Journal of the National Cancer Institute Advance Access published online on October 7, 2008
JNCI Journal of the National Cancer Institute, doi:10.1093/jnci/djn324
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© The Author 2008. Published by Oxford University Press.
ARTICLES |
Breast Cancer and Use of Nonsteroidal Anti-inflammatory Drugs: A Meta-analysis
Affiliations of authors: Department of Preventive Medicine, University of Santiago de Compostela, Santiago de Compostela, Spain (BT, CRM); Center for Clinical Epidemiology and Evaluation, Vancouver Coastal Health Research Institute, The Lung Centre, Vancouver General Hospital, and Department of Medicine, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada (ME)
Correspondence to: Bahi Takkouche, MD, PhD, Department of Preventive Medicine, University of Santiago de Compostela, 15705 Santiago de Compostela, Spain (e-mail: mrbahi{at}usc.es).
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ABSTRACT |
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Background: Breast cancer is one of the leading causes of mortality among women. The use of nonsteroidal anti-inflammatory drugs (NSAIDs) may be associated with reduced risk for breast cancer, but results from these studies of the association have been inconsistent.
Methods: Studies that examined the association between risk of breast cancer and use of NSAIDs, including aspirin and ibuprofen, that were published between January 1, 1966, and July 1, 2008, were identified using Medline, EMBASE, and other databases. We performed meta-analysis by pooling studies according to the inverse of their variances and performed separate analyses of studies pooled according to aspirin use and ibuprofen use. We evaluated publication bias and study quality.
Results: A total of 38 studies (16 case–control studies, 18 cohort studies, 3 case–control studies nested in well-defined cohorts, and 1 clinical trial) that included 2 788 715 subjects were identified. The results of these studies suggest that overall, NSAID use was associated with reduced risk for breast cancer (relative risk [RR] = 0.88, 95% confidence interval [CI] = 0.84 to 0.93). Specific analyses for aspirin (RR = 0.87, 95% CI = 0.82 to 0.92) and ibuprofen (RR = 0.79, 95% CI = 0.64 to 0.97) yielded similar results.
Conclusions: This meta-analysis provides evidence that NSAID use is associated with reduced risk for breast cancer. Future research should include careful evaluation of the biologic mechanisms involved in the relationship between NSAIDs and breast cancer.
Prior knowledge Use of nonsteroidal anti-inflammatory drugs (NSAIDs), including aspirin and ibuprofen, has been associated with reduced risk of breast cancer, but the results have been inconsistent. Study design Meta-analysis of cohort studies, case–control studies, and one clinical trial that examined the association between breast cancer risk and NSAID use. Contribution NSAID use was associated with a reduced risk for breast cancer. The inverse association was also observed in analyses of studies of aspirin or ibuprofen use alone. Implications NSAID use is associated with reduced risk for breast cancer. Limitations Limitations inherent in the designs of the studies used in the meta-analysis, such as recall bias. Behaviors that are associated with NSAID use that were not adjusted for might be associated with reduced risk of breast cancer. From the Editors
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Breast cancer is a leading cause of mortality among women, resulting in more than half a million deaths worldwide each year (1). Recently, nonsteroidal anti-inflammatory dugs (NSAIDs) have received attention as being associated with reduced risk of cancer overall (2) and breast cancer in particular (3). The inhibition of cyclooxygenase (COX), the rate-limiting enzyme of prostaglandin synthesis, is hypothesized to be one of the mechanisms by which NSAIDs might reduce cancer risk (3). Prostaglandins play an important role in the accelerated proliferation of tumor tissue (4). For example, prostaglandin levels are elevated in breast cancer tissue (5), probably due to higher expression of the cyclooxygenase-2 (COX-2) enzyme in this tissue than in normal breast tissue (6). Furthermore, NSAIDs have chemopreventive activity against breast cancer in mouse models (7).
To date, results of epidemiological studies of NSAIDs and breast cancer risk have been inconsistent. Several cohort studies (8–10) have found a reduced risk of breast cancer associated with aspirin use. Others (11,12) have failed to find any association or have even suggested an increased risk. Few meta-analyses of this association have been performed, and all have methodological limitations. None was exhaustive, and none assessed heterogeneity in an in-depth manner. For example, González-Pérez et al. (4) included only 16 studies, and Mangiapane et al. (13) limited their review to 10 studies published between 2001 and 2005 that examined only aspirin use and breast cancer.
We therefore carried out an exhaustive meta-analysis on NSAID use and risk of breast cancer following the MOOSE guidelines for meta-analyses of observational studies (14). We included COX-2–nonselective inhibitors—a group that contains aspirin and ibuprofen as the most widely used drugs—as well as the more recent COX-2–selective inhibitors. Our objective was to provide a more definitive answer about a possible inverse relationship between use of these drugs and risk for breast cancer.
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Methods |
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Data Sources and Searches
We conducted a computerized Medline search covering January 1, 1966, to July 1, 2008, to identify potentially eligible studies. We applied the following algorithm to both the Medical Subject Heading and the full text: (BREAST) AND (NEOPLAS* OR CANCER* OR TUMOR* OR TUMOUR*) AND (NON STEROIDAL ANTIINFLAMMATORY* OR NSAID* OR ASPIRIN OR IBUPROFEN OR NAPROXEN OR INDOMETHACIN OR MELOXICAM OR VALDECOXIB OR CELECOXIB OR ROFECOXIB) AND (CASE-CONTROL OR CASE-REFERENT OR RETROSPECTIVE OR COHORT OR FOLLOW-UP OR PROSPECTIVE). To ensure that every article on the topic was retrieved, we performed a second search introducing the words "breast cancer," "NSAID," "aspirin," "ibuprofen," "naproxen," "indomethacin," "meloxicam," "valdecoxib," "celecoxib," and "rofecoxib" in an unstructured fashion. We used similar strategies to search EMBASE (1980–2008) and LILACS (Latin America and Caribbean) databases (1982–2008). We searched meeting abstracts using the ISI Proceedings database from its inception in 1990 to 2008. We also examined the reference list of every article retrieved and those of recent reviews of breast cancer and NSAID use (2,4,13,15,16). We considered including any relevant article, independent of the language of the publication. Unpublished studies were not considered. All searches were carried out independently by two epidemiologists (B. Takkouche and C. Regueira-Méndez), and results were merged.
Study Selection
We included those studies that met the following criteria: 1) presented original data from case–control or cohort studies (we later extended our scope to clinical trials and performed a sensitivity analysis by including and excluding those studies), 2) the outcome of interest was clearly defined as breast cancer, 3) the exposure of interest was use of any NSAID on either a regular or a nonregular basis, and 4) provided relative risk (RR) estimates and their confidence intervals (CIs) or enough data to calculate them (raw data, P value, and/or variance estimate).
We did not consider studies of benign breast diseases, and we excluded cross-sectional studies because of their methodological limitations. If data were duplicated in more than one study, only the most recent one was included in the analysis.
We developed a questionnaire and recorded study name, year of publication, study design, sample size (numbers of case patients and control subjects or cohort size), type of control subjects for case–control studies (hospital or population based), variables used for adjustment or matching, and estimates of breast cancer risk that compared exposed subjects with unexposed subjects. When several estimates were available, we used the one that was adjusted for the most variables.
Odds ratios (ORs) were considered as estimates of the RR for case–control studies (17).
Quality Assessment
Because no universal scale is available for measuring quality of observational studies, we followed the recommendations of the MOOSE guidelines and assessed the quality of key components of design separately rather than generating a single aggregate score (14). Following this recommendation, we assessed study quality based on the following five criteria, labeled as "yes" or "no": 1) whether the response rate of the original study was higher or lower than 60%, 2) whether exposure assessment included measurement of dose and duration, 3) whether adjustment for confounding included history of benign breast disease, 4) whether loss to follow-up in cohort studies was less than 20%, and 5) whether efforts had been made to ensure that the cohort did not change exposure during follow-up. In addition to the above items, for case–control studies, we assessed whether cancers were incident or prevalent and also whether control subjects were sampled from hospitals or from the general population. Throughout this assessment, when the information on a specific item was not provided by the authors, we graded this item as "no." Within each item, we calculated two pooled ORs—one for those studies that were labeled "yes" and another for those labeled "no." As a secondary analysis, we performed a pooled analysis on those studies that fulfilled more than three criteria (ie, scored 4–5, or high quality) and compared estimates of breast cancer risk from those studies with estimates from pooled analyses of studies that fulfilled three or fewer criteria (ie, scored 3 or less, or low quality). The complete protocol for quality scoring is available on request from B. Takkouche.
Data Synthesis and Analysis
We weighted the study-specific adjusted log ORs for case–control studies and log RRs for cohort studies by the inverse of their variance to compute a pooled RR and its 95% CI. We present both fixed and random effects pooled estimates but preferentially used the latter when heterogeneity was detected. The fixed effects model assumes that there is no between-study variance, ie, that the results of the studies used in the meta-analysis are homogeneous and that variation among them is due to sampling only. The random effects model, by contrast, assumes that study results are heterogeneous. The random effects model yields pooled results that are less precise (have wider CIs) but have the correct coverage probability if heterogeneity exists.
We used a version of the DerSimonian and Laird Q test that was adapted to small samples to check for heterogeneity (18). The null hypothesis of this test is the absence of heterogeneity. To quantify this heterogeneity, we calculated the proportion of the total variance due to between-study variance (Ri statistic) (18). To further explore the origin of heterogeneity, we restricted the analysis to subgroups of studies defined by study characteristics (case–control and cohort designs) and by type of control subjects (hospital or population based).
We studied the association of breast cancer risk and use of any NSAID. Where data for different intake levels were available, we subsequently restricted the analysis to the highest intake given by each study, either the highest dose or the longest duration.
We used funnel plots to visually assess publication bias. Because funnel plots have several limitations and represent only an informal approach to detect publication bias (19), we further carried out formal testing using the test proposed by Egger (20). All statistical tests were two-sided. P values less than .05 were considered statistically significant. All analyses were performed with the software HEpiMA version 2.1.3 (21) and Stata version 8.0 (StataCorp LP, College Station, TX).
To further evaluate the possibility of publication bias in case–control studies, we recalculated pooled estimates using the following extreme assumptions: 1) only half of the case–control studies ever conducted are published; 2) of the unpublished studies, half found null associations (ie, RR = 1); and 3) the average numbers of case patients and control subjects are similar in published and unpublished studies.
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Results |
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We identified 38 studies that were performed in five countries on NSAID use and risk of breast cancer that met the inclusion criteria and were included in the meta-analysis. These included 16 case–control studies, 18 cohort studies, three case–control studies nested in well-defined cohorts, and one clinical trial (Tables 1–4). Because of their characteristics (prospective collection of data, inexistence of recall bias), the nested case–control studies and the clinical trial were included in the cohort studies group.
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Use of any NSAID was associated with reduced risk of breast cancer (random effects pooled RR = 0.88, 95% CI = 0.84 to 0.93) (Table 5) in a global analysis. This association was stronger for case–control studies (random effects pooled RR = 0.81, 95% CI = 0.74 to 0.89) than for cohort studies (random effects pooled RR = 0.93, 95% CI = 0.88 to 0.98). Heterogeneity was large and did not subside after stratification by design or other characteristics, including menopausal status. The exception was stratification by country of origin (European vs North American studies), which showed that the European studies had no heterogeneity (Ri = .08), in contrast to US and Canadian studies (Ri = 0.84).
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For high intakes of NSAIDs, the RR associated with reduced risk of breast cancer (random effects pooled RR = 0.84, 95% CI = 0.77 to 0.91) was similar to the corresponding risk associated with any intake. The association was stronger among case–control studies (random effects pooled RR = 0.70, 95% CI = 0.58 to 0.83) than among cohort studies (RR = 0.92, 95% CI = 0.85 to 1.00).
Apparently, the quality of the studies did not have a major role in the association between NSAIDs intake and breast cancer because the estimates were similar between high-quality studies (ie, those that scored 4–5 on the quality scale) and low-quality studies (ie, those that scored 
3) and between fully and incompletely adjusted studies.
Use of aspirin was associated with a reduced risk of breast cancer (random effects pooled RR = 0.87, 95% CI = 0.82 to 0.92) (Table 6). Again, the association was stronger among case–control studies (random effects pooled RR = 0.79, 95% CI = 0.72 to 0.86) than cohort studies (RR = 0.92, 95% CI = 0.86 to 0.97). High intakes did not increase the magnitude of the association.
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Because of its characteristics, we checked whether the clinical trial by Cook et al. (22) influenced our results. We repeated the analysis without this study and obtained identical results (data not shown).
Use of ibuprofen was also associated with reduced risk for breast cancer, with point estimates close to those observed for aspirin (random effects pooled RR = 0.79, 95% CI = 0.64 to 0.97) (Table 6). As with aspirin intake, high intake of ibuprofen did not increase the magnitude of the association.
We found no evidence of publication bias using the Egger regression test (P = .34 for any NSAID use and P = .17 for aspirin use). To check for publication bias in the case–control studies, we recalculated the pooled RRs under conservative assumptions (see "Methods" for details). The point estimates of the pooled RRs remained less than 1 for any NSAID use and for aspirin use.
Data on celecoxib and rofecoxib use were available in only two studies (23,24). The random effects pooled RRs for breast cancer were 0.47 (95% CI = 0.10 to 2.25) for celecoxib use and 0.60 (95% CI = 0.27 to 1.32) for rofecoxib use.
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Discussion |
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TopAbstractContext and CaveatsMethodsResultsDiscussionFundingReferencesNotes |
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This meta-analysis shows that overall, NSAID use is associated with reduced risk for breast cancer. The results were similar for use of any NSAIDs, aspirin, and ibuprofen. In general, the association was stronger for case–control studies than cohort studies, possibly due to recall bias. Unlike Harris et al. (2), who found a stronger association with intake of ibuprofen than with aspirin in their 2005 meta-analysis, we did not observe any meaningful difference in the magnitude of the associations between the use of these two drugs and risk of breast cancer. That meta-analysis (2) was based on four studies of ibuprofen and 15 studies of aspirin, whereas our meta-analysis included eight studies on ibuprofen and 27 studies on aspirin.
We did not find evidence that high intakes (either higher doses or longer duration) were associated with a greater reduction in breast cancer than any intakes, especially for aspirin and ibuprofen use. There are several plausible explanations for this lack of gradient of risk reduction. One is that the level of distortion in the relationship between NSAID use and breast cancer exerted by confounders may be different for each level of exposure. It is also possible that the relationship between NSAID use and breast cancer is not linear. Indeed, Ready et al. (25) argued that the dose–response relationship may be U-shaped, which may mask a possible stronger association at high intake levels. It is also possible that it is the combination of frequency and duration of use, rather than each of those characteristics assessed individually, that has a major role in the association between NSAID use and breast cancer. Finally, we cannot rule out the possibility of chance.
Our meta-analysis has some limitations. As a meta-analysis of observational studies it may be subject to limitations, such as residual confounding, that meta-analyses of randomized clinical trials do not have. Also, the quality of the individual studies may largely influence the results of the review. In addition, because no universally validated scale of study quality exists, we used a scale that was based on items that were selected based on common sense only. It is possible that a different scale would yield other results. In addition, because of the absence of data, we did not take into account possible interactions with other drugs. However, use of aspirin and other NSAIDs is frequently associated with the use of other drugs, and the associations observed may be difficult to untangle (26). Furthermore, residual confounding may have distorted the results, as in any meta-analysis of observational studies. For example, genetic polymorphisms of the COX-2 gene, especially the variant COX-2.8473, may have had the role of undetected confounders, as shown in one case–control study (27). In that study, the variant allele was associated with a lower risk for breast cancer among those subjects who had used NSAIDs. However, other variant alleles of the same gene did not have such an association.
In summary, the large number of studies included, the magnitude of the associations found, the consistency of the results through settings, and the existence of a mechanism that gives strong biologic plausibility to the relationship, provide evidence that NSAID use is associated with reduced risk for breast cancer. Future research should include careful evaluation of the molecular mechanisms involved in the relationship between NSAIDs and breast cancer.
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Funding |
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"CIBER en Epidemiología y Salud Pública" (CIBER-ESP), Spain (B.T. and C.R.-M.); Canadian Institutes of Health Research (postdoctoral fellowship award to M.E.).
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NOTES |
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M. Etminan, B. Takkouche, and C. Regueira-Méndez initiated the project. C. Regueira-Méndez and M. Etminan screened and extracted the data. B. Takkouche analyzed the data. All authors participated in discussing the results and writing the paper. The sponsors had no role in the study design, the data analysis, the interpretation of the results, the preparation of the manuscript, or the decision to submit the manuscript for publication.
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Manuscript received May 2, 2008; revised July 17, 2008; accepted August 6, 2008.
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