Desensitization and remission after peanut sublingual immunotherapy in 1- to 4-year-old peanut-allergic children: A randomized, placebo-controlled trial.

BACKGROUND: Prior studies of peanut sublingual immunotherapy (SLIT) have suggested a potential advantage with younger age at treatment initiation. OBJECTIVE: We studied the safety and efficacy of SLIT for peanut allergy in 1- to 4-year-old children. METHODS: Peanut-allergic 1- to 4-year-old children were randomized to receive 4 mg peanut SLIT versus placebo. Desensitization was assessed by double-blind, placebo-controlled food challenge (DBPCFC) after 36 months of treatment. Participants desensitized to at least 443 mg peanut protein discontinued therapy for 3 months and then underwent DBPCFC to assess for remission. Biomarkers were measured at baseline and longitudinally during treatment. RESULTS: Fifty participants (25 peanut SLIT, 25 placebo) with a median age of 2.4 years were enrolled across 2 sites. The primary end point of desensitization was met with actively treated versus placebo participants having a significantly greater median cumulative tolerated dose (4443 mg vs 143 mg), higher likelihood of passing the month 36 DBPCFC (60% vs 0), and higher likelihood of demonstrating remission (48% vs 0). The highest rate of desensitization and remission was seen in 1- to 2-year-olds, followed by 2- to 3-year-olds and 3- to 4-year-olds. Longitudinal changes in peanut skin prick testing, peanut-specific IgG4, and peanut-specific IgG4/IgE ratio were seen in peanut SLIT but not placebo participants. Oropharyngeal itching was more commonly reported by peanut SLIT than placebo participants. Skin, gastrointestinal, upper respiratory, lower respiratory, and multisystem adverse events were similar between treatment groups. CONCLUSION: Peanut SLIT safely induces desensitization and remission in 1- to 4-year-old children, with improved outcomes seen with younger age at initiation.

Row versus column correlations: avoiding the ecological fallacy in RNA/protein expression studies.

Biomedical researchers are often interested in computing the correlation between RNA and protein abundance. However, correlations can be computed between rows of a data matrix or between columns, and the results are not the same. The belief that these two types of correlation are estimating the same phenomenon is a special case of a well-known logical error called the ecological fallacy. In this article, we review different uses of correlation found in the literature, explain the differences between row and column correlations and argue that one of them has an undesirable interpretation in most applications. Through simulation studies and theoretical derivations, we show that the commonly used Pearson's coefficient, computed from protein and transcript data from a single sample, is only loosely related to the biological correlation that most researchers will be interested in studying. Beyond our basic exploration of the ecological fallacy, we examine how correlations are affected by relative quantification proteomics data and common normalization procedures, finding that double normalization is capable of completely masking true correlative relationships. We conclude with guidelines for properly identifying and computing consistent correlation coefficients.

Power calculations for the sequential parallel comparison design with continuous outcomes.

In the sequential parallel comparison design (SPCD) in stage 1, placebo subjects are randomized between placebo and an experimental therapy. In stage 2, stage 1 placebo non-responders are re-randomized between placebo and an experimental therapy. We give the formula for power/sample size calculations for two test statistics for the SPCD. The first one omits the correlation between the estimated treatment effects from the two stages, and the second one does not. We discuss how to construct a confidence interval for the weighted average of the treatment effects that has proper coverage.

Accelerating high-dimensional clustering with lossless data reduction.

MOTIVATION: For cluster analysis, high-dimensional data are associated with instability, decreased classification accuracy and high-computational burden. The latter challenge can be eliminated as a serious concern. For applications where dimension reduction techniques are not implemented, we propose a temporary transformation which accelerates computations with no loss of information. The algorithm can be applied for any statistical procedure depending only on Euclidean distances and can be implemented sequentially to enable analyses of data that would otherwise exceed memory limitations. RESULTS: The method is easily implemented in common statistical software as a standard pre-processing step. The benefit of our algorithm grows with the dimensionality of the problem and the complexity of the analysis. Consequently, our simple algorithm not only decreases the computation time for routine analyses, it opens the door to performing calculations that may have otherwise been too burdensome to attempt. AVAILABILITY AND IMPLEMENTATION: R, Matlab and SAS/IML code for implementing lossless data reduction is freely available in the Appendix. CONTACT: obrienj@hms.harvard.edu.

QuantFusion: Novel Unified Methodology for Enhanced Coverage and Precision in Quantifying Global Proteomic Changes in Whole Tissues.

Single quantitative platforms such as label-based or label-free quantitation (LFQ) present compromises in accuracy, precision, protein sequence coverage, and speed of quantifiable proteomic measurements. To maximize the quantitative precision and the number of quantifiable proteins or the quantifiable coverage of tissue proteomes, we have developed a unified approach, termed QuantFusion, that combines the quantitative ratios of all peptides measured by both LFQ and label-based methodologies. Here, we demonstrate the use of QuantFusion in determining the proteins differentially expressed in a pair of patient-derived tumor xenografts (PDXs) representing two major breast cancer (BC) subtypes, basal and luminal. Label-based in-spectra quantitative peptides derived from amino acid-coded tagging (AACT, also known as SILAC) of a non-malignant mammary cell line were uniformly added to each xenograft with a constant predefined ratio, from which Ratio-of-Ratio estimates were obtained for the label-free peptides paired with AACT peptides in each PDX tumor. A mixed model statistical analysis was used to determine global differential protein expression by combining complementary quantifiable peptide ratios measured by LFQ and Ratio-of-Ratios, respectively. With minimum number of replicates required for obtaining the statistically significant ratios, QuantFusion uses the distinct mechanisms to "rescue" the missing data inherent to both LFQ and label-based quantitation. Combined quantifiable peptide data from both quantitative schemes increased the overall number of peptide level measurements and protein level estimates. In our analysis of the PDX tumor proteomes, QuantFusion increased the number of distinct peptide ratios by 65%, representing differentially expressed proteins between the BC subtypes. This quantifiable coverage improvement, in turn, not only increased the number of measurable protein fold-changes by 8% but also increased the average precision of quantitative estimates by 181% so that some BC subtypically expressed proteins were rescued by QuantFusion. Thus, incorporating data from multiple quantitative approaches while accounting for measurement variability at both the peptide and global protein levels make QuantFusion unique for obtaining increased coverage and quantitative precision for tissue proteomes.

Mucus Hydration in Subjects with Stable Chronic Bronchitis: A Comparison of Spontaneous and Induced Sputum.

Mucus hydration is important in mucus clearance and lung health. This study sought to test the relative utility of spontaneous sputum (SS) versus the reasonably noninvasive induced sputum (IS) samples for measurement of mucus hydration. SS and IS samples were collected over a 2-day study interval. Sputum was induced with escalating inhaled nebulized 3-5% hypertonic saline. Viscous portions of the samples ("plugs") were utilized for percent solids and total mucin analyses. Cytokines, nucleotides/nucleosides and cell differentials were measured in plugs diluted into 0.1% Sputolysin. Overall, 61.5% of chronic bronchitis (CB) subjects produced a SS sample and 95.2% an IS sample. Total expectorate sample weights were less for the SS (0.94 ± 0.98 g) than the IS (2.67 ± 2.33 g) samples. Percent solids for the SS samples (3.56% ± 1.95; n = 162) were significantly greater than the IS samples (3.08% ± 1.81; n = 121), p = 0.133. Total mucin concentrations also exhibited a dilution of the IS samples: SS = 4.15 ± 3.23 mg/ml (n = 62) versus IS= 3.34 ± 2.55 mg/ml (n = 71) (p = 0.371). Total mucins (combined SS and IS) but not percent solids, were inversely associated with FEV1 percent predicted (p = 0.052) and FEV1,/FVC % (p = 0.035). There were no significant differences between sample types in cytokine or differential cell counts. The probability of sample collections was less for SS than IS samples. Measurements of hydration revealed modest dilution of the IS samples compared to SS. Thus for measurements of mucus hydration, both SS and IS samples appear to be largely interchangeable.

The Relationship of Mucus Concentration (Hydration) to Mucus Osmotic Pressure and Transport in Chronic Bronchitis.

RATIONALE: Chronic bronchitis (CB) is characterized by persistent cough and sputum production. Studies were performed to test whether mucus hyperconcentration and increased partial osmotic pressure, in part caused by abnormal purine nucleotide regulation of ion transport, contribute to the pathogenesis of CB. OBJECTIVES: We tested the hypothesis that CB is characterized by mucus hyperconcentration, increased mucus partial osmotic pressures, and reduced mucus clearance. METHODS: We measured in subjects with CB as compared with normal and asymptomatic smoking control subjects indices of mucus concentration (hydration; i.e., percentage solids) and sputum adenine nucleotide/nucleoside concentrations. In addition, sputum partial osmotic pressures and mucus transport rates were measured in subjects with CB. MEASUREMENTS AND RESULTS: CB secretions were hyperconcentrated as indexed by an increase in percentage solids and total mucins, in part reflecting decreased extracellular nucleotide/nucleoside concentrations. CB mucus generated concentration-dependent increases in partial osmotic pressures into ranges predicted to reduce mucus transport. Mucociliary clearance (MCC) in subjects with CB was negatively correlated with mucus concentration (percentage solids). As a test of relationships between mucus concentration and disease, mucus concentrations and MCC were compared with FEV1, and both were significantly correlated. CONCLUSIONS: Abnormal regulation of airway surface hydration may slow MCC in CB and contribute to disease pathogenesis.

Alloimmunization is associated with older age of transfused red blood cells in sickle cell disease.

Red blood cell (RBC) alloimmunization is a significant clinical complication of sickle cell disease (SCD). It can lead to difficulty with cross-matching for future transfusions and may sometimes trigger life-threatening delayed hemolytic transfusion reactions. We conducted a retrospective study to explore the association of clinical complications and age of RBC with alloimmunization in patients with SCD followed at a single institution from 2005 to 2012. One hundred and sixty six patients with a total of 488 RBC transfusions were evaluated. Nineteen patients (11%) developed new alloantibodies following blood transfusions during the period of review. The median age of RBC units was 20 days (interquartile range: 14-27 days). RBC antibody formation was significantly associated with the age of RBC units (P = 0.002), with a hazard ratio of 3.5 (95% CI: 1.71-7.11) for a RBC unit that was 7 days old and 9.8 (95% CI: 2.66-35.97) for a unit that was 35 days old, 28 days after the blood transfusion. No association was observed between RBC alloimmunization and acute vaso-occlusive complications. Although increased echocardiography-derived tricuspid regurgitant jet velocity (TRV) was associated with the presence of RBC alloantibodies (P = 0.02), TRV was not significantly associated with alloimmunization when adjusted for patient age and number of transfused RBC units. Our study suggests that RBC antibody formation is significantly associated with older age of RBCs at the time of transfusion. Prospective studies in patients with SCD are required to confirm this finding.

Cutting Edge: Brazilian pemphigus foliaceus anti-desmoglein 1 autoantibodies cross-react with sand fly salivary LJM11 antigen.

The environmental factors that contribute to the development of autoimmune diseases are largely unknown. Endemic pemphigus foliaceus in humans, known as Fogo Selvagem (FS) in Brazil, is mediated by pathogenic IgG4 autoantibodies against desmoglein 1 (Dsg1). Clusters of FS overlap with those of leishmaniasis, a disease transmitted by sand fly (Lutzomyia longipalpis) bites. In this study, we show that salivary Ags from the sand fly, and specifically the LJM11 salivary protein, are recognized by FS Abs. Anti-Dsg1 monoclonal autoantibodies derived from FS patients also cross-react with LJM11. Mice immunized with LJM11 generate anti-Dsg1 Abs. Thus, insect bites may deliver salivary Ags that initiate a cross-reactive IgG4 Ab response in genetically susceptible individuals and lead to subsequent FS. Our findings establish a clear relationship between an environmental, noninfectious Ag and the development of potentially pathogenic autoantibodies in an autoimmune disease.

Kappa statistic for clustered dichotomous responses from physicians and patients.

The bootstrap method for estimating the standard error of the kappa statistic in the presence of clustered data is evaluated. Such data arise, for example, in assessing agreement between physicians and their patients regarding their understanding of the physician-patient interaction and discussions. We propose a computationally efficient procedure for generating correlated dichotomous responses for physicians and assigned patients for simulation studies. The simulation result demonstrates that the proposed bootstrap method produces better estimate of the standard error and better coverage performance compared with the asymptotic standard error estimate that ignores dependence among patients within physicians with at least a moderately large number of clusters. We present an example of an application to a coronary heart disease prevention study.

Facilitators of transforming primary care: a look under the hood at practice leadership.

PURPOSE: This study examined how characteristics of practice leadership affect the change process in a statewide initiative to improve the quality of diabetes and asthma care. METHODS: We used a mixed methods approach, involving analyses of existing quality improvement data on 76 practices with at least 1 year of participation and focus groups with clinicians and staff in a 12-practice subsample. Existing data included monthly diabetes or asthma measures (clinical measures) and monthly practice implementation, leadership, and practice engagement scores rated by an external practice coach. RESULTS: Of the 76 practices, 51 focused on diabetes and 25 on asthma. In aggregate, 50% to 78% made improvements within in each clinical measure in the first year. The odds of making practice changes were greater for practices with higher leadership scores (odds ratios = 2.41-4.20). Among practices focused on diabetes, those with higher leadership scores had higher odds of performing nephropathy screening (odds ratio = 1.37, 95% CI, 1.08-1.74); no significant associations were seen for the intermediate outcome measures of hemoglobin A1c, blood pressure, and cholesterol. Focus groups revealed the importance of a leader, typically a physician, who believed in the transformation work (ie, a visionary leader) and promoted practice engagement through education and cross-training. Practices with greater change implementation also mentioned the importance of a midlevel operational leader who helped to create and sustain practice changes. This person communicated and interacted well with, and was respected by both clinicians and staff. CONCLUSIONS: In the presence of a vision for transformation, operational leaders within practices can facilitate practice changes that are associated with clinical improvement.

Review of feature selection approaches based on grouping of features.

With the rapid development in technology, large amounts of high-dimensional data have been generated. This high dimensionality including redundancy and irrelevancy poses a great challenge in data analysis and decision making. Feature selection (FS) is an effective way to reduce dimensionality by eliminating redundant and irrelevant data. Most traditional FS approaches score and rank each feature individually; and then perform FS either by eliminating lower ranked features or by retaining highly-ranked features. In this review, we discuss an emerging approach to FS that is based on initially grouping features, then scoring groups of features rather than scoring individual features. Despite the presence of reviews on clustering and FS algorithms, to the best of our knowledge, this is the first review focusing on FS techniques based on grouping. The typical idea behind FS through grouping is to generate groups of similar features with dissimilarity between groups, then select representative features from each cluster. Approaches under supervised, unsupervised, semi supervised and integrative frameworks are explored. The comparison of experimental results indicates the effectiveness of sequential, optimization-based (i.e., fuzzy or evolutionary), hybrid and multi-method approaches. When it comes to biological data, the involvement of external biological sources can improve analysis results. We hope this work's findings can guide effective design of new FS approaches using feature grouping.

The Performance of Flash Replenishment Contrast-Enhanced Ultrasound for the Qualitative Assessment of Kidney Lesions in Patients with Chronic Kidney Disease.

We investigated the accuracy of CEUS for characterizing cystic and solid kidney lesions in patients with chronic kidney disease (CKD). Cystic lesions are assessed using Bosniak criteria for computed tomography (CT) and magnetic resonance imaging (MRI); however, in patients with moderate to severe kidney disease, CT and MRI contrast agents may be contraindicated. Contrast-enhanced ultrasound (CEUS) is a safe alternative for characterizing these lesions, but data on its performance among CKD patients are limited. We performed flash replenishment CEUS in 60 CKD patients (73 lesions). Final analysis included 53 patients (63 lesions). Four readers, blinded to true diagnosis, interpreted each lesion. Reader evaluations were compared to true lesion classifications. Performance metrics were calculated to assess malignant and benign diagnoses. Reader agreement was evaluated using Bowker's symmetry test. Combined reader sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for diagnosing malignant lesions were 71%, 75%, 45%, and 90%, respectively. Sensitivity (81%) and specificity (83%) were highest in CKD IV/V patients when grouped by CKD stage. Combined reader sensitivity, specificity, PPV, and NPV for diagnosing benign lesions were 70%, 86%, 91%, and 61%, respectively. Again, in CKD IV/V patients, sensitivity (81%), specificity (95%), and PPV (98%) were highest. Inter-reader diagnostic agreement varied from 72% to 90%. In CKD patients, CEUS is a potential low-risk option for screening kidney lesions. CEUS may be particularly beneficial for CKD IV/V patients, where kidney preservation techniques are highly relevant.

Translating research into practice: the role of provider-based research networks in the diffusion of an evidence-based colon cancer treatment innovation.

BACKGROUND: Provider-based research networks (PBRNs)--collaborative research partnerships between academic centers and community-based practitioners--are a promising model for accelerating the translation of research into practice; however, empirical evidence of accelerated translation is limited. Oxaliplatin in adjuvant combination chemotherapy is an innovation with clinical trial-proven survival benefit compared with prior therapies. The goal of this study is to examine the diffusion of oxaliplatin into community practice, and whether affiliation with the National Cancer Institute's (NCI's) Community Clinical Oncology Program (CCOP)--a nationwide cancer-focused PBRN--is associated with accelerated innovation adoption. DESIGN, SETTING, AND PARTICIPANTS: This retrospective observational study used linked Surveillance, Epidemiology, and End Results-Medicare and NCI CCOP data to examine Medicare participants with stage III colon cancer initiating treatment in 2003 through 2006, the years surrounding oxaliplatin's Food and Drug Administration approval. A fixed-effects analysis examined chemotherapy use among patients treated outside academic centers at CCOP-affiliated practices compared with non-CCOP practices. Two-group modeling controlled for multiple levels of clustering, year of chemotherapy initiation, tumor characteristics, patient age, race, comorbidity, Medicaid dual-eligibility status, and education. RESULTS: Of 4055 community patients, 35% received 5-fluoruracil, 20% received oxaliplatin, 7% received another chemotherapy, and 38% received no chemotherapy. Twenty-five percent of CCOP patients received oxaliplatin, compared with 19% of non-CCOP patients. In multivariable analysis, CCOP exposure was associated with higher odds of receiving guideline-concordant treatment in general, and oxaliplatin specifically. CONCLUSIONS: These findings contribute to a growing set of evidence linking PBRNs with a greater probability of receiving treatment innovations and high-quality cancer care, with implications for clinical and research policy.

Group testing for case identification with correlated responses.

This article examines group testing procedures where units within a group (or pool) may be correlated. The expected number of tests per unit (i.e., efficiency) of hierarchical- and matrix-based procedures is derived based on a class of models of exchangeable binary random variables. The effect on efficiency of the arrangement of correlated units within pools is then examined. In general, when correlated units are arranged in the same pool, the expected number of tests per unit decreases, sometimes substantially, relative to arrangements that ignore information about correlation.

Deletion diagnostics for alternating logistic regressions.

Deletion diagnostics are introduced for the regression analysis of clustered binary outcomes estimated with alternating logistic regressions, an implementation of generalized estimating equations (GEE) that estimates regression coefficients in a marginal mean model and in a model for the intracluster association given by the log odds ratio. The diagnostics are developed within an estimating equations framework that recasts the estimating functions for association parameters based upon conditional residuals into equivalent functions based upon marginal residuals. Extensions of earlier work on GEE diagnostics follow directly, including computational formulae for one-step deletion diagnostics that measure the influence of a cluster of observations on the estimated regression parameters and on the overall marginal mean or association model fit. The diagnostic formulae are evaluated with simulations studies and with an application concerning an assessment of factors associated with health maintenance visits in primary care medical practices. The application and the simulations demonstrate that the proposed cluster-deletion diagnostics for alternating logistic regressions are good approximations of their exact fully iterated counterparts.

Non-small cell lung cancer: prognostic importance of positive FDG PET findings in the mediastinum for patients with N0-N1 disease at pathologic analysis.

PURPOSE: To assess the prognostic implications of mediastinal positron emission tomographic (PET) findings in patients undergoing curative resection of non-small cell lung cancer (NSCLC) who have histologically negative mediastinal lymph nodes (LNs), with the hypothesis that positive findings at PET are prognostic even in patients with negative histologic findings in the LNs. MATERIALS AND METHODS: Records of patients with a preoperative PET undergoing curative surgery, without adjuvant radiation, for pathologic T1-3N0-1 NSCLC at the University of North Carolina between 2000 and 2006 were reviewed as an institutional review board-approved HIPAA-compliant retrospective study. Ninety patients were evaluable (all histologically negative in mediastinum; 44 with both mediastinoscopy and surgery); 13 patients had positive mediastinal PET findings, and 77 had negative mediastinal PET findings. Local-regional and distant failure rates in patients with and those without mediastinal abnormalities at preoperative PET were compared by using logistic regression and log-rank tests. RESULTS: Median follow-up was 54.3 months (range, 1-99 months). There were higher rates of local-regional (P = .001) and distant (P < .001) failure as well as death (P = .001) in patients with postive PET findings than in patients with negative findings. In multivariable analysis (adjusting for other prognostic factors), positive PET findings in the mediastinum remained prognostic for distant failure (P < .001, hazard ratio = 6.9) and were marginally prognostic for local-regional failure (P = .093, hazard ratio = 1.9). CONCLUSION: Positive findings at preoperative PET in the mediastinum appear to have prognostic implications despite the mediastinal LNs being histologically negative. The high rate of local-regional and distant failure suggests that postoperative radiation therapy and/or chemotherapy may be particularly helpful in patients with positive mediastinal findings at preoperative PET.

Optimality, sample size, and power calculations for the sequential parallel comparison design.

The sequential parallel comparison design (SPCD) has been proposed to increase the likelihood of success of clinical trials in therapeutic areas where high-placebo response is a concern. The trial is run in two stages, and subjects are randomized into three groups: (i) placebo in both stages; (ii) placebo in the first stage and drug in the second stage; and (iii) drug in both stages. We consider the case of binary response data (response/no response). In the SPCD, all first-stage and second-stage data from placebo subjects who failed to respond in the first stage of the trial are utilized in the efficacy analysis. We develop 1 and 2 degree of freedom score tests for treatment effect in the SPCD. We give formulae for asymptotic power and for sample size computations and evaluate their accuracy via simulation studies. We compute the optimal allocation ratio between drug and placebo in stage 1 for the SPCD to determine from a theoretical viewpoint whether a single-stage design, a two-stage design with placebo only in the first stage, or a two-stage design is the best design for a given set of response rates. As response rates are not known before the trial, a two-stage approach with allocation to active drug in both stages is a robust design choice.

A Lutzomyia longipalpis Salivary Protein Induces Cross-Reactive Antibodies to Pemphigus Autoantigen Desmoglein 1.

Fogo selvagem (FS) is a blistering skin disease caused by pathogenic IgG4 autoantibodies to desmoglein 1 (DSG1). Preclinical FS and leishmaniasis are endemic to certain regions of Brazil and exhibit nonpathogenic anti-DSG1 antibodies. Recurring bites from Lutzomyia longipalpis, the sand fly vector of leishmaniasis, immunize individuals with L. longipalpis salivary antigens LJM17 and LJM11. We measured the antibody responses to LJM17, LJM11, and DSG1 in normal settlers and patients with FS from an endemic focus of FS and nonendemic control populations. We also immunized mice with these antigens and assessed the IgG response. Healthy individuals and patients with FS from endemic areas had significantly higher values of IgG4 anti-LJM17 antibodies than nonendemic controls (P < 0.001 for both). The levels of IgG anti-DSG1 and IgG4 anti-LJM17 and anti-LJM11 antibodies correlated positively in normal settlers and patients with FS. Mice immunized with recombinant LJM17 produced IgG1 antibodies (human IgG4 homolog) that strongly cross-reacted with recombinant DSG1; these IgG1 antibodies were inhibited by LJM17, LJM11, and DSG1 in a dose-dependent manner. However, they did not bind human or mouse epidermis by indirect immunofluorescence. Lastly, we identified short-sequence homologies of surface-exposed residues within the human DSG1 ectodomain and LJM17. Inoculation by LJM17 from L. longipalpis-elicited DSG1-cross-reactive IgG4 antibodies may lead to FS in genetically predisposed individuals.

An R2 statistic for fixed effects in the linear mixed model.

Statisticians most often use the linear mixed model to analyze Gaussian longitudinal data. The value and familiarity of the R(2) statistic in the linear univariate model naturally creates great interest in extending it to the linear mixed model. We define and describe how to compute a model R(2) statistic for the linear mixed model by using only a single model. The proposed R(2) statistic measures multivariate association between the repeated outcomes and the fixed effects in the linear mixed model. The R(2) statistic arises as a 1-1 function of an appropriate F statistic for testing all fixed effects (except typically the intercept) in a full model. The statistic compares the full model with a null model with all fixed effects deleted (except typically the intercept) while retaining exactly the same covariance structure. Furthermore, the R(2) statistic leads immediately to a natural definition of a partial R(2) statistic. A mixed model in which ethnicity gives a very small p-value as a longitudinal predictor of blood pressure (BP) compellingly illustrates the value of the statistic. In sharp contrast to the extreme p-value, a very small R(2) , a measure of statistical and scientific importance, indicates that ethnicity has an almost negligible association with the repeated BP outcomes for the study.