Abstract:
:Cancer survival trend analyses are essential to describe accurately the way medical practices impact patients' survival according to the year of diagnosis. To this end, survival models should be able to account simultaneously for non-linear and non-proportional effects and for complex interactions between continuous variables. However, in the statistical literature, there is no consensus yet on how to build such models that should be flexible but still provide smooth estimates of survival. In this article, we tackle this challenge by smoothing the complex hypersurface (time since diagnosis, age at diagnosis, year of diagnosis, and mortality hazard) using a multidimensional penalized spline built from the tensor product of the marginal bases of time, age, and year. Considering this penalized survival model as a Poisson model, we assess the performance of this approach in estimating the net survival with a comprehensive simulation study that reflects simple and complex realistic survival trends. The bias was generally small and the root mean squared error was good and often similar to that of the true model that generated the data. This parametric approach offers many advantages and interesting prospects (such as forecasting) that make it an attractive and efficient tool for survival trend analyses.
journal_name
Stat Methods Med Resjournal_title
Statistical methods in medical researchauthors
Remontet L,Uhry Z,Bossard N,Iwaz J,Belot A,Danieli C,Charvat H,Roche L,CENSUR Working Survival Group.doi
10.1177/0962280218779408subject
Has Abstractpub_date
2019-08-01 00:00:00pages
2368-2384issue
8eissn
0962-2802issn
1477-0334journal_volume
28pub_type
杂志文章abstract::Censored data make survival analysis more complicated because exact event times are not observed. Statistical methodology developed to account for censored observations assumes that patients' withdrawal from a study is independent of the event of interest. However, in practice, some covariates might be associated to b...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280216628900
更新日期:2018-02-01 00:00:00
abstract::Statistical methods for carrying out asymptotic inferences (tests or confidence intervals) relative to one or two independent binomial proportions are very frequent. However, inferences about a linear combination of K independent proportions L = Σβ(i)p(i) (in which the first two are special cases) have had very little...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280209347953
更新日期:2011-08-01 00:00:00
abstract::Many statistical studies report p-values for inferential purposes. In several scenarios, the stochastic aspect of p-values is neglected, which may contribute to drawing wrong conclusions in real data experiments. The stochastic nature of p-values makes their use to examine the performance of given testing procedures o...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217704451
更新日期:2018-12-01 00:00:00
abstract::Aim To present a flexible model for repeated measures longitudinal growth data within individuals that allows trends over time to incorporate individual-specific random effects. These may reflect the timing of growth events and characterise within-individual variability which can be modelled as a function of age. Subj...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217706728
更新日期:2018-11-01 00:00:00
abstract::Several epidemiological parameters have been introduced for quantifying the population impact of a certain exposure on morbidity on a population level, termed 'attributable risk' (AR). Of these definitions, the AR as suggested by Levin in 1953 or some algebraic transformations of it are most commonly used. A structure...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/096228020101000305
更新日期:2001-06-01 00:00:00
abstract::Within paediatric populations, there may be distinct age groups characterised by different exposure-response relationships. Several regulatory guidance documents have suggested general age groupings. However, it is not clear whether these categorisations will be suitable for all new medicines and in all disease areas....
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280220903751
更新日期:2020-09-01 00:00:00
abstract::In recent years, disease mapping studies have become a routine application within geographical epidemiology and are typically analysed within a Bayesian hierarchical model formulation. A variety of model formulations for the latent level have been proposed but all come with inherent issues. In the classical BYM (Besag...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280216660421
更新日期:2016-08-01 00:00:00
abstract::In medical experiments with the objective of testing the equality of two means, data are often partially paired by design or because of missing data. The partially paired data represent a combination of paired and unpaired observations. In this article, we review and compare nine methods for analyzing partially paired...
journal_title:Statistical methods in medical research
pub_type: 杂志文章,评审
doi:10.1177/0962280215577111
更新日期:2017-06-01 00:00:00
abstract::Simple mechanistic epidemic models are widely used for forecasting and parameter estimation of infectious diseases based on noisy case reporting data. Despite the widespread application of models to emerging infectious diseases, we know little about the comparative performance of standard computational-statistical fra...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217747054
更新日期:2018-07-01 00:00:00
abstract::The three-class Youden index serves both as a measure of medical test accuracy and a criterion to choose the optimal pair of cutoff values for classifying subjects into three ordinal disease categories (e.g. no disease, mild disease, advanced disease). We present a Bayesian nonparametric approach for estimating the th...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217742538
更新日期:2018-03-01 00:00:00
abstract::This paper presents and compares several methods of measuring continuous baseline covariate imbalance in clinical trial data. Simulations illustrate that though the t-test is an inappropriate method of assessing continuous baseline covariate imbalance, the test statistic itself is a robust measure in capturing imbalan...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280211416038
更新日期:2015-04-01 00:00:00
abstract::In many longitudinal studies, evaluating the effect of a binary or continuous predictor variable on the rate of change of the outcome, i.e. slope, is often of primary interest. Sample size determination of these studies, however, is complicated by the expectation that missing data will occur due to missed visits, earl...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280212437452
更新日期:2015-12-01 00:00:00
abstract::Appropriate handling of aggregate missing outcome data is necessary to minimise bias in the conclusions of systematic reviews. The two-stage pattern-mixture model has been already proposed to address aggregate missing continuous outcome data. While this approach is more proper compared with the exclusion of missing co...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280220983544
更新日期:2021-01-06 00:00:00
abstract::Tree-based methods are very powerful and popular tools for analysing survival data with right-censoring. The existing methods assume that the true time-to-event and the censoring times are independent given the covariates. We propose different ways to build survival forests when dependent censoring is suspected, by us...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217727314
更新日期:2019-02-01 00:00:00
abstract:BACKGROUND:When trials are subject to departures from randomised treatment, simple statistical methods that aim to estimate treatment efficacy, such as per protocol or as treated analyses, typically introduce selection bias. More appropriate methods to adjust for departure from randomised treatment are rarely employed,...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217735560
更新日期:2019-03-01 00:00:00
abstract::The probability model for periodic screening was extended to provide statistical inference for sensitivity depending on sojourn time, in which the sensitivity was modeled as a function of time spent in the preclinical state and the sojourn time. The likelihood function with the proposed sensitivity model was then eval...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280212465499
更新日期:2016-04-01 00:00:00
abstract::In medical sciences, we often encounter longitudinal temporal relationships that are non-linear in nature. The influence of risk factors may also change across longitudinal follow-up. A system of multiphase non-linear mixed effects model is presented to model temporal patterns of longitudinal continuous measurements, ...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280214537255
更新日期:2017-02-01 00:00:00
abstract::Pattern-mixture model (PMM)-based controlled imputations have become a popular tool to assess the sensitivity of primary analysis inference to different post-dropout assumptions or to estimate treatment effectiveness. The methodology is well established for continuous responses but less well established for binary res...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280220941880
更新日期:2020-12-01 00:00:00
abstract::Couples with diseases associated with the sexual chromosomes, as well as families in countries where the desire for a male is extreme, are interested in influencing the sex of the baby. We propose an original composite likelihood approach to analyse the relation between sex of the newborn and timing of the intercourse...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217702415
更新日期:2018-11-01 00:00:00
abstract::This paper illustrates the use of multidimensional scaling methods (MDS) to examine space-time patterns in epidemic data. The paper begins by outlining the principles of MDS. The model is then formally specified and illustrated by application to two data sets. The first is partly a tutorial example. It uses monthly re...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/096228029500400202
更新日期:1995-06-01 00:00:00
abstract::Early phase trials of complex interventions currently focus on assessing the feasibility of a large randomised control trial and on conducting pilot work. Assessing the efficacy of the proposed intervention is generally discouraged, due to concerns of underpowered hypothesis testing. In contrast, early assessment of e...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280215589507
更新日期:2016-06-01 00:00:00
abstract::The positivity assumption, or the experimental treatment assignment (ETA) assumption, is important for identifiability in causal inference. Even if the positivity assumption holds, practical violations of this assumption may jeopardize the finite sample performance of the causal estimator. One of the consequences of p...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280218774817
更新日期:2019-06-01 00:00:00
abstract::Multilevel models were originally developed to allow linear regression or ANOVA models to be applied to observations that are not mutually independent. This lack of independence commonly arises due to clustering of the units of observations into 'higher level units' such as patients in hospitals. In linear mixed model...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/096228020101000604
更新日期:2001-12-01 00:00:00
abstract::Age-period-cohort models are a popular tool for studying population-level rates; for example, trends in cancer incidence and mortality. Age-period-cohort models decompose observed trends into age effects that correlate with natural history, period effects that reveal factors impacting all ages simultaneously (e.g. inn...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217713033
更新日期:2019-01-01 00:00:00
abstract::Sample size calculations are needed to design and assess the feasibility of case-control studies. Although such calculations are readily available for simple case-control designs and univariate analyses, there is limited theory and software for multivariate unconditional logistic analysis of case-control data. Here we...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217737157
更新日期:2019-03-01 00:00:00
abstract::In genomic analysis, it is significant though challenging to identify markers associated with cancer outcomes or phenotypes. Based on the biological mechanisms of cancers and the characteristics of datasets, we propose a novel integrative interaction approach under a semiparametric model, in which genetic and environm...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280220909969
更新日期:2020-10-01 00:00:00
abstract::In this paper age-space-time models based on one and two-dimensional P-splines with B-spline bases are proposed for smoothing mortality rates, where both fixed relative scale and scale invariant two-dimensional penalties are examined. Model fitting and inference are carried out using integrated nested Laplace approxim...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217726802
更新日期:2019-02-01 00:00:00
abstract::Post-therapeutic surveillance is one important component of cancer care. However, there still is no evidence-based strategies to schedule patients' follow-up examinations. Our approach is based on the modeling of the probability of the onset of relapse at an early asymptotic or preclinical stage and its transition to ...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280214524178
更新日期:2016-12-01 00:00:00
abstract::Covariate-adaptive designs are widely used to balance covariates and maintain randomization in clinical trials. Adaptive designs for discrete covariates and their asymptotic properties have been well studied in the literature. However, important continuous covariates are often involved in clinical studies. Simply disc...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280218770231
更新日期:2019-06-01 00:00:00
abstract::Longitudinal zero-inflated count data are encountered frequently in substance-use research when assessing the effects of covariates and risk factors on outcomes. Often, both the time to a terminal event such as death or dropout and repeated measure count responses are collected for each subject. In this setting, the l...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280216659312
更新日期:2018-04-01 00:00:00