Upper bound estimators of the population size based on ordinal models for capture-recapture experiments.

Capture-recapture studies have attracted a lot of attention over the past few decades, especially in applied disciplines where a direct estimate for the size of a population of interest is not available. Epidemiology, ecology, public health, and biodiversity are just a few examples. The estimation of the number of unseen units has been a challenge for theoretical statisticians, and considerable progress has been made in providing lower bound estimators for the population size. In fact, it is well known that consistent estimators for this cannot be provided in the very general case. Considering a case where capture-recapture studies are summarized by a frequency of frequencies distribution, we derive a simple upper bound of the population size based on the cumulative distribution function. We introduce two estimators of this bound, without any specific parametric assumption on the distribution of the observed frequency counts. The behavior of the proposed estimators is investigated using several benchmark datasets and a large-scale simulation experiment based on the scheme discussed by Pledger.

Finite Mixtures of Hidden Markov Models for Longitudinal Responses Subject to Drop out.

Drop out is a typical issue in longitudinal studies. When the missingness is non-ignorable, inference based on the observed data only may be biased. This paper is motivated by the Leiden 85+ study, a longitudinal study conducted to analyze the dynamics of cognitive functioning in the elderly. We account for dependence between longitudinal responses from the same subject using time-varying random effects associated with a heterogeneous hidden Markov chain. As several participants in the study drop out prematurely, we introduce a further random effect model to describe the missing data mechanism. The potential dependence between the random effects in the two equations (and, therefore, between the two processes) is introduced through a joint distribution specified via a latent structure approach. The application of the proposal to data from the Leiden 85+ study shows its effectiveness in modeling heterogeneous longitudinal patterns, possibly influenced by the missing data process. Results from a sensitivity analysis show the robustness of the estimates with respect to misspecification of the missing data mechanism. A simulation study provides evidence for the reliability of the inferential conclusions drawn from the analysis of the Leiden 85+ data.

A bidimensional finite mixture model for longitudinal data subject to dropout.

In longitudinal studies, subjects may be lost to follow up and, thus, present incomplete response sequences. When the mechanism underlying the dropout is nonignorable, we need to account for dependence between the longitudinal and the dropout process. We propose to model such a dependence through discrete latent effects, which are outcome-specific and account for heterogeneity in the univariate profiles. Dependence between profiles is introduced by using a probability matrix to describe the corresponding joint distribution. In this way, we separately model dependence within each outcome and dependence between outcomes. The major feature of this proposal, when compared with standard finite mixture models, is that it allows the nonignorable dropout model to properly nest its ignorable counterpart. We also discuss the use of an index of (local) sensitivity to nonignorability to investigate the effects that assumptions about the dropout process may have on model parameter estimates. The proposal is illustrated via the analysis of data from a longitudinal study on the dynamics of cognitive functioning in the elderly.

Normal human adipose tissue functions and differentiation in patients with biallelic LPIN1 inactivating mutations.

Lipin-1 is a Mg2+-dependent phosphatidic acid phosphatase (PAP) that in mice is necessary for normal glycerolipid biosynthesis, controlling adipocyte metabolism, and adipogenic differentiation. Mice carrying inactivating mutations in the Lpin1 gene display the characteristic features of human familial lipodystrophy. Very little is known about the roles of lipin-1 in human adipocyte physiology. Apparently, fat distribution and weight is normal in humans carrying LPIN1 inactivating mutations, but a detailed analysis of adipose tissue appearance and functions in these patients has not been available so far. In this study, we performed a systematic histopathological, biochemical, and gene expression analysis of adipose tissue biopsies from human patients harboring LPIN1 biallelic inactivating mutations and affected by recurrent episodes of severe rhabdomyolysis. We also explored the adipogenic differentiation potential of human mesenchymal cell populations derived from lipin-1 defective patients. White adipose tissue from human LPIN1 mutant patients displayed a dramatic decrease in lipin-1 protein levels and PAP activity, with a concomitant moderate reduction of adipocyte size. Nevertheless, the adipose tissue develops without obvious histological signs of lipodystrophy and with normal qualitative composition of storage lipids. The increased expression of key adipogenic determinants such as SREBP1, PPARG, and PGC1A shows that specific compensatory phenomena can be activated in vivo in human adipocytes with deficiency of functional lipin-1.

Second cancer incidence in primary mediastinal B-cell lymphoma treated with methotrexate with leucovorin rescue, doxorubicin, cyclophosphamide, vincristine, prednisone, and bleomycin regimen with or without rituximab and mediastinal radiotherapy: Results from a monoinstitutional cohort analysis of long-term survivors.

Our aim is to assess the incidence of second cancer in long-time surviving primary mediastinal B-cell lymphoma (PMBCL) patients treated with combined radiochemoimmunotherapy (standard methotrexate with leucovorin rescue, doxorubicin, cyclophosphamide, vincristine, prednisone, and bleomycin with rituximab and mediastinal radiation therapy at a dose of 30 to 36 Gy). For this purpose, 92 points were evaluated. After a median overall survival of 137 months (range 76-212), we recorded second cancer in 3 of 80 long-surviving patients (3.75%) with cumulative incidence of 3.47% at 15 years and 11% at 17 years, with a 17-year second cancer-free survival of 82%. We observed 2 papillary thyroid cancers with a standardized incidence ratio (SIR) of 7.97 and an absolute excess risk (AER) of 17. 84 and 1 acute myeloid leukemia (AML) with an SIR of 66.53 and an AER of 10.05. No breast cancer occurred. Although we should take into account the limits of the proposed statistical analysis, combined modality treatment was related to a significant SIR and AER for thyroid cancer and acute myeloid leukemia.

Growth curves of "normal" serum total IgE levels throughout childhood: A quantile analysis in a birth cohort.

BACKGROUND: Previous studies of serum total IgE (t-IgE) were not able to discriminate well-enough atopic from non-atopic subjects, that is, with or without serum-specific IgE antibodies to allergens. OBJECTIVES: To model growth curves of the total IgE levels in children without atopic sensitization (hereafter defined as "normal" t-IgE levels) and to test their usefulness in predicting atopic sensitization. METHODS: The German Multicentre Allergy Study (MAS), a birth cohort with 1314 recruited newborns, began in 1990 and examined the participants until age 20 years. Total and specific IgE (t-IgE, s-IgE) were analyzed with a fluorescent enzyme immunoassay ImmunoCAP (TFS, Sweden) at ages 1, 2, 3, 5, 6, 7, 10, 13, and 20 years. Participants were classified as "never atopic" if all their available serum samples had negative response (cutoff: <0.35 kUA /L) for s-IgE to the nine common foodborne and airborne allergenic extracts (milk, egg, soy, wheat, house dust mite, cat, dog, birch, and grass) tested in the MAS birth cohort. By contrast, participants were defined as atopic if they had, for at least at one available serum sample, s-IgE≥0.35 kUA /L to at least one allergenic extract tested. The evolution of t-IgE levels in the "never atopic" children was described by growth curves, estimated by exploiting a quantile regression model. A "reference" percentile, based on the t-IgE value measured at age 5 years, was assigned to each child with no IgE sensitization at that age. Upward deviations from the own "reference" quantile of t-IgE in atopic and "never atopic" children were calculated and a ROC analysis was used to identify the best cutoff point for predicting atopic sensitization. RESULTS: Overall, 1113 of 1314 children were included in this analysis. Of these, 469 were "never atopic" and 644 atopic. Quantile trajectories of t-IgE levels in "never atopic" subjects were stable from 5 years of age, increased to a plateau at age 10-13 years, and decreased slightly afterward. The onset of atopic s-IgE responses was characterized by an upward deviation of serum t-IgE levels from their "reference" trajectory. T-IgE quantiles predicted the onset of atopy with high efficiency (AUC>80%). ROC analysis showed that deviations from the t-IgE level "reference" quantile above 0.32, 0.41, 0.42, 0.30, and 0.58 kU/L (log-units) at 6, 7, 10, 13, and 20 years of age, respectively, predicted an atopic sensitization. CONCLUSION: The growth curves of "normal" serum t-IgE concentrations were estimated in "never atopic" children; for each individual who was non-atopic at 5 years of age a "reference" quantile was identified that represented the individual's "normal" level of t-IgE production. Upward deviations of observed t-IgE levels from the own "reference" quantile, from 6 to 20 years of age, predicted at each year the occurrence of atopic sensitization. CLINICAL IMPLICATIONS: The trajectory of t-IgE levels can be elaborated since age 5 years in non-atopic children. A child whose t-IgE levels are consistently higher than those predicted by his/her growth curve may have developed atopic sensitization.

A flexible ratio regression approach for zero-truncated capture-recapture counts.

Capture-recapture methods are used to estimate the size of a population of interest which is only partially observed. In such studies, each member of the population carries a count of the number of times it has been identified during the observational period. In real-life applications, only positive counts are recorded, and we get a truncated at zero-observed distribution. We need to use the truncated count distribution to estimate the number of unobserved units. We consider ratios of neighboring count probabilities, estimated by ratios of observed frequencies, regardless of whether we have a zero-truncated or an untruncated distribution. Rocchetti et al. (2011) have shown that, for densities in the Katz family, these ratios can be modeled by a regression approach, and Rocchetti et al. (2014) have specialized the approach to the beta-binomial distribution. Once the regression model has been estimated, the unobserved frequency of zero counts can be simply derived. The guiding principle is that it is often easier to find an appropriate regression model than a proper model for the count distribution. However, a full analysis of the connection between the regression model and the associated count distribution has been missing. In this manuscript, we fill the gap and show that the regression model approach leads, under general conditions, to a valid count distribution; we also consider a wider class of regression models, based on fractional polynomials. The proposed approach is illustrated by analyzing various empirical applications, and by means of a simulation study.

Finite mixture clustering of human tissues with different levels of IGF-1 splice variants mRNA transcripts.

BACKGROUND: This study addresses a recurrent biological problem, that is to define a formal clustering structure for a set of tissues on the basis of the relative abundance of multiple alternatively spliced isoforms mRNAs generated by the same gene. To this aim, we have used a model-based clustering approach, based on a finite mixture of multivariate Gaussian densities. However, given we had more technical replicates from the same tissue for each quantitative measurement, we also employed a finite mixture of linear mixed models, with tissue-specific random effects. RESULTS: A panel of human tissues was analysed through quantitative real-time PCR methods, to quantify the relative amount of mRNA encoding different IGF-1 alternative splicing variants. After an appropriate, preliminary, equalization of the quantitative data, we provided an estimate of the distribution of the observed concentrations for the different IGF-1 mRNA splice variants in the cohort of tissues by employing suitable kernel density estimators. We observed that the analysed IGF-1 mRNA splice variants were characterized by multimodal distributions, which could be interpreted as describing the presence of several sub-population, i.e. potential tissue clusters. In this context, a formal clustering approach based on a finite mixture model (FMM) with Gaussian components is proposed. Due to the presence of potential dependence between the technical replicates (originated by repeated quantitative measurements of the same mRNA splice isoform in the same tissue) we have also employed the finite mixture of linear mixed models (FMLMM), which allowed to take into account this kind of within-tissue dependence. CONCLUSIONS: The FMM and the FMLMM provided a convenient yet formal setting for a model-based clustering of the human tissues in sub-populations, characterized by homogeneous values of concentrations of the mRNAs for one or multiple IGF-1 alternative splicing isoforms. The proposed approaches can be applied to any cohort of tissues expressing several alternatively spliced mRNAs generated by the same gene, and can overcome the limitations of clustering methods based on simple comparisons between splice isoform expression levels.

Maternal thrombophilia and adverse pregnancy outcome: a case-control study.

OBJECTIVE: To assess the risk of adverse pregnancy outcomes in patients with acquired and/or congenital thrombophilia factors. PATIENTS AND METHODS: A cohort of 130 women with a history of pregnancy loss and no successful gestation were investigated for the presence of congenital and acquired thrombophilia factors, and then compared with a control group of 130 healthy women who had had at least one successful gestation and no pregnancy loss, and were screened for congenital and acquired thrombophilia factors. RESULTS: Acquired and congenital thrombophilia factors were found in 30 (23%) patients and in 14 (10.8%) controls (p < 0.015). The presence of ≥1 congenital thrombophilia factor was associated with pregnancy loss with an odds ratio of 2.46 (p = 0.040). Moreover, women who had had >1 early fetal loss had a 2.85-fold risk of being carriers of congenital thrombophilia factors, compared to the controls. CONCLUSION: Our study showed the increased risk of miscarriage in patients with congenital thrombophilia factors and >1 early fetal loss.

Reference charts for fetal corpus callosum length: a prospective cross-sectional study of 2950 fetuses.

OBJECTIVES: The purpose of this study was to establish reference charts for fetal corpus callosum length in a convenience sample. METHODS: A prospective cross-sectional study was conducted at the Artemisia Fetal-Maternal Medical Center between December 2008 and January 2012. Among 16,975 fetal biometric measurements between 19 weeks and 37 weeks 6 days' gestation, 3438 measurements of the corpus callosum (20.3%) were available. After excluding 488 measurements (14.2%), a total of 2950 fetuses (85.8%) were considered and analyzed only once. Parametric and nonparametric quantile regression models were used for the statistical analysis. To evaluate the robustness of the proposed reference charts with respect to various distributional assumptions on the sonographic measurements at hand, we compared the gestational age (GA)-specific reference curves produced by the statistical methods used. RESULTS: The mean corpus callosum length was 26.18 mm (SD, 4.5 mm; 95% confidence interval, 26.01-26.34 mm). The linear regression equation expressing the length of the corpus callosum as a function of GA was length (mm) = -11.17 + 1.62 × GA. The correlation between the dimension and gestation was expressed by the coefficient r = 0.83. Normal mean lengths according the parametric and nonparametric methods were defined for each week of gestation. CONCLUSIONS: This work provides new quantile-based reference charts for corpus callosum length measurements that may be useful for diagnosis of congenital corpus callosum anomalies in fetal life.

Evaluation of Statistical Treatment of Left-Censored Contamination Data: Example Involving Deoxynivalenol Occurrence in Pasta and Pasta Substitute Products.

The handling of data on food contamination frequently represents a challenge because these are often left-censored, being composed of both positive and non-detected values. The latter observations are not quantified and provide only the information that they are below a laboratory-specific threshold value. Besides deterministic approaches, which simplify the treatment through the substitution of non-detected values with fixed threshold or null values, a growing interest has been shown in the application of stochastic approaches to the treatment of unquantified values. In this study, a multiple imputation procedure was applied in order to analyze contamination data on deoxynivalenol, a mycotoxin that may be present in pasta and pasta substitute products. An application of the proposed technique to censored deoxynivalenol occurrence data is presented. The results were compared to those attained using deterministic techniques (substitution methods). In this context, the stochastic approach seemed to provide a more accurate, unbiased and realistic solution to the problem of left-censored occurrence data. The complete sample of values could then be used to estimate the exposure of the general population to deoxynivalenol based on consumption data.

A three component latent class model for robust semiparametric gene discovery.

We propose a robust model for discovering differentially expressed genes which directly incorporates biological significance, i.e., effect dimension. Using the so-called c-fold rule, we transform the expressions into a nominal observed random variable with three categories: below a fixed lower threshold, above a fixed upper threshold or within the two thresholds. Gene expression data is then transformed into a nominal variable with three levels possibly originated by three different distributions corresponding to under expressed, not differential, and over expressed genes. This leads to a statistical model for a 3-component mixture of trinomial distributions with suitable constraints on the parameter space. In order to obtain the MLE estimates, we show how to implement a constrained EM algorithm with a latent label for the corresponding component of each gene. Different strategies for a statistically significant gene discovery are discussed and compared. We illustrate the method on a little simulation study and a real dataset on multiple sclerosis.

Quality of life and sexual functioning among endometrial cancer patients treated with one week adjuvant high-dose-rate vaginal brachytherapy schedule.

Purpose: To examine quality of life (QOL) and sexual functioning in a series of patients with intermediate- and high-intermediate risk endometrial cancer, treated with exclusive adjuvant one week high-dose-rate (HDR) vaginal brachytherapy (VBT) schedule. Material and methods: Between July 2008 and October 2013, 55 patients with diagnosis of endometrial cancer were treated with adjuvant exclusive VBT. All patients had undergone surgical treatment with a laparotomy approach before VBT. Post-operative VBT was administered 6-8 weeks after surgery. Treatment was delivered to vaginal vault using Nucletron HDR unit with iridium-192 source at a dose of 21 Gy/3 fractions of 7 Gy each, three times a week, every other day, prescribed at 0.5 cm depth of vaginal wall, and 3 cm in length from the apex. QOL was assessed using European Organization for Research and Treatment of Cancer (EORTC) quality of life questionnaire Core-30 (QLQ-C30), and EORTC cancer-specific quality of life questionnaire (QLQ-CX24). Results: Median follow-up time was 92 months (range, 42-162 months). Questionnaires were carried out respectively at 1, 3, 6, 12, 24, 36, 48, and 60 months after the end of BT. Response rate to questionnaires was 100% (n = 55). Nineteen patients (35%) answered all the questions of surveys, while 36 patients (65%) completed the surveys, except for questions on sex activity, vaginal function, and sex enjoyment. Longitudinal analysis during 5-year follow-up period showed a statistically significant trend towards worsening of fatigue, constipation, and diarrhea. Overall physical functioning and role functioning was not impaired after VBT. Over the time, sex enjoyment improved, except for elderly patients. For emotional functioning, sex worry and social functioning presented no significant time-related effect. Conclusions: One week brachytherapy schedule to vaginal cuff is generally well-tolerated. QOL does not worsen after applying vaginal brachytherapy.