Obesity as a Risk Factor for Prostate Cancer Mortality: A Systematic Review and Dose-Response Meta-Analysis of 280,199 Patients

Rivera-Izquierdo, Mario; Rojas, Javier; Martínez-Ruiz, Virginia; Pérez‐Gómez, Beatriz; Sánchez, María‐José; Khan, Khalid S.; Jiménez-Moleón, José Juan

doi:10.3390/cancers13164169

Cited by 41 publications

(19 citation statements)

References 79 publications

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“…Additionally, a recent meta-analysis, published in JAMA in 2021, showed that obesity (BMI ≥ 30) resulted in a 17% increase in cancer specific mortality compared to non-obese (BMI < 30) people (HR = 1.17 [1.12-1.23]) [34] (Table 1). In addition, several other meta-analyses have shown that obesity is associated with cancer mortality in a wide range of disease sites, such as prostate, breast, pancreas, and liver cancers [56][57][58][59], with many of these studies demonstrating a consistent dose response per increase in BMI [56][57][58][59][60]. Using the NEJM paper as an example, for roughly every 62 people who decrease their BMI from ≥30 to ≤24.9, and for every 130 people who decrease their BMI from 25-29.9 to ≤24.9, one cancer death would be prevented.…”

Section: Obesitymentioning

confidence: 99%

Comparing Lifestyle Modifications and the Magnitude of Their Associated Benefit on Cancer Mortality

Dougherty

Meyer

2023

Nutrients

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Many cancers are associated with poor diet, lack of physical activity, and excess weight. Improving any of these three lifestyle factors would likely reduce cancer deaths. However, modifications to each of these—better nutrition, enhanced activity and fitness, and loss of extra body fat—have different effect sizes on cancer mortality. This review will highlight the relative benefit that each lifestyle change, enacted prior to a diagnosis of cancer, might impart on cancer-related deaths, as well as attempted to quantify the changes required to derive such a benefit. The review relies primarily on epidemiological data, with meta-analyses serving as the backbone for comparisons across interventions and individual studies within the larger meta-analyses providing the data necessary to form more quantitative conclusions. The reader can then use this information to better understand, recommend, and implement behaviors that might ultimately reduce cancer mortality. Of all the interventions, it seems clear that exercise, specifically improving cardiorespiratory fitness, is the best way to decrease the risk of dying from cancer.

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Section: Obesitymentioning

confidence: 99%

Comparing Lifestyle Modifications and the Magnitude of Their Associated Benefit on Cancer Mortality

Dougherty

Meyer

2023

Nutrients

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“…Prostate volume is widely known to be correlated positively with PSA blood levels and to not be a causal factor for PCa. The relationship between BMI (BMI: weight/height 2 ) and PCa risk or aggressiveness has been the subject of contradictory reports across over 1000 publications over the last 10 years [22,23]. Recent results using Mendelian randomization approaches suggest that height increases risk of PCa, whereas BMI decreases this risk [21].…”

Section: Family History Bmi Height and Prostate Volume And Associatio...mentioning

confidence: 99%

Endemic statistical paradoxes in epidemiologic studies distort knowledge on prostate cancer: mitigation and caution of fallacies in prostate cancer causal epidemiological studies

Cussenot

Fromont

Cancel‐Tassin

et al. 2023

Current Opinion in Urology

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Purpose of review Many studies on epidemiology of prostate cancer (PCa) are based on a diagnosis of PCa using PSA (prostate-specific antigen) level. However, biases can distort the interpretation of the results, which in turn limits policy and decision making on public health prevention strategies or clinical guidelines. The main confusion is to interpret the posterior probability of the outcome following the exposure as a change in the prevalence of the disease outcome, whereas this change reflects only the predictive values of the PSA test induced by the exposure of interest. Recent findings Many studies report potential causal factors involved in PCa risk. However, the lack of integration of how physiological changes in PSA values are associated with the exposures being investigated, they explain in part contradictory and controversial results on PCa risk factors in the literature. Summary A strategy to perform case--control studies based on PSA stratification is suggested to avoid misinterpretation related to PSA misclassification. Real data are analysed, and we show that we can exploit the mechanism of selection biases using different modalities of controls recruitment based on biomarker stratification to distinguish real from false causal factors.

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“…11 Notably, obesity has been recognized to have a role in PCa development, progression, and death, although results were inconsistent. [12][13][14][15][16][17] Obese men with PCa are suggested to be at higher risk of a more aggressive tumor phenotype, advanced disease at diagnosis, and poorer treatment outcomes. 12,14 Several mechanisms may be responsible for these higher risk factors, including increased systemic inflammation, hyperinsulinemia, metabolic abnormalities associated with fat mass, and changes in the adipokine profile.…”

Section: Introductionmentioning

confidence: 99%

“…Notably, obesity has been recognized to have a role in PCa development, progression, and death, although results were inconsistent 12–17 . Obese men with PCa are suggested to be at higher risk of a more aggressive tumor phenotype, advanced disease at diagnosis, and poorer treatment outcomes 12,14 .…”

Section: Introductionmentioning

confidence: 99%

A body shape index (ABSI) but not body mass index (BMI) is associated with prostate cancer‐specific mortality: Evidence from the US NHANES database

Ku,

Cheng,

Cheng

2024

The Prostate

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BackgroundProstate cancer (PCa) is a common malignancy in males and obesity may play a role in its development and progression. Associations between visceral obesity measured by a body shape index (ABSI) and PCa mortality have not been thoroughly investigated. This study assessed the associations between ABSI, body mass index (BMI), and long‐term PCa‐specific mortality using a nationally representative US database.MethodsThis population‐based longitudinal study collected data of males aged ≥40 years diagnosed with PCa and who underwent surgery and/or radiation from the National Health and Nutrition Examination Survey database 2001–2010. All included participants were followed through the end of 2019 using the National Center for Health Statistics Linked Mortality File. Associations between PCa‐specific mortality, BMI, and ABSI were determined using Cox proportional hazards regression and receiver operating characteristic (ROC) curve analysis.ResultsData of 294 men (representing 1,393,857 US nationals) were analyzed. After adjusting for confounders, no significant associations were found between BMI (adjusted hazard ratio [aHR] = 1.06, 95% confidence interval [CI]: 0.97–1.16, p = 0.222), continuous ABSI (aHR = 1.29, 95% CI: 0.83–2.02, p = 0.253), or ABSI in category (Q4 vs. Q1–Q3: aHR = 1.52, 95% CI: 0.72–3.24, p = 0.265), and greater risk of PCa‐specific mortality. However, among participants who had been diagnosed within 4 years, the highest ABSI quartile but not in BMI was significantly associated with greater risk for PCa‐specific mortality (Q4 vs. Q1–Q3: aHR = 5.34, 95% CI: 2.26–12.62, p = 0.001). In ROC analysis for this subgroup, the area under the curve of ABSI alone for predicting PCa‐specific mortality was 0.638 (95% CI: 0.448–0.828), reaching 0.729 (95% CI: 0.490–0.968 when combined with other covariates.ConclusionsIn US males with PCa diagnosed within 4 years, high ABSI but not BMI is independently associated with increased PCa‐specific mortality.

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Obesity as a Risk Factor for Prostate Cancer Mortality: A Systematic Review and Dose-Response Meta-Analysis of 280,199 Patients

Cited by 41 publications

References 79 publications

Comparing Lifestyle Modifications and the Magnitude of Their Associated Benefit on Cancer Mortality

Comparing Lifestyle Modifications and the Magnitude of Their Associated Benefit on Cancer Mortality

Endemic statistical paradoxes in epidemiologic studies distort knowledge on prostate cancer: mitigation and caution of fallacies in prostate cancer causal epidemiological studies

A body shape index (ABSI) but not body mass index (BMI) is associated with prostate cancer‐specific mortality: Evidence from the US NHANES database

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