Long-term outcomes and cost effectiveness of high-dose dexamethasone for cardiac surgery: a randomised trial.

Prophylactic intra-operative administration of dexamethasone may improve short-term clinical outcomes in cardiac surgical patients. The purpose of this study was to evaluate long-term clinical outcomes and cost effectiveness of dexamethasone versus placebo. Patients included in the multicentre, randomised, double-blind, placebo-controlled DExamethasone for Cardiac Surgery (DECS) trial were followed up for 12 months after their cardiac surgical procedure. In the DECS trial, patients received a single intra-operative dose of dexamethasone 1 mg.kg-1 (n = 2239) or placebo (n = 2255). The effects on the incidence of major postoperative events were evaluated. Also, overall costs for the 12-month postoperative period, and cost effectiveness, were compared between groups. Of 4494 randomised patients, 4457 patients (99%) were followed up until 12 months after surgery. There was no difference in the incidence of major postoperative events, the relative risk (95%CI) being 0.86 (0.72-1.03); p = 0.1. Treatment with dexamethasone reduced costs per patient by £921 [€1084] (95%CI £-1672 to -137; p = 0.02), mainly through reduction of postoperative respiratory failure and duration of postoperative hospital stay. The probability of dexamethasone being cost effective compared with placebo was 97% at a threshold value of £17,000 [€20,000] per quality-adjusted life year. We conclude that intra-operative high-dose dexamethasone did not have an effect on major adverse events at 12 months after cardiac surgery, but was associated with a reduction in costs. Routine dexamethasone administration is expected to be cost effective at commonly accepted threshold levels for cost effectiveness.

Long-term cognitive impairment after critical illness.

BACKGROUND: Survivors of critical illness often have a prolonged and disabling form of cognitive impairment that remains inadequately characterized. METHODS: We enrolled adults with respiratory failure or shock in the medical or surgical intensive care unit (ICU), evaluated them for in-hospital delirium, and assessed global cognition and executive function 3 and 12 months after discharge with the use of the Repeatable Battery for the Assessment of Neuropsychological Status (population age-adjusted mean [±SD] score, 100±15, with lower values indicating worse global cognition) and the Trail Making Test, Part B (population age-, sex-, and education-adjusted mean score, 50±10, with lower scores indicating worse executive function). Associations of the duration of delirium and the use of sedative or analgesic agents with the outcomes were assessed with the use of linear regression, with adjustment for potential confounders. RESULTS: Of the 821 patients enrolled, 6% had cognitive impairment at baseline, and delirium developed in 74% during the hospital stay. At 3 months, 40% of the patients had global cognition scores that were 1.5 SD below the population means (similar to scores for patients with moderate traumatic brain injury), and 26% had scores 2 SD below the population means (similar to scores for patients with mild Alzheimer's disease). Deficits occurred in both older and younger patients and persisted, with 34% and 24% of all patients with assessments at 12 months that were similar to scores for patients with moderate traumatic brain injury and scores for patients with mild Alzheimer's disease, respectively. A longer duration of delirium was independently associated with worse global cognition at 3 and 12 months (P=0.001 and P=0.04, respectively) and worse executive function at 3 and 12 months (P=0.004 and P=0.007, respectively). Use of sedative or analgesic medications was not consistently associated with cognitive impairment at 3 and 12 months. CONCLUSIONS: Patients in medical and surgical ICUs are at high risk for long-term cognitive impairment. A longer duration of delirium in the hospital was associated with worse global cognition and executive function scores at 3 and 12 months. (Funded by the National Institutes of Health and others; BRAIN-ICU ClinicalTrials.gov number, NCT00392795.).

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement.

Prediction models are developed to aid health-care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health-care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).

Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): the TRIPOD Statement.

BACKGROUND: Prediction models are developed to aid healthcare providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision-making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. METHODS: An extensive list of items based on a review of the literature was created, which was reduced after a web-based survey and revised during a 3-day meeting in June 2011 with methodologists, healthcare professionals and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. RESULTS: The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. CONCLUSION: The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. A complete checklist is available at http://www.tripod-statement.org.

Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): the TRIPOD statement.

Prediction models are developed to aid healthcare providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision-making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) initiative developed a set of recommendations for the reporting of studies developing, validating or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a web-based survey and revised during a 3-day meeting in June 2011 with methodologists, healthcare professionals and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study, regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).

Improved prediction of inhibitor development in previously untreated patients with severe haemophilia A.

Treatment of previously untreated patients (PUPs) with severe haemophilia A is complicated by the formation of inhibitors. Prediction of PUPs with high risk is important to allow altering treatment with the intention to reduce the occurrence of inhibitors. An unselected multicentre cohort of 825 PUPs with severe haemophilia A (FVIII<0.01 IU mL(-1) ) was used. Patients were followed until 50 exposure days (EDs) or inhibitor development. All predictors of the existing prediction model including three new potential predictors were studied using multivariable logistic regression. Model performance was quantified [area under the curve (AUC), calibration plot] and internal validation (bootstrapping) was performed. A nomogram for clinical application was developed. Of the 825 patients, 225 (28%) developed inhibitors. The predictors family history of inhibitors, F8 gene mutation and an interaction variable of dose and number of EDs of intensive treatment were independently associated with inhibitor development. Age and reason for first treatment were not associated with inhibitor development. The AUC was 0.69 (95% CI 0.65-0.72) and calibration was good. An improved prediction model for inhibitor development and a nomogram for clinical use were developed in a cohort of 825 PUPs with severe haemophilia A. Clinical applicability was improved by combining dose and duration of intensive treatment, allowing the assessment of the effects of treatment decisions on inhibitor risk and potentially modify treatment.

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement.

Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).

Effectiveness of progestogens to improve perinatal outcome in twin pregnancies: an individual participant data meta-analysis.

BACKGROUND: In twin pregnancies, the rates of adverse perinatal outcome and subsequent long-term morbidity are substantial, and mainly result from preterm birth (PTB). OBJECTIVES: To assess the effectiveness of progestogen treatment in the prevention of neonatal morbidity or PTB in twin pregnancies using individual participant data meta-analysis (IPDMA). SEARCH STRATEGY: We searched international scientific databases, trial registration websites, and references of identified articles. SELECTION CRITERIA: Randomised clinical trials (RCTs) of 17-hydroxyprogesterone caproate (17Pc) or vaginally administered natural progesterone, compared with placebo or no treatment. DATA COLLECTION AND ANALYSIS: Investigators of identified RCTs were asked to share their IPD. The primary outcome was a composite of perinatal mortality and severe neonatal morbidity. Prespecified subgroup analyses were performed for chorionicity, cervical length, and prior spontaneous PTB. MAIN RESULTS: Thirteen trials included 3768 women and their 7536 babies. Neither 17Pc nor vaginal progesterone reduced the incidence of adverse perinatal outcome (17Pc relative risk, RR 1.1; 95% confidence interval, 95% CI 0.97-1.4, vaginal progesterone RR 0.97; 95% CI 0.77-1.2). In a subgroup of women with a cervical length of ≤25 mm, vaginal progesterone reduced adverse perinatal outcome when cervical length was measured at randomisation (15/56 versus 22/60; RR 0.57; 95% CI 0.47-0.70) or before 24 weeks of gestation (14/52 versus 21/56; RR 0.56; 95% CI 0.42-0.75). AUTHOR'S CONCLUSIONS: In unselected women with an uncomplicated twin gestation, treatment with progestogens (intramuscular 17Pc or vaginal natural progesterone) does not improve perinatal outcome. Vaginal progesterone may be effective in the reduction of adverse perinatal outcome in women with a cervical length of ≤25 mm; however, further research is warranted to confirm this finding.

Impact of adding therapeutic recommendations to risk assessments from a prediction model for postoperative nausea and vomiting.

BACKGROUND: In a large cluster-randomized trial on the impact of a prediction model, presenting the calculated risk of postoperative nausea and vomiting (PONV) on-screen (assistive approach) increased the administration of risk-dependent PONV prophylaxis by anaesthetists. This change in therapeutic decision-making did not improve the patient outcome; that is, the incidence of PONV. The present study aimed to quantify the effects of adding a specific therapeutic recommendation to the predicted risk (directive approach) on PONV prophylaxis decision-making and the incidence of PONV. METHODS: A prospective before-after study was conducted in 1483 elective surgical inpatients. The before-period included care-as-usual and the after-period included the directive risk-based (intervention) strategy. Risk-dependent effects on the administered number of prophylactic antiemetics and incidence of PONV were analysed by mixed-effects regression analysis. RESULTS: During the intervention period anaesthetists administered 0.5 [95% confidence intervals (CIs): 0.4-0.6] more antiemetics for patients identified as being at greater risk of PONV. This directive approach led to a reduction in PONV [odds ratio (OR): 0.60, 95% CI: 0.43-0.83], with an even greater reduction in PONV in high-risk patients (OR: 0.45, 95% CI: 0.28-0.72). CONCLUSIONS: Anaesthetists administered more prophylactic antiemetics when a directive approach was used for risk-tailored intervention compared with care-as-usual. In contrast to the previously studied assistive approach, the increase in PONV prophylaxis now resulted in a lower PONV incidence, particularly in high-risk patients. When one aims for a truly 'PONV-free hospital', a more liberal use of prophylactic antiemetics must be accepted and lower-risk thresholds should be set for the actionable recommendations.

Breast-feeding and health consequences in early childhood: is there an impact of time-dependent confounding?

BACKGROUND: Estimated effects of breast-feeding on childhood health vary between studies, possibly due to confounding by baseline maternal and child characteristics. Possible time-dependent confounding has received little consideration. Our aim was to evaluate the impact of such confounding. METHODS: We estimated the relationship between cumulative exclusive breast-feeding up to 6 months and wheezing, rash and body mass index (BMI) at 12 months [in the Whistler cohort (n = 494) and PROBIT (n = 11,463)], and wheezing, rash, asthma, hay fever, eczema, allergy and BMI at age 6.5 years (PROBIT). We adjusted for time-dependent confounding by weight, length, rash, respiratory illness and day care attendance using marginal structural models (MSMs). RESULTS: Weight and day care attendance appeared potential time-dependent confounders, since these predicted breast-feeding status and were influenced by previous breast-feeding. However, adjustment for time-dependent confounders did not markedly change the estimated associations. For example, in PROBIT the adjusted increase in BMI at 12 months per 1-month increase in exclusive breast-feeding was 0.04 (95% CI -0.09 to 0.01) using logistic regression and -0.06 (95% CI -0.11 to -0.01) using MSM. In Whistler, these estimates were each -0.05 (95% CI -0.10 to 0.00). CONCLUSIONS: In two cohort studies, there was little evidence of time-dependent confounding by weight, length, rash, respiratory illness or day care attendance of the effects of breast-feeding on early childhood health.

Common carotid intima-media thickness does not add to Framingham risk score in individuals with diabetes mellitus: the USE-IMT initiative.

AIMS/HYPOTHESIS: The aim of this work was to investigate whether measurement of the mean common carotid intima-media thickness (CIMT) improves cardiovascular risk prediction in individuals with diabetes. METHODS: We performed a subanalysis among 4,220 individuals with diabetes in a large ongoing individual participant data meta-analysis involving 56,194 subjects from 17 population-based cohorts worldwide. We first refitted the risk factors of the Framingham heart risk score on the individuals without previous cardiovascular disease (baseline model) and then expanded this model with the mean common CIMT (CIMT model). The absolute 10 year risk for developing a myocardial infarction or stroke was estimated from both models. In individuals with diabetes we compared discrimination and calibration of the two models. Reclassification of individuals with diabetes was based on allocation to another cardiovascular risk category when mean common CIMT was added. RESULTS: During a median follow-up of 8.7 years, 684 first-time cardiovascular events occurred among the population with diabetes. The C statistic was 0.67 for the Framingham model and 0.68 for the CIMT model. The absolute 10 year risk for developing a myocardial infarction or stroke was 16% in both models. There was no net reclassification improvement with the addition of mean common CIMT (1.7%; 95% CI -1.8, 3.8). There were no differences in the results between men and women. CONCLUSIONS/INTERPRETATION: There is no improvement in risk prediction in individuals with diabetes when measurement of the mean common CIMT is added to the Framingham risk score. Therefore, this measurement is not recommended for improving individual cardiovascular risk stratification in individuals with diabetes.

Internal validation of risk models in clustered data: a comparison of bootstrap schemes.

Internal validity of a risk model can be studied efficiently with bootstrapping to assess possible optimism in model performance. Assumptions of the regular bootstrap are violated when the development data are clustered. We compared alternative resampling schemes in clustered data for the estimation of optimism in model performance. A simulation study was conducted to compare regular resampling on only the patient level with resampling on only the cluster level and with resampling sequentially on both the cluster and patient levels (2-step approach). Optimism for the concordance index and calibration slope was estimated. Resampling of only patients or only clusters showed accurate estimates of optimism in model performance. The 2-step approach overestimated the optimism in model performance. If the number of centers or intraclass correlation coefficient was high, resampling of clusters showed more accurate estimates than resampling of patients. The 3 bootstrap schemes also were applied to empirical data that were clustered. The results presented in this paper support the use of resampling on only the clusters for estimation of optimism in model performance when data are clustered.

Prognosis and prognostic factors of patients with mesothelioma: a population-based study.

BACKGROUND: It is important to regularly update survival estimates of patients with malignant mesothelioma as prognosis may vary according to epidemiologic factors and diagnostic and therapeutic management. METHODS: We assessed overall (baseline) survival as well as related prognostic variables in a large cohort of 1353 patients with a confirmed diagnosis of malignant mesothelioma between 2005 and 2008. RESULTS: About 50% of the patients were 70 years or older at diagnosis and the median latency time since start of asbestos exposure was 49 years. One year after diagnosis, 47% of the patients were alive, 20% after 2 years and 15% after 3 years. Prognostic variables independently associated with worse survival were: older age (HR=1.04 per year 95% CI (1.03-1.06)), sarcomatoid subtype (HR=2.45 95% CI (2.06-2.90)) and non-pleural localisation (HR=1.67 95% CI (1.26-2.22)). CONCLUSION: Survival of patients with malignant mesothelioma is still limited and depends highly on patient age, mesothelioma subtype and localisation. In addition, a substantial part of the patients had a long latency time between asbestos exposure and diagnosis.

Is intrapartum fever associated with ST-waveform changes of the fetal electrocardiogram? A retrospective cohort study.

OBJECTIVE: To investigate the association between maternal intrapartum fever and ST-waveform changes of the fetal electrocardiogram. DESIGN: Retrospective cohort study. SETTING: Three academic and six non-academic teaching hospitals in the Netherlands. POPULATION: Labouring women with a high-risk singleton pregnancy in cephalic position beyond 36 weeks of gestation. METHODS: We studied 142 women with fever (≥38.0°C) during labour and 141 women with normal temperature who had been included in two previous studies. In both groups, we counted the number and type of ST-events and classified them as significant (intervention needed) or not significant, based on STAN(®) clinical guidelines. MAIN OUTCOME MEASURES: Number and type of ST-events. RESULTS: Both univariable and multivariable regression analysis showed no association between the presence of maternal intrapartum fever and the number or type of ST-events. CONCLUSIONS: Maternal intrapartum fever is not associated with ST-segment changes of the fetal electrocardiogram. Interpretation of ST-changes in labouring women with fever should therefore not differ from other situations.

A clinical prediction model to assess the risk of operative delivery.

OBJECTIVE: To predict instrumental vaginal delivery or caesarean section for suspected fetal distress or failure to progress. DESIGN: Secondary analysis of a randomised trial. SETTING: Three academic and six non-academic teaching hospitals in the Netherlands. POPULATION: 5667 labouring women with a singleton term pregnancy in cephalic presentation. METHODS: We developed multinomial prediction models to assess the risk of operative delivery using both antepartum (model 1) and antepartum plus intrapartum characteristics (model 2). The models were validated by bootstrapping techniques and adjusted for overfitting. Predictive performance was assessed by calibration and discrimination (area under the receiver operating characteristic), and easy-to-use nomograms were developed. MAIN OUTCOME MEASURES: Incidence of instrumental vaginal delivery or caesarean section for fetal distress or failure to progress with respect to a spontaneous vaginal delivery (reference). RESULTS: 375 (6.6%) and 212 (3.6%) women had an instrumental vaginal delivery or caesarean section due to fetal distress, and 433 (7.6%) and 571 (10.1%) due to failure to progress, respectively. Predictors were age, parity, previous caesarean section, diabetes, gestational age, gender, estimated birthweight (model 1) and induction of labour, oxytocin augmentation, intrapartum fever, prolonged rupture of membranes, meconium stained amniotic fluid, epidural anaesthesia, and use of ST-analysis (model 2). Both models showed excellent calibration and the receiver operating characteristics areas were 0.70-0.78 and 0.73-0.81, respectively. CONCLUSION: In Dutch women with a singleton term pregnancy in cephalic presentation, antepartum and intrapartum characteristics can assist in the prediction of the need for an instrumental vaginal delivery or caesarean section for fetal distress or failure to progress.

[Reliable diagnostics: clinical gestalt or prediction rule?] / Klinische blik of beslisregel.

Diagnostic prediction models can support the diagnostic process, both for experienced physicians and for physicians with little experience. More attention should be paid to the incorporation of diagnostic prediction models in the electronic patient record, so that a more accurate probability estimate can be made without simplification to rounded sumscores. A uniform cut-off of sum scores with associated categorization is also undesirable, because it does not take the context of the individual patient sufficiently into account. In the case of a very strong gut feeling, the outcome of a diagnostic prediction model rule alone cannot be sufficient for further policy. Diagnostic prediction models 'only' generate individual objectively estimated probabilities; the clinical decision-making based on these probabilities always needs to be made by the doctor in shared decision making with the patient. Conflict of interest and financial support: none declared.

External validation of the UK Prospective Diabetes Study (UKPDS) risk engine in patients with type 2 diabetes.

AIMS/HYPOTHESIS: Treatment guidelines recommend the UK Prospective Diabetes Study (UKPDS) risk engine for predicting cardiovascular risk in patients with type 2 diabetes, although validation studies showed moderate performance. The methods used in these validation studies were diverse, however, and sometimes insufficient. Hence, we assessed the discrimination and calibration of the UKPDS risk engine to predict 4, 5, 6 and 8 year cardiovascular risk in patients with type 2 diabetes. METHODS: The cohort included 1,622 patients with type 2 diabetes. During a mean follow-up of 8 years, patients were followed for incidence of CHD and cardiovascular disease (CVD). Discrimination and calibration were assessed for 4, 5, 6 and 8 year risk. Discrimination was examined using the c-statistic and calibration by visually inspecting calibration plots and calculating the Hosmer-Lemeshow χ(2) statistic. RESULTS: The UKPDS risk engine showed moderate to poor discrimination for both CHD and CVD (c-statistic of 0.66 for both 5 year CHD and CVD risks), and an overestimation of the risk (224% and 112%). The calibration of the UKPDS risk engine was slightly better for patients with type 2 diabetes who had been diagnosed with diabetes more than 10 years ago compared with patients diagnosed more recently, particularly for 4 and 5 year predicted CVD and CHD risks. Discrimination for these periods was still moderate to poor. CONCLUSIONS/INTERPRETATION: We observed that the UKPDS risk engine overestimates CHD and CVD risk. The discriminative ability of this model is moderate, irrespective of various subgroup analyses. To enhance the prediction of CVD in patients with type 2 diabetes, this model should be updated.

Markers for the non-invasive diagnosis of mesothelioma: a systematic review.

BACKGROUND: Numerous markers have been evaluated to facilitate the non-invasive diagnostic work-up of mesothelioma. The purpose of this study was to conduct a structured review of the diagnostic performance of non-invasive marker tests for the detection of mesothelioma in patients with suspected mesothelioma. METHODS: Studies on the diagnostic accuracy of serum and cytological markers published till 31 December 2009, available in either PUBMED or Embase, to detect or exclude the presence of mesothelioma were extracted. Study quality was assessed with use of the Quadas criteria. RESULTS: In total, 82 articles were included in this systemic review. Overall, quality of the incorporated studies to address our objective was poor. The most frequently studied immunohistochemical markers for cytological analysis were EMA, Ber-Ep4, CEA, and calretinin. The most frequently investigated serum marker was soluble mesothelin-related protein (SMRP). The markers CEA, Ber-EP4, and calretinin were most valuable in discriminating mesothelioma from other malignant diseases. Markers EMA and SMRP were most valuable in discriminating mesothelioma from non-malignant diseases. No marker performed well in discriminating between mesothelioma and all other diseases. CONCLUSION: Currently, there is only limited evidence to properly assess the value of non-invasive marker tests in the diagnosis of mesothelioma. Studies were of limited value to address our objective and results showed considerable unexplained study heterogeneity.

General and abdominal adiposity and risk of death in Europe.

BACKGROUND: Previous studies have relied predominantly on the body-mass index (BMI, the weight in kilograms divided by the square of the height in meters) to assess the association of adiposity with the risk of death, but few have examined whether the distribution of body fat contributes to the prediction of death. METHODS: We examined the association of BMI, waist circumference, and waist-to-hip ratio with the risk of death among 359,387 participants from nine countries in the European Prospective Investigation into Cancer and Nutrition (EPIC). We used a Cox regression analysis, with age as the time variable, and stratified the models according to study center and age at recruitment, with further adjustment for educational level, smoking status, alcohol consumption, physical activity, and height. RESULTS: During a mean follow-up of 9.7 years, 14,723 participants died. The lowest risks of death related to BMI were observed at a BMI of 25.3 for men and 24.3 for women. After adjustment for BMI, waist circumference and waist-to-hip ratio were strongly associated with the risk of death. Relative risks among men and women in the highest quintile of waist circumference were 2.05 (95% confidence interval [CI], 1.80 to 2.33) and 1.78 (95% CI, 1.56 to 2.04), respectively, and in the highest quintile of waist-to-hip ratio, the relative risks were 1.68 (95% CI, 1.53 to 1.84) and 1.51 (95% CI, 1.37 to 1.66), respectively. BMI remained significantly associated with the risk of death in models that included waist circumference or waist-to-hip ratio (P<0.001). CONCLUSIONS: These data suggest that both general adiposity and abdominal adiposity are associated with the risk of death and support the use of waist circumference or waist-to-hip ratio in addition to BMI in assessing the risk of death.