Destructive weighted Poisson cure rate models

In this paper, we develop a flexible cure rate survival model by assuming the number of competing causes of the event of interest to follow a compound weighted Poisson distribution. This model is more flexible in terms of dispersion than the promotion time cure model. Moreover, it gives an interesting and realistic interpretation of the biological mechanism of the occurrence of event of interest as it includes a destructive process of the initial risk factors in a competitive scenario. In other words, what is recorded is only from the undamaged portion of the original number of risk factors.

COM-Poisson cure rate survival models and an application to a cutaneous melanoma data

In this paper, we develop a flexible cure rate survival model by assuming the number of competing causes of the event of interest to follow the Conway-Maxwell Poisson distribution. This model includes as special cases some of the well-known cure rate models discussed in the literature. Next, we discuss the maximum likelihood estimation of the parameters of this cure rate survival model. Finally, we illustrate the usefulness of this model by applying it to a real cutaneous melanoma data. (C) 2009 Elsevier B.V. All rights reserved.

A general hazard model for lifetime data in the presence of cure rate

Historically, the cure rate model has been used for modeling time-to-event data within which a significant proportion of patients are assumed to be cured of illnesses, including breast cancer, non-Hodgkin lymphoma, leukemia, prostate cancer, melanoma, and head and neck cancer. Perhaps the most popular type of cure rate model is the mixture model introduced by Berkson and Gage [1]. In this model, it is assumed that a certain proportion of the patients are cured, in the sense that they do not present the event of interest during a long period of time and can found to be immune to the cause of failure under study. In this paper, we propose a general hazard model which accommodates comprehensive families of cure rate models as particular cases, including the model proposed by Berkson and Gage. The maximum-likelihood-estimation procedure is discussed. A simulation study analyzes the coverage probabilities of the asymptotic confidence intervals for the parameters. A real data set on children exposed to HIV by vertical transmission illustrates the methodology.

A flexible model for survival data with a cure rate: a Bayesian approach

In this paper we deal with a Bayesian analysis for right-censored survival data suitable for populations with a cure rate. We consider a cure rate model based on the negative binomial distribution, encompassing as a special case the promotion time cure model. Bayesian analysis is based on Markov chain Monte Carlo (MCMC) methods. We also present some discussion on model selection and an illustration with a real dataset.

A hands-on approach for fitting long-term survival models under the GAMLSS framework

In many data sets from clinical studies there are patients insusceptible to the occurrence of the event of interest. Survival models which ignore this fact are generally inadequate. The main goal of this paper is to describe an application of the generalized additive models for location, scale, and shape (GAMLSS) framework to the fitting of long-term survival models. in this work the number of competing causes of the event of interest follows the negative binomial distribution. In this way, some well known models found in the literature are characterized as particular cases of our proposal. The model is conveniently parameterized in terms of the cured fraction, which is then linked to covariates. We explore the use of the gamlss package in R as a powerful tool for inference in long-term survival models. The procedure is illustrated with a numerical example. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

On the unification of long-term survival models

In this paper we extend the long-term survival model proposed by Chen et al. [Chen, M.-H., Ibrahim, J.G., Sinha, D., 1999. A new Bayesian model for survival data with a surviving fraction. journal of the American Statistical Association 94, 909-919] via the generating function of a real sequence introduced by Feller [Feller, W., 1968. An Introduction to Probability Theory and its Applications, third ed., vol. 1, Wiley, New York]. A direct consequence of this new formulation is the unification of the long-term survival models proposed by Berkson and Gage [Berkson, J., Gage, R.P., 1952. Survival cure for cancer patients following treatment. journal of the American Statistical Association 47, 501-515] and Chen et al. (see citation above). Also, we show that the long-term survival function formulated in this paper satisfies the proportional hazards property if, and only if, the number of competing causes related to the occurrence of an event of interest follows a Poisson distribution. Furthermore, a more flexible model than the one proposed by Yin and Ibrahim [Yin, G., Ibrahim, J.G., 2005. Cure rate models: A unified approach. The Canadian journal of Statistics 33, 559-570] is introduced and, motivated by Feller`s results, a very useful competing index is defined. (c) 2008 Elsevier B.V. All rights reserved.

A Bayesian Long-term Survival Model Parametrized in the Cured Fraction

The main goal of this paper is to investigate a cure rate model that comprehends some well-known proposals found in the literature. In our work the number of competing causes of the event of interest follows the negative binomial distribution. The model is conveniently reparametrized through the cured fraction, which is then linked to covariates by means of the logistic link. We explore the use of Markov chain Monte Carlo methods to develop a Bayesian analysis in the proposed model. The procedure is illustrated with a numerical example.

Generalized log-gamma regression models with cure fraction

In this paper, the generalized log-gamma regression model is modified to allow the possibility that long-term survivors may be present in the data. This modification leads to a generalized log-gamma regression model with a cure rate, encompassing, as special cases, the log-exponential, log-Weibull and log-normal regression models with a cure rate typically used to model such data. The models attempt to simultaneously estimate the effects of explanatory variables on the timing acceleration/deceleration of a given event and the surviving fraction, that is, the proportion of the population for which the event never occurs. The normal curvatures of local influence are derived under some usual perturbation schemes and two martingale-type residuals are proposed to assess departures from the generalized log-gamma error assumption as well as to detect outlying observations. Finally, a data set from the medical area is analyzed.

The generalized log-gamma mixture model with covariates: local influence and residual analysis

In a sample of censored survival times, the presence of an immune proportion of individuals who are not subject to death, failure or relapse, may be indicated by a relatively high number of individuals with large censored survival times. In this paper the generalized log-gamma model is modified for the possibility that long-term survivors may be present in the data. The model attempts to separately estimate the effects of covariates on the surviving fraction, that is, the proportion of the population for which the event never occurs. The logistic function is used for the regression model of the surviving fraction. Inference for the model parameters is considered via maximum likelihood. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. Finally, a data set from the medical area is analyzed under the log-gamma generalized mixture model. A residual analysis is performed in order to select an appropriate model.

Improved cure of bacterial vaginosis with single dose of tinidazole (2 g), Lactobacillus rhamnosus GR-1, and Lactobacillus reuteri RC-14: a randomized, double-blind, placebo-controlled trial

Bacterial vaginosis (BV) is the most prevalent vaginal infection worldwide and is characterized by depletion of the indigenous lactobacilli. Antimicrobial therapy is often ineffective. We hypothesized that probiotic Lactobacillus rhamnosus GR-1 and Lactobacillus reuteri RC-14 might provide an adjunct to antimicrobial treatment and improve cure rates. Sixty-four Brazilian women diagnosed with BV were randomly assigned to receive a single dose of tinidazole (2 g) supplemented with either 2 placebo capsules or 2 capsules containing L. rhamnosus GR-1 and L. reuteri RC-14 every morning for the following 4 weeks. At the end of treatment (day 28), the probiotic group had a significantly higher cure rate of BV (87.5%) than the placebo group (50.0%) (p = 0.001). In addition, according to the Gram-stain Nugent score, more women were assessed with ""normal`` vaginal microbiota in the probiotic group (75.0% vs. 34.4% in the placebo group; p = 0.011). This study shows that probiotic lactobacilli can provide benefits to women being treated with antibiotics for an infectious condition.

A unified view on lifetime distributions arising from selection mechanisms

In this paper, we formulate a flexible density function from the selection mechanism viewpoint (see, for example, Bayarri and DeGroot (1992) and Arellano-Valle et al. (2006)) which possesses nice biological and physical interpretations. The new density function contains as special cases many models that have been proposed recently in the literature. In constructing this model, we assume that the number of competing causes of the event of interest has a general discrete distribution characterized by its probability generating function. This function has an important role in the selection procedure as well as in computing the conditional personal cure rate. Finally, we illustrate how various models can be deduced as special cases of the proposed model. (C) 2011 Elsevier B.V. All rights reserved.

T Helper 1-Inducing Adjuvant Protects against Experimental Paracoccidioidomycosis

Immunostimulatory therapy is a promising approach to improving the treatment of systemic fungal infections such as paracoccidioidomycosis (PCM), whose drug therapy is usually prolonged and associated with toxic side effects and relapses. The current study was undertaken to determine if the injection of a T helper (Th) 1-stimulating adjuvant in P. brasiliensis infected mice could have a beneficial effect on the course of experimental PCM. For this purpose, mice were infected and treated with complete Freund's adjuvant (CFA), a well-established Th1 experimental inductor, or incomplete Freund's adjuvant (IFA - control group) on day 20 postinfection. Four weeks after treatment, the CFA-treated mice presented a mild infection in the lungs characterized by absence of epithelioid cell granulomas and yeast cells, whereas the control mice presented multiple sites of focal epithelioid granulomas with lymphomonocytic halos circumscribing a high number of viable and nonviable yeast cells. In addition, CFA administration induced a 2.4 log reduction (>99%) in the fungal burden when compared to the control group, and led to an improvement of immune response, reversing the immunosuppression observed in the control group. The immunotherapy with Th1-inducing adjuvant, approved to be used in humans, might be a valuable tool in the treatment of PCM and potentially useful to improve the clinical cure rate in humans.

Improved treatment of vulvovaginal candidiasis with fluconazole plus probiotic Lactobacillus rhamnosus GR-1 and Lactobacillus reuteri RC-14

To determine the ability of probiotic lactobacilli to improve the treatment of vulvovaginal candidiasis (VVC) using a randomized, double-blind and placebo-controlled trial. Fifty-five women diagnosed with VVC by vaginal discharge positive for Candida spp. (according to culture method) associated with at least one of the symptoms (itching and burning vaginal feeling, dyspareunia and dysuria), were treated with single dose of fluconazole (150 mg) supplemented every morning for the following 4 weeks with two placebo or two probiotic capsules (containing Lactobacillus rhamnosus GR-1 and Lactobacillus reuteri RC-14). At 4 weeks, the probiotic treated group showed significantly less vaginal discharge associated with any of the above mentioned symptoms (10.3%vs 34.6%; P = 0.03) and lower presence of yeast detected by culture (10.3%vs 38.5%; P = 0.014). This study has shown that probiotic lactobacilli can increase the effectiveness of an anti-fungal pharmaceutical agent in curing disease. This novel finding of probiotic lactobacilli augmenting the cure rate of yeast vaginitis, not only offers an alternative approach to a highly prevalent condition that adversely affects the quality of life of women around the world, but also raises the question of how this combination works.

Mucosal leishmaniasis: description of case management approaches and analysis of risk factors for treatment failure in a cohort of 140 patients in Brazil

Background Mucosal leishmaniasis is caused mainly by Leishmania braziliensis and it occurs months or years after cutaneous lesions. This progressive disease destroys cartilages and osseous structures from face, pharynx and larynx. Objective and methods The aim of this study was to analyse the significance of clinical and epidemiological findings, diagnosis and treatment with the outcome and recurrence of mucosal leishmaniasis through binary logistic regression model from 140 patients with mucosal leishmaniasis from a Brazilian centre. Results The median age of patients was 57.5 and systemic arterial hypertension was the most prevalent secondary disease found in patients with mucosal leishmaniasis (43%). Diabetes, chronic nephropathy and viral hepatitis, allergy and coagulopathy were found in less than 10% of patients. Human immunodeficiency virus (HIV) infection was found in 7 of 140 patients (5%). Rhinorrhea (47%) and epistaxis (75%) were the most common symptoms. N-methyl-glucamine showed a cure rate of 91% and recurrence of 22%. Pentamidine showed a similar rate of cure (91%) and recurrence (25%). Fifteen patients received itraconazole with a cure rate of 73% and recurrence of 18%. Amphotericin B was the drug used in 30 patients with 82% of response with a recurrence rate of 7%. The binary logistic regression analysis demonstrated that systemic arterial hypertension and HIV infection were associated with failure of the treatment (P < 0.05). Conclusion The current first-line mucosal leishmaniasis therapy shows an adequate cure but later recurrence. HIV infection and systemic arterial hypertension should be investigated before start the treatment of mucosal leishmaniasis. Conflicts of interest The authors are not part of any associations or commercial relationships that might represent conflicts of interest in the writing of this study (e.g. pharmaceutical stock ownership, consultancy, advisory board membership, relevant patents, or research funding).

Efficacy and tolerance of metronidazole and miconazole nitrate in treatment of vaginitis

Objective: To evaluate the efficacy and tolerability of a vaginal pessary containing 750 mg of metronidazole and 200 mg of miconazole nitrate used daily for 7 days in the treatment of vaginitis. Methods: Ninety-two women with vaginitis participated in this phase 3 study using one vaginal pessary daily for 7 days. Gynecological and microbiological evaluations were carried out prior to and following treatment. Results: Reductions occurred in symptoms and signs of vaginitis. Clinical cure rate was 87.7%, while the cure rates according to microscopy and Candida albicans culture were 81.8% and 73.9%, respectively. The cure rate for bacterial vaginosis was 75% and culture of Gardnerella vaginalis turned negative in 63.6% of cases following treatment. The medication was well tolerated. Conclusion: Use of a combination of 750 mg of metronidazole and 200 mg of miconazole in a single daily application was found to be effective in the treatment of the most common causes of vaginitis. (c) 2008 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.