Tutorial in biostatistics: Analyzing associations between total plasma homocysteine and B vitamins using optimal categorization and segmented regression

Data analysts consider standard regression models (e.g., generalized linear model) or nonparametric smoothing techniques (e.g., loess or splines) when examining the association between two variables. Before this step, a quantile-based summarization is typically used for exploring the exposure-response relationship. Unfortunately, these exploratory approaches may not be optimal or efficient for guiding the formal analysis in many biological and nutritional data settings. We suggest a recently developed method for selection of cutpoints as a tool of data summary and segmented regression as a modeling approach in the analysis of plasma total homocysteine and related vitamins. These methods are often complementary in discovering the underlying complex pattern of association. Copyright © 2006 S. Karger AG

The Choice of Prior Distribution for A Covariance Matrix in Multivariate Meta-Analysis: A Simulation Study

Bayesian meta-analysis is an increasingly important component of clinical research, with multivariate meta-analysis a promising tool for studies with multiple endpoints. Model assumptions, including the choice of priors, are crucial aspects of multivariate Bayesian meta-analysis (MBMA) models. In a given model, two different prior distributions can lead to different inferences about a particular parameter. A simulation study was performed in which the impact of families of prior distributions for the covariance matrix of a multivariate normal random effects MBMA model was analyzed. Inferences about effect sizes were not particularly sensitive to prior choice, but the related covariance estimates were. A few families of prior distributions with small relative biases, tight mean squared errors, and close to nominal coverage for the effect size estimates were identified. Our results demonstrate the need for sensitivity analysis and suggest some guidelines for choosing prior distributions in this class of problems. The MBMA models proposed here are illustrated in a small meta-analysis example from the periodontal field and a medium meta-analysis from the study of stroke

The Choice of Prior Distribution for A Covariance Matrix in Multivariate Meta-Analysis: A Simulation Study

Bayesian meta-analysis is an increasingly important component of clinical research, with multivariate meta-analysis a promising tool for studies with multiple endpoints. Model assumptions, including the choice of priors, are crucial aspects of multivariate Bayesian meta-analysis (MBMA) models. In a given model, two different prior distributions can lead to different inferences about a particular parameter. A simulation study was performed in which the impact of families of prior distributions for the covariance matrix of a multivariate normal random effects MBMA model was analyzed. Inferences about effect sizes were not particularly sensitive to prior choice, but the related covariance estimates were. A few families of prior distributions with small relative biases, tight mean squared errors, and close to nominal coverage for the effect size estimates were identified. Our results demonstrate the need for sensitivity analysis and suggest some guidelines for choosing prior distributions in this class of problems. The MBMA models proposed here are illustrated in a small meta-analysis example from the periodontal field and a medium meta-analysis from the study of stroke

Risk stratification of smoldering multiple myeloma: predictive value of free light chains and group-based trajectory modeling.

We investigated the predictive role for serum free light chain ratio (FLCr) ≥100, bone marrow plasma cell (BMPC) ≥60%, and evolving biomarkers through group-based trajectory modeling (GBTM) as high-risk defining events in 273 smoldering multiple myeloma (SMM) patients with a median follow-up of 74 months. FLCr ≥100 was confirmed as a marker for high-risk progression with a median time to progression (TTP) of 40 months with a 44% risk of progression of disease (PD) at 2 years; however, 44% of FLCr ≥100 also did not progress during follow-up. For patients with BMPC ≥60% by core biopsy, the median TTP was 31 months with a 2-year PD of 41%. GBTM established high-risk trajectories for evolving hemoglobin (eHb; characterized as a 1.57 g/dL decrease in hemoglobin), evolving m-protein (eMP; 64% increase in m-protein), and evolving differences in FLC (edFLC; 169% increase in dFLC) within 1 year of diagnosis associated with a decreased median TTP and an increased 2 year rate of PD. Of all the variables examined, we identify a model where immunoparesis, eHb, eMP, and edFLC were significant predictors for ultra-high-risk progression with a median TTP of only 13 months with 3 or more variables present. Our results not only confirm a more modest 2 year PD associated with FLCr ≥100 and BMPC ≥60 but also suggest that eHb, eMP, and edFLC may help identify an ultra-high-risk SMM group

Saccadic reaction time in mirror image sectors across horizontal meridian in eye movement perimetry

In eye movement perimetry (EMP), the saccadic reaction time (SRT) to ‘seen’ visual stimuli are delayed in glaucoma. Evaluating SRT behaviour in hemi-field sectors could refine its clinical implication. The development phase included 60 controls retrospectively and for the test cohort in evaluation phase, another 30 healthy subjects and 30 glaucoma patients were recruited prospectively. The SRTs were used to calculate the normative limits within 5 predefined hemi-field sectors. Scores were assigned to probabilities for SRT at the level of 5%, 2.5% 1% and 0.5%. Per sector pair, a probability score limit (PSL) was calculated at each of the four levels and were compared with the scores obtained from the test cohort. The classification accuracy ‘normal versus abnormal’ was assessed for PSL in EMP and compared with glaucoma hemi-field test in standard automated perimetry. We found no statistically significant differences in SRTs between the mirror sectors in healthy subjects. The PSL at 2.5% had moderate classification accuracy with a specificity of 77% and sensitivity 70%. This could be suggestive of an SRT delay in the overall visual field in glaucoma

Increased shedding of HU177 correlates with worse prognosis in primary melanoma

<p>Abstract</p> <p>Background</p> <p>Increased levels of cryptic collagen epitope HU177 in the sera of melanoma patients have been shown to be associated with thicker primary melanomas and with the nodular histologic subtype. In this study, we investigate the association between HU177 shedding in the sera and clinical outcome in terms of disease-free survival (DFS) and overall survival (OS).</p> <p>Methods</p> <p>Serum samples from 209 patients with primary melanoma prospectively enrolled in the Interdisciplinary Melanoma Cooperative Group at the New York University Langone Medical Center (mean age = 58, mean thickness = 2.09 mm, stage I = 136, stage II = 41, stage III = 32, median follow-up = 54.9 months) were analyzed for HU177 concentration using a validated ELISA assay. HU177 serum levels at the time of diagnosis were used to divide the study cohort into two groups: low and high HU177. DFS and OS were estimated by Kaplan-Meier survival analysis, and the log-rank test was used to compare DFS and OS between the two HU177 groups. Multivariate Cox proportional hazards regression models were employed to examine the independent effect of HU177 category on DFS and OS.</p> <p>Results</p> <p>HU177 sera concentrations ranged from 0-139.8 ng/ml (mean and median of 6.2 ng/ml and 3.7 ng/ml, respectively). Thirty-eight of the 209 (18%) patients developed recurrences, and 34 of the 209 (16%) patients died during follow-up. Higher HU177 serum level was associated with an increased rate of melanoma recurrence (p = 0.04) and with increasing mortality (p = 0.01). The association with overall survival remained statistically significant after controlling for thickness and histologic subtype in a multivariate model (p = 0.035).</p> <p>Conclusions</p> <p>Increased shedding of HU177 in the serum of primary melanoma patients is associated with poor prognosis. Further studies are warranted to determine the clinical utility of HU177 in risk stratification compared to the current standard of care.</p

Blood Transfusions in Total Hip and Knee Arthroplasty: An Analysis of Outcomes

Background. Various studies have raised concern of worse outcomes in patients receiving blood transfusions perioperatively compared to those who do not. In this study we attempted to determine the proportion of perioperative complications in the orthopedic population attributable to the use of a blood transfusion. Methods. Data from 400 hospitals in the United States were used to identify patients undergoing total hip or knee arthroplasty (THA and TKA) from 2006 to 2010. Patient and health care demographics, as well as comorbidities and perioperative outcomes were compared. Multivariable logistic regression models were fitted to determine associations between transfusion, age, and comorbidities and various perioperative outcomes. Population attributable fraction (PAF) was determined to measure the proportion of outcome attributable to transfusion and other risk factors. Results. Of 530,089 patients, 18.93% received a blood transfusion during their hospitalization. Patients requiring blood transfusion were significantly older and showed a higher comorbidity burden. In addition, these patients had significantly higher rates of major complications and a longer length of hospitalization. The logistic regression models showed that transfused patients were more likely to have adverse health outcomes than nontransfused patients. However, patients who were older or had preexisting diseases carried a higher risk than use of a transfusion for these outcomes. The need for a blood transfusion explained 9.51% (95% CI 9.12–9.90) of all major complications. Conclusions. Advanced age and high comorbidity may be responsible for a higher proportion of adverse outcomes in THA and TKA patients than blood transfusions

Is there a role for expectation maximization imputation in addressing missing data in research using WOMAC questionnaire? Comparison to the standard mean approach and a tutorial

<p>Abstract</p> <p>Background</p> <p>Standard mean imputation for missing values in the Western Ontario and Mc Master (WOMAC) Osteoarthritis Index limits the use of collected data and may lead to bias. Probability model-based imputation methods overcome such limitations but were never before applied to the WOMAC. In this study, we compare imputation results for the Expectation Maximization method (EM) and the mean imputation method for WOMAC in a cohort of total hip replacement patients.</p> <p>Methods</p> <p>WOMAC data on a consecutive cohort of 2062 patients scheduled for surgery were analyzed. Rates of missing values in each of the WOMAC items from this large cohort were used to create missing patterns in the subset of patients with complete data. EM and the WOMAC's method of imputation are then applied to fill the missing values. Summary score statistics for both methods are then described through box-plot and contrasted with the complete case (CC) analysis and the true score (TS). This process is repeated using a smaller sample size of 200 randomly drawn patients with higher missing rate (5 times the rates of missing values observed in the 2062 patients capped at 45%).</p> <p>Results</p> <p>Rate of missing values per item ranged from 2.9% to 14.5% and 1339 patients had complete data. Probability model-based EM imputed a score for all subjects while WOMAC's imputation method did not. Mean subscale scores were very similar for both imputation methods and were similar to the true score; however, the EM method results were more consistent with the TS after simulation. This difference became more pronounced as the number of items in a subscale increased and the sample size decreased.</p> <p>Conclusions</p> <p>The EM method provides a better alternative to the WOMAC imputation method. The EM method is more accurate and imputes data to create a complete data set. These features are very valuable for patient-reported outcomes research in which resources are limited and the WOMAC score is used in a multivariate analysis.</p

Clinical relevance of Neutral Endopeptidase (NEP/CD10) in melanoma

BACKGROUND: Overexpression of Neutral Endopeptidase (NEP) has been reported in metastatic carcinomas, implicating NEP in tumor progression and suggesting a role for NEP inhibitors in its treatment. We investigated the role of NEP expression in the clinical progression of cutaneous melanoma. METHODS: We screened 7 melanoma cell lines for NEP protein expression. NEP-specific siRNA was transfected into the lines to examine the role of gene transcription in NEP expression. Immunohistochemistry was done for 93 specimens and correlated with clinicopathologic parameters. Thirty-seven metastatic melanoma specimens were examined for NEP transcript expression using Affymetrix GeneChips. In a subset of 25 specimens for which both transcript and protein expression was available, expression ratios were used to identify genes that co-express with NEP in GeneChip analysis. RESULTS: NEP was overexpressed in 4/7 human melanoma cell lines, and siRNA knock-down of NEP transcripts led to downregulation of its protein expression. NEP protein overexpression was significantly more common in metastatic versus primary tumors (P = 0.002). Twelve of 37 (32%) metastatic tumors had increased NEP transcript expression, and an association was observed between NEP transcript upregulation and protein overexpression (P < 0.0001). Thirty-eight genes were found to significantly co-express with NEP (p < 0.005). Thirty-three genes positively correlated with NEP, including genes involved in the MAP kinase pathway, antigen processing and presentation, apoptosis, and WNT signaling pathway, and 5 genes negatively correlated with NEP, including genes of focal adhesion and the notch signaling pathways. CONCLUSION: NEP overexpression, which seems to be largely driven by increased transcription, is rare in primary melanoma and occurs late in melanoma progression. Functional studies are needed to better understand the mechanisms of NEP regulation in melanoma

Best Practices for Biostatistical Consultation and Collaboration in Academic Health Centers

Given the increasing level and scope of biostatistics expertise needed at academic health centers today, we developed best practices guidelines for biostatistics units to be more effective in providing biostatistical support to their institutions, and in fostering an environment in which unit members can thrive professionally. Our recommendations focus on the key areas of: 1) funding sources and mechanisms; 2) providing and prioritizing access to biostatistical resources; and 3) interacting with investigators. We recommend that the leadership of biostatistics units negotiate for sufficient long-term infrastructure support to ensure stability and continuity of funding for personnel, align project budgets closely with actual level of biostatistical effort, devise and consistently apply strategies for prioritizing and tracking effort on studies, and clearly stipulate with investigators prior to project initiation policies regarding funding, lead time, and authorship