Standing together for reproducibility in large-scale computing: report on reproducibility@XSEDE

This is the final report on reproducibility@xsede, a one-day workshop held in conjunction with XSEDE14, the annual conference of the Extreme Science and Engineering Discovery Environment (XSEDE). The workshop's discussion-oriented agenda focused on reproducibility in large-scale computational research. Two important themes capture the spirit of the workshop submissions and discussions: (1) organizational stakeholders, especially supercomputer centers, are in a unique position to promote, enable, and support reproducible research; and (2) individual researchers should conduct each experiment as though someone will replicate that experiment. Participants documented numerous issues, questions, technologies, practices, and potentially promising initiatives emerging from the discussion, but also highlighted four areas of particular interest to XSEDE: (1) documentation and training that promotes reproducible research; (2) system-level tools that provide build- and run-time information at the level of the individual job; (3) the need to model best practices in research collaborations involving XSEDE staff; and (4) continued work on gateways and related technologies. In addition, an intriguing question emerged from the day's interactions: would there be value in establishing an annual award for excellence in reproducible research? Overvie

The impact of surgical delay on resectability of colorectal cancer: An international prospective cohort study

AIM: The SARS-CoV-2 pandemic has provided a unique opportunity to explore the impact of surgical delays on cancer resectability. This study aimed to compare resectability for colorectal cancer patients undergoing delayed versus non-delayed surgery. METHODS: This was an international prospective cohort study of consecutive colorectal cancer patients with a decision for curative surgery (January-April 2020). Surgical delay was defined as an operation taking place more than 4 weeks after treatment decision, in a patient who did not receive neoadjuvant therapy. A subgroup analysis explored the effects of delay in elective patients only. The impact of longer delays was explored in a sensitivity analysis. The primary outcome was complete resection, defined as curative resection with an R0 margin. RESULTS: Overall, 5453 patients from 304 hospitals in 47 countries were included, of whom 6.6% (358/5453) did not receive their planned operation. Of the 4304 operated patients without neoadjuvant therapy, 40.5% (1744/4304) were delayed beyond 4 weeks. Delayed patients were more likely to be older, men, more comorbid, have higher body mass index and have rectal cancer and early stage disease. Delayed patients had higher unadjusted rates of complete resection (93.7% vs. 91.9%, P = 0.032) and lower rates of emergency surgery (4.5% vs. 22.5%, P < 0.001). After adjustment, delay was not associated with a lower rate of complete resection (OR 1.18, 95% CI 0.90-1.55, P = 0.224), which was consistent in elective patients only (OR 0.94, 95% CI 0.69-1.27, P = 0.672). Longer delays were not associated with poorer outcomes. CONCLUSION: One in 15 colorectal cancer patients did not receive their planned operation during the first wave of COVID-19. Surgical delay did not appear to compromise resectability, raising the hypothesis that any reduction in long-term survival attributable to delays is likely to be due to micro-metastatic disease

Dynamic pricing in regulated automobile insurance markets with heterogeneous insurers: Strategies nice versus nasty for customers

This study examines a phenomenon in one nation's automobile insurance market where insurers adopt diverse pricing strategies in this regulated industry that does not allow for such diversions—a homogeneous, insurance industry in which a government authority sets the official pricing formula as well as all of the rating factors. Insurers use a claim coefficient that reflects previous claim records of policyholder as an implicit pricing tool to over/under charge new and repeat customers. The aim here is not so much to blow-the-whistle on pricing practices that violate regulations but to describe execution details of the practices and their outcomes. The results show that firm-level, systematic, price variances that occur differ from prices that follow from applying regulated individual-claim coefficients. Based on the unique firm-level pricing strategies, this study finds that some insurers are more nice to new customers and nasty to repeat customers to increase market shares while other insurers earn high profits by being nasty to repeat customers. The assumption that a behavioral primacy effect may exist in the market may guide some firms' pricing strategies

Organized blood pressure control programs to prevent stroke in Australia : would they be cost-effective?

Background and Purpose&mdash;: High blood pressure (BP) is the most important modifiable stroke risk factor. Worldwide high BP in many people is uncontrolled or people are unaware of their BP status. We aimed to assess whether a program of organized multidisciplinary care and medication would be cost-effective for improving BP control for the prevention of stroke.Methods&mdash;: A novel aspect was to simulate the intervention to match recent primary care initiatives (eg, new Medicare reimbursement items) to ensure policy relevance. Current practice and additional costs of each intervention were included using the best available evidence. The differences in the cost per quality-adjusted life year (QALY) gained for the interventions were compared against current practice. Cost-effectiveness was defined as cost per QALY gained was less than Australian dollars (AUD) 50 000 (societal perspective; reference year 2004). The robustness of estimates was assessed with probabilistic multivariable uncertainty analysis.Results&mdash;: For primary prevention, the median cost per QALY gained was AUD11 068 (95% uncertainty interval AUD5201 to AUD18 696) in those aged 75 years or older and was AUD17 359 (95% uncertainty interval AUD10 516 to AUD26 036) in those aged 55 to 84 years with &gt;=15% absolute risk of stroke. Primary prevention interventions were not cost-effective if aged younger than 50 years. The median cost per QALY gained for secondary prevention was AUD1811 and AUD4704, depending on which medications were modeled. Conclusions&mdash;: Organized care for BP control targeted at specific populations offers excellent value over current practice. Organized care for secondary prevention provided the greatest benefits and strongest cost-effectiveness. Translation into clinical practice requires improved use of relevant Medicare policy in Australia

PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies

Prediction models in health care use predictors to estimate for an individual the probability that a condition or disease is already present (diagnostic model) or will occur in the future (prognostic model). Publications on prediction models have become more common in recent years, and competing prediction models frequently exist for the same outcome or target population. Health care providers, guideline developers, and policymakers are often unsure which model to use or recommend, and in which persons or settings. Hence, systematic reviews of these studies are increasingly demanded, required, and performed. A key part of a systematic review of prediction models is examination of risk of bias and applicability to the intended population and setting. To help reviewers with this process, the authors developed PROBAST (Prediction model Risk Of Bias ASsessment Tool) for studies developing, validating, or updating (for example, extending) prediction models, both diagnostic and prognostic. PROBAST was developed through a consensus process involving a group of experts in the field. It includes 20 signaling questions across 4 domains (participants, predictors, outcome, and analysis). This explanation and elaboration document describes the rationale for including each domain and signaling question and guides researchers, reviewers, readers, and guideline developers in how to use them to assess risk of bias and applicability concerns. All concepts are illustrated with published examples across different topics. The latest version of the PROBAST checklist, accompanying documents, and filled-in examples can be downloaded from www.probast.org.Drs. Moons and Reitsma received financial support from the Netherlands Organisation for Scientific Research (ZONMW 918.10.615 and 91208004). Dr. Riley is a member of the Evidence Synthesis Working Group funded by the NIHR School for Primary Care Research (project 390). Dr. Whiting (time) was supported by the NIHR Collaboration for Leadership in Applied Health Research and Care West at University Hospitals Bristol NHS Foundation Trust. Dr. Collins was supported by the NIHR Biomedical Research Centre, Oxford. Dr. Mallett is supported by NIHR Birmingham Biomedical Research Centre at the University Hospitals Birmingham NHS Foundation Trust and the University of Birmingham