Estimating the number needed to treat from continuous outcomes in randomised controlled trials: methodological challenges and worked example using data from the UK Back Pain Exercise and Manipulation (BEAM) trial

Background Reporting numbers needed to treat (NNT) improves interpretability of trial results. It is unusual that continuous outcomes are converted to numbers of individual responders to treatment (i.e., those who reach a particular threshold of change); and deteriorations prevented are only rarely considered. We consider how numbers needed to treat can be derived from continuous outcomes; illustrated with a worked example showing the methods and challenges. Methods We used data from the UK BEAM trial (n = 1, 334) of physical treatments for back pain; originally reported as showing, at best, small to moderate benefits. Participants were randomised to receive 'best care' in general practice, the comparator treatment, or one of three manual and/or exercise treatments: 'best care' plus manipulation, exercise, or manipulation followed by exercise. We used established consensus thresholds for improvement in Roland-Morris disability questionnaire scores at three and twelve months to derive NNTs for improvements and for benefits (improvements gained+deteriorations prevented). Results At three months, NNT estimates ranged from 5.1 (95% CI 3.4 to 10.7) to 9.0 (5.0 to 45.5) for exercise, 5.0 (3.4 to 9.8) to 5.4 (3.8 to 9.9) for manipulation, and 3.3 (2.5 to 4.9) to 4.8 (3.5 to 7.8) for manipulation followed by exercise. Corresponding between-group mean differences in the Roland-Morris disability questionnaire were 1.6 (0.8 to 2.3), 1.4 (0.6 to 2.1), and 1.9 (1.2 to 2.6) points. Conclusion In contrast to small mean differences originally reported, NNTs were small and could be attractive to clinicians, patients, and purchasers. NNTs can aid the interpretation of results of trials using continuous outcomes. Where possible, these should be reported alongside mean differences. Challenges remain in calculating NNTs for some continuous outcomes

Artificial intelligence and machine learning algorithms for early detection of skin cancer in community and primary care settings: a systematic review.

Skin cancers occur commonly worldwide. The prognosis and disease burden are highly dependent on the cancer type and disease stage at diagnosis. We systematically reviewed studies on artificial intelligence and machine learning (AI/ML) algorithms that aim to facilitate the early diagnosis of skin cancers, focusing on their application in primary and community care settings. We searched MEDLINE, Embase, Scopus, and Web of Science (from Jan 1, 2000, to Aug 9, 2021) for all studies providing evidence on applying AI/ML algorithms to the early diagnosis of skin cancer, including all study designs and languages. The primary outcome was diagnostic accuracy of the algorithms for skin cancers. The secondary outcomes included an overview of AI/ML methods, evaluation approaches, cost-effectiveness, and acceptability to patients and clinicians. We identified 14 224 studies. Only two studies used data from clinical settings with a low prevalence of skin cancers. We reported data from all 272 studies that could be relevant in primary care. The primary outcomes showed reasonable mean diagnostic accuracy for melanoma (89·5% [range 59·7-100%]), squamous cell carcinoma (85·3% [71·0-97·8%]), and basal cell carcinoma (87·6% [70·0-99·7%]). The secondary outcomes showed a heterogeneity of AI/ML methods and study designs, with high amounts of incomplete reporting (eg, patient demographics and methods of data collection). Few studies used data on populations with a low prevalence of skin cancers to train and test their algorithms; therefore, the widespread adoption into community and primary care practice cannot currently be recommended until efficacy in these populations is shown. We did not identify any health economic, patient, or clinician acceptability data for any of the included studies. We propose a methodological checklist for use in the development of new AI/ML algorithms to detect skin cancer, to facilitate their design, evaluation, and implementation

Ultrahard carbon film from epitaxial two-layer graphene

Atomically thin graphene exhibits fascinating mechanical properties, although its hardness and transverse stiffness are inferior to those of diamond. To date, there hasn't been any practical demonstration of the transformation of multi-layer graphene into diamond-like ultra-hard structures. Here we show that at room temperature and after nano-indentation, two-layer graphene on SiC(0001) exhibits a transverse stiffness and hardness comparable to diamond, resisting to perforation with a diamond indenter, and showing a reversible drop in electrical conductivity upon indentation. Density functional theory calculations suggest that upon compression, the two-layer graphene film transforms into a diamond-like film, producing both elastic deformations and sp2-to-sp3 chemical changes. Experiments and calculations show that this reversible phase change is not observed for a single buffer layer on SiC or graphene films thicker than 3 to 5 layers. Indeed, calculations show that whereas in two-layer graphene layer-stacking configuration controls the conformation of the diamond-like film, in a multilayer film it hinders the phase transformation.Comment: Published online on Nature Nanotechnology on December 18, 201

Membranes by the Numbers

Many of the most important processes in cells take place on and across membranes. With the rise of an impressive array of powerful quantitative methods for characterizing these membranes, it is an opportune time to reflect on the structure and function of membranes from the point of view of biological numeracy. To that end, in this article, I review the quantitative parameters that characterize the mechanical, electrical and transport properties of membranes and carry out a number of corresponding order of magnitude estimates that help us understand the values of those parameters.Comment: 27 pages, 12 figure

Older adults' attitudes about continuing cancer screening later in life: a pilot study interviewing residents of two continuing care communities

BACKGROUND: Individualized decision making has been recommended for cancer screening decisions in older adults. Because older adults' preferences are central to individualized decisions, we assessed older adults' perspectives about continuing cancer screening later in life. METHODS: Face to face interviews with 116 residents age 70 or over from two long-term care retirement communities. Interview content included questions about whether participants had discussed cancer screening with their physicians since turning age 70, their attitudes about information important for individualized decisions, and their attitudes about continuing cancer screening later in life. RESULTS: Forty-nine percent of participants reported that they had an opportunity to discuss cancer screening with their physician since turning age 70; 89% would have preferred to have had these discussions. Sixty-two percent believed their own life expectancy was not important for decision making, and 48% preferred not to discuss life expectancy. Attitudes about continuing cancer screening were favorable. Most participants reported that they would continue screening throughout their lives and 43% would consider getting screened even if their doctors recommended against it. Only 13% thought that they would not live long enough to benefit from cancer screening tests. Factors important to consider stopping include: age, deteriorating or poor health, concerns about the effectiveness of the tests, and doctors recommendations. CONCLUSION: This select group of older adults held positive attitudes about continuing cancer screening later in life, and many may have had unrealistic expectations. Individualized decision making could help clarify how life expectancy affects the potential survival benefits of cancer screening. Future research is needed to determine whether educating older adults about the importance of longevity in screening decisions would be acceptable, affect older adults' attitudes about screening, or change their screening behavior

The value of predicting restriction of fetal growth and compromise of its wellbeing: Systematic quantitative overviews (meta-analysis) of test accuracy literature

BACKGROUND: Restriction of fetal growth and compromise of fetal wellbeing remain significant causes of perinatal death and childhood disability. At present, there is a lack of scientific consensus about the best strategies for predicting these conditions before birth. Therefore, there is uncertainty about the best management of pregnant women who might have a growth restricted baby. This is likely to be due to a dearth of clear collated information from individual research studies drawn from different sources on this subject. METHODS/DESIGN: A series of systematic reviews and meta-analyses will be undertaken to determine, among pregnant women, the accuracy of various tests to predict and/or diagnose fetal growth restriction and compromise of fetal wellbeing. We will search Medline, Embase, Cochrane Library, MEDION, citation lists of review articles and eligible primary articles and will contact experts in the field. Independent reviewers will select studies, extract data and assess study quality according to established criteria. Language restrictions will not be applied. Data synthesis will involve meta-analysis (where appropriate), exploration of heterogeneity and publication bias. DISCUSSION: The project will collate and synthesise the available evidence regarding the value of the tests for predicting restriction of fetal growth and compromise of fetal wellbeing. The systematic overviews will assess the quality of the available evidence, estimate the magnitude of potential benefits, identify those tests with good predictive value and help formulate practice recommendations

Case-oriented computer-based-training in radiology: concept, implementation and evaluation

BACKGROUND: Providing high-quality clinical cases is important for teaching radiology. We developed, implemented and evaluated a program for a university hospital to support this task. METHODS: The system was built with Intranet technology and connected to the Picture Archiving and Communications System (PACS). It contains cases for every user group from students to attendants and is structured according to the ACR-code (American College of Radiology) [2]. Each department member was given an individual account, could gather his teaching cases and put the completed cases into the common database. RESULTS: During 18 months 583 cases containing 4136 images involving all radiological techniques were compiled and 350 cases put into the common case repository. Workflow integration as well as individual interest influenced the personal efforts to participate but an increasing number of cases and minor modifications of the program improved user acceptance continuously. 101 students went through an evaluation which showed a high level of acceptance and a special interest in elaborate documentation. CONCLUSION: Electronic access to reference cases for all department members anytime anywhere is feasible. Critical success factors are workflow integration, reliability, efficient retrieval strategies and incentives for case authoring