This paper provides a concise review of the efficacy, effectiveness and affordability of health‐care interventions to promote and assist tobacco cessation, in order to inform national guideline development and assist countries in planning their provision of tobacco cessation support.Cochrane reviews of randomized controlled trials (RCTs) of major health‐care tobacco cessation interventions were used to derive efficacy estimates in terms of percentage‐point increases relative to comparison conditions in 6–12‐month continuous abstinence rates. This was combined with analysis and evidence from ‘real world’ studies to form a judgement on the probable effectiveness of each intervention in different settings. The affordability of each intervention was assessed for exemplar countries in each World Bank income category . Based on World Health Organization (WHO) criteria, an intervention was judged as affordable for a given income category if the estimated extra cost of saving a life‐year was less than or equal to the per‐capita gross domestic product for that category of country.Brief advice from a health‐care worker given opportunistically to smokers attending health‐care services can promote smoking cessation, and is affordable for countries in all World Bank income categories . Proactive telephone support, automated text messaging programmes and printed self‐help materials can assist smokers wanting help with a quit attempt and are affordable globally. Multi‐session, face‐to‐face behavioural support can increase quit success for cigarettes and smokeless tobacco and is affordable in middle‐ and high‐income countries. Nicotine replacement therapy, bupropion, nortriptyline, varenicline and cytisine can all aid quitting smoking when given with at least some behavioural support; of these, cytisine and nortriptyline are affordable globally.Brief advice from a health‐care worker, telephone helplines, automated text messaging, printed self‐help materials, cytisine and nortriptyline are globally affordable health‐care interventions to promote and assist smoking cessation. Evidence on smokeless tobacco cessation suggests that face‐to‐face behavioural support and varenicline can promote cessation. Stopping smoking improves life expectancy and reduces the risk of chronic disease. The earlier the age of stopping, the greater the benefit; studies in the United Kingdom and United States estimate that stopping in young adulthood recovers an average of 10 years of life Health‐care interventions to promote and support smoking cessation have a strong evidence base and are available in many countries. These interventions include brief advice and behavioural support from health‐care workers and a range of medications, including nicotine replacement therapy (NRT), varenicline, bupropion, nortriptyline and cytisine The World Health Organization (WHO) Framework Convention on Tobacco Control (FCTC) This paper aims to assist the process of implementing Article 14 of the FCTC by assessing the efficacy, effectiveness and affordability of the major health‐care interventions to promote and assist tobacco cessation, in most cases relating to smoking We use Cochrane reviews of tobacco cessation interventions to obtain efficacy estimates in terms of the percentage of tobacco users in randomized controlled trials (RCTs) helped to stop using those interventions. We then review additional studies that may help to form a judgement about the real‐world effectiveness of the interventions, and contextual and implementation factors that may enhance or reduce this effectiveness. Then we estimate the incremental cost‐effectiveness ratios (ICERs) for the effective interventions for countries in different World Bank income categories. ICERs give the incremental cost incurred for an incremental health outcome, usually expressed as cost per life‐year gained or cost per quality‐adjusted life‐year gained. Because ICERs are the ratio of the change in costs to incremental benefits of an intervention, they are good measures to compare different interventions used in tobacco cessation and across countries. These ICERs can then be used to assess the affordability of the interventions globally taking account of income levels in relevant countries.Lekan Ayo‐Yusuf, Director/Dean, Sefako Makgatho Health Sciences University, Medunsa, South Africa; Beatriz Champagne, Executive Director, InterAmerican Heart Foundation, Buenos Aires, Argentina; Elma Correa‐Acevedo, Pneumologist and Tobacco Clinic Coordinator, Instituto Nacional de Cancerología, México City, México; Thomas Glynn, Consulting Professor, Stanford Prevention Research Center, School of Medicine, Stanford University; USA; Feras Hawari, Director, Cancer Control Office and Chief, Section of Pulmonary and Critical Care, King Hussein Cancer Centre, Amman, Jordan; Hom Lal Shresha, Honorary Research Fellow, Non‐Smokers’ Rights Association of Nepal, Kathmandu, Nepal; Vimla Moodley, Director, Health Promotion, National Department of Health, South Africa; Caleb Otto, Ambassador and Permanent Representative of Palau to the United Nations, USA; Dennis Rada, Tobacco Control Coordinator, Inter‐American Heart Foundation, La Paz, Bolivia; Javier Saimovici, Chief of Home Care Section, Internal Medicine Department and Tobacco Control Program Member, Italian Hospital of Buenos Aires, Argentina; Oleg Salagay, Deputy Director, Department of International Cooperation and Public Relations, Ministry of Health of the Russian Federation, Moscow, Russia; Dan Xiao, Tobacco Medicine and Smoking Cessation Center in China‐Japan Friendship Hospital, Beijing, ChinaThe paper and the affordability calculator have undergone extensive review, user testing and revision prior to submission as a published paper, with an advisory group of key stakeholders in low‐ and middle‐income countries, to help ensure that they meet their needs. The members of the advisory panel are listed in Box 1.Considering ‘efficacy’  in more detail, Cochrane reviews provide rigorous, independent, quantitative estimates and are subject to a consistent quality control process. They provide meta‐analyses of RCTs usually with a minimum of 6‐month follow‐up, synthesizing data from direct head‐to‐head comparisons between interventions and comparison conditions. It is important to recognize that efficacy estimates based on the Cochrane reviews depend upon the particular circumstances of the trials conducted, including the control conditions used and the target population. However, they provide the best estimates available and a starting point for consideration of effectiveness.There are many reasons why efficacy estimates from RCTs might not translate into the same level of effectiveness in practice An intervention may be effective but not affordable in many countries, particularly low‐ and middle‐income countries. This paper therefore uses the efficacy estimates, qualified if necessary by real‐world effectiveness evidence, to make affordability judgements. Affordability of treatments can be construed in a variety of ways We define as affordable for a given country an intervention for which the ICER was less than the per capita gross domestic product (GDP). This corresponds to the WHO definition of ‘highly cost effective’ E is the number of ex‐tobacco users generated in a given period, N is the number of tobacco users attempting to stop and S is the probability of success of those quit attempts. Note that one may adopt different time‐periods for someone counting as an ex‐user, but for present purposes only permanent ex‐users are considered, except for smoking cessation in pregnancy.An important issue with regard to any tobacco cessation intervention is the question about how far it aims to promote attempts to quit versus helping quit attempts to succeed. This leads to what may be termed ‘the first law of tobacco cessation’, stated as:N. In populations where N is already high and S is low, it may be more efficient to seek to boost S. Of course, N and S may affect each other. For example, availability of more effective methods of stopping may boost the rate of attempts to stop. It is necessary to consider these issues when considering the different interventions.While this equation represents an obvious truth, it serves to focus attention on the need to tailor intervention strategies to different contexts. For example, in populations where the rate of cessation attempts is low but success rates are high, it is more efficient to focus resources on interventions to boost Related to this is the importance of considering the reach of an intervention. A 1 percentage‐point increase in cessation from intervention A that is delivered to 30% of smokers will have a greater population impact than a 5 percentage‐point increase from intervention B that is accessed by only 2% of smokers. Thus, some of the interventions being reviewed with low effectiveness may have a greater impact than others with high effectiveness.This review covers all forms of tobacco use and is intended to be applicable globally. However, as noted earlier, almost all the evidence is from studies of smoking, and from high‐income countries. Where we have been able to find studies from low‐ and middle‐income countries we have included them. In the absence of evidence to the contrary we propose that evidence on smoking cessation should be applied to all forms of tobacco cessation, and in the absence of evidence from low‐ and middle‐income countries we propose that the evidence from high‐income countries be applied to all countries, interpreted in the light of national circumstances and priorities.In summary, this paper provides a concise review of the evidence on tobacco cessation interventions for use in guideline development, and in selecting and prioritizing cessation interventions at the national level, and includes assessments of affordability using an approach based on the one used by the WHO. With such a diverse range of interventions and contexts, the conclusions must be stated in very broad terms and subject to major caveats. With this in mind, the review is accompanied by an affordability calculator (Supporting information) in which users can vary their estimates to assess the impact on affordability.The Cochrane Library was searched to identify all systematic reviews of the efficacy of health‐care tobacco cessation interventions. Health‐care interventions were defined as those that involved pharmacological treatment, advice or support from a health‐care worker, printed materials or automated systems delivered to individuals or groups. We have included the last two categories of intervention, because these are important and are often delivered by health‐care agencies. We have excluded mass media campaigns, although these can clearly promote cessation Major intervention types were identified from the reviews. Reviews relating to specific subgroups of smokers or specific components or forms of behavioural support  were excluded in order to focus on broad intervention categories. Those intervention types with statistically significant overall efficacy relative to a comparator from meta‐analyses were selected for inclusion in this review. Supporting information, Appendix S1, shows the reviews used for primary effect size estimation. Where there was significant variation (‘heterogeneity’) in effect sizes from different studies, it was noted. Supporting information, Appendix S2, shows Cochrane reviews that were considered and not included or were used to qualify judgements about effect size.The pooled effect sizes from the meta‐analyses were recalculated as the overall percentage‐point difference between intervention and comparator conditions together with 95% confidence intervals of the estimate, taking account of any heterogeneity in effect size across studies. Studies included in the Cochrane reviews typically involved 6–12 months of follow‐up, which allows confident extrapolation to permanent cessation in a way that can be used for cost‐effectiveness analyses In the case of some interventions the target population may be all smokers coming into contact with a clinical service, whereas in others it may be smokers who are willing to use a particular method to help them in a quit attempt. Evidence from high‐income countries suggests that, even where they are widely available, only about 5% of smokers currently use face‐to‐face behavioural interventions to help them stop, but more than 30% may use a medication such as nicotine replacement therapy, which they can buy from a shop or pharmacy When given to [population category], [intervention category] has been found in multiple (≥ 2) RCTs to increase 6–12‐month abstinence rates by [range of values] compared with [comparator].The key efficacy statements in this review take the following form:For internationally applicable statements of effectiveness, it is important to recognize that the implementation of the intervention, the intervention provider and population of tobacco users may differ widely. For example, evidence on physician advice may or may not generalize to advice from other types of health‐care worker, and the effectiveness of a given type of health‐care worker may vary across cultures. Therefore, it is necessary to form judgements about probable transferability on the basis of inference and whatever relevant evidence is available.A review was conducted using PubMed and Web of Science of studies of effectiveness of the interventions covered by the efficacy review. The initial search was conducted using labels to identify the intervention  combined with ‘smoking cessation’ or ‘tobacco cessation’. Studies were included if they were RCTs that could provide information about the generalizability of the RCTs in the Cochrane reviews or where they were observational studies that estimated the incremental cessation rates in samples using the intervention, taking account of important confounding variables such as severity of dependence on tobacco The starting points for affordability estimates were the efficacy estimates derived from the Cochrane reviews, qualified if necessary by effectiveness judgements. These were used to calculate incremental cost effectiveness ratios for life years gained (ICERs) based on cost information (see below). Because of the high variability in costs in different countries, particularly in the cost of health‐care worker time, and potentially different approaches to implementation, only broad estimates could be made. However, an affordability calculator is provided in Supporting information, File 2 to allow users to make estimates using their own data.Our method of calculating ICERs An effective intervention was judged to be ‘affordable’ for a given income category of country if the ICER was less than the per capita GDP of the reference country in that category (Table http://data.worldbank.org/indicator/NY.GDP.PCAP.PP.CD), the WHO table of costs of health‐care providers for the different WHO regions for staff costs (http://www.who.int/choice/costs/prog_costs/en/index13.html) and expert sources for local costs of medications for set‐up and ancillary costs.We used World Bank data for per capita GDP expressed in international dollars , we have used an upper estimate and incorporated the set‐up costs into a unit cost per quit attempt assuming a minimum number of users. Full details of assumptions underlying costs are given in the spreadsheet (Supporting information) notes. Our general principle has been to estimate costs at the upper end of a plausible range so that affordability assessments will be conservative.Note that our affordability assessment takes no account of savings in societal, individual or health‐care costs resulting from stopping tobacco use. In many countries, these are considerable in the case of smoking and mean that many cessation interventions produce a net financial benefit over a given time‐span.The efficacy, effectiveness and affordability of the major categories of intervention are presented in this section, with the behavioural interventions considered first and then the pharmacological interventions. Within each of these categories, we consider the interventions in approximate order in which effectiveness was first established by Cochrane reviews. Table With regard to efficacy statements, some interventions use active comparators as the control condition. For example, face‐to‐face support usually uses brief advice as a comparator which would, in itself, be expected to have an effect. This means that the total effect of some interventions will be underestimated. Therefore, Table Some interventions would be expected to combine in terms of effectiveness. For example, combining medication to behavioural support is expected to produce an approximately additive effect.Brief opportunistic advice involves a health‐care worker raising the topic of smoking with a patient, advising the patient to stop and/or offering support and follow‐up. It would normally be expected to take no more than 20 minutes and most of the interventions evaluated took considerably less time than this .When given by a physician to unselected smokers attending a consultation for a medical condition, brief smoking cessation advice has been found in multiple RCTs to increase 6–12‐month continuous abstinence rates by an average of 2 percentage points [95% confidence interval (CI) = 2–3] compared with doing nothing or usual care, with an advantage for more intensive compared with minimal advice (> 20 minutes)  Countries vary considerably in how their health‐care systems are organized, including who would deliver brief advice and how they would be trained and motivated to give brief advice routinely. Nevertheless, brief advice is potentially usable globally with a very wide reach.Our analysis is that brief advice to stop smoking and offer of support from a health‐care worker can have a small but important effect in promoting smoking cessation in any health‐care system that invests in the necessary training and support for this activity.With an effect size of 2 percentage points at 6–12 months, brief advice involving an average of 20 minutes of health professional time is globally affordable  maximize motivation to remain abstinent, (2) minimize motivation to smoke, (3) enhance the skills and capacity needed to avoid and resist urges to smoke and (4) optimize effective use of stop‐smoking medication where available When given to smokers who set a quit date and who are willing to receive such help, individual face‐to‐face behavioural support has been found in multiple RCTs to increase 6–12‐month continuous abstinence rates by 4 percentage points (95% CI = 2–5) compared with provision of written materials or brief advice Evidence from the English stop‐smoking services, which currently treat approximately more than 500, 000 smokers each year, shows success rates lower than would be expected from the RCT evidence but greater than would be expected from brief advice. There is considerable variability between different local services and individual practitioners In the English services, group support appears to be more effective than individual support, and specialist practitioners  appear to be more effective than those delivering it occasionally in addition to other clinical duties Randomized trials in Pakistan and Malaysia have found behavioural support delivered as part of a TB screening and treatment service to have an effect on tobacco cessation Overall, there is reason to believe that face‐to‐face behavioural support delivered by trained health‐care workers with content developed from that used in RCTs would be effective in any health‐care system. There are, however, likely to be significant practical and financial barriers to widespread implementation of programmes of this kind in many countries, except where they can be incorporated into existing health‐care provision.With an effect size of 4 percentage points at 6–12 months, face‐to‐face behavioural support involving an average of 180 minutes of health‐worker time per quit attempt would be affordable in most middle‐ and high‐income countries, but not in low‐income countries  compared with no intervention It seems reasonable to assume that self‐help materials would be effective in a wide range of contexts and populations. It is likely that literacy would be a significant factor limiting use, given that none of the materials evaluated relied exclusively on images. The content and style of the materials would be expected to play an important role in effectiveness, but there is no evidence to indicate what specific components should be included.Overall, printed self‐help materials would be expected to be useful in helping smokers to stop in a wide range of settings.If self‐help materials could achieve an effect size of 2 percentage points at 6–12 months, they would be globally affordable (see Table Telephone support involves similar broad categories of activity to face‐to‐face support (see above). It can be ‘proactive’ or ‘reactive’. In proactive support a trained counsellor initiates calls, following an initial enquiry by the caller, to provide support according to an agreed schedule, while in a reactive model support is available on demand to people who call a quitline number.When given to smokers wanting help with stopping, proactive telephone support has been found in multiple RCTs to increase 6–12‐month continuous abstinence rates by 3 percentage points (95% CI = 2–5) compared with the offer of reactive telephone support only A large pragmatic RCT of multi‐lingual proactive telephone support versus self‐help materials in Asian smokers in California found a clear benefit Our analysis is that there is good reason to believe that proactive telephone support can aid smoking cessation in any country, although it would be important to monitor success rates to establish that a specific service was delivering expected results.With an effect size of 3 percentage points at 6–12 months over reactive support and an average of 120 minutes of contact time per quit attempt, telephone support would be globally affordable  compared with text messaging programmes providing generic health advice As long as the content of programmes on offer to smokers is based on what was in the successful RCTs, there is reason to believe that broadly similar effects to those found in the RCTs would be seen. A large trial of a text messaging intervention, Text2Stop, showed a clear benefit Our analysis is that automated text messaging programmes can support smokers to stop and the content of the programmes should be based on those that have shown a clear benefit.With an effect size of 4 percentage points at 6–12 months, automated text messaging is globally affordable  are likely to be added to this list of licensed medicines in the coming years.Smokers typically use these products starting on the designed target quit day and continuing for up to 12 weeks. Use can be started before the quit date, and they can be used for smoking reduction with a view to quitting at a later date.When given to smokers of 15 or more cigarettes per day who are making a quit attempt on a pre‐specified day and willing to use NRT, multiple RCTs have shown that this type of aid increases 6–12‐month continuous abstinence rates by 6 percentage points (95% CI = 6–7) compared with placebo There is insufficient information to draw conclusions about whether one form of NRT is likely to be more effective than another, overall, but evidence suggests that higher‐dose forms may be more effective than lower‐dose forms Evidence from multiple RCTs has shown that combining a nicotine patch with a faster‐delivery form of NRT (such as gum) increases 6–12‐month abstinence rates by 5 percentage points compared with single‐form NRT (95% CI = 3–7) NRT has not been adequately evaluated in smokers of fewer than 10 cigarettes per day and most studies have involved smokers of 15 or more cigarettes per day.There is insufficient evidence from RCTs to draw firm conclusions as to whether or not NRT is an effective aid for smokeless tobacco cessation Several cross‐sectional surveys have been reported as having failed to find that smokers using NRT to aid a quit attempt are more likely to still be abstinent at the time of the survey Overall, our analysis suggests that NRT in the context of at least some behavioural support can aid smoking cessation in moderately heavy or heavy smokers. It appears not to be effective when bought from shops with no behavioural support. Combining transdermal patches with a faster‐acting product such as chewing gum or lozenge is more effective than using either alone.With an effect size of 6 percentage points at 6–12 months, and assuming up to 40 minutes of health‐worker time to explain and supervise use, NRT is affordable in middle‐ and high‐income countries but not in low‐income countries  compared with placebo There is insufficient evidence from RCTs to draw conclusions about whether 300 mg (the standard dose) is more effective than 150 mg Extending the course of treatment beyond 8 weeks appears to increase abstinence rates while the medication is being taken, but not when assessed 12 months after the medication has been discontinued Bupropion has not been shown to be effective for treating users of smokeless tobacco Evidence suggests that bupropion is broadly similar in effectiveness to NRT Bupropion has not been tested without behavioural support. Smokers who use it in the English stop‐smoking services have similar short‐term success rates to those who use single‐form NRT and higher than those who use no medication Our analysis is that bupropion is a useful aid to smoking cessation in moderately heavy or heavy smokers, at least in the context of behavioural support, and is at least as effective as single‐form NRT.With an effect size of 7 percentage points at 6–12 months, bupropion, together with approximately 60 minutes of health professional time for screening and checking of adverse reactions, is affordable in middle‐ and high‐income countries but not in low‐income countries  percentage points compared with placebo Nortriptyline has not been evaluated without behavioural support. There is a reasonable presumption that similar tricyclic antidepressants such as amitriptyline are also effective, but these have not been tested directly.A randomized trial among prisoners in Australia did not find a benefit from nortriptyline over and above behavioural support Our assessment is that nortriptyline in moderately heavy or heavy smokers in the context of behavioural support aids smoking cessation. Patients using it experience some minor adverse reactions, particularly dry mouth, but these are not sufficient to undermine effectiveness.Nortriptyline is inexpensive, although the side‐effect profile of the drug requires more extensive supervision. With an effect size of 10 percentage points at 6–12 months, assuming 120 minutes of prescriber time for supervision, nortriptyline is affordable globally  compared with placebo and 7 percentage points (95% CI = 4–11) compared with bupropion Evidence from RCTs suggests that varenicline is more effective than nicotine patches One trial has shown varenicline to help people stop using smokeless tobacco Varenicline has not been evaluated in RCTs without what would be considered intensive behavioural support , but an international cohort study strongly suggested effectiveness in routine clinical practice Our assessment is that varenicline in moderately heavy or heavy smokers in the context of behavioural support aids smoking cessation. On average, it is more effective than bupropion and single‐form NRT and at least as effective as combination NRT. Although there is little reason at present to believe that it can cause serious side effects, concerns have been raised and it has been suggested that health‐care workers show particular vigilance in case these emerge.With an effect size of 15 percentage points at 6–12 months varenicline, together with approximately 60 minutes of health professional time, is affordable in middle‐ and high‐income countries, but not in low‐income countries  compared with placebo An observational study from a large clinic in Warsaw found 12‐month biochemically verified abstinence rates somewhat greater than was found in a large clinical trial in the same clinic An open‐label RCT in smokers calling the New Zealand telephone helpline found cytisine to be more effective than nicotine replacement therapy There are more than 4 million users on the European Medicines Agency drug safety database, and no evidence has emerged of any safety problems, suggesting that this drug has a benign safety profile and is suitable for purchase with minimal or no medical supervision, as is currently the case in Russia and Poland.Our assessment is that cytisine is an effective aid to cessation in moderately heavy to heavy smokers.With an effect size of 6 percentage points at 6–12 months, and requiring relatively little clinical supervision (approximately 40 minutes), cytisine would be globally affordable .A major outcome of this review is that, based on reasonable assumptions about cost, and not taking any account of cost savings from tobacco cessation, health‐care systems of countries in every World Bank income category should be able to afford to implement smoking cessation interventions of established efficacy. Most notably, these are brief advice from a health‐care worker, proactive telephone support, printed self‐help materials, text messaging support and provision of medication such as cytisine or nortriptyline. Clearly, there are major practical challenges to achieving this and countries not currently doing this will need to give careful consideration to the pace of development that can be achieved, and which interventions to prioritize. Nevertheless, this review and our affordability calculator offer a basis for countries to establish what level of cessation provision they might aim for.It is important to note that the affordability judgements are very broad, and do not take into account important factors that may be operating in particular countries. For example, in countries such as Brazil and India, income is highly skewed and there are large numbers of very poor people in rural communities with limited access to health care. Furthermore, in many countries health care is provided principally by health‐care workers who are not medically or professionally trained, and in others by traditional health practitioners. This may necessitate considerable adaptation of training in, for example, brief advice, to local culture, infrastructure and traditions. A recent international survey of treatment provision found broad agreement with our findings of the affordability of medications globally This review has identified many important gaps in the tobacco cessation literature. There is little evidence about interventions relating to tobacco use other than cigarette smoking. More evidence is needed on how to deliver effective behavioural support, both in terms of the development of treatment manuals and delivery by individual practitioners. It is also important to identify factors that influence medication effectiveness in real‐world settings, including adherence to the treatment regimen, to assess the potential for internet‐based interventions and how to make interventions more attractive to tobacco users. There are now more than 250 smartphone applications that claim to aid smoking cessation, but these have not yet been evaluated adequately There is a significant gap in the literature on the effectiveness of combining different interventions. We have used an additive model for the combination of behavioural support and medication, but it is not clear whether this is correct. It could have been anything from multiplicative to partially additive. This is an important area for future research.Our current understanding of affordability of tobacco cessation interventions could benefit hugely from more advanced economic modelling when better data become available. Until such time, we believe that our customizable spreadsheet will provide local decision‐makers with a practical, evidence‐based tool to help select effective, affordable tobacco cessation interventions for their country.This review has not considered tobacco harm reduction, defined as ‘measures taken to reduce the harm from continued use of tobacco or tobacco‐derived products’. This typically involves users reducing consumption of cigarettes or switching to less harmful products. For example, the smokeless tobacco, snus, may provide a means of stopping smoking.A crucial issue with regard to effectiveness, affordability and reach concerns the logistics of delivering interventions and the effects of the setting on these parameters. This will vary considerably across countries and regions, and it is likely that considerable local expertise will be required to establish how interventions can be integrated with existing services.This review has been produced to support country‐specific national guideline development for smoking cessation by serving as a review of the evidence base, thus removing the need for a country to re‐review the evidence, a process that can be costly and time‐consuming, and to provide a starting point for considering what resources to devote to tobacco cessation support, and what the optimum blend of interventions might be. We hope it will be used alongside a detailed analysis at country level, by all relevant stakeholders working together, to determine cessation priorities within a country.R.W. undertakes research and consultancy for Pfizer, which manufactures varenicline, and J&J, which manufactures nicotine replacement therapy; he is honorary co‐director of the UK's National Centre for Smoking Cessation and Training and is a trustee of the charity, QUIT; his salary is funded by Cancer Research UK; M.R.: none; A.McN.: none; L.S.: none; P.A. has undertaken research and consultancy for the pharmaceutical industry on smoking cessation; J.B.: none; J.S. was formerly a consultant on clinical trial methodology to several manufacturers of smoking cessation medicines, but has no current involvement with commercial organizations; H.M. has received research funding from and provided consultancy to manufacturers of smoking cessation medications; S.P.: none; A.L.‐G.: none; R.B.: none.M.R. gratefully acknowledges Bloomberg Philanthropies, who funded his work on this review, and on the design and testing of the affordability calculator. We are also grateful to the Society for the Study of Addiction and Cancer Research UK funding this project.Appendix S1 Cochrane Reviews healthcare smoking cessation interventions included in this review.Appendix S2 Cochrane reviews not included in primary effect size calculation and reasons.Supporting info itemClick here for additional data file.Supporting info itemClick here for additional data file.Supporting info itemClick here for additional data file.


To compare the change in illicit opioid users’ risk of fatal drug‐related poisoning (DRP) associated with opioid agonist pharmacotherapy (OAP) and psychological support, and investigate the modifying effect of patient characteristics, criminal justice system (CJS) referral and treatment completion.National data linkage cohort study of the English National Drug Treatment Monitoring System and the Office for National Statistics national mortality database. Data were analysed using survival methods.All services in England that provide publicly funded, structured treatment for illicit opioid users.Adults treated for opioid dependence during April 2005 to March 2009: 151 983 individuals; 69% male; median age 32.6 with 442 950 person‐years of observation.The outcome was fatal DRP occurring during periods in or out of treatment, with adjustment for age, gender, substances used, injecting status and CJS referral.There were 1499 DRP deaths . DRP risk increased while patients were not enrolled in any treatment . Risk when enrolled only in a psychological intervention was double that during OAP . The increased risk when out of treatment was greater for men , illicit drug injectors  and those reporting problematic alcohol use .Patients who received only psychological support for opioid dependence in England appear to be at greater risk of fatal opioid poisoning than those who received opioid agonist pharmacotherapy. Non‐medical use of opioid drugs is associated with a significant global burden of disease Opioid agonist pharmacotherapy (OAP) is a community treatment for opioid dependence which aims to reduce heroin and other non‐medical opioid use and associated harm. Using oral methadone or buprenorphine, well‐delivered OAP manages the patient's physiological dependence, attenuates drug use cravings and facilitates access to health‐care and recovery supports. Meta‐analyses of randomized controlled trials show that OAP is effective at retaining patients in treatment and reducing heroin use Most developed health‐care systems also provide psychological support interventions to treat opioid dependence. Guided by individual need, preference and any previous clinical response, these interventions are offered either concurrently or sequentially with OAP, or they are offered as a stand‐alone treatment with no substitute medication.Widely delivered in the United Kingdom, community‐setting psychological support comprises a broad set of structured change methods which aim to reduce the opioid‐dependent person's cognitive behavioural symptoms, intra/interpersonal difficulties and social problems and build motivation for recovery. The patient is assigned a clinical key worker to help develop, implement and review their care plan NICE recommends that people with drug‐related problems are provided with information about self‐help groups and that those outside structured treatment are offered brief motivational interventions Observational studies of addiction treatment systems have reported that the risk of fatal drug‐related poisoning (DRP) is at least halved when patients are enrolled in treatment for opioid dependence Large‐scale research is therefore needed to inform policy and service providers about the DRP risk associated with psychological support interventions and identify modifiers of treatment impact. Isolating the individual effect of a particular treatment is challenging, because people may receive several different treatments in an episode of care and over time Previous studies have identified male gender, older age, illicit drug injecting and concurrent use of central nervous system depressants  as independent risk factors for DRP Approximately a quarter of treatment admissions in England are CJS referred What is the DRP risk associated with time patients spend in treatment and time spent out of treatment?What is the DRP risk associated with psychological support in comparison to OAP?Is the association between treatment and DRP risk moderated by: referral and patient characteristics; the first month after admission and discharge; and by successful completion of treatment?To investigate the DRP risk for community psychological support and residential interventions and compare it with the risk associated with OAP, we developed a national Drug Data Warehouse This was a national data linkage study of the English National Drug Treatment Monitoring System (NDTMS) and the Office for National Statistics (ONS) mortality database. NDTMS is a national system that monitors the delivery of all public treatment for psychoactive substance‐related problems by National Health Service and third‐sector providers NDTMS records four types of treatment: community OAP, community psychological support, in‐patient withdrawal management and drug‐free residential rehabilitation. Enrolment in in‐patient and residential treatment each provided a small number of person‐years . We noted that this reduced statistical power for an intervention level analysis. As both interventions are abstinence orientated, we judged it appropriate to create a combined grouping .During the observation period, 191 310 adults (aged 18–64 years) were treated for opioid dependence (for 1 or more days). Some patients received one treatment episode, while others received several episodes during this time. The date on which each patient started and ended each treatment enabled us to classify time spent in the following mutually exclusive groups: residential ; OAP ; and psychological support alone ; and an optional self‐report of up to three additional problematic psychoactive substances which were relevant at admission The ONS provided data on all deaths occurring during the observation period which were registered by 30 September 2011. This allowed for delays in the registration process pending inquest verdicts, as recommended for research Deaths due to DRP were identified from the following WHO International Classification of Disease (ICD‐10) codes: ‘mental and behavioural disorders due to psychoactive substance use, excluding alcohol and tobacco’ ; ‘accidental poisoning by drugs, medicaments and biological substances’ (X40–X44); ‘intentional self‐poisoning drugs, medicaments and biological substances’ (X60–X64); ‘assault by drugs, medicaments and biological substances’ (X85); and ‘poisoning by drugs, medicaments and biological substances, undetermined intent’ (Y10–Y14) Treatment and mortality data were linked using a minimal identifier in each database  and government region of usual residence. During preparatory work, we noted that when linking NDTMS data with person‐unique CJS identifiers, up to 22% of minimal identifiers in the treatment population were shared by one or more individuals. This is an overestimation of the true rate at which patients shared the same identifying characteristics because CJS identifiers are entered manually into the database and are subject to error. Conservatively, all such records were excluded from the analysis to reduce false positive matching. This created a cohort of 151 982 individuals for the present study. All patient identifiers were irreversibly encrypted to ensure that features of the original data could not be discerned.Following advice on the study procedure from the NHS Central Office for Research Ethics Committees and the office of the University of Manchester Research Ethics Committee, approval for access to NDTMS and mortality records was secured from the English National Treatment Agency for Substance Misuse and the ONS Microdata Release Panel, respectively.Unadjusted and adjusted proportional hazard ratios (HR and aHR) for the DRP risk were calculated by Cox regression (Stata release 13) with the calendar–time origin for survival set to 1 April 2005.In‐treatment status was defined according to the dates of admission/discharge for each treatment episode, identified by time‐dependent variables. Time spent out of treatment started from the day after the end of a treatment episode to the day prior to the start of a new episode (or to end of follow‐up if there were no further interventions recorded). Individuals in the cohort entered the DRP risk‐set on 1 April 2005 if they were already enrolled in treatment, or they entered the risk‐set from the start of their first treatment episode during the observation period. Cohort members ceased to be at risk at 31 March 2009, or from the date of their death from any cause.Typically, patients in the UK treatment system are expected to attend their clinical service fortnightly or more often. We noted that the discharge date could indicate erroneously that a DRP occurred out‐of‐treatment because the clinical service recorded the patient's last face‐to‐face clinical contact as their discharge date . Persons remained in that risk‐set until the end of the observation period;the risk‐set for CJS referral was defined from the date of treatment admission and this was updated (as necessary) for a subsequent episode; anddischarge status (completed or not completed) was defined for the periods following discharge, until the beginning of the next treatment‐episode or the end of the observation period.The following time‐dependent covariates were constructed:P < 0.01: gender; age (over 35 or not); DRP behavioural risks ; and CJS referral. Effect‐modification was assessed by individually fitting each of these six interactions and testing their statistical significance by likelihood ratio tests. To test joint effects of each reported interaction, all six interactions were included in a single, adjusted model.We fitted the following pre‐specified interactions to investigate effect modification for the relationship between treatment and changed DRP risk, with statistical significance set at The following time‐dependent indicators were used to investigate DRP risk following admission and discharge: the 28 days following admission; the intervening time enrolled in each treatment; and the 28 days following discharge (providing no further treatment was received). If an episode comprised a sequence of more than one type of treatment , the first 28 days out of treatment was assigned to discharge from the last treatment. The referent category was the intervening period enrolled in OAP. Using a categorical time‐dependent variable, the out‐of‐treatment DRP risk for those classified as having completed treatment successfully was compared with the risk for those who did not successfully complete treatment. Graphical plots of Schoenfeld residuals were used to check for the proportional hazard assumption in all regression models.There were two sensitivity checks. First, given the likelihood of imprecision in the reporting of treatment episode dates, the analyses were repeated with discharge dates extended by 14 days for patients who did not complete treatment. Secondly, to allow for length‐biased accrual, analyses were performed separately for treatment episodes which started before and those which started on or after 1 April 2005.Between 1 April 2005 and 31 March 2009, the 151 983 individuals in the cohort contributed 4423.4 person‐years (PY) of observation and 236 660 treatment episodes to the analysis  = 3.2–3.6]. The following covariates were associated with an increase in DRP risk: increasing age, drug injecting, problematic alcohol use, problematic benzodiazepine use and male gender Table .During treatment the DRP mortality rate was 2.9 (95% CI = 2.7–3.1) per 1000 PY and was 4.5 (95% CI = 4.1–4.9) per 1000 PY during periods out of treatment (Table P = 0.002), illicit drug injectors (P < 0.001), and patients who reported problematic alcohol use (P = 0.002). There was insufficient evidence of a treatment effect for patients referred from the CJS in contrast to non‐CJS referred patients (P < 0.001).Table After covariate adjustment, the DRP risk associated with community psychological support was twice that associated with OAP Table . There wThe first 28 days of OAP were associated with a lower DRP risk than that associated with the period enrolled in this treatment thereafter Table . There wThe DRP risk increased during the month immediately following discharge from OAP but there was weaker evidence of an increase during the month following discharge from psychological support. Patients discharged from residential treatment had approximately twice the risk associated with discharge from OAP. There was evidence that the increased DRP risk persisted for the period beyond the first month following discharge from any treatment.P = 0.11).There was insufficient evidence for a difference in post‐treatment DRP risk between patients judged to have completed treatment successfully and those who did not  and was comparable to the risk when not in treatment. This is consistent with an earlier observation that ‘drug‐free’ treatment is associated with a higher all‐cause mortality risk post‐hoc analysis to determine whether this might be due to the inclusion of those referred following release from prison, because this confers a substantially elevated risk of mortality There was no evidence that completing treatment successfully was associated with a reduction in DRP risk, nor was DRP risk reduced during treatment among people referred from the CJS. We conducted a In contrast to previous studies, we found no elevation in risk at OAP treatment onset. This may reflect more effective recent adherence to guidelines for initiation of opioid prescribing at the predominantly specialist treatment settings studied here compared to the primary care setting of an earlier English study Small‐scale, uncontrolled studies have observed reductions in drug use among CJS referrals Our study has several strengths. This is the largest cohort study on DRP risk to be published to date, comprising England‐wide data from all publicly funded opioid dependence treatment services in the NHS and third‐sector providers. It afforded sufficient statistical power to explore interactions and comparison of DRP risk for OAP and psychological support interventions. The findings were also robust to sensitivity analysis around the date of treatment discharge and between prevalent and incident treatment episodes .We also acknowledge several limitations. First, the start date for OAP is more clearly identified than its end date, because treatment cessation may only become apparent once a patient has failed to present for a repeat prescription. Our approach to recording end‐of‐treatment differed from those in some previous studies (e.g. utilizing prescription end‐date) Secondly, the observational design limits the capacity to make causal inferences. Uncontrolled confounding may account for some of the differences in DRP risk reported, and we lacked case‐mix information on opioid dependence severity and co‐existing health and social problems to strengthen the analysis. Also, because the variables describing behavioural risk factors are interval‐censored (i.e. information is only available at the start of treatment), controlling for these is likely to account for only part of the confounding. However, adjustment for the evidence‐supported covariates that were available indicated confounding away from the null .Thirdly, NDTMS data did not specify the specific methods of psychological support received by patients; thus, variability in the receipt of such treatment could not be explored. Similarly, it was not possible to distinguish the relative effects of methadone and buprenorphine within OAP, and this may have led to a loss of information. Both of these are accessible in the publicly funded, community‐based UK treatment setting. We note recent work indicating a lower risk associated with buprenorphine during early treatment The elevated risks observed on discharge from OAP and residential treatments are consistent with previous studies The treatment classification of successful completion  has face validity as an indicator of clinical effectiveness. Recent treatment policy in the United Kingdom has emphasized monitoring of this criterion as an important indicator of effectiveness In conclusion, our findings show that: (1) DRP risk is lower during treatment and substantially higher out of treatment; (2) psychological support is associated with twice the risk observed for OAP; and (3) that successfully completing treatment is not associated with a reduction in risk. Because psychological support was the second most common pattern observed in the present study, we recommend that there should be a clear focus upon identifying and reducing overdose risk in patients who receive stand‐alone psychological support for opioid dependence. Opioid overdose should be an explicit discussion topic with patients who present for psychological support.T.M. has received research funding from the UK National Treatment Agency for Substance Misuse  and the Home Office. He is a member of the organizing committee for, and chairs, conferences supported by unrestricted educational grants from Reckitt Benckiser, Lundbeck, Martindale Pharma and Britannia Pharmaceuticals Ltd, for which he receives no personal remuneration. S.M.B. holds GSK shares. She chaired Home Office's Surveys, Design and Statistics Subcommittee (SDSSC) when its report on 21st Century Drugs and Statistical Science was published. She has previously served as UK representative on the Scientific Committee for European Monitoring Centre for Drugs and Drug Addiction. She is co‐principal investigator for MRC‐funded, prison‐based N‐ALIVE pilot Trial. J.M. works in an integrated university  and National Health Service Academic Health Sciences Centre  and is supported by university‐based research grants from the Department of Health, Institute for Health Research , and the National Institute for Health Research (NIHR) Biomedical Research Centre for Mental Health at South London and Maudsley NHS Foundation Trust (SLaM) and IoPPN/KCL. He declares part‐time employment as Senior Academic Adviser for the Alcohol, Drugs and Tobacco Division, Health and Wellbeing Directorate, Public Health England. He acknowledges the following pharmaceutical industry support: educational grant funding to KCL and SLaM from Indivior PLC via Action on Addiction for a study psychological interventions in opioid dependence (2010‐2016); consultation to Merck Serono , and honoraria as co‐chair of the Improving Outcomes in Treatment of Opioid Dependence conference (2015) via educational grant funding from Indivior to PCM Scientific. He holds no stocks in any company. A.J. has received research funding from the UK National Treatment Agency for Substance Misuse  and the Home Office.Appendix S1 Covariates estimates for models in analysis.Appendix S2 Sensitivity analysis comparing periods in treatment with periods out after varying the treatment end date to two weeks later than the recorded date for those with an ‘unplanned’ discharge.Appendix S3 Sensitivity analysis: Separate proportional hazard analysis for those in treatment 1st April 2005  and those who entered treatment between 1st April 2005 to 31st March 2009 (incident cohort).Appendix S4 Most common sequences of treatment interventions within a treatment‐episode, first incident episodes only .Appendix S5 Post hoc analysis to assess the independent impact of CJS referrals from prison and the community.Supporting info itemClick here for additional data file.


The relationships of miRNA expression with muscle mass and strength was also determined in a group of healthy older men.Loss of muscle mass and strength is a significant comorbidity in patients with chronic obstructive pulmonary disease (COPD) that limits their quality of life and has prognostic implications but does not affect everyone equally. To identify mechanisms that may contribute to the susceptibility to a low muscle mass, we investigated microRNA (miRNA) expression, methylation status, and regeneration in quadriceps muscle from COPD patients and the effect of miRNAs on myoblast proliferation We identified miRNAs associated with a low fat‐free mass (FFM) phenotype in a small group of patients with COPD using a PCR screen of 750 miRNAs. The expression of two differentially expressed miRNAs (miR‐675 and miR‐519a) was determined in an expanded group of COPD patients and their associations with FFM and strength identified. The association of these miRNAs with FFM and strength was also explored in a group of healthy community‐dwelling older men. As the expression of the miRNAs associated with FFM could be regulated by methylation, the relative methylation of the H19 ICR was determined. Furthermore, the proportion of myofibres with centralized nuclei, as a marker of muscle regeneration, in the muscle of COPD patients was identified by immunofluorescence.In vitro, miR‐675 inhibited myoblast proliferation and patients with a low FFMI had fewer centralized nuclei suggesting miR‐675 represses regeneration.Imprinted miRNAs  were differentially expressed in the quadriceps of patients with a low fat‐free mass index (FFMI) compared to those with a normal FFMI. In larger cohorts, miR‐675 and its host gene (H19) were higher in patients with a low FFMI and strength. The association of miR‐519a expression with FFMI was present in male patients with severe COPD. Similar associations of miR expression with lean mass and strength were not observed in healthy community dwelling older men participating in the Hertfordshire Sarcopenia Study. Relative methylation of the H19 ICR was reduced in COPD patients with muscle weakness but was not associated with FFM. The data suggest that increased expression of miR‐675/H19 and altered methylation of the H19 imprinting control region are associated with a low FFMI in patients with COPD but not in healthy community dwelling older men suggesting that epigenetic control of this loci may contribute to a susceptibility to a low FFMI. Consequently the loss of muscle mass and strength that accompanies a range of chronic diseases impairs the quality of life of many individuals. Quadriceps muscle wastingIn healthy adults muscle mass is maintained by balancing loss  with synthesis (through protein synthesis and satellite cell recruitment).quadriceps muscle of COPD patients, associated with an increase in its target, HDAC4.MicroRNAs (miRNAs) are important regulators of cell phenotype involved in both normal development and disease.As many miRNAs are processed from RNA polymerase II dependent transcripts, miRNA levels will be affected by the same mechanisms that control mRNA production, including DNA methylation. Consistent with this suggestion, hypermethylation of the loci for miR‐9, ‐148, and ‐34c inactivates expression of these miRNAs in cancer cells.Smoking, a primary cause of COPD, is known to modify DNA methylation through a number of mechanisms including the introduction of DNA breaks and nicotine dependent suppression of DNA methylase (DNMT1) expression  guidelines 2004et al.TableCOPD subjects in this study form part of a larger well‐phenotyped cohort described by Natanek vastus lateralis in the mid‐thigh of the leg that strength was tested was performed under local anaesthesia using the Bergstrom technique.Quadriceps strength was determined by measuring supine isometric maximal voluntary contraction (MVC) and unpotentiated Twitch force (TwQ) as described previouslyvastus lateralis under local anaesthesia as described previously.Samples from the Herts Sarcopenia Study studyThe amplified cDNAs were quantified using Human TaqMan® Array MicroRNA Cards  according to the manufacturer's instructions on an ABI 7900HT thermocycler. Array cards were run under the 384 well TaqMan® Low Density Array default thermal‐cycling conditions defined by SDS 2.4 software. Once complete all cards were calibrated to a single control sample and one detection threshold set across all samples and assays using RQ manager software. The resultant Ct values were then exported and normalized to the geometric mean of U6, RNU44, and RNU48, using the ΔΔ Ct method. As variance tended to increase with miRNA intensity the data were standardized by a log transformation.Messenger RNA was extracted and quantified by quantitative real time PCR (qRTPCR) as described previouslyFor the quantification of individual microRNAs, custom designed primers and probes were purchased for each test gene from Applied Biosystems, and amplification was carried out on cDNA preamplified as described above according to the manufacturer's instructions. Each reaction was performed in duplicate, and the average Ct value normalized to the corresponding geometric mean of U6, and RNU44 using the ΔΔ Ct method. RNA isolated from cells was analysed using single RT reactions. MiRNAs were quantified in 16 controls, 24 low FFMI patients, and 24 normal FFMI patients the COPD cohort and from 67 individuals in the Herts Sarcopenia Study cohort.DNA from muscle biopsies  was extracted using the QIAamp DNA Mini kit (Life Technologies) according to manufacturer's instructions. The two resulting elutions were then pooled and precipitated. The resuspended DNA was diluted to 12.5 ng/μL in AFA fiber pre‐slit Snap‐Cap microtubes  and sheared using a Covaris S220 Focused‐ultrasonicator to sonicate the DNA into 200 bp fragments using a pre‐set protocol in the SONOLAB 7.2 software . DNA (1 µg) was applied to the MethylMiner Methylated DNA Enrichment kit (Life Tech) according to the manufacturer's instructions. The resulting methylation enrichment DNA was eluted in 2000 mM and 450 mM NaCl, which were then concentrated and pooled. The DNA was then quantified using the Quant‐iT PicoGreen dsDNA (Life Tech) according to manufacturer's instructions. The methylation enriched DNA was diluted to 0.1 ng/μL whilst the original (non‐enriched) DNA was diluted to 1 ng/μL; 1.5 µl of DNA was amplified in 20 µl SYBR reactions as described for cDNA using primers UBE2B: For‐CTCAGGGGTGGATTGTTGAC, Rev‐TGTGGATTCAAAGACCACGA, H19 ICR: For‐TTGGTGGAACACACTGTGATCA, Rev‐GAGCCGCACCAGATCTTCAG.n = 5) and normal FFMI (n = 10) patients  and by Mann–Whitney U‐test for non‐parametric data .All gene expression data were log transformed to stabilize variance and produce a normal distribution. To identify groupings within the data set principal components analysis (PCA) and hierarchical cluster analysis (HCA) were performed in Aabel (Gigawiz). The variables for HCA were scaled to unit variance, distances were calculated based on correlation coefficients, and groups were defined based on centroid linkage. Correlation analysis was performed using Pearson correlations assuming that correlations would be linear (Aabel). Differences between groups were calculated by Student's 1 and TLCO% of predicted. Quadriceps strength, physical activity levels, and exercise performance were all reduced compared to controls. Both the low FFMI and normal FFMI COPD groups had a lower mean FFMI than the healthy controls. The low FFMI and normal FFMI groups did not differ in any characteristic measured including daily physical activity except, by design, FFMI, and consequently weight and BMI . The remaining 45 miRNAs were expressed at lower levels in low FFMI compared to normal FFMI patients. Median expression of all but 2 miRNAs was lower in low FFMI patients compared to controls. Comparison of miRNA expression in low FFMI and normal FFMI patients relative to controls showed that the median expression of 17 miRNAs changed in opposing directions in low FFMI vs. controls  compared to normal FFMI vs. controls   FigureTable S6) Figure, and ninn = 16, normal FFMI n = 24 and low FFMI n = 24, freshly prepared cDNA samples from five normal FFMI, one low FFMI COPD patients, and four controls from the original screen were used in this expanded study). The physiological characteristics of these groups are given in TableP = 0.013, low FFMI vs. normal FFMI; P = 0.027, Bonferonni corrected P value for significance = 0.016). There was no difference in the expression of miR‐675 between normal FFMI patients and controls  were quantified in an expanded cohort of muscle samples from patients including both males and females of all GOLD stages and healthy controls  increased the association between miR‐519a and FFMI  raising the possibility of a sex‐specific effect. Analysis of a second miRNA from the same locus (miR‐518e) in GOLD III–IV males also showed a positive association of C19MC miRs with FFMI in these patients , consistent with the array, miR‐519a was lower in individuals with a low FFMI than in those with a normal FFMI  and with quadriceps strength . H19 expression was also higher in those patients defined as weak based on an MVC less than 120% of their BMI (P = 0.01). In those patients in which we analysed both miRNA and mRNA, expression of miR‐675 and H19 showed a positive association .As miR‐675 is processed from the H19 lincRNA, we determined the expression of H19. As the cDNAs for the miRNAs were generated separately from cDNAs for mRNA analysis and our samples were limited, it was only possible to obtain overlapping but distinct data sets for miR‐675 and H19. This analysis used samples from 11 controls, 34 NFFMI patients, and 22 low FFMI patients; 31 samples were included in both miRNA and mRNA analyses  to our measurements of H19 performed by non‐allele specific PCR  indicating that the approach was valid.To determine whether H19 was expressed from one or both alleles in adult muscle we used allele‐specific PCR for the polymorphism RS2075245, which is in exon 1 of H19, close to miR‐675. In this experiment homozygosity or mono‐allelic expression was assumed when there was difference in Cycle threshold for each of the alleles of four cycles . In this analysis, expression of a single SNP variant was detected in 60% of the samples whereas expression of both variants was detected in the remaining 40%. Within the European Caucasian population the A:T allele frequency is 48:52 so that the approximately 50% of individuals are heterozygous. Therefore, in the majority of individuals both alleles were active in the muscle. However in the subjects in whom both A and T alleles were detected, one allele contributed more than 75% of the transcript in all but three cases indicating that one allele was suppressed, probably by methylation. It was not possible to determine whether the same was true from homozygous individuals. As these primers are designed for genotyping and not mRNA quantification, to verify that the method quantified H19 RNA, the expression of each allele was normalized to RPLPO and the values summed. This value correlated strongly  but not with FFMI and was different between patients with normal strength and weak patients  unless normalized to FFMI . Similarly strength normalized for FFMI was also correlated with ICR methylation in the patients alone  and in the cohort as a whole . Methylation of the C19MC was not determined because these miRNAs are not expressed in differentiated cells.To determine whether methylation regulates H19 expression in muscle, we used methylated DNA immunoprecipitation (MeDIP) followed by qPCR using muscle samples from 10 healthy controls, 14 normal FFMI patients, and 15 low FFMI patients. Methylation on the ICR of precipitated H19 DNA was quantified relative to a comparatively unmethylated gene UBE2B. There was no significant difference between relative ICR methylation between patients and controls. Consistent with methylation suppressing H19 expression, the ICR:UBE enrichment ratio was inversely correlated with H19 expression in the COPD patients  or with physical capability marked by 3m walking time and 6m time to get up and go. Furthermore, there was no association of the expression of these miRNAs with birth weight. Comparison of the expression of miR‐675 and miR‐519a in people with a history of smoking and in non‐smokers also showed no difference.P = 0.037, FigureP = 0.036, FigureP = 0.014) and miR‐519a was lower  in the low FFMI patients than in the normal FFMI patients.The ability of miR‐675 to inhibit C2C12 cell proliferation . Recently it has also been shown that miR‐675 promotes myoblast differentiationin vitro. These data suggest that C19MC miRNAs may contribute to the normal FFMI phenotype by promoting stem cell survival.The C19 microRNA cluster is the largest cluster of miRNAs in the human genome but arose relatively late in evolution and is only found in primates.It is important to note that the association of C19MC expression with FFMI was only evident in males with severe COPD. The lack of association of C19MCs in the cohort as a whole and in other groups individually may be because of confounding factors and/or statistical power as some of the sub‐groups were relatively small. It is also possible that it is only apparent in the severe subgroup as, in the absence of significant physiological stress because of severe disease, the requirement for regeneration will be limited to normal muscle cell turnover.Both C19MC and H19 expressions are regulated by imprinting.Most studies of imprinted genes focus on development and the early post‐natal period. Consequently the association of H19 and miR‐675 with muscle mass and strength in adults has not previously been noted, and we did not find an association of miR‐675 with FFMI or strength in the Herts Sarcopenia Study participants. This observation suggests that the association is only present or detectable in patients with a disease that predisposes to muscle wasting. It is therefore possible that differences in the expression of this miRNA are only of functional significance when there is an increased atrophic drive and/or an increase in the demand for muscle synthesis.et al.2 compared to those with a mid thigh cross‐sectional area > 70 cm2 we found that patients with a low FFMI had reduced proportion of myofibres with centralized nuclei. This observation implies that a low level of regeneration contributes to the low FFMI phenotype. As described above both a low level of expression of C19MC miRNAs and an increased miR‐675 expression may contribute to this reduction in regeneration.Consistent with the recent studies of Theriault et al. or because the effects of miR‐675 are on the proliferation of committed myoblasts rather than the number of satellite cells. Whether any such senescence results from high miR‐675 and/or low C19MC expression remains to be established.The study is cross sectional, and as such the data can only demonstrate associations rather than causation. Nevertheless, our analysis of the muscle has highlighted a number of miRNAs with potential mechanistic relevance to the development of skeletal muscle dysfunction in COPD that warrant further investigation. Although one interpretation of our data is that there is a reduction in the number of satellite cells, we did not quantify satellite cell number directly because of the number and size of the samples available. Our analysis of centralized nuclei is consistent with the data of Theriault,There is significant variation in the amount or rate of loss of muscle mass in response to a range of diseases. In COPD, skeletal atrophy appears to be a significant factor in about 25% of patients that can start early in the disease.Our data show that increased expression of miR‐675 and H19 are associated with a low FFMI in patients with COPD. Furthermore, increased expression of H19 is inversely correlated with relative methylation of the H19 ICR. In male patients with severe COPD, expression of the paternally expressed C19MC miRNAs was suppressed in patients with a low FFMI. We also confirmed that patients with a low FFMI had lower levels of muscle regeneration than patients with a normal FFMI. Together these data suggest that expression of imprinted miRNAs may contribute to the susceptibility to a low FFMI phenotype in COPD.All subjects gave written informed consent; the COPD study protocol was approved by the Royal Brompton & Harefield NHS Trust Research Ethics Committee (Study numbers 06/Q0404/35 and 06/Q0410/54); the Herts Sarcopenia Study study protocol was approved by the Hertfordshire Research Ethics Committee (study 07/Q0204/68)PK and AL proposed the hypothesis for the study. AL, JL, AD, and SV performed the miRNA, mRNA DNA, and cell culture analysis supervised by PK. SAN collected the human COPD muscle biopsies supervised by MP. The Herts Sarcopenia Study study samples were collected by HPP under the supervision of AAS. PK wrote the first draft of the paper, and all authors contributed to the revision of the draft and the critical analysis of the project.Amy Lewis, Jen Lee, Anna Donaldson, Srividya Vaidyanathan, Holly Syddall, Avan Sayer, and Cyrus Cooper do not have any conflicts of interest. Paul Kemp has received research grant funding from GSK and Astra Zeneca, Samantha Natanek has received grant funding from GSK, and Michael Polkey has received research grant and/or consultancy funding from GSK, Lilly, Novartis, Biomarin Astra Zeneca, and Pfizer (paid to his institution).Supporting info itemClick here for additional data file.Supporting info itemClick here for additional data file.Supporting info itemClick here for additional data file.Supporting info itemClick here for additional data file.Supporting info itemClick here for additional data file.


Multiple mechanisms are involved in pain associated with osteoarthritis (OA). The painDETECT and Self‐Report Leeds Assessment of Neuropathic Symptoms and Signs (S‐LANSS) questionnaires screen for neuropathic pain and may also identify individuals with musculoskeletal pain who exhibit abnormal central pain processing. The aim of this cross‐sectional study was to evaluate painDETECT and S‐LANSS for classification agreement and fit to the Rasch model, and to explore their relationship to pain severity and pain mechanisms in OA.A total of 192 patients with knee OA completed questionnaires covering different aspects of pain. Another group of 77 patients with knee OA completed questionnaires and underwent quantitative sensory testing for pressure–pain thresholds (PPTs). Agreement between painDETECT and S‐LANSS was evaluated using kappa coefficients and receiver operator characteristic (ROC) curves. Rasch analysis of both questionnaires was conducted. Relationships between screening questionnaires and measures of pain severity or PPTs were calculated using correlations.PainDETECT and S‐LANSS shared a stronger correlation with each other than with measures of pain severity. ROC curves identified optimal cutoff scores for painDETECT and S‐LANSS to maximize agreement, but the kappa coefficient was low (κ = 0.33–0.46). Rasch analysis supported the measurement properties of painDETECT but not those of S‐LANSS. Higher painDETECT scores were associated with widespread reductions in PPTs.The data suggest that painDETECT assesses pain quality associated with augmented central pain processing in patients with OA. Although developed as a screening questionnaire, painDETECT may also function as a measure of characteristics that indicate augmented central pain processing. Agreement between painDETECT and S‐LANSS for pain classification was low, and it is currently unknown which tool may best predict treatment outcome. Pain is a major symptom of patients with osteoarthritis (OA) and has a variety of characteristics suggesting differing underlying mechanisms Although OA is traditionally considered to be nociceptive, some patients describe aspects of their pain as burning or shooting. Such characteristics suggest mechanisms that are shared with neuropathic pain P < 0.0001). However, those investigators did not control for pain intensity and did not examine agreement between classifications.S‐LANSS uses a binary response system requiring subjects to confirm whether or not they have experienced a symptom. It uses a summative score for 7 items to classify subjects into 2 groups: pain is not of a predominantly neuropathic origin (score <12) and pain is of a predominantly neuropathic origin (score ≥12). S‐LANSS exhibited good sensitivity 74%) and specificity (76%) when compared with clinical assessment of pain type across groups of individuals with primarily nociceptive conditions  or neuropathic conditions  % and speAlthough painDETECT and S‐LANSS were developed to classify neuropathic pain, these instruments have also been used to measure neuropathic pain–like symptoms It is important to examine the measurement properties of the questionnaires, because both have been used as measurement scales. This can be achieved with Rasch analysis, which has several statistical advantages, including (given fit to the model) transformation of raw scores into interval‐level data, thereby facilitating, for example, valid analysis of changes in data following an intervention The aim of this study was to optimize and compare properties of painDETECT and S‐LANSS as classification and measurement questionnaires in patients with knee OA. Relationships between these questionnaires and measures of pain intensity were investigated to explore possible confounding by pain severity and their potential for use in phenotyping. Associations between painDETECT scores and PPTs were assessed to examine the extent to which this questionnaire measures augmented central pain processing.Box 1Although painDETECT and the Self‐Report Leeds Assessment of Neuropathic Symptoms and Sign may classify people with knee osteoarthritis (OA) according to a pain phenotype, potentially representing augmented central pain processing, the level of agreement between the classifications made by these questionnaires is low. Further work is required to establish the accuracy of these questionnaires as stratification tools in this condition.Rasch‐converted painDETECT scores may function as a measurement scale for the extent of augmented pain processing in people with knee OA.Questionnaires that classify pain mechanisms in people with OA could help target treatments to those who are most likely to benefit, and identify subgroups of patients suitable for recruitment to clinical trials.Patients with radiographic evidence of knee OA and accompanying pain on most days for the past month were recruited to participate in a cross‐sectional questionnaire study between December 2010 and July 2011  pain rating index and present pain intensity scale A separate sample of patients with clinically diagnosed OA and accompanying knee pain was recruited from primary and secondary care services through another questionnaire study, in order to measure PPTs; radiographs were not scored for these patients. As part of the questionnaire study, these patients were provided an information sheet that included a section on PPT testing and were invited to indicate on their consent form if they were interested in participating. Those interested were telephoned to confirm eligibility and to arrange a time for the test. The same exclusion criteria applied, but patients were also required to be able and willing to travel and undergo PPT testing. In addition to the larger questionnaire, the patients also completed painDETECT, a pain body map, and the ICOAP scale; all of these questionnaires were completed at home. On the day of testing (an average of 34 days after the questionnaires were administered), the patients rated their worst knee pain over the last week on a scale from 0 (no pain) to 10 (pain as severe as it could be) PPTs were measured by 1 of 2 female researchers, using an electronic pressure algometer . The algometer had a 1‐cm–diameter probe, which was applied with increasing pressure at a rate of 50 kPa/second. When patients pressed a switch to indicate that the application was experienced as pain, the probe was immediately retracted, and stimulation ceased. Patients were familiarized with the testing procedure by application of the stimulus to their fingernail. PPTs were recorded at 3 sites in reference to their more painful knee Kappa coefficients Rasch analysis http://onlinelibrary.wiley.com/doi/10.1002/acr22431/abstract). These patients were not, however, included in the other analyses  or used with the other questionnaire scores.An arithmetic average was calculated for PPTs at each site and compared using Friedman's ANOVA by ranks, with pairwise comparisons. Associations between PPTs and Rasch‐transformed painDETECT scores used Spearman's correlation coefficients and partial correlations, controlling for constant and intermittent ICOAP scores. Demographics and pain scores were compared between the questionnaire study and the PPT substudy using Mann‐Whitney U and chi‐square tests. These tests were also conducted to compare patients included in the ROC curve analysis and those who were not, and to compare patients for whom there was agreement between painDETECT and S‐LANSS pain classifications and patients for whom there was no agreement. Patients with missing questionnaire data were included in the Rasch analyses of painDETECT and S‐LANSS and therefore Rasch‐based correlations with these questionnaires, because the Rasch model can handle missing data Sample size calculations for the questionnaire study were based on Rasch analysis. Approximately 150 patients were required in order to have at least 95% confidence that item calibrations were within ±0.5 logits P < 0.05).Of the 474 patients invited to take part in the questionnaire study, 192 were eligible and agreed to participate. Of the 171 patients who responded, 83 (49%) self‐reported pain localized to their knee(s) on the MPQ body map , and 88 (51%) also reported pain in other areas. Additional characteristics of the patients are shown in Table P < 0.001) using painDETECT and S‐LANSS cutoffs of ≥19 and ≥12, respectively. Although the questionnaires showed agreement for pain classifications in 100 patients (74%), they showed disagreement in 35 patients (26%). In 21 of these 35 patients, pain was classified by S‐LANSS as primarily neuropathic and by painDETECT as unlikely neuropathic or as an ambiguous result; for the remaining 14 participants, the opposite was observed. No significant differences were observed for demographic characteristics and the majority of pain scores between patients whose classifications were agreed upon and those whose classifications were not agreed upon. However, summary median painDETECT and S‐LANSS scores were significantly higher (both P < 0.001) in the group in which classifications were disagreed upon than in the group in which classifications were agreed upon, despite producing different pain classifications on an individual patient level in the former group.Fair agreement P < 0.001 and κ = 0.46 , P < 0.001, respectively) but the new cutoffs for S‐LANSS resulted in negligible change .ROC curves were constructed Figure  to deterThe item about the “course” of the patient's pain uses a negative scoring weight that cannot be entered into RUMM2020. Therefore, 1 was added to each of the scoring weights for this item. However, because this approach resulted in misfit ; however, because rescoring did not substantially affect fit, these items were left unaltered. Summary fit statistics indicated adequate fit and a unidimensional scale Table . None ofP = 0.007) following removal of item 4 . The correlations between the questionnaires were very similar when the standard scoring systems were used instead of the Rasch‐converted scores.Rasch‐transformed painDETECT and S‐LANSS scores shared a stronger correlation with each other than with measures of pain severity Table . The assP < 0.05). The sternum and anterior tibia had significantly lower PPTs (more sensitive) compared with the medial joint line (P < 0.01). Higher painDETECT scores were associated with lower PPTs at each site, both in univariate analyses , and after controlling for ICOAP scores . Correlations between the PPT sites and the ICOAP  and NRS  scores indicated that the associations were stronger between PPTs and painDETECT than between PPTs and measures of pain severity. Standard scores for painDETECT and ICOAP produced similar correlations.Of the 114 patients contacted by telephone, 77 were included in the PPT substudy. Those who were not included either were not eligible or were unwilling to participate. Of the 76 patients who responded, 34 (45%) self‐reported pain only in their knee(s) , and 42 (55%) also reported pain in other areas. Demographic characteristics are shown in Table The characteristics of OA‐related pain are diverse, and the quality of this pain suggests mechanisms overlapping with neuropathic pain. In this study, we showed that painDETECT (with 1 item removed) may function as a measure of neuropathic pain–like symptoms in OA, but that S‐LANSS does not function well as a measurement scale. The pain characteristics measured by painDETECT were associated with widespread reductions in PPTs.The mechanisms of OA pain remain incompletely understood but may include changes in the joint and changes in central pain processing PainDETECT, with removal of 1 item, displayed good fit to the Rasch model and was relatively well targeted to the sample, supporting its measurement properties. Although additional items that assess lower trait levels would be useful to fully capture the trait range, precision at this end of the scale is perhaps of reduced importance. Instead, focus should be on individuals with higher trait levels who may benefit from interventions addressing neuropathic pain–like symptoms.S‐LANSS performed less well as a measurement scale. Misfitting items were observed, and the PSI was low, raising concerns about the reliability of the fit statistics and the ability of the scale to discern distinct strata within the sample Although some characteristics distinguish painDETECT and S‐LANSS, they shared a stronger association with each other than with measures of pain severity. The correlation between painDETECT and S‐LANSS remained strong when controlling for pain severity. Both questionnaires appear to address a coherent phenotype in patients with knee OA, despite the aforementioned differences in pain classifications. MPQ PRI scores exhibited similar associations with painDETECT, S‐LANSS, and measures of pain severity, possibly because the MPQ considers neuropathic‐like as well as nociceptive‐like characteristics PainDETECT scores are increased in patients with fibromyalgia, a condition characterized by widespread pain and tenderness associated with abnormal central pain processing but without demonstrable neuropathology Another limitation of the study is that non‐OA knee pain may have confounded the results. Individuals with central pain augmentation frequently report widespread pain, and 53% of the patients in this study reported pain at another site(s) in addition to the knee. Patients with known fibromyalgia (based on self report or case note review) were excluded, but the patients were not classified as having or not having fibromyalgia. Pain mechanisms in fibromyalgia may overlap with those in OA Neuropathic pain is classified as pain caused by a lesion or disease of the somatosensory nervous system In conclusion, ∼30% of the study sample had scores above the cutoff on painDETECT or S‐LANSS, potentially representing a phenotype within knee OA. This phenotype shares characteristics with neuropathic pain and is associated with augmented central pain processing, as indicated by widespread reductions in PPTs. The data suggest that painDETECT and S‐LANSS target a discrete phenotype in knee OA, reflecting pain quality as distinct from pain severity. In addition, Rasch analysis showed that painDETECT may be used as a measurement scale for these phenotypic characteristics. However, agreement between painDETECT and S‐LANSS for pain classification was only fair, and it is currently uncertain which tool is more accurate. Further work with a larger sample size is required to develop these questionnaires as stratification and outcome tools for testing treatments directed at central processing in patients with knee OA.All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be submitted for publication. Dr. Moreton had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.Study conception and design. Moreton, das Nair, Walsh, Lincoln.Acquisition of data. Moreton, Tew, Wheeler.Analysis and interpretation of data. Moreton, das Nair, Walsh, Lincoln.Supplementary Table 1Click here for additional data file.Supplementary Table 2Click here for additional data file.