and for overall ease of use and clinical utility. The Dice-Srensen Coefficient (DSC) was used to score similarity of models generated in VR to those made in the reference platform. On multidisciplinary debrief, each case reviewed in VR provided added information to the surgical team compared to standard imaging. This included better understanding of the tumor margins and relationships to critical structures and, in three cases, modified surgical approach. The platform successfully supported multiple reviewers sharing the same VR environment and allowed for dynamic changes to 2D and 3D visualizations. The mean time to prepare cases was 70 minutes (range 25 −90) dependent on number of anatomical structures to be modeled, representing a mean cost per case of $233 USD (range $85 −$300). DSC values for 3D structures created in VR were 0.97 or higher, confirming geometric accuracy of models relative to a reference system. Measurements of length, cross-sectional area, and angle on clinical CT scans were within 0.22 mm (0.3%), 0.16 mm2 (0.02%), and 0.04 deg (0.07%) or less of expected results, respectively. Lastly, pre-defined usability tests were successfully conducted by 15 volunteer end-users, all of whom yielded accurate measurements and models, and reported high confidence in their use of the platform. VR planning of complex multidisciplinary cases is dynamic, feasible and cost effective providing enhanced appreciation of complex anatomical relationships, leading to increased surgeon confidence and impacting on surgical approach.