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Breast cancer affects mostly older women but there are no guidelines especially devoted to adjuvant chemotherapy for this population. In this context, this study was carried out in a population-based cohort of French elderly women with breast cancer, to check adherence to the existing national guidelines according to the women's age, taking into account the evolution of the situation over time for women requiring chemotherapy. Between October 2006 and December 2008, all consecutive women included in the French Health registry for a biopsy-proven primary nonmetastatic breast cancer, aged 65-80 years at diagnosis, and living in South Eastern France, were asked to participate in a cohort study. Medical information was collected from physicians. The study population was restricted to the 223 women who were recommended adjuvant chemotherapy according to national guidelines. Those who received chemotherapy were compared to those who did not receive this treatment. Among these 223 women 55% had received chemotherapy. Only three women refused the treatment. Less than 8% have had a geriatric assessment before treatment decision and only two were proposed to participate in a clinical trial. After adjustment for comorbidity score, tumor characteristics, socio-demographic characteristics, and year of diagnosis, increasing patient age was independently associated with decreased guideline concordance for adjuvant chemotherapy. Women aged 75-80 years received chemotherapy more than four times less often than women aged 65-74 years. However, the percentage of women who received chemotherapy increased from 33% to 58% between 2006 and 2008, in parallel with the setting up of Onco-Geriatric Coordination Units in the area. In France, chronological age remains a barrier to receive chemotherapy for older breast cancer women but the establishment of a formal collaboration between oncologists and geriatricians seems to be an effective way to improve care delivery in this population., (© 2016 Wiley Periodicals, Inc.)

Recently goodness-of-fit tests have been proposed for checking the proportional subdistribution hazards assumptions in the Fine and Gray regression model. Zhou, Fine, and Laird proposed weighted Schoenfeld-type residuals tests derived under an assumed model with specific form of time-varying regression coefficients. Li, Sheike, and Zhang proposed an omnibus test based on cumulative sums of Schoenfeld-type residuals. In this article, we extend the class of weighted residuals tests by allowing random weights of Schoenfeld-type residuals at ordered event times. In particular, it is demonstrated that weighted residuals tests using monotone weight functions of time are consistent against monotone proportional subdistribution hazards assumptions. Extensive Monte Carlo studies were conducted to evaluate the finite-sample performance of recent goodness-of-fit tests. Results from simulation studies show that weighted residuals tests using monotone random weight functions commonly used in non-proportional hazards regression settings tend to be more powerful for detecting monotone departures than other goodness-of-fit tests assuming no specific time-varying effect or misspecified time-varying effects. Two examples using real data are provided for illustrations. Copyright © 2016 John Wiley & Sons, Ltd., (Copyright © 2016 John Wiley & Sons, Ltd.)

In chronic diseases, such as cancer, recurrent events (such as relapses) are commonly observed; these could be interrupted by death. With such data, a joint analysis of recurrence and mortality processes is usually conducted with a frailty parameter shared by both processes. We examined a joint modeling of these processes considering death under two aspects: 'death due to the disease under study' and 'death due to other causes', which enables estimating the disease-specific mortality hazard. The excess hazard model was used to overcome the difficulties in determining the causes of deaths (unavailability or unreliability); this model allows estimating the disease-specific mortality hazard without needing the cause of death but using the mortality hazards observed in the general population. We propose an approach to model jointly recurrence and disease-specific mortality processes within a parametric framework. A correlation between the two processes is taken into account through a shared frailty parameter. This approach allows estimating unbiased covariate effects on the hazards of recurrence and disease-specific mortality. The performance of the approach was evaluated by simulations with different scenarios. The method is illustrated by an analysis of a population-based dataset on colon cancer with observations of colon cancer recurrences and deaths. The benefits of the new approach are highlighted by comparison with the 'classical' joint model of recurrence and overall mortality. Moreover, we assessed the goodness of fit of the proposed model. Comparisons between the conditional hazard and the marginal hazard of the disease-specific mortality are shown, and differences in interpretation are discussed., (Copyright © 2014 John Wiley & Sons, Ltd.)

Purpose: Several studies have been conducted to estimate persistence to hormonal therapy among women with breast cancer (BC). Most studies focus on first treatment discontinuation. Patients, however, can have numerous periods of treatment discontinuation or treatment exposure. Our objective is to estimate persistence to tamoxifen in patients with BC while accounting for temporary treatment discontinuations and this by using multi-state (MS) models., Methods: A cohort of 10,806 women with BC having received at least one prescription of tamoxifen between 1998 and 2008 was constituted from the UK General Practice Research Database. We fitted a semi-Markov model with three states to estimate the probability of being off treatment over a 5-year period while accounting for temporary treatment discontinuations (transition between on treatment and off treatment) and competing risks (recurrence of BC or death)., Results: Non-persistence, as estimated from the MS model, ranged from 12.1% (95% confidence interval [95%CI]: 9.2-15.1) at 1 year to 14.9% (95%CI: 11.7-18.1) at 5 years. Estimations of non-persistence based on the Kaplan-Meier model were higher, i.e., 29.3% (95%CI: 28.1-30.6) at 5 years, as well as those obtained from a competing risk model, i.e., 24.0% (95%CI: 22.9-25.1). Most temporary discontinuations (94.7%) lasted less than 6 months. Temporary treatment discontinuations are frequent and should be accounted for when measuring adherence to treatment. MS models can provide a useful framework for this sort of analysis insofar as they help describe patients' complex behavior. This may help tailor interventions that improve persistence to hormonal therapy among women with BC., (Copyright © 2014 John Wiley & Sons, Ltd.)

Regression-based relative survival models are commonly used in population-based cancer studies to estimate the real impact on the excess mortality of covariates that influence overall mortality. Usually, the mortality observed in a study cohort is corrected by the expected mortality hazard in the general population, which is given by life tables provided by national statistics institutes. These life tables are stratified by age, sex, calendar year, and, sometimes, other demographic data (ethnicity, deprivation, and others). However, in most cases, the same demographic data are not available for the study cohort and the general population; this leads to differences between the expected mortality of the general population and that of the study cohort. More generally, the absence of some demographic variables in life tables may introduce a measurement bias into the estimation of the excess mortality. In the present article, we used a simulation approach with different plausible scenarios to evaluate the impact of an additional life-table variable on excess mortality estimates and study the extent and the direction of the biases in estimating the effect of each covariate on the excess mortality. We showed that the use of life table that lacks stratification by a variable present in the excess hazard model results in a measurement bias not only in the estimate of the effect of this variable but also, to a lesser extent, in the estimates of the effects of the other covariates included in the model. We also demonstrated this measurement bias by a population-based colorectal cancer analysis., (Copyright © 2012 John Wiley & Sons, Ltd.)

To quantify noninvasively myocardial blood flow (MBF) and MBF reserve in isoflurane-anesthetized rats using the Look-Locker flow-alternating inversion recovery gradient-echo arterial spin labeling technique (LLFAIRGE-ASL), and to compare the results with the fluorescent microsphere (FM) technique. Male Wistar rats (weight = 200-240 g, n = 21) were anesthetized with 2.0% isoflurane. Hemodynamic parameters were recorded. In seven rats, MBF was assessed on a Bruker Biospec 4.7T MR system using an ECG- and respiration-gated LLFAIRGE-ASL (pixel size = 234 × 468µm(2) , TE = 1.52ms) at rest and during adenosine infusion (140 µg/kg/min). A mixture of 200 000 FM was injected into a second group of rats at rest and during adenosine infusion (n = 7 each), under similar physiologic conditions. Hearts and skeletal muscle samples were processed for fluorescence spectroscopy. Two-tailed unpaired, paired Student's t-test and ANOVA were used to compare groups. MBF measured with LLFAIRGE-ASL was 5.2 ± 1.0 mL/g/min at rest and 13.3 ± 3.0 mL/g/min during adenosine infusion. Results obtained with fluorescent microspheres yielded 5.9 ± 2.3 mL/g/min (nonsignificant vs. LLFAIRGE-ASL, p = 0.9) at rest and 13.1 ± 2.1 mL/g/min (nonsignificant vs. LLFAIRGE-ASL, p = 0.4) during adenosine infusion. Myocardial blood flow reserve measured using LLFAIRGE-ASL and FM were not significantly different (2.5 ± 0.6 vs. 2.4 ± 0.9, respectively; p = 0.8). Hemodynamic parameters during the experiments were not different between the groups. The myocardial blood flow reserve determined under isoflurane anesthesia was 2.5 ± 0.6, which was not different from the value obtained with FM. LLFAIRGE-ASL provided MBF maps with high spatial resolution in rats under isoflurane anesthesia. LLFAIRGE-ASL is a noninvasive measure to assess myocardial blood flow reserve and provides an interesting tool for cardiovascular research., (Copyright © 2011 John Wiley & Sons, Ltd.)

Relative survival methods permit separating the effects of prognostic factors on disease-related 'excess mortality' from their effects on other-causes 'natural mortality', even when individual causes of death are unknown. As in conventional 'crude' survival, accurate assessment of prognostic factors requires testing and possibly modeling of non-proportional effects and, for continuous covariates, of non-linear relationships with the hazard. We propose a flexible extension of the additive-hazards relative survival model, in which the observed all-causes mortality hazard is represented by a sum of disease-related 'excess' and natural mortality hazards. In our flexible model, the three functions representing (i) the baseline hazard for 'excess' mortality, (ii) the time-dependent effects, and (iii) for continuous covariates, non-linear effects, on the logarithm of this hazard, are all modeled by low-dimension cubic regression splines. Non-parametric likelihood ratio tests are proposed to test the time-dependent and non-linear effects. The accuracy of the estimated functions is evaluated in multivariable simulations. To illustrate the new insights offered by the proposed model, we apply it to re-assess the effects of patient age and of secular trends on disease-related mortality in colon cancer., (Copyright © 2011 John Wiley & Sons, Ltd.)

Limited information is available on clinical management of Flat Bone Osteosarcomas (FBOS). We retrospectively analysed prognostic factors and outcome. Twenty-eight patients were treated in our institution. Survival curves were obtained by the Kaplan-Meier method and compared with the log-rank test. The overall survival (OS) rates at 5 and 10 years were 52.4% and 45.8% respectively. The event-free survival (EFS) rates at 5 and 10 years were 41.5%. The factors influencing EFS in univariate analysis were location, metastatic disease at diagnosis, effect of neoadjuvant chemotherapy, histological response and adequate local tumour control. Location, metastatic disease at diagnosis, effect of neoadjuvant chemotherapy, histological response and local recurrence were statistically correlated with OS. Multivariate analysis retained metastatic disease at diagnosis as prognostic factors of EFS and OS. Our results suggest a more favourable outcome of FBOS as the use of a treatment scheme based on the protocols for long bone osteosarcomas. However, an adequate local treatment is essential to ensure a better outcome., (© 2010 Blackwell Publishing Ltd.)

Aims: The clinical features, prognosis, and even definition of left ventricular non-compaction (LVNC) are still the subject of much debate. The aim of this registry was to describe the clinical, echocardiographic, and prognostic features of LVNC in France. The main endpoint was to assess clinical and echocardiographic predictors of adverse outcome, defined as death or heart transplantation., Methods and Results: Between 2004 and 2006, 154 suspected cases of LNVC were identified from a nationwide survey in France. The diagnosis of LVNC was confirmed in 105 cases by echocardiographic evaluation in a core laboratory. Clinical and echocardiographic data for the 105 cases of LVNC are presented. Left ventricular non-compaction was first detected from heart failure symptoms in 45 patients, rhythm disorders in 12, and familial screening in 8. Left ventricular ejection fraction (LVEF) was < 30% in 46% of patients, but ≥ 50% in 16%. The latter had less symptoms of severe heart failure (11 vs. 54%, P = 0.001), but similar extension of the NC zone. During 2.33 ± 1.47 years of follow-up, several complications occurred, including severe heart failure in 33 patients, transplantation in 9, ventricular arrhythmia in 7, embolic events in 9, and death in 12. Factors associated with death or heart transplantation were NYHA 3 or 4 (HR = 6.69; P = 0.0007), high LV filling pressures (HR = 7.59; P = 0.001), LVEF (HR = 0.93; P = 0.006), and hospitalization for heart failure (HR = 13.55; P < 0.0001)., Conclusion: In this large reported series of LVNC, we observed that: (i) Left ventricular non-compaction was detected by familial screening in asymptomatic patients in 8% of cases. (ii) Left ventricular non-compaction was frequently over-diagnosed by echocardiography. (iii) Patients identified as LVNC presented with a high risk of severe complications, transplantation or death and needed close follow-up.

Prognostic studies often involve modeling competing risks, where an individual can experience only one of alternative events, and the goal is to estimate hazard functions and covariate effects associated with each event type. Lunn and McNeil proposed data manipulation that permits extending the Cox's proportional hazards model to estimate covariate effects on the hazard of each competing events. However, the hazard functions for competing events are assumed to remain proportional over the entire follow-up period, implying the same shape of all event-specific hazards, and covariate effects are restricted to also remain constant over time, even if such assumptions are often questionable. To avoid such limitations, we propose a flexible model to (i) obtain distinct estimates of the baseline hazard functions for each event type, and (ii) allow estimating time-dependent covariate effects in a parsimonious model. Our flexible competing risks regression model uses smooth cubic regression splines to model the time-dependent changes in (i) the ratio of event-specific baseline hazards, and (ii) the covariate effects. In simulations, we evaluate the performance of the proposed estimators and likelihood ratio tests, under different assumptions. We apply the proposed flexible model in a prognostic study of colorectal cancer mortality, with two competing events: 'death from colorectal cancer' and 'death from other causes'.

Background: O(6)-methylguanine-DNA methyltransferase (MGMT) is a key enzyme in the DNA repair process after alkylating agent action. Epigenetic silencing of the MGMT gene by promoter methylation has been associated with longer survival in patients with newly diagnosed glioblastoma multiforme (GBM) who receive alkylating agents. In this study, the authors evaluated the prognostic value of different biomarkers in recurrent GBM and analyzed the changes in MGMT status between primary tumors and recurrent tumors., Methods: Twenty-two patients who had recurrent GBM and who underwent surgery with carmustine wafer implantation were enrolled prospectively between 2005 and 2007. The authors investigated the correlation between MGMT silencing in the tumor at recurrence and survival taking into account other clinically recognized prognostic factors. MGMT status was determined by using methylation-specific polymerase chain reaction analysis, a high-throughput quantitative methylation assay, and immunohistochemistry. In addition, expression analyses of human mutL homolog 1, human mutS homolog 2, and tumor necrosis factor alpha-induced protein 3 at recurrence were conducted with regard to their prognostic impact., Results: The median progression-free survival (PFS) and overall survival (OS) rates after recurrence were 3.6 months and 9.9 months, respectively, and the 6-month PFS rate after recurrence was 27.2%. On multivariate analysis, only age (P=.04) and MGMT promoter hypermethylation at recurrence, as determined by MethyLight technology (P=.0012) and methylation-specific polymerase chain reaction (MSP) analysis (P=.004), were correlated with better PFS. On multivariate analysis, only MGMT promoter hypermethylation at recurrence, as determined by using MethyLight technology (P=.019) and MSP analysis (P=.046), was associated with better OS., Conclusions: MGMT methylation status was an important prognostic factor in patients with recurrent GBM who underwent surgery plus carmustine wafer implantation; therefore, it was useful in predicting the outcome of GBM therapy at recurrence., (Copyright (c) 2009 American Cancer Society.)

Relative survival assesses the effects of prognostic factors on disease-specific mortality when the cause of death is uncertain or unavailable. It provides an estimate of patients' survival, allowing for the effects of other independent causes of death. Regression-based relative survival models are commonly used in population-based studies to model the effects of some prognostic factors and to estimate net survival. Most often, studies focus on routinely collected prognostic factors for which the proportion of missing values is usually low (around 5 per cent). However, in some cases, additional factors are collected with a greater proportion of missingness. In the present article, we systematically assess the performance of multiple imputation in regression analysis of relative survival through a series of simulation experiments. According to the assumptions concerning the missingness mechanism (completely at random, at random, and not at random) and the missingness pattern (monotone, non-monotone), several strategies were considered and compared: all cases analysis, complete cases analysis, missing data indicator analysis, and multiple imputation by chained equations (MICE) analysis. We showed that MICE performs well in estimating the hazard ratios and the baseline hazard function when the missing mechanism is missing at random (MAR) conditionally on the vital status. In the situations where the missing mechanism was not MAR conditionally on vital status, complete case behaves consistently. As illustration, we used data of the French Cancer Registries on relative survival of patients with colorectal cancer., (Copyright 2008 John Wiley & Sons, Ltd.)

Background: Ependymomas account for 2% of all intracranial tumors in adults. Supratentorial ependymomas are less common than their infratentorial counterparts. To the authors' knowledge to date, the predictive values of surgery, histology, and patient-related prognostic factors for these tumors remain unresolved. The authors report a series of adult patients with supratentorial ependymomas to characterize the roles of surgery and histology in tumor control., Methods: The authors retrospectively studied a homogenous population of 46 adult patients who had supratentorial ependymomas from 24 French neurosurgical centers between 1990 and 2004. All clinicoradiologic and follow-up data were analyzed, and a central pathologic review was performed by 2 certified neuropathologists., Results: The mean (+/-standard error) 5- and 10-year overall survival rates for the entire population were 57.1% +/- 8.7% and 41.8% +/- 9.9%, respectively. The 5- and 10-year progression-free survival rates for the entire cohort were of 33.8% +/- 8.1% and 25.4 +/- 8%, respectively. On both univariate and multivariate analysis, age <55 years, greater extent of surgery, and lower histologic grade were associated with longer overall and progression-free survival. However, longer progression-free survival but was not considered a candidate variable for the multivariate model, because data were available for only 34 of 46 patients., Conclusions: In association with age and extent of surgery, histologic grade was identified as a major prognostic factor in adult supratentorial ependymomas. The application of a simple and reproducible grading scheme using objective anaplastic criteria appeared to be both useful practically and clinically applicable. The role of adjuvant radiotherapy for patients with incompletely resected, low-grade ependymomas needs to be investigated further., ((Copyright) 2008 American Cancer Society.)

Relative survival is a method for assessing prognostic factors for disease-specific mortality. However, most relative survival models assume that the effect of covariate on disease-specific mortality is fixed-in-time, which may not hold in some studies and requires adapted modelling. We propose an extension of the Esteve et al. regressive relative survival model that uses the counting process approach to accommodate time-dependent effect of a predictor's on disease-specific mortality. This approach had shown its robustness, and the properties of the counting process give a simple and attractive computational solution to model time-dependent covariates. Our approach is illustrated with the data from the Stanford Heart Transplant Study and with data from a hospital-based study on invasive breast cancer. Advantages of modelling time-dependent covariates in relative survival analysis are discussed., (Copyright 2005 John Wiley & Sons, Ltd.)

Relative survival, a method for assessing prognostic factors for disease-specific mortality in unselected populations, is frequently used in population-based studies. However, most relative survival models assume that the effects of covariates on disease-specific mortality conform with the proportional hazards hypothesis, which may not hold in some long-term studies. To accommodate variation over time of a predictor's effect on disease-specific mortality, we developed a new relative survival regression model using B-splines to model the hazard ratio as a flexible function of time, without having to specify a particular functional form. Our method also allows for testing the hypotheses of hazards proportionality and no association on disease-specific hazard. Accuracy of estimation and inference were evaluated in simulations. The method is illustrated by an analysis of a population-based study of colon cancer., (Copyright 2003 John Wiley & Sons, Ltd.)

The enantiomers of 1-methyl-3-(10H-phenothiazine-10-ylmethyl)-1-azoniabicyclo[2 ,2,2]octane iodide (1) were prepared by chiral chromatographic resolution of the precursor mequitazine (2). The (+)-(S)-enantiomer 1b is 10-fold more potent than (-)-(R)-enantiomer 1a as a histamine antagonist, while the two enantiomers show the same antimuscarinic activity in vitro. The absolute configuration of the more active dextrorotatory isomer has been determined by X-ray analysis. Conformational analysis and molecular modeling suggest that the (+)-(S)-enantiomer can adopt a conformation similar to that attributed to the receptor binding conformers of classical antihistamines.