Background:
In relapsing-remitting multiple sclerosis (RRMS), early identification of suboptimal responders can prevent disability progression.
Objective:
We aimed to develop and validate a dynamic ...score to guide the early decision to switch from first- to second-line therapy.
Methods:
Using time-dependent propensity scores (PS) from a French cohort of 12,823 patients with RRMS, we constructed one training and two validation PS-matched cohorts to compare the switched patients to second-line treatment and the maintained patients. We used a frailty Cox model for predicting individual hazard ratios (iHRs).
Results:
From the validation PS-matched cohort of 348 independent patients with iHR ⩽ 0.69, we reported the 5-year relapse-free survival at 0.14 (95% confidence interval (CI) 0.09–0.22) for the waiting group and 0.40 (95% CI 0.32–0.51) for the switched group. From the validation PS-matched cohort of 518 independent patients with iHR > 0.69, these values were 0.37 (95% CI 0.30–0.46) and 0.44 (95% CI 0.37–0.52), respectively.
Conclusions:
By using the proposed dynamic score, we estimated that at least one-third of patients could benefit from an earlier switch to prevent relapse.
Pseudo-values provide a method to perform regression analysis for complex quantities with right-censored data. A further complication, interval-censored data, appears when events such as dementia are ...studied in an epidemiological cohort. We propose an extension of the pseudo-value approach for interval-censored data based on a semi-parametric estimator computed using penalised likelihood and splines. This estimator takes interval-censoring and competing risks into account in an illness-death model. We apply the pseudo-value approach to three mean value parameters of interest in studies of dementia: the probability of staying alive and non-demented, the restricted mean survival time without dementia and the absolute risk of dementia. Simulation studies are conducted to examine properties of pseudo-values based on this semi-parametric estimator. The method is applied to the French cohort PAQUID, which included more than 3,000 non-demented subjects, followed for dementia for more than 25 years.
The aim of this paper was to investigate the evolution of mortality and life expectancy according to dementia in two French populations 10 years apart. Two different populations of subjects aged 65 ...or older included in PAQUID from 1988 to 1989 (n = 1342) and 3C from 1999 to 2000 (n = 1996) and initially not demented were followed over 10 years. Dementia was assessed using an algorithmic approach, and participants were considered to have dementia if they had an MMSE score < 24 AND a 4IADL score > 1. Illness-death models were used to compare mortality with and without dementia and to provide total life expectancy (LE), dementia-free life expectancy (DemFreeLE), life expectancy with dementia (DemLE), and survival with dementia. Mortality without dementia has decreased between the two populations among men HR = 0.63 (0.49–0.81) and women HR = 0.67 (0.50–0.90), whereas mortality with dementia has decreased for women only HR = 0.59 (0.41–0.87). Total LE and DemFreeLE have increased between the 1990s and the 2000s populations (total LE: + 2.5 years; DemFreeLE: + 2.2 years); DemLE only slightly increased between the populations (DemLE: + 0.3 years). For survival with dementia, an increase in survival has been evidenced (mean survival: + 1.3 years) for women only. The improvement in DemFreeLE is promising. However, as the duration of life with dementia tends to increase for women, efforts to delay the onset of dementia should be reinforced.
•Dementia is associated with a lower likelihood of receiving cancer treatment.•Dementia is associated with higher mortality in cancer untreated older patients.•Dependency is associated with higher ...mortality in cancer treated older patients.
Several studies have reported disparities in the care management and survival of older cancer patients. The aim of our study was to identify determinants of treatment administration in this population of cancer patients aged over 65 years taking into account competing risks of death.
The INCAPAC study is a population-based study. Four cancer registries and three prospective cohort studies on older subjects (age ≥65 years) from Gironde, a French department, were merged to identify older cancer patients. We used a non-parametric multi-state model including three states (cancer, treatment and all-cause death). This model allowed studying determinants of treatment administration (all treatments including curative, symptomatic and palliative treatments) and mortality considering that patients can move from cancer state to death state, either directly or through the treatment phase. Studied variables were demographic and socioeconomic-, cancer-, health-, and geriatric-related.
A total of 450 patients were included in the analyses. They were mainly aged 85 and over, men and educated. Among included patients, 372 (83%) received cancer treatment. In the final multivariate model, dementia was associated with a lower likelihood of receiving cancer treatment (HR = 0.68, 95% CI = 0.47–0.99). In treated patients, age, sex, comorbidities, dependency and stage at diagnosis were associated to all-cause mortality, and in untreated patients, diagnosis of dementia and stage at diagnosis were associated to mortality.
Further studies are necessary to understand the impact of geriatric impairments on treatment administration and to develop clinical practice guidelines.
Les indicateurs épidémiologiques de la démence tels que l'espérance de vie sans démence pour un âge donné ou le risque absolu sont des quantités utiles en santé publique. L'observation de la démence ...en temps discret entraine une censure par intervalle du temps d'apparition de la pathologie. De plus, certains individus peuvent développer une démence et décéder entre deux visites de suivi. Un modèle illness-death pour données censurées par intervalle est une solution pour modéliser simultanément les risques de démence et de décès et pour éviter la sous-estimation de l'incidence de la démence.Ces indicateurs dépendent à la fois du risque de démence mais aussi du risque de décès, contrairement à l'intensité de transition de la démence. Les modèles de régression disponibles ne prennent pas en compte la censure par intervalle ou ne sont pas adaptés à ces indicateurs. L'objectif de ce travail est de quantifier l'effet de facteurs de risque sur ces indicateurs épidémiologiques par des modèles de régression. La première partie de cette thèse est consacrée à l'extension de l'approche par pseudo-valeurs aux données censurées par intervalle. Les pseudo-valeurs sont calculées à partir d'estimateurs paramétriques ou d'estimateurs du maximum de vraisemblance pénalisée. Elles sont utilisées comme variable d'intérêt dans des modèles linéaires généralisés ou des modèles additifs généralisés pour permettre un effet non-linéaire des variables explicatives quantitatives. La seconde partie de cette thèse porte sur le développement d'un modèle par linéarisation des indicateurs épidémiologiques. L'idée est de calculer l'indicateur conditionnellement aux variables explicatives à partir des intensités de transition d'un modèle illness-death avec censure par intervalle du temps d'apparition de la maladie. Ces deux approches sont appliquées aux données de la cohorte française PAQUID pour étudier par exemple l'effet d'un score psychométrique (le MMS) sur des indicateurs épidémiologiques de la démence.
Dementia epidemiological indicators as the life expectancy without dementia at a specific age or the absolute risk are quantities meaningful for public health. Dementia is observed on discrete-time in cohort studies which leads to interval censoring of the time-to-onset. Moreover, some subjects can develop dementia and die between two follow-up visits. Illness-death model for interval-censored data is a solution to model simultaneously dementia risk and death risk and to avoid under-estimation of dementia incidence. These indicators depend on both dementia and death risks as opposed to dementia transition intensity. Available regression models do not take into account interval censoring or are not suitable for these indicators. The aim of this work is to propose regression models to quantify impact of risk factors on these indicators. Firstly, the pseudo-values approach is extended to interval-censored data. Pseudo-values are computed by parametric estimators or by maximum penalized likelihood estimators. Then pseudo-values are used as outcome in a generalized linear models or in a generalized additive models in case of non-linear effect of quantitative covariates. Secondly, the effect of covariates are summarized by linearization of the maximum likelihood estimator. In this part, the idea is to compute indicators conditionally on the covariates values from transition intensities of an illness-death model. These two approaches are applied to the French cohort PAQUID to study effect of a psychometric test (the MMS) on these indicators for example.
Pseudo-values provide a method to perform regression analysis for complex quantities with right-censored data. A further complication, interval-censored data, appears when events such as dementia are ...studied in an epidemiological cohort. We propose an extension of the pseudo-value approach for interval-censored data based on a semi-parametric estimator computed using penalised likelihood and splines. This estimator takes interval-censoring and competing risks into account in an illness-death model. We apply the pseudo-value approach to three mean value parameters of interest in studies of dementia: the probability of staying alive and non-demented, the restricted mean survival time without dementia and the absolute risk of dementia. Simulation studies are conducted to examine properties of pseudo-values based on this semi-parametric estimator. The method is applied to the French cohort PAQUID, which included more than 3,000 non-demented subjects, followed for dementia for more than 25 years.
More than half of cancer patients require palliative care; however, inequality in access and late referral in the illness trajectory are major issues. This study assessed the cumulative incidence of ...first hospital-based palliative care (HPC) referral, as well as the influence of patient-, tumor-, and care-related factors.
This is a retrospective population-based study.
The study included patients from the 2014 population-based cancer registry of Gironde, France. International Classification of Diseases, Tenth Revision, coding for palliative care identified HPC referrals from 2014 to 2018. The study included 8424 patients. Analyses considered the competing risk of death and were stratified by initial cancer prognosis (favorable vs unfavorable if metastatic or progressive cancer).
The 4-year incidence of HPC was 16.7% (95% confidence interval, 16.6–16.8). Lung cancer led to more referrals, whereas breast, colorectal, and prostatic locations were associated to less frequent HPC compared with other solid tumors. Favorable prognosis central nervous system tumors and unfavorable prognosis hematological malignancies also showed less HPC. The incidence of HPC was higher in tertiary centers, particularly for older patients. In the favorable prognosis subgroup, older and non-deprived patients received more HPC. In the unfavorable prognosis subgroup, the incidence of HPC was lower in patients who lived in rural areas than those who lived in urban areas.
One-sixth of cancer patients require HPC. Some factors influencing referral depend on the initial cancer prognosis. Our findings support actions to improve accessibility, especially for deprived patients, people living in rural areas, those with hematological malignancies, and those treated outside tertiary centers. In addition, consideration of age as factor of HPC may allow for improved design of the referral system.
Patients with metastatic breast cancer (MBC) often require inpatient palliative care (IPC). However, mounting evidence suggests age-related disparities in palliative care delivery. This study aimed ...to assess the cumulative incidence function (CIF) of IPC delivery, as well as the influence of age.
The national ESME (Epidemio-Strategy-Medical-Economical)-MBC cohort includes consecutive MBC patients treated in 18 French Comprehensive Cancer Centres. ICD-10 palliative care coding was used for IPC identification.
Our analysis included 12,375 patients, 5093 (41.2%) of whom were aged 65 or over. The median follow-up was 41.5 months (95% confidence interval CI, 40.5–42.5). The CIF of IPC was 10.3% (95% CI, 10.2–10.4) and 24.8% (95% CI, 24.7–24.8) at 2 and 8 years, respectively. At 2 years, among triple-negative patients, young patients (<65 yo) had a higher CIF of IPC than older patients after adjusting for cancer characteristics, centre and period (65+/<65: β = −0.05; 95% CI, −0.08 to −0.01). Among other tumour sub-types, older patients received short-term IPC more frequently than young patients (65+/<65: β = 0.02; 95% CI, 0.01 to 0.03). At 8 years, outside large centres, IPC was delivered less frequently to older patients adjusted to cancer characteristics and period (65+/<65: β = −0.03; 95% CI, −0.06 to −0.01).
We found a relatively low CIF of IPC and that age influenced IPC delivery. Young triple-negative and older non-triple-negative patients needed more short-term IPCs. Older patients diagnosed outside large centres received less long-term IPC. These findings highlight the need for a wider implementation of IPC facilities and for more age-specific interventions.
•Age was an independent factor of inpatient palliative care (IPC) delivery in metastatic breast cancer (MBC) patients.•This association depended on the tumour sub-type and the centre activity.•Young HER2-/HR- and older non-triple-negative patients needed more short-term IPC.•Older patients diagnosed in large centres more frequently received long-term IPC.•A wider implementation of IPC might improve access for older MBC patients.
