Article

The Hazards of Hazard Ratios

Department of Epidemiology, Harvard School of Public Health, and the Harvard-MIT Division of Health Sciences and Technology, Boston, MA 02115, USA.
Epidemiology (Cambridge, Mass.) (Impact Factor: 6.2). 01/2010; 21(1):13-5. DOI: 10.1097/EDE.0b013e3181c1ea43
Source: PubMed

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    • "Even more importantly, the cohort method fails to acknowledge that the probability of infection of an individual depends on the infection prevalence in the population, i.e. on the infection status of others. With a dynamic modelling approach, instead, the problem of constant hazard ratios (Hernán, 2010) can be circumvented, as can limitations of the indirect cohort method (Moberley and Andrews, 2014) for purposes of vaccine efficacy estimation. Furthermore, data can be interpreted relaxing the stationarity requirement and accounting for pathogen type replacement. "
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    ABSTRACT: The efficacy of vaccines is typically estimated prior to implementation, on the basis of randomized controlled trials. This does not preclude, however, subsequent assessment post-licensure, while mass-immunization and nonlinear transmission feedbacks are in place. In this paper we show how cross-sectional prevalence data post-vaccination can be interpreted in terms of pathogen transmission processes and vaccine parameters, using a dynamic epidemiological model. We advocate the use of such frameworks for model-based vaccine evaluation in the field, fitting trajectories of cross-sectional prevalence of pathogen strains before and after intervention. Using SI and SIS models, we illustrate how prevalence ratios in vaccinated and non-vaccinated hosts depend on true vaccine efficacy, the absolute and relative strength of competition between target and non-target strains, the time post follow-up and transmission intensity. We argue that a mechanistic approach should be added to vaccine efficacy estimation against multi-type pathogens, because it naturally accounts for inter-strain competition and indirect effects, leading to a robust measure of individual protection per contact. Our study calls for systematic attention to epidemiological feedbacks when interpreting population level impact. At a broader level, our parameter estimation procedure also provides a promising proof of principle for a generalizable framework to infer vaccine efficacy post-licensure.
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    • "This study also reported only the weighted average of the period-specific scores, despite changes in the HRs over time. To overcome this limitation , sensitivity analyses calculating a series of average HRs for several durations are suggested (Hernán, 2010). "
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    ABSTRACT: This study aimed to examine the influences of social, attitudinal, and intrapersonal factors at hree levels on tobacco use among female adolescents in South Korea using longitudinal national data. The study analyzed data from the Korean Youth Panel Study, with a study population consisting of middle-school second-graders (N = 1,594). Using time dependent Cox regression, our analyses yielded the following main findings: the TTI model was verified to provide a theoretical framework for smoking among Korean female adolescents. All of the social factors at the three levels, including parental supervision, attachment to friends, and having smoking friends, were found to influence tobacco use among Korean female adolescents. Stigma on the distal level and attitude toward smoking on the proximal level were significant attitudinal factors. Among intrapersonal factors, self-control on the distal level and stress on the proximal level were found to be significant. The study findings suggest that including parental education and promoting attachment to non-smoking friends, as well as enhancing sound relationships with them, would provide an effective strategy for the prevention and cessation of smoking. Prevention and cession should include strategies that alleviate stigma and stress, and improve negative attitude toward smoking and the level of self-control.
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    • "Hazards as a metric of disease occurrence along with semi-parametric methods have provided a means to understanding many diseases. However, hazards have limitations [15] that become compounded in competing-risk problems: CSHs and SUBHs are decoupled; CSHs lack specificity as they are strongly influenced by the competing event; SUBHs are specific but they are intrinsically tethered because their cumulative incidences must add up to one; both CSHs and SUBHs combine frequency and timing of events, making it difficult to identify exposures that modify only the timing of an event but not the frequency. "
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    ABSTRACT: A competing risk is an event (for example, death in the ICU) that hinders the occurrence of an event of interest (for example, nosocomial infection in the ICU) and it is a common issue in many critical care studies. Not accounting for a competing event may affect how results related to a primary event of interest are interpreted. In the previous issue of Critical Care, Wolkewitz and colleagues extended traditional models for competing risks to include random effects as a means to quantify heterogeneity among ICUs. Reported results from their analyses based on cause-specific hazards and on sub-hazards of the cumulative incidence function were indicative of lack of proportionality of these hazards over time. Here, we argue that proportionality of hazards can be problematic in competing-risk problems and analyses must consider time by covariate interactions as a default. Moreover, since hazards in competing risks make it difficult to disentangle the effects of frequency and timing of the competing events, their interpretation can be murky. Use of mixtures of flexible and succinct parametric time-to-event models for competing risks permits disentanglement of the frequency and timing at the price of requiring stronger data and a higher number of parameters. We used data from a clinical trial on fluid management strategies for patients with acute respiratory distress syndrome to support our recommendations.
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