Prognostic factors for progression-free and overall survival in advanced biliary tract cancer.

BACKGROUND: Biliary tract cancer is an uncommon cancer with a poor outcome. We assembled data from the National Cancer Research Institute (UK) ABC-02 study and 10 international studies to determine prognostic outcome characteristics for patients with advanced disease. METHODS: Multivariable analyses of the final dataset from the ABC-02 study were carried out. All variables were simultaneously included in a Cox proportional hazards model, and backward elimination was used to produce the final model (using a significance level of 10%), in which the selected variables were associated independently with outcome. This score was validated externally by receiver operating curve (ROC) analysis using the independent international dataset. RESULTS: A total of 410 patients were included from the ABC-02 study and 753 from the international dataset. An overall survival (OS) and progression-free survival (PFS) Cox model was derived from the ABC-02 study. White blood cells, haemoglobin, disease status, bilirubin, neutrophils, gender, and performance status were considered prognostic for survival (all with P < 0.10). Patients with metastatic disease {hazard ratio (HR) 1.56 [95% confidence interval (CI) 1.20-2.02]} and Eastern Cooperative Oncology Group performance status (ECOG PS) 2 had worse survival [HR 2.24 (95% CI 1.53-3.28)]. In a dataset restricted to patients who received cisplatin and gemcitabine with ECOG PS 0 and 1, only haemoglobin, disease status, bilirubin, and neutrophils were associated with PFS and OS. ROC analysis suggested the models generated from the ABC-02 study had a limited prognostic value [6-month PFS: area under the curve (AUC) 62% (95% CI 57-68); 1-year OS: AUC 64% (95% CI 58-69)]. CONCLUSION: These data propose a set of prognostic criteria for outcome in advanced biliary tract cancer derived from the ABC-02 study that are validated in an international dataset. Although these findings establish the benchmark for the prognostic evaluation of patients with ABC and confirm the value of longheld clinical observations, the ability of the model to correctly predict prognosis is limited and needs to be improved through identification of additional clinical and molecular markers.

Ostotapahtuman ennustemallin kehittäminen ajoneuvomarkkinoinnin tueksi

Perinteisesti ajoneuvojen markkinointikampanjoissa kohderyhmät muodostetaan yksinkertaisella kriteeristöllä koskien henkilön tai hänen ajoneuvonsa ominaisuuksia. Ennustavan analytiikan avulla voidaan tuottaa kohderyhmänmuodostukseen teknisesti kompleksisia mutta kuitenkin helppokäyttöisiä menetelmiä. Tässä työssä on sovellettu luokittelu- ja regressiomenetelmiä uuden auton ostajien joukkoon. Tämän työn menetelmiksi on rajattu tukivektorikone sekä Coxin regressiomalli. Coxin regression avulla on tutkittu elinaika-analyysien soveltuvuutta ostotapahtuman tapahtumahetken mallintamiseen. Luokittelu tukivektorikonetta käyttäen onnistuu tehtävässään noin 72% tapauksissa. Tukivektoriregressiolla mallinnetun hankintahetken virheen keskiarvo on noin neljä kuukautta. Työn tulosten perusteella myös elinaika-analyysin käyttö ostotapahtuman tapahtumahetken mallintamiseen on menetelmänä käyttökelpoinen.

Correlation of mixed lymphocyte culture with chronic graft-versus-host disease following allogeneic stem cell transplantation

The purpose of the present study was to evaluate the mixed lymphocyte culture as a predictive assay of acute and chronic graft-versus-host disease (GVHD). We studied 153 patients who received a first bone marrow transplantation from human leukocyte antigen-identical siblings. Acute GVHD was observed in 26 of 128 (20.3%) patients evaluated and chronic GVHD occurred in 60 of 114 (52.6%). One-way mixed lymphocyte culture (MLC) assays were performed by the standard method. MLC results are reported as the relative response (RR) from donor against patient cells. The responses ranged from -47.0 to 40.7%, with a median of 0.5%. The Kaplan-Meier probability of developing GVHD was determined for patients with positive and negative MLC. There was no significant difference in incidence of acute GVHD between the groups studied. However, the incidence of chronic GVHD was higher in recipients with RR >4.5% than in those with RR <=4.5%. The Cox Proportional Hazards model was used to examine the effect of MLC levels on incidence of chronic GVHD, while adjusting for the potential confounding effect of others suspected or observed risk factors. The relative risk of chronic GVHD was 2.5 for patients with positive MLC (RR >4.5%), 2.9 for those who received peripheral blood progenitor cells as a graft, and 2.2 for patients who developed previous acute GVHD. MLC was not useful for predicting acute GVHD, but MLC with RR >4.5% associated with other risk factors could predict the development of chronic GVHD, being of help for the prevention and/or treatment of this late complication.

New statistical methods to assess the effect of time-dependent exposures in case-control studies

Contexte. Les études cas-témoins sont très fréquemment utilisées par les épidémiologistes pour évaluer l’impact de certaines expositions sur une maladie particulière. Ces expositions peuvent être représentées par plusieurs variables dépendant du temps, et de nouvelles méthodes sont nécessaires pour estimer de manière précise leurs effets. En effet, la régression logistique qui est la méthode conventionnelle pour analyser les données cas-témoins ne tient pas directement compte des changements de valeurs des covariables au cours du temps. Par opposition, les méthodes d’analyse des données de survie telles que le modèle de Cox à risques instantanés proportionnels peuvent directement incorporer des covariables dépendant du temps représentant les histoires individuelles d’exposition. Cependant, cela nécessite de manipuler les ensembles de sujets à risque avec précaution à cause du sur-échantillonnage des cas, en comparaison avec les témoins, dans les études cas-témoins. Comme montré dans une étude de simulation précédente, la définition optimale des ensembles de sujets à risque pour l’analyse des données cas-témoins reste encore à être élucidée, et à être étudiée dans le cas des variables dépendant du temps. Objectif: L’objectif général est de proposer et d’étudier de nouvelles versions du modèle de Cox pour estimer l’impact d’expositions variant dans le temps dans les études cas-témoins, et de les appliquer à des données réelles cas-témoins sur le cancer du poumon et le tabac. Méthodes. J’ai identifié de nouvelles définitions d’ensemble de sujets à risque, potentiellement optimales (le Weighted Cox model and le Simple weighted Cox model), dans lesquelles différentes pondérations ont été affectées aux cas et aux témoins, afin de refléter les proportions de cas et de non cas dans la population source. Les propriétés des estimateurs des effets d’exposition ont été étudiées par simulation. Différents aspects d’exposition ont été générés (intensité, durée, valeur cumulée d’exposition). Les données cas-témoins générées ont été ensuite analysées avec différentes versions du modèle de Cox, incluant les définitions anciennes et nouvelles des ensembles de sujets à risque, ainsi qu’avec la régression logistique conventionnelle, à des fins de comparaison. Les différents modèles de régression ont ensuite été appliqués sur des données réelles cas-témoins sur le cancer du poumon. Les estimations des effets de différentes variables de tabac, obtenues avec les différentes méthodes, ont été comparées entre elles, et comparées aux résultats des simulations. Résultats. Les résultats des simulations montrent que les estimations des nouveaux modèles de Cox pondérés proposés, surtout celles du Weighted Cox model, sont bien moins biaisées que les estimations des modèles de Cox existants qui incluent ou excluent simplement les futurs cas de chaque ensemble de sujets à risque. De plus, les estimations du Weighted Cox model étaient légèrement, mais systématiquement, moins biaisées que celles de la régression logistique. L’application aux données réelles montre de plus grandes différences entre les estimations de la régression logistique et des modèles de Cox pondérés, pour quelques variables de tabac dépendant du temps. Conclusions. Les résultats suggèrent que le nouveau modèle de Cox pondéré propose pourrait être une alternative intéressante au modèle de régression logistique, pour estimer les effets d’expositions dépendant du temps dans les études cas-témoins

A Study on the Kerridge's Inaccuracy Measure and Related Conceptss

Department of Statistics, Cochin University of Sciene ans Technology

Regression models for bivariate survival data

Multivariate lifetime data arise in various forms including recurrent event data when individuals are followed to observe the sequence of occurrences of a certain type of event; correlated lifetime when an individual is followed for the occurrence of two or more types of events, or when distinct individuals have dependent event times. In most studies there are covariates such as treatments, group indicators, individual characteristics, or environmental conditions, whose relationship to lifetime is of interest. This leads to a consideration of regression models.The well known Cox proportional hazards model and its variations, using the marginal hazard functions employed for the analysis of multivariate survival data in literature are not sufficient to explain the complete dependence structure of pair of lifetimes on the covariate vector. Motivated by this, in Chapter 2, we introduced a bivariate proportional hazards model using vector hazard function of Johnson and Kotz (1975), in which the covariates under study have different effect on two components of the vector hazard function. The proposed model is useful in real life situations to study the dependence structure of pair of lifetimes on the covariate vector . The well known partial likelihood approach is used for the estimation of parameter vectors. We then introduced a bivariate proportional hazards model for gap times of recurrent events in Chapter 3. The model incorporates both marginal and joint dependence of the distribution of gap times on the covariate vector . In many fields of application, mean residual life function is considered superior concept than the hazard function. Motivated by this, in Chapter 4, we considered a new semi-parametric model, bivariate proportional mean residual life time model, to assess the relationship between mean residual life and covariates for gap time of recurrent events. The counting process approach is used for the inference procedures of the gap time of recurrent events. In many survival studies, the distribution of lifetime may depend on the distribution of censoring time. In Chapter 5, we introduced a proportional hazards model for duration times and developed inference procedures under dependent (informative) censoring. In Chapter 6, we introduced a bivariate proportional hazards model for competing risks data under right censoring. The asymptotic properties of the estimators of the parameters of different models developed in previous chapters, were studied. The proposed models were applied to various real life situations.

Timing and the holding periods of institutional real estate

Literature on investors' holding periods for securities suggests that high transaction costs are associated with longer holding periods. Return volatility, by contrast, is associated with shorter holding periods. In real estate, high transaction costs and illiquidity imply longer holding periods. Research on depreciation and obsolescence suggests that there might be an optimal holding period. Sales rates and holding periods for U.K. institutional real estate are analyzed, using a proportional hazards model, over an 18-year period. The results show longer holding periods than those claimed by investors, with marked differences by type of property and over time. The results shed light on investor behavior.

Menopausal status: A possible predictive factor for recurrence in women with cancer of the uterine cervix without pelvic lymph node metastasis

Objectives: To evaluate risk factors for recurrence of carcinoma of the uterine cervix among women who had undergone radical hysterectomy without pelvic lymph node metastasis, while taking into consideration not only the classical histopathological factors but also sociodemographic, clinical and treatment-related factors. Study design: This was an exploratory analysis on 233 women with carcinoma of the uterine cervix (stages IB and IIA) who were treated by means of radical hysterectomy and pelvic lymphadenectomy, with free surgical margins and without lymph node metastases on conventional histopathological examination. Women with histologically normal lymph nodes but with micrometastases in the immunohistochemical analysis (AE1/AE3) were excluded. Disease-free survival for sociodemographic, clinical and histopathological variables was calculated using the Kaplan-Meier method. The Cox proportional hazards model was used to identify the independent risk factors for recurrence. Results: Twenty-seven recurrences were recorded (11.6%), of which 18 were pelvic, four were distant, four were pelvic + distant and one was of unknown location. The five-year disease-free survival rate among the study population was 88.4%. The independent risk factors for recurrence in the multivariate analysis were: postmenopausal status (HR 14.1; 95% CI: 3.7-53.6; P < 0.001), absence of or slight inflammatory reaction (HR 7.9; 95% CI: 1.7-36.5; P = 0.008) and invasion of the deepest third of the cervix (FIR 6.1; 95% CI: 1.3-29.1; P = 0.021). Postoperative radiotherapy was identified as a protective factor against recurrence (HR 0.02; 95% CI: 0.001-0.25; P = 0.003). Conclusion: Postmenopausal status is a possible independent risk factor for recurrence even when adjusted for classical prognostic factors (such as tumour size, depth of turnout invasion, capillary embolisation) and treatment-related factors (period of treatment and postoperative radiotherapy status). (C) 2009 Elsevier Ireland Ltd. All rights reserved.

Comparison of biological behavior between early-stage adenocarcinoma and squamous cell carcinoma of the uterine cervix

Objectives: (1) To compare the anatomopathological variables and recurrence rates in patients with early-stage adenocarcinoma (AC) and squamous cell carcinoma (SCC) of the uterine cervix; (2) to identify the independent risk factors for recurrence. Study design: This historical cohort study assessed 238 patients with carcinoma of the uterine cervix (113 and IIA), who underwent radical hysterectomy with pelvic lymph node dissection between 1980 and 1999. Comparison of category variables between the two histological types was carried out using the Pearson`s X-2 test or Fisher exact test. Disease-free survival rates for AC and SCC were calculated using the Kaplan-Meier method and the curves were compared using the log-rank test. The Cox proportional hazards model was used to identify the independent risk factors for recurrence. Results: There were 35 cases of AC (14.7%) and 203 of SCC (85.3%). AC presented lower histological grade than did SCC (grade 1: 68.6% versus 9.4%; p < 0.001), lower rate of lymphovascular space involvement (25.7% versus 53.7%; p = 0.002), lower rate of invasion into the middle or deep thirds of the uterine cervix (40.0% versus 80.8%; p < 0.001) and lower rate of lymph node metastasis (2.9% versus 16.3%; p = 0.036). Although the recurrence rate was lower for AC than for SCC (11.4% versus 15.8%), this difference was not statistically significant (p = 0.509). Multivariate analysis identified three independent risk factors for recurrence: presence of metastases in the pelvic lymph nodes, invasion of the deep third of the uterine cervix and absence of or slight inflammatory reaction in the cervix. When these variables were adjusted for the histological type and radiotherapy status, they remained in the model as independent risk factors. Conclusion: The AC group showed less aggressive histological behavior than did the SCC group, but no difference in the disease-free survival rates was noted. (C) 2006 Elsevier Ireland Ltd. All rights reserved.

Fatores de risco para morte em pacientes diabéticos e não diabéticos em tratamento hemodialítico

A mortalidade dos pacientes diabéticos, quando iniciam tratamento hemodialítico, ainda é muito elevada, significativamente maior do que a dos pacientes não diabéticos. As doenças cardíacas são a principal causa de morte nestes pacientes. O diabetes, por si só, está associado a uma alta prevalência de hipertensão, doença cardiovascular e insuficiência cardíaca, resultando em morbi-mortalidade significativas. Tradicionalmente, a mortalidade tem sido associada à cardiopatia isquêmica. A mortalidade cardiovascular, entretanto, não está relacionada apenas à isquemia, mas também à insuficiência cardíaca e à morte súbita. O objetivo deste estudo foi analisar o papel da doença cardiovascular como fator prognóstico para a morte de pacientes diabéticos e não diabéticos, que iniciam hemodiálise, levando em consideração outros fatores. Este foi um estudo prospectivo de uma coorte de 40 pacientes diabéticos e 28 não diabéticos, que iniciaram programa de hemodiálise, de agosto de 1996 a junho de 1999, em 5 hospitais de Porto Alegre, Brasil. O tempo total de acompanhamento foi de 4,25 anos. A avaliação inicial, realizada entre o 20 e o 30 mês de hemodiálise, incluiu: um questionário com características demográficas, história do diabetes e suas complicações, história de hipertensão e acidente vascular cerebral; o exame físico incluindo avaliação nutricional e exame oftalmológico; e avaliação laboratorial com medidas de parâmetros nutricionais, bioquímicos, hormonais, perfil lipídico, e controle metabólico do diabetes, além da avaliação da adequação da diálise. Para a avaliação cardiovascular foram utilizados: questionário Rose, ECG em repouso, cintilografia em repouso e sob dipiridamol, e ecocardiograma bi-dimensional e com Doppler. A mortalidade foi analisada ao final dos 51 meses, e as causas de morte, definidas pelos registros médicos, atestados de óbito ou informações do médico assistente ou familiar. Na análise estatística, foram empregados o teste t de Student, o qui-quadrado (χ2) ou teste exato de Fisher. Para a análise da sobrevida, o método de Kaplan-Meier foi utilizado, e, para identificar os principais fatores associados à mortalidade, construiu-se um modelo de regressão múltipla de Cox. O nÍvel de significância adotado foi de 5%. Ao final do estudo, os pacientes diabéticos tiveram um índice de mortalidade significativamente mais elevado do que os pacientes sem diabetes (47,5% vs. 7,1%; P=0,0013, log rank test). Na análise de Cox, o padrão pseudonormal ou restritivo de disfunção diastólica esteve associado a um risco de 3,2 (IC 95%:1,2-8,8; P=0,02), e a presença de diabetes, a um risco de 4,7 (IC 95%:1,03-21,4; P=0,04) para a morte. Concluiu-se que a disfunção diastólica do ventrículo esquerdo foi o principal preditor de mortalidade nesta coorte de pacientes que estão iniciando tratamento hemodialítico.

Avaliação genética da eficiência reprodutiva em vacas pardo-suíças por meio da análise de sobrevivência

Among the traits of economic importance to dairy cattle livestock those related to sexual precocity and longevity of the herd are essential to the success of the activity, because the stayability time of a cow in a herd is determined by their productive and reproductive lives. In Brazil, there are few studies about the reproductive efficiency of Swiss-Brown cows and no study was found using the methodology of survival analysis applied to this breed. Thus, in the first chapter of this study, the age at first calving from Swiss-Brown heifers was analyzed as the time until the event by the nonparametric method of Kaplan-Meier and the gamma shared frailty model, under the survival analysis methodology. Survival and hazard rate curves associated with this event were estimated and identified the influence of covariates on such time. The mean and median times at the first calving were 987.77 and 1,003 days, respectively, and significant covariates by the Log-Rank test, through Kaplan-Meier analysis, were birth season, calving year, sire (cow s father) and calving season. In the analysis by frailty model, the breeding values and the frailties of the sires (fathers) for the calving were predicted modeling the risk function of each cow as a function of the birth season as fixed covariate and sire as random covariate. The frailty followed the gamma distribution. Sires with high and positive breeding values possess high frailties, what means shorter survival time of their daughters to the event, i.e., reduction in the age at first calving of them. The second chapter aimed to evaluate the longevity of dairy cows using the nonparametric Kaplan-Meier and the Cox and Weibull proportional hazards models. It were simulated 10,000 records of the longevity trait from Brown-Swiss cows involving their respective times until the occurrence of five consecutive calvings (event), considered here as typical of a long-lived cow. The covariates considered in the database were age at first calving, herd and sire (cow s father). All covariates had influence on the longevity of cows by Log-Rank and Wilcoxon tests. The mean and median times to the occurrence of the event were 2,436.285 and 2,437 days, respectively. Sires that have higher breeding values also have a greater risk of that their daughters reach the five consecutive calvings until 84 months

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

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

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.

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.

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.