Safety and efficacy of transitioning from selexipag to oral treprostinil in pulmonary arterial hypertension: Findings from the ADAPT registry.

PURPOSE: Oral treprostinil and selexipag are drugs targeting the prostacyclin pathway and are approved for treatment of pulmonary arterial hypertension (PAH). In the setting of unsatisfactory clinical response or tolerability issues while on selexipag, there is little data on clinical benefit, safety, or strategies on transitioning to oral treprostinil. Using prospective data from the ADAPT registry, we aimed to evaluate clinical outcomes, safety, and transition strategies in ten patients with PAH transitioning from selexipag to oral treprostinil. METHODS: ADAPT was a prospective, real-world, multicenter, United States-based registry of patients with PAH newly started on oral treprostinil, with a cohort of patients (n = 10) transitioning from selexipag to oral treprostinil. PAH variables of interest were collected from standard-of-care clinic visits. Clinical improvement was defined by modified REPLACE criterion, and risk was assessed by REVEAL Lite 2 from baseline to last follow-up. Real world transition strategies were recorded. Healthcare utilization or worsening PAH was evaluated within 30 days of transitions. RESULTS: Seven patients transitioned due to worsening PAH or lack of efficacy on selexipag, and three patients transitioned due to tolerability issues. Based on the modified REPLACE criterion, five patients demonstrated clinical improvement after transition from selexipag to oral treprostinil. Using REVEAL Lite 2 to assess risk, three patients improved and five patients maintained risk category from baseline to last follow-up. All transitions occurred in an outpatient setting either as abrupt stop/start or cross-titration, without parenteral treprostinil bridging. CONCLUSION: Transition from selexipag to oral treprostinil was safe, performed without parenteral prostacyclin bridging, and resulted in clinical and categorical risk improvements in some patients.

Missing at random: a stochastic process perspective.

We offer a natural and extensible measure-theoretic treatment of missingness at random. Within the standard missing-data framework, we give a novel characterization of the observed data as a stopping-set sigma algebra. We demonstrate that the usual missingness-at-random conditions are equivalent to requiring particular stochastic processes to be adapted to a set-indexed filtration. These measurability conditions ensure the usual factorization of likelihood ratios. We illustrate how the theory can be extended easily to incorporate explanatory variables, to describe longitudinal data in continuous time, and to admit more general coarsening of observations.

A novel placental tissue biologic, PTP-001, inhibits inflammatory and catabolic responses in vitro and prevents pain and cartilage degeneration in a rat model of osteoarthritis.

OBJECTIVE: Characterization of a novel human placental tissue-derived biologic, PTP-001, which is in development as a candidate therapeutic for the treatment of osteoarthritis symptoms and pathophysiology. METHODS: Human placental tissues from healthy donors were prepared as a particulate formulation, PTP-001. PTP-001 extracts were assayed for the presence of disease-relevant biofactors which could have beneficial effects in treating osteoarthritis. PTP-001 eluates were tested in human chondrocyte cultures to determine effects on the production of a key collagen-degrading matrix metalloproteinase, MMP-13. PTP-001 eluates were also assessed for anti-inflammatory potential in human monocyte/macrophage cultures, as well as for growth-stimulating anabolic effects in human synoviocytes. The in vivo effects of PTP-001 on joint pain and histopathology were evaluated in a rat model of osteoarthritis induced surgically by destabilization of the medial meniscus. RESULTS: PTP-001 was found to contain an array of beneficial growth factors, cytokines and anti-inflammatory molecules. PTP-001 eluates dose-dependently inhibited the production of chondrocyte MMP-13, and the secretion of proinflammatory cytokines from monocyte/macrophage cultures. PTP-001 eluates also promoted proliferation of cultured synovial cells. In a rat osteoarthritis model, PTP-001 significantly reduced pain responses throughout 6 weeks post-dosing. The magnitude and duration of pain reduction following a single intraarticular treatment with PTP-001 was comparable to that observed for animals treated with a corticosteroid (active control). For rats dosed twice with PTP-001, significant reductions in cartilage histopathology scores were observed. CONCLUSIONS: PTP-001 represents a promising biologic treatment for osteoarthritis, with a multi-modal mechanism of action that may contribute to symptom management and disease modification.

Calibration of a high spectral resolution lidar using a Michelson interferometer, with data examples from ORACLES.

The NASA Langley airborne second-generation High Spectral Resolution Lidar (HSRL-2) uses a density-tuned field-widened Michelson interferometer to implement the HSRL technique at 355 nm. The Michelson interferometer optically separates the received backscattered light between two channels, one of which is dominated by molecular backscattering, while the other contains most of the light backscattered by particles. This interferometer achieves high and stable contrast ratio, defined as the ratio of particulate backscatter signal received by the two channels. We show that a high and stable contrast ratio is critical for precise and accurate backscatter and extinction retrievals. Here, we present retrieval equations that take into account the incomplete separation of particulate and molecular backscatter in the measurement channels. We also show how the accuracy of the contrast ratio assessment propagates to error in the optical properties. For both backscattering and extinction, larger errors are produced by underestimates of the contrast ratio (compared to overestimates), more extreme aerosol loading, and-most critically-smaller true contrast ratios. We show example results from HSRL-2 aboard the NASA ER-2 aircraft from the 2016 ORACLES field campaign in the southeast Atlantic, off the coast of Africa, during the biomass burning season. We include a case study where smoke aerosol in two adjacent altitude layers showed opposite differences in extinction- and backscatter-related Ångström exponents and a reversal of the lidar ratio spectral dependence, signatures which are shown to be consistent with a relatively modest difference in smoke particle size.

A two-step method for variable selection in the analysis of a case-cohort study.

Background: Accurate detection and estimation of true exposure-outcome associations is important in aetiological analysis; when there are multiple potential exposure variables of interest, methods for detecting the subset of variables most likely to have true associations with the outcome of interest are required. Case-cohort studies often collect data on a large number of variables which have not been measured in the entire cohort (e.g. panels of biomarkers). There is a lack of guidance on methods for variable selection in case-cohort studies. Methods: We describe and explore the application of three variable selection methods to data from a case-cohort study. These are: (i) selecting variables based on their level of significance in univariable (i.e. one-at-a-time) Prentice-weighted Cox regression models; (ii) stepwise selection applied to Prentice-weighted Cox regression; and (iii) a two-step method which applies a Bayesian variable selection algorithm to obtain posterior probabilities of selection for each variable using multivariable logistic regression followed by effect estimation using Prentice-weighted Cox regression. Results: Across nine different simulation scenarios, the two-step method demonstrated higher sensitivity and lower false discovery rate than the one-at-a-time and stepwise methods. In an application of the methods to data from the EPIC-InterAct case-cohort study, the two-step method identified an additional two fatty acids as being associated with incident type 2 diabetes, compared with the one-at-a-time and stepwise methods. Conclusions: The two-step method enables more powerful and accurate detection of exposure-outcome associations in case-cohort studies. An R package is available to enable researchers to apply this method.

An evaluation of penalised survival methods for developing prognostic models with rare events.

Prognostic models for survival outcomes are often developed by fitting standard survival regression models, such as the Cox proportional hazards model, to representative datasets. However, these models can be unreliable if the datasets contain few events, which may be the case if either the disease or the event of interest is rare. Specific problems include predictions that are too extreme, and poor discrimination between low-risk and high-risk patients. The objective of this paper is to evaluate three existing penalised methods that have been proposed to improve predictive accuracy. In particular, ridge, lasso and the garotte, which use penalised maximum likelihood to shrink coefficient estimates and in some cases omit predictors entirely, are assessed using simulated data derived from two clinical datasets. The predictions obtained using these methods are compared with those from Cox models fitted using standard maximum likelihood. The simulation results suggest that Cox models fitted using maximum likelihood can perform poorly when there are few events, and that significant improvements are possible by taking a penalised modelling approach. The ridge method generally performed the best, although lasso is recommended if variable selection is required.

Familial effects on the clinical course of multiple sclerosis.

BACKGROUND: Familial factors influence susceptibility to multiple sclerosis (MS) but it is unknown whether there are additional effects on the natural history of the disease. METHOD: We evaluated 1,083 families with > or =2 first-degree relatives with MS for concordance of age at onset, clinical course, and disease severity and investigated transmission patterns of these clinical features in affected parent-child pairs. RESULTS: There is concordance for age at onset for all families (correlation coefficient 0.14; p < 0.001), as well as for affected siblings (correlation coefficient 0.15; p < 0.001), and affected parent-child pairs (correlation coefficient 0.12; p = 0.03) when each is evaluated separately. Concordance for year of onset is present among affected siblings (correlation coefficient 0.18; p < 0.001) but not the parent-child group (correlation coefficient 0.08; p = 0.15). The clinical course is similar between siblings (kappa 0.12; p < 0.001) but not affected parents and their children (kappa -0.04; p = 0.09). This influence on the natural history is present in all clinical subgroups of relapsing-remitting, and primary and secondary progressive MS, reflecting a familial effect on episodic and progressive phases of the disease. There is no concordance for disease severity within any of the considered family groups (correlation coefficients: all families analyzed together, 0.02, p = 0.53; affected sibling group, 0.02, p = 0.61; affected parent-child group, 0.02, p = 0.69). Furthermore, there are no apparent transmission patterns of any of the investigated clinical features in affected parent-child pairs and no evidence for anticipation or effects of genetic loading. CONCLUSION: Familial factors do not significantly affect eventual disease severity. However, they increase the probability of a progressive clinical course, either from onset or after a phase of relapsing remitting disease. The familial effect is more likely to reflect genetic than environmental conditions. The results are relevant for counseling patients and have implications for the design of studies seeking to identify factors that influence the natural history of the disease.

Formation of iodoacetic acids during cooking: interaction of iodized table salt with chlorinated drinking water.

Iodoacetic and chloroiodoacetic acids were formed when municipal chlorinated tap water was allowed to react with iodized (with potassium iodide) table salt or with potassium iodide itself. Iodoacetic acid was recently shown to be a potent cytotoxic and genotoxic agent. For analysis, samples were extracted with t-amyl methyl ether and converted to the corresponding methyl esters using methanol and sulfuric acid. The concentration of iodoacetic acid was determined by gas chromatography-mass spectrometry (GC-MS) using an authentic standard. The identities of iodoacetic and chloroiodoacetic acids were further confirmed by gas chromatography-high-resolution mass spectrometry (GC-HRMS). Certain influences of sodium hypochlorite and humic acid as well as the concentration of potassium iodide on the yields of these acids were investigated. The concentration of iodoacetic acid in tap water samples boiled with 2 g l-1 of iodized table salt was found to be in the 1.5 microg l-1 range, whilst the concentration of chloroiodoacetic acid was estimated to be three to five times lower.

Semicarbazide in Canadian bakery products.

Levels of semicarbazide were determined by liquid chromatography-tandem mass spectrometry using isotope dilution ((13)C(15)N(2)-semicarbazide) methodology, and they were measured, after hydrolysis in 0.125 M hydrochloric acid and derivatization with 2-nitrobenzaldehyde, as a sum of free and bound semicarbazide. Levels of semicarbazide in 11 bakery products, which were sampled at three time intervals from the same source, varied from not detected (<1ng g(-1)) to 560 ng g(-1). In some instances, concentrations of semicarbazide varied between batches of the same product, at times more than tenfold, suggesting that the addition of azodicarbonamide to the same product is not standardized in many baking establishments.

Development and validation of a headspace method for determination of furan in food.

In the past furan had been found to form in foods during thermal processing. These findings and a recent classification of furan as a possible human carcinogen prompted us to develop a simple isotope dilution method for its determination in foods. We also investigated effects of furan volatility, sample matrix and partitioning of furan between water and fat constituents of sample on the analytical determination of furan. The method is based on headspace sampling of a 2 ml vial containing 1 g of sample. For analysis, samples were spiked with d(4)-furan, homogenized in a blender at 0 degree C, with water if required, and sub-sampled to vials containing sodium sulphate. After equilibration at 30 degrees C, 50 microl of headspace was injected into the split/splitless injection port of a GC/MS (EI, SIM). The method is linear in the 0.4-1000 ng/g range with a limit of detection of 0.1 ng/g.

Effect of genotyping error on type-I error rate of affected sib pair studies with genotyped parents.

OBJECTIVE: In affected sib pair studies without genotyped parents the effect of genotyping error is generally to reduce the type I error rate and power of tests for linkage. The effect of genotyping error when parents have been genotyped is unknown. We investigated the type I error rate of the single-point Mean test for studies in which genotypes of both parents are available. METHODS: Datasets were simulated assuming no linkage and one of five models for genotyping error. In each dataset, Mendelian-inconsistent families were either excluded or regenotyped, and then the Mean test applied. RESULTS: We found that genotyping errors lead to an inflated type I error rate when inconsistent families are excluded. Depending on the genotyping-error model assumed, regenotyping inconsistent families has one of several effects. It may produce the same type I error rate as if inconsistent families are excluded; it may reduce the type I error, but still leave an anti-conservative test; or it may give a conservative test. Departures of the type I error rate from its nominal level increase with both the genotyping error rate and sample size. CONCLUSION: We recommend that markers with high error rates either be excluded from the analysis or be regenotyped in all families.

Multiple Sclerosis Severity Score: using disability and disease duration to rate disease severity.

BACKGROUND: There is no consensus method for determining progression of disability in patients with multiple sclerosis (MS) when each patient has had only a single assessment in the course of the disease. METHODS: Using data from two large longitudinal databases, the authors tested whether cross-sectional disability assessments are representative of disease severity as a whole. An algorithm, the Multiple Sclerosis Severity Score (MSSS), which relates scores on the Expanded Disability Status Scale (EDSS) to the distribution of disability in patients with comparable disease durations, was devised and then applied to a collection of 9,892 patients from 11 countries to create the Global MSSS. In order to compare different methods of detecting such effects the authors simulated the effects of a genetic factor on disability. RESULTS: Cross-sectional EDSS measurements made after the first year were representative of overall disease severity. The MSSS was more powerful than the other methods the authors tested for detecting different rates of disease progression. CONCLUSION: The Multiple Sclerosis Severity Score (MSSS) is a powerful method for comparing disease progression using single assessment data. The Global MSSS can be used as a reference table for future disability comparisons. While useful for comparing groups of patients, disease fluctuation precludes its use as a predictor of future disability in an individual.

Rapid simulation of P values for product methods and multiple-testing adjustment in association studies.

A major aim of association studies is the identification of polymorphisms (usually SNPs) associated with a trait. Tests of association may be based on individual SNPs or on sets of neighboring SNPs, by use of (for example) a product P value method or Hotelling's T test. Linkage disequilibrium, the nonindependence of SNPs in physical proximity, causes problems for all these tests. First, multiple-testing correction for individual-SNP tests or for multilocus tests either leads to conservative P values (if Bonferroni correction is used) or is computationally expensive (if permutation is used). Second, calculation of product P values usually requires permutation. Here, we present the direct simulation approach (DSA), a method that accurately approximates P values obtained by permutation but is much faster. It may be used whenever tests are based on score statistics--for example, with Armitage's trend test or its multivariate analogue. The DSA can be used with binary, continuous, or count traits and allows adjustment for covariates. We demonstrate the accuracy of the DSA on real and simulated data and illustrate how it might be used in the analysis of a whole-genome association study.

Bayesian trio models for association in the presence of genotyping errors.

Errors in genotyping can greatly affect family-based association studies. If a mendelian inconsistency is detected, the family is usually removed from the analysis. This reduces power, and may introduce bias. In addition, a large proportion of genotyping errors remain undetected, and these also reduce power. We present a Bayesian framework for performing association studies with SNP data on samples of trios consisting of parents with an affected offspring, while allowing for the presence of both detectable and undetectable genotyping errors. This framework also allows for the inclusion of missing genotypes. Associations between the SNP and disease were modelled in terms of the genotypic relative risks. The performances of the analysis methods were investigated under a variety of models for disease association and genotype error, looking at both power to detect association and precision of genotypic relative risk estimates. As expected, power to detect association decreased as genotyping error probability increased. Importantly, however, analyses allowing for genotyping error had similar power to standard analyses when applied to data without genotyping error. Furthermore, allowing for genotyping error yielded relative risk estimates that were approximately unbiased, together with 95% credible intervals giving approximately correct coverage. The methods were also applied to a real dataset: a sample of schizophrenia cases and their parents genotyped at SNPs in the dysbindin gene. The analysis methods presented here require no prior information on the genotyping error probabilities, and may be fitted in WinBUGS.

Gamma knife stereotactic radiosurgery for unilateral acoustic neuromas.

OBJECTIVE: To evaluate the clinical results achievable using current techniques of gamma knife stereotactic radiosurgery to treat sporadic unilateral acoustic neuromas. METHODS: A retrospective review of 234 consecutive patients treated for unilateral acoustic neuromas between 1996 and 1999, with a mean (SD) follow up of 35 (16) months. Tumour control was assessed with serial radiological imaging and by the need for surgical intervention. Hearing preservation was assessed using Gardner-Robertson grades. Details of complications including cranial neuropathies and non-specific vestibulo-cochlear symptoms are included. RESULTS: A tumour control rate in excess of 92% was achieved, with only 3% of patients undergoing surgery after radiosurgery. Results were less good for larger tumours, but control rates of 75% were achieved for 35-45 mm diameter lesions. Of patients with discernible hearing, Gardner-Robertson grades were unchanged in 75%. Facial nerve function was adversely affected in 4.5%, but fewer than 1% of patients had persistent weakness. Trigeminal symptoms improved in 3%, but developed in 5% of patients, being persistent in less than 1.5%. Transient non-specific vestibulo-cochlear symptoms were reported by 13% of patients. CONCLUSIONS: Tumour control rates, while difficult to define, are comparable after radiosurgery with those experienced after surgery. The complications and morbidity after radiosurgery are far less frequent than those encountered after surgery. This, combined with its minimally invasive nature, may make radiosurgery increasingly the treatment of choice for small and medium sized acoustic neuromas.

Osteopontin gene and clinical severity of multiple sclerosis.

Osteopontin transcription is increased in the central nervous system of patients with multiple sclerosis and rats with experimental allergic encephalomyelitis; where expression correlates with disease severity. We typed four single nucleotide polymorphisms located in exons 6 and 7 of the osteopontin gene in a large cohort of 1056 multiple sclerosis patients and 325 controls. We did not find significant allelic differences of the screened polymorphisms between the cases and controls and there was no allelic association with disease severity. Despite strong theoretical reasons to consider osteopontin as a potential candidate, the results of our study argue against the gene being a susceptibility locus for either the development or clinical severity of MS.

A Bayesian partition model for case-control studies on highly polymorphic candidate genes.

We present a new statistical model for the analysis of case-control or cohort studies examining a highly polymorphic candidate disease susceptibility gene. Many genotypes are possible for such a gene. Consequently, the average number of subjects having each genotype will be modest. If analyzed separately, the risks associated with most genotypes will be estimated imprecisely. Our Bayesian partition model clusters genotypes according to risk, only allowing partitions that satisfy a particular assumption about the joint effect of the two alleles making up a genotype. This assumption is genetically plausible, imposes structure on the set of genotype risks, and still leaves a highly flexible model. By Bayesian model averaging over partitions, the model becomes, in effect, a semiparametric model for genotype risk. It allows borrowing of strength, i.e., estimates of risk for one genotype are informed by the risk estimates of all the genotypes. We present the results of fitting the model to two datasets, one simulated and one genuine case-control study of the NAT1 gene and lung cancer, and compare it in a simulation study with a haplotype relative risk model. The partition model enables genotype risks to be estimated more accurately and the alleles to be ranked according to risk.

Proportional hazards model for interval-censored failure times and time-dependent covariates: application to hazard of HIV infection of injecting drug users in prison.

Interval-censored survival data are data in which the failure times are not known precisely, but are known to lie within an interval. Such data can be analysed using a proportional hazards model with piecewise-exponential baseline hazard, a model which can be fitted by an EM algorithm easily programmed in standard statistical software. In this paper we extend the model to allow for time-dependent covariates and left-truncation, and demonstrate its use by assessing the effect of imprisonment on hazard of HIV infection in a cohort of injecting drug users from Edinburgh. No conclusive effect of incarceration on hazard of HIV infection was found, but there was a suggestion that imprisonment might have been a significant relative risk factor for infection in the later period, when risk behaviour among drug users in the community was reduced.

Estimating the relative incidence of heroin use: application of a method for adjusting observed reports of first visits to specialized drug treatment agencies.

In this paper, the authors propose a method for estimating the incidence of heroin use by adjusting reported numbers of heroin users visiting drug treatment agencies for the time lag between onset of heroin use and first treatment request (lag distribution). The adjusted incidence is relative, since it represents the number of individuals beginning heroin use in each year whose cases will be reported within 8 years of starting use. Users with longer lag times or whose cases are never reported are excluded. Utilizing data from southeastern England (1991--1998), the authors analyzed the effects of covariates (sex, age group, ethnic group, route of consumption, and year of onset of drug use) on the lag distribution. Trends in the adjusted incidence of heroin use were very different for injectors and noninjectors: Incidence among injectors seemed to be stable, while in noninjectors it increased twofold between 1991 and 1996--1997. These results must be interpreted cautiously, especially in relation to the wider context of underlying trends in the population. Potential biases derive from underreporting and from changes in the proportion of heroin users in treatment. The lag correction method adds substantially to the value of routine treatment data, at least for heroin use, and is potentially the best method for obtaining estimates of incidence.