IntroductionIn the UK, most people with lung cancer are diagnosed at a late stage when curative treatment is not possible. To aid earlier detection, the sociodemographic and early clinical features predictive of lung cancer need to be identified. Methods We studied 12 074 cases of lung cancer and 120 731 controls in a large general practice database. Logistic regression analyses were used to identify the socio-demographic and clinical features associated with cancer up to 2 years before diagnosis. A risk prediction model was developed using variables that were independently associated with lung cancer up to 4 months before diagnosis. The model performance was assessed in an independent dataset of 1 826 293 patients from the same database. Discrimination was assessed by means of a receiver operating characteristic (ROC) curve. Results Clinical and socio-demographic features that were independently associated with lung cancer were patients' age, sex, socioeconomic status and smoking history. From 4 to 12 months before diagnosis, the frequency of consultations and symptom records of cough, haemoptysis, dyspnoea, weight loss, lower respiratory tract infections, non-specific chest infections, chest pain, hoarseness, upper respiratory tract infections and chronic obstructive pulmonary disease were also independently predictive of lung cancer. On validation, the model performed well with an area under the ROC curve of 0.88. Conclusions This new model performed substantially better than the current National Institute for Health and Clinical Excellence referral guidelines and all comparable models. It has the potential to predict lung cancer cases sufficiently early to make detection at a curable stage more likely by allowing general practitioners to better risk stratify their patients. A clinical trial is needed to quantify the absolute benefits to patients and the cost effectiveness of this model in practice.

ObjectiveTo assess low-density lipoprotein cholesterol (LDL-C) response in patients after initiation of statins, and future risk of cardiovascular disease (CVD).MethodsProspective cohort study of 165 411 primary care patients, from the UK Clinical Practice Research Datalink, who were free of CVD before statin initiation, and had at least one pre-treatment LDL-C within 12 months before, and one post-treatment LDL-C within 24 months after, statin initiation. Based on current national guidelines, <40% reduction in baseline LDL-C within 24 months was classified as a sub-optimal statin response. Cox proportional regression and competing-risks survival regression models were used to determine adjusted hazard ratios (HRs) and sub-HRs for incident CVD outcomes for LDL-C response to statins.Results84 609 (51.2%) patients had a sub-optimal LDL-C response to initiated statin therapy within 24 months. During 1 077 299 person-years of follow-up (median follow-up 6.2 years), there were 22 798 CVD events (12 142 in sub-optimal responders and 10 656 in optimal responders). In sub-optimal responders, compared with optimal responders, the HR for incident CVD was 1.17 (95% CI 1.13 to 1.20) and 1.22 (95% CI 1.19 to 1.25) after adjusting for age and baseline untreated LDL-C. Considering competing risks resulted in lower but similar sub-HRs for both unadjusted (1.13, 95% CI 1.10 to 1.16) and adjusted (1.19, 95% CI 1.16 to 1.23) cumulative incidence function of CVD.ConclusionsOptimal lowering of LDL-C is not achieved within 2 years in over half of patients in the general population initiated on statin therapy, and these patients will experience significantly increased risk of future CVD.

A diagnosis of COPD is strongly associated with a diagnosis of lung cancer, however, this association is largely explained by smoking habit, strongly dependent on the timing of COPD diagnosis, and not specific to COPD. It seems unlikely, therefore, that COPD is an independent risk factor for lung cancer.

BackgroundThe UK has poor lung cancer survival rates and high early mortality, compared to other countries. We aimed to identify factors associated with early death, and features of primary care that might contribute to late diagnosis.MethodsAll cases of lung cancer diagnosed between 2000 and 2013 were extracted from The Health Improvement Network database. Patients who died within 90 days of diagnosis were compared with those who survived longer. Standardised chest X-ray (CXR) and lung cancer rates were calculated for each practice.ResultsOf 20 142 people with lung cancer, those who died early consulted with primary care more frequently prediagnosis. Individual factors associated with early death were male sex (OR 1.17; 95% CI 1.10 to 1.24), current smoking (OR 1.43; 95% CI 1.28 to 1.61), increasing age (OR 1.80; 95% CI 1.62 to 1.99 for age ≥80 years compared to 65–69 years), social deprivation (OR 1.16; 95% CI 1.04 to 1.30 for Townsend quintile 5 vs 1) and rural versus urban residence (OR 1.22; 95% CI 1.06 to 1.41). CXR rates varied widely, and the odds of early death were highest in the practices which requested more CXRs. Lung cancer incidence at practice level did not affect early deaths.ConclusionsPatients who die early from lung cancer are interacting with primary care prediagnosis, suggesting potentially missed opportunities to identify them earlier. A general increase in CXR requests may not improve survival; rather, a more timely and appropriate targeting of this investigation using risk assessment tools needs further assessment.