The competing risk of death and selective survival cannot fully explain the inverse cancer‐dementia association

Abstract

Introduction: We evaluated whether competing risk of death or selective survival could explain the reported inverse association between cancer history and dementia incidence (incidence rate ratio [IRR] ≈ 0.62-0.85). Methods: A multistate simulation model of a cancer-and dementia-free cohort of 65year-olds was parameterized with real-world data (cancer and dementia incidence, mortality), assuming no effect of cancer on dementia (true IRR = 1.00). To introduce competing risk of death, cancer history increased mortality. To introduce selective survival, we included a factor (prevalence ranging from 10% to 50%) that reduced cancer mortality and dementia incidence (IRRs ranged from 0.30 to 0.90). We calculated IRRs for cancer history on dementia incidence in the simulated cohorts. Results: Competing risk of death yielded unbiased cancer-dementia IRRs. With selective survival, bias was small (IRRs = 0.89 to 0.99), even under extreme scenarios. Discussion: The bias induced by selective survival in simulations was too small to explain the observed inverse cancer-dementia link, suggesting other mechanisms drive this association.

Investigating the association between cancer and the risk of dementia: Results from the Memento cohort

“…This observed protective effect of cancer against dementia is largely in line with previous research 1,4,10,22,23 . For example, a recent prospective cohort study found that individuals diagnosed with cancer during follow‐up had a 3‐fold reduction in risk of AD 4 .…”

“…This observed protective effect of cancer against dementia is largely in line with previous research. 1 , 4 , 10 , 22 , 23 For example, a recent prospective cohort study found that individuals diagnosed with cancer during follow‐up had a 3‐fold reduction in risk of AD. 4 Recent meta‐analyses similarly reflect a protective effect in extant literature, estimating an overall pooled effect size associated with a 15% to 37% decrease in risk of AD.…”

“…Statistical methodology exists to tackle many of the potential biases, although most previous research has been limited, for example, to the use of standard survival models, which ignores the potential role of competing events, or to simulation studies 10 . Illness‐death models (IDMs), similar to competing risk analyses, can help to account for survivor bias by accurately considering differential mortality while concurrently modeling risk of disease progression (ie, competing risks).…”

“…Statistical methodology exists to tackle many of the potential biases, although most previous research has been limited, for example, to the use of standard survival models, which ignores the potential role of competing events, or to simulation studies. 10 Illness‐death models (IDMs), similar to competing risk analyses, can help to account for survivor bias by accurately considering differential mortality while concurrently modeling risk of disease progression (ie, competing risks). This study investigates the effect of incident cancer on dementia risk in a large clinical cohort of persons with either mild cognitive impairment (MCI) or isolated cognitive complaints, with the hypothesis that processes related to cancer and dementia are inversely related.…”

Choosing questions before methods in dementia research with competing events and causal goals

“…This may explain counterintuitive results, where exposures that are known to be harmful for mortality risk, such as smoking [4,5] or history of cancer [6], sometimes seem protective for the risk of dementia. Authors have attempted to make sense of these counterintuitive results by naming biases such as "competing risk bias" or "survival bias" [7,8]. However, the bias associated with a particular analytic method cannot be defined or assessed if the causal question is not explicitly specified.…”