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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Prostate Cancer Prostatic Dis. Author manuscript; available in PMC May 3, 2011.
Published in final edited form as:
PMCID: PMC3085982
NIHMSID: NIHMS284136
DOES PRE-EXISTING DIABETES AFFECT PROSTATE CANCER PROGNOSIS? A SYSTEMATIC REVIEW
Claire F. Snyder, PhD,abc Kelly B. Stein, MD,a Bethany B. Barone, ScM,d Kimberly S. Peairs, MD,a Hsin-Chieh Yeh, PhD,ad Rachel L. Derr, MD,a Antonio C. Wolff, MD,b Michael A. Carducci, MD,b and Frederick L. Brancati, MD, MHSad
aDepartment of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
bDepartment of Oncology, Johns Hopkins School of Medicine, Baltimore, MD, USA
cDepartment of Health Policy & Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
dDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
Corresponding Author: Claire Snyder, PhD Assistant Professor of Medicine Division of General Internal Medicine Johns Hopkins School of Medicine 624 N. Broadway, Room 657 Baltimore, MD 21205 Phone: 443/287-5469 Fax: 410/955-0470 ; csnyder/at/jhsph.edu
Objectives
To summarize the influence of pre-existing diabetes on mortality and morbidity in men with prostate cancer.
Methods
We searched MEDLINE and EMBASE from inception through October 1, 2008. Search terms were related to diabetes, cancer, and prognosis. Studies were included if they reported an original data analysis of prostate cancer prognosis, compared outcomes between men with and without diabetes, and were in English. Titles, abstracts, and articles were reviewed independently by two authors. Conflicts were settled by consensus or third review. We abstracted data on study design, analytic methods, outcomes, and quality. We summarized mortality and morbidity outcomes qualitatively and conducted a preliminary meta-analysis to quantify the risk of long-term (>3 months), overall mortality.
Results
11 articles were included in the review. 1/4 studies found increased prostate-cancer mortality, 1/2 studies found increased non-prostate cancer mortality, and 1/1 study found increased 30-day mortality. Data from 4 studies could be included in a preliminary meta-analysis for long-term, overall mortality and produced a pooled hazard ratio of 1.57 (95% CI: 1.12-2.20). Diabetes was also associated with receiving radiation therapy, complication rates, recurrence, and treatment failure.
Conclusions
Our analysis suggests that pre-existing diabetes affects the treatment and outcomes of men with prostate cancer.
Keywords: diabetes, prostate cancer, prognosis, meta-analysis
The American Cancer Society estimates that, in 2009, there will be 192,280 new cases of prostate cancer in the US,1 and approximately 63% of those cases will be diagnosed in men age 65 years or older.2 Because prostate cancer tends to affect older men, prostate cancer patients are likely to have other comorbid conditions. In fact, about 62% of people age 65 and older have two or more chronic conditions.3 One of the most common chronic conditions in older adults is diabetes. An estimated 23.6 million people in the US have diabetes mellitus, representing approximately 8% of the adult population.4 Diabetes rates in the population older than 65 is even higher: an estimated 15.3%.5
A recent meta-analysis found that pre-existing diabetes was associated with worse overall, long-term mortality in cancer patients generally.6 However, the impact of diabetes varied across different cancer types (ranging from 1.09 for pancreas to 1.76 for endometrial), suggesting the need to evaluate specific cancers individually. One reason that prostate cancer warrants particular attention is that a meta-analysis by Kasper et al.7 demonstrated a decreased risk of incident prostate cancer among men with diabetes (pooled relative risk: 0.84; 95% confidence interval (CI): 0.76-0.93), raising the question of whether this protective effect extends to prognosis among men who do get prostate cancer. However, little research has been conducted in this area. Diabetes could have important implications for treatment selection and outcome in prostate cancer patients, but no systematic reviews have been conducted to test how pre-existing diabetes affects mortality and other important outcomes. Because of the indolent nature of prostate cancer and the long-term expected survival associated with it, attention to modifiable conditions like diabetes and its potential influence on morbidity and mortality is warranted.
We conducted a systematic literature review to summarize and synthesize diabetes’ impact on prostate cancer management and prognosis. We also wanted to quantify the impact of pre-existing diabetes on prostate cancer-specific and overall mortality. While there was insufficient evidence to conduct a formal meta-analysis of prostate cancer-specific mortality, we were able to conduct a preliminary assessment of diabetes’ impact on overall, long-term mortality.
Objectives
This systematic review and meta-analysis was conducted to summarize and quantify the effect of pre-existing diabetes on mortality among prostate cancer patients. We also examined and summarized the impact of pre-existing diabetes on non-mortality outcomes.
Literature Search
We searched the MEDLINE and EMBASE databases from inception to October 1, 2008, to identify articles that addressed the relationship between pre-existing diabetes and cancer prognosis. Search terms were related to diabetes (e.g., diabetes, glucose intolerance, hyperglycemia), cancer (e.g., cancer, malignant neoplasm), and prognosis (e.g., mortality, survival, recurrence). Articles were limited to English-language, human studies. We also reviewed the reference lists of included articles to identify any other studies that were not captured through the initial literature search.
To be included in this review, articles had to (1) evaluate prognosis by glycemic status, (2) include patients with prostate cancer, and (3) contain an original data analysis. Articles were excluded if the study (1) included non-cancer patients, (2) included only subjects with diabetes, (3) did not analyze a prognostic outcome, (4) was a case report, or (5) was not in English. To evaluate studies’ eligibility for inclusion, titles, abstracts, and articles were reviewed independently by two authors; discrepancies were resolved by a third reviewer or by consensus. To be included in the meta-analysis, the articles had to provide a risk estimate (e.g., hazard ratio, relative risk) and a measure of precision (e.g., confidence interval) for the impact of pre-existing diabetes on overall, long-term (>3 months) mortality. Authors of articles that only reported that diabetes was “not significant” were contacted to obtain the actual estimates and precision measures.
Data Abstraction and Analysis
The following data were abstracted from included articles: sample size, data source, study recruitment years, study eligibility criteria, length of follow-up, outcome assessed, risk estimate, and confounders adjusted for in models. All studies were evaluated for quality based on population source, method of diabetes and outcome ascertainment, and statistical methods. Each article was abstracted by one author, and a second author reviewed the abstraction for accuracy.
We summarized qualitatively diabetes’ impact on prostate cancer-specific mortality, non-prostate cancer mortality, overall mortality, and other mortality outcomes. We also summarized diabetes’ influence on non-mortality outcomes. There was sufficient data to conduct a preliminary meta-analysis for overall, long-term mortality by diabetes status but not the other outcomes. Based on the Q-statistic (12.76 on 3 degrees of freedom, p=0.005) and I2 of 76.5%, we determined there was substantial between-study heterogeneity and therefore used a DerSimonian-Laird random-effects model for the meta-analysis. Begg’s (p>0.99) and Egger’s (p=0.43) tests did not find evidence of publication bias. However, we conducted a sensitivity analysis using Duval and Tweedie’s8 nonparametric “trim and fill” to assess the effect of hypothetical missing studies since we were unable to include two nonsignificant studies with insufficient reporting.
Literature Search
Figure 1 illustrates the steps in the evaluation of the articles for inclusion in the review and meta-analysis. The literature search identified 8208 titles, of which 7473 were excluded, leaving 735 abstracts. There were 486 abstracts that did not meet our eligibility criteria and were excluded, leaving 249 articles for further review. Based on the review of the 249 articles, 97 provided some estimate of diabetes’ impact on cancer prognosis, and 4 additional articles were identified by searching references. Of the 101 articles, 119-19 addressed the impact of diabetes on prostate cancer in particular and were included in this review. The Merrick 2007 article15 reports an expansion and extension of a previous publication.14
Figure 1
Figure 1
Flowchart of Literature Search and Review
Study Description and Quality Assessment
The majority of the studies were conducted in the United States (n=7). 9,10,13-15,17,19 The other four studies were conducted in Korea,16 Germany,11 Sweden,12 and the Netherlands.18 All of the studies were published within the past 10 years: 2 studies in 1999,13,19 2 in 2003,10,11 3 in 2005,9,12,14 1 in 2006,16 2 in 2007,15,18 and 1 in 2008.17 The sample sizes ranged from 25616 to 13,398.19
The four studies included in the meta-analysis were all deemed high quality by our review.15-18 Two were population-based cohorts16,18 and two were groups of patients undergoing radiation therapy.15,17 All four studies used blood test or medical records to ascertain diabetes. Two studies used national registries,16,18 one used medical records,15 and one used active study follow-up17 to determine vital status. Each study used adjusted Cox proportional hazards models. Though all of the studies adjusted for age, other covariates varied across studies (see Table 1). Of the remaining seven studies included in the review, six used medical records to ascertain diabetes status,10-14,19 and one used self-report.9 Three used national registries to determine vital status,10,12,19 one used active follow-up,9 and the remaining three used medical records.11,13,14 Though outcomes varied, all studies used more sophisticated statistical methods with regression models.
Table 1
Table 1
Studies Reporting the Quantitative Impact of Diabetes on Overall Mortality*
Diabetes and Mortality
Of the 11 studies included in the systematic review, 4 assessed prostate cancer-specific mortality, 2 assessed non-prostate cancer mortality, 1 assessed 30-day mortality, and 6 assessed overall, long-term mortality (Tables (Tables11 and and2).2). Hammarsten et al.12 was the only study to find an elevated risk of prostate cancer-specific mortality among men with type 2 diabetes (estimate not reported; p=0.035). They examined 320 men who were seen in the Urological Section at a Swedish hospital between 1995 and 2002. Three other studies that evaluated prostate cancer-specific mortality did not find statistically significant relationships. Merrick et al.15 investigated prostate cancer-specific mortality among 530 men who had undergone brachytherapy at least three years prior but did not find a significant relationship in univariate analyses (p=0.712), so diabetes was not included in the multivariate analyses. Smith et al.17 evaluated 1551 men with prostate cancer participating in a randomized controlled trial of radiation therapy with short- versus long-term adjuvant goserelin for locally advanced prostate cancer. In its evaluation of prostate cancer-specific mortality, they found a hazard ratio of 0.80 (95% CI: 0.51-1.25; p=0.32). Froehner et al.11 reported only that diabetes was not significantly associated with prostate cancer mortality.
Table 2
Table 2
Impact of Diabetes on Other Mortality Outcomes*
Similarly, Froehner et al.11 evaluated non-cancer mortality but again reported only that diabetes was not significant. In contrast, Smith et al.17 did find a significant association between diabetes and non-prostate cancer mortality (hazard ratio: 2.12; 95% CI: 1.69-2.66; p<0.0001). Wilt et al. examined the 30-day mortality outcomes for 13,398 men in the Veterans Administration database who underwent radical prostatectomy between 1986 and 1996.19 They found that pre-existing diabetes was associated with increased odds of 30-day mortality (odds ratio: 1.87; 95% CI: 1.11-3.15; p=0.02), after adjusting for a number of factors. Thus, 1 of 4 studies found increased prostate cancer-specific mortality, 1 of 2 studies found increased non-prostate cancer mortality, and 1 of 1 study found increased 30-day mortality.
Six studies reported on the impact of pre-existing diabetes on overall, long-term mortality (Table 1).10-11,15-18 Merrick et al. found a hazard ratio for mortality of 2.41 (p=0.011) for men with versus without diabetes.15 van de Poll-Franse investigated diabetes’ impact in 5478 men in the Eindhoven cancer registry who were 3 to 10 years post-diagnosis.18 They also found an elevated risk (hazard ratio: 1.19; 95% CI: 1.04-1.37). The Smith et al. study17 found increased mortality among men with diabetes (hazard ratio: 1.77; 95% CI: 1.45-2.16). Park et al.16 used the Korean cancer registry to investigate the impact of glucose tolerance on survival. Men with a fasting serum glucose (FSG) 126 or greater had a nonsignificantly increased risk compared to men with FSG<110 (hazard ratio: 1.81; 95% CI: 0.61-5.40). Two other studies found non-significant relationships between pre-existing diabetes and long-term, overall mortality in prostate cancer patients, but did not report numeric risk estimates and did not report the direction of effect.10,11 We attempted to contact these authors, but they were either unable to provide the needed estimates or did not respond. Combining the hazard ratios from the four studies with sufficient reporting in a random-effects model produced a pooled hazard ratio of 1.57 (95% CI: 1.12-2.20; p=0.008) (Figure 2). In a sensitivity analysis using the nonparametric trim and fill method which adjusts for publication bias, the pooled hazard ratio was attenuated but remained statistically significant with a hazard ratio of 1.47 (95% CI: 1.08-2.00; p=0.015).
Figure 2
Figure 2
Meta-Analysis of the Impact of Pre-Existing Diabetes on Overall, Long-Term Mortality
Diabetes and Non-Mortality Outcomes
Five studies examined the impact of pre-existing diabetes on a variety of non-mortality outcomes, including treatment choice, complications and acute morbidities, treatment failure, and recurrence.9,13,14,15,18 Two studies found that diabetes affected treatment choice.9,18 Specifically, among prostate cancer patients aged 35 to 64, men with diabetes were more likely to receive treatment with radiotherapy versus men without diabetes (odds ratio: 2.24; 95% CI: 1.29-3.87), although no differences were found between men with and without diabetes for surgery or hormonal therapy and no differences were found for men age 65 and older.18 Similarly, Chan et al. found that compared to surgery, men with diabetes were more likely to undergo external beam radiation (OR: 1.54; 95% CI: 1.12-2.13) or hormonal therapy (OR: 1.63; 95% CI: 1.17-2.27), but they found no difference in brachytherapy or watchful waiting.9
Herold et al.13 found no difference in acute morbidities between men with and without diabetes receiving radiotherapy, but they did find differences in late complications. There was a higher 5-year actuarial rate of combined Grades 2 to 4 gastrointestinal and genitourinary late complications for men with versus without diabetes (34% vs. 23%, p=0.013).
In both the original Merrick study and its extension, there was no association between diabetes and biochemical progression-free survival.14,15 In terms of cancer recurrence, Chan et al.9 found no association in an overall analysis by diabetes status for patients undergoing surgery or radiation therapy; however, among patients undergoing radiation therapy stratified by prognostic risk, patients in the low-risk group who were diabetic were more likely to recur (hazard ratio: 3.79; 95% CI: 1.28-11.19; p=0.01). Also, among men who underwent radiation therapy and who were age 69 or younger at diagnosis, diabetic status was associated with reduced time to treatment failure (hazard ratio=2.17; 95% CI: 1.02-4.62, p=0.04).9
Diabetes and prostate cancer are both prevalent conditions in older men; however, little research has been conducted to evaluate the impact of pre-existing diabetes on prostate cancer treatment and outcomes. We conducted a systematic review to summarize the research to date on how diabetes affects prostate cancer mortality and morbidity. We also conducted a preliminary meta-analysis to quantify the effects of diabetes on long-term, overall mortality. While only four studies could be included in this meta-analysis, resulting in a pooled hazard ratio of 1.57 (95% CI: 1.12-2.20), perhaps of greater importance is the lack of evidence to conduct even a preliminary meta-analysis of the impact of diabetes on prostate cancer-specific mortality. Because diabetes is associated with worse mortality in general (aside from any cancer diagnosis), it is particularly important to investigate diabetes’ influence on prostate cancer-specific outcomes, and future research should focus on this area. Studies conducted to date indicate mixed results regarding the impact of diabetes on prostate cancer-specific and non-prostate cancer mortality. Additional research is critical to inform our understanding of whether the difference found in overall mortality is cancer-related, non-cancer related, or both. Diabetes was also associated with differences in treatment selection, complications, and recurrence.
What might explain an adverse biological interaction between diabetes mellitus and prostate cancer? As discussed in our previous paper,6 an environment of hyperinsulinemia and hyperglycemia might lead to increased tumor proliferation and metastasis. In vitro, insulin appears to be a growth factor for prostatic epithelia.20 Insulin-like growth factor-1 (IGF-1) and IGF binding protein-3 are also associated with prostate growth.21-22 Such findings have prompted the development of IGF receptor inhibitors, and prostate cancer has been cited as a tumor type that may benefit from treatment with such agents. Studies are underway to elucidate further the biology of diabetes mellitus, IGF, and prostate cancer.
There might also be biological interactions with regards to the effects of radiotherapy. Chan et al. found that younger men with diabetes who received radiotherapy had a shorter time to treatment failure.9 Herold et al. found that men with diabetes who underwent radiotherapy had higher rates of gastrointestinal and genitourinary late complications than men without diabetes.13 Potential biologic mechanisms for these worse outcomes among men with diabetes include alterations in IGF, its receptors, and their signaling pathways that may affect resistance to treatment.23 For example, heme oxygenase -1 and clusterin are up-regulated in diabetes mellitus and associated with worse treatment outcomes.24-25
There are at least two additional circumstances in which prostate cancer therapy can adversely interact with pre-existing diabetes. First, androgen-deprivation therapy initiation might aggravate insulin resistance and provoke deterioration in glycemia and/or dyslipidemia. Second, use of corticosteroids (e.g. in combination with docetaxel) can immediately aggravate glycemia and heighten diabetes-related susceptibility to bacterial infection. Further research should explore the biologic mechanisms for differences in treatment outcomes and evaluate whether differences in outcomes are related to selection bias or are related to the treatment itself.
This study benefits from rigorous methods, including a comprehensive, systematic review of the literature. The study team included experts in multiple disciplines, including cancer, diabetes, and epidemiology. All steps of the process involved two levels of review with disagreements addressed by consensus or a third review. Nevertheless, there are some limitations to our study that warrant mention. One challenge was the heterogeneity of studies in terms of the populations included and the outcomes assessed. For the four studies included in the meta-analysis, each used adjusted multivariate Cox proportional hazards models, and we allowed for between-study differences by using a random-effects model. However, two of the studies used population-based cohorts while two studies used cohorts undergoing radiation therapy, so these results should be interpreted with caution. Though we do not know the direction of effect in the two studies we were unable to include due to insufficient reporting, we are reassured by the consistent result of our sensitivity analysis. Variation in study design and other quality components across the 11 studies included in the systematic review may limit conclusions.
Perhaps the most important finding from this review is the lack of research investigating how diabetes affects prostate cancer prognosis. As noted above, only 11 studies addressed this issue. Six of those 11 studies estimated diabetes’ impact on overall, long-term mortality, but only four studies addressed the more important question of whether diabetes affects prostate cancer-specific mortality. Because both prostate cancer and diabetes are common conditions among older men, significantly more research is needed to investigate how diabetes affects prostate cancer management and prognosis and on the proper management of men with prostate cancer who have comorbid diabetes. Important research questions include whether men with diabetes should get different treatments than men without diabetes and what the appropriate treatments are. For example, are men with diabetes indeed more likely to receive radiotherapy? Are the worse outcomes and increased complication rates associated with radiotherapy in men with diabetes due to selection bias or a direct result of the disease? Would a modified radiotherapy regimen for men with diabetes improve the benefit to risk ratio? Can tighter control of diabetes improve survival for men with prostate cancer more generally? In all cases, additional research should use rigorous methods for diabetes ascertainment, sufficient follow-up time, and appropriate adjustment for confounders. The findings of this review and meta-analysis clearly support the need for further research in this area.
Acknowledgments
Funding Sources and Conflict of Interest Disclosure: Dr. Snyder is supported by a Mentored Research Scholar Grant from the American Cancer Society (MRSG-08-011-01-CPPB). Ms. Barone and Dr. Derr are supported by the NIDDK Diabetes and Obesity Training Grant (T32 DK062707). Dr. Stein is supported by a NIH fellowship from Health Services and Administration (T32HP10025-14). Dr. Brancati is supported by the NIDDK Patient Oriented Research in Type 2 Diabetes Grants (K24-DK62222). Drs. Yeh and Brancati are supported by the NIDDK Diabetes Research and Training Center (P60 DK079637). No funding body had a role in study design, data collection, analysis, or reporting. The authors declare no conflict of interest.
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