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BACKGROUND: Most subsequent new primary or recurrent melanomas might be self-detected if patients are trained to systematically self-examine their skin and have access to timely medical review (patient-led surveillance). Routinely scheduled clinic visits (clinician-led surveillance) is resource-intensive and has not been shown to improve health outcomes; fewer visits may be possible if patient-led surveillance is shown to be safe and effective. The MEL-SELF trial is a randomised controlled trial comparing patient-led surveillance with clinician-led surveillance in people who have been previously treated for localised melanoma. METHODS: Stage 0/I/II melanoma patients (n = 600) from dermatology, surgical, or general practice clinics in NSW Australia, will be randomised (1:1) to the intervention (patient-led surveillance, n = 300) or control (usual care, n = 300). Patients in the intervention will undergo a second randomisation 1:1 to polarised (n = 150) or non-polarised (n = 150) dermatoscope. Patient-led surveillance comprises an educational booklet, skin self-examination (SSE) instructional videos; 3-monthly email/SMS reminders to perform SSE; patient-performed dermoscopy with teledermatologist feedback; clinical review of positive teledermoscopy through fast-tracked unscheduled clinic visits; and routinely scheduled clinic visits following each clinician's usual practice. Clinician-led surveillance comprises an educational booklet and routinely scheduled clinic visits following each clinician's usual practice. The primary outcome, measured at 12 months, is the proportion of participants diagnosed with a subsequent new primary or recurrent melanoma at an unscheduled clinic visit. Secondary outcomes include time from randomisation to diagnosis (of a subsequent new primary or recurrent melanoma and of a new keratinocyte cancer), clinicopathological characteristics of subsequent new primary or recurrent melanomas (including AJCC stage), psychological outcomes, and heal

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© Author(s) (or their employer(s)) 2018. Objectives To assess evidence for 'legacy' (post-trial) effects on cardiovascular disease (CVD) mortality and all-cause mortality among adult participants of placebocontrolled randomised controlled trials (RCTs) of statins. Design Meta-analysis of aggregate data. Setting/Participants Placebo-controlled statin RCTS for primary and secondary CVD prevention. Methods Data sources: PubMed, Embase from inception and forward citations of Cholesterol Treatment Trialists' Collaborators RCTs to 16 June 2016. Study selection: Two independent reviewers identified all statin RCT follow-up reports including ≥1000 participants, and cardiovascular and all-cause mortality. Data extraction and synthesis: Two independent reviewers extracted data in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Main outcomes: Post-trial CVD and all-cause mortality. Results We included eight trials, with mean post-trial follow-up ranging from 1.6 to 15.1 years, and including 13 781 post-trial deaths (6685 CVD). Direct effects of statins within trials were greater than legacy effects posttrials. The pooled data from all eight studies showed no evidence overall of legacy effects on CVD mortality, but some evidence of legacy effects on all-cause mortality (p=0.01). Exploratory subgroup analysis found possible differences in legacy effect for primary prevention trials compared with secondary prevention trials for both CVD mortality (p=0.15) and all-cause mortality (p=0.02). Pooled post-trial HR for the three primary prevention studies demonstrated possible post-trial legacy effects on CVD mortality (HR=0.87; 95% CI 0.79 to 0.95) and on all-cause mortality (HR=0.90; 95% CI 0.85 to 0.96). Conclusions Possible post-trial statin legacy effects on all-cause mortality appear to be driven by the primary prevention studies. Although these relative benefits were smaller than those observed within the trial, the absolute ben

© 2018 Bell et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Objective Blood pressure variability (BPV) has been associated with risk of cardiovascular events in observational studies, independently of mean BP levels. In states with higher autonomic imbalance, such as in diabetes, the importance of BP variability may theoretically be even greater. We aimed to investigate the incremental value of BPV for prediction of cardiovascular and all-cause mortality in patients with type 2 diabetes. Methods We identified 9,855 patients without pre-existing cardiovascular disease who did not change BP-lowering treatment during the observation period from a Swedish primary health care cohort of patients with type 2 diabetes. BPV was summarized as the standard deviation (SD), coefficient of variation (CV), or variation independent of mean (VIM). Patients were followed for a median of 4 years and associations with cardiovascular and all-cause mortality were investigated using Cox proportional hazards models. Results BPV was not associated with cardiovascular specific or all-cause mortality in the total sample. In patients who were not on BP-lowering drugs during the observation period (n = 2,949), variability measures were associated with all-cause mortality: hazard ratios were 1.05, 1.04 and 1.05 for 50% increases in SD, CV and VIM, respectively, adjusted for Framingham risk score risk factors, including mean BP. However, the addition of the variability measures in this subgroup only led to very minimal improvement in discrimination, indicating they may have limited clinical usefulness (change in C-statistic ranged from 0.000–0.003 in all models). Conclusions Although BPV was independently associated with all-cause mortality in diabetes patients in primary care who did not have pre-existin

© 2017 The Author(s). Background: In the two-stage randomised trial design, a randomly sampled subset of study participants are permitted to choose their own treatment, while the remaining participants are randomised to treatment in the usual way. Appropriate analysis of the data from both arms of the study allows investigators to estimate the impact on study outcomes of treatment preferences that patients may have, in addition to evaluating the usual direct effect of treatment. In earlier work, we showed how to optimise this design by making a suitable choice of the proportion of participants who should be assigned to the choice arm of the trial. However, we ignored the possibility of some participants being indifferent to the treatments under study. In this paper, we extend our earlier work to consider the analysis of two-stage randomised trials when some participants have no treatment preference, even if they are assigned to the choice arm and allowed to choose. Methods: We compare alternative characterisations of the response profiles of the indifferent or undecided participants, and derive estimates of the treatment and preference effects on study outcomes. We also present corresponding test statistics for these parameters. The methods are illustrated with data from a clinical trial contrasting medical and surgical interventions. Results: Expressions are obtained to estimate and test the impact of treatment choices on study outcomes, as well as the impact of the actual treatment received. Contrasts are defined between patients with stated treatment preferences and those with no preference. Alternative assumptions concerning the outcomes of undecided participants are described, and an approach leading to unbiased estimation and testing is identified. Conclusions: Use of the two-stage design can provide important insights into determinants of study outcomes that are not identifiable with other designs. The design can remain attractive even in the presence of part

Our primary purpose was to assess the clinical (predictive) validity of central retinal thickness (CRT) and best corrected visual acuity (BCVA) at 1 week and 1 month after starting treatment with ranibizumab for central retinal vein occlusion. The authors also assessed detectability of response to treatment.The authors used data from 325 participants in the CRUISE study, which included measurement of time-domain CRT and BCVA at baseline, 1 week, 1 month, and 6 months postrandomization. Analysis of covariance models were fitted to assess clinical validity, and distributions of change were constructed to assess detectability of response.There was no evidence that 1-week CRT, and very strong evidence that 1-week BCVA were associated with baseline-adjusted BCVA at 6 months (P = 0.17 and P < 0.001, respectively). There was strong evidence that both 1-month CRT and 1-month BCVA were associated with baseline-adjusted 6-month BCVA (P = 0.005 and P < 0.001, respectively), but simultaneous adjustment found evidence of independent association only for BCVA (P = 0.71 and P < 0.001 for CRT and BCVA, respectively). Detectability of response tended to be higher for CRT than BCVA at 1 week and 1 month but by 6 months these were equivalent for CRT and BCVA.In this study, BCVA monitoring of treated central retinal vein occlusion patients seemed more informative than time-domain optical coherence tomography monitoring.

BACKGROUND: Various lipid measurements in monitoring/screening programmes can be used, alone or in cardiovascular risk scores, to guide treatment for prevention of cardiovascular disease (CVD). Because some changes in lipids are due to variability rather than true change, the value of lipid-monitoring strategies needs evaluation. OBJECTIVE: To determine clinical value and cost-effectiveness of different monitoring intervals and different lipid measures for primary and secondary prevention of CVD. DATA SOURCES: We searched databases and clinical trials registers from 2007 (including the Cochrane Central Register of Controlled Trials, MEDLINE, EMBASE, the Clinical Trials Register, the Current Controlled Trials register, and the Cumulative Index to Nursing and Allied Health Literature) to update and extend previous systematic reviews. Patient-level data from the Clinical Practice Research Datalink and St Luke's Hospital, Japan, were used in statistical modelling. Utilities and health-care costs were drawn from the literature. METHODS: In two meta-analyses, we used prospective studies to examine associations of lipids with CVD and mortality, and randomised controlled trials to estimate lipid-lowering effects of atorvastatin doses. Patient-level data were used to estimate progression and variability of lipid measurements over time, and hence to model lipid-monitoring strategies. Results are expressed as rates of true-/false-positive and true-/false-negative tests for high lipid or high CVD risk. We estimated incremental costs per quality-adjusted life-year. RESULTS: A total of 115 publications reported strength of association between different lipid measures and CVD events in 138 data sets. The summary adjusted hazard ratio per standard deviation of total cholesterol (TC) to high-density lipoprotein (HDL) cholesterol ratio was 1.25 (95% confidence interval 1.15 to 1.35) for CVD in a primary prevention population but heterogeneity was high (I(2) = 98%); similar results we

Objectives To describe how evidence from trials and cohort studies may be used to guide choice of test for monitoring patients with chronic disease. Study Design and Setting Exploration of potential criteria for choosing the best monitoring test. Criteria are defined and options for assessment measures for test performance on each criterion discussed. Results Monitoring in clinical practice occurs in three main phases: before treatment, response to treatment, and long-term monitoring. Four important criteria may be used to choose the best test for monitoring a patient in each of these phases. Clinical validity describes the ability of the test to predict the clinically relevant outcome that we are trying to control or prevent. Responsiveness describes how much the test changes in response to an intervention relative to background random variation. Detectability of long-term change describes the size of changes in the test over the long term relative to background random variation. Practicality describes the ease of use, invasiveness, and cost of the test. Test performance generally requires longitudinal data from trial and/or cohort studies using statistical methods such as those discussed. Conclusion Four specific criteria can help clinicians inform evidence-based decisions on which monitoring test to use. © 2014 Elsevier Inc. All rights reserved.

Objective: To understand general practitioners' (GPs) use of individual risk factors (blood pressure and cholesterol levels) versus absolute risk in cardiovascular disease (CVD) risk management decision-making. Design: Randomised experiment. Absolute risk, systolic blood pressure (SBP), cholesterol ratio (total cholesterol/high-density lipoprotein (TC/HDL)) and age were systematically varied in hypothetical cases. High absolute risk was defined as 5-year risk of a cardiovascular event >15%, high blood pressure levels varied between SBP 147 and 179 mm Hg and high cholesterol (TC/HDL ratio) between 6.5 and 7.2 mmol/L. Setting: 4 GP conferences in Australia. Participants: 144 Australian GPs. Outcomes: GPs indicated whether they would prescribe cholesterol and/or blood pressure lowering medication. Analyses involved logistic regression. Results: For patients with high blood pressure: 93% (95% CI 86% to 96%) of high absolute risk patients and 83% (95% CI 76% to 88%) of lower absolute risk patients were prescribed blood pressure medication. Conversely, 30% (95% CI 25% to 36%) of lower blood pressure patients were prescribed blood pressure medication if absolute risk was high and 4% (95% CI 3% to 5%) if lower. 69% of high cholesterol/high absolute risk patients were prescribed cholesterol medication (95% CI 61% to 77%) versus 34% of high cholesterol/ lower absolute risk patients (95% CI 28% to 41%). 36% of patients with lower cholesterol (95% CI 30% to 43%) were prescribed cholesterol medication if absolute risk was high versus 10% if lower (95% CI 8% to 13%). Conclusions: GPs' decision-making was more consistent with the management of individual risk factors than an absolute risk approach, especially when prescribing blood pressure medication. The results suggest medical treatment of lower risk patients (5-year risk of CVD event <15%) with mildly elevated blood pressure or cholesterol levels is likely to occur even when an absolute risk assessment is specifically provided

© 2014, BMJ Publishing Group. All rights reserved. Objective: To determine the incremental value of ambulatory blood pressure (BP) in predicting cardiovascular risk when the Framingham Risk Score (FRS) is known. Methods: We included 780 men without cardiovascular disease from the Uppsala Longitudinal Study of Adult Men, all aged approximately 70 years at baseline. We first screened ambulatory systolic BP (ASBP) parameters for their incremental value by adding them to a model with 10-year FRS. For the best ASBP parameter we estimated HRs and changes in discrimination, calibration and reclassification. We also estimated the difference in the number of men started on treatment and in the number of men protected against a cardiovascular event. Results: Mean daytime ASBP had the highest incremental value; adding other parameters did not yield further improvements. While ASBP was an independent risk factor for cardiovascular disease, addition to FRS led to only small increases to the overall model fit, discrimination (a 1% increase in the area under the receiver operating characteristic (ROC) curve), calibration and reclassification. We estimated that for every 10 000 men screened with ASBP, 141 fewer would start a new BP-lowering treatment (95% CI 62 to 220 less treated), but this would result in 7 fewer cardiovascular events prevented over the subsequent 10 years (95% CI 21 fewer events prevented to 7 more events prevented). Conclusions: In addition to a standard cardiovascular risk assessment it is not clear that ambulatory BP measurement provides further incremental value. The clinical role of ambulatory BP requires ongoing careful consideration.

Objective To review the evidence on diagnostic accuracy of red flag signs and symptoms to screen for fracture or malignancy in patients presenting with low back pain to primary, secondary, or tertiary care. Design Systematic review. Data sources Medline, OldMedline, Embase, and CINAHL from earliest available up to 1 October 2013. Inclusion criteria Primary diagnostic studies comparing red flags for fracture or malignancy to an acceptable reference standard, published in any language. Review methods Assessment of study quality and extraction of data was conducted by three independent assessors. Diagnostic accuracy statistics and post-test probabilities were generated for each red flag. Results We included 14 studies (eight from primary care, two from secondary care, four from tertiary care) evaluating 53 red flags; only five studies evaluated combinations of red flags. Pooling of data was not possible because of index test heterogeneity. Many red flags in current guidelines provide virtually no change in probability of fracture or malignancy or have untested diagnostic accuracy. The red flags with the highest post-test probability fo

Objective: To estimate the probability of becoming high risk for cardiovascular disease among people at low and intermediate risk and not being treated for high blood pressure or lipid levels. Design: Observational study. Setting: General communities in Japan and the United States. Participants: 13 757 participants of the Tokyo health check-up study and 3855 of the Framingham studies aged 30-74 years with complete data on risk equation covariates, not receiving blood pressure or cholesterol lowering treatment, and with an estimated risk of cardiovascular disease <20% within 10 years. We stratified participants on the basis of baseline risk: <5%, 5-<10%, 10-<15%, and 15-<20%. We used follow-up measurements from the Tokyo study done annually over three years (2006-10) and follow-up visits in the Framingham study done between eight (1968-75) and 19 years (1990-1995) after baseline. Main outcome measure: Estimated 10 year risk of a cardiovascular event >20% using the Framingham equation. Results: At baseline most participants had <5% risk (60.6% of Tokyo cohort and 45.7% of Framingham cohort) or 5-<10% risk (24.0% and 28.0%, respectively) of a cardiovascular event within 10 years. There was <10% probability of crossing the treatment threshold at 19, 8, and 3 years for baseline risk groups <5%, 5-<10%, and 10-<15%, respectively, and >10% probability of crossing the treatment threshold at one year for the 15-<20% baseline risk group. Conclusions: Decisions on the frequency of remeasuring for cardiovascular risk should be made on the basis of baseline risk. Repeat risk estimation before 8-10 years is not warranted for most people initially not requiring treatment. However, remeasurement within a year seems warranted in those with an initial 15-<20% risk.

OBJECTIVES: To identify factors that influence the extent to which general practitioners use absolute risk (AR) assessment in cardiovascular disease (CVD) risk assessment.DESIGN, SETTING AND PARTICIPANTS: Semi-structured interviews with 25 currently practising GPs from eight Divisions of General Practice in New South Wales, Australia, between October 2011 and May 2012. Data were analysed using framework analysis.RESULTS: The study identified five strategies that GPs use with patients in different situations, defined in terms of the extent to which AR was used and the reasons given for this: the AR-focused strategy, used when AR assessment was considered useful for the patient; the AR-adjusted strategy, used to account for additional risk factors such as family history; the clinical judgement strategy, used when GPs considered that their judgement took multiple risk factors into account as effectively as AR; the passive disregard strategy, used when GPs lacked sufficient time, access or experience to use AR; and the active disregard strategy, used when AR was considered to be inappropriate for the patient. The strategies were linked with different opportunity, capability and motivation barriers to the use of AR.CONCLUSIONS: This study provides an in-depth insight into the factors that influence GPs' use of AR in CVD risk assessment. The results suggest that GPs use a range of strategies in different situations, so different approaches may be required to improve the use of AR guidelines in practice.

Objective To review the evidence on diagnostic accuracy of red flag signs and symptoms to screen for fracture or malignancy in patients presenting with low back pain to primary, secondary, or tertiary care. Design Systematic review. Data sources Medline, OldMedline, Embase, and CINAHL from earliest available up to 1 October 2013. Inclusion criteria Primary diagnostic studies comparing red flags for fracture or malignancy to an acceptable reference standard, published in any language. Review methods Assessment of study quality and extraction of data was conducted by three independent assessors. Diagnostic accuracy statistics and post-test probabilities were generated for each red flag. Results We included 14 studies (eight from primary care, two from secondary care, four from tertiary care) evaluating 53 red flags; only five studies evaluated combinations of red flags. Pooling of data was not possible because of index test heterogeneity. Many red flags in current guidelines provide virtually no change in probability of fracture or malignancy or have untested diagnostic accuracy. The red flags with the highest post-test probability for detection of fracture were older age (9%, Conclusions While several red flags are endorsed in guidelines to screen for fracture or malignancy, only a small subset of these have evidence that they are indeed informative. These findings suggest a need for revision of many current guidelines.

Biochemical markers of bone turnover have been proposed to monitor the response to bisphosphonate therapy for osteoporosis, but this requires true between-person differences in the response to therapy. Using mixed models we analyzed three annual measurements of two markers (bone alkaline phosphatase [BAP] and cross-linked N-telopeptide of type I collagen [NTX]) from the Fracture Intervention Trial. We compared marker variation among women allocated to alendronate with that among women allocated to placebo to estimate how much variation was due to true between-person differences in response to treatment, and how much was due to random within-person fluctuations unrelated to treatment. For both markers we found that the mean effect of treatment differed by the baseline level of the marker. After allowing for this and other effects, we found large true between-person differences in response to treatment for both markers, with a coefficient of variation (CV) for NTX of 25.1% and for BAP of 21.2%. However, random within-person fluctuation was even larger, with a CV for change in NTX of 42.5% and for change in BAP of 25.8%. Although repeated measurements have the potential to reduce within person variability, even triplicate baseline marker measurements resulted in an averaged value that was only within 31% of the true value with 95% certainty. In summary, although bone turnover markers appear promising for monitoring between-person differences in response to treatment, their use in clinical practice is currently limited by large random within-person variation. Copyright © 2012 American Society for Bone and Mineral Research.

Background: Current guidelines recommend that decisions to start preventative therapy for cardiovascular disease (CVD) should be based on absolute risk; however, current risk equations are based on single measurements of risk factors. We aimed to assess whether two measurements of blood pressure and lipids improves the prediction of cardiovascular risk compared to one measurement.Methods and results: We used sex-specific Cox proportional hazards models to evaluate the risk of first CVD event in 2385 participants of the Framingham Offspring Study attending both the second and third visits. We estimated the effects on risk prediction of using the average of two measurements of blood pressure, total cholesterol, and HDL cholesterol compared to using one measurement of the risk factors. We found that these risk factors were each markedly more predictive of CVD when the average of two measurements was used rather than one measurement and age was less predictive of CVD. There were small improvements in the overall model fit, discrimination, and calibration. Reclassification also showed small improvements across the risk spectrum (net reclassification information, NRI, for women 3.0%, 95% CI -0.9 to 24.8%; NRI for men 4.0%, 95% CI -2.2 to 14.1%) and possibly greater improvements for intermediate-risk individuals (NRI for women 32.3%, 95% CI -21.9 to 46.8%; NRI for men 16.0%, 95% CI -3.3 to 43%).Conclusions: Averaging two measurements of blood pressure and lipids results in marked increases in the predictiveness of these risk factors and smaller improvements in the overall prediction of cardiovascular risk including reclassification. © 2011 The European Society of Cardiology.

Objective: Statistical process control charts have been advocated for use in monitoring of lung function in asthma. We aimed to evaluate their application in asthma using existing data from a randomized trial. Study Design and Setting: Patients on optimal inhaled corticosteroid/bronchodilator therapy (n = 81) were randomized to continue the same or change to corticosteroid alone. Baseline statistical control was assessed from 20 days of electronically recorded lung function (peak expiratory flow [PEF], forced expiratory volume in one second [FEV 1]). The ability to detect lung function changes was assessed during 10 days after randomization. Results: PEF measurements were in statistical control during baseline for only 59-79% of patients for different combinations of five control chart rules (e.g., Rule 1: >3 standard deviations outside mean and 95% expected to be in control), with similar proportions for FEV 1. After randomization, among those previously in statistical control, Rule 1 signaled lower FEV 1 for 35% of patients randomized to treatment change compared with 6% continuing baseline treatment (P = 0.004). Control charts performed poorly for PEF, signaling a decrease for 8% of patients randomized to treatment change compared with 11% continuing treatment (P = 0.7). A paradoxical increase was signaled for many patients continuing treatment. Conclusion: Control charts may not be suitable for use in many patients with asthma. © 2012 Elsevier Inc. All rights reserved.

Purpose: To develop more evidence-based guidelines for the frequency of patient follow-up after treatment of localized (American Joint Committee on Cancer [AJCC] stage I or II) melanoma. Methods: We used data from Melanoma Institute Australia on an inception cohort of 3,081 consecutive patients first diagnosed with stage I or II melanoma between January 1985 and December 2009. Kaplan-Meier curves and Cox models were used to characterize the time course and predictors for recurrence and new primaries. We modeled the delay in diagnosis of recurrence or new primary as well as the number of monitoring visits required using two monitoring schedules: first, according to 2008 Australian and New Zealand guidelines and, second, with fewer visits, especially for those at lowest risk of recurrence. Results: For every 1,000 patients beginning follow-up, 229 developed recurrence and 61 developed new primary within 10 years. There was only a small difference in modeled delay in diagnosis (extra 44.9 and 9.6 patients per 1,000 for recurrence and new primary, respectively, with delay greater than 2 months) using a schedule that requires far fewer visits (3,000 fewer visits per 1,000 patients) than recommended by current guidelines. AJCC substage was the most important predictor of recurrence, whereas age and date of primary diagnosis were important predictors of developing new primary. Conclusion: By providing less intensive monitoring, more efficient follow-up strategies are possible. Fewer visits with a more focused approach may address the needs of patients and clinicians to detect recurrent or new melanoma. © 2011 by American Society of Clinical Oncology.

Objective: To estimate the accuracy of monitoring cholesterol concentration for detecting non-adherence to lipid lowering treatment. Design: Secondary analysis of data on cholesterol concentration in the LIPID (long term intervention with pravastatin in ischaemic disease) study by using three measures of non-adherence: discontinuation of treatment, allocation to placebo arm, less than 80% of pills taken. Setting: Randomised placebo controlled trial in Australia and New Zealand. Participants: 9014 patients with previous coronary heart disease. Interventions: Pravastatin 40 mg or placebo daily. Main outcome measures: Sensitivity, specificity, area under the receiver operating characteristics (ROC) curve, post-test probability. Results: Monitoring of cholesterol concentration had modest ability for detecting complete non-adherence. One year after the start of treatment, half (1957/3937) of the non-adherent patients and 6% (253/3944) of adherent patients had a rise in concentration of low density lipoprotein cholesterol. Accuracy was reasonable (area under the curve 0.89). Cholesterol monitoring, however, had weak ability for detecting partial non-adherence. One year after the start of treatment,16%(34/213) of partially adherent and 4% (155/3585) of fully adherent patients had a rise in concentration of low density lipoprotein cholesterol. Accuracy was poor (area under the curve 0.65). For typical pre-test probabilities of non-adherence ranging from low (25%) to high (75%), the post-test probabilities indicate continuing uncertainty after lipid testing. A patient with no change in low density lipoprotein cholesterol concentration has a post-test probability of being completely non-adherent of between 67% and 95% and a post-test probability of being partially non-adherent of between 48% and 89%. A patient with a decrease in concentration of 1.0 mmol/L has a post-test probability of being completely non-adherent of between 7% and 40% and a post-test probability of being p