Investigating the missing data mechanism in quality of life outcomes: a comparison of approaches

Background: Missing data is classified as missing completely at random (MCAR), missing at random (MAR) or missing not at random (MNAR). Knowing the mechanism is useful in identifying the most appropriate analysis. The first aim was to compare different methods for identifying this missing data mechanism to determine if they gave consistent conclusions. Secondly, to investigate whether the reminder-response data can be utilised to help identify the missing data mechanism. Methods: Five clinical trial datasets that employed a reminder system at follow-up were used. Some quality of life questionnaires were initially missing, but later recovered through reminders. Four methods of determining the missing data mechanism were applied. Two response data scenarios were considered. Firstly, immediate data only; secondly, all observed responses (including reminder-response). Results: In three of five trials the hypothesis tests found evidence against the MCAR assumption. Logistic regression suggested MAR, but was able to use the reminder-collected data to highlight potential MNAR data in two trials. Conclusion: The four methods were consistent in determining the missingness mechanism. One hypothesis test was preferred as it is applicable with intermittent missingness. Some inconsistencies between the two data scenarios were found. Ignoring the reminder data could potentially give a distorted view of the missingness mechanism. Utilising reminder data allowed the possibility of MNAR to be considered.The Chief Scientist Office of the Scottish Government Health Directorate. Research Training Fellowship (CZF/1/31

Regional variation in hospitalization for stroke among Asians/Pacific Islanders in the United States: a nationwide retrospective cohort study

BACKGROUND: In Asia, stroke incidence varies dramatically from country to country. Little is known about stroke incidence in Asians/Pacific Islanders in the US, where regional heterogeneity in Asian/Pacific Islander sub-populations is great. We sought to characterize both the national and regional incidences of first and recurrent hospitalized acute ischemic stroke, subarachnoid hemorrhage, and intracerebral hemorrhage in Asians/Pacific Islanders compared to non-Hispanic whites. METHODS: We used the National Inpatient Sample of the 1997 Healthcare Cost and Utilization Project. It is a 20% stratified sample of hospitalizations to nonfederal hospitals in the US. National and regional projections were made using sampling weights specific for patients and hospitals. We identified stroke subtypes using previously validated ICD-9 codes. Age-adjusted incidence rates were calculated using the direct method with the US population in 2000 as the standard. RESULTS: There were 169,386 stroke hospitalizations in the database. Nationally, compared to whites, Asians/Pacific Islanders were more likely to have subarachnoid hemorrhage (incidence rate ratio {RR} female: 1.53, 95% CI 1.41–1.65; male RR: 1.13, 95% CI 1.00–1.27) and intracerebral hemorrhage (female RR 1.29, 95% CI 1.22–1.36; male RR: 1.58, 95% CI 1.50–1.67). However, when examined by geographic regions, Asians/Pacific Islanders had higher incidence rates of subarachnoid hemorrhage and intracerebral hemorrhage predominantly in the West, and lower rates of stroke elsewhere. CONCLUSION: Stroke incidence varies 3-fold among Asians/Pacific Islanders residing in different US regions. Geographic variation is less dramatic in whites. Whether genetic or cultural differences are responsible for dramatic heterogeneity among Asian/Pacific Islander populations is unclear and deserves further study

Psychometric properties of the Vertigo symptom scale – Short form

<p>Abstract</p> <p>Background</p> <p>The aim of the study was to examine the psychometric properties of the Vertigo symptom scale – short form (VSS-SF), a condition-specific measure of dizziness, following translation of the scale into Norwegian.</p> <p>Methods</p> <p>A cross-sectional survey design was used to examine the factor structure, internal consistency and discriminative ability (sample I, n = 503). A cross-sectional pre-intervention design was used to examine the construct validity (sample II, n = 36) of the measure and a test-retest design was used to examine reliability (sub-sample of sample II, n = 28).</p> <p>Results</p> <p>The scree plot indicated a two factor structure accounting respectively for 41% and 12% of the variance prior to rotation. The factors were related to vertigo-balance (VSS-V) and autonomic-anxiety (VSS-A). Twelve of the items loaded clearly on either of the two dimensions, while three items cross-loaded. Internal consistency of the VSS-SF was high (alpha = 0.90). Construct validity was indicated by correlation between path length registered by platform posturography and the VSS-V (r = 0.52), but not with the VSS-A. The ability to discriminate between dizzy and not dizzy patients was excellent for the VSS-SF and sub-dimension VSS-V (area under the curve 0.87 and 0.91, respectively), and acceptable for the sub-dimension VSS-A (area under the curve 0.77). High test-retest reliability was demonstrated (ICC VSS-SF: 0.88, VSS-V: 0.90, VSS-A: 0.90) and no systematic change was observed in the scores from test to retest after 2 days.</p> <p>Conclusion</p> <p>Using a Norwegian translated version of the VSS-SF, this is the first study to provide evidence of the construct validity of this instrument demonstrating a stable two factor structure of the scale, and the identified sub-dimensions of dizziness were related to vertigo-balance and autonomic-anxiety, respectively. Evidence regarding a physical construct underlying the vertigo-balance sub-scale was provided. Satisfactory internal consistency was indicated, and the discriminative ability of the instruments was demonstrated. The instrument showed satisfactory test-retest reliability.</p

Application of ordinal logistic regression analysis in determining risk factors of child malnutrition in Bangladesh

<p>Abstract</p> <p>Background</p> <p>The study attempts to develop an ordinal logistic regression (OLR) model to identify the determinants of child malnutrition instead of developing traditional binary logistic regression (BLR) model using the data of Bangladesh Demographic and Health Survey 2004.</p> <p>Methods</p> <p>Based on weight-for-age anthropometric index (Z-score) child nutrition status is categorized into three groups-severely undernourished (< -3.0), moderately undernourished (-3.0 to -2.01) and nourished (≥-2.0). Since nutrition status is ordinal, an OLR model-proportional odds model (POM) can be developed instead of two separate BLR models to find predictors of both malnutrition and severe malnutrition if the proportional odds assumption satisfies. The assumption is satisfied with low p-value (0.144) due to violation of the assumption for one co-variate. So partial proportional odds model (PPOM) and two BLR models have also been developed to check the applicability of the OLR model. Graphical test has also been adopted for checking the proportional odds assumption.</p> <p>Results</p> <p>All the models determine that age of child, birth interval, mothers' education, maternal nutrition, household wealth status, child feeding index, and incidence of fever, ARI & diarrhoea were the significant predictors of child malnutrition; however, results of PPOM were more precise than those of other models.</p> <p>Conclusion</p> <p>These findings clearly justify that OLR models (POM and PPOM) are appropriate to find predictors of malnutrition instead of BLR models.</p

Polychlorinated biphenyls, cytochrome P450 1A1 (CYP1A1) polymorphisms, and breast cancer risk among African American women and white women in North Carolina: a population-based case-control study

INTRODUCTION: Epidemiologic studies have not shown a strong relationship between blood levels of polychlorinated biphenyls (PCBs) and breast cancer risk. However, two recent studies showed a stronger association among postmenopausal white women with the inducible M2 polymorphism in the cytochrome P450 1A1 (CYP1A1) gene. METHODS: In a population-based case-control study, we evaluated breast cancer risk in relation to PCBs and the CYP1A1 polymorphisms M1 (also known as CYP1A1*2A), M2 (CYP1A1*2C), M3 (CYP1A1*3), and M4 (CYP1A1*4). The study population consisted of 612 patients (242 African American, 370 white) and 599 controls (242 African American, 357 white). RESULTS: There was no evidence of strong joint effects between CYP1A1 M1-containing genotypes and total PCBs in African American or white women. Statistically significant multiplicative interactions were observed between CYP1A1 M2-containing genotypes and elevated plasma total PCBs among white women (P value for likelihood ratio test = 0.02). Multiplicative interactions were also observed between CYP1A1 M3-containing genotypes and elevated total PCBs among African American women (P value for likelihood ratio test = 0.10). CONCLUSIONS: Our results confirm previous reports that CYP1A1 M2-containing genotypes modify the association between PCB exposure and risk of breast cancer. We present additional evidence suggesting that CYP1A1 M3-containing genotypes modify the effects of PCB exposure among African American women. Additional studies are warranted, and meta-analyses combining results across studies will be needed to generate more precise estimates of the joint effects of PCBs and CYP1A1 genotypes

Significance of Aurora B overexpression in hepatocellular carcinoma. Aurora B Overexpression in HCC

<p>Abstract</p> <p>Background</p> <p>To investigate the significance of Aurora B expression in hepatocellular carcinoma (HCC).</p> <p>Methods</p> <p>The <it>Aurora B </it>and <it>Aurora A </it>mRNA level was measured in 160 HCCs and the paired nontumorous liver tissues by reverse transcription-polymerase chain reaction. Mutations of the <it>p53 </it>and <it>β-catenin </it>genes were analyzed in 134 and 150 tumors, respectively, by direct sequencing of exon 2 to exon 11 of <it>p53 </it>and exon 3 of <it>β-catenin</it>. Anticancer effects of AZD1152-HQPA, an Aurora B kinase selective inhibitor, were examined in Huh-7 and Hep3B cell lines.</p> <p>Results</p> <p><it>Aurora B </it>was overexpressed in 98 (61%) of 160 HCCs and in all 7 HCC cell lines examined. The overexpression of <it>Aurora B </it>was associated with <it>Aurora A </it>overexpression (<it>P </it>= 0.0003) and <it>p53 </it>mutation (<it>P </it>= 0.002) and was inversely associated with <it>β</it>-<it>catenin </it>mutation (<it>P </it>= 0.002). <it>Aurora B </it>overexpression correlated with worse clinicopathologic characteristics. Multivariate analysis confirmed that <it>Aurora B </it>overexpression was an independent poor prognostic factor, despite its interaction with Aurora A overexpression and mutations of <it>p53 </it>and <it>β</it>-<it>catenin</it>. In Huh-7 and Hep3B cells, AZD1152-HQPA induced proliferation blockade, histone H3 (Ser10) dephosphorylation, cell cycle disturbance, and apoptosis.</p> <p>Conclusion</p> <p><it>Aurora B </it>overexpression is an independent molecular marker predicting tumor invasiveness and poor prognosis of HCC. Aurora B kinase selective inhibitors are potential therapeutic agents for HCC treatment.</p

Why do paediatricians prescribe antibiotics? Results of an Italian regional project

<p>Abstract</p> <p>Background</p> <p>To investigate determinants of antibiotic prescription in paediatric care, as a first step of a multilevel intervention to improve prescribing for common respiratory tract infections (RTIs) in a northern Italian region with high antibiotic prescription rate.</p> <p>Methods</p> <p>A two-step survey was performed: in phase I, knowledge, and attitudes were explored involving all family and hospital paediatricians of Emilia-Romagna and a sample of parents. In phase II, patient care practices were explored in a stratified random sample of visits, both in hospitals and family physician's clinics; parent expectations were investigated in a sub-sample of these visits.</p> <p>Results</p> <p>Out of overall 4352 visits for suspected RTIs, in 38% of children an antibiotic was prescribed. Diagnostic uncertainty was perceived by paediatricians as the most frequent cause of inappropriate prescription (56% of 633 interviewed paediatricians); but, rapid antigen detecting tests was used in case of pharyngitis/pharyngotonsillitis by 36% and 21% of family and hospital paediatricians only. More than 50% of paediatricians affirmed to not adopt a "wait and see strategy" in acute otitis. The perceived parental expectation of antibiotics was not indicated by paediatricians as a crucial determinant of prescription, but this perception was the second factor most strongly associated to prescription (OR = 12.8; 95% CI 10.4 - 15.8), the first being the presence of othorrea. Regarding parents, the most important identified factors, potentially associated to overprescribing, were the lack of knowledge of RTIs and antibiotics (41% of 1029 parents indicated bacteria as a possible cause of common cold), and the propensity to seek medical care for trivial infections (48% of 4352 children accessing ambulatory practice presented only symptoms of common cold).</p> <p>Conclusion</p> <p>A wide gap between perceived and real determinants of antibiotic prescription exists. This can promote antibiotic overuse. Inadequate parental knowledge can also induce inappropriate prescription. The value of this study is that it simultaneously explored determinants of antimicrobial prescribing in an entire region involving both professionals and parents.</p

Testing for heterogeneity among the components of a binary composite outcome in a clinical trial

<p>Abstract</p> <p>Background</p> <p>Investigators designing clinical trials often use composite outcomes to overcome many statistical issues. Trialists want to maximize power to show a statistically significant treatment effect and avoid inflation of Type I error rate due to evaluation of multiple individual clinical outcomes. However, if the treatment effect is not similar among the components of this composite outcome, we are left not knowing how to interpret the treatment effect on the composite itself. Given significant heterogeneity among these components, a composite outcome may be judged as being invalid or un-interpretable for estimation of the treatment effect. This paper compares the power of different tests to detect heterogeneity of treatment effect across components of a composite binary outcome.</p> <p>Methods</p> <p>Simulations were done comparing four different models commonly used to analyze correlated binary data. These models included: logistic regression for ignoring correlation, logistic regression weighted by the intra cluster correlation coefficient, population average logistic regression using generalized estimating equations (GEE), and random effects logistic regression.</p> <p>Results</p> <p>We found that the population average model based on generalized estimating equations (GEE) had the greatest power across most scenarios. Adequate power to detect possible composite heterogeneity or variation between treatment effects of individual components of a composite outcome was seen when the power for detecting the main study treatment effect for the composite outcome was also reasonably high.</p> <p>Conclusions</p> <p>It is recommended that authors report tests of composite heterogeneity for composite outcomes and that this accompany the publication of the statistically significant results of the main effect on the composite along with individual components of composite outcomes.</p

Burn injury leads to increased long-term susceptibility to respiratory infection in both mouse models and population studies

Background: Burn injury initiates an acute inflammatory response that subsequently drives wound repair. However, acute disruption to the immune response is also common, leading to susceptibility to sepsis and increased morbidity and mortality. Despite increased understanding of the impact of burn injury on the immune system in the acute phase, little is known about longterm consequences of burn injury on immune function. This study was established to determine whether burn injury has long-term clinical impacts on patients' immune responses. Methods: Using a population-based retrospective longitudinal study and linked hospital morbidity and death data from Western Australia, comparative rates of hospitalisation for respiratory infections in burn patients and a non-injured comparator cohort were assessed. In addition, a mouse model of non-severe burn injury was also used in which viral respiratory infection was induced at 4 weeks post-injury using a mouse modified version of the Influenza A virus (H3NN; A/mem/71-a). Results and conclusions: The burn injured cohort contained 14893 adult patients from 1980-2012 after removal of those patients with evidence of smoke inhalation or injury to the respiratory tract. During the study follow-up study a total of 2,884 and 2,625 respiratory infection hospital admissions for the burn and uninjured cohorts, respectively, were identified. After adjusting for covariates, the burn cohort experienced significantly elevated admission rates for influenza and viral pneumonia (IRR, 95%CI: 1.73, 1.27-2.36), bacterial pneumonia (IRR, 95%CI: 2.05, 1.85-2.27) and for other types of upper and lower respiratory infections (IRR, 95% CI: 2.38, 2.09-2.71). In the mouse study an increased viral titre was observed after burn injury, accompanied by a reduced CD8 response and increased NK and NKT cells in the draining lymph nodes. This data suggests burn patients are at long-term increased risk of infection due to sustained modulation of the immune response