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PubMed · 10564852

[Competing death risks].

J Llorca·M Delgado-Rodríguez
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Abstract

The death of an individual is not a repetitive event, so if a cause of death overtakes another cause in producing death, mortality rates from the overtaken cause decrease. This phenomenon is known as competing risks of death and it must be taken into account in any cause-specific mortality analysis. In this work the competing risks concept is formalized and some historical data are described. The main parametric tools to analyze competing risks are displayed, with a special look at the Gompertz and Weibull functions. Regarding non-parametric models, the Chiang method is shown and its applicability on both dependent and independent causes of death is discussed. Finally, other tools specially useful in clinical epidemiology are enumerated, including Cox regression, Kaplan-Meier and log-rank methods, as well as the interactions between competing risks and misclassification and selection biases.

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BibTeXRIS

J Llorca, M Delgado-Rodríguez. [Competing death risks].. https://doi.org/10.1016/s0213-9111(99)71391-9

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In randomized controlled trials (RCTs), study participants and research personnel are often blinded to minimize biases related to knowing treatment allocation. To determine if blinding was effective, participants may be asked which treatment they believe they received ("treatment guess"). This descriptive review characterized blinding assessment (BA) reporting in pharmacotherapy and neuromodulation neuropathic pain RCTs. Of 288 papers, 36 (12.5%) reported a BA. One paper reported the results of 2 studies, so in total 37 studies with a BA were assessed. Of these, 19 were crossover, 17 parallel, and 1 partial crossover in design. All 37 studies assessed participant blinding, and 10 also assessed investigator blinding. Approximately 27% included an "unsure" answer option for treatment guess, and 38% asked the reason for the guess. There were no clear patterns in BA reporting across time nor based on treatment type. Seventeen trials provided sufficient data to calculate Bang Blinding Index (BI) to determine blinding success. Participants remained blinded (BI = 0 &#xb1; 0.2) in 10/17 placebo and 10/17 treatment arms, 6 placebo and 5 treatment arms had a BI > 0.2 suggesting possible unblinding, whereas 1 placebo and 2 treatment arms had a BI < -0.2 suggesting misinformed guessing. Overall, we found that BAs are done in a minority of published neuropathic pain trials and with variable methodology. Given the importance of minimizing risk of bias because of treatment unblinding, future studies should consider including BAs, and further consensus building is necessary to determine if and how BAs should be conducted and interpreted in analgesic clinical trials.

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