The effects of nonignorable missing data on label-free mass spectrometry proteomics experiments.

An idealized version of a label-free discovery mass spectrometry proteomics experiment would provide absolute abundance measurements for a whole proteome, across varying conditions. Unfortunately, this ideal is not realized. Measurements are made on peptides requiring an inferential step to obtain protein level estimates. The inference is complicated by experimental factors that necessitate relative abundance estimation and result in widespread non-ignorable missing data. Relative abundance on the log scale takes the form of parameter contrasts. In a complete-case analysis, contrast estimates may be biased by missing data and a substantial amount of useful information will often go unused. To avoid problems with missing data, many analysts have turned to single imputation solutions. Unfortunately, these methods often create further difficulties by hiding inestimable contrasts, preventing the recovery of interblock information and failing to account for imputation uncertainty. To mitigate many of the problems caused by missing values, we propose the use of a Bayesian selection model. Our model is tested on simulated data, real data with simulated missing values, and on a ground truth dilution experiment where all of the true relative changes are known. The analysis suggests that our model, compared with various imputation strategies and complete-case analyses, can increase accuracy and provide substantial improvements to interval coverage.

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.

Divergent Specificity Development of IgG1 and IgG4 Autoantibodies in Endemic Pemphigus Foliaceus (Fogo Selvagem).

We have shown that although the IgG response in fogo selvagem (FS) is mainly restricted to desmoglein (Dsg) 1, other keratinocyte cadherins are also targeted by FS patients and healthy control subjects living in the endemic region of Limão Verde, Brazil (endemic controls). Evaluating nonpathogenic IgG1 and pathogenic IgG4 subclass responses to desmosomal proteins may reveal important differences between pathogenic and nonpathogenic responses, and how these differences relate to the pathogenic IgG4 response and resultant FS. In this study, we tested by ELISA >100 sera from each FS patient, endemic control, and nonendemic control for IgG1 and IgG4 autoantibodies to keratinocyte cadherins besides Dsg1. IgG1 and IgG4 subclass responses in endemic controls are highly correlated between Dsg1 and other keratinocyte cadherins. This correlation persists in the IgG1 response among FS patients, but diminishes in IgG4 response, suggesting that IgG1 binds highly conserved linear epitopes among cadherins, whereas IgG4 binds mainly specific conformational epitopes on Dsg1. A confirmatory test comparing serum samples of 11 individuals before and after their FS onset substantiated our findings that IgG1 recognizes primarily linear epitopes on Dsg1 both before and after disease onset, whereas IgG4 recognizes primarily linear epitopes before disease onset, but recognizes more conformational epitopes on Dsg1 after the onset of disease. This study may provide a mechanism by which a specificity convergence of the IgG4 response to unique Dsg1 epitopes, most likely conformational pathogenic epitopes, leads to the onset of FS disease.

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.

Cancer Risk after Fat Transfer: A Multicenter Case-Cohort Study.

BACKGROUND: Fat transfer is an increasingly popular method for refining postmastectomy breast reconstructions. However, concern persists that fat transfer may promote disease recurrence. Adipocytes are derived from adipose-derived stem cells and express adipocytokines that can facilitate active breast cancer cells in laboratory models. The authors sought to evaluate the association between fat transfer to the reconstructed breast and cancer recurrence in patients diagnosed with local or regional invasive breast cancers. METHODS: A multicenter, case-cohort study was performed. Eligible patients from four centers (Memorial Sloan Kettering, M. D. Anderson Cancer Center, Alvin J. Siteman Cancer Center, and the University of Chicago) were identified by each site's institutional tumor registry or cancer data warehouse. Eligibility criteria were as follows: mastectomy with immediate breast reconstruction between 2006 and 2011, age older than 21 years, female sex, and incident diagnosis of invasive ductal carcinoma (stage I, II, or III). Cases consisted of all recurrences during the study period, and controls consisted of a 30 percent random sample of the study population. Cox proportional hazards regression was used to evaluate for association between fat transfer and time to recurrence in bivariate and multivariate models. RESULTS: The time to disease recurrence unadjusted hazard ratio for fat transfer was 0.99 (95 percent CI, 0.56 to 1.7). After adjustment for age, body mass index, stage, HER2/Neu receptor status, and estrogen receptor status, the hazard ratio was 0.97 (95 percent CI, 0.54 to 1.8). CONCLUSION: In this population of breast cancer patients who had mastectomy with immediate reconstruction, fat transfer was not associated with a higher risk of cancer recurrence. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, III.

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.

Unanticipated hospital admissions during or soon after radiation therapy: Incidence and predictive factors.

PURPOSE: Unplanned hospital admissions in cancer patients undergoing treatment is an understudied area with important implications for both health care costs and patient outcomes. The goal of this retrospective study was to evaluate the rate, reasons for, and predictors of unplanned hospital admissions during or soon after palliative or curative radiation therapy for cancer, with or without chemotherapy. METHODS AND MATERIALS: A total of 1116 consecutive patients who received external beam radiation therapy for a malignancy at the University of North Carolina at Chapel Hill from January 1 through December 31, 2010, were studied. The primary outcome was unplanned hospitalization within 90 days of starting radiation therapy (ie, during or soon after). Multivariable logistic regression was used to examine patient and treatment factors associated with admissions. RESULTS: Twenty percent of patients experienced an unplanned admission, which was especially likely in patients with lung (25% of such patients admitted), head and neck (22%), and gastrointestinal (21%) cancers, as well as those treated with palliative intent (31%). The most common causes for admission were gastrointestinal symptoms, neurologic symptoms, respiratory symptoms, pain, and fever or infection. Forty-seven percent of admitted patients were seen in the clinic within 2 weeks of unplanned hospital admission, and 61% of those patients had a related complaint in the clinic. Multivariate analysis showed that married patients (odds ratio [OR] = 0.58; P < .001), curative intent (OR = 0.38; P < .001), and no concurrent chemotherapy (OR = 0.55; P < .001) were associated with decreased odds for admission. CONCLUSIONS: Unplanned admissions are relatively common during or soon after radiation therapy in our patient series. Additional work is needed to gather data from other centers and to better understand, and hopefully reduce, these unplanned admissions.

The fidelity of the ligation step determines how ends are resolved during nonhomologous end joining.

Nonhomologous end joining (NHEJ) can effectively resolve chromosome breaks despite diverse end structures; however, it is unclear how the steps employed for resolution are determined. We sought to address this question by analysing cellular NHEJ of ends with systematically mispaired and damaged termini. We show NHEJ is uniquely proficient at bypassing subtle terminal mispairs and radiomimetic damage by direct ligation. Nevertheless, bypass ability varies widely, with increases in mispair severity gradually reducing bypass products from 85 to 6%. End-processing by nucleases and polymerases is increased to compensate, although paths with the fewest number of steps to generate a substrate suitable for ligation are favoured. Thus, both the frequency and nature of end processing are tailored to meet the needs of the ligation step. We propose a model where the ligase organizes all steps during NHEJ within the stable paired-end complex to limit end processing and associated errors.

ORTH: R and SAS software for regression models of correlated binary data based on orthogonalized residuals and alternating logistic regressions.

This article describes a new software for modeling correlated binary data based on orthogonalized residuals, a recently developed estimating equations approach that includes, as a special case, alternating logistic regressions. The software is flexible with respect to fitting in that the user can choose estimating equations for association models based on alternating logistic regressions or orthogonalized residuals, the latter choice providing a non-diagonal working covariance matrix for second moment parameters providing potentially greater efficiency. Regression diagnostics based on this method are also implemented in the software. The mathematical background is briefly reviewed and the software is applied to medical data sets.

Validation of interobserver agreement in lung cancer assessment: hematoxylin-eosin diagnostic reproducibility for non-small cell lung cancer: the 2004 World Health Organization classification and therapeutically relevant subsets.

CONTEXT: Precise subtype diagnosis of non-small cell lung carcinoma is increasingly relevant, based on the availability of subtype-specific therapies, such as bevacizumab and pemetrexed, and based on the subtype-specific prevalence of activating epidermal growth factor receptor mutations. OBJECTIVES: To establish a baseline measure of interobserver reproducibility for non-small cell lung carcinoma diagnoses with hematoxylin-eosin for the current 2004 World Health Organization classification, to estimate interobserver reproducibility for the therapeutically relevant squamous/nonsquamous subsets, and to examine characteristics that improve interobserver reproducibility. DESIGN: Primary, resected lung cancer specimens were converted to digital (virtual) slides. Based on a single hematoxylin-eosin virtual slide, pathologists were asked to assign a diagnosis using the 2004 World Health Organization classification. Kappa statistics were calculated for each pathologist-pair for each slide and were summarized by classification scheme, pulmonary pathology expertise, diagnostic confidence, and neoplastic grade. RESULTS: The 12 pulmonary pathology experts and the 12 community pathologists each independently diagnosed 48 to 96 single hematoxylin-eosin digital slides derived from 96 cases of non-small cell lung carcinoma resection. Overall agreement improved with simplification from the comprehensive 44 World Health Organization diagnoses (κ  =  0.25) to their 10 major header subtypes (κ  =  0.48) and improved again with simplification into the therapeutically relevant squamous/nonsquamous dichotomy (κ  =  0.55). Multivariate analysis showed that higher diagnostic agreement was associated with better differentiation, better slide quality, higher diagnostic confidence, similar years of pathology experience, and pulmonary pathology expertise. CONCLUSIONS: These data define the baseline diagnostic agreement for hematoxylin-eosin diagnosis of non-small cell lung carcinoma, allowing future studies to test for improved diagnostic agreement with reflex ancillary tests.

Orthogonalized residuals for estimation of marginally specified association parameters in multivariate binary data.

This paper focuses on marginal regression models for correlated binary responses when estimation of the association structure is of primary interest. A new estimating function approach based on orthogonalized residuals is proposed. A special case of the proposed procedure allows a new representation of the alternating logistic regressions method through marginal residuals. The connections between second-order generalized estimating equations, alternating logistic regressions, pseudo-likelihood and other methods are explored. Eficiency comparisons are presented, with emphasis on variable cluster size and on the role of higher-order assumptions. The new method is illustrated with an analysis of data on impaired pulmonary function.

IgG autoantibody response against keratinocyte cadherins in endemic pemphigus foliaceus (fogo selvagem).

It is well established that autoantibodies against desmoglein 3 and desmoglein 1 (Dsg1) are relevant in the pathogenesis of pemphigus vulgaris and pemphigus foliaceus, including its endemic form fogo selvagem (FS). Isolated reports have shown that in certain patients with these diseases, autoantibodies against other desmosomal cadherins and E-cadherin may also be present. The goal of this investigation was to determine whether FS patients and normal individuals living in endemic areas possess autoantibodies against other desmosomal cadherins and E-cadherin. By testing a large number of FS and endemic control sera by ELISA, we found a consistent and specific autoantibody response against Dsg1 and other keratinocyte cadherins in these individuals, which is quite different from healthy individuals from the United States (US controls). Overall, the highest correlations among the autoantibody responses tested were in the endemic controls, followed by FS patients, and lowest in the US controls. These findings suggest that multiple, perhaps cross-reactive, keratinocyte cadherins are recognized by FS patients and endemic controls.

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.

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.

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.

Large vestibular aqueduct syndrome: anatomic and functional parameters.

OBJECTIVES/HYPOTHESIS: To correlate imaging and audiologic findings in patients with large vestibular aqueduct syndrome (LVAS). STUDY DESIGN: Retrospective analysis. METHODS: Thirty-eight patients with LVAS evident on magnetic resonance imaging with available clinical and audiometric data were selected from the databases of the study institution. Images were analyzed for endolymphatic sac and duct size, evidence of incomplete cochlear partitioning, and endolymphatic sac signal heterogeneity. The endolymphatic duct was measured in two different locations: near the vestibular aperture (ED(VA)) and at the midpoint between the common crus and the operculum (ED(MID)). Imaging data were correlated with audiologic variables. RESULTS: There was significant correlation between ears for the audiologic and anatomic variables collected. Twenty-one (62%) patients had a fluctuating or progressive hearing loss, and 13 (38%) remained stable (four were not evaluable). At the time of the analysis, 41% of ears had a profound loss. Significant correlation was identified between the presence of endolymphatic signal heterogeneity and worse pure tone average (PTA). ED(VA) measures were significantly larger among ears with a progressive pattern of hearing loss when compared to those that were stable. Also, ED(VA) correlated with PTA and the presence of progressive hearing loss, but ED(MID) had no such a relationship. CONCLUSIONS: Evidence of endolymphatic sac signal heterogeneity and larger measures of endolymphatic width when measured near the vestibule (ED(VA)) are markers of poorer hearing in these patients. By contrast, midpoint measures of the endolymphatic duct (ED(MID)) have no correlation with audiometric parameters.

Local failure after complete resection of N0-1 non-small cell lung cancer.

PURPOSE: To estimate the risk of local-regional failure (LRF) after surgery for operable NSCLC, and the effect of clinical/pathologic factors on this risk. METHODS: Records of 335 patients undergoing complete resection (lobectomy, pneumonectomy) for pathological T1-4 N0-1 NSCLC (without post-operative radiation) from 1996 to 2006 were reviewed. Crude and actuarial estimated failure rates were computed; local-regional sites included ipsilateral lung, surgical stump, hilar, mediastinal, or supraclavicular nodes. Failure times in sub-groups were calculated with the Kaplan-Meier method and compared via log-rank test. Independent factors adversely affecting LRF were determined with Cox regression. RESULTS: The median follow-up duration for event-free surviving patients was 40 months (range: 1-150). The crude and actuarial 5-year probability of any failure (LR or distant) were 33% and 43%, respectively. Of all failures; 37% were LR only, 35% LR and distant and 28% distant only. The 5-year crude and actuarial probability of LRF were 24% and 35% (95% CI: 29-42%). Five-year crude LRF rates for T1-2N0, T1-2N1, T3-4N0 and T3-4N1 disease were 19% (41/216), 27% (16/59), 37.5% (15/40) and 40% (8/20), respectively. The corresponding actuarial estimates were T1-2N0 28%, T1-2N1 39%, T3-4N0 50% and T3-4N1 67%. In Cox multiple regression analysis, lymphovascular space invasion (p=0.03, HR: 1.7) and tumor size (p=0.01, HR: 1.67 for 5 cm increment) were associated with an increased risk of LRF. CONCLUSION: Five-year LRF rates are ≥19% in essentially all patient subsets.

Development of an IgG4-based predictor of endemic pemphigus foliaceus (fogo selvagem).

Fogo selvagem (FS) is mediated by pathogenic, predominantly IgG4, anti-desmoglein 1 (Dsg1) autoantibodies and is endemic in Limao Verde, Brazil. IgG and IgG subclass autoantibodies were tested in a sample of 214 FS patients and 261 healthy controls by Dsg1 ELISA. For model selection, the sample was randomly divided into training (50%), validation (25%), and test (25%) sets. Using the training and validation sets, IgG4 was chosen as the best predictor of FS, with index values above 6.43 classified as FS. Using the test set, IgG4 has sensitivity of 92% (95% confidence interval (95% CI): 82-95%), specificity of 97% (95% CI: 89-100%), and area under the curve of 0.97 (95% CI: 0.94-1.00). The IgG4 positive predictive value (PPV) in Limao Verde (3% FS prevalence) was 49%. The sensitivity, specificity, and PPV of IgG anti-Dsg1 were 87, 91, and 23%, respectively. The IgG4-based classifier was validated by testing 11 FS patients before and after clinical disease and 60 Japanese pemphigus foliaceus patients. It classified 21 of 96 normal individuals from a Limao Verde cohort as having FS serology. On the basis of its PPV, half of the 21 individuals may currently have preclinical FS and could develop clinical disease in the future. Identifying individuals during preclinical FS will enhance our ability to identify the etiological agent(s) triggering FS.

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.