Residuals for log-Burr XII regression models in survival analysis

In this paper, we compare three residuals to assess departures from the error assumptions as well as to detect outlying observations in log-Burr XII regression models with censored observations. These residuals can also be used for the log-logistic regression model, which is a special case of the log-Burr XII regression model. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and the empirical distribution of each residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended to the modified martingale-type residual in log-Burr XII regression models with censored data.

Prognostic factors and survival analysis in a sample of oral squamous cell carcinoma patients

Objectives. The aims of this report were to describe the 5-year overall survival (OS) in a group of oral squamous cell carcinoma (OSCC) patients and to investigate the effects of age, gender, anatomic localization, tumor evolution time, smoking and alcohol intake, nodal status, tumoral recurrences, histologic classification, p53 and p63 immunoexpression, human papillomavirus DNA presence, and treatment on the prognostic outcome. Study design. Survival curves were generated using Kaplan-Meier method, and univariate and multivariate analyses were made using the log rank test and Cox regression, respectively. Results. The 5-year OS was 28.6%, and the univariate analysis showed significant results for p53 and p63 immunoexpression, age, and anatomic localization. The Cox regression demonstrated poor OS for tumors with p53 immunoexpression and for patients aged over 60 years. There were also significant differences in survival depending on the anatomic localizations. Conclusion. These results highlight the influence of p53 immunoexpression, age, and anatomic localization in OSCC evolution. (Oral Surg Oral Med Oral Pathol Oral Radiol Endod 2008; 106: 685-95)

Occult Axillary Lymph Node Metastases in Breast Cancer Do Matter: Results of 10-Year Survival Analysis

Axillary lymph node status is one of the most powerful prognostic factors for patients with breast cancer and is often critical in stratifying patients into adjuvant treatment regimens. In 203 apparently node-negative cases of breast cancer, a combination of immunohistochemical staining and step-sectioning identified occult metastases in 25% of cases. Ten-year follow-up information is available for these patients. Histologic features of the primary tumor and immunohistochemical staining for estrogen receptor, progesterone receptor, Her-2, and p53 were also evaluated. With multivariate analysis, both occult metastases and higher histologic grade of the primary tumor were independent predictors of disease-free survival. Histologic grade was the only significant independent predictor of overall survival. Estrogen receptor, progesterone receptor, Her-2, and p53 status did not predict the presence of metastases or survival when all tumor types were considered together. Metastases >0.5 mm significantly predicted a poorer disease-free survival when invasive ductal carcinomas were considered alone. Histologic grade was significantly associated with disease-free survival in the premenopausal and perimenopausal patients but not in the postmenopausal patients. The presence of occult metastases approached significance for overall survival in the premenopausal and perimenopausal patients but not in the postmenopausal patients.

Survival Analysis Employed in Predicting Corporate Failure: A Forecasting Model Proposal

In face of the current economic and financial environment, predicting corporate bankruptcy is arguably a phenomenon of increasing interest to investors, creditors, borrowing firms, and governments alike. Within the strand of literature focused on bankruptcy forecasting we can find diverse types of research employing a wide variety of techniques, but only a few researchers have used survival analysis for the examination of this issue. We propose a model for the prediction of corporate bankruptcy based on survival analysis, a technique which stands on its own merits. In this research, the hazard rate is the probability of ‘‘bankruptcy’’ as of time t, conditional upon having survived until time t. Many hazard models are applied in a context where the running of time naturally affects the hazard rate. The model employed in this paper uses the time of survival or the hazard risk as dependent variable, considering the unsuccessful companies as censured observations.

Survival analysis: a tool in the study of post-harvest diseases in peaches

Survival analysis is applied when the time until the occurrence of an event is of interest. Such data are routinely collected in plant diseases, although applications of the method are uncommon. The objective of this study was to use two studies on post-harvest diseases of peaches, considering two harvests together and the existence of random effect shared by fruits of a same tree, in order to describe the main techniques in survival analysis. The nonparametric Kaplan-Meier method, the log-rank test and the semi-parametric Cox's proportional hazards model were used to estimate the effect of cultivars and the number of days after full bloom on the survival to the brown rot symptom and the instantaneous risk of expressing it in two consecutive harvests. The joint analysis with baseline effect, varying between harvests, and the confirmation of the tree effect as a grouping factor with random effect were appropriate to interpret the phenomenon (disease) evaluated and can be important tools to replace or complement the conventional analysis, respecting the nature of the variable and the phenomenon.

Liver morphology with emphasis on bile ducts changes and survival analysis in mice submitted to multiple Schistosoma mansoni infections and chemotherapy

In an attempt to be as close as possible to the infected and treated patients of the endemic areas of schistosomiasis (S. mansoni) and in order to achieve a long period of follow-up, mice were repeatedly infected with a low number of cercariae. Survival data and histological variables such as schistosomal granuloma, portal changes, hepatocellular necrosis, hepatocellular regeneration, schistosomotic pigment, periductal fibrosis and chiefly bile ducts changes were analysed in the infected treated and non treated mice. Oxamniquine chemotherapy in repeatedly infected mice prolonged survival significantly when compared to non-treated animals (chi-square 9.24, p = 0.0024), thus confirming previous results with a similar experimental model but with a shorter term follow-up. Furthermore, mortality decreased rapidly after treatment suggesting an abrupt reduction in the severity of hepatic lesions. A morphological and immunohistochemical study of the liver was carried out. Portal fibrosis, with a pattern resembling human Symmers fibrosis was present at a late phase in the infected animals. Bile duct lesions were quite close to those described in human Mansonian schistosomiasis. Schistosomal antigen was observed in one isolated altered bile duct cell. The pathogenesis of the bile duct changes and its relation to the parasite infection and/or their antigens are discussed.

Applications of the bootstrap to survival analysis

En este trabajo se revisan algunas de las aplicaciones clásicas del bootstrap al análisis de la supervivencia. Se consideran en primer lugar el estimador bootstrap de la varianza y el estimador de la mediana corregido para el sesgo del estimador de Kaplan-Meier de la función de supervivencia. A continuación se consideran algunos aspectos mas recientes, tales como métodos para construir bandas de confianza para el estimador de la funcidn de supervivencia y contrastes aproximados para la comparación de funciones de supervivencia. En ambas situaciones el bootstrap resulta de gran utilidad para la aproximación de 10s valores críticos necesarios.

Factors favoring a degradation or an improvement in activities of daily living (ADL) performance among nursing home (NH) residents: A survival analysis.

Different factors influence ADL performance among nursing home (NH) residents in long term care. The aim was to investigate which factors were associated with a significant change of ADL performance in NH residents, and whether or not these factors were gender-specific. The design was a survival analysis. The 10,199 participants resided in ninety Swiss NHs. Their ADL performance had been assessed by the Resident Assessment Instrument Minimum Data Set (RAI-MDS) in the period from 1997 to 2007. Relevant change in ADL performance was defined as 2 levels of change on the ADL scale between two successive assessments. The occurrence of either an improvement or a degradation of the ADL status) was analyzed using the Cox proportional hazard model. The analysis included a total of 10,199 NH residents. Each resident received between 2 and 23 assessments. Poor balance, incontinence, impaired cognition, a low BMI, impaired vision, no daily contact with proxies, impaired hearing and the presence of depression were, by hierarchical order, significant risk factors for NH residents to experience a degradation of ADL performance. Residents, who were incontinent, cognitively impaired or had a high BMI were significantly less likely to improve their ADL abilities. Male residents with cancer were prone to see their ADL improve. The year of NH entry was significantly associated with either degradation or improvement of ADL performance. Measures aiming at improving balance and continence, promoting physical activity, providing appropriate nourishment and cognitive enhancement are important for ADL performance in NH residents.

Univariate Parametric Survival Analysis using GS-distributions

The GS-distribution is a family of distributions that provide an accurate representation of any unimodal univariate continuous distribution. In this contribution we explore the utility of this family as a general model in survival analysis. We show that the survival function based on the GS-distribution is able to provide a model for univariate survival data and that appropriate estimates can be obtained. We develop some hypotheses tests that can be used for checking the underlying survival model and for comparing the survival of different groups.

Survival analysis of female dogs with mammary tumors after mastectomy: epidemiological, clinical and morphological aspects

Abstract: Mammary gland tumors are the most common type of tumors in bitches but research on survival time after diagnosis is scarce. The purpose of this study was to investigate the relationship between survival time after mastectomy and a number of clinical and morphological variables. Data was collected retrospectively on bitches with mammary tumors seen at the Small Animal Surgery Clinic Service at the University of Brasília. All subjects had undergone mastectomy. Survival analysis was conducted using Cox's proportional hazard method. Of the 139 subjects analyzed, 68 died and 71 survived until the end of the study (64 months). Mean age was 11.76 years (SD=2.71), 53.84% were small dogs. 76.92% of the tumors were malignant, and 65.73% had both thoracic and inguinal glands affected. Survival time in months was associated with age (hazard rate ratios [HRR] =1.23, p-value =1.4x10-4), animal size (HRR between giant and small animals =2.61, p-value =0.02), nodule size (HRR =1.09, p-value =0.03), histological type (HRR between solid carcinoma and carcinoma in a mixed tumor =2.40, p-value =0.02), time between diagnosis and surgery (TDS, with HRR =1.21, p-value =2.7x10-15), and the interaction TDS*follow-up time (HRR =0.98, p-value =1.6x10-11). The present study is one of the few on the subject matter. Several important covariates were evaluated and age, animal size, nodule size, histological type, TDS and TDS*follow up time were identified as significantly associated to survival time.

Survival analysis of cereal crop variety innovations in the UK

This paper explores the changing survival patterns of cereal crop variety innovations in the UK since the introduction of plant breeders’ rights in the mid-1960s. Using non-parametric, semi-parametric and parametric approaches, we examine the determinants of the survival of wheat variety innovations, focusing on the impacts of changes to Plant Variety Protection (PVP) regime over the last four decades. We find that the period since the introduction of the PVP regime has been characterised by the accelerated development of new varieties and increased private sector participation in the breeding of cereal crop varieties. However, the increased flow of varieties has been accompanied by a sharp decline in the longevity of innovations. These trends may have contributed to a reduction in the returns appropriated by plant breeders from protected variety innovations and may explain the decline of conventional plant breeding in the UK. It may also explain the persistent demand from the seed industry for stronger protection. The strengthening of the PVP regime in conformity with the UPOV Convention of 1991, the introduction of EU-wide protection through the Community Plant Variety Office and the introduction of royalties on farm-saved seed have had a positive effect on the longevity of protected variety innovations, but have not been adequate to offset the long term decline in survival durations.

Survival analysis statistics applied to threshold data obtained from the ascending forced-choice method of limits

Sensory thresholds are often collected through ascending forced-choice methods. Group thresholds are important for comparing stimuli or populations; yet, the method has two problems. An individual may correctly guess the correct answer at any concentration step and might detect correctly at low concentrations but become adapted or fatigued at higher concentrations. The survival analysis method deals with both issues. Individual sequences of incorrect and correct answers are adjusted, taking into account the group performance at each concentration. The technique reduces the chance probability where there are consecutive correct answers. Adjusted sequences are submitted to survival analysis to determine group thresholds. The technique was applied to an aroma threshold and a taste threshold study. It resulted in group thresholds similar to ASTM or logarithmic regression procedures. Significant differences in taste thresholds between younger and older adults were determined. The approach provides a more robust technique over previous estimation methods.

Use of survival analysis as a tool for the genetic improvement of age at first conception in Nellore cattle

Restricted breeding seasons in beef cattle lead to censoring of reproductive data. In this paper, age at first conception (AFC) of Nellore females exposed to the sires for the first time between 11 and 16 months of age, was studied aiming to verify the possibility of genetically advance sexual precocity using a survival model. The final data set contained 6699 records of AFC in days. Records of females that did not calve in the next year following exposure to the sire were considered censored (77.5% of total). The model used was a Weibull mixed survival model including effects of contemporary groups, period (fixed) and animal (random). The effect of the contemporary groups on AFC was important (p < 0.01). Heritabilities were 0.51 and 0.76 in logarithmic and original scales respectively. Results indicate that it is possible to genetically advance sexual precocity, using the outcome of survival analysis of AFC as selection criterion. They also suggest that improvements of the environment could advance sexual precocity too, thus an adequate pregnancy rate for farmers could quickly be achieved.