Little evidence for genetic variation associated with susceptibility to sea star wasting syndrome in the keystone species Pisaster ochraceus.

The keystone species Pisaster ochraceus suffered mass mortalities along the northeast Pacific Ocean from Sea Star Wasting Syndrome (SSWS) outbreaks in 2013-2016. SSWS causation remains of debate, leading to concerns as to whether outbreaks will continue to impact this species. Considering the apparent link between ocean temperature and SSWS, the future of this species and intertidal communities remains uncertain. Surveys of co-occurring apparently normal and wasting P. ochraceus along the central Oregon coast in 2016 allowed us to address whether variation in disease status showed genetic variation that may be associated with differences in susceptibility to SSWS. We performed restriction site-associated DNA sequencing (2bRAD-seq) to genotype ~72,000 single nucleotide polymorphism (SNP) loci across apparently normal and wasting sea stars. Locus-specific analyses of differentiation (FST ) between disease-status groups revealed no signal of genetic differences separating the two groups. Using a multivariate approach, we observed weak separation between the groups, but identified 18 SNP loci showing highest discriminatory power between the groups and scanned the genome annotation for linked genes. A total of 34 protein-coding genes were found to be located within 15 kb (measured by linkage disequilibrium decay) of at least one of the 18 SNPs, and 30 of these genes had homologies to annotated protein databases. Our results suggest that the likelihood of developing SSWS symptoms does not have a strong genetic basis. The few genomic regions highlighted had only modest levels of differentiation, but the genes associated with these regions may form the basis for functional studies aiming to understand disease progression.

Neuroleptic Malignant Syndrome (NMS) on Clozapine with a Potential Atypical Interaction with Paliperidone.

Neuroleptic Malignant Syndrome (NMS) associated with the use of first-generation antipsychotics is a widely known phenomenon. This idiosyncratic reaction is less significant with the use of second-generation antipsychotics, and only a few cases in the literature exist, describing this reaction with clozapine use. While being titrated on clozapine, the patient developed major and minor criteria features of NMS as per the Diagnostic and Statistical Manual of Mental Disorders, Fifth edition (DSM-5) criteria except for fever, a core symptom which created diagnostic uncertainty. Initially, clozapine was temporarily discontinued due to his deteriorating mental and physical state. A rechallenge was considered at a much lower dose, but due to a rapid increase in his creatinine kinase (CK) levels within a 12-hour timeframe, clozapine was permanently stopped. The evidence further suggests that the presentation of NMS for patients on this medication may be different to the classical presentation, and other criteria for diagnosis are suggested, which may lower the threshold for investigating NMS for patients on clozapine.

Evaluation of software for multiple imputation of semi-continuous data.

It is now widely accepted that multiple imputation (MI) methods properly handle the uncertainty of missing data over single imputation methods. Several standard statistical software packages, such as SAS, R and STATA, have standard procedures or user-written programs to perform MI. The performance of these packages is generally acceptable for most types of data. However, it is unclear whether these applications are appropriate for imputing data with a large proportion of zero values resulting in a semi-continuous distribution. In addition, it is not clear whether the use of these applications is suitable when the distribution of the data needs to be preserved for subsequent analysis. This article reports the findings of a simulation study carried out to evaluate the performance of the MI procedures for handling semi-continuous data within these statistical packages. Complete resource use data on 1060 participants from a large randomized clinical trial were used as the simulation population from which 500 bootstrap samples were obtained and missing data imposed. The findings of this study showed differences in the performance of the MI programs when imputing semi-continuous data. Caution should be exercised when deciding which program should perform MI on this type of data.

A retrospective evaluation of the feasibility of intrapatient dose escalation as appropriate methodology for dose-ranging studies for combination cytotoxic regimens.

PURPOSE: To investigate the feasibility of intrapatient dose-escalation methodology for dose-ranging studies of conventional cytotoxics in combination. PATIENTS AND METHODS: Case records were identified for patients with ovarian cancer treated first-line with either single-agent carboplatin or carboplatin and paclitaxel in combination and routinely subjected to a 10% dose escalation in carboplatin at each cycle, towards a target day-22 neutrophil count in the range 1.0-1.5x10(9)/l and a platelet count in the range 75-110x10(9)/l, defining adequate dose. 'Entry level' carboplatin doses were in the range AUC 5.1 to AUC 7.4; paclitaxel was given at 175 mg/m(2) as a 3-h infusion throughout. All drugs were administered three-weekly. RESULTS: The distribution of carboplatin maximum tolerated doses (MTDs) indicated a wide interpatient variation, ranging from AUC 5.4 to AUC 9.8. The median MTD in those receiving carboplatin alone (AUC 6.9) was significantly lower than in those treated with carboplatin and paclitaxel (AUC 7.6) ( P=0.01). Also, paclitaxel had both neutrophil- and platelet-protective effects. CONCLUSIONS: The median MTD documented here using intrapatient dose escalation for carboplatin combined with paclitaxel is remarkably similar to that derived from conventional phase I studies. Furthermore, the striking range of carboplatin MTDs recorded in previously untreated patients may have implications for the wider development of management strategies based on the adequacy of treatment, as defined by the modest levels of dose-limiting toxicity encountered. The ready availability of an expanded set of MTD data by this methodology may also provide more compelling evidence about potential pharmacodynamic drug interactions than may be available from conventional phase I combination studies. These retrospective findings clearly justify further prospective evaluation of intrapatient dose-escalation methodology in dose-ranging studies.

Synthesis of systematic review evidence of interprofessional education.

Interprofessional education (IPE) continues to be a central focus within health care and research spheres. As a result, there is a sustained interest in understanding its overall effects on learners, professions, organizations, and patients. Systematic reviews are instrumental in assessing evidence and informing disciplinary fields about the effects of interventions and providing direction for future activity and research. This paper provides a synthesis and critical appraisal of the evidence for IPE contained in the small, but growing, systematic review literature. Six IPE reviews were located. In general, the reviews shared similar definitions of IPE and similar methodological approaches to their inclusion of studies. Findings from the synthesis indicated that IPE varied in terms of content, duration, and professional participation. The synthesis also indicated that studies that evaluated this form of education were of variable quality and captured a range of different outcomes-from reports of learner satisfaction to changes in the delivery of care. While a number of methodological problems were found, in general the synthesis indicated that IPE delivered in a variety of settings was generally well received by learners and enabled the acquisition of knowledge and skills necessary for collaborative working. Some evidence was also found that IPE can improve the delivery of services and make a positive impact on care. The paper goes on to discuss the synthesis findings in relation to the most recent IPE literature and also offers a series of suggestions for future directions.

Cost-effectiveness in clinical trials: using multiple imputation to deal with incomplete cost data.

BACKGROUND: Cost-effectiveness has become an important outcome in many clinical trials and has resulted in the collection of resource use data and the calculation of costs for individual patients. A specific example is a Cancer Research UK phase III trial comparing chemotherapy (CT) against standard palliative care in patients with advanced non-small cell lung cancer. Resource usage from trial entry until death were collected and costs obtained on a subset of 115 trial patients. For some patients, however, the unavailability of medical notes resulted in some cost components, and hence total cost, being missing. The 82 patients with complete data were not representative of all trial patients in terms of effectiveness and thus it was necessary to address the missing data problem. METHODS: Multiple imputation (MI) was used to impute values for the unobserved individual cost components, allowing total cost to be calculated and cost-effectiveness carried out for all patients in the cost sub-study. The results are compared with those from a complete case analysis. RESULTS: After MI, the results indicated that CT had a high probability of being cost-effective for a societal willingness to pay over 20,000 Pounds per life-year gained. This was in stark contrast with the complete case analysis, which suggested that CT was not a cost-effective use of resources at any reasonable level of willingness to pay for a life-year. LIMITATIONS: Our findings are based on a relatively small retrospective study with all events observed. CONCLUSION: In conclusion, cost-effectiveness analysis of the complete cases only may give biased results, and therefore, in situations where there are missing costs, MI is recommended.

The design of simulation studies in medical statistics.

Simulation studies use computer intensive procedures to assess the performance of a variety of statistical methods in relation to a known truth. Such evaluation cannot be achieved with studies of real data alone. Designing high-quality simulations that reflect the complex situations seen in practice, such as in prognostic factors studies, is not a simple process. Unfortunately, very few published simulation studies provide sufficient details to allow readers to understand fully all the processes required to design a simulation study. When planning a simulation study, it is recommended that a detailed protocol be produced, giving full details of how the study will be performed, analysed and reported. This paper details the important considerations necessary when designing any simulation study, including defining specific objectives of the study, determining the procedures for generating the data sets and the number of simulations to perform. A checklist highlighting the important considerations when designing a simulation study is provided. A small review of the literature identifies the current practices within published simulation studies.