Causal relationships between body composition and hematological malignancies: a multivariable mendelian randomization

Shan Liu1, Yaobin Lin2, Zhihong Wang3,4

  • 1Department of Hematology-Oncology, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fujian Children's Hospital, Fuzhou, Fujian, China.

PubMed
Summary

Body composition influences cancer risk. Specific body fat and mass measurements are linked to increased leukemia and lymphoma risk, while height and waist-to-hip ratio are independent risk factors for lymphoma and multiple myeloma, respectively.

Related Concept Videos

Hematopoiesis01:21

Hematopoiesis

The process of blood cell formation is called hematopoiesis. Hematopoiesis starts early during development, on the seventh day of embryogenesis. This phase of hematopoiesis is called the primitive wave, wherein the extraembryonic yolk sac allows the production of erythroid cells and endothelial cells from a common precursor called hemangioblast. The erythroid cells provide oxygen to support the growth of the rapidly dividing embryo. Hemangioblasts later develop into hematopoietic stem cells or...
5.0K
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
23
Cancer Survival Analysis01:21

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
319
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
117