Looking to the future: Framing the implementation of interprofessional education and practice with scenario planning

Background: Adapting to interprofessional education and practice requires a change of perspective for many health professionals. We aimed to explore the potential of scenario planning to bridge the understanding gap and framing strategic planning for interprofessional education (IPE) and practice (IPP), as well as to implement innovative techniques and technology for large‑group scenario planning. Methods: A full‑day scenario planning workshop incorporating innovative methodology was designed and offered to participants. The 71 participants included academics from nine universities, as well as service providers, government, students and consumer organisations. The outcomes were evaluated by statistical and thematic analysis of a mixed method survey questionnaire. Results: The scenario planning method resulted in a positive response as a means of collaboratively exploring current knowledge and broadening entrenched attitudes. It was perceived to be an effective instrument for framing strategy for the implementation of IPE/IPP, with 81 percent of respondents to a post‑workshop survey indicating they would consider using scenario planning in their own organisations. Discussion: The scenario planning method can be used by tertiary academic institutions as a strategy in developing, implementing and embedding IPE, and for the enculturation of IPP in practice settings.Government of Western Australia, Department of Health

AUC-guided dosing of tacrolimus prevents progressive systemic overexposure in renal transplant recipients

AUC-guided dosing of tacrolimus prevents progressive systemic overexposure in renal transplant recipients.BackgroundTacrolimus has a narrow therapeutic window, and bioavailability is known to vary considerably between renal transplant recipients. Most centers still rely on measurement of trough levels, but there are conflicting reports on the correlation between tacrolimus trough levels and systemic exposure, as measured by the area-under-the-concentration-over-time curve (AUC(0-12h)).MethodsWe developed and validated a two-compartmental population-based pharmacokinetic model with Bayesian estimation of tacrolimus systemic exposure. Subsequently, we used this model to apply prospectively AUC-guided dosing of tacrolimus in 15 consecutive renal transplant recipients. The main objective was to study intrapatient variability in the course of time.ResultsBayesian forecasting with a two-point sampling strategy, a trough level, and a second sample obtained between two and four hours post-dose significantly improved the squared correlation with the AUC(0-12h) (r2= 0.94). Compared with trough level monitoring only, this approach reduced the 95%-prediction interval by 50%. The Bayesian approach proved to be feasible in clinical practice, and provided accurate information about systemic tacrolimus exposure in individual patients. In the AUC-guided dosing cohort the apparent clearance of tacrolimus decreased gradually over time, which was not reflected in corresponding trough levels.ConclusionThis simple, flexible method provides the opportunity to tailor immunosuppression, and should help minimize tacrolimus-related toxicity, such as nephrotoxicity and post-transplant diabetes mellitus

Scenario planning: the future of the cattle and sheep industries in Scotland and their resiliency to disease

In this paper, we present a description of foresighting activities undertaken by EPIC, Scotland’s Centre of Expertise on Animal Disease Outbreaks, to investigate the future uncertainty of animal health security in the Scottish sheep and cattle sectors. Using scenario planning methodologies, we explored four plausible but provocative long-term futures which identify dynamics underpinning the resilience of these agricultural sectors to animal disease. These scenarios highlight a number of important drivers that influence disease resilience: industry demographics, the role of government support and regulation and the capacity for technological innovation to support the industry to meet local and global market demand. Participants in the scenario planning exercises proposed creative, robust strategies that policy makers could consider implementing now to enhance disease control and industry resilience in multiple, uncertain futures. Using these participant-led strategies as a starting point, we offer ten key questions for policy makers and stakeholders to provoke further discussion about improving resiliency and disease preparedness. We conclude with a brief discussion of the value of scenario planning, not only for the development of futures which will inform disease contingency plans and improve industry resilience, but as a mechanism for dialogue and information sharing between stakeholders and government

Predictive factors for sustained pain after (sub)acute osteoporotic vertebral fractures:Combined results from the VERTOS II and VERTOS IV trial

PURPOSE: Osteoporotic vertebral compression fractures are treated conservatively or in selected cases with percutaneous vertebroplasty (PV). The purpose of this retrospective analysis is to determine predictive factors for a high visual analogue scale (VAS) pain score after conservative, sham or PV and is based on previously published randomized trials. METHODS: The VERTOS II compared conservative versus PV, and VERTOS IV compared sham versus PV treatment. The conservative group received pain medication. The sham and PV group received subcutaneous lidocaine/bupivacaine. In addition, the PV group received cementation, which was simulated in the sham group. Nineteen different predictors of high (≥ 5) versus low ( 8, long-term baseline pain, mild/severe Genant and new fractures. CONCLUSIONS: Statistically significant more patients had a high pain score at 12 months in the sham and conservative group when compared with the PV group. Five predictors were identified for sustained high local back pain, regardless of the received treatment. Patients with moderate fracture deformity were less likely to have high pain scores at 12 months if they received PV than if they had sham or conservative therapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00270-022-03170-7

Construction and Evaluation of Scenarios as a Learning Strategy through Modelling-Simulation

[EN] From a systemic perspective and in the context of an increasing generalization in the use of new technologies and the change in the educational paradigm -which emphasizes guided and autonomous learning-, the learning strategy should be routed to join logical reasoning and instrumental skills (software). The inclusion of new computing and communication resources to the learning process turns them into teaching tools, which makes it possible to organize the teaching and learning process in a different way. The design of these new scenarios of study has important implications to the way information is processed, to the different levels of learning (descriptive, explanatory or analytical ones) and to the way knowledge is acquired and evaluated. In addition, that design takes into account the greater student-content, student-student and student-teacher interactivities, always emphasizing guided independent learning. Thus, the construction, analysis and evaluation of scenarios through models and simulation are the strategy that best suits the current learning style followed by students.Peñaloza Figueroa, JL.; Vargas Perez, C. (2015). Construction and Evaluation of Scenarios as a Learning Strategy through Modelling-Simulation. Multidisciplinary Journal for Education, Social and Technological Sciences. 2(1):40-62. doi:10.4995/muse.2015.2245.SWORD40622

BRCA2 polymorphic stop codon K3326X and the risk of breast, prostate, and ovarian cancers

Background: The K3326X variant in BRCA2 (BRCA2*c.9976A>T; p.Lys3326*; rs11571833) has been found to be associated with small increased risks of breast cancer. However, it is not clear to what extent linkage disequilibrium with fully pathogenic mutations might account for this association. There is scant information about the effect of K3326X in other hormone-related cancers. Methods: Using weighted logistic regression, we analyzed data from the large iCOGS study including 76 637 cancer case patients and 83 796 control patients to estimate odds ratios (ORw) and 95% confidence intervals (CIs) for K3326X variant carriers in relation to breast, ovarian, and prostate cancer risks, with weights defined as probability of not having a pathogenic BRCA2 variant. Using Cox proportional hazards modeling, we also examined the associations of K3326X with breast and ovarian cancer risks among 7183 BRCA1 variant carriers. All statistical tests were two-sided. Results: The K3326X variant was associated with breast (ORw = 1.28, 95% CI = 1.17 to 1.40, P = 5.9x10- 6) and invasive ovarian cancer (ORw = 1.26, 95% CI = 1.10 to 1.43, P = 3.8x10-3). These associations were stronger for serous ovarian cancer and for estrogen receptor–negative breast cancer (ORw = 1.46, 95% CI = 1.2 to 1.70, P = 3.4x10-5 and ORw = 1.50, 95% CI = 1.28 to 1.76, P = 4.1x10-5, respectively). For BRCA1 mutation carriers, there was a statistically significant inverse association of the K3326X variant with risk of ovarian cancer (HR = 0.43, 95% CI = 0.22 to 0.84, P = .013) but no association with breast cancer. No association with prostate cancer was observed. Conclusions: Our study provides evidence that the K3326X variant is associated with risk of developing breast and ovarian cancers independent of other pathogenic variants in BRCA2. Further studies are needed to determine the biological mechanism of action responsible for these associations

High-throughput automated scoring of Ki67 in breast cancer tissue microarrays from the Breast Cancer Association Consortium.

Automated methods are needed to facilitate high-throughput and reproducible scoring of Ki67 and other markers in breast cancer tissue microarrays (TMAs) in large-scale studies. To address this need, we developed an automated protocol for Ki67 scoring and evaluated its performance in studies from the Breast Cancer Association Consortium. We utilized 166 TMAs containing 16,953 tumour cores representing 9,059 breast cancer cases, from 13 studies, with information on other clinical and pathological characteristics. TMAs were stained for Ki67 using standard immunohistochemical procedures, and scanned and digitized using the Ariol system. An automated algorithm was developed for the scoring of Ki67, and scores were compared to computer assisted visual (CAV) scores in a subset of 15 TMAs in a training set. We also assessed the correlation between automated Ki67 scores and other clinical and pathological characteristics. Overall, we observed good discriminatory accuracy (AUC = 85%) and good agreement (kappa = 0.64) between the automated and CAV scoring methods in the training set. The performance of the automated method varied by TMA (kappa range= 0.37-0.87) and study (kappa range = 0.39-0.69). The automated method performed better in satisfactory cores (kappa = 0.68) than suboptimal (kappa = 0.51) cores (p-value for comparison = 0.005); and among cores with higher total nuclei counted by the machine (4,000-4,500 cells: kappa = 0.78) than those with lower counts (50-500 cells: kappa = 0.41; p-value = 0.010). Among the 9,059 cases in this study, the correlations between automated Ki67 and clinical and pathological characteristics were found to be in the expected directions. Our findings indicate that automated scoring of Ki67 can be an efficient method to obtain good quality data across large numbers of TMAs from multicentre studies. However, robust algorithm development and rigorous pre- and post-analytical quality control procedures are necessary in order to ensure satisfactory performance.ABCS was supported by the Dutch Cancer Society [grants NKI 2007-3839; 2009-4363]; BBMRI-NL, which is a Research Infrastructure financed by the Dutch government (NWO 184.021.007); and the Dutch National Genomics Initiative. CNIO-BCS was supported by the Genome Spain Foundation, the Red Tematica de Investigacion Cooperativa en Cancer and grants from the Asociacion Espaola Contra el Cancer and the Fondo de Investigacion Sanitario (PI11/00923 and PI081120). The Human Genotyping-CEGEN Unit (CNIO) is supported by the Instituto de Salud Carlos III. The ESTHER study was supported by a grant from the Baden Wurttemberg Ministry of Science, Research and Arts. Additional cases were recruited in the context of the VERDI study, which was supported by a grant from the German Cancer Aid (Deutsche Krebshilfe). The KBCP was financially supported by the special Government Funding (EVO) of Kuopio University Hospital grants, Cancer Fund of North Savo, the Finnish Cancer Organizations, the Academy of Finland and by the strategic funding of the University of Eastern Finland. We wish to thank Heather Thorne, Eveline Niedermayr, all the kConFab research nurses and staff, the heads and staff of the Family Cancer Clinics, and the Clinical Follow Up Study (which has received funding from the NHMRC, the National Breast Cancer Foundation, Cancer Australia, and the National Institute of Health (USA)) for their contributions to this resource, and the many families who contribute to kConFab. kConFab is supported by a grant from the National Breast Cancer Foundation, and previously by the National Health and Medical Research Council (NHMRC), the Queensland Cancer Fund, the Cancer Councils of New South Wales, Victoria, Tasmania and South Australia, and the Cancer Foundation of Western Australia. The MARIE study was supported by the Deutsche Krebshilfe e.V. [70-2892-BR I, 106332, 108253, 108419], the Hamburg Cancer Society, the German Cancer Research Center (DKFZ) and the Federal Ministry of Education and Research (BMBF) Germany [01KH0402]. The MCBCS was supported by an NIH Specialized Program of Research Excellence (SPORE) in Breast Cancer [CA116201], the Breast Cancer Research Foundation, the Mayo Clinic Breast Cancer Registry and a generous gift from the David F. and Margaret T. Grohne Family Foundation and the Ting Tsung and Wei Fong Chao Foundation. ORIGO authors thank E. Krol-Warmerdam, and J. Blom; The contributing studies were funded by grants from the Dutch Cancer Society (UL1997-1505) and the Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL CP16). PBCS was funded by Intramural Research Funds of the National Cancer Institute, Department of Health and Human Services, USA. The RBCS was funded by the Dutch Cancer Society (DDHK 2004-3124, DDHK 2009-4318). SEARCH is funded by programme grant from Cancer Research UK [C490/A10124. C490/A16561] and supported by the UK National Institute for Health Research Biomedical Research Centre at the University of Cambridge. Part of this work was supported by the European Community’s Seventh Framework Programme under grant agreement number 223175 (grant number HEALTH-F2-2009223175) (COGS). The UKBGS is funded by Breakthrough Breast Cancer and the Institute of Cancer Research (ICR), London. ICR acknowledges NHS funding to the NIHR Biomedical Research Centre. We acknowledge funds from Breakthrough Breast Cancer, UK, in support of MGC at the time this work was carried out and funds from the Cancer Research, UK, in support of MA.This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1002/cjp2.4