The Association between Blood Test Trends and Undiagnosed Cancer: A Systematic Review and Critical Appraisal.

Clinical guidelines include monitoring blood test abnormalities to identify patients at increased risk of undiagnosed cancer. Noting blood test changes over time may improve cancer risk stratification by considering a patient's individual baseline and important changes within the normal range. We aimed to review the published literature to understand the association between blood test trends and undiagnosed cancer. MEDLINE and EMBASE were searched until 15 May 2023 for studies assessing the association between blood test trends and undiagnosed cancer. We used descriptive summaries and narratively synthesised studies. We included 29 articles. Common blood tests were haemoglobin (24%, n = 7), C-reactive protein (17%, n = 5), and fasting blood glucose (17%, n = 5), and common cancers were pancreatic (29%, n = 8) and colorectal (17%, n = 5). Of the 30 blood tests studied, an increasing trend in eight (27%) was associated with eight cancer types, and a decreasing trend in 17 (57%) with 10 cancer types. No association was reported between trends in 11 (37%) tests and breast, bile duct, glioma, haematological combined, liver, prostate, or thyroid cancers. Our review highlights trends in blood tests that could facilitate the identification of individuals at increased risk of undiagnosed cancer. For most possible combinations of tests and cancers, there was limited or no evidence.

Digital Medication Management in Polypharmacy.

BACKGROUND: Inappropriate drug prescriptions for patients with polypharmacy can have avoidable adverse consequences. We studied the effects of a clinical decision-support system (CDSS) for medication management on hospitalizations and mortality. METHODS: This stepped-wedge, cluster-randomized, controlled trial involved an open cohort of adult patients with polypharmacy in primary care practices (=clusters) in Westphalia-Lippe, Germany. During the period of the intervention, their medication lists were checked annually using the CDSS. The CDSS warns against inappropriate prescriptions on the basis of patient-related health insurance data. The combined primary endpoint consisted of overall mortality and hospitalization for any reason. The secondary endpoints were mortality, hospitalizations, and high-risk prescription. We analyzed the quarterly health insurance data of the intention- to-treat population with a mixed logistic model taking account of clustering and repeated measurements. Sensitivity analyses addressed effects of the COVID-19 pandemic and other effects. RESULTS: 688 primary care practices were randomized, and data were obtained on 42 700 patients over 391 994 quarter years. No significant reduction was found in either the primary endpoint (odds ratio [OR] 1.00; 95% confidence interval [0.95; 1.04]; p = 0.8716) or the secondary endpoints (hospitalizations: OR 1.00 [0.95; 1.05]; mortality: OR 1.04 [0.92; 1.17]; high-risk prescription: OR 0.98 [0.92; 1.04]). CONCLUSION: The planned analyses did not reveal any significant effect of the intervention. Pandemicadjusted analyses yielded evidence that the mortality of adult patients with polypharmacy might potentially be lowered by the CDSS. Controlled trials with appropriate follow-up are needed to prove that a CDSS has significant effects on mortality in patients with polypharmacy.

Multi-cancer early detection test in symptomatic patients referred for cancer investigation in England and Wales (SYMPLIFY): a large-scale, observational cohort study.

BACKGROUND: Analysis of circulating tumour DNA could stratify cancer risk in symptomatic patients. We aimed to evaluate the performance of a methylation-based multicancer early detection (MCED) diagnostic test in symptomatic patients referred from primary care. METHODS: We did a multicentre, prospective, observational study at National Health Service (NHS) hospital sites in England and Wales. Participants aged 18 or older referred with non-specific symptoms or symptoms potentially due to gynaecological, lung, or upper or lower gastrointestinal cancers were included and gave a blood sample when they attended for urgent investigation. Participants were excluded if they had a history of or had received treatment for an invasive or haematological malignancy diagnosed within the preceding 3 years, were taking cytotoxic or demethylating agents that might interfere with the test, or had participated in another study of a GRAIL MCED test. Patients were followed until diagnostic resolution or up to 9 months. Cell-free DNA was isolated and the MCED test performed blinded to the clinical outcome. MCED predictions were compared with the diagnosis obtained by standard care to establish the primary outcomes of overall positive and negative predictive value, sensitivity, and specificity. Outcomes were assessed in participants with a valid MCED test result and diagnostic resolution. SYMPLIFY is registered with ISRCTN (ISRCTN10226380) and has completed follow-up at all sites. FINDINGS: 6238 participants were recruited between July 7 and Nov 30, 2021, across 44 hospital sites. 387 were excluded due to staff being unable to draw blood, sample errors, participant withdrawal, or identification of ineligibility after enrolment. Of 5851 clinically evaluable participants, 376 had no MCED test result and 14 had no information as to final diagnosis, resulting in 5461 included in the final cohort for analysis with an evaluable MCED test result and diagnostic outcome (368 [6·7%] with a cancer diagnosis and 5093 [93·3%] without a cancer diagnosis). The median age of participants was 61·9 years (IQR 53·4-73·0), 3609 (66·1%) were female and 1852 (33·9%) were male. The MCED test detected a cancer signal in 323 cases, in whom 244 cancer was diagnosed, yielding a positive predictive value of 75·5% (95% CI 70·5-80·1), negative predictive value of 97·6% (97·1-98·0), sensitivity of 66·3% (61·2-71·1), and specificity of 98·4% (98·1-98·8). Sensitivity increased with increasing age and cancer stage, from 24·2% (95% CI 16·0-34·1) in stage I to 95·3% (88·5-98·7) in stage IV. For cases in which a cancer signal was detected among patients with cancer, the MCED test's prediction of the site of origin was accurate in 85·2% (95% CI 79·8-89·3) of cases. Sensitivity 80·4% (95% CI 66·1-90·6) and negative predictive value 99·1% (98·2-99·6) were highest for patients with symptoms mandating investigation for upper gastrointestinal cancer. INTERPRETATION: This first large-scale prospective evaluation of an MCED diagnostic test in a symptomatic population demonstrates the feasibility of using an MCED test to assist clinicians with decisions regarding urgency and route of referral from primary care. Our data provide the basis for a prospective, interventional study in patients presenting to primary care with non-specific signs and symptoms. FUNDING: GRAIL Bio UK.

BLOod Test Trend for cancEr Detection (BLOTTED): protocol for an observational and prediction model development study using English primary care electronic health record data.

BACKGROUND: Simple blood tests can play an important role in identifying patients for cancer investigation. The current evidence base is limited almost entirely to tests used in isolation. However, recent evidence suggests combining multiple types of blood tests and investigating trends in blood test results over time could be more useful to select patients for further cancer investigation. Such trends could increase cancer yield and reduce unnecessary referrals. We aim to explore whether trends in blood test results are more useful than symptoms or single blood test results in selecting primary care patients for cancer investigation. We aim to develop clinical prediction models that incorporate trends in blood tests to identify the risk of cancer. METHODS: Primary care electronic health record data from the English Clinical Practice Research Datalink Aurum primary care database will be accessed and linked to cancer registrations and secondary care datasets. Using a cohort study design, we will describe patterns in blood testing (aim 1) and explore associations between covariates and trends in blood tests with cancer using mixed-effects, Cox, and dynamic models (aim 2). To build the predictive models for the risk of cancer, we will use dynamic risk modelling (such as multivariate joint modelling) and machine learning, incorporating simultaneous trends in multiple blood tests, together with other covariates (aim 3). Model performance will be assessed using various performance measures, including c-statistic and calibration plots. DISCUSSION: These models will form decision rules to help general practitioners find patients who need a referral for further investigation of cancer. This could increase cancer yield, reduce unnecessary referrals, and give more patients the opportunity for treatment and improved outcomes.

Consultations for clinical features of possible cancer and associated urgent referrals before and during the COVID-19 pandemic: an observational cohort study from English primary care.

BACKGROUND: It remains unclear to what extent reductions in urgent referrals for suspected cancer during the COVID-19 pandemic were the result of fewer patients attending primary care compared to GPs referring fewer patients. METHODS: Cohort study including electronic health records data from 8,192,069 patients from 663 English practices. Weekly consultation rates, cumulative consultations and referrals were calculated for 28 clinical features from the NICE suspected cancer guidelines. Clinical feature consultation rate ratios (CRR) and urgent referral rate ratios (RRR) compared time periods in 2020 with 2019. FINDINGS: Consultations for cancer clinical features decreased by 24.19% (95% CI: 24.04-24.34%) between 2019 and 2020, particularly in the 6-12 weeks following the first national lockdown. Urgent referrals for clinical features decreased by 10.47% (95% CI: 9.82-11.12%) between 2019 and 2020. Overall, once patients consulted with primary care, GPs urgently referred a similar or greater proportion of patients compared to previous years. CONCLUSION: Due to the significant fall in patients consulting with clinical features of cancer there was a lower than expected number of urgent referrals in 2020. Sustained efforts should be made throughout the pandemic to encourage the public to consult their GP with cancer clinical features.

Quit and Win contests for smoking cessation.

This review has been withdrawn because it has been superceded by the Cochrane Review of Competitions for smoking cessation.

Effectiveness of the application of an electronic medication management support system in patients with polypharmacy in general practice: a study protocol of cluster-randomised controlled trial (AdAM).

INTRODUCTION: Clinically complex patients often require multiple medications. Polypharmacy is associated with inappropriate prescriptions, which may lead to negative outcomes. Few effective tools are available to help physicians optimise patient medication. This study assesses whether an electronic medication management support system (eMMa) reduces hospitalisation and mortality and improves prescription quality/safety in patients with polypharmacy. METHODS AND ANALYSIS: Planned design: pragmatic, parallel cluster-randomised controlled trial; general practices as randomisation unit; patients as analysis unit. As practice recruitment was poor, we included additional data to our primary endpoint analysis for practices and quarters from October 2017 to March 2021. Since randomisation was performed in waves, final study design corresponds to a stepped-wedge design with open cohort and step-length of one quarter. SCOPE: general practices, Westphalia-Lippe (Germany), caring for BARMER health fund-covered patients. POPULATION: patients (≥18 years) with polypharmacy (≥5 prescriptions). SAMPLE SIZE: initially, 32 patients from each of 539 practices were required for each study arm (17 200 patients/arm), but only 688 practices were randomised after 2 years of recruitment. Design change ensures that 80% power is nonetheless achieved. INTERVENTION: complex intervention eMMa. FOLLOW-UP: at least five quarters/cluster (practice). recruitment: practices recruited/randomised at different times; after follow-up, control group practices may access eMMa. OUTCOMES: primary endpoint is all-cause mortality and hospitalisation; secondary endpoints are number of potentially inappropriate medications, cause-specific hospitalisation preceded by high-risk prescribing and medication underuse. STATISTICAL ANALYSIS: primary and secondary outcomes are measured quarterly at patient level. A generalised linear mixed-effect model and repeated patient measurements are used to consider patient clusters within practices. Time and intervention group are considered fixed factors; variation between practices and patients is fitted as random effects. Intention-to-treat principle is used to analyse primary and key secondary endpoints. ETHICS AND DISSEMINATION: Trial approved by Ethics Commission of North-Rhine Medical Association. Results will be disseminated through workshops, peer-reviewed publications, local and international conferences. TRIAL REGISTRATION: NCT03430336. ClinicalTrials.gov (https://clinicaltrials.gov/ct2/show/NCT03430336).

Combining simple blood tests to identify primary care patients with unexpected weight loss for cancer investigation: Clinical risk score development, internal validation, and net benefit analysis.

BACKGROUND: Unexpected weight loss (UWL) is a presenting feature of cancer in primary care. Existing research proposes simple combinations of clinical features (risk factors, symptoms, signs, and blood test data) that, when present, warrant cancer investigation. More complex combinations may modify cancer risk to sufficiently rule-out the need for investigation. We aimed to identify which clinical features can be used together to stratify patients with UWL based on their risk of cancer. METHODS AND FINDINGS: We used data from 63,973 adults (age: mean 59 years, standard deviation 21 years; 42% male) to predict cancer in patients with UWL recorded in a large representative United Kingdom primary care electronic health record between January 1, 2000 and December 31, 2012. We derived 3 clinical prediction models using logistic regression and backwards stepwise covariate selection: Sm, symptoms-only model; STm, symptoms and tests model; Tm, tests-only model. Fifty imputations replaced missing data. Estimates of discrimination and calibration were derived using 10-fold internal cross-validation. Simple clinical risk scores are presented for models with the greatest clinical utility in decision curve analysis. The STm and Tm showed improved discrimination (area under the curve ≥ 0.91), calibration, and greater clinical utility than the Sm. The Tm was simplest including age-group, sex, albumin, alkaline phosphatase, liver enzymes, C-reactive protein, haemoglobin, platelets, and total white cell count. A Tm score of 5 balanced ruling-in (sensitivity 84.0%, positive likelihood ratio 5.36) and ruling-out (specificity 84.3%, negative likelihood ratio 0.19) further cancer investigation. A Tm score of 1 prioritised ruling-out (sensitivity 97.5%). At this threshold, 35 people presenting with UWL in primary care would be referred for investigation for each person with cancer referred, and 1,730 people would be spared referral for each person with cancer not referred. Study limitations include using a retrospective routinely collected dataset, a reliance on coding to identify UWL, and missing data for some predictors. CONCLUSIONS: Our findings suggest that combinations of simple blood test abnormalities could be used to identify patients with UWL who warrant referral for investigation, while people with combinations of normal results could be exempted from referral.

Can party balloons replace autoinflation balloons to treat glue ear? A technical comparison.

BACKGROUND: Autoinflation balloons are used to treat patients with otitis media with effusion (OME) to help avoid surgery. AIM: To compare the ability of party balloons with Otovent balloons to produce sufficient pressure for a Valsalva manoeuvre. DESIGN & SETTING: Pressure testing was used to determine the number of times each balloon could produce pressures sufficient for a Valsalva manoeuvre. Subsequently, Otovent balloons were compared with spherical party balloons in a pilot clinical trial of 12 healthy adults. METHOD: Each balloon was inflated 20 times and the maximum pressure was recorded. Three balloons of each type were tested to 50 inflations to assess pressures over persistent use. RESULTS: Otovent balloons' mean inflation pressure was 93 mmHg (95% confidence interval [CI] = 89 to 97 mmHg) on first inflation, dropping to 83 mmHg (95% CI = 80 to 86 mmHg) after 20 inflations. Two types of spherical party balloon required mean inflation pressures of 84 mmHg (95% CI = 77 to 90 mmHg) and 108 mmHg (95% CI = 97 to 119 mmHg) on first inflation, dropping to 74 mmHg (95% CI = 68 to 81 mmHg) and 83 mmHg (95% CI = 77 to 88 mmHg) after 20 inflations. In the pilot trial, there was no difference between the ability of Otovent and spherical balloons (χ2 = 0.24, P = 0.89) to produce the sensation of a Valsalva manoeuvre. CONCLUSION: Otovent balloons can be used more than the 20 times quoted by the manufacturer. The two spherical balloons produced similar pressures to Otovent balloons, indicating potentially the same clinical effect. The pilot study suggests a potential use of spherical party balloons instead of Otovent balloons as a cost-efficient treatment.

Predicting negative health outcomes in older general practice patients with chronic illness: Rationale and development of the PROPERmed harmonized individual participant data database.

The prevalence of multimorbidity and polypharmacy increases significantly with age and are associated with negative health consequences. However, most current interventions to optimize medication have failed to show significant effects on patient-relevant outcomes. This may be due to ineffectiveness of interventions themselves but may also reflect other factors: insufficient sample sizes, heterogeneity of population. To address this issue, the international PROPERmed collaboration was set up to obtain/synthesize individual participant data (IPD) from five cluster-randomized trials. The trials took place in Germany and The Netherlands and aimed to optimize medication in older general practice patients with chronic illness. PROPERmed is the first database of IPD to be drawn from multiple trials in this patient population and setting. It offers the opportunity to derive prognostic models with increased statistical power for prediction of patient-relevant outcomes resulting from the interplay of multimorbidity and polypharmacy. This may help patients from this heterogeneous group to be stratified according to risk and enable clinicians to identify patients that are likely to benefit most from resource/time-intensive interventions. The aim of this manuscript is to describe the rationale behind PROPERmed collaboration, characteristics of the included studies/participants, development of the harmonized IPD database and challenges faced during this process.

A prognostic model predicted deterioration in health-related quality of life in older patients with multimorbidity and polypharmacy.

OBJECTIVES: To develop and validate a prognostic model to predict deterioration in health-related quality of life (dHRQoL) in older general practice patients with at least one chronic condition and one chronic prescription. STUDY DESIGN AND SETTING: We used individual participant data from five cluster-randomized trials conducted in the Netherlands and Germany to predict dHRQoL, defined as a decrease in EQ-5D-3 L index score of ≥5% after 6-month follow-up in logistic regression models with stratified intercepts to account for between-study heterogeneity. The model was validated internally and by using internal-external cross-validation (IECV). RESULTS: In 3,582 patients with complete data, of whom 1,046 (29.2%) showed deterioration in HRQoL, and 12/87 variables were selected that were related to single (chronic) conditions, inappropriate medication, medication underuse, functional status, well-being, and HRQoL. Bootstrap internal validation showed a C-statistic of 0.71 (0.69 to 0.72) and a calibration slope of 0.88 (0.78 to 0.98). In the IECV loop, the model provided a pooled C-statistic of 0.68 (0.65 to 0.70) and calibration-in-the-large of 0 (-0.13 to 0.13). HRQoL/functionality had the strongest prognostic value. CONCLUSION: The model performed well in terms of discrimination, calibration, and generalizability and might help clinicians identify older patients at high risk of dHRQoL. REGISTRATION: PROSPERO ID: CRD42018088129.

Development and internal validation of prognostic models to predict negative health outcomes in older patients with multimorbidity and polypharmacy in general practice.

BACKGROUND: Polypharmacy interventions are resource-intensive and should be targeted to those at risk of negative health outcomes. Our aim was to develop and internally validate prognostic models to predict health-related quality of life (HRQoL) and the combined outcome of falls, hospitalisation, institutionalisation and nursing care needs, in older patients with multimorbidity and polypharmacy in general practices. METHODS: Design: two independent data sets, one comprising health insurance claims data (n=592 456), the other data from the PRIoritising MUltimedication in Multimorbidity (PRIMUM) cluster randomised controlled trial (n=502). Population: ≥60 years, ≥5 drugs, ≥3 chronic diseases, excluding dementia. Outcomes: combined outcome of falls, hospitalisation, institutionalisation and nursing care needs (after 6, 9 and 24 months) (claims data); and HRQoL (after 6 and 9 months) (trial data). Predictor variables in both data sets: age, sex, morbidity-related variables (disease count), medication-related variables (European Union-Potentially Inappropriate Medication list (EU-PIM list)) and health service utilisation. Predictor variables exclusively in trial data: additional socio-demographics, morbidity-related variables (Cumulative Illness Rating Scale, depression), Medication Appropriateness Index (MAI), lifestyle, functional status and HRQoL (EuroQol EQ-5D-3L). Analysis: mixed regression models, combined with stepwise variable selection, 10-fold cross validation and sensitivity analyses. RESULTS: Most important predictors of EQ-5D-3L at 6 months in best model (Nagelkerke's R² 0.507) were depressive symptoms (-2.73 (95% CI: -3.56 to -1.91)), MAI (-0.39 (95% CI: -0.7 to -0.08)), baseline EQ-5D-3L (0.55 (95% CI: 0.47 to 0.64)). Models based on claims data and those predicting long-term outcomes based on both data sets produced low R² values. In claims data-based model with highest explanatory power (R²=0.16), previous falls/fall-related injuries, previous hospitalisations, age, number of involved physicians and disease count were most important predictor variables. CONCLUSIONS: Best trial data-based model predicted HRQoL after 6 months well and included parameters of well-being not found in claims. Performance of claims data-based models and models predicting long-term outcomes was relatively weak. For generalisability, future studies should refit models by considering parameters representing well-being and functional status.

UMBRELLA protocol: systematic reviews of multivariable biomarker prognostic models developed to predict clinical outcomes in patients with heart failure.

BACKGROUND: Heart failure (HF) is a chronic and common condition with a rising prevalence, especially in the elderly. Morbidity and mortality rates in people with HF are similar to those with common forms of cancer. Clinical guidelines highlight the need for more detailed prognostic information to optimise treatment and care planning for people with HF. Besides proven prognostic biomarkers and numerous newly developed prognostic models for HF clinical outcomes, no risk stratification models have been adequately established. Through a number of linked systematic reviews, we aim to assess the quality of the existing models with biomarkers in HF and summarise the evidence they present. METHODS: We will search MEDLINE, EMBASE, Web of Science Core Collection, and the prognostic studies database maintained by the Cochrane Prognosis Methods Group combining sensitive published search filters, with no language restriction, from 1990 onwards. Independent pairs of reviewers will screen and extract data. Eligible studies will be those developing, validating, or updating any prognostic model with biomarkers for clinical outcomes in adults with any type of HF. Data will be extracted using a piloted form that combines published good practice guidelines for critical appraisal, data extraction, and risk of bias assessment of prediction modelling studies. Missing information on predictive performance measures will be sought by contacting authors or estimated from available information when possible. If sufficient high quality and homogeneous data are available, we will meta-analyse the predictive performance of identified models. Sources of between-study heterogeneity will be explored through meta-regression using pre-defined study-level covariates. Results will be reported narratively if study quality is deemed to be low or if the between-study heterogeneity is high. Sensitivity analyses for risk of bias impact will be performed. DISCUSSION: This project aims to appraise and summarise the methodological conduct and predictive performance of existing clinically homogeneous HF prognostic models in separate systematic reviews.Registration: PROSPERO registration number CRD42019086990.

CASNET2: evaluation of an electronic safety netting cancer toolkit for the primary care electronic health record: protocol for a pragmatic stepped-wedge RCT.

INTRODUCTION: Safety-netting in primary care is the best practice in cancer diagnosis, ensuring that patients are followed up until symptoms are explained or have resolved. Currently, clinicians use haphazard manual solutions. The ubiquitous use of electronic health records provides an opportunity to standardise safety-netting practices.A new electronic safety-netting toolkit has been introduced to provide systematic ways to track and follow up patients. We will evaluate the effectiveness of this toolkit, which is embedded in a major primary care clinical system in England:Egerton Medical Information System(EMIS)-Web. METHODS AND ANALYSIS: We will conduct a stepped-wedge cluster RCT in 60 general practices within the RCGP Research and Surveillance Centre (RSC) network. Groups of 10 practices will be randomised into the active phase at 2-monthly intervals over 12 months. All practices will be activated for at least 2 months. The primary outcome is the primary care interval measured as days between the first recorded symptom of cancer (within the year prior to diagnosis) and the subsequent referral to secondary care. Other outcomes include referrals rates and rates of direct access cancer investigation.Analysis of the clustered stepped-wedge design will model associations using a fixed effect for intervention condition of the cluster at each time step, a fixed effect for time and other covariates, and then include a random effect for practice and for patient to account for correlation between observations from the same centre and from the same participant. ETHICS AND DISSEMINATION: Ethical approval has been obtained from the North West-Greater Manchester West National Health Service Research Ethics Committee (REC Reference 19/NW/0692). Results will be disseminated in peer-reviewed journals and conferences, and sent to participating practices. They will be published on the University of Oxford Nuffield Department of Primary Care and RCGP RSC websites. TRIAL REGISTRATION NUMBER: ISRCTN15913081; Pre-results.

Factors associated with COVID-19-related death using OpenSAFELY.

Coronavirus disease 2019 (COVID-19) has rapidly affected mortality worldwide1. There is unprecedented urgency to understand who is most at risk of severe outcomes, and this requires new approaches for the timely analysis of large datasets. Working on behalf of NHS England, we created OpenSAFELY-a secure health analytics platform that covers 40% of all patients in England and holds patient data within the existing data centre of a major vendor of primary care electronic health records. Here we used OpenSAFELY to examine factors associated with COVID-19-related death. Primary care records of 17,278,392 adults were pseudonymously linked to 10,926 COVID-19-related deaths. COVID-19-related death was associated with: being male (hazard ratio (HR) 1.59 (95% confidence interval 1.53-1.65)); greater age and deprivation (both with a strong gradient); diabetes; severe asthma; and various other medical conditions. Compared with people of white ethnicity, Black and South Asian people were at higher risk, even after adjustment for other factors (HR 1.48 (1.29-1.69) and 1.45 (1.32-1.58), respectively). We have quantified a range of clinical factors associated with COVID-19-related death in one of the largest cohort studies on this topic so far. More patient records are rapidly being added to OpenSAFELY, we will update and extend our results regularly.

Incentives for smoking cessation.

BACKGROUND: Financial incentives, monetary or vouchers, are widely used in an attempt to precipitate, reinforce and sustain behaviour change, including smoking cessation. They have been used in workplaces, in clinics and hospitals, and within community programmes. OBJECTIVES: To determine the long-term effect of incentives and contingency management programmes for smoking cessation. SEARCH METHODS: For this update, we searched the Cochrane Tobacco Addiction Group Specialised Register, clinicaltrials.gov, and the International Clinical Trials Registry Platform (ICTRP). The most recent searches were conducted in July 2018. SELECTION CRITERIA: We considered only randomised controlled trials, allocating individuals, workplaces, groups within workplaces, or communities to smoking cessation incentive schemes or control conditions. We included studies in a mixed-population setting (e.g. community, work-, clinic- or institution-based), and also studies in pregnant smokers. DATA COLLECTION AND ANALYSIS: We used standard Cochrane methods. The primary outcome measure in the mixed-population studies was abstinence from smoking at longest follow-up (at least six months from the start of the intervention). In the trials of pregnant women we used abstinence measured at the longest follow-up, and at least to the end of the pregnancy. Where available, we pooled outcome data using a Mantel-Haenzel random-effects model, with results reported as risk ratios (RRs) and 95% confidence intervals (CIs), using adjusted estimates for cluster-randomised trials. We analysed studies carried out in mixed populations separately from those carried out in pregnant populations. MAIN RESULTS: Thirty-three mixed-population studies met our inclusion criteria, covering more than 21,600 participants; 16 of these are new to this version of the review. Studies were set in varying locations, including community settings, clinics or health centres, workplaces, and outpatient drug clinics. We judged eight studies to be at low risk of bias, and 10 to be at high risk of bias, with the rest at unclear risk. Twenty-four of the trials were run in the USA, two in Thailand and one in the Phillipines. The rest were European. Incentives offered included cash payments or vouchers for goods and groceries, offered directly or collected and redeemable online. The pooled RR for quitting with incentives at longest follow-up (six months or more) compared with controls was 1.49 (95% CI 1.28 to 1.73; 31 RCTs, adjusted N = 20,097; I2 = 33%). Results were not sensitive to the exclusion of six studies where an incentive for cessation was offered at long-term follow up (result excluding those studies: RR 1.40, 95% CI 1.16 to 1.69; 25 RCTs; adjusted N = 17,058; I2 = 36%), suggesting the impact of incentives continues for at least some time after incentives cease.Although not always clearly reported, the total financial amount of incentives varied considerably between trials, from zero (self-deposits), to a range of between USD 45 and USD 1185. There was no clear direction of effect between trials offering low or high total value of incentives, nor those encouraging redeemable self-deposits.We included 10 studies of 2571 pregnant women. We judged two studies to be at low risk of bias, one at high risk of bias, and seven at unclear risk. When pooled, the nine trials with usable data (eight conducted in the USA and one in the UK), delivered an RR at longest follow-up (up to 24 weeks post-partum) of 2.38 (95% CI 1.54 to 3.69; N = 2273; I2 = 41%), in favour of incentives. AUTHORS' CONCLUSIONS: Overall there is high-certainty evidence that incentives improve smoking cessation rates at long-term follow-up in mixed population studies. The effectiveness of incentives appears to be sustained even when the last follow-up occurs after the withdrawal of incentives. There is also moderate-certainty evidence, limited by some concerns about risks of bias, that incentive schemes conducted among pregnant smokers improve smoking cessation rates, both at the end of pregnancy and post-partum. Current and future research might explore more precisely differences between trials offering low or high cash incentives and self-incentives (deposits), within a variety of smoking populations.

Competitions for smoking cessation.

BACKGROUND: Competitions might encourage people to undertake and/or reinforce behaviour change, including smoking cessation. Competitions involve individuals or groups having the opportunity to win a prize following successful cessation, either through direct competition or by entry into a lottery or raffle. OBJECTIVES: To determine whether competitions lead to higher long-term smoking quit rates. We also aimed to examine the impact on the population, the costs, and the unintended consequences of smoking cessation competitions. SEARCH METHODS: This review has merged two previous Cochrane reviews. Here we include studies testing competitions from the reviews 'Competitions and incentives for smoking cessation' and 'Quit & Win interventions for smoking cessation'. We updated the evidence by searching the Cochrane Tobacco Addiction Group Specialized Register in June 2018. SELECTION CRITERIA: We considered randomized controlled trials (RCTs), allocating individuals, workplaces, groups within workplaces, or communities to experimental or control conditions. We also considered controlled studies with baseline and post-intervention measures in which participants were assigned to interventions by the investigators. Participants were smokers, of any age and gender, in any setting. Eligible interventions were contests, competitions, lotteries, and raffles, to reward cessation and continuous abstinence in smoking cessation programmes. DATA COLLECTION AND ANALYSIS: For this update, data from new studies were extracted independently by two review authors. The primary outcome measure was abstinence from smoking at least six months from the start of the intervention. We performed meta-analyses to pool study effects where suitable data were available and where the effect of the competition component could be separated from that of other intervention components, and report other findings narratively. MAIN RESULTS: Twenty studies met our inclusion criteria. Five investigated performance-based reward, where groups of smokers competed against each other to win a prize (N = 915). The remaining 15 used performance-based eligibility, where cessation resulted in entry into a prize draw (N = 10,580). Five of these used Quit & Win contests (N = 4282), of which three were population-level interventions. Fourteen studies were RCTs, and the remainder quasi-randomized or controlled trials. Six had suitable abstinence data for a meta-analysis, which did not show evidence of effectiveness of performance-based eligibility interventions (risk ratio (RR) 1.16, 95% confidence interval (CI) 0.77 to 1.74, N = 3201, I2 = 57%). No trials that used performance-based rewards found a beneficial effect of the intervention on long-term quit rates.The three population-level Quit & Win studies found higher smoking cessation rates in the intervention group (4% to 16.9%) than the control group at long-term follow-up, but none were RCTs and all had important between-group differences in baseline characteristics. These studies suggested that fewer than one in 500 smokers would quit because of the contest.Reported unintended consequences in all sets of studies generally related to discrepancies between self-reported smoking status and biochemically-verified smoking status. More serious adverse events were not attributed to the competition intervention.Using the GRADE system we rated the overall quality of the evidence for smoking cessation as 'very low', because of the high and unclear risk of bias associated with the included studies, substantial clinical and methodological heterogeneity, and the limited population investigated. AUTHORS' CONCLUSIONS: At present, it is impossible to draw any firm conclusions about the effectiveness, or a lack of it, of smoking cessation competitions. This is due to a lack of well-designed comparative studies. Smoking cessation competitions have not been shown to enhance long-term cessation rates. The limited evidence suggesting that population-based Quit & Win contests at local and regional level might deliver quit rates above baseline community rates has not been tested adequately using rigorous study designs. It is also unclear whether the value or frequency of possible cash reward schedules influence the success of competitions. Future studies should be designed to compensate for the substantial biases in the current evidence base.

Statistical models for the deterioration of kidney function in a primary care population: A retrospective database analysis.

Background: Evidence for kidney function monitoring intervals in primary care is weak, and based mainly on expert opinion. In the absence of trials of monitoring strategies, an approach combining a model for the natural history of kidney function over time combined with a cost-effectiveness analysis offers the most feasible approach for comparing the effects of monitoring under a variety of policies. This study aimed to create a model for kidney disease progression using routinely collected measures of kidney function. Methods: This is an open cohort study of patients aged ≥18 years, registered at 643 UK general practices contributing to the Clinical Practice Research Datalink between 1 April 2005 and 31 March 2014. At study entry, no patients were kidney transplant donors or recipients, pregnant or on dialysis. Hidden Markov models for estimated glomerular filtration rate (eGFR) stage progression were fitted to four patient cohorts defined by baseline albuminuria stage; adjusted for sex, history of heart failure, cancer, hypertension and diabetes, annually updated for age. Results: Of 1,973,068 patients, 1,921,949 had no recorded urine albumin at baseline, 37,947 had normoalbuminuria (<3mg/mmol), 10,248 had microalbuminuria (3-30mg/mmol), and 2,924 had macroalbuminuria (>30mg/mmol). Estimated annual transition probabilities were 0.75-1.3%, 1.5-2.5%, 3.4-5.4% and 3.1-11.9% for each cohort, respectively. Misclassification of eGFR stage was estimated to occur in 12.1% (95%CI: 11.9-12.2%) to 14.7% (95%CI: 14.1-15.3%) of tests. Male gender, cancer, heart failure and age were independently associated with declining renal function, whereas the impact of raised blood pressure and glucose on renal function was entirely predicted by albuminuria. Conclusions: True kidney function deteriorates slowly over time, declining more sharply with elevated urine albumin, increasing age, heart failure, cancer and male gender. Consecutive eGFR measurements should be interpreted with caution as observed improvement or deterioration may be due to misclassification.

Practice variation in the use of tests in UK primary care: a retrospective analysis of 16 million tests performed over 3.3 million patient years in 2015/16.

BACKGROUND: The UK's National Health Service (NHS) is currently subject to unprecedented financial strain. The identification of unnecessary healthcare resource use has been suggested to reduce spending. However, there is little very research quantifying wasteful test use, despite the £3 billion annual expenditure. Geographical variation has been suggested as one metric in which to quantify inappropriate use. We set out to identify tests ordered from UK primary care that are subject to the greatest between-practice variation in their use. METHODS: We used data from 444 general practices within the Clinical Practice Research Datalink to calculate a coefficient of variation (CoV) for the ordering of 44 specific tests from UK general practices. The coefficient of variation was calculated after adjusting for differences between practice populations. We also determined the tests that had both a higher-than-average CoV and a higher-than-average rate of use. RESULTS: In total, 16,496,218 tests were ordered for 4,078,091 patients over 3,311,050 person-years from April 1, 2015, to March 31, 2016. The tests subject to the greatest variation were drug monitoring 158% (95%CI 153 to 163%), urine microalbumin (52% (95%CI 49.9 to 53.2%)), pelvic CT (51% (95%CI 50 to 53%)) and Pap smear (49% (95%CI 48 to 51%). Seven tests were classified as high variability and high rate (clotting, vitamin D, urine albumin, prostate-specific antigen (PSA), bone profile, urine MCS and C-reactive protein (CRP)). CONCLUSIONS: There are wide variations in the use of common tests, which is unlikely to be explained by clinical indications. Since £3 billion annually are spent on tests, this represents considerable variation in the use of resources and inefficient management in the NHS. Our results can be of value to policy makers, researchers, patients and clinicians as the NHS strives towards identifying overuse and underuse of tests.

The mapping of cancer incidence and mortality trends in the UK from 1980-2013 reveals a potential for overdiagnosis.

The incidence of cancer in the United Kingdom has increased significantly over the last four decades. The aim of this study was to examine trends in UK cancer incidence and mortality by cancer site and assess the potential for overdiagnosis. Using Cancer Research UK incidence and mortality data for the period (1971-2014) we estimated percentage change in incidence and mortality rates and the incidence-mortality ratio (IMR) for cancers in which incidence had increased >50%. Incidence and mortality trend plots were used to assess the potential for overdiagnosis. Incidence rates increased from 67% (uterine) to 375% (melanoma). Change in mortality rates ranged from -69% (cervical) to +239% (liver). The greatest divergences occurred in uterine (IMR = 132), prostate (IMR = 9.6), oral (IMR = 9.8) and thyroid cancer (IMR = 5.3). Only in liver cancer did mortality track incidence (IMR = 1.1). For four cancer sites; uterine, prostate, oral and thyroid, incidence and mortality trends are suggestive of overdiagnosis. Trends in melanoma and kidney cancer suggest potential overdiagnosis and an underlying increase in true risk, whereas for cervical and breast cancer, trends may also reflect improvements in treatments or earlier diagnosis. A more detailed analysis is required to fully understand these patterns.