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We propose an extension of the landmark model for ordinary survival data as a new approach to the problem of dynamic prediction in competing risks with time-dependent covariates. We fix a set of landmark time points tLM within the follow-up interval. For each of these landmark time points tLM , we create a landmark data set by selecting individuals at risk at tLM ; we fix the value of the time-dependent covariate in each landmark data set at tLM . We assume Cox proportional hazard models for the cause-specific hazards and consider smoothing the (possibly) time-dependent effect of the covariate for the different landmark data sets. Fitting this model is possible within the standard statistical software. We illustrate the features of the landmark modelling on a real data set on bone marrow transplantation., (Copyright © 2012 John Wiley & Sons, Ltd.)

We address the problem of meta-analysis of pairs of survival curves under heterogeneity. Starting point for the meta-analysis is a set of studies, each comparing the same two treatments, containing information about multiple survival outcomes. Under heterogeneity, we model the number of events using an extension of the Poisson correlated gamma-frailty model with serial within-arm and positive between-arm correlations. The parameters of the models are estimated following a two-stage estimation procedure. In the first stage the underlying hazards and between-study variance are estimated using the marginals, while a second stage is used to estimate both within-arm and between-arm correlations. The methodology is illustrated with an observational study on breast cancer.

Typically long-lived sibling pairs have been collected for linkage analysis of human longevity and information on life span of first-degree relatives is available to assess familial aggregation of life span. We propose a new weighted statistic for aggregation analysis, which tests for a relationship between a family history of excessive survival of the sibships of the long-lived pairs and the survival of their parents and their offspring. For linkage analysis, we derive a new weighted score statistic from a simple gamma frailty model, which assigns more weight to excessive long-lived pairs. We apply the methods to data from the Leiden Longevity Study, which consists of sibling pairs of age 90 years or above and their first-degree relatives. The pairs have been genotyped for microsatellite markers in a candidate region. Association was present between survival within the sibships and survival of the offspring, but not with the parental generation. For linkage analysis, weighting increased the value of the test statistic, but the result was not statistically significant. About the methods we conclude that the statistic for aggregation provides insight into clustering of life span and the statistic for linkage provides a new tool to include demographic information into the analysis., (Copyright (c) 2008 John Wiley & Sons, Ltd.)

Randomized clinical trials with long-term survival data comparing two treatments often show Kaplan-Meier plots with crossing survival curves. Such behaviour implies a violation of the proportional hazards assumption for treatment. The Cox proportional hazards regression model with treatment as a fixed effect can therefore not be used to assess the influence of treatment of survival. In this paper we analyse long-term follow-up data from the Dutch Gastric Cancer Trial, a randomized study comparing limited (D1) lymph node dissection with extended (D2) lymph node dissection. We illustrate a number of ways of dealing with survival data that do not obey the proportional hazards assumption, each of which can be easily implemented in standard statistical packages., (Copyright 2005 John Wiley & Sons, Ltd.)

Prognostic models can be developed with multiple regression analysis of a data set containing individual patient data. Often this data set is relatively small, while previously published studies present results for larger numbers of patients. We describe a method to combine univariable regression results from the medical literature with univariable and multivariable results from the data set containing individual patient data. This 'adaptation method' exploits the generally strong correlation between univariable and multivariable regression coefficients. The method is illustrated with several logistic regression models to predict 30-day mortality in patients with acute myocardial infarction. The regression coefficients showed considerably less variability when estimated with the adaptation method, compared to standard maximum likelihood estimates. Also, model performance, as distinguished in calibration and discrimination, improved clearly when compared to models including shrunk or penalized estimates. We conclude that prognostic models may benefit substantially from explicit incorporation of literature data., (Copyright 2000 John Wiley & Sons, Ltd.)

This paper concerns the survival analysis of liver transplant patients when patients with a potentially fatal rejection of the transplanted organ may receive a retransplant. A multistate model, analysing the states 'alive with first graft' and 'alive with second graft' separately, is suggested. Proportional hazards models and logistic regression models are used to evaluate which risk factors related to donor, preservation and recipient, influence the transition intensities. The complete model is used to predict overall survival of a patient and to study the influence of the risk factors on total survival.

A review is given of different ways of estimating the error rate of a prediction rule based on a statistical model. A distinction is drawn between apparent, optimum and actual error rates. Moreover it is shown how cross-validation can be used to obtain an adjusted predictor with smaller error rate. A detailed discussion is given for ordinary least squares, logistic regression and Cox regression in survival analysis. Finally, the splitsample approach is discussed and demonstrated on two data sets.

In this study the authors applied flow cytometric DNA-ploidy analysis to multiple female genital tract malignant tumors in 43 patients, most of whom (n = 37) had bilateral ovarian cancer. An algorithm was developed for calculation of the likelihood ratio of the probabilities that measured DNA index differences between multiple tumor localizations within the same patient could be attributed to measurement variation or to true biologic DNA content differences. The results of this statistical analysis show that in 72% of the cases (31 of 43) this probability ratio exceeded 1. Because the probability that two independent tumors will have a near-identical aneuploid DNA content is very low, this finding supports a metastatic process rather than the occurrence of multiple primary tumors in these patients. Thus, flow cytometric DNA-ploidy analysis can be helpful in the identification of metastatic disease in patients with multiple female genital tract malignant tumors.

The study was designed to determine the efficacy of a two-drug and three-drug combination chemotherapy regimen for patients with advanced epithelial ovarian carcinoma resistant to alkylating monotherapy. Patients were randomized to receive either Adriamycin (doxorubicin) and cis-diamminedichloroplatinum(II) (AP) repeated every 3 weeks, or AP plus hexamethylmelamine (HAP) repeated every 5 weeks. Forty-five patients were evaluable for response and 49 for survival. No significant differences were found between the treatment groups as to response rate, progression-free survival, and survival. A remission was achieved in 20% of the patients and stable disease in another 20%. Median progression-free survival of all patients was only 4 months (median survival, 6 months). All patients showed progressive disease within 13 months after the onset of chemotherapy. Patients responding to treatment and those with an interval of more than 2 years between the initial diagnosis and cancer recurrence, experienced prolonged survival. Two conclusions can be drawn from the results of this study; neither of the regimens is superior to the other, and the effect of both in alkylator-resistant patients with ovarian cancer are meager. In studies on salvage chemotherapy, to the contrary, these combinations induced remissions in more than 40% of the patients. This difference in response rate might be due to differences between the prognostic factors of the patient populations. Better results are to be expected when these drugs are used in initial drug programs for previously untreated patients.