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Criteria for Causality: Bradford Hill Criteria - II01:28

Criteria for Causality: Bradford Hill Criteria - II

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The Bradford Hill criteria serve as guidelines for establishing causative links in epidemiological research. Beyond Strength, Consistency, Specificity, and Temporality, key criteria also include Biological Gradient, Plausibility, Coherence, Experiment, and Analogy. These principles assist scientists in assessing the likelihood of causation in complex biological contexts. Below is a summary of these concepts:
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Randomized Experiments01:13

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The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
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Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
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Causality in Epidemiology01:21

Causality in Epidemiology

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Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
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Hazard Ratio01:12

Hazard Ratio

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The hazard ratio (HR) is a widely used measure in clinical trials to compare the risk of events, such as death or disease recurrence, between two groups over time. It reflects the ratio of hazard rates—the instantaneous risk of the event occurring—between a treatment group and a control group. This measure provides valuable insights into the relative effectiveness of a treatment by assessing how the risk of an event differs between the two groups.
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Odds Ratio01:09

Odds Ratio

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The odds ratio (OR) is a statistical measure used extensively in epidemiology and research to quantify the strength of association between exposure and outcome across different groups. Unlike relative risk, which compares the probabilities of an event occurring, the odds ratio compares the odds of an event occurring in the exposed group to the odds of it occurring in the unexposed group. The odds, in this context, are calculated as the probability of the event happening divided by the...
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Related Experiment Video

Updated: May 8, 2025

Changes in Mammary Gland Morphology and Breast Cancer Risk in Rats
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Causal Effects of Breast Cancer Risk Factors across Hormone Receptor Breast Cancer Subtypes: A Two-Sample Mendelian

Renée M G Verdiesen1, Mehrnoosh Shokouhi1, Stephen Burgess2,3

  • 1Division of Molecular Pathology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam, the Netherlands.

Cancer Epidemiology, Biomarkers & Prevention : a Publication of the American Association for Cancer Research, Cosponsored by the American Society of Preventive Oncology
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Summary

Established breast cancer risk factors like height and body mass index (BMI) show causal effects across subtypes. However, other factors vary in their impact on different breast cancer types, highlighting subtype-specific prevention strategies.

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Area of Science:

  • Genetics and Epidemiology
  • Oncology
  • Public Health

Background:

  • Breast cancer comprises diverse subtypes with distinct biological behaviors and clinical outcomes.
  • The differential impact of established risk factors on these subtypes remains incompletely understood.
  • Clarifying these associations is crucial for targeted prevention and risk stratification.

Purpose of the Study:

  • To investigate and compare the causal effects of key breast cancer risk factors across five major hormone receptor subtypes.
  • To determine if risk factors like height, BMI, and lifestyle choices have a uniform or variable influence on different breast cancer subtypes.

Main Methods:

  • Utilized a two-sample Mendelian randomization approach with genetic instrumental variables from large genome-wide association studies.
  • Analyzed publicly available data from the Breast Cancer Association Consortium, including luminal A-like, luminal B-/HER2-negative-like, luminal B-like, HER2-enriched, and triple-negative subtypes.
  • Employed multiple Mendelian randomization methods to assess causal evidence for risk factor-subtype associations.

Main Results:

  • Increased height and decreased body mass index (BMI) were identified as probable causal risk factors for all five breast cancer subtypes.
  • The strength of causal effects for age at menopause and breast density varied significantly across subtypes, with null findings for triple-negative tumors.
  • Regular smoking showed no evidence of a causal effect on any of the studied breast cancer subtypes.

Conclusions:

  • Established breast cancer risk factors exhibit differential causal effects across hormone receptor subtypes.
  • These findings underscore the importance of considering subtype-specific etiologies in breast cancer research and prevention.
  • The results can inform primary prevention strategies and improve risk stratification for diverse breast cancer populations.