@article{5d83900ec4fc4e6aa969445d1ddcd0a8,
title = "Causal Considerations Can Inform the Interpretation of Surprising Associations in Medical Registries",
abstract = "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.",
keywords = "Bayesian, Zodiac sign, causal inference, frequentist, horoscope, seasonality",
author = "Alberto Carmona-Bayonas and Paula Jim{\'e}nez-Fonseca and Javier Gallego and Pavlos Msaouel",
note = "Funding Information: P.M. has received honoraria for service on a Scientific Advisory Board for Mirati Therapeutics, Bristol Myers Squibb, and Exelixis; consulting for Axiom Healthcare Strategies; non-branded educational programs supported by Exelixis and Pfizer; and research funding for clinical trials from Takeda, Bristol Myers Squibb, Mirati Therapeutics, Gateway for Cancer Research, and UT MD Anderson Cancer Center. All other authors state no conflict of interest related to this study. Funding Information: This is an academic study. The study was supported by the authors themselves. Pavlos Msaouel is supported by a Career Development Award by the American Society of Clinical Oncology, a Research Award by KCCure, the MD Anderson Khalifa Scholar Award, the Andrew Sabin Family Foundation Fellowship, and the MD Anderson Physician-Scientist Award. Various statisticians and clinicians have commented on these results in https://discourse.datamethods.org, providing informal insights into the results. The insights of Sander Greenland greatly contributed to this manuscript, although we alone are responsible for any possible errors. We thank the anonymous reviewer for providing many insightful comments and suggestions. We also thank the IRICOM S.L. team for the support of the website registry. Publisher Copyright: {\textcopyright} 2021 Taylor & Francis Group, LLC.",
year = "2022",
doi = "10.1080/07357907.2021.1999971",
language = "English (US)",
volume = "40",
pages = "1--13",
journal = "Cancer Investigation",
issn = "0735-7907",
publisher = "Informa Healthcare",
number = "1",
}