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HomeEconomyHow does delayed lung cancer diagnosis affect outcomes? – Medical Economist

How does delayed lung cancer diagnosis affect outcomes? – Medical Economist


One would think this question would be a relatively easy one to answer empirically: just compare patients with delays to those without delays to see if there is a difference in health outcomes (e.g., survival). However, this approach is problematic due to three key methodological issues.

  • measurement problemIdeally, one would like to compare patients diagnosed and treated with lung cancer at a particular stage to patients who were not diagnosed and treated. However, underlying lung cancer staging is often not observed during parts of delayed care because a lung cancer diagnosis has not yet been made, or a complete staging may have been made but not yet completed.
  • mediator. A mediator is a variable that sits in the causal path between the exposed variable and the outcome of interest. For example, consider two patients with stage III lung cancer (patients A and B) for which the researchers do not yet know. Consider the situation in which patient B’s tumor has progressed to stage IV at the diagnostic stage while patient A’s tumor is still in stage III. In this case, the researchers considered patient A to be a stage III patient and patient B to be a stage IV patient. Here, a worsening outcome (stage progression) leads to stage progression. The problem is that researchers can compare patient B with other stage IV patients without delay, and patient B may have a better outcome than those with conventional stage IV because patient B’s tumor has just progressed.
  • mixed factors. Confusion occurs when a third variable affects both the exposure variable and the outcome variable. For example, when an interventional pulmonologist looks at a lesion, they may view it as high or low risk. High-risk patients may be diagnosed quickly; low-risk patients may be more prone to delays in diagnosis. Therefore, when comparing outcomes, people with delayed diagnosis appeared to have better outcomes. However, it is actually a third variable (ie, lesion risk) that causes delays and outcomes.

Due in part to the complexity of these methodologies, a systematic literature review Zuniga and the East (2021) Discover some counterintuitive results. They found that longer delay resulted in worse survival in n=8 studies, delay had no statistically significant effect on survival in n=10 studies, and a paradoxical effect that longer delay resulted in n= Better survival for 8 articles, with mixed results (for n = 9, some formations were worse, while others were paradoxical or had no effect. The extent to which we observed so many counterintuitive effects clearly shows that, Mediators and confounders are important empirical issues that have not been adequately addressed in research.

Below are related articles. Articles in bold show shorter delays lead to better survival; italics means shorter delay leads have no effect; underlined means shorter delays lead to worse results, no formatting means shorter delays lead to different Survival outcomes, depending on the group.

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