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Causal Considerations Can Inform the Interpretation of Surprising Associations in Medical Registries.

Alberto Carmona-BayonasPaula Jiménez-FonsecaJavier GallegoPavlos Msaouel
Published in: Cancer investigation (2021)
An exploratory analysis of registry data from 2437 patients with advanced gastric cancer revealed a surprising association between astrological birth signs and overall survival (OS) with p = 0.01. After dichotomizing or changing the reference sign, p-values <0.05 were observed for several birth signs following adjustments for multiple comparisons. Bayesian models with moderately skeptical priors still pointed to these associations. A more plausible causal model, justified by contextual knowledge, revealed that these associations arose from the astrological sign association with seasonality. This case study illustrates how causal considerations can guide analyses through what would otherwise be a hopeless maze of statistical possibilities.
Keyphrases
  • healthcare
  • single cell
  • gestational age
  • neoadjuvant chemotherapy
  • electronic health record
  • big data
  • pregnant women
  • artificial intelligence
  • deep learning
  • preterm birth