Analysis of time-to-event for observational studies: Guidance to the use of intensity models

This paper provides guidance for researchers with some mathematical background on the conduct of time-to-event analysis in observational studies based on intensity (hazard) models. Discussions of basic concepts like time axis, event definition and censoring are given. Hazard models are introduced, with special emphasis on the Cox proportional hazards regression model. We provide check lists that may be useful both when fitting the model and assessing its goodness of fit and when interpreting the results. Special attention is paid to how to avoid problems with immortal time bias by introducing time-dependent covariates. We discuss prediction based on hazard models and difficulties when attempting to draw proper causal conclusions from such models. Finally, we present a series of examples where the methods and check lists are exemplified. Computational details and implementation using the freely available R software are documented in Supplementary Material. The paper was prepared as part of the STRATOS initiative.Comment: 28 pages, 12 figures. For associated Supplementary material, see http://publicifsv.sund.ku.dk/~pka/STRATOSTG8

Prenatal exposure to maternal cigarette smoking, amygdala volume, and fat intake in adolescence

Context : Prenatal exposure to maternal cigarette smoking is a well-established risk factor for obesity, but the underlying mechanisms are not known. Preference for fatty foods, regulated in part by the brain reward system, may contribute to the development of obesity. Objective : To examine whether prenatal exposure to maternal cigarette smoking is associated with enhanced fat intake and risk for obesity, and whether these associations may be related to subtle structural variations in brain regions involved in reward processing. Design : Cross-sectional study of a population-based cohort. Setting : The Saguenay Youth Study, Quebec, Canada. Participants : A total of 378 adolescents (aged 13 to 19 years; Tanner stage 4 and 5 of sexual maturation), half of whom were exposed prenatally to maternal cigarette smoking (mean [SD], 11.1 [6.8] cigarettes/d). Main Outcome Measures : Fat intake was assessed with a 24-hour food recall (percentage of energy intake consumed as fat). Body adiposity was measured with anthropometry and multifrequency bioimpedance. Volumes of key brain structures involved in reward processing, namely the amygdala, nucleus accumbens, and orbitofrontal cortex, were measured with magnetic resonance imaging. Results : Exposed vs nonexposed subjects exhibited a higher total body fat (by approximately 1.7 kg; P = .009) and fat intake (by 2.7%; P = .001). They also exhibited a lower volume of the amygdala (by 95 mm3; P < .001) but not of the other 2 brain structures. Consistent with its possible role in limiting fat intake, amygdala volume correlated inversely with fat intake (r = −0.15; P = .006). Conclusions : Prenatal exposure to maternal cigarette smoking may promote obesity by enhancing dietary preference for fat, and this effect may be mediated in part through subtle structural variations in the amygdala

Comparison of nested case-control and survival analysis methodologies for analysis of time-dependent exposure

BACKGROUND: Epidemiological studies of exposures that vary with time require an additional level of methodological complexity to account for the time-dependence of exposure. This study compares a nested case-control approach for the study of time-dependent exposure with cohort analysis using Cox regression including time-dependent covariates. METHODS: A cohort of 1340 subjects with four fixed and seven time-dependent covariates was used for this study. Nested case-control analyses were repeated 100 times for each of 4, 8, 16, 32, and 64 controls per case, and point estimates were compared to those obtained using Cox regression on the full cohort. Computational efficiencies were evaluated by comparing central processing unit times required for analysis of the cohort at sizes 1, 2, 4, 8, 16, and 32 times its initial size. RESULTS: Nested case-control analyses yielded results that were similar to results of Cox regression on the full cohort. Cox regression was found to be 125 times slower than the nested case-control approach (using four controls per case). CONCLUSIONS: The nested case-control approach is a useful alternative for cohort analysis when studying time-dependent exposures. Its superior computational efficiency may be particularly useful when studying rare outcomes in databases, where the ability to analyze larger sample sizes can improve the power of the study

A review of spline function procedures in R

Background: With progress on both the theoretical and the computational fronts the use of spline modelling has become an established tool in statistical regression analysis. An important issue in spline modelling is the availability of user friendly, well documented software packages. Following the idea of the STRengthening Analytical Thinking for Observational Studies initiative to provide users with guidance documents on the application of statistical methods in observational research, the aim of this article is to provide an overview of the most widely used spline-based techniques and their implementation in R. Methods: In this work, we focus on the R Language for Statistical Computing which has become a hugely popular statistics software. We identified a set of packages that include functions for spline modelling within a regression framework. Using simulated and real data we provide an introduction to spline modelling and an overview of the most popular spline functions. Results: We present a series of simple scenarios of univariate data, where different basis functions are used to identify the correct functional form of an independent variable. Even in simple data, using routines from different packages would lead to different results. Conclusions: This work illustrate challenges that an analyst faces when working with data. Most differences can be attributed to the choice of hyper-parameters rather than the basis used. In fact an experienced user will know how to obtain a reasonable outcome, regardless of the type of spline used. However, many analysts do not have sufficient knowledge to use these powerful tools adequately and will need more guidance

Group-based vs individual pelvic floor muscle training to treat urinary incontinence in older women : a randomized clinical trial

Importance Urinary incontinence is one of the most prevalent health concerns experienced by older women (aged ≥60 years). Individual pelvic floor muscle training (PFMT) is the recommended first-line treatment for stress or mixed urinary incontinence in women, but human and financial resources limit its delivery. Whether group-based PFMT performs as well as individual PFMT in this population remains unclear. Objective To assess the efficacy of group-based PFMT relative to individual PFMT for urinary incontinence in older women. Design, Setting, and Participants The Group Rehabilitation or Individual Physiotherapy (GROUP) study is a single-blind, randomized, noninferiority trial conducted in 2 Canadian research centers, from July 1, 2012, to June 2, 2018. A total of 362 community-dwelling women aged 60 years or older with symptoms of stress or mixed urinary incontinence were enrolled. Interventions After an individual session conducted to learn how to contract pelvic floor muscles, participants completed 12-week PFMT as part of a group of 8 women (n = 178) or in individual sessions (n = 184). Main Outcomes and Measures The primary outcome measure was the percentage reduction in urinary incontinence episodes at 1 year, as reported in a 7-day bladder diary and relative to pretreatment baseline. Secondary outcomes included lower urinary tract–related signs, symptoms, and quality of life immediately following treatment and at 1 year. Per-protocol analysis was used. Results Among 362 women who were randomized (mean [SD] age, 67.9 [5.8] years), 319 women (88%) completed the 1-year follow-up and were included in the per-protocol analysis. Median percentage reduction in urinary incontinence episodes was 70% (95% CI, 44%-89%) in individual PFMT compared with 74% (95% CI, 46%-86%) in group-based PFMT. The upper boundary of the 95% CI for the difference in the percentage reduction in urinary incontinence episodes at 1 year was lower than the prespecified margin for noninferiority of 10% (difference, 4%; 95% CI, −10% to 7%; P = .58), confirming noninferiority. Individual PFMT and group-based PFMT had similar effectiveness for all secondary outcomes at 1 year. Adverse events were minor and uncommon. Conclusions and Relevance Results of the GROUP study suggest that group-based PFMT is not inferior to the recommended individual PFMT for the treatment of stress and mixed urinary incontinence in older women. Widespread use in clinical practice may help increase continence-care affordability and treatment availability

Immediate and delayed impact of oral glucocorticoid therapy on risk of serious infection in older patients with rheumatoid arthritis: a nested case–control analysis

Objectives: To explore the relationship of serious infection risk with current and prior oral glucocorticoid (GC) therapy in elderly patients with rheumatoid arthritis (RA). Methods: A case-control analysis matched 1947 serious infection cases to five controls, selected from 16207 RA patients aged ≥65 between 1985-2003 in Quebec, Canada. Adjusted odds ratios for infection associated with different GC patterns were estimated using conventional models and a weighted cumulative dose (WCD) model. Results: The WCD model predicted risks better than conventional models. Current and recent GC doses had highest impact on current risk. Doses taken up to 2.5 years ago were also associated with increased risk, albeit to a lesser extent. A current user of 5mg prednisolone had a 30%, 46% or 100% increased risk of serious infection when used continuously for the last 3 months, 6 months or 3 years, respectively, compared to a non-user. The risk associated with 5mg prednisolone taken for the last 3 years was similar to that associated with 30mg taken for the last month. Discontinuing a two-year course of 10mg prednisolone six months ago halved the risk compared to ongoing use. Conclusions: GC therapy is associated with infection risk in older patients with RA. The WCD model provided more accurate risk estimates than conventional models. Current and recent doses have greatest impact on infection risk, but the cumulative impact of doses taken in the last 2-3 years still affects risk. Knowing how risk depends on pattern of GC use will contribute to an improved benefit/harm assessment

Methods for prospectively incorporating gender into health sciences research

©. This manuscript version is made available under the CC BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ This document is the Submitted, Accepted, Published, version of a Published Work that appeared in final form in Journal of Clinical Epidemiology. To access the final edited and published work see https://doi.org/10.1016/j.jclinepi.2020.08.018Numerous studies have demonstrated that sex (a biological variable) and gender (a psychosocial construct) impact health and have dis-cussed the mechanisms that may explain these relationships. Funding agencies have called for all health researchers to incorporate sex andgender into their studies; however, the way forward has been unclear to many, particularly due to the varied definition of gender. We arguethat just as there is no standardized definition of gender, there can be no standardized measurement thereof. However, numerous measurablegender-related variables may influence individual or population-level health through various pathways. The initial question should guide theselection of specific gender-related variables based on their relevance to the study, to prospectively incorporate gender into research. Weoutline various methods to provide clarification on how to incorporate gender into the design of prospective clinical and epidemiologicalstudies as well as methods for statistical analysi

Using linked administrative, clinical and primary data to explore the impact of and factors associated with non-adherence to in-hospital medication changes in 30-days post hospital discharge

Introduction Identifying strategies to prevent hospital readmissions remains elusive since the reasons for returning to hospital can include a number of interlinked patient, health provider and system level factors. The impact of patient medications are of significant interest since a large proportion of re-admissions are related to adverse drug events. Objectives and Approach The objective was to determine which factors are associated with non-adherence to in-hospital medications and the impact of non-adherence on re-hospitalization, emergency department visits and death in the 30-days post discharge for patients admitted at two tertiary care academic hospitals in Montreal, Quebec between October 2014 and May 2016. Non-adherence to in-hospital changes was measured by comparing patient discharge prescriptions (patient chart) to medications filled in community 30-days post-discharge (dispensing data) and included i) community medications stopped in-hospital and filled post-discharge, ii) community medications modified in-hospital but not filled at the modified daily-dose, and iii) new medications not filled post-discharge. Results Among 2,895 included patients, mean age was 70 (SD 15) and 58% were males. A median of 4 in-hospital medication changes were made (IQR:3-6) and 54% of patients were non-adherent to at least one change. Multivariable Poisson models suggested that the most important factor associated with the number of new medications not filled post discharge was out of pocket cost; for each additional $10 increase in costs there was a 20% increase in the number of new medications not filled. Multivariable time-varying Cox models suggested that in patients who filled medications post-discharge, selective non-adherence to new and discontinued medications reduced the risk adverse health outcomes in 30-days, while not filling any medications post discharge more than doubled the risk of an adverse event in 30-days. Conclusion/Implications Not only did the majority of patients not follow all medication changes that were made during hospitalization, the extent to which this occurred significantly impacted the risk of hospital re-admissions and ED visits. Policy and patient level interventions should be developed specifically targeting barriers for adherence to medication changes