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. 2025 Jul 9;2(7):388-396.
doi: 10.5588/ijtldopen.25.0142. eCollection 2025 Jul.

Conflation of prediction and causality in the TB literature

Affiliations

Conflation of prediction and causality in the TB literature

M L Romo et al. IJTLD Open. .

Abstract

Background: Observational data can answer both predictive and etiologic research questions; however, the model-building approach and interpretation of results differ based on the research goal (i.e., prediction versus causal inference). Conflation occurs when aspects of the methodology and/or interpretation that are unique to prediction or etiology are combined or confused, potentially leading to biased results and erroneous conclusions.

Methods: We conducted a rapid review using MEDLINE (2018-2023) of a subset of the observational TB literature: cohort studies among people with drug-resistant TB that considered HIV status an exposure of interest and reported on TB treatment outcomes. For each article, we assessed the research question, statistical approach, presentation of results, and discussion and interpretation of results.

Results: Among the 40 articles included, 32 (80%) had evidence of conflation. The most common specific types of conflation were recommending or proposing interventions to modify exposures in a predictive study and having a causal interpretation of predictors, with both types frequently co-occurring.

Conclusion: Conflation between prediction and etiology was common, highlighting the importance of increasing awareness about it and its potential consequences. We propose simple steps on how TB and lung health researchers can avoid conflation, beginning with clearly defining the research question.

Keywords: data interpretation; drug-resistant; epidemiologic methods; risk factors; tuberculosis.

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Conflict of interest statement

Conflicts of interest: none declared.

Figures

Figure 1.
Figure 1.
Visual representation of the assessment of domains for each publication included in the review. The top part of the figure shows how each domain was classified and the overall determination for each of the 40 articles, sorted by classification of the research question. The bottom part of the figure shows a table with summary frequencies.
Figure 2.
Figure 2.
Types of conflation among etiologic and predictive studies included in the review.* *Assessment of types of conflation was limited to articles that could be classified as etiologic or predictive based on their research question (types A and E) and/or statistical approach (types B, C, D, F, G, and H). One article with an unclear research question and conflated statistical approach (#24 in Figure 1) and 5 articles with both an unclear research question and statistical approach (#36-40 in Figure 1) were not included in this assessment. The one article that had both an etiologic and predictive research question and a predictive statistical approach (#23 in Figure 1) was only considered as a predictive study for the assessment of types F, G, and H. Three articles (#20-22 in Figure 1) overlapped as being classified as etiologic or predictive because they had both an etiologic research question and predictive statistical approach.

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