Development and validation of QMortality risk prediction algorithm to estimate short term risk of death and assess frailty: cohort study

Objectives To derive and validate a risk prediction equation to estimate the short term risk of death, and to develop a classification method for frailty based on risk of death and risk of unplanned hospital admission.

Design Prospective open cohort study.

Participants Routinely collected data from 1436 general practices contributing data to QResearch in England between 2012 and 2016. 1079 practices were used to develop the scores and a separate set of 357 practices to validate the scores. 1.47 million patients aged 65-100 years were in the derivation cohort and 0.50 million patients in the validation cohort.

Methods Cox proportional hazards models in the derivation cohort were used to derive separate risk equations in men and women for evaluation of the risk of death at one year. Risk factors considered were age, sex, ethnicity, deprivation, smoking status, alcohol intake, body mass index, medical conditions, specific drugs, social factors, and results of recent investigations. Measures of calibration and discrimination were determined in the validation cohort for men and women separately and for each age and ethnic group. The new mortality equation was used in conjunction with the existing QAdmissions equation (which predicts risk of unplanned hospital admission) to classify patients into frailty groups.

Main outcome measure The primary outcome was all cause mortality.

Results During follow-up 180 132 deaths were identified in the derivation cohort arising from 4.39 million person years of observation. The final model included terms for age, body mass index, Townsend score, ethnic group, smoking status, alcohol intake, unplanned hospital admissions in the past 12 months, atrial fibrillation, antipsychotics, cancer, asthma or chronic obstructive pulmonary disease, living in a care home, congestive heart failure, corticosteroids, cardiovascular disease, dementia, epilepsy, learning disability, leg ulcer, chronic liver disease or pancreatitis, Parkinson’s disease, poor mobility, rheumatoid arthritis, chronic kidney disease, type 1 diabetes, type 2 diabetes, venous thromboembolism, anaemia, abnormal liver function test result, high platelet count, visited doctor in the past year with either appetite loss, unexpected weight loss, or breathlessness. The model had good calibration and high levels of explained variation and discrimination. In women, the equation explained 55.6% of the variation in time to death (R2), and had very good discrimination—the D statistic was 2.29, and Harrell’s C statistic value was 0.85. The corresponding values for men were 53.1%, 2.18, and 0.84. By combining predicted risks of mortality and unplanned hospital admissions, 2.7% of patients (n=13 665) were classified as severely frail, 9.4% (n=46 770) as moderately frail, 43.1% (n=215 253) as mildly frail, and 44.8% (n=223 790) as fit.

Conclusions We have developed new equations to predict the short term risk of death in men and women aged 65 or more, taking account of demographic, social, and clinical variables. The equations had good performance on a separate validation cohort. The QMortality equations can be used in conjunction with the QAdmissions equations, to classify patients into four frailty groups (known as QFrailty categories) to enable patients to be identified for further assessment or interventions.

Reference: BMJ 2017;358:j4208

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Quadrivalent HPV Vaccination and the Risk of Adverse Pregnancy Outcomes

BACKGROUND

The quadrivalent human papillomavirus (HPV) vaccine is recommended for all girls and women 9 to 26 years of age. Some women will have inadvertent exposure to vaccination during early pregnancy, but few data exist regarding the safety of the quadrivalent HPV vaccine in this context.

METHODS

We assessed a cohort that included all the women in Denmark who had a pregnancy ending between October 1, 2006, and November 30, 2013. Using nationwide registers, we linked information on vaccination, adverse pregnancy outcomes, and potential confounders among women in the cohort. Women who had vaccine exposure during the prespecified time windows were matched for propensity score in a 1:4 ratio with women who did not have vaccine exposure during the same time windows. Outcomes included spontaneous abortion, stillbirth, major birth defect, small size for gestational age, low birth weight, and preterm birth.

RESULTS

In matched analyses, exposure to the quadrivalent HPV vaccine was not associated with significantly higher risks than no exposure for major birth defect (65 cases among 1665 exposed pregnancies and 220 cases among 6660 unexposed pregnancies; prevalence odds ratio, 1.19; 95% confidence interval [CI], 0.90 to 1.58), spontaneous abortion (20 cases among 463 exposed pregnancies and 131 cases among 1852 unexposed pregnancies; hazard ratio, 0.71; 95% CI, 0.45 to 1.14), preterm birth (116 cases among 1774 exposed pregnancies and 407 cases among 7096 unexposed pregnancies; prevalence odds ratio, 1.15; 95% CI, 0.93 to 1.42), low birth weight (76 cases among 1768 exposed pregnancies and 277 cases among 7072 unexposed pregnancies; prevalence odds ratio, 1.10; 95% CI, 0.85 to 1.43), small size for gestational age (171 cases among 1768 exposed pregnancies and 783 cases among 7072 unexposed pregnancies; prevalence odds ratio, 0.86; 95% CI, 0.72 to 1.02), or stillbirth (2 cases among 501 exposed pregnancies and 4 cases among 2004 unexposed pregnancies; hazard ratio, 2.43; 95% CI, 0.45 to 13.21).

CONCLUSIONS

Quadrivalent HPV vaccination during pregnancy was not associated with a significantly higher risk of adverse pregnancy outcomes than no such exposure. (Funded by the Novo Nordisk Foundation and the Danish Medical Research Council.)

Non-steroidal anti-inflammatory drugs and risk of heart failure in four European countries: nested case-control study

Objectives To investigate the cardiovascular safety of non-steroidal anti-inflammatory drugs (NSAIDs) and estimate the risk of hospital admission for heart failure with use of individual NSAIDs.

Design Nested case-control study.

Setting Five population based healthcare databases from four European countries (the Netherlands, Italy, Germany, and the United Kingdom).

Participants Adult individuals (age ≥18 years) who started NSAID treatment in 2000-10. Overall, 92 163 hospital admissions for heart failure were identified and matched with 8 246 403 controls (matched via risk set sampling according to age, sex, year of cohort entry).

Main outcome measure Association between risk of hospital admission for heart failure and use of 27 individual NSAIDs, including 23 traditional NSAIDs and four selective COX 2 inhibitors. Associations were assessed by multivariable conditional logistic regression models. The dose-response relation between NSAID use and heart failure risk was also assessed.

Results Current use of any NSAID (use in preceding 14 days) was found to be associated with a 19% increase of risk of hospital admission for heart failure (adjusted odds ratio 1.19; 95% confidence interval 1.17 to 1.22), compared with past use of any NSAIDs (use >183 days in the past). Risk of admission for heart failure increased for seven traditional NSAIDs (diclofenac, ibuprofen, indomethacin, ketorolac, naproxen, nimesulide, and piroxicam) and two COX 2 inhibitors (etoricoxib and rofecoxib). Odds ratios ranged from 1.16 (95% confidence interval 1.07 to 1.27) for naproxen to 1.83 (1.66 to 2.02) for ketorolac. Risk of heart failure doubled for diclofenac, etoricoxib, indomethacin, piroxicam, and rofecoxib used at very high doses (≥2 defined daily dose equivalents), although some confidence intervals were wide. Even medium doses (0.9-1.2 defined daily dose equivalents) of indomethacin and etoricoxib were associated with increased risk. There was no evidence that celecoxib increased the risk of admission for heart failure at commonly used doses.

Conclusions The risk of hospital admission for heart failure associated with current use of NSAIDs appears to vary between individual NSAIDs, and this effect is dose dependent. This risk is associated with the use of a large number of individual NSAIDs reported by this study, which could help to inform both clinicians and health regulators.

BMJ 2016;354:i4857

Atrial fibrillation and risks of cardiovascular disease, renal disease, and death: systematic review and meta-analysis

Objective To quantify the association between atrial fibrillation and cardiovascular disease, renal disease, and death.

Design Systematic review and meta-analysis.

Data sources Medline and Embase.

Eligibility criteria Cohort studies examining the association between atrial fibrillation and cardiovascular disease, renal disease, and death. Two reviewers independently extracted study characteristics and the relative risk of outcomes associated with atrial fibrillation: specifically, all cause mortality, cardiovascular mortality, major cardiovascular events, any stroke, ischaemic stroke, haemorrhagic stroke, ischaemic heart disease, sudden cardiac death, congestive heart failure, chronic kidney disease, and peripheral arterial disease. Estimates were pooled with inverse variance weighted random effects meta-analysis.

Results 104 eligible cohort studies involving 9 686 513 participants (587 867 with atrial fibrillation) were identified. Atrial fibrillation was associated with an increased risk of all cause mortality (relative risk 1.46, 95% confidence interval 1.39 to 1.54), cardiovascular mortality (2.03, 1.79 to 2.30), major cardiovascular events (1.96, 1.53 to 2.51), stroke (2.42, 2.17 to 2.71), ischaemic stroke (2.33, 1.84 to 2.94), ischaemic heart disease (1.61, 1.38 to 1.87), sudden cardiac death (1.88, 1.36 to 2.60), heart failure (4.99, 3.04 to 8.22), chronic kidney disease (1.64, 1.41 to 1.91), and peripheral arterial disease (1.31, 1.19 to 1.45) but not haemorrhagic stroke (2.00, 0.67 to 5.96). Among the outcomes examined, the highest absolute risk increase was for heart failure. Associations between atrial fibrillation and included outcomes were broadly consistent across subgroups and in sensitivity analyses.

Conclusions Atrial fibrillation is associated with an increased risk of death and an increased risk of cardiovascular and renal disease. Interventions aimed at reducing outcomes beyond stroke are warranted in patients with atrial fibrillation.

BMJ 2016;354:i4482

External validation of prognostic models to predict risk of gestational diabetes mellitus in one Dutch cohort: prospective multicentre cohort study

Objective To perform an external validation and direct comparison of published prognostic models for early prediction of the risk of gestational diabetes mellitus, including predictors applicable in the first trimester of pregnancy.

Design External validation of all published prognostic models in large scale, prospective, multicentre cohort study.

Setting 31 independent midwifery practices and six hospitals in the Netherlands.

Participants Women recruited in their first trimester (<14 weeks) of pregnancy between December 2012 and January 2014, at their initial prenatal visit. Women with pre-existing diabetes mellitus of any type were excluded.

Main outcome measures Discrimination of the prognostic models was assessed by the C statistic, and calibration assessed by calibration plots.

Results 3723 women were included for analysis, of whom 181 (4.9%) developed gestational diabetes mellitus in pregnancy. 12 prognostic models for the disorder could be validated in the cohort. C statistics ranged from 0.67 to 0.78. Calibration plots showed that eight of the 12 models were well calibrated. The four models with the highest C statistics included almost all of the following predictors: maternal age, maternal body mass index, history of gestational diabetes mellitus, ethnicity, and family history of diabetes. Prognostic models had a similar performance in a subgroup of nulliparous women only. Decision curve analysis showed that the use of these four models always had a positive net benefit.

Conclusions In this external validation study, most of the published prognostic models for gestational diabetes mellitus show acceptable discrimination and calibration. The four models with the highest discriminative abilities in this study cohort, which also perform well in a subgroup of nulliparous women, are easy models to apply in clinical practice and therefore deserve further evaluation regarding their clinical impact.

BMJ 2016;354:i4338

Low dose oestrogen combined oral contraception and risk of pulmonary embolism, stroke, and myocardial infarction in five million French women: cohort study

Objective To assess the risk of pulmonary embolism, ischaemic stroke, and myocardial infarction associated with combined oral contraceptives according to dose of oestrogen (ethinylestradiol) and progestogen.

Design Observational cohort study.

Setting Data from the French national health insurance database linked with data from the French national hospital discharge database.

Participants 4 945 088 women aged 15-49 years, living in France, with at least one reimbursement for oral contraceptives and no previous hospital admission for cancer, pulmonary embolism, ischaemic stroke, or myocardial infarction, between July 2010 and September 2012.

Main outcome measures Relative and absolute risks of first pulmonary embolism, ischaemic stroke, and myocardial infarction.

Results The cohort generated 5 443 916 women years of oral contraceptive use, and 3253 events were observed: 1800 pulmonary embolisms (33 per 100 000 women years), 1046 ischaemic strokes (19 per 100 000 women years), and 407 myocardial infarctions (7 per 100 000 women years). After adjustment for progestogen and risk factors, the relative risks for women using low dose oestrogen (20 µg v 30-40 µg) were 0.75 (95% confidence interval 0.67 to 0.85) for pulmonary embolism, 0.82 (0.70 to 0.96) for ischaemic stroke, and 0.56 (0.39 to 0.79) for myocardial infarction. After adjustment for oestrogen dose and risk factors, desogestrel and gestodene were associated with statistically significantly higher relative risks for pulmonary embolism (2.16, 1.93 to 2.41 and 1.63, 1.34 to 1.97, respectively) compared with levonorgestrel. Levonorgestrel combined with 20 µg oestrogen was associated with a statistically significantly lower risk than levonorgestrel with 30-40 µg oestrogen for each of the three serious adverse events.

Conclusions For the same dose of oestrogen, desogestrel and gestodene were associated with statistically significantly higher risks of pulmonary embolism but not arterial thromboembolism compared with levonorgestrel. For the same type of progestogen, an oestrogen dose of 20 µg versus 30-40 µg was associated with lower risks of pulmonary embolism, ischaemic stroke, and myocardial infarction.

BMJ 2016;353:i2002

Prediction models for cardiovascular disease risk in the general population: systematic review

Objective To provide an overview of prediction models for risk of cardiovascular disease (CVD) in the general population.

Design Systematic review.

Data sources Medline and Embase until June 2013.

Eligibility criteria for study selection Studies describing the development or external validation of a multivariable model for predicting CVD risk in the general population.

Results 9965 references were screened, of which 212 articles were included in the review, describing the development of 363 prediction models and 473 external validations. Most models were developed in Europe (n=167, 46%), predicted risk of fatal or non-fatal coronary heart disease (n=118, 33%) over a 10 year period (n=209, 58%). The most common predictors were smoking (n=325, 90%) and age (n=321, 88%), and most models were sex specific (n=250, 69%). Substantial heterogeneity in predictor and outcome definitions was observed between models, and important clinical and methodological information were often missing. The prediction horizon was not specified for 49 models (13%), and for 92 (25%) crucial information was missing to enable the model to be used for individual risk prediction. Only 132 developed models (36%) were externally validated and only 70 (19%) by independent investigators. Model performance was heterogeneous and measures such as discrimination and calibration were reported for only 65% and 58% of the external validations, respectively.

Conclusions There is an excess of models predicting incident CVD in the general population. The usefulness of most of the models remains unclear owing to methodological shortcomings, incomplete presentation, and lack of external validation and model impact studies. Rather than developing yet another similar CVD risk prediction model, in this era of large datasets, future research should focus on externally validating and comparing head-to-head promising CVD risk models that already exist, on tailoring or even combining these models to local settings, and investigating whether these models can be extended by addition of new predictors.

BMJ 2016;353:i2416