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- Materials and methods
Ovarian cancer remains the most fatal gynaecological malignancy. Although relatively uncommon, afflicting ∼ 1 of 60 women , the high mortality rate makes this disease a major health concern. The high mortality rate arises from the lack of an effective screening approach  combined with the limited success of the current therapy for advanced disease . Strategies that focus on prevention may therefore provide the most rational approach for meaningful reductions in deaths attributable to ovarian carcinoma.
Analgesics have been suggested as potential chemopreventive agents. However, a recent meta-analysis failed to find evidence for a beneficial role of nonsteroidal anti-inflammatory drugs (NSAIDs) in the chemoprevention of ovarian cancer .
Several epidemiological studies have also examined paracetamol as a potential chemopreventive agent. However, the findings from these studies are inconsistent. Some indicated risk reductions in ovarian cancer with consumption of paracetamol, while others found no association.
Because of the widespread use of paracetamol, an association with a decreased ovarian cancer risk may have important public health implications. The nonconclusive nature of the epidemiological evidence prompted us to conduct a detailed meta-analysis of the studies published on the subject in peer-reviewed literature.
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- Materials and methods
To the best of our knowledge, this is the first meta-analysis of published studies that evaluates paracetamol for ovarian cancer prevention. Our pooled results of observational studies suggest a protective association between paracetamol use and ovarian cancer (random-effects model RR = 0.84, 95% CI 0.70, 1.00). When the analysis was restricted to the studies that evaluated consumption of paracetamol in relation to ovarian cancer incidence, the heterogeneity decreased and the calculated effect estimate was identical in both a fixed- and a random-effects model (RR = 0.76, 95% CI 0.62, 0.93). Furthermore, our results provide evidence for a dose effect; ‘Regular use’ was associated with a statistically significant 30% reduction in the risk of developing ovarian cancer compared with non-use (random-effects model RR = 0.70, 95% CI 0.51, 0.95). On the other hand, the fact that the effect estimate was much weaker in the cohort studies questions the true nature of the association.
These results extend prior observational studies by permitting synthesis of data and providing more stable estimates of effect. Examined singly, existing observational studies did not show a consistent benefit (although none showed a harmful association), and most lacked statistical power to analyse this association adequately.
When meta-analysis of observational data is performed, consideration of study bias is critical . Existence of a bias in favour of publication of statistically significant results is well documented in the literature [31–33]. However, the likelihood of important selection or publication bias in our results is small. We did not exclude any article during the identification and selection process, and the Begg and Mazumdar test as well as the Egger’s test revealed no relation between the estimate of relative risk and study size. So, we are confident that important publication bias due to preferential publication of large studies with significant findings is unlikely to have occurred. Similarly, the tests of heterogeneity indicated very little variability between studies that cannot be explained by chance.
Nevertheless, several limitations should be considered in interpreting the results of this meta-analysis. First, our search was restricted to studies published in indexed journals. We did not search for unpublished studies or for original data. However, we did not impose any exclusion criteria with regard to language, type of publication or quality. Second, the included studies were different in terms of study design and definitions of drug exposure. We tried to explore sources of heterogeneity conducting subgroup and sensitivity analyses. However, the summary effect estimates are based on sparse and heterogeneous data, and therefore should be interpreted with caution.
Third, the sources of exposure data differ among the individual studies. Six studies [22, 24, 26–29] used personal interviews or self-administered questionnaires that are subject to recall bias. Two studies [23, 25] used automated databases that provide detailed information on dates of use and types of drugs used. This information is equally good for cases and controls irrespective of the event of interest, since it was recorded prospectively. However, studies that used prescription databases lacked information on over-the-counter use. Fourth, observational studies lack the experimental random allocation of the intervention necessary to optimally test exposure-outcome hypotheses. Thus, results may have been confounded by several factors, given that each one of the studies included in our meta-analysis controlled for somewhat different confounding factors (Table 1). Furthermore, the possibility of residual confounding of lifestyle factors should be considered, as it is possible that there may be systematic lifestyle differences between women who use paracetamol compared with those who use other painkillers.
Fifth, observational epidemiological studies of drug exposure often encounter a specific type of confounding, which is called ‘confounding by indication’. It occurs when the underlying condition, for which the drug is prescribed, rather than the drug itself, increases or decreases the risk of the outcome under study . It has been shown that paracetamol is particularly prone to this bias [21, 30]. Confounding by indication could arise due to prescription of paracetamol to treat early symptoms related to ovarian cancer. It should, certainly, produce a positive association between the drug use and ovarian cancer. If such bias exists, it would imply that the reduction in ovarian cancer risk among paracetamol users, shown in our meta-analysis, is underestimated. In other words, existence of ‘confounding by indication’ should mask the protective effect of paracetamol.
Although the epidemiological data currently available suggest a protective association between paracetamol use and ovarian cancer risk, our knowledge of the mechanisms underlying this association is incomplete. It is improbable that paracetamol reduces risk via a prostaglandin inhibitor pathway, because of its limited anti-inflammatory and prostaglandin inhibitory properties .
At present, the possible paracetamol-induced reduction of ovarian cancer risk may be attributed to three specific mechanisms of action : (i) induction of specific reproductive atrophy due to its sex-steroid resembling phenolic ring [37, 38]; (ii) reduction of glutathione pools due to its NAPQI metabolite, which may play an important role in sterilizing premalignant ovarian lesions, since they are shown to lack proper levels of glutathione ; and (iii) inhibition of ‘macrophage migration inhibitory factor’ activity, which is necessary for proper ovulation . Clearly, laboratory investigations should to be conducted to define further the biological mechanism by which paracetamol may influence risk.
In conclusion, synthesis of existing studies provides suggestive evidence for a potential role of paracetamol in the primary prevention of ovarian cancer. Although the risks (i.e. liver and chronic renal failure) of long-term use of paracetamol may outweigh the potential benefits in preventing ovarian cancer in populations at low risk for ovarian cancer, a randomized trial of paracetamol might be appropriate in high-risk populations. Mathematical models might be applied in the identification of women at high risk for ovarian cancer [41, 42]. Nevertheless, the question of whether the epidemiological evidence provides a firm basis for randomized clinical trials needs to be examined carefully, especially when the evidence comes from sparse and heterogeneous data.
Until the validity of and mechanisms for an association between paracetamol and ovarian cancer protection are better defined, this association cannot yet be regarded as one which would prompt a public health recommendation.