Predictors of Long-Term Survival among High-Grade Serous Ovarian Cancer Patients

Association of allostatic load with overall survival in epithelial ovarian cancer

OBJECTIVE

Elevated allostatic load (AL), an integrated, cumulative marker of physiologic damage due to socioenvironmental stress, is associated with increased mortality in patients with breast, lung, and other cancers. The relationship between allostatic load and mortality in ovarian cancer patients remains unknown. We examined the relationship between allostatic load and overall survival in ovarian cancer patients.

METHODS

This cross-sectional study used data from 201 patients enrolled in a prospective observational ovarian cancer cohort study at a National Cancer Institute-designated Comprehensive Cancer Center from October 2012 through June 2022. All patients underwent debulking surgery and completed a full course of standard-of-care platinum-based chemotherapy. Follow-up was completed through January 2024. Allostatic load was calculated as a summary score by assigning one point to the worst sample quartile for each of ten biomarkers measured within 45 days before the ovarian cancer diagnosis. High allostatic load was defined as having an allostatic load in the top quartile of the summary score. A Cox proportional hazard model with robust variance tested the association between allostatic load and overall survival.

RESULTS

There were no associations between allostatic load and ovarian cancer clinical characteristics. After accounting for demographic, clinical, and treatment factors, high allostatic load was associated with a significant increase in mortality (hazard ratio 2.17 [95%CI, 1.13-4.15]; P = 0.02).

CONCLUSION

Higher allostatic load is associated with worse survival among ovarian cancer patients. Allostatic load could help identify patients at risk for poorer outcomes who may benefit from greater socioenvironmental support during treatment.

Influence of Intraoperative Fluid Management on Postoperative Outcome and Mortality of Cytoreductive Surgery for Advanced Ovarian Cancer-A Retrospective Observational Study

Background: The surgical treatment of advanced ovarian cancer is associated with extensive tissue trauma, prolonged operating times and a considerable volume shift. It, therefore, represents a challenge for anaesthesiological management. Aim: The aim of this single-centre, retrospective, observational study was to investigate whether intraoperative extensive volume supply influences postoperative outcomes and long-term survival. Methods: The study included 73 patients with a mean (SD) age of 63 (13) years who underwent extensive tumour-reducing surgery for ovarian cancer between 2012 and 2015. The effect of the intraoperative fluid balance on postoperative complications, such as anastomotic insufficiency or pleural effusions, was investigated using logistic regression. Further, the influence of fluid balance, lactate and creatinine levels on 5-year survival was analysed in a Cox regression model. Associations between anaesthesia time and the intraoperative fluid balance were examined using Spearman's rank correlation coefficients. Results: The mean (SD) postoperative fluid balance in the considered patient cohort was 9.1 (3.4) litres (l) at a mean (SD) anaesthesia time of 529 (106) minutes. Cox regression did not reveal a statistically significant effect of the fluid balance, but it did reveal a statistically significant association between the lactate level 24 h following surgery and the 5-year survival (HR [95%-CI] fluid balance: 0.97 [0.85, 1.11]; HR [95%-CI] lactate: 1.79 [1.24, 2.58]). According to logistic regression, the intraoperative fluid balance was associated with an increased chance of postoperative complications in the considered patient cohort (OR [95%-CI] 1.28 [1.1, 1.54]). Conclusions: We could not detect a negative impact of an increased fluid balance on 5-year survival, but a negative impact on postoperative complications was found in our patient cohort.

Insulin-like growth factor (IGF) and hepatocyte growth factor (HGF) in follicular fluid cooperatively promote the oncogenesis of high-grade serous carcinoma from fallopian tube epithelial cells: Dissection of the molecular effects

Incessant ovulation is believed to be a potential cause of epithelial ovarian cancer (EOC). Our previous investigations have shown that insulin-like growth factor (IGF2) and hepatocyte growth factor (HGF) in the ovulatory follicular fluid (FF) contributed to the malignant transformation initiated by p53 mutations. Here we examined the individual and synergistic impacts of IGF2 and HGF on enhancing the malignant properties of high-grade serous carcinoma (HGSC), the most aggressive type of EOC, and its precursor lesion, serous tubal intraepithelial carcinoma (STIC). In a mouse xenograft co-injection model, we observed that FF co-injection induced tumorigenesis of STIC-mimicking cells, FE25. Co-injection with IGF2 or HGF partially recapitulated the tumorigenic effects of FF, but co-injection with both resulted in a higher tumorigenic rate than FF. We analyzed the different transformation phenotypes influenced by these FF growth signals through receptor inhibition. The IGF signal was necessary for clonogenicity, while the HGF signal played a crucial role in the migration and invasion of STIC and HGSC cells. Both signals were necessary for the malignant phenotype of anchoring-independent growth but had little impact on cell proliferation. The downstream signals responsible for these HGF activities were identified as the tyrosine-protein kinase Met (cMET)/mitogen-activated protein kinase and cMET/AKT pathways. Together with the previous finding that the FF-IGF2 could mediate clonogenicity and stemness activities via the IGF-1R/AKT/mammalian target of rapamycin and IGF-1R/AKT/NANOG pathways, respectively, this study demonstrated the cooperation of the FF-sourced IGF and HGF growth signals in the malignant transformation and progression of HGSC through both common and distinct signaling pathways. These findings help develop targeted prevention of HGSC.

Prognostic risk factors of serous ovarian carcinoma based on mesenchymal stem cell phenotype and guidance for therapeutic efficacy

BACKGROUND

Epithelial ovarian cancer is the leading cause of death from gynecologic cancer, in which serous ovarian carcinoma (SOC) is the most common histological subtype. Although PARP inhibitors (PARPi) and antiangiogenics have been accepted as maintenance treatment in SOC, response to immunotherapy of SOC patients is limited.

METHODS

The source of transcriptomic data of SOC was from the Cancer Genome Atlas database and Gene Expression Omnibus. The abundance scores of mesenchymal stem cells (MSC scores) were estimated for each sample by xCell. Weighted correlation network analysis is correlated the significant genes with MSC scores. Based on prognostic risk model construction with Cox regression analysis, patients with SOC were divided into low- and high-risk groups. And distribution of immune cells, immunosuppressors and pro-angiogenic factors in different risk groups was achieved by single-sample gene set enrichment analysis. The risk model of MSC scores was further validated in datasets of immune checkpoint blockade and antiangiogenic therapy. In the experiment, the mRNA expression of prognostic genes related to MSC scores was detected by real-time polymerase chain reaction, while the protein level was evaluated by immunohistochemistry.

RESULTS

Three prognostic genes (PER1, AKAP12 and MMP17) were the constituents of risk model. Patients classified as high-risk exhibited worse prognosis, presented with an immunosuppressive phenotype, and demonstrated high micro-vessel density. Additionally, these patients were insensitive to immunotherapy and would achieve a longer overall survival with antiangiogenesis treatment. The validation experiments showed that the mRNA of PER1, AKAP12, and MMP17 was highly expressed in normal ovarian epithelial cells compared to SOC cell lines and there was a positive correlation between protein levels of PER1, AKAP12 and MMP17 and metastasis in human ovarian serous tumors.

CONCLUSION

This prognostic model established on MSC scores can predict prognosis of patients and provide the guidance for patients receiving immunotherapy and molecular targeted therapy. Because the number of prognostic genes was fewer than other signatures of SOC, it will be easily accessible on clinic.

Body Composition and Metabolic Dysfunction Really Matter for the Achievement of Better Outcomes in High-Grade Serous Ovarian Cancer

Although obesity-associated metabolic disorders have a negative impact on various cancers, such evidence remains controversial for ovarian cancer. Here, we aimed to evaluate the impact of body composition (BC) and metabolism disorders on outcomes in high-grade serous ovarian cancer (HGSOC).

METHODS

We analyzed clinical/genomic data from two cohorts (PUC n = 123/TCGA-OV n = 415). BC was estimated using the measurement of adiposity/muscle mass by a CT scan. A list of 425 genes linked to obesity/lipid metabolism was used to cluster patients using non-negative matrix factorization. Differential expression, gene set enrichment analyses, and Ecotyper were performed. Survival curves and Cox-regression models were also built-up.

RESULTS

We identified four BC types and two clusters that, unlike BMI, effectively correlate with survival. High adiposity and sarcopenia were associated with worse outcomes. We also found that recovery of a normal BC and drug interventions to correct metabolism disorders had a positive impact on outcomes. Additionally, we showed that immune-cell-depleted microenvironments predominate in HGSOC, which was more evident among the BC types and the obesity/lipid metabolism cluster with worse prognosis.

CONCLUSIONS

We have demonstrated the relevance of BC and metabolism disorders as determinants of outcomes in HGSOC. We have shone a spotlight on the relevance of incorporating corrective measures addressing these disorders to obtain better results.

Prediagnosis Depression Rather Than Anxiety Symptoms Is Associated with Decreased Ovarian Cancer Survival: Findings from the Ovarian Cancer Follow-Up Study (OOPS)

Background: The relationship between prediagnosis depression, anxiety symptoms, and ovarian cancer (OC) survival is unknown. We aimed to explore these associations to provide further epidemiological evidence. Methods: We investigated the relationship between prediagnosis depression, anxiety symptoms, and OC survival in a prospective cohort study of newly diagnosed OC patients aged 18−79 years. Depression and anxiety symptoms were assessed using the Patient Health Questionnaire 9 and Generalized Anxiety Disorder 7 at diagnosis, respectively. Deaths were ascertained until 31 March 2021 via medical records and active follow-up. Multivariable-adjusted Cox proportional hazards regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) with prediagnosis depression and anxiety symptoms and all-cause mortality of OC. Results: We found 56 (9.4%) and 235 (39.3%) OC patients with depression and anxiety symptoms, respectively. During a median follow-up of 37.2 months (interquartile range 24.7−50.2 months), 130 deaths were confirmed. Compared with non-depression symptoms, patients with prediagnosis depressive symptoms showed a significantly increased risk of OC mortality (HR = 2.10, 95% CI: 1.20−3.70). Of note, the association was still robust when focusing on the OC patients with severe depressive symptoms (HR = 2.10, 95% CI: 1.07−4.12). However, we observed no association between prediagnosis anxiety symptoms of different severity and OC mortality. Interestingly, OC patients with combined moderate depression and anxiety symptoms had a significantly increased risk of OC mortality (HR = 3.23, 95% CI: 1.14−9.11) compared to those with no symptoms of depression and anxiety. Notably, Wilms’s tumor 1 was significantly associated with depression and anxiety symptoms (p < 0.05). Conclusions: Prediagnosis depression increases the risk of OC mortality. Large multicenter studies are required to confirm this finding.

Pre-diagnosis fiber : carbohydrate intake ratio and mortality of ovarian cancer: results from a prospective cohort study

Background: The association between the ratio of fiber to carbohydrate (F : C-R) and cancer mortality is not currently well-known. We prospectively evaluated for the first time the aforementioned topic among ovarian cancer (OC) patients. Methods: A total of 703 newly diagnosed OC patients aged 18-79 years were included. Pre-diagnosis diet intake details were collected with a validated food frequency questionnaire. Deaths were ascertained until March 31, 2021, based on medical records and the cancer registry. Cox proportional hazard models were used to evaluate hazard ratios (HRs) and 95% confidence intervals (CIs) between pre-diagnostic fiber, carbohydrate, and F : C-R intake and OC mortality. Restricted cubic splines were used to analyze the potential nonlinear relationship between F : C-R and OC mortality. Results: During the follow-up period (median: 37.2 months; interquartile: 24.7-50.2 months), we observed 130 (18.49%) OC patients died. The pre-diagnosis higher fiber intake (comparing the highest with the lowest tertile of intake: HR = 0.56, 95% CI = 0.35-0.92; HR per 1 SD increment: 0.78, 95% CI = 0.64-0.96; P trend < 0.05) and higher F : C-R intake (comparing the highest with the lowest tertile of intake: HR = 0.51, 95% CI = 0.31-0.85; HR per 1-SD increment: 0.73; 95% CI = 0.59-0.91; P trend < 0.05) were significantly associated with lower mortality for OC patients, but no evidence of the association between pre-diagnosis carbohydrate intake and OC mortality was observed. We found no evidence of a nonlinear relationship between F : C-R and OC mortality. Significant inverse associations were also observed for subgroup analyses stratified by age at diagnosis, menopausal status, residual lesions, histological type, FIGO stage, and body mass index, although not all associations showed statistical significance. Conclusion: Pre-diagnosis high fiber intake and high F : C-R diet intake were associated with a decreased risk of OC mortality.

Modifiable risk factors associated with long-term survival in women with serous ovarian cancer: a National Cancer Database study

OBJECTIVE

To identify patient, clinical and hospital factors associated with long-term survival (≥10 years) in women with serous ovarian cancer.

METHODS

This National Cancer Database cohort study included women with stage II-IV serous ovarian cancer. Multivariate logistic regression models were used to examine the association of long-term survival with patient (race, insurance, location, household income, education, distance traveled), clinical (age, comorbidities, stage, grade, primary treatment) and hospital factors (region, institution, hospital volume ≥20).

RESULTS

Of the 4640 women identified, 12% (n=561) experienced long-term survival. Median overall survival was 41 months (95% CI 39 to 42). The odds of long-term survival were lower for women with public or no insurance (adjusted OR 0.71, 95% CI 0.55 to 0.92), age ≥75 years (0.33, 0.22 to 0.50), any comorbidities (0.70, 0.54 to 0.92), higher stage (stage III: 0.31, 0.25 to 0.41; stage IV: 0.16, 0.12 to 0.22), and moderately/poorly differentiated, undifferentiated, or tumors of unknown grade (moderately/poorly differentiated: 0.30, 0.20 to 0.47; undifferentiated: 0.28, 0.17 to 0.47; unknown: 0.30, 0.18 to 0.50). The odds of long-term survival among women who were publicly insured were lower with neoadjuvant chemotherapy (0.13, 0.04 to 0.044) and higher with optimal cytoreduction (2.24, 1.49 to 3.36). Among women who were privately insured, the odds of long-term survival were higher with optimal cytoreduction (1.99, 1.46 to 2.70) and unaffected by neoadjuvant chemotherapy.

CONCLUSIONS

While immutable clinical factors such as age, stage, and grade are associated with long-term survival in women with serous ovarian cancer, modifiable factors, such as insurance type, optimal cytoreductive status, and neoadjuvant chemotherapy provide an opportunity for targeted improvement in care with potential to affect long-term patient outcomes.

Ovarian cancer survival by stage, histotype, and pre-diagnostic lifestyle factors, in the prospective UK Million Women Study

BACKGROUND

Ovarian cancer is the fifth leading cause of cancer mortality in UK women. Ovarian cancer survival varies by disease stage at diagnosis, but evidence is mixed on the effect of tumour histological type (histotype) and other factors.

METHODS

1.3 million UK women completed a detailed health questionnaire in 1996-2001 and were followed for incident cancers and deaths via linkage to national databases. Using Cox regression models, we estimated adjusted relative risks (RRs) of death from ovarian cancer, by stage at diagnosis, tumour histotype, and 16 other personal characteristics of the women.

RESULTS

During 17.7 years' average follow-up, 13,222 women were diagnosed with ovarian cancer, and 8697 of them died from the disease. Stage at diagnosis was a major determinant of survival (stage IV vs I, RR=10.54, 95% CI: 9.16-12.13). Histotype remained a significant predictor after adjustment for stage and other factors, but associations varied over the follow-up period. Histotype-specific survival was worse for high-grade than low-grade tumours. Survival appeared worse with older age at diagnosis (per 5 years: RR=1.19, 95% CI: 1.15-1.22), higher BMI (per 5-unit increase: RR=1.06, 95% CI: 1.02-1.11), and smoking (current vs never: RR=1.17, 95% CI: 1.07-1.27), but there was little association with 13 other pre-diagnostic reproductive, anthropometric, and lifestyle factors.

CONCLUSION

Stage at diagnosis is a strong predictor of ovarian cancer survival, but tumour histotype and grade remain predictors of survival even after adjustment for stage and other factors, contributing further evidence of biological dissimilarity between the ovarian cancer histotypes. Obesity and smoking represent potentially-modifiable determinants of survival, but the stronger association with stage suggests that improving earlier diagnosis would have a greater impact on increasing ovarian cancer survival.

Long-Term Survival Among Histological Subtypes in Advanced Epithelial Ovarian Cancer: Population-Based Study Using the Surveillance, Epidemiology, and End Results Database

BACKGROUND

Actual long-term survival rates for advanced epithelial ovarian cancer (EOC) are rarely reported.

OBJECTIVE

This study aimed to assess the role of histological subtypes in predicting the prognosis among long-term survivors (≥5 years) of advanced EOC.

METHODS

We performed a retrospective analysis of data among patients with stage III-IV EOC diagnosed from 2000 to 2014 using the Surveillance, Epidemiology, and End Results cancer data of the United States. We used the chi-square test, Kaplan-Meier analysis, and multivariate Cox proportional hazards model for the analyses.

RESULTS

We included 8050 patients in this study, including 6929 (86.1%), 743 (9.2%), 237 (2.9%), and 141 (1.8%) patients with serous, endometrioid, clear cell, and mucinous tumors, respectively. With a median follow-up of 91 months, the most common cause of death was primary ovarian cancer (80.3%), followed by other cancers (8.1%), other causes of death (7.3%), cardiac-related death (3.2%), and nonmalignant pulmonary disease (3.2%). Patients with the serous subtype were more likely to die from primary ovarian cancer, and patients with the mucinous subtype were more likely to die from other cancers and cardiac-related disease. Multivariate Cox analysis showed that patients with endometrioid (hazard ratio [HR] 0.534, P<.001), mucinous (HR 0.454, P<.001), and clear cell (HR 0.563, P<.001) subtypes showed better ovarian cancer-specific survival than those with the serous subtype. Similar results were found regarding overall survival. However, ovarian cancer-specific survival and overall survival were comparable among those with endometrioid, clear cell, and mucinous tumors.

CONCLUSIONS

Ovarian cancer remains the primary cause of death in long-term ovarian cancer survivors. Moreover, the probability of death was significantly different among those with different histological subtypes. It is important for clinicians to individualize the surveillance program for long-term ovarian cancer survivors.

Artificial intelligence-based image analysis can predict outcome in high-grade serous carcinoma via histology alone

High-grade extrauterine serous carcinoma (HGSC) is an aggressive tumor with high rates of recurrence, frequent chemotherapy resistance, and overall 5-year survival of less than 50%. Beyond determining and confirming the diagnosis itself, pathologist review of histologic slides provides no prognostic or predictive information, which is in sharp contrast to almost all other carcinoma types. Deep-learning based image analysis has recently been able to predict outcome and/or identify morphology-based representations of underlying molecular alterations in other tumor types, such as colorectal carcinoma, lung carcinoma, breast carcinoma, and melanoma. Using a carefully stratified HGSC patient cohort consisting of women (n = 30) with similar presentations who experienced very different treatment responses (platinum free intervals of either ≤ 6 months or ≥ 18 months), we used whole slide images (WSI, n = 205) to train a convolutional neural network. The neural network was trained, in three steps, to identify morphologic regions (digital biomarkers) that are highly associating with one or the other treatment response group. We tested the classifier using a separate 22 slide test set, and 18/22 slides were correctly classified. We show that a neural network based approach can discriminate extremes in patient response to primary platinum-based chemotherapy with high sensitivity (73%) and specificity (91%). These proof-of-concept results are novel, because for the first time, prospective prognostic information is identified specifically within HGSC tumor morphology.

The Long-Term Prognostic Significance of Circulating Tumor Cells in Ovarian Cancer-A Study of the OVCAD Consortium

INTRODUCTION

We previously reported the prognostic impact of circulating tumor cells (CTCs) in a multicenter study on minimal residual disease in primary ovarian cancer. With additional follow-up data, we evaluated the combined CTC approach (CTCs^combo), in particular for the patients who had survived more than five years.

MATERIAL AND METHODS

Blood samples taken at baseline and six months after adjuvant treatment (follow-up) were assessed by quantitative PCR (qPCR) measuring PPIC transcripts and immunofluorescent staining (IF). A positive result with either IF or qPCR was classified as CTC^combo-positive. Further, PPIC was assessed in the primary tumor tissue.

RESULTS

The concordance of IF and qPCR was 65% at baseline and 83% after treatment. Results showed that 50.5% of the baseline and 29.5% of the follow-up samples were CTC^combo-positive. CTCs^combo after treatment were associated with increased mortality after adjusting for FIGO stage (HR 2.574, 95% CI: 1.227-5.398, p = 0.012), a higher risk of recurrence after adjusting for peritoneal carcinosis (HR 4.068, 95% CI: 1.948-8.498, p < 0.001), and increased mortality after five survived years.

DISCUSSION

The two-sided analytical approach revealed CTC subpopulations associated with ovarian cancer progression and may illuminate a potential treatment-related shift in molecular phenotypes. That approach can identify patients who have elevated risk of recurrence and death due to ovarian cancer and who may require risk-adapted treatment strategies.

Impact of clinical factors and surgical outcome on long-term survival in high-grade serous ovarian cancer: a multicenter analysis

INTRODUCTION

Long-term survivors of ovarian cancer are a unique group of patients in whom prognostic factors for long-term survival have been poorly described. Such factors may provide information for a more personalized therapeutic approach. The objective of this study is to determine further characteristics of long-term survivors with high-grade serous ovarian cancer.

METHODS

Long-term survivors were defined as patients living longer than 8 years after first diagnosis and were recruited within seven high volume centers across Europe from November 1988 to November 2008. The control group included patients with high-grade serous ovarian cancer with less than 5 years' survival identified from the systematic 'Tumorbank ovarian cancer' database. A subanalysis of Charité patients only was performed separately for in-depth analysis of tumor dissemination. Propensity score matching with nearest-neighbor caliper width was used to match long-term survivors and the control group regarding age, FIGO stage, and residual tumor.

RESULTS

A total of 276 patients with high-grade serous ovarian cancer were included, divided into 131 long-term survivors and 145 control group patients. After propensity score matching and multivariable adjustment, platinum sensitivity (p=0.002) was an independent favorable prognostic factor whereas recurrence (p<0.001) and ascites (p=0.021) were independent detrimental predictors for long-term survival. Significantly more long-term survivors tested positive for mutation in the BRCA1 gene than the BRCA2 gene (p=0.016). Intraoperatively, these patients had less tumor involvement of the upper abdomen at initial surgery (p=0.024). Complexity of surgery and surgical techniques were similar in both cohorts.

CONCLUSION

Platinum sensitivity constitutes a favorable factor for long-term survival whereas tumor involvement of the upper abdomen, ascites, and recurrence have a negative impact. Based on clinical estimation, long-term survival is associated with combinations of clinical, surgical, and molecular factors.

Programmed Death-1 Receptor (PD-1) as a Potential Prognosis Biomarker for Ovarian Cancer Patients

Aim

Ovarian cancer (OC) is one of the most lethal gynecological malignancies. Recent studies suggest a crucial role of the PD-1/PD-L1 pathway in OC pathogenesis. Therefore, our study aimed at evaluation of the clinical importance of PD-1 expression in ovarian cancer patients.

Patients and Methods

In this study, we investigated the role of PD-1 in OC patients (n=50) by analyzing its expression on CD4⁺ and CD8⁺ T cells in three OC environments: peripheral blood (PB), peritoneal fluid (PF), and tumor (TT) as well as soluble PD-1 (sPD-1) in plasma and PF in terms of their clinical and prognostic significance. T cells with PD-1 expression were analyzed using flow cytometry. The concentration of sPD-1 was determined with the use of ELISA. Our research demonstrated differences in PD-1 expression on CD4⁺ and CD8⁺ T cells in the OC environments.

Results

We found an elevated level of CD4⁺PD-1⁺ T cells in tumor and PF, compared to PB. Additionally, we found the highest percentage of CD8⁺ PD-1⁺ in tumor, compared to PB and PF. The levels of sPD-1 were higher (p<0.0001) in plasma than in PF. For the first time, we discovered that the higher level of CD4⁺PD-1⁺ T cells in the circulation and the higher sPD-1 level in plasma predict poor survival of OC patients.

Conclusion

We suggest that PD-1 could be a predictive biomarker for OC patients and successful immunotherapy.

Predictors of survival trajectories among women with epithelial ovarian cancer

OBJECTIVE

Although ovarian cancer is a deadly disease, approximately a third of women survive ≥9 years after diagnosis. The factors associated with achieving long-term survival are not well understood. In this study, data from the Surveillance, Epidemiology, and End Results (SEER) program were used to determine predictors of survival trajectories among women with epithelial ovarian cancer and across histotype (high-grade serous carcinoma (HGSC) and non-HGSC).

METHODS

Data on 35,868 women diagnosed with epithelial ovarian cancer in 2004-2016 were extracted from SEER. Extended Cox proportional hazards regression was used to estimate overall and histotype-specific associations between patient and tumor characteristics and all-cause mortality within each survival time (t) interval (t < 3, 3 ≤ t < 6, 6 ≤ t < 9, and 9 ≤ t < 13 years).

RESULTS

Age at diagnosis, marital status, race/ethnicity, stage, and surgery were more strongly associated with mortality in the short-term survival period, and these associations waned with increasing survival time. Exceptions to this pattern were age >70 years at diagnosis, where a high risk of mortality was observed in both the t < 3 and t ≥ 9 year time periods, and non-Hispanic Asian/Pacific Islanders, where a more pronounced inverse association with mortality was observed in t ≥ 9 years after diagnosis. Similar associations were observed for HGSC, although the waning effect was not apparent for most characteristics. Mortality associations for non-HGSC were more pronounced for stage and race/ethnicity, primarily for non-Hispanic Asian/Pacific Islanders.

CONCLUSIONS

Most patient and tumor characteristics were more strongly associated with mortality in the years following diagnosis, but have declining impact with increasing survival time. Given this waning effect, it is critical to identify factors impacting risk of mortality as ovarian cancer patients advance through the survival trajectory.

"I am not a statistic" ovarian cancer survivors' views of factors that influenced their long-term survival

OBJECTIVE

Although a high proportion of women with advanced stage ovarian cancer die within five years, approximately 30% will survive longer than this. The factors contributing to exceptional survival are currently poorly understood. The viewpoints of ovarian cancer survivors were qualitatively explored to determine the factors they felt have influenced their exceptional ovarian cancer survival.

METHODS

Four focus groups, one each in Los Angeles (California), Ann Arbor (Michigan), New York (New York) and Edmonton (Alberta, Canada), were conducted with women who had survived at least five years. Physical activity, diet, meditation, prayer, treatment, complementary medicine, and side effects were explored in semi-structured discussions. The audiotaped sessions were transcribed and coded and then analyzed using Dedoose Version 8.0.35, a qualitative analysis software.

RESULTS

Of the 26 women who participated, 23 had advanced stage disease. Three overarching themes emerged: (a) survivors had improved their 'lifestyles', including but not limited to fitness and diet; (b) survivors were able to draw on strong support systems, which included family, friends, support groups, faith communities, and healthcare workers; and (c) survivors had a strong life purpose, which manifested as positivity, taking charge of their lives, and advocating for themselves.

CONCLUSIONS

Long-term survivors have varying experiences with their cancer, but identified lifestyle modification, motivation and persistence, strong life purpose, and strong support systems as key elements in their better survival. These preliminary findings indicate the need for further prospective studies to determine whether meaningful differences exist between short term and long term survivors on these characteristics.