Objectives: To estimate data loss and bias in studies of Clinical Practice Research Datalink (CPRD) data that restrict analyses to Read codes, omitting anything recorded as text. Design: Matched case–control study. Setting: Patients contributing data to the CPRD. Participants: 4915 bladder and 3635 pancreatic, cancer cases diagnosed between 1 January 2000 and 31 December 2009, matched on age, sex and general practitioner practice to up to 5 controls (bladder: n=21 718; pancreas: n=16 459). The analysis period was the year before cancer diagnosis. Primary and secondary outcome measures: Frequency of haematuria, jaundice and abdominal pain, grouped by recording style: Read code or text-only (ie, hidden text). The association between recording style and case–control status (χ ² test). For each feature, the odds ratio (OR; conditional logistic regression) and positive predictive value (PPV; Bayes’ theorem) for cancer, before and after addition of hidden text records. Results: Of the 20 958 total records of the features, 7951 (38%) were recorded in hidden text. Hidden text recording was more strongly associated with controls than with cases for haematuria (140/336=42% vs 556/3147=18%) in bladder cancer (χ ² test, p<0.001), and for jaundice (21/31=67% vs 463/1565=30%, p<0.0001) and abdominal pain (323/1126=29% vs 397/1789=22%, p<0.001) in pancreatic cancer. Adding hidden text records corrected PPVs of haematuria for bladder cancer from 4.0% (95% CI 3.5% to 4.6%) to 2.9% (2.6% to 3.2%), and of jaundice for pancreatic cancer from 12.8% (7.3% to 21.6%) to 6.3% (4.5% to 8.7%). Adding hidden text records did not alter the PPV of abdominal pain for bladder (codes: 0.14%, 0.13% to 0.16% vs codes plus hidden text: 0.14%, 0.13% to 0.15%) or pancreatic (0.23%, 0.21% to 0.25% vs 0.21%, 0.20% to 0.22%) cancer. Conclusions: Omission of text records from CPRD studies introduces bias that inflates outcome measures for recognised alarm symptoms. This potentially reinforces clinicians’ views of the known importance of these symptoms, marginalising the significance of ‘low-risk but not no-risk’ symptoms.

Objective Analysis of routinely collected electronic health record (EHR) data from primary care is reliant on the creation of codelists to define clinical features of interest. To improve scientific rigour, transparency and replicability, we describe and demonstrate a standardised reproducible methodology for clinical codelist development. Design We describe a three-stage process for developing clinical codelists. First, the clear definition a priori of the clinical feature of interest using reliable clinical resources. Second, development of a list of potential codes using statistical software to comprehensively search all available codes. Third, a modified Delphi process to reach consensus between primary care practitioners on the most relevant codes, including the generation of an ‘uncertainty’ variable to allow sensitivity analysis. Setting These methods are illustrated by developing a codelist for shortness of breath in a primary care EHR sample, including modifiable syntax for commonly used statistical software. Participants The codelist was used to estimate the frequency of shortness of breath in a cohort of 28 216 patients aged over 18 years who received an incident diagnosis of lung cancer between 1 January 2000 and 30 November 2016 in the Clinical Practice Research Datalink (CPRD). Results Of 78 candidate codes, 29 were excluded as inappropriate. Complete agreement was reached for 44 (90%) of the remaining codes, with partial disagreement over 5 (10%). 13 091 episodes of shortness of breath were identified in the cohort of 28 216 patients. Sensitivity analysis demonstrates that codes with the greatest uncertainty tend to be rarely used in clinical practice. Conclusions Although initially time consuming, using a rigorous and reproducible method for codelist generation ‘future-proofs’ findings and an auditable, modifiable syntax for codelist generation enables sharing and replication of EHR studies. Published codelists should be badged by quality and report the methods of codelist generation including: definitions and justifications associated with each codelist; the syntax or search method; the number of candidate codes identified; and the categorisation of codes after Delphi review.

1. Time courses for the uptake of L-lactate, D-lactate and pyruvate into isolated cardiac ventricular myocytes from guinea pig were determined at 11 degrees C or 0 degrees C (for pyruvate) in a citrate-based buffer by using a silicone-oil-filtration technique. These conditions enabled initial rates of transport to be measured without interference from metabolism of the substrates. 2. At a concentration of 0.5 mM, transport of all these substrates was inhibited by approx. 90% by 5 mM-alpha-cyano-4-hydroxycinnamate; at 10 mM-L-lactate a considerable portion of transport could not be inhibited. 3. Initial rates of L-lactate and pyruvate uptake in the presence of 5 mM-alpha-cyano-4-hydroxycinnamate were linearly related to the concentration of the monocarboxylate and probably represented diffusion of the free acid. The inhibitor-sensitive component of uptake obeyed Michaelis-Menten kinetics, with Km values for L-lactate and pyruvate of 2.3 and 0.066 mM respectively. 4. Pyruvate and D-lactate inhibited the transport of L-lactate, with Ki values (competitive) of 0.077 and 6.6 mM respectively; the Ki for pyruvate was very similar to its Km for transport. The Ki for alpha-cyano-4-hydroxycinnamate as a non-competitive inhibitor was 0.042 mM. 5. These results indicate that L-lactate, D-lactate and pyruvate share a common carrier in guinea-pig cardiac myocytes; the low stereoselectivity for L-lactate over D-lactate and the high affinity for pyruvate distinguish it from the carrier in erythrocytes and hepatocytes. The metabolic roles for this novel carrier in heart are discussed.

Pre-existing non-cancer conditions may complicate and delay colorectal cancer diagnosis. Incident cases (aged ⩾40 years, 2007-2009) with colorectal cancer were identified in the Clinical Practice Research Datalink, UK. Diagnostic interval was defined as time from first symptomatic presentation of colorectal cancer to diagnosis. Comorbid conditions were classified as 'competing demands' (unrelated to colorectal cancer) or 'alternative explanations' (sharing symptoms with colorectal cancer). The association between diagnostic interval (log-transformed) and age, gender, consultation rate and number of comorbid conditions was investigated using linear regressions, reported using geometric means. Out of the 4512 patients included, 72.9% had ⩾1 competing demand and 31.3% had ⩾1 alternative explanation. In the regression model, the numbers of both types of comorbid conditions were independently associated with longer diagnostic interval: a single competing demand delayed diagnosis by 10 days, and four or more by 32 days; and a single alternative explanation by 9 days. For individual conditions, the longest delay was observed for inflammatory bowel disease (26 days; 95% CI 14-39). The burden and nature of comorbidity is associated with delayed diagnosis in colorectal cancer, particularly in patients aged ⩾80 years. Effective clinical strategies are needed for shortening diagnostic interval in patients with comorbidity.

Background: Decision-support tools quantify the risk of undiagnosed cancer in symptomatic patients, and may help GPs when making referrals.Aim: To quantify the availability and use of cancer decision-support tools (QCancer^® and risk assessment tools) and to explore the association between tool availability and 2-week-wait (2WW) referrals for suspected cancer.Design and setting: A cross-sectional postal survey in UK primary care.Methods: Out of 975 UK randomly selected general practices, 4600 GPs and registrars were invited to participate. Outcome measures included the proportions of UK general practices where cancer decision-support tools are available and at least one GP uses the tool. Weighted least-squares linear regression with robust errors tested the association between tool availability and number of 2WW referrals, adjusting for practice size, sex, age, and Index of Multiple Deprivation.Results: In total, 476 GPs in 227 practices responded (response rates: practitioner, 10.3%; practice, 23.3%). At the practice level, 83/227 (36.6%, 95% confidence interval [CI] = 30.3 to 43.1) practices had at least one GP or registrar with access to cancer decision-support tools. Tools were available and likely to be used in 38/227 (16.7%, 95% CI = 12.1 to 22.2) practices. In subgroup analyses of 172 English practices, there was no difference in mean 2WW referral rate between practices with tools and those without (mean adjusted difference in referrals per 100 000: 3.1, 95% CI = −5.5 to 11.7).Conclusion: This is the first survey of cancer decision-support tool availability and use. It suggests that the tools are an underused resource in the UK. Given the cost of cancer investigation, a randomised controlled trial of such clinical decision-support aids would be appropriate.

Background: UK Asian and Black ethnic groups have poorer outcomes for some cancers and are less likely to report a positive care experience than their White counterparts. This study investigated ethnic differences in the route to diagnosis (RTD) to identify areas in patients' cancer journeys where inequalities lie, and targeted intervention might have optimum impact. Methods: We analysed data of 243,825 patients with 10 cancers (2006–2016) from the RTD project linked to primary care data. Crude and adjusted proportions of patients diagnosed via six routes (emergency, elective GP referral, two-week wait (2WW), screen-detected, hospital, and Other routes) were calculated by ethnicity. Adjusted odds ratios (including two-way interactions between cancer and age, sex, IMD, and ethnicity) determined cancer-specific differences in RTD by ethnicity. Results: Across the 10 cancers studied, most patients were diagnosed via 2WW (36.4%), elective GP referral (23.2%), emergency (18.2%), hospital routes (10.3%), and screening (8.61%). Patients of Other ethnic group had the highest proportion of diagnosis via the emergency route, followed by White patients. Asian and Black group were more likely to be GP-referred, with the Black and Mixed groups also more likely to follow the 2WW route. However, there were notable cancer-specific differences in the RTD by ethnicity. Conclusion: Our findings suggest that, where inequalities exist, the adverse cancer outcomes among Asian and Black patients are unlikely to be arising solely from a poorer diagnostic process.