BackgroundIn the UK, the cancer antigen 125 (CA125) test is recommended as a first-line investigation in women with symptoms of possible ovarian cancer.AimTo compare time between initial primary care CA125 test and diagnosis, tumour morphology, and stage in women with normal (<35 U/ml) and abnormal (≥35 U/ml) CA125 levels prior to ovarian cancer diagnosis.Design and settingRetrospective cohort study using English primary care and cancer registry data.MethodAssociations between CA125 test results and test-to-diagnosis interval, stage, and ovarian cancer morphology were examined.ResultsIn total, 456 women were diagnosed with ovarian cancer in the 12 months after having a CA125 test. of these, 351 (77%) had an abnormal, and 105 (23%) had a normal, CA125 test result. The median test-to-diagnosis interval was 35 days (interquartile range [IQR] 21–53) for those with abnormal CA125 levels, and 64 days (IQR 42–127) for normal CA125 levels. Tumour morphology differed by CA125 result: indolent borderline tumours were less common in those with abnormal CA125 levels (n = 47, 13%) than those with normal CA125 levels (n = 51, 49%) (P<0.001). Staging data were available for 304 women with abnormal, and 77 with normal, CA125 levels. of those with abnormal CA125 levels, 35% (n = 106) were diagnosed at an early stage, compared to 86% (n = 66) of women with normal levels. The odds of being diagnosed with early-stage disease were higher in women with normal as opposed to abnormal CA125 levels (odds ratio 12.2, 95% confidence interval = 5.8 to 25.1, P<0.001).ConclusionDespite longer intervals between testing and diagnosis, women with normal, compared with abnormal, CA125 levels more frequently had indolent tumours and were more commonly diagnosed at an early stage in the course of the disease. Although testing approaches that have greater sensitivity might expedite diagnosis for some women, it is not known if this would translate to earlier-stage diagnosis.

OBJECTIVES: to investigate how the COVID-19 pandemic affected the number of people aged 50+ years presenting to primary care with features that could potentially indicate cancer, and to explore how reporting differed by patient characteristics and in face-to-face vs remote consultations. DESIGN, SETTING AND PARTICIPANTS: a retrospective cohort study of general practitioner (GP), nurse and paramedic primary care consultations in 21 practices in South-West England covering 123 947 patients. The models compared potential cancer indicators reported in April-July 2019 with April-July 2020. MAIN OUTCOME MEASURES: Potential indicators of cancer were identified using code lists for symptoms, signs, test results and diagnoses listed in the National Institute for Health and Care Excellence suspected cancer referral guidance (NG12). RESULTS: During April-July 2019, 17% of registered patients aged 50+ years reported a potential cancer indicator in a consultation with a GP or nurse. During April-July 2020, this reduced to 11% (incidence rate ratio (IRR) 0.64, 95% CI 0.62 to 0.67, p

BACKGROUND: a standard measure of the cancer diagnostic pathway, diagnostic interval, is the time from "first presentation of cancer" to diagnosis. Cancer presentation may be unclear in patients with multimorbidity or non-specific symptoms, signs or test results ("features"). We propose an alternative, guideline interval, with a more certain start date; namely, when the patient first meets suspected-cancer criteria for investigation or referral. METHODS: This retrospective cohort study used Clinical Practice Research Datalink (CPRD) and English cancer registry data. Participants, aged ≥55 years, had diagnostic codes for oesophagogastric cancers in 1/1/12-31/12/17. Features of oesophagogastric cancer in the year before diagnosis were identified from CPRD codes for dysphagia, haematemesis, upper-abdominal mass or pain, low haemoglobin, reflux, dyspepsia, nausea, vomiting, weight loss or thrombocytosis. Diagnostic interval was the time from first feature to diagnosis; guidance interval, the time from first meeting criteria in NICE suspected-cancer guidance to diagnosis. Multimorbidity burden was quantified using Adjusted Clinical Groups®. Accelerated failure-time models explored associations between multimorbidity burden and length of both diagnostic and guideline interval. RESULTS: There were 3,793 eligible participants (69.0 % male), mean age 74.1 years (SD 10.5). 3,097 (81.7 %) presented with ≥1 feature in the year before diagnosis, and 1,990 (52.5 %) met NICE suspected-cancer criteria. The median for both intervals was 11 days in healthy users, and rose with increasing morbidity burden. At very high multimorbidity burden, diagnostic interval was 5.47 (95%CI 3.25-9.20) times longer and guideline interval was 3.91 (2.63-5.80) times longer than for healthy users. CONCLUSIONS: Guideline interval is proposed as a new measure of the cancer diagnostic pathway. It has a more certain start date than diagnostic interval, and is lengthened less than diagnostic interval in people with a very high multimorbidity burden. Guideline interval has potential for assessing the implementation of suspected-cancer policies.

Background
The diagnostic assessment of abdominal symptoms in primary care presents a challenge. Evidence is needed about the positive predictive values (PPVs) of abdominal symptoms for different cancers and inflammatory bowel disease (IBD).


Methods and findings
Using data from the Health Improvement Network (THIN) in the United Kingdom (2000–2017), we estimated the PPVs for diagnosis of (i) cancer (overall and for different cancer sites); (ii) IBD; and (iii) either cancer or IBD in the year post-consultation with each of 6 abdominal symptoms: dysphagia (n = 86,193 patients), abdominal bloating/distension (n = 100,856), change in bowel habit (n = 106,715), rectal bleeding (n = 235,094), dyspepsia (n = 517,326), and abdominal pain (n = 890,490). The median age ranged from 54 (abdominal pain) to 63 years (dysphagia and change in bowel habit); the ratio of women/men ranged from 50%:50% (rectal bleeding) to 73%:27% (abdominal bloating/distension). Across all studied symptoms, the risk of diagnosis of cancer and the risk of diagnosis of IBD were of similar magnitude, particularly in women, and younger men. Estimated PPVs were greatest for change in bowel habit in men (4.64% cancer and 2.82% IBD) and for rectal bleeding in women (2.39% cancer and 2.57% IBD) and lowest for dyspepsia (for cancer: 1.41% men and 1.03% women; for IBD: 0.89% men and 1.00% women). Considering PPVs for specific cancers, change in bowel habit and rectal bleeding had the highest PPVs for colon and rectal cancer; dysphagia for esophageal cancer; and abdominal bloating/distension (in women) for ovarian cancer. The highest PPVs of abdominal pain (either sex) and abdominal bloating/distension (men only) were for non-abdominal cancer sites. For the composite outcome of diagnosis of either cancer or IBD, PPVs of rectal bleeding exceeded the National Institute of Health and Care Excellence (NICE)-recommended specialist referral threshold of 3% in all age–sex strata, as did PPVs of abdominal pain, change in bowel habit, and dyspepsia, in those aged 60 years and over. Study limitations include reliance on accuracy and completeness of coding of symptoms and disease outcomes.


Conclusions
Based on evidence from more than 1.9 million patients presenting in primary care, the findings provide estimated PPVs that could be used to guide specialist referral decisions, considering the PPVs of common abdominal symptoms for cancer alongside that for IBD and their composite outcome (cancer or IBD), taking into account the variable PPVs of different abdominal symptoms for different cancers sites. Jointly assessing the risk of cancer or IBD can better support decision-making and prompt diagnosis of both conditions, optimising specialist referrals or investigations, particularly in women.

Abstract
. Background
. Expediting cancer diagnosis may be achieved by targeted decreases in referral thresholds to increase numbers of patients referred for urgent investigation.
.
. Methods
. Clinical Practice Research Datalink data from England for 150,921 adults aged ≥40 were used to identify participants with features of possible cancer equating to risk thresholds ≥1%, ≥2% or ≥3% for breast, lung, colorectal, oesophago-gastric, pancreatic, renal, bladder, prostatic, ovarian, endometrial and laryngeal cancers.
.
. Results
. The mean age of participants was 60 (SD 13) years, with 73,643 males (49%). In 2016, 8576 consultation records contained coded features having a positive predictive value (PPV) of ≥3% for any of the 11 cancers. This equates to a rate of 5682/100,000 patients compared with 4601/100,000 Suspected Cancer NHS referrals for these cancers from April 2016–March 2017. Nine thousands two hundred ninety-one patient-consultation records had coded features equating to a ≥2% PPV, 8% more than met PPV ≥ 3%. Similarly, 19,517 had features with a PPV ≥ 1%, 136% higher than for PPV ≥ 3%.
.
. Conclusions
. This study estimated the number of primary-care patients presenting at lower thresholds of cancer risk. The resource implications of liberalising this threshold to 2% are modest and manageable. The details across individual cancer sites should assist planning of English cancer services.
.

BACKGROUND: Thrombocytosis is an excess of platelets, which is diagnosed as a platelet count >400 × 109/l. An association of thrombocytosis with undiagnosed cancer has recently been established, but the association with non-malignant disease has not been studied in primary care. AIM: to examine, in English primary care, the 1-year incidence of non-malignant diseases in patients with new thrombocytosis and the incidence of pre-existing non-malignant diseases in patients who develop new thrombocytosis. DESIGN AND SETTING: Prospective cohort study using English Clinical Practice Research Datalink data from 2000 to 2013. METHOD: Newly incident and pre-existing rates of non-malignant diseases associated with thrombocytosis were compared between patients with thrombocytosis and age- and sex-matched patients with a normal platelet count. Fifteen candidate non-malignant diseases were identified from literature searches. RESULTS: in the thrombocytosis cohort of 39 850 patients, 4579 (11.5%) were newly diagnosed with any one of the candidate diseases, compared with 443 out of 9684 patients (4.6%) in the normal platelet count cohort (relative risk [RR] 2.5, 95% confidence intervals [CI] = 2.3 to 2.8); iron-deficiency anaemia was the most common new diagnosis (4.5% of patients with thrombocytosis, RR 4.9, 95% CI = 4.0 to 6.1). A total of 22 612 (57.0%) patients with thrombocytosis had a pre-existing non-malignant diagnosis compared with 4846 patients (50%) in the normal platelet count cohort (odds ratio 1.3, 95% CI = 1.2 to 1.4). There was no statistically significant difference in cancer diagnoses between patients with and without pre-existing disease in the thrombocytosis cohort. CONCLUSION: Thrombocytosis is associated with several non-malignant diseases. Clinicians can use these findings as part of their holistic diagnostic approach to help guide further investigations and management of patients with thrombocytosis.

. Background
. Tools based on diagnostic prediction models are available to help general practitioners diagnose cancer. It is unclear whether or not tools expedite diagnosis or affect patient quality of life and/or survival.
.
.
. Objectives
. The objectives were to evaluate the evidence on the validation, clinical effectiveness, cost-effectiveness, and availability and use of cancer diagnostic tools in primary care.
.
.
. Methods
. Two systematic reviews were conducted to examine the clinical effectiveness (review 1) and the development, validation and accuracy (review 2) of diagnostic prediction models for aiding general practitioners in cancer diagnosis. Bibliographic searches were conducted on MEDLINE, MEDLINE In-Process, EMBASE, Cochrane Library and Web of Science) in May 2017, with updated searches conducted in November 2018. A decision-analytic model explored the tools’ clinical effectiveness and cost-effectiveness in colorectal cancer. The model compared patient outcomes and costs between strategies that included the use of the tools and those that did not, using the NHS perspective. We surveyed 4600 general practitioners in randomly selected UK practices to determine the proportions of general practices and general practitioners with access to, and using, cancer decision support tools. Association between access to these tools and practice-level cancer diagnostic indicators was explored.
.
.
. Results
. Systematic review 1 – five studies, of different design and quality, reporting on three diagnostic tools, were included. We found no evidence that using the tools was associated with better outcomes. Systematic review 2 – 43 studies were included, reporting on prediction models, in various stages of development, for 14 cancer sites (including multiple cancers). Most studies relate to QCancer® (ClinRisk Ltd, Leeds, UK) and risk assessment tools.
.
.
. Decision model
. In the absence of studies reporting their clinical outcomes, QCancer and risk assessment tools were evaluated against faecal immunochemical testing. A linked data approach was used, which translates diagnostic accuracy into time to diagnosis and treatment, and stage at diagnosis. Given the current lack of evidence, the model showed that the cost-effectiveness of diagnostic tools in colorectal cancer relies on demonstrating patient survival benefits. Sensitivity of faecal immunochemical testing and specificity of QCancer and risk assessment tools in a low-risk population were the key uncertain parameters.
.
.
. Survey
. Practitioner- and practice-level response rates were 10.3% (476/4600) and 23.3% (227/975), respectively. Cancer decision support tools were available in 83 out of 227 practices (36.6%, 95% confidence interval 30.3% to 43.1%), and were likely to be used in 38 out of 227 practices (16.7%, 95% confidence interval 12.1% to 22.2%). The mean 2-week-wait referral rate did not differ between practices that do and practices that do not have access to QCancer or risk assessment tools (mean difference of 1.8 referrals per 100,000 referrals, 95% confidence interval –6.7 to 10.3 referrals per 100,000 referrals).
.
.
. Limitations
. There is little good-quality evidence on the clinical effectiveness and cost-effectiveness of diagnostic tools. Many diagnostic prediction models are limited by a lack of external validation. There are limited data on current UK practice and clinical outcomes of diagnostic strategies, and there is no evidence on the quality-of-life outcomes of diagnostic results. The survey was limited by low response rates.
.
.
. Conclusion
. The evidence base on the tools is limited. Research on how general practitioners interact with the tools may help to identify barriers to implementation and uptake, and the potential for clinical effectiveness.
.
.
. Future work
. Continued model validation is recommended, especially for risk assessment tools. Assessment of the tools’ impact on time to diagnosis and treatment, stage at diagnosis, and health outcomes is also recommended, as is further work to understand how tools are used in general practitioner consultations.
.
.
. Study registration
. This study is registered as PROSPERO CRD42017068373 and CRD42017068375.
.
.
. Funding
. This project was funded by the National Institute for Health Research (NIHR) Health Technology programme and will be published in full in Health Technology Assessment; Vol. 24, No. 66. See the NIHR Journals Library website for further project information.
.

BACKGROUND: Most patients diagnosed with lung cancer present with symptoms. It is not known if the proportions of patients presenting with each symptom has changed over time. Identifying trends in lung cancer's presenting symptoms is important for medical education and early-diagnosis initiatives. AIM: to identify the first reported symptom of possible lung cancer (index symptom), and to test whether the percentages of patients with each index symptom changed during 2000-2017. DESIGN AND SETTING: This was a serial, cross-sectional, observational study using UK Clinical Practice Research Datalink (CPRD) data with cancer registry linkage. METHOD: the index symptom was identified for patients with an incident diagnosis of lung cancer in annual cohorts between 1 January 2000 and 31 December 2017. Searches were constrained to symptoms in National Institute for Health and Care Excellence (NICE) suspected-cancer referral guidelines, and to the year before diagnosis. Generalised linear models (with a binomial function) were used to test if the percentages of patients with each index symptom varied during 2000-2017. RESULTS: the percentage of patients with an index symptom of cough (odds ratio [OR] 1.01; 95% confidence interval [CI] = 1.00 to 1.02 per year; P

BACKGROUND: Pre-existing concurrent medical conditions (multimorbidity) complicate cancer diagnosis when they provide plausible diagnostic alternatives for cancer symptoms. AIM: to investigate associations in bladder cancer between: first, pre-existing condition count and advanced-stage diagnosis; and, second, comorbidities that share symptoms with bladder cancer and advanced-stage diagnosis. DESIGN AND SETTING: This observational UK cohort study was set in the Clinical Practice Research Datalink with Public Health England National Cancer Registration and Analysis Service linkage. METHOD: Included participants were aged ≥40 years with an incident diagnosis of bladder cancer between 1 January 2000 and 31 December 2015, and primary care records of attendance for haematuria, dysuria, or abdominal mass in the year before diagnosis. Stage at diagnosis (stage 1 or 2 versus stage 3 or 4) was the outcome variable. Putative explanatory variables using logistic regression were examined, including patient-level count of pre-existing conditions and 'alternative-explanations', indicating whether pre-existing condition(s) were plausible diagnostic alternatives for the index cancer symptom. RESULTS: in total, 1468 patients (76.4% male) were studied, of which 399 (35.6%) males and 217 (62.5%) females had alternative explanations for their index cancer symptom, the most common being urinary tract infection with haematuria. Females were more likely than males to be diagnosed with advanced-stage cancer (adjusted odds ratio [aOR] 1.62; 95% confidence interval [CI] = 1.20 to 2.18; P = 0.001). Alternative explanations were strongly associated with advanced-stage diagnosis in both sexes (aOR 1.69; 95% CI = 1.20 to 2.39; P = 0.003). CONCLUSION: Alternative explanations were associated with advanced-stage diagnosis of bladder cancer. Females were more likely than males to be diagnosed with advanced-stage disease, but the effect was not driven entirely by alternative explanations.

We examine the suitability of three methods using patient-level data to evaluate the time-varying impacts of national healthcare guidelines. Such guidelines often codify progressive change and are implemented gradually; for example, National Institute for Health and Care Excellence (NICE) suspected-cancer referral guidelines. These were revised on June 23, 2015, to include more cancer symptoms and test results ("features"), partly reflecting changing practice. We explore the time-varying impact of guideline revision on time to colorectal cancer diagnosis, which is linked to improved outcomes in decision-analytic models. We included 11,842 patients diagnosed in 01/01/2006-31/12/2017 in the Clinical Practice Research Datalink with England cancer registry data linkage. Patients were classified by whether their first pre-diagnostic cancer feature was in the original guidelines (NICE-2005) or was added during the revision (NICE-2015-only). Outcome was diagnostic interval: time from first cancer feature to diagnosis. All analyses adjusted for age and sex. Two difference-in-differences analyses used either a Pre (01/08/2012-31/12/2014, n = 2243) and Post (01/08/2015-31/12/2017, n = 1017) design, or event-study cohorts (2006-2017 vs 2015) to estimate change in diagnostic interval attributable to official implementation of the revised guidelines. A semiparametric varying-coefficient model analysed the difference in diagnostic interval between the NICE groups over time. After model estimation, primary and broader treatment effects of guideline content and implementation were measured. The event-study difference-in-differences and the semiparametric varying-coefficient methods showed that shorter diagnostic intervals were attributable to official implementation of the revised guidelines. This impact was only detectable by pre-to-post difference-in-differences when the pre/post periods were selected according to the estimation results from the varying-coefficient model. Formal tests of the parametric models, which are special cases of the semiparametric model, suggest that they are misspecified. We conclude that the semiparametric method is well suited to explore the time-varying impacts of guidelines codifying progressive change.

Abstract
.
. Background
. Pre-existing conditions interfere with cancer diagnosis by offering diagnostic alternatives, competing for clinical attention or through patient surveillance.
.
.
. Objective
. To investigate associations between oesophagogastric cancer stage and pre-existing conditions.
.
.
. Methods
. Retrospective cohort study using Clinical Practice Research Datalink (CPRD) data, with English cancer registry linkage. Participants aged ≥40 years had consulted primary care in the year before their incident diagnosis of oesophagogastric cancer in 01/01/2010–31/12/2015. CPRD records pre-diagnosis were searched for codes denoting clinical features of oesophagogastric cancer and for pre-existing conditions, including those providing plausible diagnostic alternatives for those features. Logistic regression analysed associations between stage and multimorbidity (≥2 conditions; reference category: no multimorbidity) and having ‘diagnostic alternative(s)’, controlling for age, sex, deprivation and cancer site.
.
.
. Results
. of 2444 participants provided, 695 (28%) were excluded for missing stage, leaving 1749 for analysis (1265/1749, 72.3% had advanced-stage disease). Multimorbidity was associated with stage [odds ratio 0.63, 95% confidence interval (CI) 0.47–0.85, P = 0.002], with moderate evidence of an interaction term with sex (1.76, 1.08–2.86, P = 0.024). There was no association between alternative explanations and stage (odds ratio 1.18, 95% CI 0.87–1.60, P = 0.278).
.
.
. Conclusions
. In men, multimorbidity is associated with a reduced chance of advanced-stage oesophagogastric cancer, to levels seen collectively for women.
.

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: Pre-existing non-cancer conditions may complicate and delay colorectal cancer diagnosis. METHOD: 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. RESULTS: 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). CONCLUSIONS: 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.

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.

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=21â€
718; pancreas: n=16â€
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

BACKGROUND: Diagnosis of bladder cancer relies on investigation of symptoms presented to primary care, notably visible haematuria. The importance of non-visible haematuria has never been estimated. AIM: to estimate the risk of bladder cancer with non-visible haematuria. DESIGN AND SETTING: a case-control study using UK electronic primary care medical records, including uncoded data to supplement coded records. METHOD: a total of 4915 patients (aged ≥40 years) diagnosed with bladder cancer between January 2000 and December 2009 were selected from the Clinical Practice Research Datalink and matched to 21 718 controls for age, sex, and practice. Variables for visible and non-visible haematuria were derived from coded and uncoded data. Analyses used multivariable conditional logistic regression, followed by estimation of positive predictive values (PPVs) for bladder cancer using Bayes' theorem. RESULTS: Non-visible haematuria (coded/uncoded data) was independently associated with bladder cancer: odds ratio (OR) 20 (95% confidence interval [CI] =12 to 33). The PPV of non-visible haematuria was 1.6% (95% CI = 1.2 to 2.1) in those aged ≥60 years and 0.8% (95% CI = 0.1 to 5.6) in 40-59-year-olds. The PPV of visible haematuria was 2.8% (95% CI = 2.5 to 3.1) and 1.2% (95% CI = 0.6 to 2.3) for the same age groups respectively, lower than those calculated using coded data alone. The proportion of records of visible haematuria in coded, rather than uncoded, format was higher in cases than in controls (P

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.