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Background: Older adults with bacterial skin infections may present with atypical symptoms, making diagnosis difficult. There is limited authoritative guidance on how older adults in the community present with bacterial skin infections. To date there have been no systematic reviews assessing the diagnostic value of symptoms and signs in identifying bacterial skin infections in older adults in the community. Methods: We searched Medline and Medline in process, Embase and Web of Science, from inception to September 2017. We included cohort and cross-sectional studies assessing the diagnostic accuracy of symptoms and signs in predicting bacterial skin infections in adults in primary care aged over 65 years. The QUADAS-2 tool was used to assess study quality. Results: We identified two observational studies of low-moderate quality, with a total of 7991 participants, providing data to calculate the diagnostic accuracy of 5 unique symptoms in predicting bacterial skin infections. The presence of wounds [LR+: 7.93 (CI 4.81-13.1)], pressure sores [LR+: 4.85 (CI 2.18-10.8)] and skin ulcers [LR+: 6.26 (CI 5.49-7.13)] help to diagnose bacterial skin infections. The presence of urinary incontinence does not help to predict bacterial skin infections (LR + 's of 0.99 and 1.04; LR-'s of 0.96 and 1.04). Conclusions: Currently, there is insufficient evidence to inform the diagnosis of bacterial skin infections in older adults in the community; clinicians should therefore rely upon their clinical judgement and experience. Evidence from high quality primary care studies in older adults, including studies assessing symptoms traditionally associated with bacterial skin infections (e.g. erythema and warmth), is urgently needed to guide practice.
\n \n\n \n \nThis is the protocol for a review and there is no abstract. The objectives are as follows: The main aim of this review will be to assess the effects of changing practitioner empathy or patient expectations for all conditions. The main objective is to conduct a systematic review of randomised trials where the intervention involves manipulating either (a) practitioner empathy or (b) patient expectations, or (c) both.
\n \n\n \n \nObjectives: To critically appraise and evaluate the diagnostic value of symptoms and signs in identifying UTI in older adult outpatients, using evidence from observational studies. Methods: We searched Medline and Medline in process, Embase and Web of Science, from inception up to September 2017. We included studies assessing the diagnostic accuracy of symptoms and/or signs in predicting UTI in outpatients aged 65 years and above. Study quality was assessed using the QUADAS-2 tool. Results: We identified 15 eligible studies of variable quality, with a total of 12,039 participants (range 65\u20134259), and assessed the diagnostic accuracy of 66 different symptoms and signs in predicting UTI. A number of symptoms and signs typically associated with UTI, such as nocturia, urgency and abnormal vital signs, were of limited use in older adult outpatients. Inability to perform a number of acts of daily living were predictors of UTI: For example, disability in feeding oneself, + ve LR: 11.8 (95% CI 5.51\u201325.2) and disability in washing one's hands and face, + ve LR: 6.84 (95% CI 4.08\u201311.5). Conclusions: The limited evidence of varying quality shows that a number of symptoms and signs traditionally associated with UTI may have limited diagnostic value in older adult outpatients.
\n \n\n \n \nThis is a protocol for a Cochrane Review (Intervention). The objectives are as follows: The primary objectives are to summarise the evidence from Cochrane Reviews that assessed the effect of behavioural interventions designed to support smoking cessation attempts, and address the following two questions: How do modes of delivery, person delivering the intervention, and the behavioural and motivational components of behavioural interventions for smoking cessation compare with each other in achieving abstinence at follow-up of six months or longer? Do the effects of behavioural interventions vary by other characteristics, including population, setting, and length of intervention? The secondary objective of this review is to summarise the availability and principal findings of economic evaluations of behavioural interventions for smoking cessation, in terms of comparative costs and cost-effectiveness, in the form of a brief economic commentary.
\n \n\n \n \nBackground Competitions might encourage people to undertake and/or reinforce behaviour change, including smoking cessation. Competitions involve individuals or groups having the opportunity to win a prize following successful cessation, either through direct competition or by entry into a lottery or raffle. Objectives To determine whether competitions lead to higher long-term smoking quitrates.We also aimed to examine the impact on the population, the costs, and the unintended consequences of smoking cessation competitions. Search methods This review has merged two previous Cochrane reviews. Here we include studies testing competitions from the reviews 'Competitions and incentives for smoking cessation' and 'Quit &Win interventions for smoking cessation'. We updated the evidence by searching the Cochrane Tobacco Addiction Group Specialized Register in June 2018. Selection criteria We considered randomized controlled trials (RCTs), allocating individuals, workplaces, groups within workplaces, or communities to experimental or control conditions. We also considered controlled studies with baseline and post-intervention measures in which participants were assigned to interventions by the investigators. Participants were smokers, of any age and gender, in any setting. Eligible interventions were contests, competitions, lotteries, and raffles, to reward cessation and continuous abstinence in smoking cessation programmes. Data collection and analysis For this update, data from new studies were extracted independently by two review authors. The primary outcome measure was abstinence from smoking at least six months from the start of the intervention. We performed meta-analyses to pool study effects where suitable data were available and where the effect of the competition component could be separated from that of other intervention components, and report other findings narratively. Main results Twenty studies met our inclusion criteria. Five investigated performance-based reward, where groups of smokers competed against each other to win a prize (N = 915). The remaining 15 used performance-based eligibility, where cessation resulted in entry into a prize draw (N = 10,580). Five of these used Quit &Win contests (N = 4282), of which three were population-level interventions. Fourteen studies were RCTs, and the remainder quasi-randomized or controlled trials. Six had suitable abstinence data for a meta-analysis, which did not show evidence of effectiveness of performance-based eligibility interventions (risk ratio (RR) 1.16, 95% confidence interval (CI) 0.77 to 1.74, N = 3201, I2 = 57%). No trials that used performance-based rewards found a beneficial effect of the intervention on long-term quit rates. The three population-level Quit &Win studies found higher smoking cessation rates in the intervention group (4% to 16.9%) than the control group at long-term follow-up, but none were RCTs and all had important between-group differences in baseline characteristics. These studies suggested that fewer than one in 500 smokers would quit because of the contest. Reported unintended consequences in all sets of studies generally related to discrepancies between self-reported smoking status and biochemically-verified smoking status. More serious adverse events were not attributed to the competition intervention. Using the GRADE system we rated the overall quality of the evidence for smoking cessation as 'very low', because of the high and unclear risk of bias associated with the included studies, substantial clinical and methodological heterogeneity, and the limited population investigated. Authors' conclusions At present, it is impossible to draw any firm conclusions about the effectiveness, or a lack of it, of smoking cessation competitions. This is due to a lack of well-designed comparative studies. Smoking cessation competitions have not been shown to enhance longterm cessation rates. The limited evidence suggesting that population-based Quit &Win contests at local and regional level might deliver quit rates above baseline community rates has not been tested adequately using rigorous study designs. It is also unclear whether the value or frequency of possible cash reward schedules influence the success of competitions. Future studies should be designed to compensate for the substantial biases in the current evidence base.
\n \n\n \n \nBackground Nicotine replacement therapy (NRT) aims to replace nicotine from cigarettes to ease the transition from cigarette smoking to abstinence. It works by reducing the intensity of craving and withdrawal symptoms. Although there is clear evidence that NRT used after smoking cessation is effective, it is unclear whether higher doses, longer durations of treatment, or using NRT before cessation add to its effectiveness. Objectives To determine the effectiveness and safety of different forms, deliveries, doses, durations and schedules of NRT, for achieving long-term smoking cessation, compared to one another. Search methods We searched the Cochrane Tobacco Addiction Group trials register, and trial registries for papers mentioning NRT in the title, abstract or keywords. Date of most recent search: April 2018. Selection criteria Randomized trials in people motivated to quit, comparing one type of NRT use with another. We excluded trials that did not assess cessation as an outcome, with follow-up less than six months, and with additional intervention components not matched between arms. Trials comparing NRT to control, and trials comparing NRT to other pharmacotherapies, are covered elsewhere. Data collection and analysis We followed standard Cochrane methods. Smoking abstinence was measured after at least six months, using the most rigorous definition available. We extracted data on cardiac adverse events (AEs), serious adverse events (SAEs), and study withdrawals due to treatment. We calculated the risk ratio (RR) and the 95% confidence interval (CI) for each outcome for each study, where possible. We grouped eligible studies according to the type of comparison. We carried out meta-analyses where appropriate, using a Mantel-Haenszel fixed-effect model. Main results We identified 63 trials with 41,509 participants. Most recruited adults either from the community or from healthcare clinics. People enrolled in the studies typically smoked at least 15 cigarettes a day. We judged 24 of the 63 studies to be at high risk of bias, but restricting the analysis only to those studies at low or unclear risk of bias did not significantly alter results, apart from in the case of the preloading comparison. There is high-certainty evidence that combination NRT (fast-acting form + patch) results in higher long-term quit rates than single form (RR 1.25, 95% CI 1.15 to 1.36, 14 studies, 11,356 participants; I2 = 4%). Moderate-certainty evidence, limited by imprecision, indicates that 42/44 mg are as effective as 21/22 mg (24-hour) patches (RR 1.09, 95% CI 0.93 to 1.29, 5 studies, 1655 participants; I2 = 38%), and that 21 mg are more effective than 14 mg (24-hour) patches (RR 1.48, 95% CI 1.06 to 2.08, 1 study, 537 participants). Moderate-certainty evidence (again limited by imprecision) also suggests a benefit of 25 mg over 15 mg (16-hour) patches, but the lower limit of the CI encompassed no difference (RR 1.19, 95% CI 1.00 to 1.41, 3 studies, 3446 participants; I2 = 0%). Five studies comparing 4 mg gum to 2 mg gum found a benefit of the higher dose (RR 1.43, 95% CI 1.12 to 1.83, 5 studies, 856 participants; I2 = 63%); however, results of a subgroup analysis suggest that only smokers who are highly dependent may benefit. Nine studies tested the effect of using NRT prior to quit day (preloading) in comparison to using it from quit day onward; there was moderate-certainty evidence, limited by risk of bias, of a favourable effect of preloading on abstinence (RR 1.25, 95% CI 1.08 to 1.44, 9 studies, 4395 participants; I2 = 0%). High-certainty evidence from eight studies suggests that using either a form of fast-acting NRT or a nicotine patch results in similar long-term quit rates (RR 0.90, 95% CI 0.77 to 1.05, 8 studies, 3319 participants; I2 = 0%). We found no evidence of an effect of duration of nicotine patch use (low-certainty evidence); 16-hour versus 24-hour daily patch use; duration of combination NRT use (low-and very low-certainty evidence); tapering of patch dose versus abrupt patch cessation; fast-acting NRT type (very low-certainty evidence); duration of nicotine gum use; ad lib versus fixed dosing of fast-acting NRT; free versus purchased NRT; length of provision of free NRT; ceasing versus continuing patch use on lapse; and participant-versus clinician-selected NRT. However, in most cases these findings are based on very low-or low-certainty evidence, and are the findings from single studies. AEs, SAEs and withdrawals due to treatment were all measured variably and infrequently across studies, resulting in low-or very low-certainty evidence for all comparisons. Most comparisons found no evidence of an effect on cardiac AEs, SAEs or withdrawals. Rates of these were low overall. Significantly more withdrawals due to treatment were reported in participants using nasal spray in comparison to patch in one trial (RR 3.47, 95% CI 1.15 to 10.46, 922 participants; very low certainty) and in participants using 42/44 mg patches in comparison to 21/22 mg patches across two trials (RR 4.99, 95% CI 1.60 to 15.50, 2 studies, 544 participants; I2 = 0%; low certainty). Authors\u2019 conclusions There is high-certainty evidence that using combination NRT versus single-form NRT, and 4 mg versus 2 mg nicotine gum, can increase the chances of successfully stopping smoking. For patch dose comparisons, evidence was of moderate certainty, due to imprecision. Twenty-one mg patches resulted in higher quit rates than 14 mg (24-hour) patches, and using 25 mg patches resulted in higher quit rates than using 15 mg (16-hour) patches, although in the latter case the CI included one. There was no clear evidence of superiority for 42/44 mg over 21/22 mg (24-hour) patches. Using a fast-acting form of NRT, such as gum or lozenge, resulted in similar quit rates to nicotine patches. There is moderate-certainty evidence that using NRT prior to quitting may improve quit rates versus using it from quit date only; however, further research is needed to ensure the robustness of this finding. Evidence for the comparative safety and tolerability of different types of NRT use is of low and very low certainty. New studies should ensure that AEs, SAEs and withdrawals due to treatment are both measured and reported.
\n \n\n \n \nBackground: Most tobacco control programmes for adolescents are based around prevention of uptake, but teenage smoking is still common. It is unclear if interventions that are effective for adults can also help adolescents to quit. This is the update of a Cochrane Review first published in 2006. Objectives: To evaluate the effectiveness of strategies that help young people to stop smoking tobacco. Search methods: We searched the Cochrane Tobacco Addiction Group's Specialized Register in June 2017. This includes reports for trials identified in CENTRAL, MEDLINE, Embase and PsyclNFO. Selection criteria: We included individually and cluster-randomized controlled trials recruiting young people, aged under 20 years, who were regular tobacco smokers. We included any interventions for smoking cessation; these could include pharmacotherapy, psycho-social interventions and complex programmes targeting families, schools or communities. We excluded programmes primarily aimed at prevention of uptake. The primary outcome was smoking status after at least six months' follow-up among those who smoked at baseline. Data collection and analysis: Two review authors independently assessed the eligibility of candidate trials and extracted data. We evaluated included studies for risk of bias using standard Cochrane methodology and grouped them by intervention type and by the theoretical basis of the intervention. Where meta-analysis was appropriate, we estimated pooled risk ratios using a Mantel-Haenszel fixed-effect method, based on the quit rates at six months' follow-up. Main results: Forty-one trials involving more than 13,000 young people met our inclusion criteria (26 individually randomized controlled trials and 15 cluster-randomized trials). We judged the majority of studies to be at high or unclear risk of bias in at least one domain. Interventions were varied, with the majority adopting forms of individual or group counselling, with or without additional self-help materials to form complex interventions. Eight studies used primarily computer or messaging interventions, and four small studies used pharmacological interventions (nicotine patch or gum, or bupropion). There was evidence of an intervention effect for group counselling (9 studies, risk ratio (RR) 1.35, 95% confidence interval (CI) 1.03 to 1.77), but not for individual counselling (7 studies, RR 1.07, 95% CI 0.83 to 1.39), mixed delivery methods (8 studies, RR 1.26, 95% CI 0.95 to 1.66) or the computer or messaging interventions (pooled RRs between 0.79 and 1.18, 9 studies in total). There was no clear evidence for the effectiveness of pharmacological interventions, although confidence intervals were wide (nicotine replacement therapy 3 studies, RR 1.11, 95% CI 0.48 to 2.58; bupropion 1 study RR 1.49, 95% CI 0.55 to 4.02). No subgroup precluded the possibility of a clinically important effect. Studies of pharmacotherapies reported some adverse events considered related to study treatment, though most were mild, whereas no adverse events were reported in studies of behavioural interventions. Our certainty in the findings for all comparisons is low or very low, mainly because of the clinical heterogeneity of the interventions, imprecision in the effect size estimates, and issues with risk of bias. Authors' conclusions: There is limited evidence that either behavioural support or smoking cessation medication increases the proportion of young people that stop smoking in the long-term. Findings are most promising for group-based behavioural interventions, but evidence remains limited for all intervention types. There continues to be a need for well-designed, adequately powered, randomized controlled trials of interventions for this population of smokers.
\n \n\n \n \nBackground: Although smoking cessation is currently the only guaranteed way to reduce the harm caused by tobacco smoking, a reasonable secondary tobacco control approach may be to try and reduce the harm from continued tobacco use amongst smokers unable or unwilling to quit. Possible approaches to reduce the exposure to toxins from smoking include reducing the amount of tobacco used, and using less toxic products, such as pharmaceutical, nicotine and potential reduced-exposure tobacco products (PREPs), as an alternative to cigarettes. Objectives: To assess the effects of interventions intended to reduce the harm to health of continued tobacco use, we considered the following specific questions: do interventions intended to reduce harm have an effect on long-term health status?; do they lead to a reduction in the number of cigarettes smoked?; do they have an effect on smoking abstinence?; do they have an effect on biomarkers of tobacco exposure?; and do they have an effect on biomarkers of damage caused by tobacco? Search methods: We searched the Cochrane Tobacco Addiction Group Trials Register (CRS) on the 21st October 2015, using free-text and MeSH terms for harm reduction, smoking reduction and cigarette reduction. Selection criteria: Randomized or quasi-randomized controlled trials of interventions to reduce the amount smoked, or to reduce harm from smoking by means other than cessation. We include studies carried out in smokers with no immediate desire to quit all tobacco use. Primary outcomes were change in cigarette consumption, smoking cessation and any markers of damage or benefit to health, measured at least six months from the start of the intervention. Data collection and analysis: We assessed study eligibility for inclusion using standard Cochrane methods. We pooled trials with similar interventions and outcomes (> 50% reduction in cigarettes a day (CPD) and long-term smoking abstinence), using fixed-effect models. Where it was not possible to meta-analyse data, we summarized findings narratively. Main results: Twenty-four trials evaluated interventions to help those who smoke to cut down the amount smoked or to replace their regular cigarettes with PREPs, compared to placebo, brief intervention, or a comparison intervention. None of these trials directly tested whether harm reduction strategies reduced the harms to health caused by smoking. Most trials (14/24) tested nicotine replacement therapy (NRT) as an intervention to assist reduction. In a pooled analysis of eight trials, NRT significantly increased the likelihood of reducing CPD by at least 50% for people using nicotine gum or inhaler or a choice of product compared to placebo (risk ratio (RR) 1.75, 95% confidence interval (CI) 1.44 to 2.13; 3081 participants). Where average changes from baseline were compared for different measures, carbon monoxide (CO) and cotinine generally showed smaller reductions than CPD. Use of NRT versus placebo also significantly increased the likelihood of ultimately quitting smoking (RR 1.87, 95% CI 1.43 to 2.44; 8 trials, 3081 participants; quality of the evidence: low). Two trials comparing NRT and behavioural support to brief advice found a significant effect on reduction, but no significant effect on cessation. We found one trial investigating each of the following harm reduction intervention aids: bupropion, varenicline, electronic cigarettes, snus, plus another of nicotine patches to facilitate temporary abstinence. The evidence for all five intervention types was therefore imprecise, and it is unclear whether or not these aids increase the likelihood of smoking reduction or cessation. Two trials investigating two different types of behavioural advice and instructions on reducing CPD also provided imprecise evidence. Therefore, the evidence base for this comparison is inadequate to support the use of these types of behavioural advice to reduce smoking. Four studies of PREPs (cigarettes with reduced levels of tar, carbon and nicotine, and in one case delivered using an electronically-heated cigarette smoking system) showed some reduction in exposure to some toxicants, but it is unclear whether this would substantially alter the risk of harm. We judged the included studies to be generally at a low or unclear risk of bias; however, there were some ratings of high risk, due to a lack of blinding and the potential for detection bias. Using the GRADE system, we rated the overall quality of the evidence for our cessation outcomes as 'low' or 'very low', due to imprecision and indirectness. A 'low' grade means that further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate. A 'very low' grade means we are very uncertain about the estimate. Authors' conclusions: People who do not wish to quit can be helped to cut down the number of cigarettes they smoke and to quit smoking in the long term, using NRT, despite original intentions not to do so. However, we rated the evidence contributing to the cessation outcome for NRT as 'low' by GRADE standards. There is a lack of evidence to support the use of other harm reduction aids to reduce the harm caused by continued tobacco smoking. This could simply be due to the lack of high-quality studies (our confidence in cessation outcomes for these aids is rated 'low' or 'very low' due to imprecision by GRADE standards), meaning that we may have missed a worthwhile effect, or due to a lack of effect on reduction or quit rates. It is therefore important that more high-quality RCTs are conducted, and that these also measure the long-term health effects of treatments.
\n \n\n \n \nBackground Pharmacotherapies for smoking cessation increase the likelihood of achieving abstinence in a quit attempt. It is plausible that providing support, or, if support is offered, offering more intensive support or support including particular components may increase abstinence further. Objectives To evaluate the effect of adding or increasing the intensity of behavioural support for people using smoking cessation medications, and to assess whether there are different effects depending on the type of pharmacotherapy, or the amount of support in each condition. We also looked at studies which directly compare behavioural interventions matched for contact time, where pharmacotherapy is provided to both groups (e.g. tests of different components or approaches to behavioural support as an adjunct to pharmacotherapy). Search methods We searched theCochraneTobaccoAddictionGroup SpecialisedRegister, clinicaltrials.gov, and the ICTRP in June 2018 for recordswith any mention of pharmacotherapy, including any type of nicotine replacement therapy (NRT), bupropion, nortriptyline or varenicline, that evaluated the addition of personal support or compared two or more intensities of behavioural support. Selection criteria Randomised or quasi-randomised controlled trials in which all participants received pharmacotherapy for smoking cessation and conditions differed by the amount or type of behavioural support. The intervention condition had to involve person-to-person contact (defined as face-to-face or telephone). The control condition could receive less intensive personal contact, a different type of personal contact, written information, or no behavioural support at all.We excluded trials recruiting only pregnant women and trials which did not set out to assess smoking cessation at six months or longer. Data collection and analysis For this update, screening and data extraction followed standard Cochrane methods. The main outcome measure was abstinence from smoking after at least six months of follow-up. We used the most rigorous definition of abstinence for each trial, and biochemicallyvalidated rates, if available. We calculated the risk ratio (RR) and 95% confidence interval (CI) for each study. Where appropriate, we performed meta-analysis using a random-effects model.Main results Eighty-three studies, 36 of which were new to this update, met the inclusion criteria, representing 29,536 participants. Overall, we judged 16 studies to be at low risk of bias and 21 studies to be at high risk of bias. All other studies were judged to be at unclear risk of bias. Results were not sensitive to the exclusion of studies at high risk of bias. We pooled all studies comparing more versus less support in the main analysis. Findings demonstrated a benefit of behavioural support in addition to pharmacotherapy. When all studies of additional behavioural therapy were pooled, there was evidence of a statistically significant benefit from additional support (RR 1.15, 95% CI 1.08 to 1.22, I\ufffd = 8%, 65 studies, n = 23,331) for abstinence at longest follow-up, and this effect was not different when we compared subgroups by type of pharmacotherapy or intensity of contact. This effect was similar in the subgroup of eight studies in which the control group received no behavioural support (RR 1.20, 95% CI 1.02 to 1.43, I2 = 20%, n = 4,018). Seventeen studies compared interventions matched for contact time but that differed in terms of the behavioural components or approaches employed. Of the 15 comparisons, all had small numbers of participants and events. Only one detected a statistically significant effect, favouring a health education approach (which the authors described as standard counselling containing information and advice) over motivational interviewing approach (RR 0.56, 95% CI 0.33 to 0.94, n = 378). Authors' conclusions There is high-certainty evidence that providing behavioural support in person or via telephone for people using pharmacotherapy to stop smoking increases quit rates. Increasing the amount of behavioural support is likely to increase the chance of success by about 10% to 20%, based on a pooled estimate from 65 trials. Subgroup analysis suggests that the incremental benefit from more support is similar over a range of levels of baseline support.More research is needed to assess the effectiveness of specific components that comprise behavioural support.
\n \n\n \n \nMcm2-7 (MCM) proteins are part of the origin licensing machinery that regulates initiation of DNA replication. Geminin is a licensing repressor and prevents reinitiation of DNA replication during S-G2-M phase by blocking reloading of Mcm2-7 at replication origins. Here, we have analysed these replication licensing factors (RLFs) to determine whether the pathway becomes deregulated during mammary carcinogenesis, and have assessed their potential value as prognostic markers. Protein expression profiles were generated for Ki67, Mcm2, geminin, HER-2, ER and PR in a series of reduction mammoplasty (n=18) and breast cancer specimens (n=120), and compared to clinicopathological parameters. A large proportion of epithelial cells of the terminal duct lobular unit reside in a primed 'replication licensed' but not proliferating state. This state is characterised by Mcm2 expression and absence of Ki67 and the S/G2/M marker geminin. In breast cancers, increasing tumour grade is associated with increased Ki67, Mcm2 and geminin expression. The Mcm2/Ki67 ratio decreases through the grades, indicating a shift from a predominantly licensed state to an actively proliferating state. This shift is associated with an increase in the geminin/Ki67 ratio, signifying a shortening of G1 phase in breast cancer cells. Ki67, Mcm2 and the Mcm2/Ki67 ratio are statistically significantly associated with the Nottingham Prognostic Index (NPI), but geminin and the geminin/Ki67 ratio are not. Ki67, Mcm2 and Mcm2/Ki67 are highly correlated with one another, with Mcm2 being the single most important predictor of NPI score (P<0.001). However, only 12% of variation in NPI is explained by Mcm2, as the labelling index for this marker is approaching 100% for many of the high-grade tumours. The origin licensing phenotypes of normal breast and breast cancers therefore relate to their cellular differentiation status, and high-level MCM expression in more poorly differentiated tumours severely constrains their use as prognostic markers in breast cancer. \u00a9 2005 Cancer Research UK.
\n \n\n \n \nBackground and Objectives As teaching technology advances, medical education is increasingly using digital mediums and exploring instructional models such as the flipped classroom and blended learning courses, where the in-class taught sessions are more groups on content delivered before class. Early evidence suggests lectures and foundational material can be equally provided online, but we have low-quality research to be convinced. We aim to test and develop an online evidence-based teaching resource that seeks to improve the availability and scalability of evidence-based medicine (EBM) learning tools. We evaluate the feasibility of a study design that could test for changes in academic performance in EBM skills using an online supplement. Methods Mixed-methods feasibility study of a randomised controlled trial (RCT) in an undergraduate medical student cohort. Results Of a small cohort (n=34), eight participants agreed to randomisation and completed the study. No study participant completed the EBM supplementary course in full. Students report time-management as a significant barrier in participation, and all aspects of the study and communications should be delivered with efficiency a key consideration. Conclusion Randomising students to an online EBM supplement within a medical school programme presents challenges of recruitment and student motivation, but the study design is potentially feasible.
\n \n\n \n \nIntroduction: We examined the design, analysis and reporting in multi-reader multi-case (MRMC) research studies using the area under the receiver-operating curve (ROC AUC) as a measure of diagnostic performance. Methods: We performed a systematic literature review from 2005 to 2013 inclusive to identify a minimum 50 studies. Articles of diagnostic test accuracy in humans were identified via their citation of key methodological articles dealing with MRMC ROC AUC. Two researchers in consensus then extracted information from primary articles relating to study characteristics and design, methods for reporting study outcomes, model fitting, model assumptions, presentation of results, and interpretation of findings. Results were summarized and presented with a descriptive analysis. Results: Sixty-four full papers were retrieved from 475 identified citations and ultimately 49 articles describing 51 studies were reviewed and extracted. Radiological imaging was the index test in all. Most studies focused on lesion detection vs. characterization and used less than 10 readers. Only 6 (12%) studies trained readers in advance to use the confidence scale used to build the ROC curve. Overall, description of confidence scores, the ROC curve and its analysis was often incomplete. For example, 21 (41%) studies presented no ROC curve and only 3 (6%) described the distribution of confidence scores. Of 30 studies presenting curves, only 4 (13%) presented the data points underlying the curve, thereby allowing assessment of extrapolation. The mean change in AUC was 0.05 (20.05 to 0.28). Non-significant change in AUC was attributed to underpowering rather than the diagnostic test failing to improve diagnostic accuracy. Conclusions: Data reporting in MRMC studies using ROC AUC as an outcome measure is frequently incomplete, hampering understanding of methods and the reliability of results and study conclusions. Authors using this analysis should be encouraged to provide a full description of their methods and results.
\n \n\n \n \nBackground: Both behavioural support (including brief advice and counselling) and pharmacotherapies (including nicotine replacement therapy (NRT), varenicline and bupropion) are effective in helping people to stop smoking. Combining both treatment approaches is recommended where possible, but the size of the treatment effect with different combinations and in different settings and populations is unclear. Objectives: To assess the effect of combining behavioural support and medication to aid smoking cessation, compared to a minimal intervention or usual care, and to identify whether there are different effects depending on characteristics of the treatment setting, intervention, population treated, or take-up of treatment. Search methods: We searched the Cochrane Tobacco Addiction Group Specialised Register in July 2015 for records with any mention of pharmacotherapy, including any type of NRT, bupropion, nortriptyline or varenicline. Selection criteria: Randomized or quasi-randomized controlled trials evaluating combinations of pharmacotherapy and behavioural support for smoking cessation, compared to a control receiving usual care or brief advice or less intensive behavioural support. We excluded trials recruiting only pregnant women, trials recruiting only adolescents, and trials with less than six months follow-up. Data collection and analysis: Search results were prescreened by one author and inclusion or exclusion of potentially relevant trials was agreed by two authors. Data was extracted by one author and checked by another. The main outcome measure was abstinence from smoking after at least six months of follow-up. We used the most rigorous definition of abstinence for each trial, and biochemically validated rates if available. We calculated the risk ratio (RR) and 95% confidence interval (CI) for each study. Where appropriate, we performed meta-analysis using a Mantel-Haenszel fixed-effect model. Main results: Fifty-three studies with a total of more than 25,000 participants met the inclusion criteria. A large proportion of studies recruited people in healthcare settings or with specific health needs. Most studies provided NRT. Behavioural support was typically provided by specialists in cessation counselling, who offered between four and eight contact sessions. The planned maximum duration of contact was typically more than 30 minutes but less than 300 minutes. Overall, studies were at low or unclear risk of bias, and findings were not sensitive to the exclusion of any of the six studies rated at high risk of bias in one domain. One large study (the Lung Health Study) contributed heterogeneity due to a substantially larger treatment effect than seen in other studies (RR 3.88, 95% CI 3.35 to 4.50). Since this study used a particularly intensive intervention which included extended availability of nicotine gum, multiple group sessions and long term maintenance and recycling contacts, the results may not be comparable with the interventions used in other studies, and hence it was not pooled in other analyses. Based on the remaining 52 studies (19,488 participants) there was high quality evidence (using GRADE) for a benefit of combined pharmacotherapy and behavioural treatment compared to usual care, brief advice or less intensive behavioural support (RR 1.83, 95% CI 1.68 to 1.98) with moderate statistical heterogeneity (I2 = 36%). The pooled estimate for 43 trials that recruited participants in healthcare settings (RR 1.97, 95% CI 1.79 to 2.18) was higher than for eight trials with community-based recruitment (RR 1.53, 95% CI 1.33 to 1.76). Compared to the first version of the review, previous weak evidence of differences in other subgroup analyses has disappeared. We did not detect differences between subgroups defined by motivation to quit, treatment provider, number or duration of support sessions, or take-up of treatment. Authors' conclusions: Interventions that combine pharmacotherapy and behavioural support increase smoking cessation success compared to a minimal intervention or usual care. Updating this review with an additional 12 studies (5,000 participants) did not materially change the effect estimate. Although trials differed in the details of their populations and interventions, we did not detect any factors that modified treatment effects apart from the recruitment setting. We did not find evidence from indirect comparisons that offering more intensive behavioural support was associated with larger treatment effects.
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