Outcomes of colic treatment are of great interest to clinicians, horse owners and insurers. One commonly used criterion of success is the overall short-term survival rate. This is used as to compare treatments and to measure quality of veterinary care, but may be biased by demographic or social factors such as attitudes towards animal suffering and euthanasia. The aims of this study were to 1) describe and analyse characteristics in horses with signs of colic referred to the University Hospital for Large Animals (UHLA), University of Copenhagen, Denmark over a 10-year period and 2) to compare these rates with those published in other comparable studies.The overall survival rate for colic horses over the 10-year study period was 68% : 66–71%; 1087/1588). In the medical group, 1093 horses, short-term survival was 87% (CI: 85–89%). Thirty one % of referred horses were given diagnoses requiring surgical intervention (CI: 29–33%). In this group 32% of the horses were euthanized before surgery . Of the surgical cases 27% (CI: 23-31%) were euthanized or died during surgery. Of the horses that recovered from surgery 25% died or were euthanized , while 75% survived to discharge (CI: 68–81%).The short term survival rates of Danish horses with colic were similar or lower to those reported from other countries. Apart from variability of veterinary care, attitudes towards euthanasia vary among the countries, which may bias the outcomes. This study indicates that qualitative interview studies on owners’ attitudes towards animal suffering and euthanasia need to be conducted. Our opinion is that survival rates are not valid as sole indicators of quality of care in colic treatment due to selection bias. If the survival rates are to be compared between hospitals, techniques or surgeons, prospective studies including mutually agreed-on disease severity scores and a predefined set of reasons for euthanasia are needed. This paPrior to hospitalization at UHLA, the horses had been examined by a referring veterinarian on one or several occasions. Medical records from 1st January 2000 and 31st December 2009 of all horses suspected to have colic aged >1 year were reviewed and variables relating to the history and signalment of the horse ; for diagnosis and treatment of the colic ; and for outcome  were extracted. To improve consistency of assignment of data the consensus decisions of three authors  reviewing the hospital records together were used. When they disagreed, the decision of the first author of the study was used. Inclusion criteria were: gastric reflux and signs of abdominal discomfort or pain ; with or without peritoneal fluid abnormality or rectal palpation abnormalities. Horses either dead or moribund on arrival to the hospital were excluded, as were horses with a primary diagnosis of oesophageal obstruction, diarrhoea without signs of colic, gastric ulcers without signs of colic, or inguinal, diaphragmatic or umbilical hernia. For horses with more than one hospitalization due to colic and horses with re-laparotomy due to colic, only the first time was included. Decisions on surgery were made by the surgeon on call. Generally, however, they were based on two or more of the following criteria: persistent gastric reflux of more than 2 L, refractory to pain management, absence of borborygmi, findings on rectal palpation consistent with volvulus, cardiovascular and systemic abnormalities, elevated plasma lactate concentration, peritoneal fluid with protein concentrations > 25 g per L and/or abnormal contents such as white blood cells or haemolysis. Horses not fulfilling the criteria for surgery were treated medically. If a decision was changed from medical to surgical treatment during hospitalization, only the final assignment was recorded. To describe the hospital population as a whole, data on the age, breed  and gender of all horses admitted to the UHLA during the period 2005–2009 were obtained from the medical record. The client communication records were screened for qualitative information on the decisions made. Statements on owner’s preferences were noted before, during and after colic surgery.We compared our results with a number of other studies selected by applying the following criteria: all colic horses admitted to a university hospital during a certain period were included; a large proportion of horses were referred cases; medical, surgical, dead and euthanized cases could be identified; and the specific short-term survival and mortality rates for medical and surgical colic cases could be calculated. For ease of comparison, the data of the present study were included as "UHLA".2) or Fishers exact test, as were comparisons with other studies. All levels of significance were set to p < 0.05.The number of horses surviving to the point of discharge in the medical and surgical group was used to calculate overall short-term survival rates. In the surgical cases this rate was calculated as the number of horses that underwent surgery divided by the number of horses discharged from the hospital. Mortality for horses in the surgical group was noted at several critical control points: pre-operatively, intra-operatively and post-operatively. Descriptive parameters were evaluated non-statistically. Survival rate percentages, standard error (SE) and 95% confidence intervals (CIs) were calculated using R 3.0.0 for Windows. A test for normality of age distribution was conducted using the D’Agostino and Pearson omnibus test. Age distribution was assessed using the Z test. The variables gender and breed distribution were tested using Chi-square . The number of horses allocated to medical and surgical treatment and the subsequent outcomes are shown in Figure Short-term survival was grouped according to diagnosis Table . No statAmong the cited studies in Table This study is the first to report the short term survival rates for all horses with colic admitted to a Danish university hospital. The overall short term survival rate of 68% was similar to those in some studies,5-7 but Because surgical colic cases generally carry a higher risk of mortality than medical colic cases, the proportion between medical and surgical cases in a hospital influences the overall outcome of colic. Among the cited studies in Table et al.[et al.[Also, diagnosis, localization and type of lesion play a role for the prognosis. From Table et al. who founet al. identifi[et al. obtainedIn the present study the single largest risk for mortality was euthanasia, since 59% of all horses recommended for surgery were euthanized, either before surgery or on the operating table, and 159 (10%) of the horses were euthanized without the recommended surgical treatment. From the owner information record and the medical record it appeared that this was not necessarily the horses with the worst prognoses. In some studies it was not possible to distinguish between euthanasia and other causes of death, and it was not always possible to determine when the decision to euthanize was taken, and in particular whether it was made before or after a diagnosis had been made. One would expect a relationship between a high euthanasia rate and high surgical short-term survival rate if only the most severe cases were euthanized. Interestingly, there was no such relationship, suggesting again that the choice of euthanasia was not related to severity.et al.[The study showed that euthanasia is very complex factor affecting the use of survival as a success parameter. Wide vaet al. explicitThe present study shows that factors lying beyond the control of the clinician may influence the outcome of the hospital service. The continuous improvement of diagnosis, treatment and clinical skills requires a systematic approach, described as clinical governance,16. The In conclusion, this retrospective study of equine colic outcomes demonstrates that short-term survival rates were biased by the prevalence of euthanasia, and thus that it is difficult to use such rates as the sole criterion for evaluation of success. If survival rates are to be used as an indicator of the quality of care in colic treatment, and if they are to permit hospitals, techniques and surgeons to be compared, the use of disease severity scores and a predefined set of reasons for euthanasia will be needed in prospective studies.The authors declare that they have no competing interests.MTC participated in collection and verification of data, carried out descriptive statistics and drafted the manuscript. ND participated in collection of data and carried out descriptive statistics. CK participated in collection of data and carried out descriptive statistics. KSBS participated in collection of data and carried out descriptive statistics. THP participated in the verification of the data and helped draft the manuscript. PHA conceived of the study, participated in its design and coordination, verification of data and helped draft the manuscript. All authors read and approved the final manuscript.


The CoPanFlu-France cohort of households was set up in 2009 to study the risk factors for infection by the pandemic influenza virus (H1N1pdm) in the French general population. The authors developed an integrative data-driven approach to identify individual, collective and environmental factors associated with the post-seasonal serological H1N1pdm geometric mean titer, and derived a nested case-control analysis to identify risk factors for infection during the first season. This analysis included 1377 subjects (601 households). The GMT for the general population was 47.1 : 45.1, 49.2). According to a multivariable analysis, pandemic vaccination, seasonal vaccination in 2009, recent history of influenza-like illness, asthma, chronic obstructive pulmonary disease, social contacts at school and use of public transports by the local population were associated with a higher GMT, whereas history of smoking was associated with a lower GMT. Additionally, young age at inclusion and risk perception of exposure to the virus at work were identified as possible risk factors, whereas presence of an air humidifier in the living room was a possible protective factor. These findings will be interpreted in light of the longitudinal analyses of this ongoing cohort. Since the novel influenza A/H1N1 pandemic virus (H1N1pdm) started spreading in April 2009, several studies have identified risk factors for H1N1pdm infection in the community such as young age The CoPanFlu-France cohort, which has previously been described elsewhere Inclusion of households started in December 2009, at the end of the first H1N1pdm season in metropolitan France. We studied factors associated with the post-pandemic H1N1pdm titer from blood samples collected at inclusion. Previous studies showed that post-pandemic titer was linked to age classes This study relies on 601 households (1450 subjects) included in the study between December 2009 and July 2010, according to a stratified geographical sampling scheme in the French general population. More details on this sampling procedure, the representativeness of the sample and the global study design are available in a previous publication During the inclusion visit, nurses collected detailed data from all subjects with questionnaires and blood samples for serological analyses. As 73 of these samples (5.0%) were either too difficult to obtain  or of insufficient quality or quantity to be analyzed, the analyses presented here focused on the 1377 subjects for whom haemagglutination inhibition (HI) titer was measured.The outcome measure was the post-seasonal HI titer, measured from blood samples collected at inclusion. A standard HI technique was adapted to the detection and quantification of antibodies to H1N1pdm. HI assay was conducted in a Bio-Safety Level 3 laboratory using 5.33 haemagglutinating units of non-inactivated antigen Though some authors previously carried out risk factors analyses after defining cases as subjects with HI titer ≥1/40 All covariates used in the analysis are listed elsewhere Some quantitative covariates were either dichotomized or log-transformed to enhance log-linearity of the studied relation . Age was studied as a quantitative covariate. Subjects reported medical history and vaccinations with the help of their health records. We defined history of ILI as fever ≥37.8°C and cough and/or sore throat without another known cause A contact was defined as someone the subject either spoke with (at least 3 words) or had a physical contact with. All subjects reported meetings with their contacts during a 3-day period ending the day before inclusion. Duration and location of meetings were collected, as well as age of contacts. In order to study meetings as covariates likely to be associated with the HI titer, we summed the individual durations of daily meetings according to their location  and to the age of contacts respectively. Summed durations of meetings were log-transformed . No information was collected on simultaneity of meetings, and the total reported duration of meetings was additional .All collected covariates likely to be associated with post-seasonal elevated HI titer were studied. Comparison tests between subgroups were Fisher's exact test  and Kruskal-Wallis rank sum test (for continuous covariates).GMTs were estimated for HI assays with the use of regression models for interval-censored data We defined the “GMT ratio” (GMTR) as the multiplicative factor between the GMT in exposed versus non-exposed (for a binary covariate) or for each unit increase (for a quantitative covariate).As age and pandemic vaccination status had an important impact on the serological titer, GMTR was systematically adjusted on these major confounders in all univariable analyses. For analyses regarding environmental characteristics of the bedroom and of the IRIS, correlations were considered at these two levels respectively. Analyses of contacts were adjusted on the proportion of weekend days in the 3-day period.Risk factors for infection were studied with the use of alternating logistic regression to model the pairwise odds ratios (ORs) between responses of subjects living in the same room, the same household or the same IRIS The same selection process was used for both analyses. GMTRs and ORs were estimated for all covariates individually. Since a large number of covariates were tested, we adjusted the p-value to control the alpha inflation associated with multiple hypothesis testing and to account for the false discovery rate (FDR) for all covariates P<0.30 in univariable analyses were included in a multivariable analysis. Thirty datasets were imputed via multiple imputations by chained equations (MICE) All covariates with an adjusted P<0.05 for all covariates.The criterion for model selection was the mean residual sum of squares with 10-fold cross-validation – aimed at avoiding overfitting and controlling FDR – run over the 30 imputed datasets and considering only models with Resulting coefficients and standard errors were combined to obtain the reported results Statistical analyses were performed with R version 2.15. We estimated GMTRs with the function “survreg” . Multiple imputation was done with the package “mice” and we ran alternating logistic regression with the package “orth”.Characteristics of the 1377 subjects are given in Tables S1–S6 in P<0.0001). Nine hundred and thirteen subjects (66.3%) were living in a house and the median area per inhabitant was 36.7  m2.The proportion of pandemic vaccine recipients was 12.2%. The median time since pandemic vaccination was 3.2  months. Pandemic vaccine recipients were younger than seasonal vaccine recipients: 46.4  vs. 63.8  years  and the median summed duration was 963  mn/day, with significant differences according to age groups and locations . SubjectRaw measured HI titer was ≥1/20 for 1319 subjects (95.8%), ≥1/40 for 832 subjects (60.4%), ≥1/80 for 259 subjects (18.8%) and ≥1/160 for 50 subjects (3.6%). After post-stratification the estimated proportions were 95.3% for ≥1/20, 59.0% for ≥1/40, 16.1% for ≥1/80 and 2.8% for ≥1/160.The estimated GMT for the general population was 47.1 : 45.1, 49.2]) It was higher in pandemic vaccine recipients  vs. 44.2  for unvaccinated subjects with no history of ILI and 58.7  for unvaccinated subjects with history of ILI) and in subjects aged ess than 5 years  vs. 45.7  for older ones). P<0.30 were retained in the multivariate analysis.All univariable GMTR estimates are listed in Tables S1–S6 in Selected multivariable models are listed in Considering the 1,207 subjects without pandemic vaccination, “asthma” was the only covariate that did not remain in the final model. Considering the 171 pandemic vaccine recipients, history of ILI remained in the model, while older age at inclusion and time since pandemic vaccination were associated with a lower GMT.P<0.0001). The final multivariable model retained (i) COPD, asthma, duration of meetings at school, proportion of workers using public transports and belief that not going to work protects against H1N1pdm as factors associated with a higher risk of probable infection, and (ii) older age and having an air humidifier in the living room as factors associated with a lower risk , or by any combination of these different factors. We review our findings in light of other studies on the same topic.The global multivariate model including pandemic vaccination gave information on the association of this factor with the GMT. Adjustment on this factor in the same model allowed us to study factors that may have an impact on GMT increase after either vaccination or infection, whereas stratified analyses according to this vaccination intended to focus more specifically on factors associated with other causes of elevated GMT.We found a lower anti-H1N1pdm GMT in older subjects in the univariable analysis and in the multivariable model run among pandemic vaccine recipients. This covariate did not remain in the other multivariate models mainly because of the adjustment on duration of contacts at school . Older age was also associated with a lower risk of probable infection in the case-control analysis.These results are consistent with other cross-sectional post-pandemic studies worldwide, including modeling As expected, a reported history of ILI was associated with an elevated GMT, which indicates that some of these ILIs were probably caused by H1N1pdm infection. Though this factor lacks sensitivity and specificity to be considered as a good correlate of infection, its coefficient in selected multivariable models gives more information on the relative role of infections among all causes leading to a GMT increase. Its association with the GMT in vaccinated subjects indicates that the GMT was also caused by H1N1pdm infections. Indeed, as most vaccinations occurred at the end of the pandemic course , we coulAsthma and COPD were associated with a higher GMT and possible risk factors in the case-control analysis. Asthmatics may have increased susceptibility for H1N1pdm infection We found that smoking history was associated with a lower GMT. Although several studies already found an association between cigarette smoking and risk to contract influenza infection Seasonal vaccination for any season since 2006–2007 was associated with an increase in the GMT, maybe because of a cross-reactive immune response with seasonal vaccination H1N1 strains In covariates related to the environmental characteristics of the housing, only the association between presence of an air humidifier in the living room and lower risk remained in the case-control multivariable model, which may be consistent with the possible impact of relative humidity on influenza aerosol transmission The multivariable analysis retained no covariate related to attitudes, beliefs and risk perception, except the belief that not going to work may protect against H1N1pdm infection, associated with a higher risk in the case-control analysis. We have no clear interpretation for this finding, except that this covariate may be a correlate of more general characteristics of risk perception, which affect the transmission patterns of pandemic influenza.Increasing GMT and a higher risk of probable infection associated with duration of meetings at school were not surprising since schools are identified as places with high meeting rates between influenza susceptible subjects The multivariable analysis retained no covariate related to the characteristics of the surrounding area, except the proportion of workers using public transportation to go to work, which also appeared as a possible risk factor.The important pairwise OR we found in the case-control analysis for subjects living in the same household suggests a common environmental exposure or susceptibility for these subjects who often belong to the same family, or more probably an elevated intra-household secondary attack rate , duration of meetings at school , characteristics of the local population or risk perception. Additional data is being collected and analyzed in this ongoing cohort. The longitudinal analysis of these households will permit integrative analyses of complex phenomena such as individual, collective and environmental risk factors for infection, routes of transmission, or determinants of the immune response to infection or vaccination.File S1Tables S1–S6. Description and univariable analyses for all covariates.(DOC)Click here for additional data file.File S2Tables S7 and S8. Multivariable models for the case-control analysis of risk factors for probable infection in CoPanFlu-France unvaccinated subjects: sensitivity analysis.(DOC)Click here for additional data file.


P > 0.05). In conclusion, in coiled cerebral aneurysms MRA with application of the threefold Roy classification is well suited for detecting or excluding sac residuals that might require retreatment.This meta-analysis summarizes the accuracy of magnetic resonance angiography (MRA) for diagnosing residuals in coiled cerebral aneurysms by using the threefold Roy classification . Four databases were searched from 2000 to June 2013 for eligible studies that compared MRA to digital subtraction angiography (DSA) and reported 3 × 3 count data of threefold Roy classification, or a reduced scheme of 2 × 2 count data. Bivariate and trivariate Bayesian random-effects models were used for meta-analysis. Among 27 included studies  the average prevalence of DSA-confirmed sac residuals was 18.2 % (range 0–43 %). The pooled sensitivity was 88.0 % (95 % CI 81.4−94.0) and specificity was 97.2 % (94.6−99.0 %) for assessing sac residuals by MRA. In the trivariate meta-analysis, a “sac residual” finding at MRA had a high positive likelihood ratio of 28.2 (14.0–79.0). A “neck residual” finding had a moderate negative likelihood ratio of 0.246 (0.111–0.426), and the MRA finding of “no residual” had a good negative likelihood ratio of 0.044 (0.013–0.096). Subgroup analyses identified no significant influence of covariates on diagnostic accuracy (The online version of this article (doi:10.1007/s00415-013-7053-5) contains supplementary material, which is available to authorized users. Cerebral aneurysms can cause substantial morbidity and mortality, especially if they rupture, leading to non-traumatic subarachnoid haemorrhage . SymptomFollow-up of coiled cerebral aneurysms has been traditionally performed by digital subtraction angiography (DSA), the diagnostic reference standard . MagnetiThe purpose of the present meta-analysis was to determine the diagnostic accuracy and predictive value of MRA for assessing flow residuals in coiled cerebral aneurysms compared to DSA, by applying bivariate and trivariate statistical approaches, and by including primary studies that have not been meta-analyzed before.This work applied the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA guideline) without prepublication of the review protocol , 21.The PubMed, Scopus, Biosis and ISI databases were searched for “coiled cerebral aneurysm”, “MRA”, “DSA”, and related terms from January 2000 to June 2013 without language restriction (Online Table e1). Reference lists of retrieved articles were also searched.Two observers independently selected eligible studies with disagreement solved in consensus. The inclusion criteria were: (a) the patients harbored one or more cerebral aneurysm(s) treated with detachable coils; (b) the study included at least 10 coiled aneurysms and was not limited to specific aneurysm sizes or locations; (c) MRA, the index test, was performed with one or more of these sequences: time-of-flight (TOF-MRA), contrast-enhanced TOF (ceTOF-MRA), and/or contrast-enhanced T1-weighted (CE-MRA); (d) DSA was the reference standard; (e) 3 × 3 count data of the Roy classification, or 2 × 2 count data of the “any residual” or “sac residual” assessment could be reconstructed. A study was excluded if it did not meet all of these inclusion criteria. If a research group reported growing experience in successive publications, then only the most recent publication was included to avoid duplicate counting of findings.Data from included studies were independently extracted by two observers using electronic forms, with disagreement solved in consensus. Extracted study characteristics comprised details about study design, patients, MRA, and DSA. Count data were extracted on a per-aneurysm basis. Some additional data were obtained from the study authors via e-mail.On the study level, the methodological quality and sources of bias were assessed by the 14 quality items of the QUADAS tool . Item 4 If any study had investigated more than one MRA sequence, the according raw 2 × 2 or 3 × 3 count data were averaged to obtain one contingency table per study. Such averaging was not performed for subgroup analyses that investigated differences among the MRA sequences.Q-test and I-squared statistics of between-study heterogeneity were calculated by the freeware program Meta-DiSc . Twelve studies reported the aneurysm size before coiling in millimeter categories . About 29 % of them were small (up to 4 mm), 46 % medium-sized (5–10 mm), and 25 % large (≥11 mm). Six studies reported 2 × 2 count data exclusively of the “any residual” assessment (Roy class 1 versus classes 2 + 3) in 566 aneurysms. The other 21 studies provided 3 × 3 count data in 1,553 aneurysms. Among these 21 studies, DSA showed on average 53.8 % complete occlusions (range 14–91 %), 28.0 % neck residuals (range 4–68 %), and sac residuals 18.2 % (range 0–43 %). In most cases, follow-up was performed 3–24 months after coiling. Twelve studies compared two or more different MRA sequences to DSA. In total, 1,365 coiled aneurysms were studied by 1,216 TOF-MRA, 232 aneurysms by 206 ceTOF-MRA, 660 aneurysms by 569 CE-MRA, and 503 aneurysms by 460 MRA with mixed sequences. About 72 % of MRA were performed at 1.5 Tesla and 28 % at 3.0 Tesla. In most studies the MRA readers were blinded to the DSA results, and vice versa . Further descriptive data are provided in Table e-4 (study characteristics) and Table e-5 (reasons for exclusion of patients/aneurysms from the primary studies).P = 0.44). The between-study heterogeneity was low to moderate .The study quality was generally high . The funnel plot and regression test indicated no significant publication bias  for the bivariate “any residual” assessment, 0.74 (0.63–0.77) for the bivariate “sac residual” assessment, and 0.64 (0.49–0.93) for the trivariate assessment, indicating moderate to good inter-observer agreement. Five of these studies compared TOF-MRA versus CE-MRA and/or compared MRA at 1.5 versus 3.0 Tesla . Among these studies, the according interobserver reproducibility showed no consistent trend in favor of a certain MRA technique.For the individual studies, 2 × 2 count data of the “any residual” and “sac residual” assessment and corresponding estimates of sensitivity and specificity are given in Table e-6. Table e-7 provides trivariate 3 × 3 count data of the Roy classification.Diagnosing “any residual” (neck or sac) by MRA showed a pooled sensitivity of 89.0 %  and specificity of 89.0 % (82.6−94.0 %) (Table 1 = 0.044) was below 0.1, indicating this finding’s suitability for excluding sac residuals. The negative likelihood ratio of “neck residual at MRA” (LRN2 = 0.246) was above 0.1, indicating limited value of that intermediate finding for excluding sac residuals. Corresponding trivariate conditional probabilities are presented in Fig. 2) of about 94.7 %, and is therefore still a useful finding  of cases, whereas underestimation occurred in 5.6 % (3.5–8.0 %) and overestimation in 7.6 % 3.7–12.9 %) of cases. It was rare that MRA deviated from DSA by two classes, i.e. that MRA indicated “no residual” in a DSA-confirmed sac residual (2.7 %) or a “sac residual” in a DSA-confirmed occluded aneurysm (1.7 %). The positive likelihood ratio (LRP = 28.2) of “sac residual at MRA” was above 10, indicating the suitability of MRA for detecting true sac residuals. The negative likelihood ratio of “no residual at MRA” (LRN.9 % of cP > 0.05). This referred to MRA sequence (TOF-MRA versus CE-MRA), field strength (1.5 versus 3.0 Tesla), number of MRA readers (1 versus 2–3), and several other covariates (Table e-8). The 19 included prospective studies showed results similar to those reported in Tables The subgroup analyses showed no significant differences in diagnostic accuracy  , 16. It The reported per-aneurysm results approximately represent per-patient results, since most patients had a single coiled aneurysm. DSA showed on average 53.8 % complete occlusions (Roy class 1), 28.0 % neck residuals (class 2), and 18.2 % sac residuals (class 3). MRA correctly assessed about 86.8 % of cases, and over-/underestimated 8.8 % of cases by one Roy class. Over-/underestimation by two classes was more rare (4.4 %).Differentiating neck and sac residuals is clinically relevant, since about 50 % of sac residuals are retreated, whereas neck residuals are generally not retreated , 10. NecThe simple bivariate “any residual” assessment  might indicate just moderate diagnostic accuracy of MRA for aneurysm residuals. However, in that assessment the sac and neck residuals are summed to one group, although having different therapeutic implications. The according statistical results are therefore clinically less meaningful than the bivariate “sac residual” assessment or the more detailed trivariate assessment.The refined bivariate “sac residual” assessment  shows a high specificity, i.e. the number of false-positive sac residual findings at MRA is small. Accordingly, the positive predictive value is nearly similar to the trivariate assessment. However, the bivariate “sac residual” assessment does not differentiate the predictive value of the Roy classes 1 and 2.The trivariate meta-analytic assessment is considered to be the best approach, since it fully accounts for the 3×3 data of the Roy classification. In the trivariate meta-analysis, the finding of “no residual at MRA” showed a good negative likelihood ratio (mean 0.044) for ruling out a true sac residual. Among the studies the mean prevalence of sac residuals was 18.2 %, and at this prevalence an MRA finding of “no residual” truly excludes a sac residual in 99.0 % of cases, obviating the need for additional DSA. In aneurysms with adequate occlusion 6 months after coiling (those <10 mm and not located on the basilar tip), prolonged imaging follow-up seems unnecessary, since late reopening with need of retreatment is very rare .The intermediate finding of “neck residual at MRA” had only a moderate negative likelihood ratio mean 0.246) for ruling out a true sac residual. However, the according predictive value depends on the pretest probability, as visualized in the graph of conditional probabilities , and is therefore well suited for detecting a true sac residual. DSA may then be subsequently performed to exclude some false-positives, and to evaluate retreatment in the approximately 87.9 % of cases with true sac residuals , 10. HowSome primary studies had found differences in diagnostic accuracy among different MRA methodologies. However, on the meta-analytic level the according subgroup analyses showed no consistent significant differences. For example, MRAs with 1.5 Tesla magnets generally performed similar to 3.0 Tesla. Additionally, double-reading of MRA is not mandatory, since single-reading has similar diagnostic accuracy, if performed by an appropriately trained radiologist. The accuracy of TOF-MRA was not significantly different from contrast-enhanced MRA. While the former requires more acquisition time than the latter, it saves on the costs of contrast medium and avoids the small potential risks of contrast medium in patients with renal failure.Two previous meta-analyses summarized findings in about 800–880 coiled aneurysms from studies published between 1997 and 2006 , 19. OurThis meta-analysis has some limitations. MRA after stent-assisted coiling was not meta-analysed, since according publications are currently too few –44. ThisIn conclusion, non-invasive MRA with application of the threefold Roy classification is well suited for assessing flow residuals in coiled cerebral aneurysms. A “sac residual” finding at MRA should be confirmed by catheter angiography to exclude false-positives and to possibly retreat the true-positives. A “neck residual” finding at MRA should be followed up further. An MRA finding of “no residual” generally requires no confirmation by DSA.Supplementary material 1 (PDF 270 kb)Below is the link to the electronic supplementary material.


Previous studies have reported the lower reference limit (LRL) of quantitative cord glucose-6-phosphate dehydrogenase (G6PD), but they have not used approved international statistical methodology. Using common standards is expecting to yield more true findings. Therefore, we aimed to estimate LRL of quantitative G6PD detection in healthy term neonates by using statistical analyses endorsed by the International Federation of Clinical Chemistry (IFCC) and the Clinical and Laboratory Standards Institute (CLSI) for reference interval estimation.This cross sectional retrospective study was performed at King Abdulaziz Hospital, Saudi Arabia, between March 2010 and June 2012. The study monitored consecutive neonates born to mothers from one Arab Muslim tribe that was assumed to have a low prevalence of G6PD-deficiency. Neonates that satisfied the following criteria were included: full-term birth (37 weeks); no admission to the special care nursery; no phototherapy treatment; negative direct antiglobulin test; and fathers of female neonates were from the same mothers’ tribe. The G6PD activity (Units/gram Hemoglobin) was measured spectrophotometrically by an automated kit. This study used statistical analyses endorsed by IFCC and CLSI for reference interval estimation. The 2.5th percentiles and the corresponding 95% confidence intervals (CI) were estimated as LRLs, both in presence and absence of outliers.207 males and 188 females term neonates who had cord blood quantitative G6PD testing met the inclusion criteria. Method of Horn detected 20 G6PD values as outliers . Distributions of quantitative cord G6PD values exhibited a normal distribution in absence of the outliers only. The Harris-Boyd method and proportion criteria revealed that combined gender LRLs were reliable. The combined bootstrap LRL in presence of the outliers was 10.0 (95% CI: 7.5-10.7) and the combined parametric LRL in absence of the outliers was 11.0 (95% CI: 10.5-11.3).These results contribute to the LRL of quantitative cord G6PD detection in full-term neonates. They are transferable to another laboratory when pre-analytical factors and testing methods are comparable and the IFCC-CLSI requirements of transference are satisfied. We are suggesting using estimated LRL in absence of the outliers as mislabeling G6PD-deficient neonates as normal is intolerable whereas mislabeling G6PD-normal neonates as deficient is tolerable. Glucose-6-phosphate dehydrogenase (G6PD) deficiency is a common X-linked recessive enzymopathy . GenotypWe conducted this cross sectional retrospective study at King Abdulaziz Hospital (KAH) in the Al-Ahsa area of the Eastern province of Saudi Arabia. Since 2009, KAH has been accredited by the Joint Commission of International Accreditation and its laboratory has been accredited by the College of American Pathologists, which implements the CLSI standards in its accreditation checklists.In early 2008, KAH began universal cord blood screening for G6PD deficiency coupled with direct antiglobulin testing and blood grouping . A semi-Just after delivery of the placenta, whole cord blood was collected in ethylenediaminetetraacetic acid (EDTA) Vacutainer tubes . Blood specimens were transported to the laboratory by pneumatic tubes. Quantitative G6PD activity measurements were performed in batches every morning, 7 days a week, with blood samples stored in the vertical position at 2–8 degree Celsius (°C) until analysis. The principal method of the Udilipse kit is in accordance with the standardized WHO method for G6PD assay of the hemolysate at 25°C outlined as follows [The reagents of this kit are outlined as follows:Reagent 1 (G6PD Buffer): Ready to use 50 micromolar (mM)/Liter triethanolamine buffer, 5 mM/Liter EDTA, pH 7.6 ± 0.05 (25°C).Reagent 2 (G6PD NADP): Reconstituted 30 mM nicotinamide adenine dinucleotide phosphate (NADP).Reagent 3 (G6PD Substrate): Reconstituted 17 mM Glucose-6-Phosphate Sodium.Reagent 4 (G6PD Lysis): Ready to use 0.2% Saponin aqueous solution.Hemolysate was prepared according to the manufacturer’s manual for the Udilipse kit by adding a well-mixed 100 microliters of whole blood to 400 microliters of 0.2% Saponin. The G6PD activity was measured within one hour of hemolysate preparation. The activity of the G6PD enzyme is measured by the rate of NADPH formation, which is measured spectrophotometrically by means of the increase in extinction at 340, 334 or 365 nanometer. As the Udilipse kit only measures G6PD activity, hemoglobin was measured spectrophotometrically on the same sample by CELL-DYN Sapphire . Then, the values of G6PD activity and hemoglobin were entered and stored in Cerner Lab Information System Software , which is already programmed to express the G6PD activity in U/g Hb by dividing the obtained G6PD activity by the obtained hemoglobin values.- (WHO class III) represents 5.8% [The IFCC-CLSI recommends estimating RLs from a healthy population ,25. In onts 5.8% ,31. G6PDnts 5.8% -34. A rents 5.8% . Therefonts 5.8% . HencefoThe reference sample group was identified from the delivery room log book via the mothers’ names. It consisted of all consecutive neonates born to mothers from the reference tribe between March, 2010 and June, 2012 that satisfied all the following posteriori inclusion criteria: 1) full-term (37 weeks of gestation); 2) roomed in with mothers and were not admitted to the special care nursery; 3) no phototherapy treatment during the neonatal period; 4) negative direct antiglobulin test; and 5) fathers of female neonates were from the reference tribe. For male neonates it does not matter whether the father is from the reference tribe or not, but it does matter for female neonates as the G6PD is inherited as X-linked recessive. Thus, only copies of birth notices of female neonates were reviewed to ascertain that both parents were from the reference tribe. At KAH, birth notices that include the full name of both parents are issued upon home discharges and copies of these birth notices are stored in hard and electronic medical records of neonates. We selected only full-term neonates as we did not expect to have an adequate number of preterm neonates of the reference sample group during the study period and as G6PD values have been shown to be higher in preterm neonates <34 weeks of gestation ,36,37. GWe performed statistical analyses as endorsed by the IFCC- CLSI ,25. The The IFCC-CLSI suggests detecting outliers by Tukey’s boxplot for unskewed data and by method of Horn for skewed data. The method of horn uses Tukey’s boxplot on Box-Cox transformed data . AlthougP value > .05 for skewness coefficient, kurtosis coefficient, and the Anderson-Darling or Shapiro-Wilk tests [Data extraction and entry of the outliers were double-checked. It was difficult to ascertain whether these outliers were due to G6PD mutations or to pre-analytic errors as these values were not cross-referenced with molecular testing. Assuming that the reference tribe is in Hardy-Weinberg equilibrium, the Hardy-Weinberg equation was used as a surrogate to determine whether these outliers represent G6PD mutations ,44. The lk tests ,47. The lk tests . The Shalk tests .The IFCC-CLSI recommends excluding values from unhealthy individuals and estimating the LRLs from healthy individuals only ,25. Thust-test assuming equal variances or Mann–Whitney U test was used to compare differences between male and female neonates’ continuous variables when appropriate. The two-sample t-test assuming unequal variances was used to compare means of this study with those of previous studies. The one-sample Wilcoxon signed rank test was used to compare medians of this study with hypothetical values equal to medians of previous studies. A two-sided P value < .05 was considered statistically significant. Data analysis was performed using the RefVal 4.11, IBM SPSS Statistics 20 , and OpenEpi 2.2.1 programs.The binomial test was used to compare the observed frequencies of male and female neonates. The two-sample Figure The combined gender reference sample group had a mean (SD) birth weight of 3281 (452) grams and a mean gestational age of 39.6 (1.3) weeks.The G6PD values among the males had no significant skewness (0.07). The SPSS syntax indicated that the original data had the lowest skewness. Thus, Tukey’s boxplot was performed on their original values Figure . Both thThe G6PD values among the females had significant negative skewness -0.93), thus, Tukey’s boxplot was performed on their Box-Cox transformed values (Method of Horn). The SPSS program indicated that a lambda of 1.84 is the best. The Box-Cox transformed G6PD values had a skewness of -0.003. Both the RefVal and SPSS programs detected exactly the same12 (6.4%) G5PD values as outliers among the females . Assuming that the frequency of mutated G6PD alleles among males is 0.039 , the Hardy-Weinberg equation revealed that the expected number of both heterozygous and homozygous females would be 14, nearly the same as number of the detected outliers (P = .87).The histograms Figures  and 5, mTable After the outliers were excluded, LRLs were estimated from cord blood samples of 375 neonates . The histograms Figures  suggesteTable Table The present study estimated the LRLs of quantitative cord G6PD using standard statistical methods endorsed by the IFCC-CLSI for establishing RIs ,25. The Reference limits are the cornerstones of interpretation of quantitative cord G6PD activity measurements. Standardization of statistical analysis for RI estimation is critical and is enabled by the IFCC-CLSI’s endorsement of a standard statistical analysis for RI estimation ,25. Yet,Our observed gaps in G6PD values of males confirmed the findings of others ,13,16,54Our observed gap in the cord G6PD values of females has not been reported before. It is rather contradicting that G6PD values of females are continuum as heterozygotes may express a spectrum of values; normal, intermediate, and deficient ,56. The Comprehensive normal distribution testing in the present study showed that the distribution of quantitative cord G6PD exhibited a normal distribution only in absence of the outliers. Previous studies that have run limited normal distribution testing diverge on the normal distribution of G6PD values. The G6PD values exhibited a normal distribution in the study by Boo et al. but a non-normal distribution in the study by Fok et al. ,8. The fOutliers are known to skew statistical tests based on sample means and variances, making it strongly advisable to detect outliers before performing these tests. Thus, it was not surprising that presence of these outliers widened the 95% CIs and distorted the homogeneity and the normal distributions, particularly for the combined gender group where even the two-stage transformation did not yield a normal distribution. The IFCC-CLSI emphasizes retaining outliers unless they are due to human or laboratory errors or representing unhealthy individuals. Retrospective nature of study precludes ascertaining whether or not these outliers were due to human or laboratory errors. However, there were three evidences suggesting that the outliers in the present study might be due to G6PD mutations. First, the frequencies of these outliers were in Hardy-Weinberg proportions. Second, presence of gaps between some of these outliers and the rest of presumed normal G6PD values. Third, a recent study from Jeddah area of western Saudi Arabia that found all the 20 female neonates with a cord G6PD value 6.6 U/g Hb subjected to molecular testing were G6PD- deficient . Howevert-test assuming equal variances and Mann–Whitney U test also showed that G6PD levels were similar in male and female neonates. This is logic and consistent with the fact that the LRL was estimated from non-G6PD deficient neonates, as normal males and females should have the same G6PD values [We are suggesting using estimated LRLs in absence of the outliers for three reasons. First, the outliers of the present study might be due to pre-analytic errors. Second, they might be due to G6PD mutations. Third, all estimated LRLs were higher in absence than in presence of the outliers. Increasing cut-off point of LRLs will increase their sensitivity at the expense of their specificity. This is quite acceptable as mislabeling G6PD-deficient neonates as normal is intolerable whereas mislabeling G6PD-normal neonates as deficient is tolerable . The parD values . ConsequD values ,36,37.Some laboratory professionals have advocated estimating the 5.0th percentile as the LRL when a one-sided RI is assumed . We elecThe IFCC-CLSI allow transferal of a reference limit from one laboratory to another when pre-analytical factors and testing methods are comparable in both laboratories and when one of their 3 validation methods is satisfied . One of Observed mean and median G6PD values were statistically significantly different from those reported in previous studies. The discrepancy could be due to differences in the timing of these studies, the ethnicities of the reference sample groups, gestational ages, G6PD kits and their reagents, and statistical strategies for LRL estimation Table . HoweverControversy exists as to whether G6PD activity should be expressed as U/g Hb or per number of RBCs. The WHO and some researchers have endorsed expressing the G6PD activity per number of RBCs to per U/g Hb, as the hemoglobin content may fluctuate independently of the G6PD activity, particularly when RBCs are hypochromic . Other rt-test assuming equal variances and Mann–Whitney U test also showed that G6PD levels were similar in male and female neonates.The present study has four limitations that should be noted. First, retrospective nature of the study precluded assuring that the grandmothers were form the reference tribe as their names were not printed in the birth notices. Nevertheless, we do not assume that prevalence of neonates of grandmothers who were not from the reference tribe was high enough to alter prevalence of G6PD deficiency in the reference tribe significantly. The intermarriages between the reference tribe and other tribes are not a familiar tradition. The intermarriages between Bedouin descents and urban descents rarely occurred. For instance, in the present study, 3 out of 222 (1.4%) female neonates were product of intermarriages between the reference tribe and other tribes that all were Bedouin descents. Second, reported LRLs were not cross-referenced with molecular testing, so a future study using molecular testing to verify these LRLs is warranted. Third, the G6PD activity was only expressed as U/g Hb, precluding comparison with other studies that expressed G6PD activity per number of RBCs . Fourth,The present study estimated the LRLs of cord G6PD activity using the standard method of statistical analysis endorsed by the IFCC-CLSI. We believe that we have included healthy neonates as we used stringent inclusion criteria and we included a reference group that has a low prevalence of G6PD deficiency. The results showed that the LRL of cord G6PD activity for full-term neonates of both genders is 11.0 U/g Hb and that this value is transferable to other settings when the IFCC-CLSI requirements of transference are satisfied. Further studies are warranted on LRLs for preterm neonates using the statistical standards of the IFCC-CLSI, cross-referencing the LRL with molecular testing, comparing methods of expressing cord G6PD activity, and comparing various commercial kits. Standardized statistical analysis and reporting of studies on RI estimation should be encouraged.KAH: King Abdulaziz Hospital; G6PD: Glucose-6-phosphate dehydrogenase; LRL: Lower reference limit; LDL: Lower decision limit; RI: Reference interval; IFCC: International federation of clinical chemistry; CLSI: Clinical laboratory standard institute; WHO: World Health Organization; u/gHb: Units/gram hemoglobin; RBCs: Red blood cells; FST: Fluorescence spot test; °C: Degree celsius; EDTA: Ethylenediaminetetraacetic acid; NADP: Nicotinamide adenine dinucleotide phosphate; IQR: Interquartile range; 95% CI: 95% Confidence interval.We do not have any conflicts of interest to disclose.SYA conceptualized and designed the study, double checked and cleaned data, performed the statistical analysis, drafted the initial manuscript, and approved the final manuscript as submitted. He had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. ASS contributed substantially to the designing the study, data collection, interpretation of this work, reviewed and revised, and approved the final manuscript as submitted. FLD contributed substantially to the designing the study, data collection, interpretation of this work, reviewed and revised, and approved the final manuscript as submitted. AAS contributed substantially to the designing the study, data collection, interpretation of this work, reviewed and revised, and approved the final manuscript as submitted. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2431/13/137/prepub


For complex diseases like cancer, pooled-analysis of individual data represents a powerful tool to investigate the joint contribution of genetic, phenotypic and environmental factors to the development of a disease. Pooled-analysis of epidemiological studies has many advantages over meta-analysis, and preliminary results may be obtained faster and with lower costs than with prospective consortia.MC1R) gene, SKin cancer and Phenotypic characteristics (M-SKIP) project, we describe the most important steps in planning and conducting a pooled-analysis of genetic epidemiological studies. We then present the statistical analysis plan that we are going to apply, giving particular attention to methods of analysis recently proposed to account for between-study heterogeneity and to explore the joint contribution of genetic, phenotypic and environmental factors in the development of a disease. Within the M-SKIP project, data on 10,959 skin cancer cases and 14,785 controls from 31 international investigators were checked for quality and recoded for standardization. We first proposed to fit the aggregated data with random-effects logistic regression models. However, for the M-SKIP project, a two-stage analysis will be preferred to overcome the problem regarding the availability of different study covariates. The joint contribution of MC1R variants and phenotypic characteristics to skin cancer development will be studied via logic regression modeling.Based on our experience with the study design of the Melanocortin-1 receptor (Methodological guidelines to correctly design and conduct pooled-analyses are needed to facilitate application of such methods, thus providing a better summary of the actual findings on specific fields. Since millions of Single Nucleotide Polymorphisms (SNPs) were identified by the SNP Consortium , a growiMeta-analysis of genetic epidemiological studies has been adopted to increase the power of smaller candidate gene studies by summarizing results from multiple studies. However the lack of access to individual data precludes in-depth investigations, including analyses of gene-gene and gene-environment interaction, and appropriate stratified analyses. This may potentially lead to false-positive or false-negative results, or biased magnitudes of associations, as previously pointed out .Pooled-analysis of the primary data has been shown to have critical methodological advantages over meta-analysis ,4 and haWe describe here our experience with the study design of an international pooled-analysis on Melanocortin-1 receptor gene, SKin cancer and Phenotypic characteristics (M-SKIP project). In the first part of the paper, we explain the procedures that were used to identify studies and to collect and standardize data. In the second part we describe the statistical analysis plan that we are going to apply, giving particular attention to methods of analysis recently proposed to account for between-study heterogeneity and to explore the joint contribution of genetic, phenotypic and environmental factors in the development of a disease.MC1R, MIM#155555) is one of the major genes that determine skin pigmentation and it has been reported to be associated with risk of melanoma [MC1R variants and melanoma also in darkly-pigmented European populations suggests that MC1R signaling may have an additional role in skin carcinogenesis beyond the UV-filtering differences between dark and fair skin [MC1R variants R151C, R160W, D294H, D84E and R142H, and suggested a possible role in melanoma development, via non-pigmentary pathways, for I155T and R163Q variants. However, the specific contribution of each MC1R variant to melanoma development via pigmentary and non-pigmentary pathways could not be evaluated in meta-analyses due to the lack of individually joint information on MC1R variants and phenotypic characteristics.Melanocortin-1-receptor  assess the association of MC1R variants with melanoma, basal cell carcinoma (BCC) and squamous cell carcinoma (SCC); 2) assess the association between MC1R variants and phenotypic characteristics, including hair and eye color, skin color, skin type, common and atypical nevi, freckles, and solar lentigines; and 3) perform stratified analyses on MC1R variants and skin cancer by phenotypic characteristics, and evaluate MC1R-phenotype interaction in skin cancer risk.The aim of the M-SKIP project is therefore to perform a pooled-analysis of individual data on sporadic skin cancer cases and controls with information on MC1R variants, melanoma, non-melanoma skin cancer (NMSC) and phenotypic characteristics associated with melanoma [Published epidemiological studies on melanoma ,22 were MC1R variant or 2) control series with information on any MC1R variant and at least one phenotypic characteristic under study. Permanent exclusion criteria were: 1) populations selected for MC1R status or for other genetic factors, 2) studies including only familial and/or multiple-primary melanoma cases, because we wanted to study MC1R-melanoma association at a population level, therefore excluding cases for whom the role of genetics is probably stronger. In the first step of the project, we also excluded genome-wide association studies (GWAS), because their different study design and genotyping methodology would significantly increase the heterogeneity of our data; however GWAS with epidemiological data would be included in a next step of the project and their results would be compared with those of classical genetic epidemiological studies.We selected papers according to the following inclusion criteria: 1) observational studies on single-primary sporadic skin cancer cases with information on any MC1R variants (N = 12), case reports, commentaries or reviews (N = 6), GWAS (N = 6), populations selected for genetic factors (N = 4) and multiple primary melanoma cases only (N = 1). The remaining 62 independent studies were considered eligible for inclusion in the pooled-analysis.The original search provided 748 papers, among them 111 were considered potentially interesting and full-text articles were retrieved and evaluated. We excluded 49 articles for the following reasons: duplicate populations (N = 20), no data on outcome (case/control status or any of the studied phenotypic characteristics) or on For each independent study, we identified the corresponding investigator and retrieved his/her contact information. Each investigator was invited to join the M-SKIP project: this required them to sign a participation form and a document attesting to approval of the study guidelines, and then to provide their data in electronic form without restrictions on format. A detailed list of variables relevant for skin cancer was provided and, for each available variable in the list, the authors were required to compile a form with a clear and complete description on how it was collected and coded. Investigators did not send any personal identifier with data, but only identification codes. Finally, investigators were asked to send a signed statement declaring that the original study was approved by an Ethic Committee and/or that study subjects provided a written consent to participate in the original study.Data collection started in May 2009 and was closed in December 2010. During this period, 43 investigators were contacted and invited to share data. Thirty-one (72%) agreed to participate and provided data on 28,998 subjects, including 13,511 skin cancer cases  and 15,477 controls from 37 independent published ,23-62 anMC1R variants (N = 1081), non-skin melanoma cases (N = 150), subjects with atypical mole syndrome and no skin cancer (N = 58), non first-primary melanoma cases (N = 24), familial melanoma cases, defined as subjects with two first-degree relatives or three or more any-degree relatives with melanoma (N = 25), other reasons including: unknown case/control status, duplicate subjects, or inappropriate controls (N = 232).We inspected the data for completeness and resolved inconsistencies with the investigator of each study. A number of subjects were excluded due to the following reasons: multiple-primary melanoma cases (N = 1596), missing data on MC1R variants were entered for each subject. Quality controls and data coding were performed independently by two investigators, and inconsistencies were solved via consensus.The following study-related variables were recoded uniformly: study country, study design, source of controls, application of case–control matching, methods to define phenotypic characteristics, genotyping methodology, whether genotyping was done in the same center for cases and controls and was blinded for case/control status, and DNA source. These variables were not used to assign a quality score to each study, but will be taken into account in meta-regression and sensitivity analyses. In addition, the variables listed in Table Some variables were collected in different ways in different studies. We report here as an example the rules we used to standardize sun exposure variables, in order to provide suggestions on how to recode variables with highly heterogeneous assessment among studies.Intermittent and continuous sun exposure was coded as hours of exposure per day if the information was structured in this way. If not, we converted it to hours/day on a scale of 0 as no exposure and 6 as the maximum hours of exposure per day. For example, for datasets with four classes of exposure , we recoded the classes as 0, 2, 4, 6 hours/day. If individual sun exposure was collected over different time periods, we calculated the average exposure weighting for years of exposure in each time period. Other continuous variables  were converted to hours/day using the following algorithm:1) calculate the variable mean on all the study subjects as:xi is the measure of the continuous variable on subject i, and n is the study sample size;where ν) over all the datasets with the variable coded (or recoded) in this way as in 1);2) calculate the average hours of exposure/day (3) recode each observation basing on the proportion 4) set as 6 (maximum hours of exposure per day) the value of all calculated values greater than 6.The assumption underlying this coding was that the average sun exposure pattern for study subjects was similar for different studies (and countries). Since we will use this variable only for confounding adjustment and/or effect modifier analyses, the purpose was to regroup subjects with a similar pattern of sun exposure, although the precise individual amount of sun exposure could not be estimated.As a general rule, when a variable (i.e. common nevi count) was collected into classes, we recoded each class by using its median. The maximum numbers for open categories were chosen according to the available M-SKIP data.The final dataset was created in June 2011 and included data on 7,806 melanoma cases, 3,151 NMSC cases , and 14,875 controls.Distribution of data according to study country in which the study was performed is presented in Table MC1R (67%) and used blood as DNA source (62%).The main characteristics of the studies included in the M-SKIP database are described in Table MC1R variant and melanoma assuming a similar association to that observed in our previous meta-analysis [MC1R variant, around 5,000 cases and 5,000 controls would be needed to observe a multiplicative interaction effect of 2.0, arising to 16,000 cases and 16,000 controls to observe a smaller multiplicative effect of 1.5, both with 90% statistical power. For common MC1R variants, the same gene-environment interaction effects of 2.0 and 1.5 could be observed with around 1,200 cases and 1,200 controls, and with around 3,500 cases and 3,500 controls, respectively. Our sample size therefore is appropriate for the purpose of the analysis, and large enough to allow stratified and interaction analyses, especially to find even small interaction effects with the most frequent variants, and larger interaction effects for less common variants.We calculated that the minimum required sample size to find a statistically significant association between a analysis   of study k  conditional on the presence of a certain MC1R variant (X). We will account for the fixed MC1R effect and the random selection of studies, assuming a model that relates MC1R and study effects linearly to the logit of the probabilities:A first analysis using data combined into one dataset, is to fit them with logistic regression models with random slope. Considering a dominant model, let β) is the odds of skin cancer for a subject with the MC1R variant compared with a subject without the MC1R variant, and the bk are the study-specific coefficients accounting for the random selection of studies, with bk ~ N, where σ2b represents the between study variance of the MC1R effect.In this model the transformed regression coefficient exp, controlling for confounders Zk. For study k , assuming just one confounder, the model is written as:First, study-specific ORs will be calculated by applying logistic regression to the data from each study to estimate the odds of skin cancer conditional on the presence of a πik is the conditional probability of skin cancer for subject i  of study k. Although MC1R variants were uniformly defined across studies, the confounders Zk may be specific to a particular study. Analyses with original covariates and with recoded data will be performed and compared. The exposure log-odds ratio for study k is denoted βk, the confounding log-odds ratio is denoted γk, and the αk are the study-specific intercepts. The βk are assumed to vary across studies according to the second-stage model:where β is the pooled-exposure log-odds ratio, bk are random effects with bk ~ N, where σ2b represents the variability of the study-specific exposure effects βk about the population mean β, and ek are independent errors with ek ~ N, where σ2k describes the within-study variation of the βk. In the first stage where β is a weighted average of the The two-stage estimator of the pooled exposure effect σ2b in equations 6 and 7. These methods are pseudo-maximum likelihood and moment estimation.Two methods  are freqHomogeneity among the study estimates will be measured by Q statistic and I-Square , the latMC1R variants with each skin cancer type will be performed for different phenotypic characteristics. The hypothesis of homogeneity of ORs among strata will be verified using the Breslow-Day test [Stratified analysis for the association of Day test .MC1R variants and phenotypic characteristics associated with each skin cancer type, we will perform logic regression, a recently proposed tree-based statistical method intended for binary predictors [X1, X2,…, Xp be the binary predictors obtained by dichotomization, and let Y be the binary response variable (case/control status). The appropriate logic regression model can be written as:In order to identify combinations of edictors . This apedictors  that in Lj is a Boolean expression of the predictors Xi, such as Lj that minimize the binomial deviance, with the parameters βj and the Boolean expressions Lj estimated simultaneously. The output from logic regression is represented as a series of trees, one for each Boolean predictor Lj, and the associated regression coefficient. An example of a logic tree that may be applied to our pooled analysis is shown in Figure where =X4C∧X5∨X∨X3C withMC1R variants and phenotypic characteristics mostly associated with skin cancer will be undertaken by a (stochastic) simulated annealing algorithm [The searching for the optimum combinations of lgorithm -106. Thilgorithm ,105.In an explanatory setting, at risk gene-phenotype combinations will be identified among a very large number of possible combinations by logic regression-based methods recently proposed ,107. TheMC1R variants on skin cancer by phenotypic characteristics.Structural equation models will be also applied to eventually clarify the independent and dependent role of Finally, the role of environmental exposure will be investigated by entering new covariates in the models, by subgroup analyses and by studying gene-environment and phenotype-environment interactions using traditional and new proposed methodologies .MC1R variants , as well as known rare mutations affecting MC1R function [MC1R variant alleles and of the scores obtained from appropriate classification of MC1R variants [In all the proposed analyses, each of the nine most frequently investigated function  will be function ,111, andvariants .Based on our experience with the study design of the M-SKIP project, we have described here the most important steps in planning, conducting and analyzing pooled individual data from genetic epidemiological studies. A previously published commentary highlighted the advantages and limitations of this kind of analyses, but did not describe the statistical methods that could be used to pool datasets . Some meWithin the M-SKIP project, we collected a large amount of data in which multiple hypotheses can be examined with greater statistical power than is possible in individual studies. The response rate of invited investigators was high (72%), probably due to the well defined criteria of data collection and use, the clear publication policy, and the presence of an Advisory Committee tasked with monitoring adherence to project guidelines and scientific quality. Another strength of the pooled-analysis here described is the carefully-planned approach to standardizing the demographic, epidemiological and phenotypic information obtained from individual studies, giving the opportunity to perform appropriate and detailed subgroup and interaction analyses. Because the inclusion of an individual study in a particular analysis is not dependent on whether those investigators have published findings on that association, and because of inclusion of unpublished datasets, our pooled-analysis should not be affected by publication bias, as it might a meta-analysis of the published literature. Finally, we plan to analyze data by conventional and recently proposed statistical methods, and will compare and integrate the results obtained with these different approaches.a priori standardization of data collection. On the other hand, pooled-analysis may be feasible with fewer funds than those required for a prospective consortium, and it takes shorter time to obtain results because the original data have already been collected. The quality of genotype methodology may be heterogeneous among different participant laboratories. We will take into account this possible problem both by calculation of Hardy-Weinberg equilibrium and by meta-regression analysis. Finally, while we will try to assess the existence of participation bias, we cannot completely rule out that the results could be affected by the exclusions of the studies from the investigators who refused to participate in this pooled analysis.The main limitation of a pooled analysis, especially with respect to prospective consortia, is that it was planned retrospectively, and hence there was no MC1R variants and skin cancer, particularly for population subgroups, and may be an appropriate setting to better investigate the genetics of sporadic skin cancer. A pooled-analysis of epidemiological studies is feasible, has many advantages over meta-analysis in making it possible to adjust for confounders and assess interactions, and in addition preliminary results may be obtained with lower costs and shorter time than with prospective consortia. We are convinced that its success depends upon the initial definition and approval of clear guidelines necessary for conducting such studies. The diffusion of pooled-analysis in genetic epidemiology field will assist epidemiologists and other health professionals in synthesizing the vast amount of available data on specific gene-disease associations and a common data-base would be the source of possible future investigations.In conclusion, the data collected within the M-SKIP project are a valuable resource for investigating associations between The authors declare that they have no competing interests.SR designed the study and directed its implementation, including quality assurance and control, wrote the paper and was the project leader. SG contributed to the design and supervision of the study and advised on recoding epidemiological data. MCF advised on recoding genetic data, is a member of the Advisory Committee of the project and contributed data to the study. VB, CS helped to carry out the statistical analysis plan of the study. PM contributed to the design and supervision of the study. RK, EN, JH, PG, NAG, TD, LB, RFdM, WB, TD, NM, GP, GR, AS, LC, TM, SA, PH, THW, FL, MK, TN and the GEM Study Group contributed data to the study. JH, PAK, MTL are members of the Advisory Committee of the project and contributed data to the study. PA, GCGB, JL, JNB, FS are members of the Advisory Committee of the project. All the members of the Advisory Committee were involved in the design and supervision of the study. All authors have revised and approved the manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2288/12/116/prepub


MDM2 promoter region SNP309 has been demonstrated to be associated with an increased MDM2 expression and a significantly earlier age of onset of several tumors, including gastric cancer. Several studies were published to evaluate the association between SNP309 and gastric cancer risk. However, the results remain conflicting rather than conclusive.MDM2 is a major negative regulator of p53, and a single nucleotide polymorphism (SNP) in the MDM2 SNP309 polymorphism and gastric risk.The aim of this study was to assess the association between the We performed a meta-analysis to investigate this relationship. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to assess the strength of the association. The pooled ORs were performed for codominant model, dominant model, and recessive model, respectively.MDM2 SNP309 polymorphism was associated with a significantly increased risk of gastric cancer risk when all studies were pooled into the meta-analysis . Furthermore, Egger's test did not show any evidence of publication bias (P = 0.799 for GG versus TT).Five published case-control studies, including 1,621 gastric cancer cases and 2,639 controls were identified. We found that the MDM2 SNP309 polymorphism may be a low-penetrant risk factor for the development of gastric cancer.Our results suggest that the  Helicobacter pylori (H. pylori) infection on the development of gastric cancer Gastric cancer is the fourth most commonly diagnosed cancer and the second leading cause of cancer death worldwide MDM2 promoter, SNP309 T>G (rs2279744), was identified MDM2 RNA and protein. It was further demonstrated that the heightened level of MDM2 was mediated by and dependent on transcription factor Sp1. Interestingly, amplification of MDM2 alone can enhance tumorigenesis A single nucleotide polymorphism in the MDM2 SNP309 polymorphism in gastric cancer risk, but the results are inconclusive, partially because of the possible small effect of the polymorphism on gastric cancer and the relatively small size in each of the published studies. Therefore, we carried out a meta-analysis on all eligible case-control studies to estimate the overall gastric cancer risk of MDM2 SNP309 polymorphism as well as to quantify the between-study heterogeneity and potential bias.Recently, a number of studies have reported the role of MDM2,” “polymorphism,” and “gastric cancer”). The search was limited to English-language papers. Additional studies were identified by a hand search of the references of original studies. Of the studies with the same or overlapping data published by the same investigators, we selected the most recent ones with the largest number of subjects. Studies included in our meta-analysis have to meet the following criteria: (a) evaluation of MDM2 SNP309 polymorphism and gastric cancer risk, (b) use a case-control design, and (c) have available genotype frequencies for both patients and control populations.We searched the electronic literature PubMed and Embase for all relevant articles , dominant model (GG/GT versus TT), and recessive model (GG vs. GT/TT), respectively. In consideration of the possibility of heterogeneity across the studies, a statistical test for heterogeneity was performed based on the Q statistic P>0.05 of the Q-test which indicates a lack of heterogeneity among studies, the summary OR estimate of each study was calculated by the fixed-effects model (the Mantel-Haenszel method). Otherwise, the random-effects model (the DerSimonian and Laird method) was used. Sensitivity analyses were performed to assess the stability of the results, namely, a single study in the meta-analysis was deleted each time to reflect the influence of the individual data set to the pooled OR. Funnel plots and Egger's linear regression test were used to provide diagnosis of the potential publication bias. All analyses were done with Stata software , using two-sided P values.Crude odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the strength of association between the There were 47 published papers relevant to the search terms Fig. 1. MDM2 SNP309 polymorphism was associated with a significantly increased risk of gastric cancer in recessive model , but not in dominant model .As shown in Pheterogeneity = 0.073 for GG versus GT/TT). Influence analysis was performed to assess the influence of each individual study on the pooled OR by sequential removal of individual studies. The results suggested that no individual study significantly affect the pooled ORs (Significant heterogeneity between studies was observed in overall comparisons except for recessive model (P = 0.799 for GG versus TT, Begg's funnel plot and Egger's test were performed to assess the publication bias of literatures. The shapes of the funnel plots did not reveal any evidence of obvious asymmetry in all comparison models. Then, the Egger's test was used to provide statistical evidence of funnel plot symmetry. The results still did not show any evidence of publication bias (t = −0.28, MDM2 SNP309 polymorphism and the risk of gastric cancer, which might be influenced by relatively small sample size and different genetic background. Ohmiya et al. MDM2 SNP309 polymorphism had an increased risk of gastric cancer. Given the important roles of MDM2 in the regulation of p53, it is biologically plausible that MDM2 polymorphism may modulate the risk of gastric cancer. The MDM2 SNP309 polymorphism increases the affinity of Sp1 for the MDM2 promoter and causes overexpression of MDM2. Accordingly, the cell lines with the SNP309 GG and TG genotypes expressed higher levels of MDM2 than those with the TT genotypes MDM2 SNP309 polymorphism and gastric cancer risk MDM2 SNP309 polymorphism is associated with a significantly increased risk of gastric cancer.The previous study has conflicting results about the association between the Some limitations of this meta-analysis should be addressed. First, misclassifications on disease status and genotypes may influence the results, because cases in several studies were not confirmed by pathology or other gold standard method, and the quality control of genotyping was also not well-documented in some studies. Second, selection bias could have played a role because the genotype distribution of this polymorphism among control subjects deviated from the Hardy-Weinberg equilibrium in one study In spite of these, our meta-analysis also had some advantages. First, although the number of studies involved in the meta-analysis was relatively small, the number of total cases and controls were substantial, which significantly increased the statistical power of the analysis. Second, the quality of case-control studies included in current meta-analysis was satisfactory and met our inclusion criterion. Third, we did not detect any publication bias indicating that the whole pooled result should be unbiased.MDM2 SNP309 polymorphism and gastric cancer risk, supporting the hypothesis that the SNP309 polymorphism may be a low-penetrance susceptibility marker of gastric cancer. However, large sample studies are warranted to validate our findings. Moreover, more gene-gene and gene-environment interactions should also be considered in future analysis, which should lead to better, comprehensive understanding of the association between the MDM2 SNP309 polymorphism and gastric cancer risk.In summary, this meta-analysis provided evidence of the association between


Dietary studies differ in design and quality making it difficult to compare results. This study quantifies the prospective association between dietary energy density (DED) and adiposity in children using a meta-analysis method that adjusts for differences in design and quality through eliciting and incorporating expert opinion on the biases and their uncertainty.Six prospective studies identified by a previous systematic literature search were included. Differences in study quality and design were considered respectively as internal and external biases and captured in bias checklists. Study results were converted to correlation coefficients; biases were considered either additive or proportional on this scale. The extent and uncertainty of the internal and external biases in each study were elicited in a formal process by five quantitatively-trained assessors and five subject-matter specialists. Biases for each study were combined across assessors using median pooling and results combined across studies by random-effects meta-analysis.2 = 52%). After bias-adjustment the pooled correlation was 0.17 , and the studies were apparently compatible (I2 = 0%).The unadjusted combined correlation between DED and adiposity change was 0.06 , but with considerable heterogeneity (IThis method allowed quantitative synthesis of the prospective association between DED and adiposity change in children, which is important for the development of evidence-informed policy. Bias adjustment increased the magnitude of the positive association but the widening confidence interval reflects the uncertainty of the assessed biases and implies that higher quality studies are required. The prevalence of obesity in childhood is increasing around the world and is causally linked to large predicted increases in morbidity -4. The f2) in children.To overcome this diversity problem and to be able to estimate an overall pooled estimate of the association, we have adapted and applied a recently developed experimental meta-analysis method that allows adjustment for differences in study design and quality through a formal process of eliciting and incorporating expert opinion . This meThis meta-analysis considered all cohort studies investigating the prospective associations between DED and measures of adiposity n = 8) -17, whic -17, whiThe bias-adjustment method is described in detail by Turner et al. . The steThe precise definition of the public health target question, which the meta-analysis aims to address, was agreed as "Is dietary energy density associated with change in fat mass index in children?"The target setting, which describes the optimal study protocol answering the target question with regards to study population, exposure and outcome measures and follow-up time, was defined as:(i) General population of children aged 4-11yrs in the UK(ii) DED assessed by 7 day weighed food diaries calculated by dividing total food energy (kJ) by total food weight (g) excluding beverages2, kg/m2), measured from baseline to follow-up(iii) Change in FMI (fat mass/height(iv) Outcome assessed 2 years after the baseline measurement.The target setting focuses on children between 4 and 11 years excluding both baby to toddler stages and advanced stages of puberty to match the policy focus on the UK Healthy Weight, Healthy Lives strategy . DED calFor each study included in the meta-analysis, an idealized version was defined. The idealized study is an imagined repeat of the actual study with modifications to eliminate all sources of internal biases such as selection bias, attrition bias, inappropriate adjustment for confounding and biases arising from how the exposure and outcome were measured. The design of the idealized study does not need to be practically feasible. For example, the idealized study of Savage et al.  Table 11 include(i) Non-Hispanic women living in central Pennsylvania, USA(ii) DED assessed by three 24 h recalls, including two weekdays and one weekend day and calculated by dividing total food energy by total food weight(iii) Change in body weight measured from baseline to follow-up(iv) Outcome assessed six years after the baseline measurement.Potential internal biases in each study were identified by comparing the study against its idealized version. For this meta-analysis, internal biases were categorized as biases related to the measurement of the outcome ("outcome bias") and the exposure ("exposure bias"), missing data and loss to follow-up ("attrition bias"), appropriate confounders ("confounding bias") and whether the inclusion and exclusion criteria were clear and adhered to ("selection bias"). Biases related to inappropriate statistical analysis or any other flaws were included in a separate category ("other bias suspected"). Important variables potentially related to both the outcome and exposure were considered by the subject matter specialists and statisticians and the following reference set of confounders was selected: energy-containing beverages, sex, total energy intake or energy misreporting, socio-economic status, ethnicity, some measure of baseline body size, physical activity and, depending on the age of the study population, Tanner stage and smoking status. Many DED studies adjust for fat and fiber intake; we did not consider these as confounders as both are expected to be direct determinants of DED. The adjustment for confounding in each study was judged against this reference set.Potential external biases were identified by comparing each idealized study against the target setting. External biases were categorized as biases related to the follow-up time ("timing bias"), the presented outcome ("outcome bias") and exposure measures ("exposure bias") and the study population ("population bias").Bias checklists were prepared for each study, highlighting information that might be relevant in the assessment of each of the possible internal and external biases. To ensure consistency, biases were identified by the same subject-matter specialist together with one statistician for each study.z = 0.5ln[(1+r)/(1-r)] and z having a standard error SE(z) = 1/√ (n-3), where r is the correlation and n is the sample size. The number of SEs z is away from zero is derived from the p-value, thus providing an estimate of z. We back-transformed z to the correlation r in order to present results. The Fisher-transformed and original scales were in fact almost identical in the range - 0.3 to +0.3.The studies expressed the association between baseline DED and change in adiposity differently, with a mix of regression coefficients, summary statistics, odds ratios and p-values. To allow pooling of results it was necessary to transform the associations onto a common metric. From the available information a p-value could be calculated for the association in each study and, using the respective sample size, this was subsequently transformed into a correlation and standard error for each study. Biases were assessed on the correlation scale. To do the calculations we applied a Fisher-transformation to the correlations, the Fisher-transformed correlation being Internal bias elicitation meetings involved five quantitatively-trained assessors and separate external bias elicitation meetings involved five assessors with subject-matter knowledge. At the meetings, each study report and bias checklist were discussed in turn in a non-quantitative manner. The discussion included consideration of whether each bias would only change the magnitude of the association  or if it could change the direction of the association (an additive bias). Following the discussion, each assessor independently provided their quantitative opinion on the impact and uncertainty of each of the biases on a bias elicitation form. The biases were indicated using 67% intervals, such that the assessor thought that the bias was twice as likely to lie inside the interval as outside it. The additive and proportional elicitation scales for quantifying internal and external biases are given in Figure 2 statistic [The elicited internal biases from each assessor were used to calculate the mean and variance of the total additive and total proportional bias for each study, which were then used to adjust the estimated correlation coefficients and standard errors. The same process was used to adjust these results for the external biases. All calculations used formulae adapted from Turner et al . The restatistic , which gTable DED was assessed by food diaries -16, 24 hTable Internal biases suspected to affect all source studies were selection, attrition and/or confounding biases. For example, insufficient information had been provided regarding the recruitment strategy in the source studies and related papers and it seemed likely that losses to follow-up or immediate dropouts had affected the results -17 Tabl. ConfounExternal biases were expected because of differences between the source studies and the pre-defined target setting regarding the way the diet was assessed and DED was calculated, the varying outcome measures, differences in the population as well as the follow-up time Table .Figure The impact of adjusting the estimated correlation from the study by Savage et al.  for firs2 = 52%) making it difficult to interpret. After adjustment for internal biases that reflects lack in study quality, the pooled correlation was 0.14, with a widened confidence interval  and studies were apparently compatible (I2 = 0%). After adjusting for both internal and external biases, which allows drawing conclusions that are specific to the particular target setting, the pooled correlation between DED and subsequent change in FMI in children was 0.17  and the results remained compatible (I2 = 0%).Figure This meta-analysis with bias-adjustment allows a quantitative evaluation of the totality of the evidence on the prospective relationship between DED and the change in FMI in children. A previous narrative review reported that decreasing the energy density of the diet may offset weight gain in childhood. However, because of the lack of prospective DED studies, their heterogeneous nature and the difficulties in comparing results presented in different ways, the evidence has not been synthesized quantitatively. This limits the possibility of drawing an overall conclusion and making policy related decisions.2 = 52%), which therefore limits interpretability. The bias-adjustment process eliminated the heterogeneity amongst studies (I2 = 0%). Thus, while the association is no longer statistically significant, the data can now be interpreted with a clearer understanding of the biases. In our view, the magnitude of the correlation provides increased support to policymakers for interventions to reduce DED to prevent obesity in children, and for advice to consumers of the importance of reducing dietary energy density.Our analysis provides an overall quantitative synthesis of the evidence-base for decision-makers. The unadjusted results from the six studies gave a combined correlation of baseline DED with change in adiposity of 0.064 . After bias adjustment the association between DED of food and the change in FMI in children for the target setting was 0.17 . Relative to the unadjusted analysis, the magnitude of the correlation coefficient was increased, indicating the possibility that DED is an important determinant of excess weight gain. However, the confidence interval widened after bias-adjustment, which is due to incorporating the assessors' uncertainty regarding the size of the biases, and implies that higher quality studies are required. The statistical heterogeneity among studies was large in the unadjusted meta-analysis (IThe process of bias-adjustment, at the heart of this method, relies on expert opinion and might be considered to be somewhat subjective. We do not claim that the elicited bias distributions are 'correct'; we are dealing with epistemic uncertainty, and they express judgements about our beliefs. However, the opinions of several experts are combined so that individual opinions do not unduly influence the final result of the meta-analysis. The experts were chosen for their quantitative or subject-matter skills, and we prefer to incorporate their judgements rather than simply ignore the suspected biases in the studies available. In addition, consistency across studies and transparency is ensured by the very structured and systematic process of bias-adjustment. Although some opinions on biases varied between the assessors, the differences were in general quite small Figure  and mainA similar bias-adjusted meta-analysis has already been conducted for a systematic review of prospective observational studies of physical activity and subsequent gain in fat mass in children . This meThis bias-adjustment meta-analysis allowed quantitative synthesis of the prospective association between DED and change in adiposity in children. The result indicates that DED may be an important dietary determinant of unhealthy weight gain in children. Our analysis emphasizes the need for higher quality studies with more precise measurements of dietary intake and body composition and presentation of adequate analyses.This is a collaborative project between nutritionists, epidemiologists and statisticians from three UK Medical Research Council units. All authors contributed to the study design, the bias assessments, and drafting the paper. RMT, SGT and SAJ initiated the study, DCW carried out the systematic review and coordinated the expert groups, APM undertook the statistical analyses with input from SJS, and AKL coordinated the study. All authors have given final approval of the version to be published.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/11/48/prepub