Pelvic Inflammatory Disease and the Risk of Ovarian Cancer and Borderline Ovarian Tumors: A Pooled Analysis of 13 Case-Control Studies

Risk factors in progression from endometriosis to ovarian cancer: a cohort study based on medical insurance data

Objective

The objective was to identify risk factors that were associated with the progression from endometriosis to ovarian cancer based on medical insurance data.

Methods

The study was performed on a dataset obtained from the National Health Insurance Research Database, which covered all the inpatient claim data from 2000 to 2013 in Taiwan. The International Classification of Diseases (ICD) code 617 was used to screen the dataset for the patients who were admitted to hospital due to endometriosis. They were then tracked for subsequent diagnosis of ovarian cancer, and available biological, socioeconomic and clinical information was also collected. Univariate and multivariate analyses were then performed based on the Cox regression model to identify risk factors. C-index was calculated and cross validated.

Results

A total of 229,617 patients who were admitted to hospital due to endometriosis from 2000 to 2013 were included in the study, out of whom 1,473 developed ovarian cancer by the end of 2013. A variety of factors, including age, residence, hospital stratification, premium range, and various comorbidities had significant impact on the progression (p<0.05). Among them, age, urbanization of residence, hospital stratification, premium range, post-endometriosis childbearing, pelvic inflammation, and depression all had independent, significant impact (p<0.05). The validated C-index was 0.69.

Conclusion

For a woman diagnosed with endometriosis, increased age, residing in a highly urbanized area, low or high income, depression, pelvic inflammation, and absence of childbearing post-endometriosis all put her at high-risk to develop ovarian cancer. The findings may be of help to gynecologists to identify high-risk patients.

Menstrual pain and risk of epithelial ovarian cancer: Results from the Ovarian Cancer Association Consortium

Menstrual pain, a common gynecological condition, has been associated with increased risk of ovarian cancer in some, but not all studies. Furthermore, potential variations in the association between menstrual pain and ovarian cancer by histologic subtype have not been adequately evaluated due to lack of power. We assessed menstrual pain using either direct questions about having experienced menstrual pain, or indirect questions about menstrual pain as indication for use of hormones or medications. We used multivariate logistic regression to calculate the odds ratio (OR) for the association between severe menstrual pain and ovarian cancer, adjusting for potential confounders and multinomial logistic regression to calculate ORs for specific histologic subtypes. We observed no association between ovarian cancer and menstrual pain assessed by indirect questions. Among studies using direct question, severe pain was associated with a small but significant increase in overall risk of ovarian cancer (OR = 1.07, 95% CI: 1.01-1.13), after adjusting for endometriosis and other potential confounders. The association appeared to be more relevant for clear cell (OR = 1.48, 95% CI: 1.10-1.99) and serous borderline (OR = 1.31, 95% CI: 1.05-1.63) subtypes. In this large international pooled analysis of case-control studies, we observed a small increase in risk of ovarian cancer for women reporting severe menstrual pain. While we observed an increased ovarian cancer risk with severe menstrual pain, the possibility of recall bias and undiagnosed endometriosis cannot be excluded. Future validation in prospective studies with detailed information on endometriosis is needed.

Current Gaps in Ovarian Cancer Epidemiology: The Need for New Population-Based Research

With recent ovarian cancer screening studies showing no clinically significant mortality benefit, preventing this disease, identifying high-risk populations, and extending survival remain priorities. However, several challenges are impeding progress in ovarian cancer research. With most studies capturing exposure information from 10 or more years ago, evaluation of how changing patterns of exposures, such as new oral contraceptive formulations and increased intrauterine device use, might influence ovarian cancer risk and survival is difficult. Risk factors for ovarian cancer should be evaluated in the context of tumor histotypes, which have unique molecular features and cells of origin; this is a task that requires large collaborative studies to achieve meaningful sample sizes. Importantly, identification of novel modifiable risk factors, in addition to those currently known to reduce risk (eg, childbearing, tubal ligation, oral contraceptive use), is needed; this is not feasibly implemented at a population level. In this Commentary, we describe important gaps in knowledge and propose new approaches to advance epidemiologic research to improve ovarian cancer prevention and survival, including updated classification of tumors, collection of data on changing and novel exposures, longer follow-up on existing studies, evaluation of diverse populations, development of better risk prediction models, and collaborating prospectively with consortia to develop protocols for new studies that will allow seamless integration for future pooled analyses.

The inflammatory potential of diet and ovarian cancer risk: results from two prospective cohort studies

BACKGROUND

We used a food-based empirical dietary inflammatory pattern (EDIP) score to investigate whether diets with higher inflammatory potential are associated with increased ovarian cancer risk.

METHODS

We followed 186 314 women in the Nurses' Health Study and Nurses' Health Study-II, from 1984 to 2013, to examine associations between EDIP scores and ovarian cancer risk, using Cox regression analyses.

RESULTS

During 3 454 514 person-years of follow-up, 989 ovarian cancer cases were identified. In pooled multivariable-adjusted analyses, higher EDIP scores (more pro-inflammatory diets) were not significantly associated with ovarian cancer risk (HRquintile5vs1 0.99; 95% CI: 0.80-1.22; P-trend=0.97). Similarly, we found no evidence of heterogeneity by histologic subtype (P-heterogeneity=0.52) or by tumour aggressiveness (P-heterogeneity=0.63).

CONCLUSIONS

In contrast with two previous case-control studies that found a positive association between a literature-derived nutrient-based dietary inflammatory index and ovarian cancer risk, our prospective analyses using a food-based score observed no evidence of an association.

Pelvic inflammatory disease and the risk of ovarian cancer: a meta-analysis

PURPOSE

Previous studies on pelvic inflammatory disease (PID) and the risk of ovarian cancer have found inconsistent results. We performed an updated meta-analysis to summarize the evidence of this association.

METHODS

PubMed, Embase, and ISI web of science databases were searched through October 2016 for studies that investigated the PID and ovarian cancer association. Summary risk estimates were calculated using random-effects meta-analysis.

RESULT

Thirteen studies were eligible for analysis, which included six cohort studies and seven case-control studies. PID was associated with an increased risk of ovarian cancer overall [relative risk (RR) 1.24, 95% CI 1.06-1.44; I ²  = 58.8%]. In analyses stratified by race, a significant positive association was observed in studies conducted among Asian women (RR 1.69, 95% CI 1.22-2.34; I ²  = 0%), but marginally significant among Caucasians (RR 1.18, 95% CI 1.00-1.39; I ²  = 60.7%).Risk estimates were elevated in both cohort (RR1.32; 95% CI 1.05-1.66; I ²  = 64.7%) and case-control studies (RR 1.17; 95% CI 0.93-1.49; I ²  = 57.6%), albeit not statistically significant in case-control studies.

CONCLUSIONS

Our results suggested that PID might be a potential risk factor of ovarian cancer, with pronounced associations among Asian women. Large and well-designed studies with objective assessment methods, such as hospital records, are needed to confirm the findings of this meta-analysis.