Ovarian cancer comprises a heterogeneous group of tumors with a wide variation in clinical behaviors, histologies, and molecular features. Low-grade serous epithelial ovarian cancers (LGSCs) represent about 10% of all ovarian cancers.1 In 2004, Malpica et al2 proposed a 2-tier grading system for ovarian cancer that classified grades 2 and 3 tumors as high grade and grade 1 tumors as low grade. Low-grade serous epithelial ovarian cancer comprises 1 subtype of type 1 epithelial ovarian cancers (EOCs) as proposed by Kurman and Shih.3 Patients diagnosed with LGSC are younger4,5 and live longer,5,6 and their disease is more likely to be confined to the ovary.5 Although LGSCs may arise de novo, LGSCs may arise from benign serous adenofibromas and serous tumors of low malignant potential.7 Because of the indolent nature of LGSC, optimal surgical debulking remains the frontline treatment because recurrent or persistent disease traditionally responds poorly to chemotherapeutics,8 and patients may ultimately die of the burden of their recurrent disease.9
Because of the prolonged disease course, potentially modifiable risk factors could alter the course of disease. To our knowledge, only 1 other study has investigated modifiable factors that may contribute to outcomes in women with LGSC. Schlumbrecht et al10 found that smoking had a negative association with overall survival (OS) and progression-free survival (PFS). Although not significant, patients who received hormonal consolidation (tamoxifen, letrozole, or leuprolide) after primary chemotherapy therapy had longer OS and PFS. When viewed as a single entity, nonmodifiable risk factors for EOC include a family history of ovarian cancer, increasing age, early age at menarche, and late age at menopause. Protective factors for development of EOC include increasing parity, a history of oral contraceptive use, oophorectomy, bilateral tubal ligation, and previous hysterectomy. Modifiable risk factors suspected to increase development of ovarian cancer include hormone replacement therapy (HRT), high-fat diet, obesity, smoking history, alcohol use, and inactivity.11 The relationship between body mass index (BMI), obesity, and ovarian cancer is uncertain, and there are minimal data about obesity and outcomes in women with LGSC.
Because of the rather indolent course of LGSC and lack of information regarding prognostic factors and conflicting results regarding obesity, we sought to evaluate prognostic modifiable and nonmodifiable risk factors for women with this disease.
MATERIALS AND METHODS
Each institution obtained institutional review board approval. A database was created to identify all patients diagnosed with LGSC between January 1996 and December 2010. When available, archival pathology slides were reviewed by gynecologic pathologists (S.B., S.W., and M.D.) to verify that the neoplasms were LGSC. Pathologic inclusion criteria were based on the 2-tier grading system for serous ovarian carcinoma originally described by Malpica et al.2 Briefly, serous ovarian tumors with (1) relatively uniform round to oval nuclei with mild to moderate atypia and evenly distributed chromatin, (2) 12 mitotic figures per 10 high-power fields or less, and (3) definitive stromal invasion of more than 5 mm, were considered LGSC. When pathology slides were not available, the original pathology report was reviewed, and grade 1 disease was used as a surrogate for LGSC.
From medical charts, demographic data were abstracted. Patients who were lost to follow-up were excluded from analysis. Epidemiologic risk factors for EOC that were evaluated included obesity (BMI ≥30 kg/m2), BMI, age, parity, race, smoking, history of oral contraceptive pill (OCP)/and or HRT use, previous hysterectomy, and previous surgery on fallopian tubes and/or ovaries. Other variables evaluated included stage of disease, residual disease after debulking, extent of debulking, and disease status. Information regarding residual disease and extent of debulking were obtained from the operative report. Optimal debulking was defined as residual disease less than 1 cm. Body mass index, defined as kilograms per meter squared, was used to classify patients as underweight (<18.5 kg/m2), normal weight (≥18.5 to <25.0 kg/m2), overweight (≥25.0 to <30.0 kg/m2), and obese (≥30.0 kg/m2). Cox proportional hazards modeling adjusted for age at diagnosis, status of tumor debulking, BMI, and history of use of HRT because these factors were thought to be relevant clinically.
Both univariate and multivariate Cox proportional hazards regression models were used to predict OS, disease-specific survival (DSS), and PFS. Multivariate Cox proportional hazards modeling was conducted using the backward selection technique with an α = 0.50,12 using the following candidate predictors: age at diagnosis, tumor debulking, obesity, BMI, and a history of HRT use. Overall survival was calculated from time of diagnosis to death due to any cause. For those still alive, it was censored at the last follow-up visit. Disease-specific survival was calculated from time of diagnosis to death due to disease and was censored for deaths due to other causes or at last follow-up visit for those still alive. Progression-free survival was calculated from diagnosis until first recurrence or death, whichever occurred first, and was censored for those still alive without recurrence at last follow-up visit. P < 0.05 was considered statistically significant. All statistical analyses were conducted using SAS version 9.2 (SAS Institute, Cary, NC).
Eighty-one eligible patients were identified. Median age at diagnosis was 56 years (range, 21–86 years). Thirty-four percent were obese (Table 1), and 90% had optimally debulked disease. At the study conclusion, 46% were alive, 14% with disease, whereas 25% were dead of disease, 2% died of intercurrent disease, and 27% had an unknown status (Table 1). The diagnosis of LGSC was confirmed by review of glass slides for 58 (71.6%) and by review of original pathology reports for the remaining patients (23; 28.3%).
In a univariate analysis, BMI was associated with OS. Increasing BMI was associated with a 1.4-fold increased risk of death (P = 0.05) (Table 2). More specifically, a 5-unit increase in BMI was associated with a 1.4-fold increase risk in death, whereas a 10-unit increase was associated with a 2.1-fold increase risk of death. For instance, a person with BMI of 35 or 40 kg/m2 is 2.1 times more at risk of death than a person with a BMI of 25 or 30 kg/m2, respectively. Obesity, defined as a BMI of 30.0 kg/m2 or greater, demonstrated a marginal association with worse OS (hazard ratio [HR], 2.08; confidence interval [CI], 0.93–4.66; P = 0.07) in the univariate analysis. Using a multivariate Cox proportional hazards modeling to predict OS using age at diagnosis, status of tumor debulking, BMI, and history of use of HRT, obesity was associated with OS. The obese condition was associated with a 2.8-fold increase risk of death (P = 0.04) (Table 3).
Surgical debulking and extent of residual disease were also associated with clinical outcome (Tables 2 and 3). In a univariate Cox proportional hazards model, lower extent of residual disease (P = 0.02) was associated with improved PFS, whereas optimal surgical debulking was associated with improved PFS (P = 0.01), DFS (P = 0.03), and OS (P < 0.001) (Table 2). The majority of patients (94.3%) received adjuvant chemotherapy after initial cytoreduction. Primary regimens included carboplatin/paclitaxel (80%), carboplatin (1.43%), carboplatin/topotecan (1.43%), carboplatin/paclitaxel/doxorubicin (1.43%), carboplatin/docetaxel (2.86%), cisplatin/paclitaxel (2.86%), platinum agent/cyclophosphamide (2.86%), and paclitaxel poliglumex (Xyotax) (1.43%). Because a high proportion of patients received chemotherapy, this variable was not tested in the predictive survival models. Hormonal therapy was also unable to be included in the predictive survival models because only 4 patients received tamoxifen after initial cytoreduction. Hormonal therapy was also unable to be included in the predictive survival models because only 4 patients received tamoxifen after initial cytoreduction. Debulking status was included in the multivariate model; however, because of the limited number of patients who were suboptimally cytoreduced (n = 7), we could not reliably explore associations between tumor reduction and survival (Table 3).
Prediction of DSS and PFS using the backward selection technique did not identify 2 or more variable models; therefore, multivariate models could not be constructed for DSS or PFS. There was a trend toward worse median survival for obese women with LGSC compared with nonobese women (6.5 vs 9.5 years; P = 0.07) (Fig. 1). There were no significant differences in DSS (8.4 vs 12.2 years; P = 0.5) and PFS (1.5 vs 2.6 years; P = 0.2) in obese and nonobese women with LGSC (Fig. 2). There was no significant difference in optimal cytoreduction rates in obese and nonobese patients (88% in obese vs 93% in nonobese; P = 0.7).
Body mass index and obesity were predictors of survival for women with LGSC. We evaluated body habitus based on BMI and obesity to capture the effect of different weight classification on survival. In our univariate models, BMI and obesity were associated with a significant 1.4-fold and a marginal 2.1-fold increased risk of death, respectively, but neither was associated with worse DSS. In our multivariate analysis, obesity was significantly associated with a 2.8-fold increased risk in death. In the multivariate model, the association between BMI and OS was lost. This is due to the high correlation between BMI and obesity. At the time of the analysis, 25% of the study population died. Longer follow-up is needed to determine the magnitude of obesity’s effect on survival in the patient population with a less aggressive tumor biology. Previously, Schlumbrecht et al10 reported that patients with a BMI of 35 kg/m2 or greater were identified as having a greater likelihood of dying (HR, 2.53; 95% CI, 1.19–5.38; P = 0.02).10 While one of the cutoffs for the study by Schlumbrecht et al10 was BMI of 35 kg/m2 or greater and ours used BMI of 30 kg/m2 or greater, the HRs were comparable (2.53 vs 2.8). Furthermore, BMI assessed as a continuous variable was also associated with worse survival outcomes (HR, 1.02; 95% CI, 1.00–1.1; P = 0.05).
In contrast to our study, Schlumbrecht et al10 found that residual disease after surgery was not statistically significant (P = 0.29) for OS in a Cox univariate analysis. Tumor debulking has long been associated with improved outcomes in women with EOC.13 We were unable to explore associations between debulking status and survival because of the limited number of patients who were suboptimally cytoreduced. But, it is also important to note that optimal debulking rates did not differ in obese and nonobese women with LGSC. The majority of our patients received chemotherapy, so we were unable to test chemotherapy as a variable in our survival models because of the small number of patients who did not receive it. The effect of chemotherapy on LGSC warrants further study. Gershenson et al4 reported relative insensitivity of LGSC to chemotherapy due to an observed low rate of patients who were clinically disease-free after adjuvant platinum-based chemotherapy (52%). In a follow-up study, overall response rate to chemotherapy in 108 patients was only 3.8% in patients with recurrent LGSC.8 While chemotherapy does seem to have a less efficacious role in LGSC than in high-grade disease, the majority of patients continue to receive frontline therapy, and chemotherapy does play an important role in the treatment of women with LGSC.14
The relationship between BMI, obesity, and ovarian cancer is uncertain. Multiple studies have suggested that obesity does not negatively impact surgical outcomes, clinicopathologic factors,15 prognosis,16,17 or survival15,18 in all patients with EOC, when controlling for optimal debulking status18 and whether the patient received optimal doses of chemotherapy or hormonal therapy.16 Other studies suggest that after adjustment for confounders including stage, grade, age, histology, and residual disease, there is a trend toward shorter PFS in patients with a normal BMI, but OS is not significantly related to BMI.19 Conversely, results from other retrospective studies suggest that obesity was independently associated with both shorter time to recurrence and OS.20 Body mass index before and after diagnosis, as well as weight gain during adulthood, has also been associated with an increase in ovarian cancer mortality.21 Meta-analyses have attempted to better elucidate these conflicting results and suggest possible relationships between obesity in early adulthood and higher mortality among patients with EOC22 and slightly worse survival than nonobese women.23 Because of the variation between all of the studies, no definitive conclusions may be drawn, however. These studies take into account all patients with EOC, and so far no attempts have been made to understand the impact of obesity of LGSC.
Given the obesity epidemic, it would be helpful to improve our understanding of its effect on ovarian cancer biology. The role of obesity in LGSC may be multifactorial. Given the lack of association between obesity and DSS and PFS, mortality of obese patients with LGSC may result from other comorbidities secondary to obesity. Patients diagnosed with LGSC represent a unique population as compared with those diagnosed with other types of EOC. Patients with LGSC tend to live longer and have more indolent disease. The natural history of this disease may render lifestyle modifications worthwhile, particularly if the tumor microenvironment is adversely affected by excess adipose tissue. The GOG (Gynecologic Oncology Group) is currently evaluating the impact of diet and exercise in survival and recurrence rates in women with newly diagnosed stage II–IV ovarian cancer after successful first-line therapy (GOG225). Data from this study may help determine if lifestyle modifications targeting obesity will improve survival in women with LGSC.
According to the World Health Organization, overweight and obesity are the fifth leading risk for global deaths, and at least 2.8 million adults die each year as a result. More than 1.4 billion adults (aged ≥20 years) were overweight according to 2008 World Health Organization estimates.24 Obesity comprises a major risk factor for complications including type 2 diabetes, hypertension, hyperlipidemia, coronary artery disease, and stroke. In our study, 28% of patients were diagnosed with hypertension, which may contribute to higher incidence of coronary artery disease and/or stroke. However, only 6% of our study participants had diabetes. Our study did not take into account those patients with impaired fasting glucose or undiagnosed diabetes, and it is possible that we underestimated the percentage of patients with diabetes and LGSC. It is very likely that the association between obesity and worse survival we observed is secondary to obesity-related comorbid conditions. In a prospective trial of more than 900,000 adults, BMI was associated with significantly higher rates of death in men and women because of a variety of cancers including esophagus, colon and rectum, liver, gallbladder, pancreas, and kidney. Furthermore, women with a higher BMI had a trend of increased risk of death due to cancers of the breast, uterus, cervix, and ovary.25
In addition to obesity-related illnesses, the increased risk of death in obese patients with LGSC may also be due to direct effects of obesity on carcinogenesis. Tumors in an obese environment may behave differently. Increased adipose tissue influences the bioavailability of sex steroids through multiple pathways. Obesity increases insulin resistance, bioavailability of sex hormones, and chronic inflammation that may promote the growth, rate, or metastases of certain tumors.26 Leptin, found at higher concentrations in obese patients, induces expression of vascular endothelial growth factor and may promote angiogenesis.27 The role of obesity on ovarian cancer in the literature provides conflicting evidence. It is possible that certain histopathologic types of ovarian cancer are more influenced by the obese environment. Furthermore, the association between obesity and risk of developing EOC may vary depending on tumor grade and the specific type of ovarian cancer. Increased height and obesity may be associated with an increased risk of endometrioid types of EOC.28,29 Elevated BMI has been associated with an increased risk for borderline serous (odds ratio [OR], 1.24), invasive endometrioid cancers (OR, 1.17), and invasive mucinous cancers (OR, 1.19). There was no association with BMI and invasive serous cancers (OR, 0.98) except in premenopausal women (OR, 1.11), but there was an increased risk for LGSC (OR, 1.13) associated with higher BMI.30
This study is limited by a small sample size. Also, we did not analyze outcomes related to treatment with chemotherapy or hormonal therapy because of the small number of patients who received and did not receive this type of therapy, respectively. We also did not evaluate outcomes after additional surgery if recurrence did occur. We used BMI calculated at the time of diagnosis and did not take into account BMI during adolescence, if BMI changed postoperatively, or BMI at the conclusion of treatment. Recent studies suggest that adolescent exposure to obesity is associated with worse OS in women who develop EOC.22
Pathology was reviewed for more than 70% of patients included in this study to incorporate newer definitions of low-grade disease. For the remaining patients, pathology was not reviewed often because the original slides were returned to the referring laboratories, but the diagnosis of grade 1 disease was used as a surrogate for low-grade disease. In addition, 27% of our study population was unknown or lost to follow-up. Although the mean ages and BMIs between the lost-to-follow-up group were similar to the group with outcome data, this could potentially affect our results. Future prospective and/or studies that address BMI over the course of a patient’s lifetime could validate the trends observed in this series.
Despite these limitations, our findings indicate that obesity and tumor cytoreduction are associated with OS outcomes in women with LGSC. Obesity is a modifiable risk factor that was associated with worse survival in women with LGSC. In addition, obesity may be related to DSS and PFS, but we were unable to detect an association because of our limited sample size. Further study is warranted to address the role of obesity and weight-loss interventions in women with LGSC.
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Keywords:© 2014 by the International Gynecologic Cancer Society and the European Society of Gynaecological Oncology.
Low-grade serous ovarian cancer; Obesity