title: Prediction of coronary heart disease using risk factor categories. Individualised multifactorial lifestyle intervention trial for high-risk cardiovascular patients in primary care. Predicting risk of type 2 diabetes in England and Wales: prospective derivation and validation of QDScore Effect on smoking quit rate of telling patients their lung age: the Step2quit randomised controlled trial One-year follow-up of a therapeutic lifestyle intervention targeting cardiovascular disease risk Multiple risk factor intervention trial. Risk factor changes and mortality results. Multiple Risk Factor Intervention Trial Research Group.
abstract: BACKGROUND The objective of this study was to examine the association of Joint National Committee ( JNC-V ) blood pressure and National Cholesterol Education Program ( NCEP ) cholesterol categories with coronary heart disease ( CHD ) risk , to incorporate them into coronary prediction algorithms , and to compare the discrimination properties of this approach with other noncategorical prediction functions . METHODS AND RESULTS This work was design ed as a prospect i ve , single-center study in the setting of a community-based cohort . The patients were 2489 men and 2856 women 30 to 74 years old at baseline with 12 years of follow-up . During the 12 years of follow-up , a total of 383 men and 227 women developed  CHD , which was significantly associated with categories of blood pressure , total cholesterol , LDL cholesterol , and HDL cholesterol ( all P<.001 ) . Sex-specific prediction equations were formulated to predict CHD risk according to age , diabetes , smoking , JNC-V blood pressure categories , and NCEP total cholesterol and LDL cholesterol categories . The accuracy of this categorical approach was found to be comparable to CHD prediction when the continuous variables themselves were used . After adjustment for other factors , approximately 28 % of CHD events in men and 29 % in women were attributable to blood pressure levels that exceeded high normal ( > or = 130/85 ) . The corresponding multivariable-adjusted attributable risk percent associated with elevated total cholesterol ( > or = 200 mg/dL ) was 27 % in men and 34 % in women . CONCLUSIONS Recommended guidelines of blood pressure , total cholesterol , and LDL cholesterol effectively predict CHD risk in a middle-aged white population sample . A simple coronary disease prediction algorithm was developed using categorical variables , which allows physicians to predict multivariate CHD risk in patients without overt CHD BACKGROUND The multiprofessional teams in Finnish health centres are well placed to carry out interventions aim ed at the prevention of cardiovascular diseases . AIM To evaluate the effectiveness of an individually tailored multifactorial lifestyle intervention in primary care for individuals at high risk for cardiovascular disease . DESIGN OF STUDY A r and omised controlled trial was conducted over 24 months with interim assessment s at six and 12 months . SETTING A health centre in Finl and with a patient population of 11,000 . METHOD One hundred and fifty adults aged 18 to 65 years old with existing cardiovascular disease or multiple risk factors were r and omised to active multiprofessional risk factor intervention or to st and ard care . The main outcome measure was a change in cardiovascular risk-factor score . Secondary outcomes were changes in blood pressure , weight , body-mass index , serum cholesterol , blood glucose , smoking cessation , and exercise habits . RESULTS The cardiovascular risk score decreased by 28 % in the intervention group ( 23 % in the control group ) , body weight decreased by 3.7 % ( 2 % ) and total cholesterol decreased by 10.8 % ( 6.5 % ) , while time engaged in exercise increased by 39 % ( 43 % ) . Differences were not significant . CONCLUSIONS Cardiovascular risk levels of high-risk individuals decreased in both intervention and control groups . Primary care prevention should be targeted to high-risk persons . Long-term follow-up studies are needed Objective To develop and vali date a new diabetes risk algorithm ( the QDScore ) for estimating 10 year risk of acquiring diagnosed type 2 diabetes  over a 10 year time period in an ethnically and socioeconomically diverse population . Design Prospect i ve open cohort study using routinely collected data from 355 general practice s in Engl and and Wales to develop the score and from 176 separate practice s to vali date the score . Participants 2 540 753 patients aged 25 - 79 in the derivation cohort , who contributed 16 436 135 person years of observation and of whom 78 081 had an incident diagnosis of type 2 diabetes ; 1 232 832 patients ( 7 643 037 person years ) in the validation cohort , with 37 535 incident cases of type 2 diabetes . Outcome measures A Cox proportional hazards model was used to estimate effects of risk factors in the derivation cohort and to derive a risk equation in men and women . The predictive variables examined and included in the final model were self assigned ethnicity , age , sex , body mass index , smoking status , family history of diabetes , Townsend deprivation score , treated hypertension , cardiovascular disease , and current use of corticosteroids ; the outcome of interest was incident diabetes recorded in general practice records . Measures of calibration and discrimination were calculated in the validation cohort . Results A fourfold to fivefold variation in risk of type 2 diabetes existed between different ethnic groups . Compared with the white reference group , the adjusted hazard ratio was 4.07 ( 95 % confidence interval 3.24 to 5.11 ) for Bangladeshi women , 4.53 ( 3.67 to 5.59 ) for Bangladeshi men , 2.15 ( 1.84 to 2.52 ) for Pakistani women , and 2.54 ( 2.20 to 2.93 ) for Pakistani men . Pakistani and Bangladeshi men had significantly higher hazard ratios than Indian men . Black African men and Chinese women had an increased risk compared with the corresponding white reference group . In the validation data set , the model explained 51.53 % ( 95 % confidence interval 50.90 to 52.16 ) of the variation in women and 48.16 % ( 47.52 to 48.80 ) of that in men . The risk score showed good discrimination , with a D statistic of 2.11 ( 95 % confidence interval 2.08 to 2.14 ) in women and 1.97 ( 1.95 to 2.00 ) in men . The model was well calibrated . Conclusions The QDScore is the first risk prediction algorithm to estimate the 10 year risk of diabetes on the basis of a prospect i ve cohort study and including both social deprivation and ethnicity . The algorithm does not need laboratory tests and can be used in clinical setting s and also by the public through a simple web calculator ( www.qdscore.org ) Objective To evaluate the impact of telling patients their estimated spirometric lung age as an incentive to quit smoking . Design R and omised controlled trial . Setting Five general practice s in Hertfordshire , Engl and . Participants 561 current smokers aged over 35 . Intervention All participants were offered spirometric assessment of lung function . Participants in intervention group received their results in terms of  “  lung age ” ( the age of the average healthy individual who would perform similar to them on spirometry ) . Those in the control group received a raw figure for forced expiratory volume at one second ( FEV1 ) . Both groups were advised to quit and offered referral to local NHS smoking cessation services . Main outcome measures The primary outcome measure was verified cessation of smoking by salivary cotinine testing 12 months after recruitment . Secondary outcomes were reported changes in daily consumption of cigarettes and identification of new diagnoses of chronic obstructive lung disease . Results Follow-up was 89 % . Independently verified quit rates at 12 months in the intervention and control groups , respectively , were 13.6 % and 6.4 % ( difference 7.2 % , P=0.005 , 95 % confidence interval 2.2 % to 12.1 % ; number needed to treat 14 ) . People with worse spirometric lung age were no more likely to have quit than those with normal lung age in either group . Cost per successful quitter was estimated at £ 280 ( € 366 , $ 556 ) . A new diagnosis of obstructive lung disease was made in 17 % in the intervention group and 14 % in the control group ; a total of 16 % ( 89/561 ) of participants . Conclusion Telling smokers their lung age significantly improves the likelihood of them quitting smoking , but the mechanism by which this intervention achieves its effect is unclear . Trial registration National Research Register N0096173751 Background : In this study , we tested the efficacy of a low-intensity lifestyle intervention aim ed at reducing the risk of cardiovascular disease among mid-life individuals . Methods : We conducted a r and omized controlled trial in which participants were r and omly assigned either to receive a health report card with counselling ( from a Telehealth nurse ) on smoking , exercise , nutrition and stress or to receive usual care . The patients were divided into 2 groups on the basis of risk : the primary prevention group , with a Framingham risk score of 10 % or higher ( intervention , n = 157 ; control , n = 158 ) , and the secondary prevention group , who had a diagnosis of coronary artery disease ( intervention , n = 153 ; control , n = 143 ) . The primary outcome was a change in the Framingham global risk score between baseline and 1-year follow-up . Data were analyzed separately for the 2 prevention groups using an intention-to-treat analysis controlling for covariates . Results : Within the primary prevention group , there were statistically significant changes for the treatment group relative to the controls , from baseline to year 1 , in Framingham score ( intervention , –3.10 [ 95 % confidence interval ( CI ) –3.98 to –2.22 ] ; control , –1.30 [ 95 % CI –2.18 to –0.42 ] ; p < 0.01 ) and scores for total cholesterol ( intervention , –0.41 [ 95 % CI –0.59 to –0.23 ] ; control , –0.14 [ 95 % CI –0.32 to 0.04 ] ; p < 0.05 ) , systolic blood pressure ( intervention , –7.49 [ 95 % CI –9.97 to –5.01 ] ; control , –3.58 [ 95 % CI –6.08 to –1.08 ] ; p < 0.05 ) , nutrition level ( intervention , 0.30 [ 95 % CI 0.13 to 0.47 ] ; control , –0.05 [ 95 % CI –0.22 to 0.12 ] ; p < 0.01 ) , and health confidence ( intervention , 0.20 [ 95 % CI 0.09 to 0.31 ] ; control , 0.04 [ 95 % CI –0.07 to 0.15 ] ; p < 0.05 ) , with adjustment for covariates . No significant changes in outcome variables were found for the secondary prevention group . Interpretation : We found evidence for the efficacy of an intervention addressing multiple risk factors for primary prevention at 1 year using Framingham risk score report cards and telephone counselling . ( Requirement for clinical trial registration waived [ enrolment completed before requirement became applicable ] . The Multiple Risk Factor Intervention Trial was a r and omized primary prevention trial to test the effect of a multifactor intervention program on mortality from coronary heart disease ( CHD )  in 12,866 high-risk men aged 35 to 57 years . Men were r and omly assigned either to a special intervention ( SI ) program consisting of stepped-care treatment for hypertension , counseling for cigarette smoking , and dietary advice for lowering blood cholesterol levels , or to their usual sources of health care in the community ( UC ) . Over an average follow-up period of seven years , risk factor levels declined in both groups , but to a greater degree for the SI men . Mortality from CHD was 17.9 deaths per 1,000 in the SI group and 19.3 per 1,000 in the UC group , a statistically nonsignificant difference of 7.1 % ( 90 % confidence interval , -15 % to 25 ) . Total mortality rates were 41.2 per 1,000 ( SI ) and 40.4 per 1,000 ( UC ) . Three possible explanations for these findings are considered : ( 1 ) the overall intervention program , under these circumstances , does not affect CHD mortality ; ( 2 ) the intervention used does affect CHD mortality , but the benefit was not observed in this trial of seven years ' average duration , with lower-than-expected mortality and with considerable risk factor change in the UC group ; and ( 3 ) measures to reduce cigarette smoking and to lower blood cholesterol levels may have reduced CHD mortality within subgroups of the SI cohort , with a possibly unfavorable response to antihypertensive drug therapy in certain but not all hypertensive subjects . This last possibility was considered most likely , needs further investigation , and lends support to some preventive measures while requiring re assessment of others
target: Conclusions This review demonstrates the potential for multifactorial interventions aim ed at individuals selected by CVD risk scores for lowering CVD risk and mortality .
  However , the majority of studies in this area do not provide an intensity of intervention which is sufficient in significantly reducing CVD mortality or vali date d CVD risk
background: Objectives The high prevalence of cardiovascular disease ( CVD ) and the increased cost of treatment have prompted strategies for the primary prevention of CVD in the UK to move towards the use of vali date d CVD risk scores to identify individuals at the highest risk .
  There are no review s evaluating the effectiveness of this strategy as a means of reducing CVD risk or mortality .
  This review summarizes current evidence for and against the use of vali date d CVD risk scores for the primary prevention of CVD .