Tests of proportional hazards and proportional odds models for grouped survival data

In this paper, we derive score test statistics to discriminate between proportional hazards and proportional odds models for grouped survival data. These models are embedded within a power family transformation in order to obtain the score tests. In simple cases, some small-sample results are obtained for the score statistics using Monte Carlo simulations. Score statistics have distributions well approximated by the chi-squared distribution. Real examples illustrate the proposed tests.

Choosing between Cox proportional hazards and logistic models for interval-censored data via bootstrap

This work develops a new methodology in order to discriminate models for interval-censored data based on bootstrap residual simulation by observing the deviance difference from one model in relation to another, according to Hinde (1992). Generally, this sort of data can generate a large number of tied observations and, in this case, survival time can be regarded as discrete. Therefore, the Cox proportional hazards model for grouped data (Prentice & Gloeckler, 1978) and the logistic model (Lawless, 1982) can befitted by means of generalized linear models. Whitehead (1989) considered censoring to be an indicative variable with a binomial distribution and fitted the Cox proportional hazards model using complementary log-log as a link function. In addition, a logistic model can be fitted using logit as a link function. The proposed methodology arises as an alternative to the score tests developed by Colosimo et al. (2000), where such models can be obtained for discrete binary data as particular cases from the Aranda-Ordaz distribution asymmetric family. These tests are thus developed with a basis on link functions to generate such a fit. The example that motivates this study was the dataset from an experiment carried out on a flax cultivar planted on four substrata susceptible to the pathogen Fusarium oxysoprum. The response variable, which is the time until blighting, was observed in intervals during 52 days. The results were compared with the model fit and the AIC values.

Anemia at one year is an independent risk factor of graft survival

Background Post-transplant anemia is multifactorial and highly prevalent. Some studies have associated anemia with mortality and graft failure. The purpose of this study was to assess whether the presence of anemia at 1 year is an independent risk factor of mortality and graft survival. Methods All patients transplanted at a single center who survived at least 1 year after transplantation and showed no graft loss (n = 214) were included. Demographic and clinical data were collected at baseline and at 1 year. Patients were divided into two groups (anemic and nonanemic) based on the presence of anemia (hemoglobin<130 g/l in men and 120 g/l in women). Results Baseline characteristics such as age, gender, type of donor, CKD etiology, rejection, andmismatches were similar in both groups. Creatinine clearance was similar in both anemic and nonanemic groups (69.32 ± 29.8 × 75.69 ± 30.5 ml/mim; P = 0.17). A Kaplan- Meier plot showed significantly poorer death-censored graft survival in the anemic group, P = 0.003. Multivariate analysis revealed that anemic patients had a hazard ratio for the graft loss of 3.85 (95% CI: 1.49-9.96; P = 0.005). Conclusions In this study, anemia at 1 year was independently associated with death-censored graft survival and anemic patients were 3.8-fold more likely to lose the graft. © 2010 Springer Science+Business Media, B.V.

Pathological and behavioral risk factors for higher serum c-reactive protein concentrations in free-living adults - A Brazilian community-based study

Low-grade chronic systemic inflammation is often associated with chronic non-communicable diseases, and its most frequently used marker, the C-reactive protein (CRP), has become an identifier of such diseases as well as an independent predictor for cardiovascular disorders and mortality. CRP is produced in response to pro-inflammatory signaling and to individual and behavioral factors, leading to pathological states. The aim of this study was to rank the predicting factors of high CRP concentrations in free-living adults from a community-based sample. We evaluated 522 adults (40-84 years old; 381 women) for anthropometric characteristics, dietary intake, clinical and physical tests, and blood analysis. Subjects were assigned to groups, according to CRP concentrations, as normal CRP (G1;<3.0 mg/L; n = 269), high CRP (G2; 3.0-6.0 mg/L; n = 139), and very high CRP (G3; >6.0 mg/dL; n = 116). Statistical comparison between groups used one-way ANOVA or Kruskal-Wallis tests, and prediction of altered values in increasing CRP was evaluated by proportional hazard models (odds ratio). CRP distribution was influenced by gender, body mass index, body and abdominal fatness, blood leukocytes, and neutrophil counts. The higher CRP group was discriminated by the above variables in addition to lower VO2max, serum metabolic syndrome components (triglycerides, glucose, and HDL cholesterol), higher insulin, homeostasis assessment of insulin resistance, uric acid, gamma-GT, and homocysteine. After adjustments, only fatness, blood leukocytes, and hyperglycemia remained as independent predictors for increased serum CRP concentrations. Intervention procedures to treat low-grade chronic inflammation in overweight women would mainly focus on restoring muscle mass and functions in addition to an antioxidant-rich diet. © 2012 Springer Science+Business Media, LLC.

Absence of RKIP expression is an independent prognostic biomarker for gastric cancer patients

Gastric cancer is a leading cause of cancer-related mortality, and the presence of lymph node metastasis an important prognostic factor. Downregulation of RKIP has been associated with tumor progression and metastasis in several types of neoplasms, being currently categorized as a metastasis suppressor gene. Our aim was to determine the expression levels of RKIP in gastric tissues and to evaluate its impact in the clinical outcome of gastric carcinoma patients. RKIP expression levels were studied by immunohistochemistry in a series of gastric tissues. Overall, we analysed 222 non-neoplastic gastric tissues, 152 primary tumors and 42 lymph node metastasis samples. We observed that RKIP was highly expressed in ∼83% of non-neoplastic tissues (including normal tissue and metaplasia), was lost in ∼56% of primary tumors and in ∼90% of lymph node metastasis samples. Loss of RKIP expression was significantly associated with several markers of poor clinical outcome, including the presence of lymph node metastasis. Furthermore, the absence of RKIP protein constitutes an independent prognostic marker for these patients. In conclusion, RKIP expression is significantly lost during gastric carcinoma progression being almost absent in lymph node metastasis samples. Of note, we showed that the absence of RKIP expression is associated with poor outcome features of gastric cancer patients, this being also an independent prognostic marker.

Characterization of the variable cow's age at last calving as a measurement of longevity by using the Kaplan-Meier estimator and the Cox model

In most studies on beef cattle longevity, only the cows reaching a given number of calvings by a specific age are considered in the analyses. With the aim of evaluating all cows with productive life in herds, taking into consideration the different forms of management on each farm, it was proposed to measure cow longevity from age at last calving (ALC), that is, the most recent calving registered in the files. The objective was to characterize this trait in order to study the longevity of Nellore cattle, using the Kaplan-Meier estimators and the Cox model. The covariables and class effects considered in the models were age at first calving (AFC), year and season of birth of the cow and farm. The variable studied (ALC) was classified as presenting complete information (uncensored = 1) or incomplete information (censored = 0), using the criterion of the difference between the date of each cow's last calving and the date of the latest calving at each farm. If this difference was >36 months, the cow was considered to have failed. If not, this cow was censored, thus indicating that future calving remained possible for this cow. The records of 11 791 animals from 22 farms within the Nellore Breed Genetic Improvement Program ('Nellore Brazil') were used. In the estimation process using the Kaplan-Meier model, the variable of AFC was classified into three age groups. In individual analyses, the log-rank test and the Wilcoxon test in the Kaplan-Meier model showed that all covariables and class effects had significant effects (P < 0.05) on ALC. In the analysis considering all covariables and class effects, using the Wald test in the Cox model, only the season of birth of the cow was not significant for ALC (P > 0.05). This analysis indicated that each month added to AFC diminished the risk of the cow's failure in the herd by 2%. Nonetheless, this does not imply that animals with younger AFC had less profitability. Cows with greater numbers of calvings were more precocious than those with fewer calvings. Copyright © The Animal Consortium 2012.

Likelihood approximations and discrete models for tied survival data

Ties among event times are often recorded in survival studies. For example, in a two week laboratory study where event times are measured in days, ties are very likely to occur. The proportional hazards model might be used in this setting using an approximated partial likelihood function. This approximation works well when the number of ties is small. on the other hand, discrete regression models are suggested when the data are heavily tied. However, in many situations it is not clear which approach should be used in practice. In this work, empirical guidelines based on Monte Carlo simulations are provided. These recommendations are based on a measure of the amount of tied data present and the mean square error. An example illustrates the proposed criterion.

Shorter CAG repeat length in the AR gene is associated with poor outcome in head and neck cancer

Objective: Alterations in the size of the [CAG](n) repeats of the AR gene have been described in several types tumors. The purpose of this study was to evaluate if there is an association between the AR [CAG](n) repeat alleles and the relative risk for head and neck cancer and to analyse microsatellite instability (MSI) and loss of heterozygosity (LOH) in these tumors.Design: Matched samples of blood and head and neck tumors were evaluated using two methodologies, silver-stained gels to perform the analyses of MSI and LOH, and automated analysis to confirm these results and for genotyping of the AR [CAG](n), repeat length. Sixty-nine individuals without cancer were used as a control group for both procedures. The Log-rank test was used to compare overall survival and disease-free survival curves. The Cox proportional hazards regression models were performed to determine the [CAG], repeats as an independent prognostic factor.Results: Patients with alleles <= 20 in the male group showed a correlation with lower disease-free survival (P = 0.0325) and with recurrence or metastasis (RR 2.52, CI 95%). in the female group, the allele 2 (longer allele) showed a significant lower mean of [CAG](n), repeat when compared to the control group. Microsatellite instability was detected in nine cases in both procedures. In six out of these nine cases, we observed a reduction of the AR [CAG](n) repeat length. LOH was detected in one out of 17 women informative for oral cancer in both procedures.Conclusion: These results suggest that short [CAG](n) repeat length (: 20) polymorphism is associated with poor prognosis in a subset of male patients with head and neck cancer and that AR gene microsatellite instability is uncommon in these tumors. (C) 2007 Elsevier Ltd. All rights reserved.

Modeling grouped survival data with time-dependent covariates

In this article, proportional hazards and logistic models for grouped survival data were extended to incorporate time-dependent covariates. The extension was motivated by a forestry experiment designed to compare five different water stresses in Eucalyptus grandis seedlings. The response was the seedling lifetime. The data set was grouped since there were just three occasions in which the seedlings was visited by the researcher. In each of these occasions also the shoot height was measured and therefore it is a time-dependent covariate. Both extended models were used in this example, and the results were very similar.

A Generalized Log-Normal Model for Grouped Survival Data

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Additive genetic relationship of longevity with fertility and production traits in Nellore cattle based on bivariate models

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Preditores de recidiva hemorrágica ou óbito na hemorragia digestiva alta por úlcera péptica ou lesão aguda da mucosa gastroduodenal

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Potentially modifiable predictors of mortality in patients treated with long-term oxygen therapy

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Predictors of first-year survival in patients with advanced COPD treated using long-term oxygen therapy

Little evidence-based guidance is available to aid clinicians in determining short-term prognoses in very severe COPD patients. Therefore, the present study was designed to provide a prospective assessment (1) of the mortality rates and (2) whether the baseline measurements may be determinants of 1-year mortality in hypoxemic COPD patients receiving long-term oxygen therapy (LTOT).Seventy-eight clinically stable patients with advanced COPD treated using LTOT were enrolled in a prospective cohort study. Outcome variable: first-year mortality. Baseline measurements: categorical variables: age (<60 or >= 60 years); gender; body mass index (<20 or >= 20 kg/m(2)); fat-free mass (FFM) index (<16 [men] and <15kg/m(2) [women]; baseline dyspnea index (BDI) (<= 3 or >3); and corticosteroid use. Continuous variables: smoking history; lung function; FFM; fat mass; hemoglobin; hematocrit; arterial blood gases; forearm muscle strength; St. George's Respiratory Questionnaire (SGRQ); and comorbidity score. By the end of 1-year of follow-up, 12 patients (15.4%) had died. Kaplan-Meier curves showed that BDI <= 3 was the only variable associated with higher mortality. Cox proportional hazards analysis revealed that tower PaO2 and SPO2, higher PaCO2 and SGRQ scores were associated with reduced survival. In the multivariate analysis, BDI remained predictive of mortality (hazard ratio [HR], 0.50; 95% confidence interval [CI], 0.31-0.81), as did PaO2 (HR, 0.49; 95% CI, 0.26-0.95). These data suggest that readily available parameters as dyspnea intensity and hypoxemia severity may be useful in predicting first-year survival rates in advanced COPD patients receiving LTOT (C) 2007 Elsevier Ltd. All rights reserved.

Desigualdade da sobrevivência de trabalhadores de Botucatu, São Paulo, Brasil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)