Haseeb Jafri1, Alawi A Alsheikh-Ali, Richard H Karas. 1. Molecular Cardiology Research Institute, Department of Medicine, Tufts Medical Center and Tufts University School of Medicine, Boston, Massachusetts 02111, USA.
Abstract
OBJECTIVES: We sought to examine the relationship between high-density lipoprotein cholesterol (HDL-C) levels and the risk of the development of cancer in large randomized controlled trials (RCTs) of lipid-altering interventions. BACKGROUND: Epidemiologic data demonstrate an inverse relationship between serum total cholesterol levels and incident cancer. We recently reported that lower levels of low-density lipoprotein cholesterol are associated with a significantly higher risk of incident cancer in a meta-analysis of large RCTs of statin therapy. However, little is known about the relationship between HDL-C levels and cancer risk. METHODS: A systematic MEDLINE search identified lipid intervention RCTs with >or=1,000 person-years of follow-up, providing baseline HDL-C levels and rates of incident cancer. Using random-effects meta-regressions, we evaluated the relationship between baseline HDL-C and incident cancer in each RCT arm. RESULTS: A total of 24 eligible RCTs were identified (28 pharmacologic intervention arms and 23 control arms), with 625,477 person-years of follow-up and 8,185 incident cancers. There was a significant inverse association between baseline HDL-C levels and the rate of incident cancer (p = 0.018). The inverse association persisted after adjusting for baseline low-density lipoprotein cholesterol, age, body mass index (BMI), diabetes, sex, and smoking status, such that for every 10-mg/dl increment in HDL-C, there was a 36% (95% confidence interval: 24% to 47%) relatively lower rate of the development of cancer (p < 0.001). CONCLUSIONS: There is a significant inverse association between HDL-C and the risk of incident cancer that is independent of LDL-C, age, BMI, diabetes, sex, and smoking. Copyright (c) 2010 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.
OBJECTIVES: We sought to examine the relationship between high-density lipoprotein cholesterol (HDL-C) levels and the risk of the development of cancer in large randomized controlled trials (RCTs) of lipid-altering interventions. BACKGROUND: Epidemiologic data demonstrate an inverse relationship between serum total cholesterol levels and incident cancer. We recently reported that lower levels of low-density lipoprotein cholesterol are associated with a significantly higher risk of incident cancer in a meta-analysis of large RCTs of statin therapy. However, little is known about the relationship between HDL-C levels and cancer risk. METHODS: A systematic MEDLINE search identified lipid intervention RCTs with >or=1,000 person-years of follow-up, providing baseline HDL-C levels and rates of incident cancer. Using random-effects meta-regressions, we evaluated the relationship between baseline HDL-C and incident cancer in each RCT arm. RESULTS: A total of 24 eligible RCTs were identified (28 pharmacologic intervention arms and 23 control arms), with 625,477 person-years of follow-up and 8,185 incident cancers. There was a significant inverse association between baseline HDL-C levels and the rate of incident cancer (p = 0.018). The inverse association persisted after adjusting for baseline low-density lipoprotein cholesterol, age, body mass index (BMI), diabetes, sex, and smoking status, such that for every 10-mg/dl increment in HDL-C, there was a 36% (95% confidence interval: 24% to 47%) relatively lower rate of the development of cancer (p < 0.001). CONCLUSIONS: There is a significant inverse association between HDL-C and the risk of incident cancer that is independent of LDL-C, age, BMI, diabetes, sex, and smoking. Copyright (c) 2010 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.
Authors: C Alicia Traughber; Emmanuel Opoku; Gregory Brubaker; Jennifer Major; Hanxu Lu; Shuhui Wang Lorkowski; Chase Neumann; Aimalie Hardaway; Yoon-Mi Chung; Kailash Gulshan; Nima Sharifi; J Mark Brown; Jonathan D Smith Journal: J Biol Chem Date: 2020-05-01 Impact factor: 5.157
Authors: Peter Penson; D Leann Long; George Howard; Virginia J Howard; Steven R Jones; Seth S Martin; Dimitri P Mikhailidis; Paul Muntner; Manfredi Rizzo; Daniel J Rader; Monika M Safford; Amirhossein Sahebkar; Peter P Toth; Maciej Banach Journal: Cardiovasc Res Date: 2019-01-01 Impact factor: 10.787
Authors: Lorenzo Scappaticcio; Maria Ida Maiorino; Giuseppe Bellastella; Dario Giugliano; Katherine Esposito Journal: Endocrine Date: 2016-12-31 Impact factor: 3.633
Authors: Michele L Mietus-Snyder; Mark K Shigenaga; Jung H Suh; Swapna V Shenvi; Ashutosh Lal; Tara McHugh; Don Olson; Joshua Lilienstein; Ronald M Krauss; Ginny Gildengoren; Joyce C McCann; Bruce N Ames Journal: FASEB J Date: 2012-05-01 Impact factor: 5.191
Authors: Yukiko Morimoto; Shannon M Conroy; Nicholas J Ollberding; Susanne M Henning; Adrian A Franke; Lynne R Wilkens; Marc T Goodman; Brenda Y Hernandez; Loïc Le Marchand; Brian E Henderson; Laurence N Kolonel; Gertraud Maskarinec Journal: Cancer Causes Control Date: 2012-08-21 Impact factor: 2.506
Authors: Maryam Zamanian-Daryoush; Daniel Lindner; Thomas C Tallant; Zeneng Wang; Jennifer Buffa; Elizabeth Klipfell; Yvonne Parker; Denise Hatala; Patricia Parsons-Wingerter; Pat Rayman; Mohamed Sharif S Yusufishaq; Edward A Fisher; Jonathan D Smith; Jim Finke; Joseph A DiDonato; Stanley L Hazen Journal: J Biol Chem Date: 2013-05-17 Impact factor: 5.157
Authors: Sankar D Navaneethan; Jesse D Schold; Carl P Walther; Susana Arrigain; Stacey E Jolly; Salim S Virani; Wolfgang C Winkelmayer; Joseph V Nally Journal: J Clin Lipidol Date: 2018-03-30 Impact factor: 4.766