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Systematic Review and Meta-Analysis of the Associations Between Body Mass Index, Prostate Cancer, Advanced Prostate Cancer and Prostate Specific Antigen

Sean Harrison1, Kate Tilling1, Emma L Turner1, Richard M. Martin1, Richard M. Martin2, Rosie J. Lennon3, J. Athene Lane1, J. Athene Lane2, Jenny L Donovan1, Jenny L Donovan4, Freddie C. Hamdy5, David E. Neal6, David E. Neal5, J.L.H. Ruud Bosch7, Hayley E Jones1 •
University of Bristol1, University Hospitals Bristol NHS Foundation Trust2, University of York3, National Institute for Health Research4, University of Oxford5, University of Cambridge6, University Medical Center Utrecht7
09 Sep 2019-medRxiv (Cold Spring Harbor Laboratory Press)-pp 19005421
TL;DR: There is little or no evidence of a association between BMI and risk of prostate cancer or advanced prostate cancer, and strong evidence of an inverse and non-linear association between body-mass index and PSA.
Abstract: Purpose The relationship between body-mass index (BMI) and prostate cancer remains unclear. However, there is an inverse association between BMI and prostate-specific antigen (PSA), used for prostate cancer screening. We conducted this review to estimate the associations between BMI and (1) prostate cancer, (2) advanced prostate cancer, and (3) PSA. Methods We searched PubMed and Embase for studies until 02 October 2017 and obtained individual participant data from four studies. In total, 78 studies were identified for the association between BMI and prostate cancer, 21 for BMI and advanced prostate cancer, and 35 for BMI and PSA. We performed random-effects meta-analysis of linear associations of log PSA and prostate cancer with BMI and, to examine potential non-linearity, of associations between categories of BMI and each outcome. Results In the meta-analyses with continuous BMI, a 5 kg/m2 increase in BMI was associated with a percentage change in PSA of −5.88% (95% CI −6.87% to −4.87%). Using BMI categories, compared to normal weight men the PSA levels of overweight men were 3.43% lower (95% CI −5.57% to −1.23%), and obese men were 12.9% lower (95% CI −15.2% to −10.7%). Prostate cancer and advanced prostate cancer analyses showed little or no evidence associations. Conclusion There is little or no evidence of an association between BMI and risk of prostate cancer or advanced prostate cancer, and strong evidence of an inverse and non-linear association between BMI and PSA. The association between BMI and prostate cancer is likely biased if missed diagnoses are not considered.

Summary (5 min read)

Jump to: [Background] – [Eligibility criteria] – [Data sources] – [Data extraction] – [Risk of bias assessment] – [Combining data] – [Albatross plots] – [Results] – [Continuous BMI] – [Categorical BMI] – [Overall prostate cancer] – [Advanced prostate cancer] – [PSA] – [Strengths and Limitations] and [Conclusion]

Background

  • Prostate cancer is the second commonest male cancer worldwide, [1] and the most commonly diagnosed cancer in men in the UK, with an estimated 47,151 diagnoses in 2015 [2].
  • Generally, most prostate cancers are slow growing, but can metastasize to the bones, lungs, and brain.
  • The authors therefore sought to perform an updated review of the literature, including more studies, and additionally examining non-linear associations.
  • A negative association between BMI and PSA could also induce a spurious positive association between BMI and advanced prostate cancer, as obese men may be diagnosed later, due to their lower PSA levels.
  • The authors objectives were to i) precisely quantify the (assumed linear) associations between BMI and prostate cancer, advanced prostate cancer, and PSA; ii) update previous meta-analyses using all relevant evidence, including case–control studies; and iii) explore potential non-linearity in these associations.

Eligibility criteria

  • The authors performed a systematic review in which they included original articles published in peer reviewed journals that measured an association between BMI and total prostate cancer incidence and/or advanced prostate cancer; and studies that measured an association between BMI and PSA, including supplements and meeting abstracts; human randomized controlled trials (RCTs), case–control, cohort, crosssectional, and non-randomized experimental studies.
  • If the abstract did not specifically mention BMI but mentioned height or weight, the authors acquired the full text to determine if BMI was calculable from data included in the publication.
  • The authors determined the effect estimate to be for advanced prostate cancer if the individual studies labeled the effect as “advanced” or “aggressive,” or if the effect was for locally advanced, extra-prostatic, nodular or metastatic prostate cancer.
  • Advanced prostate cancer represents clinically meaningful cancer, with lower survival rates than nonadvanced cancers.

Data sources

  • The authors searched Medline and Embase databases up to 02 October 2017 for studies in humans associating BMI with either prostate cancer or PSA.
  • The search query was as follows (each term as a text word search): (BMI or body mass index or obese or obesity or body weight or body size or adiposity) AND (prostate cancer or prostate neoplasm or PSA or prostate-specific antigen) NOT psoriatic arthritis.
  • Psoriatic arthritis was excluded as its initialism is also PSA.
  • The authors also reviewed the reference lists of previous meta-analyses for further studies for inclusion [6, 8, 14].
  • Duplicate studies were removed prior to download using the Ovid deduplication tool.

Data extraction

  • One author (SH) screened the titles and abstracts of all papers for inclusion and retrieved full texts for all studies that met the inclusion criteria.
  • If no full text could be found, and the abstract provided insufficient information for inclusion, the study was excluded.
  • One author (SH) screened all full texts for inclusion, and one of three independent reviewers (KT, ET, HJ) reviewed the first 60 full texts to check for consistency.
  • Specifically, the authors estimated linear associations between BMI and the log odds of prostate cancer or advanced prostate cancer, and between BMI and log transformed PSA.
  • If both adjusted (e.g., for potential confounders such as age, ethnicity, etc.) and unadjusted results were given in the same paper, the most-adjusted model was used in the meta-analysis.

Risk of bias assessment

  • SH and RL assessed the risk of bias in each study independently using an assessment tool created for a previous meta-analysis [18], with disagreements resolved by discussion.
  • The authors assessed risk of bias in six categories: confounding, selection of participants, missing data, outcome measurement, exposure measurement, and results’ reporting.
  • The authors included baseline age, BMI, log-PSA, family history of prostate cancer, and study as explanatory variables to predict prostate cancer status using multiple imputation.
  • Additionally, the authors visually inspected a plot of estimated prostate cancer risk against PSA for the imputed studies, to see whether the predicted risk of prostate cancer at low PSA levels for each study was plausible .
  • In each of the three included IPD studies, the authors estimated associations between BMI and (1) prostate cancer, (2) advanced prostate cancer, and (3) PSA.

Combining data

  • The authors combined estimates from studies identified through the systematic review and the IPD studies using random-effects and fixed-effect meta-analyses.
  • Studies presenting HRs and ORs were analyzed and presented separately.
  • In meta-analyses of categorical associations, studies from the systematic review were included if they presented ORs or HRs for overweight and/or obese men relative to normal weight men (for the outcomes of prostate cancer and advanced prostate cancer) or means and SDs of PSA or log-PSA for each of these BMI categories (for the outcome of PSA).
  • ORs and HRs that were presented for other categories of BMI were not used (such as morbidly obese, BMI ≥ 35 kg/m2), though the authors combined the mean and SD of PSA for different categories with neighboring categories when sufficient information was available.
  • Meta‑regression Meta-regression [33] was used to determine if the effect estimates from individual studies included in the metaanalyses varied by study-level factors.

Albatross plots

  • As not all studies reported enough information to be included in the meta-analyses, the authors also present albatross plots containing results from studies with and without sufficient information to be included in the meta-analyses [17].
  • These are plots of the p value of an association against the number of participants and can be used to assess heterogeneity between studies and assess the rough magnitude of an association using limited information.
  • By indicating which studies had insufficient data to contribute to meta-analysis on the albatross plots, the authors determined whether inclusion of the remaining studies would have altered the overall interpretation of the evidence.

Results

  • In total, 9,127 papers were found that had keywords for BMI and prostate cancer or PSA.
  • After title and abstract screening, 725 papers remained (see Fig. 1, PRISMA flow diagram).

Continuous BMI

  • All studies in the meta-analysis adjusted for age in either the study design or analysis, while 9 studies (47%) adjusted for ethnicity.
  • No other variable (of 13 other variables) was adjusted for in more than four studies.
  • The funnel plot (Supplementary Fig. 11) showed little evidence of small study effects.

Categorical BMI

  • Overall, there were 17 studies and 218,700 participants included in this analysis.
  • Forest plots are presented in Supplementary Figs.  13 and 14.
  • The weighted mean BMI across all studies was 22.2 kg/m2 for the normal BMI category, 26.5 kg/m2 for the overweight category, and 31.3 kg/m2 for the obese category.

Overall prostate cancer

  • There was no compelling evidence to suggest there is a linear association between BMI and prostate cancer risk as the effect estimate was null with a very tight confidence interval, nor an association between being overweight and prostate cancer risk, and only weak evidence for a small reduction in prostate cancer risk in obesity.
  • There is likely a reduced risk of being diagnosed with prostate cancer in overweight/obese men due to the role of PSA screening or testing in many prostate cancer diagnoses.
  • This finding is consistent with their hypothesis regarding the expected direction of bias due to the negative association of BMI with PSA.
  • Overall, their results are consistent with previous metaanalyses.
  • In addition, an umbrella review of systematic reviews and meta-analysis by Kyrgiou et al. [3] concluded that there was no strong evidence for an association between BMI and prostate cancer risk, with a summary OR for prostate cancer for a 5 kg/m2 increase in BMI of 1.03 (95% CI 0.99–1.06).

Advanced prostate cancer

  • This association was null in studies reporting an OR (OR = 1.00, 95% CI 0.94–1.06), but still consistent with a small positive association in studies, such that the difference between the two groups of studies may be due to chance or differences in study design or population.
  • Additionally, there may be collider bias [24] in both estimates from conditioning on prostate cancer, since any unmeasured confounders associated with both prostate cancer and advanced prostate cancer could induce an association between BMI and advanced prostate cancer.
  • The effect estimate may be increased in the WCRF analysis by the inclusion of high-grade and/or fatal prostate cancers or exclusion of case–control studies.
  • Kyrgiou et al. [3] concluded that there was weak evidence for a positive association between increasing BMI and advanced prostate cancer risk, with a RR for advanced prostate cancer for a 5 kg/ m2 increase in BMI of 1.09 (95% CI 1.02–1.16), although their meta-analysis included more up-to-date studies with a stricter inclusion criteria.

PSA

  • There was strong evidence of an inverse association between BMI and PSA, which the authors found to be likely non-linear, decreasing more quickly between overweight and obese than normal weight and overweight.
  • On average, obese men have an estimated 12.9% lower PSA than a normal weight man, and overweight men 3.4% lower PSA.
  • The authors could only find one previous review of the association between BMI and PSA, which did not include a meta-analysis or estimate effect size [152].
  • Their conclusion was that many studies reported an inverse association between BMI and PSA, in agreement with their findings.
  • It could thus be potentially beneficial to account for BMI when interpreting the results of a PSA test, however, prospective research would be necessary to confirm whether this would have a beneficial effect on prostate cancerrelated outcomes.

Strengths and Limitations

  • The authors synthesized data from many studies, including participants from many different populations at different time points, improving generalizability.
  • By including IPD studies and imputing prostate cancer status in men who were not biopsied, the authors were able to show and account for bias in the association between BMI and prostate cancer from PSA testing.
  • It is also possible the association between BMI and PSA varies by population, though their meta-regressions did not find any explanatory factors.
  • There was at least a moderate risk of bias for all studies, as all studies were observational and therefore could have been biased by unobserved confounding.
  • As such, relatively few studies were included; a superior approach would be to gather IPD from all eligible studies and to determine the precise form of any non-linear associations, which would also allow more accurate corrections to men’s PSA levels.

Conclusion

  • There was little evidence of any association between BMI and prostate cancer risk, and some evidence for a small positive association with advanced prostate cancer risk.
  • There was evidence from IPD studies to suggest this could bias the association between BMI and prostate cancer in screening studies.
  • The authors would like to acknowledge the support of the National Cancer Research Institute (NCRI) formed by the Department of Health, the Medical Research Council (MRC), and Cancer Research UK.
  • The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
  • This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.

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Vol.:(0123456789)
1 3
Cancer Causes & Control (2020) 31:431–449
https://doi.org/10.1007/s10552-020-01291-3
REVIEW ARTICLE
Systematic review andmeta‑analysis oftheassociations
betweenbody mass index, prostate cancer, advanced prostate cancer,
andprostate‑specic antigen
SeanHarrison
1,2
· KateTilling
1,2
· EmmaL.Turner
1
· RichardM.Martin
1,3
· RosieLennon
4
· J.AtheneLane
1,3
·
JennyL.Donovan
1,5
· FreddieC.Hamdy
6
· DavidE.Neal
6,7
· J.L.H.RuudBosch
8
· HayleyE.Jones
1
Received: 23 August 2019 / Accepted: 27 February 2020 / Published online: 11 March 2020
© The Author(s) 2020
Abstract
Purpose The relationship between body mass index (BMI) and prostate cancer remains unclear. However, there is an inverse
association between BMI and prostate-specific antigen (PSA), used for prostate cancer screening. We conducted this review
to estimate the associations between BMI and (1) prostate cancer, (2) advanced prostate cancer, and (3) PSA.
Methods We searched PubMed and Embase for studies until 02 October 2017 and obtained individual participant data
from four studies. In total, 78 studies were identified for the association between BMI and prostate cancer, 21 for BMI and
advanced prostate cancer, and 35 for BMI and PSA. We performed random-effects meta-analysis of linear associations of
log-PSA and prostate cancer with BMI and, to examine potential non-linearity, of associations between categories of BMI
and each outcome.
Results In the meta-analyses with continuous BMI, a 5kg/m
2
increase in BMI was associated with a percentage change
in PSA of −5.88% (95% CI −6.87 to −4.87). Using BMI categories, compared to normal weight men the PSA levels of
overweight men were 3.43% lower (95% CI −5.57 to −1.23), and obese men were 12.9% lower (95% CI −15.2 to −10.7).
Prostate cancer and advanced prostate cancer analyses showed little or no evidence associations.
Conclusion There is little or no evidence of an association between BMI and risk of prostate cancer or advanced prostate
cancer, and strong evidence of an inverse and non-linear association between BMI and PSA. The association between BMI
and prostate cancer is likely biased if missed diagnoses are not considered.
Keywords Prostate cancer· Prostate-specific antigen· Body mass index· Screening· Meta-analysis· Systematic review
Electronic supplementary material The online version of this
article (https ://doi.org/10.1007/s1055 2-020-01291 -3) contains
supplementary material, which is available to authorized users.
* Sean Harrison
sean.harrison@bristol.ac.uk
1
Department ofPopulation Health Sciences, Bristol Medical
School, University ofBristol, Bristol, England
2
Medical Research Council Integrative Epidemiology Unit,
University ofBristol, Bristol, England
3
National Institute forHealth Research Bristol Biomedical
Research Centre, University Hospitals Bristol NHS
Foundation Trust andUniversity ofBristol, Bristol, England
4
Department ofEnvironment andGeography, University
ofYork, York, England
5
National Institute forHealth Research Collaboration
forLeadership inApplied Health Research andCare West,
University Hospitals Bristol NHS Trust, Bristol, England
6
Nuffield Department ofSurgical Sciences, University
ofOxford, Oxford, England
7
Department ofOncology, Addenbrooke’s Hospital,
University ofCambridge, Cambridge, England
8
Department ofUrology, University Medical Centre Utrecht,
Utrecht, TheNetherlands
432 Cancer Causes & Control (2020) 31:431–449
1 3
Background
Prostate cancer is the second commonest male cancer
worldwide, [1] and the most commonly diagnosed cancer
in men in the UK, with an estimated 47,151 diagnoses in
2015 [2]. Generally, most prostate cancers are slow grow-
ing, but can metastasize to the bones, lungs, and brain.
Worldwide, there were an estimated 307,000 deaths from
prostate cancer in 2012 [1], and in the UK, around 11,600
men died from prostate cancer in 2016 [2].
Body mass index (BMI) has been associated with
many cancers [3], but its association with prostate can-
cer is unclear. Previous meta-analyses and reviews have
suggested that BMI is not associated with prostate cancer
[4, 5], positively associated with prostate cancer [6, 7],
inversely associated with localized prostate cancer [8], and
positively associated with advanced [8], aggressive [9],
high-grade, and fatal prostate cancers [4]. These meta-
analyses were either limited to cohort studies [4, 5, 7, 8] or
in need of updating [6, 7]. Additionally, no meta-analysis
assessed potential non-linear associations between BMI
and risk of prostate cancer or advanced prostate cancer.
We therefore sought to perform an updated review of the
literature, including more studies, and additionally exam-
ining non-linear associations.
BMI has also been inversely associated with prostate-
specific antigen (PSA) [10], although no previous meta-
analysis of this relationship exists. The presence of such an
association could bias observed relationships between BMI
and prostate cancer as PSA testing often plays a key role in
diagnosis. More specifically, a negative association between
BMI and PSA could lead to a spurious negative association
or mask a positive association between BMI and localized
prostate cancer, as obese men, with lower PSA values, would
be less likely to be offered a biopsy as the result of a PSA
test. A negative association between BMI and PSA could
also induce a spurious positive association between BMI
and advanced prostate cancer, as obese men may be diag-
nosed later, due to their lower PSA levels. In addition, if the
association between BMI and prostate cancer (or advanced
prostate cancer) is non-linear, then studies with different
distributions of BMI will give rise to different estimates
of the BMI-prostate cancer association. There may also be
an association between BMI and prostate cancer screening
behavior (including uptake of PSA testing), though stud-
ies have shown conflicting results. In the USA, men with
high BMI values were more likely to receive PSA tests [11],
whereas in the UK men with both very low and high BMI
values were less likely to receive a PSA test [12]. This fur-
ther complicates the relationship between BMI and prostate
cancer diagnosis (though not BMI and PSA values), and this
review does not aim to assess this association.
We systematically reviewed the literature for all relevant
studies and performed meta-analyses. We also examined
these relationships using individual participant data (IPD)
from prostate cancer studies. In analyzing the IPD studies,
we aimed to account for incomplete and PSA-dependent
diagnosis by imputing prostate cancer status for all men who
did not receive a biopsy, and in doing, avoid potential bias
resulting from an association between BMI and PSA.
Our objectives were to i) precisely quantify the (assumed
linear) associations between BMI and prostate cancer,
advanced prostate cancer, and PSA; ii) update previ-
ous meta-analyses using all relevant evidence, including
case–control studies; and iii) explore potential non-linear-
ity in these associations. Our overall aim was to understand
whether BMI is a risk factor for prostate cancer, and to iden-
tify whether failure to account for the role of PSA in many
prostate cancer diagnoses is likely to lead to biased estimates
of the association between BMI and prostate cancer.
Methods
Eligibility criteria
We performed a systematic review in which we included
original articles published in peer reviewed journals that
measured an association between BMI and total prostate
cancer incidence and/or advanced prostate cancer; and stud-
ies that measured an association between BMI and PSA,
including supplements and meeting abstracts; human rand-
omized controlled trials (RCTs), case–control, cohort, cross-
sectional, and non-randomized experimental studies. If the
abstract did not specifically mention BMI but mentioned
height or weight, we acquired the full text to determine if
BMI was calculable from data included in the publication.
We excluded reviews, books, commentaries, letters, and
animal and cell-line studies; studies examining pre-malig-
nant disease if there was no mention of prostate cancer or
PSA; studies where BMI was measured after diagnosis of
prostate cancer, as this increases the likelihood of reverse
causality; and studies that we considered to be at critical risk
of bias (see ‘Risk of Bias Assessment’ below).
We determined the effect estimate to be for advanced
prostate cancer if the individual studies labeled the effect as
“advanced” or “aggressive,” or if the effect was for locally
advanced, extra-prostatic, nodular or metastatic prostate
cancer. Advanced prostate cancer represents clinically
meaningful cancer, with lower survival rates than non-
advanced cancers. High-grade prostate cancer on its own
was not considered equivalent to advanced prostate cancer
and was not extracted, as the definition of “high-grade” has
been inconsistent over time, incorporating Gleason scores
433Cancer Causes & Control (2020) 31:431–449
1 3
(the definition of which has changed over time [13]), tumor,
node, metastases [TNM] scores, and PSA levels.
Data sources
We searched Medline and Embase databases up to 02 Octo-
ber 2017 for studies in humans associating BMI with either
prostate cancer or PSA. The search query was as follows
(each term as a text word search): (BMI or body mass index
or obese or obesity or body weight or body size or adipos-
ity) AND (prostate cancer or prostate neoplasm or PSA or
prostate-specific antigen) NOT psoriatic arthritis. Psoriatic
arthritis was excluded as its initialism is also PSA. We also
reviewed the reference lists of previous meta-analyses for
further studies for inclusion [6, 8, 14]. Duplicate studies
were removed prior to download using the Ovid deduplica-
tion tool.
Data extraction
One author (SH) screened the titles and abstracts of all
papers for inclusion and retrieved full texts for all studies
that met the inclusion criteria. Full texts were also sought
if no abstract was available or if the abstract did not include
sufficient information to decide on inclusion. We also sought
full texts for conference abstracts, if a corresponding full text
was not found in the original search. If no full text could be
found, and the abstract provided insufficient information for
inclusion, the study was excluded. We excluded one pub-
lished paper where we could not locate a full text [15].
One author (SH) screened all full texts for inclusion, and
one of three independent reviewers (KT, ET, HJ) reviewed
the first 60 full texts to check for consistency. We resolved
any inconsistency with discussion to clarify screening crite-
ria. A random subset of the remaining studies [30 full texts]
was also reviewed by the independent reviewers to check for
drift from inclusion/exclusion criteria.
Both SH and RL independently extracted all relevant data
from included studies, with disagreements resolved by dis-
cussion. The first ten extractions were also performed by
HEJ, KT, and ELT to check for consistency.
We categorized prostate cancer studies as “before” if BMI
was measured on average at least two years before diagnosis
(prospective studies), and “same time” if BMI was measured
on average less than two years before diagnosis. In general,
“before” studies were cohort studies and “same time” stud-
ies were case–control studies. We considered the “before”
studies to be at lower risk of reverse causation.
We extracted data that were (or could be transformed to)
an odds ratio (OR) or hazard ratio (HR) quantifying the con-
tinuous association between BMI and total and advanced
prostate cancer risk, and a regression coefficient for the
association between BMI and log-PSA. Log-PSA was used
as an outcome rather than PSA as we assumed a multiplica-
tive association between BMI and PSA, which fits with the
theory that haemodilution is responsible for any observed
association [16]. Studies reported associations in a variety
of ways; a detailed list of the statistical conversions used to
estimate the ORs, HRs, and regression coefficients and their
standard errors (SEs) is in Supplementary appendix 1.
We estimated linear associations, taking BMI as a con-
tinuous exposure variable, and assessing the possibility
of non-linear associations by coding BMI as a categori-
cal exposure. Specifically, we estimated linear associa-
tions between BMI and the log odds of prostate cancer or
advanced prostate cancer, and between BMI and log trans-
formed PSA. For simplicity, we refer to linear associations
as “continuous” throughout. The following BMI categories
were used: normal weight (BMI < 25kg/m
2
), overweight
(25kg/m
2
≤ BMI < 30kg/m
2
), and obese (BMI ≥ 30kg/m
2
).
We refer to these as “categorical” associations throughout.
When several papers reported on the same study, for con-
tinuous associations we prioritized papers that presented
continuous effect estimates (e.g., HR or OR per 1kg/m
2
increase in BMI) over papers presenting categorical effect
estimates (e.g., HR or OR for overweight and obese groups
versus normal weight), and these were prioritized over mean
differences. For categorical associations, we extracted esti-
mates from papers presenting categorical associations only.
If duplicate studies presented the same effect estimate types
in multiple papers, the paper with the largest number of
participants was used in the meta-analysis. If both adjusted
(e.g., for potential confounders such as age, ethnicity, etc.)
and unadjusted results were given in the same paper, the
most-adjusted model was used in the meta-analysis.
If the data were insufficient to estimate a regression coef-
ficient, OR or HR and SE, we extracted a p value, the num-
ber of participants and direction of association from the most
relevant analysis for use in an albatross plot [17].
Risk ofbias assessment
SH and RL assessed the risk of bias in each study inde-
pendently using an assessment tool created for a previous
meta-analysis [18], with disagreements resolved by discus-
sion. This tool uses the categories of assessment from a draft
of the ROBINS-I tool [19], and questions from the CASP
case–control and cohort questionnaires [20, 21], see Sup-
plementary appendix 2.
We assessed risk of bias in six categories: confounding,
selection of participants, missing data, outcome measure-
ment, exposure measurement, and results’ reporting. We
assigned overall and category-specific risks of bias: either
low, moderate, high, critical, or unclear (if there was insuffi-
cient information to assign a risk). We based the overall risk
of bias on a subjective combination of the category-specific
434 Cancer Causes & Control (2020) 31:431–449
1 3
risk of biases, looking at the maximum risk of bias that
could have been introduced into the study by each category.
The overall risk of bias was not low in any study, as all
studies were observational and thus potentially subject to
unmeasured confounding.
We determined that a study had a critical risk of bias if
i) age was not accounted for in either the design or analy-
sis of the study and, for BMI-prostate cancer case–control
studies, if there was more than a 3-year difference in the
mean or median ages of cases and controls, because age is
strongly associated with BMI [22], prostate cancer risk [23],
and PSA [23]; or ii) if the design of the study was such that
participation was conditional upon PSA levels, both for the
association between BMI and PSA (as this would involve
conditioning on the outcome) and the association between
BMI and prostate cancer (as this would involve conditioning
on a collider) [24].
Studies with a critical risk of bias were excluded prior to
analysis and were not considered further.
In the studies found in the systematic review, it was gen-
erally unclear whether men considered as not having prostate
cancer had received biopsies. Usually, the controls were “not
known to have prostate cancer,” rather than “known not to
have prostate cancer.” Therefore, screening could have intro-
duced bias in the association between BMI and prostate can-
cer. Although we did not consider this a critical risk of bias,
we sought to investigate and quantify this bias using large
studies where biopsy status was known, and IPD available.
Individual participant data studies
Studies that offered prostate biopsies if the participants’
PSA were above threshold values (screening studies) were
excluded from our systematic review for having a critical
risk of bias. However, we noted that some of the largest
potentially relevant studies for our research questions were
screening studies, and that bias due to screening could
potentially be accounted for using imputation of prostate
cancer status if IPD were available. This would then allow
these studies to be included in the meta-analyses.
We approached four prospective studies looking at pros-
tate cancer to obtain IPD: Krimpen [25], Prostate Cancer
Prevention Trial (PCPT) [26], Prostate, Lung, Colorectal,
and Ovarian cancer screening trial (PLCO) [27] and Pros-
tate Testing for cancer and treatment trial (ProtecT) [28].
These studies were chosen because they were large studies of
prostate cancer with known PSA screening protocols, or the
biopsy status of all participants was known. Key to inform-
ing the imputation model was PCPT, which offered biopsies
to all participants regardless of PSA level. This information
allowed us to predict prostate cancer status for men with a
PSA level below the threshold for biopsy in the other three
studies using multiple imputation. However, PCPT only
included men with a PSA less than 3.0ng/ml, biasing both
the BMI-PSA and BMI-prostate cancer analyses, and as such
was excluded from the meta-analyses due to the critical risk
of bias from conditioning on a collider or outcome. Imputa-
tion is valid if the missing data (prostate cancer status) is
missing at random given other variables in the imputation
model, so imputing prostate cancer is not biased even though
PCPT is restricted to men with a PSA less than 3.0ng/ml, as
PSA is in the imputation model [29].
For each IPD study, we requested data measured at
baseline on BMI and PSA, as well as age, family history
of prostate cancer and ethnicity. We also requested data on
prostate cancer status (including tumor, node, metastases
[TNM], and Gleason scores). For each man who was not
biopsied, we imputed prostate cancer status by the end of
the study in which he participated using multiple imputa-
tion. We included baseline age, BMI, log-PSA, family his-
tory of prostate cancer, and study as explanatory variables
to predict prostate cancer status using multiple imputation.
BMI, log-PSA, and family history of prostate cancer were
also imputed if missing.
We checked the validity of the imputation model by
checking whether the predicted incidence of prostate cancer
among men without prostate biopsies was credible, given
results from autopsy studies [30]. Additionally, we visually
inspected a plot of estimated prostate cancer risk against
PSA for the imputed studies, to see whether the predicted
risk of prostate cancer at low PSA levels for each study was
plausible (see Supplementary Appendix3.4).
In each of the three included IPD studies, we estimated
associations between BMI and (1) prostate cancer, (2)
advanced prostate cancer, and (3) PSA. We restricted the
analyses to men with white ethnicity (due to low numbers
of non-white men and therefore difficulties in imputation),
and adjusted the analyses for age, family history of prostate
cancer (for prostate cancer analyses), and prostate cancer
status (for the PSA analyses). Full details of the IPD studies,
the imputation method, and statistical analyses are available
in Supplementary Appendix3.
Combining data
Meta‑analysis
We combined estimates from studies identified through the
systematic review and the IPD studies using random-effects
and fixed-effect meta-analyses. We performed separate meta-
analyses of continuous and categorical associations for each
outcome (prostate cancer, advanced prostate cancer, and
PSA). All meta-analysis results are presented in forest plots.
Studies presenting HRs and ORs were analyzed and pre-
sented separately. For studies presenting ORs, “same time”
and “before” studies were meta-analyzed in subgroups,
435Cancer Causes & Control (2020) 31:431–449
1 3
and labeled as such in forest plots. Studies presenting HRs
were all classed as “before” studies, and labeled simply
“HR.” The results are presented as the HR or OR for pros-
tate cancer or advanced prostate cancer and percentage
change in PSA for a 5kg/m
2
increase in BMI. Heterogene-
ity was tested for and quantified using the Cochran’s Q and
I
2
statistics [31, 32].
In meta-analyses of categorical associations, studies
from the systematic review were included if they presented
ORs or HRs for overweight and/or obese men relative to
normal weight men (for the outcomes of prostate cancer
and advanced prostate cancer) or means and SDs of PSA
or log-PSA for each of these BMI categories (for the out-
come of PSA). ORs and HRs that were presented for other
categories of BMI were not used (such as morbidly obese,
BMI ≥ 35kg/m
2
), though we combined the mean and SD
of PSA for different categories with neighboring catego-
ries when sufficient information was available.
Meta‑regression
Meta-regression [33] was used to determine if the effect
estimates from individual studies included in the meta-
analyses varied by study-level factors. For all meta-regres-
sions, we considered ethnicity (non-white versus white in
each study, defined as > 80% white participants or from a
country with a majority white population), mid-year of
recruitment, mean BMI in the study, and the overall risk of
bias (high versus medium). For the associations between
BMI and prostate cancer and advanced prostate cancer, we
also considered the mean age at diagnosis, and study mean
time between BMI measurement and diagnosis.
Funnel plots
Funnel plots [34] were drawn to assess for small study
effects in each analysis [35].
Albatross plots
As not all studies reported enough information to be
included in the meta-analyses, we also present albatross
plots containing results from studies with and without suf-
ficient information to be included in the meta-analyses [17].
These are plots of the p value of an association against the
number of participants and can be used to assess heteroge-
neity between studies and assess the rough magnitude of an
association using limited information. By indicating which
studies had insufficient data to contribute to meta-analysis on
the albatross plots, we determined whether inclusion of the
remaining studies would have altered the overall interpreta-
tion of the evidence.
Results
In total, 9,127 papers were found that had keywords for
BMI and prostate cancer or PSA. After title and abstract
screening, 725 papers remained (see Fig.1, PRISMA flow
diagram). After full text screening, risk of bias assessment,
and removal of papers reporting the same studies, 78 stud-
ies examined the association between BMI and prostate
cancer [67 with data for meta-analysis], 21 studies exam-
ined the association between BMI and advanced prostate
cancer [18 with data for meta-analysis], and 35 studies
examined the association between BMI and PSA [20 with
data for meta-analysis, one of which only had data for
categorical associations].
A summary of all results is given in Table1.
BMI andprostate cancer
Continuous BMI
Of the 78 studies examining the association between BMI
and prostate cancer [25, 27, 28, 36–110], 11 (14%) could
not be included in the meta-analysis due to insufficient
data but were included in the albatross plot [100–110].
All studies are detailed in Supplementary Table1, with
the results of the risk of bias assessment in Supplementary
Table2. All studies in the meta-analysis adjusted for age
in either the study design or analysis, while 23 studies
(34%) adjusted for smoking status, 22 (33%) for ethnicity,
20 (30%) for family history of prostate cancer, 13 (19%)
for education, 10 (15%) for area, 10 (15%) for diabetes,
10 (15%) for physical activity, 9 (13%) for alcohol, 6 (9%)
for diet, and 6 (9%) for income. No other variable (of 24
other variables) was adjusted for in more than four studies.
In total, 9,513,326 men from 67 studies were included
in the HR and OR meta-analyses, (9,351,795 in 30 HR
studies, 161,531,383 in 37 OR studies); of these, 201,311
(2.1%) men had prostate cancer (157,990 cases [1.7%] in
HR studies, 41,863 [25.9%] in OR studies). The random-
effects meta-analyses (Figs.2 and 3) estimated the average
HR and OR for prostate cancer for a 5kg/m
2
increase in
BMI to be 1.01 (95% CI 0.99–1.04, p = 0.29) and 0.99
(95% CI 0.96–1.02, p = 0.64), respectively. There was
strong evidence for heterogeneity in effect estimates
across studies for the studies reporting an HR (p < 0.001,
I
2
= 79.9%), and studies reporting an OR (p < 0.001,
I
2
= 65.8%). Pooled estimates from fixed-effect meta-
analyses were essentially the same.
Citations
More filters
Journal Article•DOI•
Modifiable risk factors for prostate cancer in low- and lower-middle-income countries: a systematic review and meta-analysis

[...]

Filipe Cirne, Coralea Kappel, Shijie Zhou, Som D. Mukherjee, Mahshid Dehghan, Jo-Anne Petropoulos, Darryl P. Leong 
05 Jul 2022-Prostate Cancer and Prostatic Diseases
TL;DR: High fat intake was associated with higher risk of PCa while a diet rich in vegetables and tea intake wasassociated with a lower risk, and future prospective studies will be important to inform impactful and cost-effective preventive strategies in these countries.

5 citations

Journal Article•DOI•
"time" for obesity-related cancer: the role of the circadian rhythm in cancer pathogenesis and treatment.

[...]

Caterina Miro, A. Docimo, Luigi Barrea, L. Verde, Simona Cernea, Antoan Stefan Sojat, Ljiljana Marina, Giovanni Docimo, Annamaria Colao, Monica Dentice, Giovanna Muscogiuri 
01 Mar 2023-Seminars in Cancer Biology
TL;DR: In this paper , the aberrant circadian rhythms affect the development and prognosis of different types of obesity-related cancers (breast, prostate, colon rectal and thyroid cancer) focusing on both human studies and on molecular aspects.

2 citations

Posted Content•DOI•
Incorporating Genetic Determinants of Prostate-Specific Antigen Levels Improves Prostate Cancer Screening

[...]

Linda Kachuri, Thomas J. Hoffmann, Sophie I. Berndt, John P. Shelley, Kerry Schaffer, Mitchell J. Machiela, N. D. Freadman, W.Y. Huang, S. Li, Ryder L. Easterlin, Phyllis J. Goodman, Cathee Till, Ian M. Thompson, Hans Lilja, Stephen K. Van Den Eeden, Stephen J. Chanock, C. Haiman, David V. Conti, Robert J. Klein, Jonathan D. Mosley, Rebecca E. Graff, J. Witte 
21 Apr 2022-medRxiv
TL;DR: Genetically adjusted PSA was more predictive of aggressive prostate cancer than unadjusted PSA and improved detection of aggressive disease when combined with a prostate cancer PGS, and it was shown that PSA-related selection bias distorts genetic associations with prostate cancer and hampers PGS performance.
Abstract: Prostate-specific antigen (PSA) screening for prostate cancer remains controversial because it increases overdiagnosis and overtreatment of clinically insignificant tumors. We evaluated the potential of genetic determinants of PSA levels to improve screening utility by accounting for variation in PSA not due to cancer. A multi-ancestry genome-wide meta-analysis of 95,768 men without prostate cancer discovered 128 PSA-associated index variants (P<5 x 10-8), including 82 novel signals. The resulting 128-variant polygenic score for PSA (PGSPSA) explained 7.3-8.8% of PSA variation in external validation cohorts. Adjusting PSA values using PGSPSA enabled more accurate diagnostic decisions, such as avoiding 17-20% of negative prostate biopsies. Genetically adjusted PSA was more predictive of aggressive prostate cancer (odds ratio (OR)=3.04, P=3.3 x 10-7; AUC=0.716) than unadjusted PSA (OR=2.80, P=3.2 x 10-6; AUC=0.684) and improved detection of aggressive disease when combined with a prostate cancer PGS (AUC: 0.732 vs. 0.645, P=3.3 x 10-4). We further showed that PSA-related selection bias distorts genetic associations with prostate cancer and hampers PGS performance. Our findings provide a roadmap towards personalizing cancer biomarkers and screening.

2 citations

Journal Article•DOI•
Obesity and Main Urologic Cancers: Current Systematic Evidence, Novel Biological Mechanisms, Perspectives and Challenges.

[...]

Georgios S. Papavasileiou, Dimitrios Tsilingiris, Nikolaos Spyrou, Natalia G. Vallianou, Irene Karampela, Faidon Magkos, Maria Dalamaga 
01 Mar 2023-Seminars in Cancer Biology
TL;DR: In this paper , the role of obesity in the development and progression of urologic cancers was examined. And the molecular pathways that link obesity to the development of these cancers were reviewed.

2 citations

Leveraging Genetic Determinants of Prostate-Specific Antigen Levels Towards Improving Prostate Cancer Screening

[...]

Linda Kachuri, Thomas J. Hoffmann, Yu Jiang, Sonja I. Berndt, John P. Shelley, Kerry Schaffer, Mitchell J. Machiela, Neal D. Freedman, Weng-Yi Huang, Shengchao A. Li, Ryder L. Easterlin, J Phyllis, Goodman, Cathee Till, Ian M. Thompson, Hans Lilja, Stephen K. Van Den Eeden, Stephen J. Chanock, Christopher A. Haiman, David V. Conti, Robert J. Klein, Jonathan D. Mosley, Rebecca E. Graff, John S. Witte 
TL;DR: This multi-ancestry genome-wide meta-analysis of 95,768 men discovered 128 PSA-associated variants and showed that PSA G was a more robust predictor of aggressive prostate cancer, relative to both baseline PSA and an established 269-variant prostate cancer risk score.
Abstract: Prostate-specific antigen (PSA) screening for prostate cancer remains controversial because it increases overdiagnosis and overtreatment of clinically insignificant tumors. We investigated whether accounting for genetic determinants of variation in PSA that is not due to cancer has potential to improve screening utility. Our multi-ancestry genome-wide meta-analysis of 95,768 men discovered 128 PSA-associated variants ( P <5×10 -8 ), 82 of which were novel. A genome-wide polygenic score for PSA (PGS PSA ) explained 7.08-9.61% of PSA variation in external, multi-ancestry validation cohorts. Diagnostic decisions in men of European ancestry based on PSA values adjusted using PGS PSA would have avoided 31% of negative prostate biopsies, but also resulted in 12% fewer biopsies in prostate cancer cases, mostly in patients with Gleason score <7 tumors. Genetically adjusted PSA was more predictive of aggressive prostate cancer (odds ratio (OR)=3.44, P =6.2×10 -14 ; AUC=0.755) than unadjusted PSA (OR=3.31, P =1.1×10 -16 ; AUC=0.738), and improved detection of aggressive disease when combined with a prostate cancer PGS (AUC: 0.786 vs. 0.712, P =7.2×10 -4 ) in a multi-ancestry sample of 106 cases and 23,667 controls. We also detected PSA-related selection bias that distorts genetic associations with prostate cancer and hinders risk prediction. Our findings provide a roadmap towards personalizing cancer biomarkers and screening. In PCPT and SELECT, we showed that PSA G was a more robust predictor of aggressive prostate cancer, relative to both baseline PSA and an established 269-variant prostate cancer risk score. Furthermore, we demonstrated that GWAS-identified prostate cancer risk variants, including those in PGS 269 , are affected by a systematic PSA-related selection bias. Correcting for this bias represents an extension of the PSA de-Mendelization paradigm that improves PGS 269 performance. or 0.20

1 citations

References
More filters
Journal Article•DOI•
Body size and composition and prostate cancer risk: systematic review and meta-regression analysis.

[...]

Robert J. MacInnis1, Robert J. MacInnis2, Dallas R. English2, Dallas R. English1•
Cancer Council Victoria1, University of Melbourne2
01 Oct 2006-Cancer Causes & Control
TL;DR: It is indicated that obesity is weakly associated with an increased risk of prostate cancer (particularly advanced stage tumors), while increased stature may also increase risk, and there is little evidence for an association with central obesity.
Abstract: The evidence that measures of obesity and stature are associated with prostate cancer is weak and inconsistent. We performed a systematic review and meta-analysis of the relationship between body mass index (BMI), height, weight, waist circumference and waist-to-hips ratio (WHR) and the risk of prostate cancer. Study-specific dose-response slopes were obtained, and random effects rate ratios (RRs) were computed from linear meta-regression models. We included 55,521 cases identified among 2,818,767 men from 31 cohort studies, and 13,232 cases and 16,317 controls from 25 case–control studies. The overall RR for BMI was 1.05 per 5 kg/m2 increment, 95% CI 1.01–1.08. For studies that reported results by stage of disease, the RRs were stronger for advanced disease (RR 1.12 per 5 kg/m2 increment, 95% CI 1.01–1.23) compared with localized disease (RR 0.96 per 5 kg/m2 increment, 95% CI 0.89–1.03), p = 0.02. Height was also positively associated with risk (RR 1.05 per 10 cm increment, 95% CI 1.02–1.09), but the evidence was weak for weight (RR 1.01 per 10 kg increment, 95% CI 0.97–1.04), waist circumference (RR 1.03 per 10 cm increment, 95% CI 0.99–1.07), and WHR (RR 1.11 per 0.1 unit increment, 95% CI 0.95–1.30). Stronger associations were observed among cohort studies compared with case–control studies for BMI (p = 0.006), height (p < 0.001) and weight (p = 0.02). This meta-analysis indicates that obesity is weakly associated with an increased risk of prostate cancer (particularly advanced stage tumors). While increased stature may also increase risk, there is little evidence for an association with central obesity.

380 citations

Journal Article•DOI•
Body mass index, weight change, and risk of prostate cancer in the Cancer Prevention Study II Nutrition Cohort.

[...]

Carmen Rodriguez1, Stephen J. Freedland, Anusila Deka, Eric J. Jacobs, Marjorie L. McCullough, Alpa V. Patel, Michael J. Thun, Eugenia E. Calle •
American Cancer Society1
01 Jan 2007-Cancer Epidemiology, Biomarkers & Prevention
TL;DR: Obesity increases the risk of more aggressive prostate cancer and may decrease either the occurrence or the likelihood of diagnosis of less-aggressive tumors, and men who lose weight may reduce their risk of prostate cancer.
Abstract: Background: Obesity has been associated with aggressive prostate cancer. The extent of this association, which varies by stage and grade, remains unclear. The role of recent weight change had not been previously examined. Methods: We examined body mass index (BMI) and weight change in relation to incident prostate cancer by disease stage and grade at diagnosis among 69,991 men in the Cancer Prevention Study II Nutrition Cohort. Participants provided information on height and weight in 1982, and again at enrollment in 1992. During follow-up through June 30, 2003 (excluding the first 2 years of follow-up), we documented 5,252 incident prostate cancers. Cox proportional hazards models were used to estimate rate ratios (RR) and 95% confidence intervals (95% CI). Results: The association between BMI in 1992 and risk of prostate cancer differed by stage and grade at diagnosis. BMI was inversely associated with risk of nonmetastatic low-grade prostate cancer (RR, 0.84; 95% CI, 0.66-1.06), but BMI was positively associated with risk of nonmetastatic high-grade prostate cancer (RR, 1.22; 95% CI, 0.96-1.55) and risk of metastatic or fatal prostate cancer (RR, 1.54; 95% CI, 1.06-2.23). Compared with weight maintenance, men who lost >11 pounds between 1982 and 1992 were at a decreased risk of nonmetastatic high-grade prostate cancer (RR, 0.58; 95% CI, 0.42-0.79). Conclusion: Obesity increases the risk of more aggressive prostate cancer and may decrease either the occurrence or the likelihood of diagnosis of less-aggressive tumors. Men who lose weight may reduce their risk of prostate cancer. (Cancer Epidemiol Biomarkers Prev 2007;16(1):63–9)

355 citations

Journal Article•DOI•
Animal fat consumption and prostate cancer: a prospective study in Hawaii.

[...]

Loic Le Marchand1, Laurence N. Kolonel, Lynne R. Wilkens, Beth C. Myers, Tomio Hirohata •
University of Hawaii1
01 May 1994-Epidemiology
TL;DR: In this paper, the authors evaluated consumption of high-fat animal products, raw vegetables, and fresh fruits, as well as obesity, smoking, and drinking, in relation to subsequent occurrence of prostate cancer.
Abstract: Whereas case-control studies have been very consistent in suggesting a positive association between intake of dietary fat, especially animal fat, and prostate cancer, the results from past cohort studies have been mostly inconclusive. In this study, we evaluated consumption of high-fat animal products, raw vegetables, and fresh fruits, as well as obesity, smoking, and drinking, in relation to subsequent occurrence of prostate cancer. We studied a cohort of 20,316 men of various ethnicities interviewed between 1975 and 1980 in Hawaii. As of December 1989, 198 incident cases with invasive prostate cancer were identified by computer-assisted linkage of this cohort to the statewide Surveillance, Epidemiology, and End Results registry. Relative risks (RRs) for prostate cancer computed by proportional hazards regression were elevated for intake of beef [RR for highest to lowest tertile of intake = 1.6; 95% confidence interval (CI) = 1.1-2.4] and milk (RR = 1.4; 95% CI = 1.0-2.1), and for a summary variable for intake of high-fat animal products (RR = 1.6; 95% CI = 1.0-2.4). Weight was not consistently associated with prostate cancer, but there was an association with height (> 167 cm) (RR = 1.8; 95% CI = 1.0-3.2 for the third and fourth quartiles relative to the lowest quartile in height). These associations were stronger in men diagnosed before age 72.5 years. The risk estimates for raw vegetable and fresh fruit intakes were close to 1.0. Smoking and alcohol drinking appeared to be unrelated to risk.(ABSTRACT TRUNCATED AT 250 WORDS)

340 citations

Journal Article•DOI•
Obesity-related plasma hemodilution and PSA concentration among men with prostate cancer.

[...]

Lionel L. Bañez1, Robert J. Hamilton2, Robert J. Hamilton1, Alan W. Partin3, Robin T. Vollmer1, Leon Sun1, Carmen Rodriguez4, Yiting Wang4, Martha K. Terris5, Martha K. Terris6, William J. Aronson7, Joseph C. Presti8, Christopher J. Kane9, Christopher J. Kane10, Christopher L. Amling11, Judd W. Moul1, Stephen J. Freedland1 •
Duke University1, University of Toronto2, Johns Hopkins University3, American Cancer Society4, Veterans Health Administration5, Georgia Regents University6, University of California, Los Angeles7, Stanford University8, United States Department of Veterans Affairs9, University of California, San Francisco10, University of Alabama at Birmingham11
21 Nov 2007-JAMA
TL;DR: In men undergoing radical prostatectomy, higher BMI was associated with higher plasma volume; hemodilution may therefore be responsible for the lower serum PSA concentrations among obese men with prostate cancer.
Abstract: ContextRecent studies have suggested that obese men have lower serum prostate-specific antigen (PSA) concentrations than nonobese men. Because men with higher body mass index (BMI) have greater circulating plasma volumes, lower PSA concentrations among obese men may be due to hemodilution.ObjectiveTo determine the association between hemodilution and PSA concentration in obese men with prostate cancer.Design, Setting, and ParticipantsRetrospective study of men who underwent radical prostatectomy for prostate adenocarcinoma from 1988 to 2006, using data from the databases of the Shared Equal Access Regional Cancer Hospital (n = 1373), Duke Prostate Center (n = 1974), and Johns Hopkins Hospital (n = 10 287). Multivariate linear regression models adjusting for clinicopathological characteristics were used to analyze the main outcome measures.Main Outcome MeasuresAssociations between BMI and mean adjusted PSA concentrations, mean plasma volume, and mean adjusted PSA mass (total circulating PSA protein, calculated as PSA concentration multiplied by plasma volume), assessed by determining P values for trend.ResultsAfter controlling for clinicopathological characteristics, higher BMI was significantly associated with higher plasma volume (P < .001 for trend) and lower PSA concentrations (P ≤ .02 for trend) in all cohorts. In 2 of the 3 cohorts, PSA mass did not change significantly with increasing BMI. In the third cohort, higher BMI was associated with increased PSA mass (P < .001 for trend), but only between BMI category less than 25 and the other categories.ConclusionsIn men undergoing radical prostatectomy, higher BMI was associated with higher plasma volume; hemodilution may therefore be responsible for the lower serum PSA concentrations among obese men with prostate cancer. Prospective studies are needed to evaluate this association in screened populations.

336 citations

Journal Article•DOI•
Association of Obesity and Cancer Risk in Canada

[...]

Sai Yi Pan1, Kenneth C. Johnson, Anne-Marie Ugnat, Shi Wu Wen, Yang Mao •
Health Canada1
01 Feb 2004-American Journal of Epidemiology
TL;DR: This study provides further evidence that obesity increases the risk of overall cancer, non-Hodgkin's lymphoma, leukemia, multiple myeloma, and cancers of the kidney, colon, rectum, breast (in postmenopausal women), pancreas, ovary, and prostate.
Abstract: The authors conducted a population-based, case-control study of 21,022 incident cases of 19 types of cancer and 5,039 controls aged 20-76 years during 1994-1997 to examine the association between obesity and the risks of various cancers. Compared with people with a body mass index of less than 25 kg/m(2), obese (body mass index of > or = 30 kg/m(2)) men and women had an increased risk of overall cancer (multivariable adjusted odds ratio = 1.34, 95% confidence interval (CI): 1.22, 1.48), non-Hodgkin's lymphoma (odds ratio = 1.46, 95% CI: 1.24, 1.72), leukemia (odds ratio = 1.61, 95% CI: 1.32, 1.96), multiple myeloma (odds ratio = 2.06, 95% CI: 1.46, 2.89), and cancers of the kidney (odds ratio = 2.74, 95% CI: 2.30, 3.25), colon (odds ratio = 1.93, 95% CI: 1.61, 2.31), rectum (odds ratio = 1.65, 95% CI: 1.36, 2.00), pancreas (odds ratio = 1.51, 95% CI: 1.19, 1.92), breast (in postmenopausal women) (odds ratio = 1.66, 95% CI: 1.33, 2.06), ovary (odds ratio = 1.95, 95% CI: 1.44, 2.64), and prostate (odds ratio = 1.27, 95% CI: 1.09, 1.47). Overall, excess body mass accounted for 7.7% of all cancers in Canada-9.7% in men and 5.9% in women. This study provides further evidence that obesity increases the risk of overall cancer, non-Hodgkin's lymphoma, leukemia, multiple myeloma, and cancers of the kidney, colon, rectum, breast (in postmenopausal women), pancreas, ovary, and prostate.

334 citations

Related Papers (5)
Systematic review and meta-analysis of the associations between body mass index, prostate cancer, advanced prostate cancer, and prostate-specific antigen

[...]

11 Mar 2020-Cancer Causes & Control
Sean Harrison, Kate Tilling, Emma L Turner, Richard M. Martin, Richard M. Martin, Rosie J. Lennon, J. Athene Lane, J. Athene Lane, Jenny L Donovan, Jenny L Donovan, Freddie C. Hamdy, David E. Neal, David E. Neal, J.L.H. Ruud Bosch, Hayley E Jones 
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Stephanie E Bonn, Arvid Sjölander, Annika Tillander, Fredrik Wiklund, Henrik Grönberg, Katarina Bälter, Katarina Bälter 
Association of body mass index and prostate cancer mortality

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01 Jul 2014-Obesity Research & Clinical Practice
Reina Haque, Stephen K. Van Den Eeden, Lauren P. Wallner, Kathryn Richert-Boe, Bhaskar Kallakury, Renyi Wang, Sheila Weinmann 
Relationship between prostate-specific antigen and obesity in prostate cancer screening: Analysis of a large cohort in Japan

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01 Jan 2011-International Journal of Urology
Yasuaki Kubota, Kensaku Seike, Shin-ichi Maeda, Yuka Shinohara, Masamitsu Iwata, Norio Sugimoto 
Obesity and the risk of prostate cancer (United States).

[...]

01 Jun 2005-Cancer Causes & Control
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Frequently Asked Questions (7)
Q1. What are the contributions mentioned in the paper "Systematic review and meta‐analysis of the associations between body mass index, prostate cancer, advanced prostate cancer, and prostate‐specific antigen sean harrison1,2 · kate tilling1,2 · emma l. turner1 · richard m. martin1,3 · rosie lennon4 · j. athene lane1,3 · jenny l. donovan1,5 · freddie c. hamdy6 · david e. neal6,7 · j. l. h. ruud bosch8 · hayley e. jones1" ?

The authors conducted this review to estimate the associations between BMI and ( 1 ) prostate cancer, ( 2 ) advanced prostate cancer, and ( 3 ) PSA. The authors performed random-effects meta-analysis of linear associations of log-PSA and prostate cancer with BMI and, to examine potential non-linearity, of associations between categories of BMI and each outcome. 

Meta‑regressionMeta-regression [33] was used to determine if the effect estimates from individual studies included in the metaanalyses varied by study-level factors. 

PCPT onlyincluded men with a PSA less than 3.0 ng/ml, biasing both the BMI-PSA and BMI-prostate cancer analyses, and as such was excluded from the meta-analyses due to the critical risk of bias from conditioning on a collider or outcome. 

because the studies may not have used the same definition of advanced prostate cancer, and because advanced prostate cancers could be locally advanced prostate cancer, nodes or metastatic cancer, these studies may be relatively heterogeneous. 

For the randomeffects meta-analysis, the average HR for prostate cancer between overweight and normal weight men was estimatedto be 1.02 (95% CI 0.98–1.05, p = 0.35) with no evidence of heterogeneity (I2 = 0.0%, p = 0.66), and the average OR was estimated to be 0.99 (95% CI 0.91–1.08, p = 0.81, combined across ORs for BMI measured before and at the same time as prostate cancer diagnosis) with little evidence of heterogeneity (I2 = 32.6%, p = 0.19). 

For the randomeffects meta-analysis, the average percentage change in PSA between overweight and normal weight men was estimated to be −  3.43% (95% CI −  5.57 to −  1.23,1 3p = 0.002), with strong evidence of heterogeneity across studies (I2 = 80.9%, p < 0.001), and the average percentage change in PSA between obese and normal weight men was estimated to be − 12.9% (95% CI − 15.2 to − 10.7, p < 0.001), with strong evidence of heterogeneity across studies (I2 = 69.5%, p < 0.001). 

This work was supported by Cancer Research UK project Grants C11043/ A4286, C18281/A8145, C18281/A11326, and C18281/A15064 and a programme grant (the CRUK Integrative Cancer Epidemiology Programme, ICEP: C18281/A19169).