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Collider Bias Is an Insufficient Explanation for the Inverse Obesity Paradox in Prostate Cancer

Stocks, Tanja LU ; Häggström, Christel LU and Fritz, Josef LU orcid (2025) In Cancer Medicine 14(8).
Abstract

Background: Collider bias is often considered a potential explanation when the association between obesity and disease diagnosis differs from that with disease outcome, as seen in the “obesity paradox.” For prostate cancer (PCa), in particular localized PCa, an “inverse” obesity paradox has been observed, where body mass index (BMI) is negatively associated with diagnosis (hazard ratio [HR] ~0.9 per 5-kg/m2 increase), but positively associated with PCa-specific death (HR ~ 1.2). However, collider bias in this context remains unexplored. Methods: We simulated binary disease diagnosis and outcome data, including the typically unmeasured/unknown background variable (U) that could introduce collider bias. We calculated... (More)

Background: Collider bias is often considered a potential explanation when the association between obesity and disease diagnosis differs from that with disease outcome, as seen in the “obesity paradox.” For prostate cancer (PCa), in particular localized PCa, an “inverse” obesity paradox has been observed, where body mass index (BMI) is negatively associated with diagnosis (hazard ratio [HR] ~0.9 per 5-kg/m2 increase), but positively associated with PCa-specific death (HR ~ 1.2). However, collider bias in this context remains unexplored. Methods: We simulated binary disease diagnosis and outcome data, including the typically unmeasured/unknown background variable (U) that could introduce collider bias. We calculated U-unadjusted (biased) and U-adjusted (true) marginal odds ratios (OR) from a case-only analysis, and determined the bias percentage using (Formula presented.). Similar simulations were performed for classical confounding. Results: Across a broad range of plausible parameter values for the PCa context, collider bias did not distort the OR of BMI on PCa death by more than 4%, equivalent to a ± 0.04 distortion in the OR estimate for continuous BMI. In comparison, classical confounding showed a higher potential for distorting BMI and PCa death associations than collider bias. Conclusions: Collider bias alone is unlikely to explain the inverse obesity paradox in (localized) PCa, reinforcing some mechanistic evidence that the observed positive relationship between BMI and PCa death is real, and not a statistical artifact. This finding emphasizes the importance of exploring alternative mechanisms beyond collider bias to better understand the underlying factors driving this paradox.

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author
; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
body mass index, case-only analysis, collider bias, obesity paradox, prostate cancer, simulation
in
Cancer Medicine
volume
14
issue
8
article number
e70871
publisher
John Wiley & Sons Inc.
external identifiers
  • scopus:105003109077
  • pmid:40231651
ISSN
2045-7634
DOI
10.1002/cam4.70871
language
English
LU publication?
yes
id
4edce082-01b9-4cfc-bcc5-beec2d67886a
date added to LUP
2026-01-09 11:52:48
date last changed
2026-03-06 17:32:28
@article{4edce082-01b9-4cfc-bcc5-beec2d67886a,
  abstract     = {{<p>Background: Collider bias is often considered a potential explanation when the association between obesity and disease diagnosis differs from that with disease outcome, as seen in the “obesity paradox.” For prostate cancer (PCa), in particular localized PCa, an “inverse” obesity paradox has been observed, where body mass index (BMI) is negatively associated with diagnosis (hazard ratio [HR] ~0.9 per 5-kg/m<sup>2</sup> increase), but positively associated with PCa-specific death (HR ~ 1.2). However, collider bias in this context remains unexplored. Methods: We simulated binary disease diagnosis and outcome data, including the typically unmeasured/unknown background variable (U) that could introduce collider bias. We calculated U-unadjusted (biased) and U-adjusted (true) marginal odds ratios (OR) from a case-only analysis, and determined the bias percentage using (Formula presented.). Similar simulations were performed for classical confounding. Results: Across a broad range of plausible parameter values for the PCa context, collider bias did not distort the OR of BMI on PCa death by more than 4%, equivalent to a ± 0.04 distortion in the OR estimate for continuous BMI. In comparison, classical confounding showed a higher potential for distorting BMI and PCa death associations than collider bias. Conclusions: Collider bias alone is unlikely to explain the inverse obesity paradox in (localized) PCa, reinforcing some mechanistic evidence that the observed positive relationship between BMI and PCa death is real, and not a statistical artifact. This finding emphasizes the importance of exploring alternative mechanisms beyond collider bias to better understand the underlying factors driving this paradox.</p>}},
  author       = {{Stocks, Tanja and Häggström, Christel and Fritz, Josef}},
  issn         = {{2045-7634}},
  keywords     = {{body mass index; case-only analysis; collider bias; obesity paradox; prostate cancer; simulation}},
  language     = {{eng}},
  number       = {{8}},
  publisher    = {{John Wiley & Sons Inc.}},
  series       = {{Cancer Medicine}},
  title        = {{Collider Bias Is an Insufficient Explanation for the Inverse Obesity Paradox in Prostate Cancer}},
  url          = {{http://dx.doi.org/10.1002/cam4.70871}},
  doi          = {{10.1002/cam4.70871}},
  volume       = {{14}},
  year         = {{2025}},
}