On the 12th day of Christmas, a statistician sent to me . . .

The BMJ’s statistical editors relish a quiet Christmas, so make their wish come true and pay attention to the list of common statistical faux pas presented here by Riley and colleagues

Beliefs about Appropriate Antibacterial Therapy, California

To our knowledge, previous population-based surveys have not assessed misconceptions about antibacterial drug use over time. We documented a 26.3% decline in a key misconception in California women in 2003 compared to 2000; declines varied significantly by education level. Educational campaigns specifically designed to influence important subpopulations are needed

New technologies for diagnosing active TB: the VANTDET diagnostic accuracy study

BackgroundTuberculosis (TB) is a devastating disease for which new diagnostic tests are desperately needed.ObjectiveTo validate promising new technologies [namely whole-blood transcriptomics, proteomics, flow cytometry and quantitative reverse transcription-polymerase chain reaction (qRT-PCR)] and existing signatures for the detection of active TB in samples obtained from individuals with suspected active TB.DesignFour substudies, each of which used samples from the biobank collected as part of the interferon gamma release assay (IGRA) in the Diagnostic Evaluation of Active TB study, which was a prospective cohort of patients recruited with suspected TB.SettingSecondary care.ParticipantsAdults aged ≥ 16 years presenting as inpatients or outpatients at 12 NHS hospital trusts in London, Slough, Oxford, Leicester and Birmingham, with suspected active TB.InterventionsNew tests using genome-wide gene expression microarray (transcriptomics), surface-enhanced laser desorption ionisation time-of-flight mass spectrometry/liquid chromatography–mass spectrometry (proteomics), flow cytometry or qRT-PCR.Main outcome measuresArea under the curve (AUC), sensitivity and specificity were calculated to determine diagnostic accuracy. Positive and negative predictive values were calculated in some cases. A decision tree model was developed to calculate the incremental costs and quality-adjusted life-years of changing from current practice to using the novels tests.ResultsThe project, and four substudies that assessed the previously published signatures, measured each of the new technologies and performed a health economic analysis in which the best-performing tests were evaluated for cost-effectiveness. The diagnostic accuracy of the transcriptomic tests ranged from an AUC of 0.81 to 0.84 for detecting all TB in our cohort. The performance for detecting culture-confirmed TB or pulmonary TB was better than for highly probable TB or extrapulmonary tuberculosis (EPTB), but was not high enough to be clinically useful. None of the previously described serum proteomic signatures for active TB provided good diagnostic accuracy, nor did the candidate rule-out tests. Four out of six previously described cellular immune signatures provided a reasonable level of diagnostic accuracy (AUC = 0.78–0.92) for discriminating all TB from those with other disease and latent TB infection in human immunodeficiency virus-negative TB suspects. Two of these assays may be useful in the IGRA-positive population and can provide high positive predictive value. None of the new tests for TB can be considered cost-effective.LimitationsThe diagnostic performance of new tests among the HIV-positive population was either underpowered or not sufficiently achieved in each substudy.ConclusionsOverall, the diagnostic performance of all previously identified ‘signatures’ of TB was lower than previously reported. This probably reflects the nature of the cohort we used, which includes the harder to diagnose groups, such as culture-unconfirmed TB or EPTB, which were under-represented in previous cohorts.Future workWe are yet to achieve our secondary objective of deriving novel signatures of TB using our data sets. This was beyond the scope of this report. We recommend that future studies using these technologies target specific subtypes of TB, specifically those groups for which new diagnostic tests are required.FundingThis project was funded by the Efficacy and Mechanism Evaluation (EME) programme, a MRC and NIHR partnership

MICE or NICE? An economic evaluation of clinical decision rules in the diagnosis of heart failure in primary care.

BACKGROUND: Detection and treatment of heart failure (HF) can improve quality of life and reduce premature mortality. However, symptoms such as breathlessness are common in primary care, have a variety of causes and not all patients require cardiac imaging. In systems where healthcare resources are limited, ensuring those patients who are likely to have HF undergo appropriate and timely investigation is vital. DESIGN: A decision tree was developed to assess the cost-effectiveness of using the MICE (Male, Infarction, Crepitations, Edema) decision rule compared to other diagnostic strategies to identify HF patients presenting to primary care. METHODS: Data from REFER (REFer for EchocaRdiogram), a HF diagnostic accuracy study, was used to determine which patients received the correct diagnosis decision. The model adopted a UK National Health Service (NHS) perspective. RESULTS: The current recommended National Institute for Health and Care Excellence (NICE) guidelines for identifying patients with HF was the most cost-effective option with a cost of £4400 per quality adjusted life year (QALY) gained compared to a "do nothing" strategy. That is, patients presenting with symptoms suggestive of HF should be referred straight for echocardiography if they had a history of myocardial infarction or if their NT-proBNP level was ≥400pg/ml. The MICE rule was more expensive and less effective than the other comparators. Base-case results were robust to sensitivity analyses. CONCLUSIONS: This represents the first cost-utility analysis comparing HF diagnostic strategies for symptomatic patients. Current guidelines in England were the most cost-effective option for identifying patients for confirmatory HF diagnosis. The low number of HF with Reduced Ejection Fraction patients (12%) in the REFER patient population limited the benefits of early detection

Hypoglycemia in Non-Diabetic In-Patients: Clinical or Criminal?

BACKGROUND AND AIM: We wished to establish the frequency of unexpected hypoglycemia observed in non diabetic patients outside the intensive care unit and to determine if they have a plausible clinical explanation. METHODS: We analysed data for 2010 from three distinct sources to identify non diabetic hypoglycaemic patients: bedside and laboratory blood glucose measurements; medication records for those treatments (high-strength glucose solution and glucagon) commonly given to reverse hypoglycemia; and diagnostic codes for hypoglycemia. We excluded from the denominator admissions of patients with a diagnosis of diabetes or prescribed diabetic medication. Case notes of patients identified were reviewed. We used capture-recapture methods to establish the likely frequency of hypoglycemia in non-diabetic in-patients outside intensive care unit at different cut-off points for hypoglycemia. We also recorded co-morbidities that might have given rise to hypoglycemia. RESULTS: Among the 37,898 admissions, the triggers identified 71 hypoglycaemic episodes at a cut-off of 3.3 mmol/l. Estimated frequency at 3.3 mmol/l was 50(CI 33-93), at 3.0 mmol/l, 36(CI 24-64), at 2.7 mmol/l, 13(CI 11-19), at 2.5 mmol/l, 11(CI 9-15) and at 2.2 mmol/l, 8(CI 7-11) per 10,000 admissions. Admissions of patients aged above 65 years were approximately 50% more likely to have an episode of hypoglycemia. Most were associated with important co-morbidities. CONCLUSION: Significant non-diabetic hypoglycemia in hospital in-patients (at or below 2.7 mmol/l) outside critical care is rare. It is sufficiently rare for occurrences to merit case-note review and diagnostic blood tests, unless an obvious explanation is found

Methods Used in Economic Evaluations of Chronic Kidney Disease Testing — A Systematic Review

Background: The prevalence of chronic kidney disease (CKD) is high in general populations around the world. Targeted testing and screening for CKD are often conducted to help identify individuals that may benefit from treatment to ameliorate or prevent their disease progression. Aims: This systematic review examines the methods used in economic evaluations of testing and screening in CKD, with a particular focus on whether test accuracy has been considered, and how analysis has incorporated issues that may be important to the patient, such as the impact of testing on quality of life and the costs they incur. Methods: Articles that described model-based economic evaluations of patient testing interventions focused on CKD were identified through the searching of electronic databases and the hand searching of the bibliographies of the included studies. Results: The initial electronic searches identified 2,671 papers of which 21 were included in the final review. Eighteen studies focused on proteinuria, three evaluated glomerular filtration rate testing and one included both tests. The full impact of inaccurate test results was frequently not considered in economic evaluations in this setting as a societal perspective was rarely adopted. The impact of false positive tests on patients in terms of the costs incurred in re-attending for repeat testing, and the anxiety associated with a positive test was almost always overlooked. In one study where the impact of a false positive test on patient quality of life was examined in sensitivity analysis, it had a significant impact on the conclusions drawn from the model. Conclusion: Future economic evaluations of kidney function testing should examine testing and monitoring pathways from the perspective of patients, to ensure that issues that are important to patients, such as the possibility of inaccurate test results, are properly considered in the analysis

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]