Pre-hospital antibiotic treatment and mortality caused by invasive meningococcal disease, adjusting for indication bias.

Background: Mortality from invasive meningococcal disease (IMD) has remained stable over the last thirty years and it is unclear whether pre-hospital antibiotherapy actually produces a decrease in this mortality. Our aim was to examine whether pre-hospital oral antibiotherapy reduces mortality from IMD, adjusting for indication bias. Methods: A retrospective analysis was made of clinical reports of all patients (n = 848) diagnosed with IMD from 1995 to 2000 in Andalusia and the Canary Islands, Spain, and of the relationship between the use of pre-hospital oral antibiotherapy and mortality. Indication bias was controlled for by the propensity score technique, and a multivariate analysis was performed to determine the probability of each patient receiving antibiotics, according to the symptoms identified before admission. Data on in-hospital death, use of antibiotics and demographic variables were collected. A logistic regression analysis was then carried out, using death as the dependent variable, and prehospital antibiotic use, age, time from onset of symptoms to parenteral antibiotics and the propensity score as independent variables. Results: Data were recorded on 848 patients, 49 (5.72%) of whom died. Of the total number of patients, 226 had received oral antibiotics before admission, mainly betalactams during the previous 48 hours. After adjusting the association between the use of antibiotics and death for age, time between onset of symptoms and in-hospital antibiotic treatment, pre-hospital oral antibiotherapy remained a significant protective factor (Odds Ratio for death 0.37, 95% confidence interval 0.15–0.93). Conclusion: Pre-hospital oral antibiotherapy appears to reduce IMD mortality.

Determinants of non- response to a second assessment of lifestyle factors and body weight in the EPIC-PANACEA study.

BACKGROUND This paper discusses whether baseline demographic, socio-economic, health variables, length of follow-up and method of contacting the participants predict non-response to the invitation for a second assessment of lifestyle factors and body weight in the European multi-center EPIC-PANACEA study. METHODS Over 500.000 participants from several centers in ten European countries recruited between 1992 and 2000 were contacted 2-11 years later to update data on lifestyle and body weight. Length of follow-up as well as the method of approaching differed between the collaborating study centers. Non-responders were compared with responders using multivariate logistic regression analyses. RESULTS Overall response for the second assessment was high (81.6%). Compared to postal surveys, centers where the participants completed the questionnaire by phone attained a higher response. Response was also high in centers with a short follow-up period. Non-response was higher in participants who were male (odds ratio 1.09 (confidence interval 1.07; 1.11), aged under 40 years (1.96 (1.90; 2.02), living alone (1.40 (1.37; 1.43), less educated (1.35 (1.12; 1.19), of poorer health (1.33 (1.27; 1.39), reporting an unhealthy lifestyle and who had either a low (<18.5 kg/m2, 1.16 (1.09; 1.23)) or a high BMI (>25, 1.08 (1.06; 1.10); especially ≥30 kg/m2, 1.26 (1.23; 1.29)). CONCLUSIONS Cohort studies may enhance cohort maintenance by paying particular attention to the subgroups that are most unlikely to respond and by an active recruitment strategy using telephone interviews.

Use of Two-Part Regression Calibration Model to Correct for Measurement Error in Episodically Consumed Foods in a Single-Replicate Study Design: EPIC Case Study.

In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted two-part regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM) and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC) study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model.

Drug assessment by a Pharmacy and Therapeutics committee: from drug selection criteria to use in clinical practice.

BACKGROUND In Spain, hospital medicines are assessed and selected by local Pharmacy and Therapeutics committees (PTCs). Of all the drugs assessed, cancer drugs are particularly important because of their budgetary impact and the sometimes arguable added value with respect to existing alternatives. This study analyzed the PTC drug selection process and the main objective was to evaluate the degree of compliance of prescriptions for oncology drugs with their criteria for use. METHODS This was a retrospective observational study (May 2007 to April 2010) of PTC-assessed drugs. The variables measured to describe the committee's activity were number of drugs assessed per year and number of drugs included in any of these settings: without restrictions, with criteria for use, and not included in formulary. These drugs were also analyzed by therapeutic group. To assess the degree of compliance of prescriptions, a score was calculated to determine whether prescriptions for bevacizumab, cetuximab, trastuzumab, and bortezomib were issued in accordance with PTC drug use criteria. RESULTS The PTC received requests for inclusion of 40 drugs, of which 32 were included in the hospital formulary (80.0%). Criteria for use were established for 28 (87.5%) of the drugs included. In total, 293 patients were treated with the four cancer drugs in eight different therapeutic indications. The average prescription compliance scores were as follows: bevacizumab, 83% for metastatic colorectal cancer, 100% for metastatic breast cancer, and 82.3% for non-small-cell lung cancer; cetuximab, 62.0% for colorectal cancer and 50% for head and neck cancer; trastuzumab, 95.1% for early breast cancer and 82.4% for metastatic breast cancer; and bortezomib, 63.7% for multiple myeloma. CONCLUSION The degree of compliance with criteria for use of cancer drugs was reasonably high. PTC functions need to be changed so that they can carry out more innovative tasks, such as monitoring conditions for drug use.