Survival of epithelial ovarian cancer in Black women: a society to cell approach in the African American Cancer Epidemiology Study (AACES)

doi:10.21203/rs.3.rs-2002005/v1

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Research Article

Survival of epithelial ovarian cancer in Black women: a society to cell approach in the African American Cancer Epidemiology Study (AACES)

https://doi.org/10.21203/rs.3.rs-2002005/v1

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Purpose: The five-year relative survival for epithelial ovarian cancer (EOC) is worse among Black women compared with White women. The causes for this disparity are likely multi-factorial but unclear as to date, no cohort study has focused specifically on Black EOC survivors. Here we present the African-American Cancer Epidemiology Study (AACES), the largest cohort of Black women diagnosed with EOC.

Methods: Phase 1 began in 2010 as a multi-site population-based case-control study focused on risk, and phase 2 began enrolling newly diagnosed EOC cases in 2020. Phase 2 builds on existing infrastructure with the goal to increase the number of EOC cases by 50% and evaluate factors affecting survival with a society-to-cell approach. Both phases use rapid case ascertainment to identify potential participants and collect extensive survey data, biospecimens, medical record abstraction, and annual follow-up.

Results: Phase 1 enrolled 592 women with EOC, with a median survival of 4.8 years as of 2021. These survival rates approximate those of Black women in SEER who survive at least 10 months past diagnosis. A high proportion of the cohort was found to have relatively low levels of household income, education, and insurance coverage.

Conclusions and Implications for Cancer Survivors: AACES is well-positioned to evaluate the contribution of social determinants of health to the poor survival of Black women with EOC, advance understanding of the multi-factorial causes of the ovarian cancer survival disparity in Black women, and serve as an example of a multi-site, epidemiologic population-based study of a rare cancer in a minority population.

epithelial ovarian cancer

cancer survivors

racial disparities

social determinants of health

The five-year relative survival for ovarian cancer is markedly worse for Black women, at 36.4%, when compared with White women, at 44.3% [1]. In fact, after stratifying on stage at diagnosis, survival is worse in Black women compared to any other racial group for both early and late stage disease [2]. Factors affecting epithelial ovarian cancer (EOC) prognosis are under-studied among Black women despite notable differences in age at diagnosis, clinical-pathological features, and survival compared to White women [3]. The causes for this survival disparity are most likely multi-factorial.

Social determinants of health could contribute to poorer survival in Black women. For example, lower socio-economic status (SES), with limited access to care, may lead to more advanced stage at diagnosis and receipt of suboptimal treatment [4]. Social determinants of health can also contribute to individual-level susceptibility factors that lead to poorer prognosis, such as higher prevalence of co-morbidities and a higher inflammatory response [5, 6]. A pooled analysis from the Ovarian Cancer in Women of African Ancestry (OCWAA) consortium, suggested that several factors including reproductive factors, co-morbid conditions and hormone use appear to mediate ovarian cancer survival differences between Black and White women [7].

To date, no cohort study has focused on Black EOC survivors. Here we present the African-American Cancer Epidemiology Study (AACES) [8], the largest cohort of Black women with EOC residing in several U.S. states where we will further explore why EOC survival is poor among Black women by applying a multi-level approach that simultaneously includes an assessment of the impact of neighborhood, lifestyle, and biological factors on EOC outcomes in Black women (Fig. 1). Our approach evaluates how multiple factors can affect EOC survival through three levels: environmental (from neighborhood-level and census tract factors), individual (from data collected during interviews with each participant), and cellular (tumor immunity). In AACES we focus on inflammatory factors, given the strong role of inflammation in ovarian carcinogenesis and growing evidence of its role in prognosis [5].

Given its size, geographical diversity, and breadth of data including biospecimens, the AACES cohort provides a unique resource to advance understanding of the multi-factorial causes of the ovarian cancer survival disparity in Black women. This information can in turn provide the foundational information needed to develop strategies to reduce and eventually eliminate this disparity. As described here, AACES also serves as a roadmap for the conduct of a multi-site, epidemiologic population-based study of a rare cancer in a minority population. For this reason, the methods section provides detailed information about the study design and conduct.

The AACES Study Design

Phase 1 of the AACES study (R01CA142081) was initiated in 2010 as a multi-site population-based, case-control study, described in detail elsewhere [8]. The study was designed to evaluate genetic and lifestyle risk factors for EOC in Black women, with the intention of also conducting follow-up of the participants to evaluate survival in the future. Phase 2 of AACES (R01CA237318), which began in 2020, builds upon the infrastructure developed in the AACES phase 1, and focuses on evaluating associations of multi-level factors (neighborhood, lifestyle, and biological factors) with EOC survival using a prospective cohort design, which includes participants from AACES phase 1 and newly recruited participants in phase 2. The chosen study sites (Supplemental Fig. 1) [9] represent geographic diversity as well as an approach for an efficient means for accrual of minority women diagnosed with a rare cancer. Consideration was also given for the proportion of Black residents, the incidence rates of ovarian cancer, and the frequency of newly diagnosed cases of EOC within the geographic regions.

AACES Phase 1. In phase 1, the study sites were selected based on geographic regions with high Black population density and included Alabama, Georgia, Louisiana, metropolitan Detroit, Illinois, New Jersey, North Carolina, Ohio, South Carolina, Tennessee, and Texas.

Potential participants were eligible if they had histologically confirmed EOC, self-identified as African American or Black, were 20–79 years of age at diagnosis and had the ability to complete the interview in English. Rapid case ascertainment was used to identify potential participants through state cancer or Surveillance Epidemiology, and End Results (SEER) registries, and through gynecologic oncology departments at individual hospitals. Participants were recruited between December 2010 and December 2015.

AACES Phase 2. Based on the AACES phase 1 design and infrastructure, we are currently enrolling women newly diagnosed with invasive epithelial ovarian cancer in phase 2. Our goal is to increase the number of participants recruited in Phase 1 by ~ 50%. Based on the enrollment in phase 1, we chose a subset of the sites for phase 2 with the largest number of enrolled participants, including the states of Georgia, New Jersey, Louisiana, South Carolina, North Carolina, Tennessee and the Detroit metropolitan area. A new site, the Southern California SEER registry, is also included in phase 2. Four of the sites participating in phase 2, Georgia, New Jersey, Louisiana, and Southern California, are SEER registries. All sites employ rapid-case-ascertainment, described below. We have established a single IRB using the Western Institutional Review Board-Copernicus Group (WCG IRB) that all sites rely on. In phase 2, we continue to incorporate the majority of survey questions and indices used in phase 1 to maximize our ability to pool data from the two phases of AACES. However, we have updated some survey questions when we determined improvement was required and added other constructs of interest that were not collected in phase 1, such as financial toxicity (Fig. 2). We now obtain information about genetic counseling in a population that has been shown to be deficient in BRCA1 and BRCA2 testing [10] and we obtain information concerning COVID 19, as phase 2 began during the beginning of the COVID 19 pandemic.

Initial Patient Identification and Contact. After passive approval from the physician, potential participants from Georgia, New Jersey, and South Carolina are contacted by their cancer registry by mail and by telephone. Participant approval (verbally or by mail) is required from these sites before their contact information is passed to the study team. Participants from California, Louisiana, North Carolina, and Tennessee do not require active approval from the patient to send participant contact information to the study team. Some hospitals in the Detroit metropolitan area require active physician approval before reaching out to the potential participant. All potential study participants are mailed a packet of introductory material. Consent can be obtained verbally for the study survey, and written consent is obtained for other study activities. New Jersey and the Detroit metropolitan area sites are responsible for consenting the participants and completing the baseline survey. The central study team reaches out to the participant to complete the food frequency questionnaires, the annual follow-up surveys, making medical records requests and requests for paraffin-embedded tumor tissue samples.

Enrollment & Retention Strategies. To mitigate obstacles when contacting participants, we implemented several strategies including an identifiable study logo. Additionally, a brochure that highlights aspects of study participation and compensations is mailed to each potential study participant. We also provide a website (https://aaces.emory.edu/) and a toll-free number to accommodate those who want more information. An informational one-page flyer is sent prior to initiating phone contact to alert the patient about the study, informing the patient that she will be contacted by phone. This flyer includes a toll-free phone number, name, and picture to inform the participant who will be contacting them. All telephone numbers that are involved with patient contact have a caller ID labelled as “AACES Study Office” or “AACES Study” so participants can recognize the study phone numbers.

Multiple call attempts are made to reach the potential participant at different times of the day including early evening and weekends. Study participants are given alternative options to complete the survey online or on a paper version if the baseline telephone interview does not offer a desired time commitment and flexibility. Additionally, if a potential participant is unable to complete a survey at the time of contact, we offer to check back in after a few months. Upon completion of the interview, we send newsletters twice a year that includes recent publications, study updates, and educational materials on topics related to cancer survivorship. One goal of these newsletters is to maintain up-to-date contact information. A $50.00 compensation is paid to participants who complete the baseline survey.

Baseline and Follow-Up Surveys

In phase 1, participants completed a baseline telephone survey that collected information on sociodemographic characteristics, medical history, self-reported family history of cancer, lifestyle characteristics [11], perceived daily and lifetime discrimination [12], social support [13, 14], religiosity [15], health insurance status, health care provider access, and trust in physicians [16]. For phase 2, some survey content was revised: social support was switched from the Multidimensional Scale of Perceived Social Support (MSPSS) [13] to the modified Medical Outcomes Study Social Support Survey (mMOS-SS) [14]. We also added additional questions to the phase 2 baseline survey including the Short Form Health Survey (SF-12 version 2) quality of life [17], the Pittsburgh sleep quality index [18], an index for financial toxicity [19], COVID-19 diagnosis and vaccination, and questions pertaining to genetic testing and counseling (Fig. 2). Both phase 1 and phase 2 include a follow-up survey at approximately one year after baseline interview that addresses changes and updates such as changes in physical activity [11], employment, quality of life (SF-8 in phase 1, and SF-12 version 2 in phase 2) [20, 17], medication use, new diagnoses of cancer and other comorbid conditions in the participant and family members, and genetic counseling and testing.

In phase 2, study data for baseline and follow-up surveys were collected and managed using Research Electronic Data Capture (REDCap) hosted at Emory University [21, 22]. The online and hardcopy version of the baseline survey has an abbreviated assessment of some factors including parity, oral contraceptive use, family history, access to care and symptoms and provide flexibility for the participant who requests this option.

Geocoding and Area-Level Variables

In order to link neighborhood-level variables, we use the participant’s residential address at diagnosis and geocode to latitude and longitude coordinates. These data can be linked to various levels of geospatial data related to indices of socioeconomic status and/or deprivation, environmental pollution, measures of access to care, and more [23–28]. This will enable a wider variety and scope of analyses in the future using the AACES sample population.

Biospecimen Collection

Upon receipt of a written informed consent, we initiate collection of biospecimens, including blood or saliva and tumor tissue. When blood or saliva is obtained, a second $50.00 compensation is paid.

Blood or Saliva Collection. In both phases of AACES, we contracted with an outside vendor for blood or saliva collection and anthropometric measurements. In phase 2, we contracted with ExamOne, a subsidiary of Quest Diagnostics. Our goal is to obtain a 22 mL blood sample (10mL purple top EDTA tube, 4mL EDTA purple top tube, and 8mL plasma separator tube for DNA extraction) from all women. If a participant is unwilling or contraindicated to give a blood sample but would be willing to provide a saliva sample for DNA extraction (or if blood collection was prevented due to the COVID-19 pandemic), an Oragene kit is sent to the participant with instructions for collection of a saliva sample.

Formalin Fixed Paraffin-Embedded (FFPE) Tumor Tissue. For participants who signed a specimen release form, study staff contact the pathology department at the institution where the patient was diagnosed and request pathology reports and tumor blocks that are representative of the primary ovarian cancer. If the hospital pathologist is unwilling to release FFPE tumor blocks, we request 25 5-micron unstained slices. For those that we receive FFPE tumor tissue blocks, the pathology laboratory at Emory prepares 25 5-micron slides and selects 3 cores from the primary tissue to assemble tissue microarrays (TMAs). A pathology slide is prepared for each of the tissues received and stained with hematoxylin and eosin (H&E). Immunofluorescent staining of selected immune markers is in process for both phases [29].

Specimen Processing and Storage. For phase 1, blood and saliva samples are stored at the Biofluids Shared Resource at Duke. Upon receipt, DNA was extracted and quantified using Quant-iT PicoGreen from Thermo Fisher Scientific. All samples are barcoded and tracked in the Laboratory Information Management (LIM) system. For phase 2, samples are processed and stored at Mayo Clinic Bioservices. 10mL EDTA tubes are centrifuged at lab standards to create four plasma aliquots at 1000uL each and one white blood cell aliquot. 4mL EDTA tubes are used to create two DNA aliquots. 8mL plasma separator tubes are centrifuged immediately after blood draw and Mayo Clinic Bioservices creates four plasma aliquots at 900uL each once samples are received. If a saliva sample is collected instead of blood, accessioning and automated DNA extraction are performed to create two DNA aliquots and are stored for future genotyping.

We genotyped all study subjects enrolled in Phase 1 with an available germline DNA sample using the Illumina OncoArray [30]. In phase 2, we are considering using an array that better addresses genetic variation in minority populations [31].

Pathology

Eligible participants for phase 2 were based on International Classification of Diseases for Oncology, 3rd Edition (ICD-O-3) site and morphology codes for EOC which incorporate 2021 updates in the WHO Classification of Tumors, 5th Edition, Volume 4: Female Genital Tumors. These codes and their descriptions are shown in Supplemental Table 1. The eligible ICD-O cancer sites are ovary (C56.9), fallopian tube (C57.0), retroperitoneum (C48.0), specified parts of the peritoneum (C48.1), peritoneum (C48.2), overlapping lesions of retroperitoneum & peritoneum (C48.8), and overlapping lesions of female genital organs: tubo-ovarian (C57.8).

Medical Record Abstraction (Acquisition and Review)

All study participants in phase 1 and 2, diagnosed with EOC, are asked to sign a medical record release form and tumor tissue release form as well as the name of the institution where the diagnosis took place. Information on each participant’s frontline chemotherapy regimen (neoadjuvant and adjuvant, start and end date, name of agent, number of cycles, dose), debulking surgery (type, date), residual disease, debulking status, CA125 levels before and after adjuvant chemotherapy, white blood cell counts before surgery and treatment, and anthropometric measurements at initiation of chemotherapy is collected to the extent possible.

Follow-Up and Vital Status Collection

In phase 1 annual follow-up interviews were attempted to collect the information described above, as well as to capture any updates in contact information and length of survival. The goal for time between baseline interview and follow-up was one year. When follow-up interviews were not possible, a thorough search with the National Death Index was implemented to obtain date and cause of death where applicable. We are also in the process of using LexisNexis to further identify vital status and survival time. We plan to continue these processes for phase 2.

Statistical Analysis

Variable Distribution. We generate descriptive statistics of our study population including basic demographics, clinical characteristics, and inflammatory-related factors that are displayed for all participants at baseline and by follow-up status, which was defined as completion of at least one follow-up survey or not. Demographics include variables such as age at diagnosis, marital status (single/never married, married/living as married, divorced/separated, widowed), highest level of education achieved (high school or less, some college, college graduate, graduate/professional school), insurance status (Medicaid/none, any other combination), and total annual family income (<$10,000, $10,000-$24,999, $25,000-$49,999, $50,000-$74,999, $75,000-$100,000, >$100,000). Clinical characteristics included summary stage, FIGO stage, histotype, time between baseline and follow up surveys (where available), residual disease (residual tumor diameter after cytoreductive debulking surgery; no residual disease, < 1 cm residual tumor diameter, ≥ 1 cm residual tumor diameter, residual disease but unknown size of tumor), and debulking status (optimal [no residual disease or < 1cm residual tumor diameter], suboptimal [≥ 1 cm residual tumor diameter]); described in further detail below). Physical inactivity is classified into categories of < 2 hours per week vs ≥ 2 hours per week. Physical Activity Guidelines for Americans (PAGA) consider insufficient physical activity to be < 2.5 hours of moderate activity or < 1.25 hours of vigorous physical activity [32]. Other factors include aspirin and other non-steroidal anti-inflammatory drug (NSAID) use, body mass index (BMI, kg/m²), smoking status (never, former, current), talc use (ever vs never), oral contraceptive duration (never, < 5 years, ≥ 5 years), hormone replacement therapy duration (never, < 5 years, ≥ 5 years), parity (number of full-term pregnancies), prior diagnosis of breast cancer, prior diagnosis of any cancer excluding breast cancer, and the Charlson comorbidity index [33].

Debulking Status. As debulking status is one of the most important prognostic factors [34, 35], particular care is taken to minimize missing data. Upon medical record abstraction, data on residual disease and debulking status was coalesced. If residual disease or debulking status is missing and debulking surgery was performed, CA125 levels at the end of frontline adjuvant chemotherapy is used as a proxy [36–38]. CA125 < 35 units/mL was classified as optimal debulking (or < 1 cm residual tumor diameter), and CA125 ≥ 35 units/mL was classified as suboptimal. Using the White-Royston method [39], we imputed debulking status for participants still missing debulking status using site, histology, stage, receipt of frontline adjuvant chemotherapy, receipt of frontline neoadjuvant chemotherapy, and age at diagnosis.

Survival Comparisons of AACES Participants to SEER Data. In order to better understand the population that is captured by AACES, we used SEER*Stat [40] to compare survival rates from our data to women diagnosed with ovarian cancer between 2008–2013 for sufficient sample size and a comparative length of follow-up time. We standardized Kaplan-Meier estimates from Black women in SEER to the AACES age distribution. Further, after fitting several conditional curves based on surviving past specific time points, we determined the survival proportions for Black women within SEER data conditioning on at least 10 months of survival post-diagnosis to account for the low response rates among the sickest women and those with aggressive disease. Additionally, to assess the racial disparity related to ovarian cancer survival in our study population we determined the same set of conditional age-standardized Kaplan-Meier estimates for White women.

To compare the distribution of histotype-specific survival, we determined age-standardized Kaplan-Meier estimates for the 5 major histotypes: high-grade serous, low-grade serous, mucinous, clear cell, and endometrioid. Here we also conditioned on at least 10 months survival time to enable comparison of the overall population of Black women with ovarian cancer and the AACES study participants.

AACES Phase 1 Accrual

Of 1,720 potential participants interviewers attempted to contact, 1,199 (70%) were actively reached. Of these, 592 (49%) were interviewed, and 388 (32%) actively refused. Using rapid case ascertainment, the average and median time from diagnosis to the baseline survey interview for participants in phase 1 was 7.1 and 5.8 months, respectively.

Among the 592 patients in phase 1, 540 agreed to provide their medical record and tissue sample (91%). Of these, 497 medical records were obtained (92%) and 437 FFPE tumor tissue samples (81%) were obtained. Phase 1 participants have been followed annually through 2016 and again in 2021, with 228 (39%) participants who remain alive and 364 (61%) participants deceased as of the latest update in 2021. For all women with EOC, overall survival ranged from 0.5 years to 10.6 years with a median of 4.8 years. A total of 577 (97%) participants survived at least 10 months past diagnosis. The mean and median time to the first follow-up survey was 1.6 and 1.2 years, respectively. Participants with 2 or more follow-up survey completions (N = 104) had an average time to first follow-up of 1.3 years (median: 1.2 years).

The participants who did not complete any follow-up survey (N = 294) are further described according to whether they died before being contacted or rather were lost to follow-up. During phase 1, interviewing ended in April 2016, and therefore, 70 (24%) participants who were interviewed at baseline in April 2015 or later were not eligible to complete follow-up surveys until phase 2 had begun but were deceased upon the start of phase 2. An additional 67 (23%) participants who did not complete a follow-up survey died within a year of their baseline interview over the course of phase 1, and 157 (53%) did not complete a follow-up survey due to other reasons (i.e. no answer on the phone, phone number no longer in service, active refusal, passive refusal via failing to schedule an interview, passive refusal via failing to attend a scheduled interview).

As shown in Table 1, AACES phase 1 participants demonstrated better survival than age-standardized Black women in SEER but were virtually the same after conditioning on survival of at least 10 months. Comparing survival of this age-standardized group of Black women in SEER to that of age-standardized White women in SEER (when looking at unrestricted survival and when conditioning on at least a 10-month survival time), Black women have consistently poorer survival (p-value < 0.0001) (Fig. 3).

Table 1

Overall Survival (OS) Rates for AACES and SEER, Black and White EOC
	AACES 2010–2015	SEER AA^a,b 2008–2013	SEER AA^a,b 2008–2013, given ≥ 10 months survival	SEER White^b,c 2008–2013	SEER White^b,c 2008–2013, given ≥ 10 months survival
Months	%, N = 592	%, N = 1,828	%, N = 1,342	%, N = 16,630	%, N = 14,296
12	97	73	97	87	98
24	81	61	80	76	86
36	67	52	67	67	75
48	56	45	58	59	67
60	49	39	51	53	60
^aBlack women diagnosed with first primary ovarian cancer, restricted to histology codes eligible in AACES 1
^bAge standardized to AACES age distribution
^cWhite women diagnosed with first primary ovarian cancer, restricted to histology codes eligible in AACES 1
Note: 14% (N = 2,334) of White women died within 10 months, while 27% (N = 486) of Black women died within 10 months.

Survey Results. The distributions of the epidemiological, clinical and tumor characteristics of the phase 1 participants in AACES are summarized in Table 2 and include sociodemographic characteristics, other inflammatory-related exposures and comorbidities, and tumor and clinical characteristics. Due to some participants opting to complete an abbreviated version of the survey, variables not included in this version, such as insurance status and annual family income, are missing at higher rates (N = 51; 9%).

Table 2

–Characteristics by Follow-Up Completion
		Follow-Up Status
	Group 1: Full Baseline Cohort (N = 592)	Group 2: Completed ≥ 1 Follow-Up (N = 298)	Group 3: No Follow-Up (N = 294)	p-value
	N (%)	N (%)	N (%)
SES-Related & other Demographic Characteristics
Age at diagnosis (years)				0.45
20–40	29 (4.9)	13 (4.4)	16 (5.4)
41–60	309 (52.2)	163 (54.7)	146 (49.7)
61–75	254 (42.9)	122 (40.9)	132 (44.9)
Education				0.95
High School or less	302 (51.0)	155 (52.0)	147 (50.0)
Some college	106 (17.9)	51 (17.1)	55 (18.7)
College Graduate	112 (18.9)	56 (18.8)	56 (19.1)
Graduate/Professional School	72 (12.2)	36 (12.1)	36 (12.2)
Marital Status				0.61
Single/never married	142 (24.0)	65 (21.8)	77 (26.2)
Married/living as married	195 (32.9)	103 (34.6)	92 (31.3)
Divorced/separated	166 (28.0)	86 (28.9)	80 (27.2)
Widowed	89 (15.0)	44 (14.8)	45 (15.3)
Insurance status (before diagnosis)				0.39
Uninsured or Medicaid	172 (31.9)	85 (30.2)	87 (33.7)
Other	367 (68.1)	196 (69.8)	171 (66.3)
Missing	53 (-)	17 (-)	36 (-)
Total Family Income (year before diagnosis)				0.39
Less than $10,000	115 (21.7)	52 (18.7)	63 (24.9)
$10,000 to $24,999	125 (23.5)	72 (25.9)	53 (20.9)
$25,000 to $49,999	132 (24.9)	74 (26.6)	58 (22.9)
$50,000 to $74,999	79 (14.9)	39 (14.0)	40 (15.8)
$75,000 to $100,000	48 (9.0)	26 (9.4)	22 (8.7)
More than $100,000	32 (6.0)	15 (5.4)	17 (6.7)
Missing	61 (-)	20 (-)	41 (-)
Rural-Urban Commuting Area				0.01
Metropolitan	467 (86.6)	251 (88.4)	216 (84.7)
Micropolitan	44 (8.2)	14 (4.9)	30 (11.8)
Small Town	18 (3.3)	11 (3.9)	7 (2.7)
Rural	10 (1.9)	8 (2.8)	2 (0.8)
Missing	53 (-)	14 (-)	39 (-)
Inflammation-Related Factors
Anti-Inflammatory Medications before diagnosis
Aspirin	90 (16.9)	41 (14.6)	49 (19.3)	0.15
other NSAID	117 (21.9)	63 (22.5)	54 (21.3)	0.73
BMI (kg/m² – self-reported at initial interview)				0.86
< 18.5	5 (0.9)	2 (0.7)	3 (1.0)
[18.5, 25)	81 (13.8)	44 (14.8)	37 (12.7)
[25, 30)	155 (26.4)	78 (26.3)	77 (26.5)
30+	347 (59.0)	173 (58.2)	174 (59.8)
Missing	4 (-)	1 (-)	3 (-)
Smoking status				0.15
Never	327 (55.2)	176 (59.1)	151 (51.4)
Former	205 (34.6)	96 (32.2)	109 (37.1)
Current	60 (10.1)	26 (8.7)	34 (11.6)
Talc Use				0.97
Never	221 (37.3)	111 (37.2)	110 (37.4)
Ever	371 (62.7)	187 (62.8)	184 (62.6)
Physical Inactivity				0.88
Less than 2 hours weekly	331 (61.5)	172 (61.2)	159 (61.9)
2 + hours weekly	207 (38.5)	109 (38.8)	98 (38.1)
Missing	54 (-)	17 (-)	37 (-)
Hormonal- and Reproductive-Related Factors
PMH duration				0.58
None	488 (83.0)	250 (84.5)	238 (81.5)
< 5 years	61 (10.4)	27 (9.1)	34 (11.6)
5 + years	39 (6.6)	19 (6.4)	20 (6.8)
Missing	4 (-)	2 (-)	2 (-)
OC Duration				0.80
Never	178 (30.4)	86 (29.2)	92 (31.7)
< 5 years	234 (40.0)	120 (40.7)	114 (39.3)
5 + years	173 (29.6)	89 (30.2)	84 (29.0)
Missing	7 (-)	3 (-)	4 (-)
Parity				0.83
0	109 (18.4)	54 (18.1)	55 (18.7)
1	105 (17.7)	48 (16.1)	57 (19.4)
2	143 (24.2)	74 (24.8)	69 (23.5)
3	113 (19.1)	57 (19.1)	56 (19.0)
4+	122 (20.6)	65 (21.8)	57 (19.4)
Other Comorbidities
Previous Cancer Diagnosis
Prior cancer (excludes breast cancer)	27 (4.6)	11 (3.7)	16 (5.4)	0.30
Prior breast cancer*	39 (6.6)	25 (8.4)	14 (4.8)	0.08
Charlson Comorbidity Index¹				0.30
0	216 (36.5)	113 (37.9)	103 (35.0)
1	136 (23.0)	75 (25.2)	61 (20.7)
2	99 (16.7)	44 (14.8)	55 (18.7)
3+	141 (23.8)	66 (22.1)	75 (25.5)
Clinical Characteristics
Time between Baseline & Follow-Up (months)
Median [Min, Max]		14.93 [6.18, 108.00]
Mean (SD)		19.13 (14.48)
Time Between Diagnosis & Death or Last Contact (years)
Median [Min, Max]	4.81[0.45, 10.59]	6.21 [1.77, 10.59]	2.74 [0.45, 10.18]
Mean (SD)	4.79 (2.62)	5.95 (2.33)	3.63 (2.38)	< 0.01
Vital Status as of 2021				< 0.01
Alive	228 (38.5)	141 (47.3)	87 (29.6)
Deceased	364 (61.5)	157 (52.7)	207 (70.4)
Stage*				0.09
Localized	131 (23.8)	79 (27.5)	52 (19.7)
Regional	52 (9.4)	27 (9.4)	25 (9.5)
Distant	368 (66.8)	181 (63.1)	187 (70.8)
Missing	41 (-)	11 (-)	30 (-)
FIGO Stage				0.51
I	130 (25.6)	74 (27.4)	56 (23.5)
II	57 (11.2)	31 (11.6)	26 (10.9)
III	227 (44.7)	121 (44.8)	106 (44.5)
IV	94 (18.5)	44 (16.3)	50 (21.0)
Unknown/Unstaged	84 (-)	28 (-)	56 (-)
Histotype*				0.08
High-Grade Serous	397 (67.7)	204 (68.5)	193 (67.0)
Low-Grade Serous	17 (2.9)	9 (3.0)	8 (2.8)
Endometrioid	57 (9.7)	32 (10.7)	25 (8.7)
Clear Cell	23 (3.9)	17 (5.7)	6 (2.1)
Mucinous²	29 (4.9)	13 (4.4)	16 (5.6)
Carcinosarcoma	18 (3.1)	7 (2.4)	11 (3.8)
Other Epithelial	45 (7.7)	16 (5.4)	29 (10.1)
Missing	6 (-)	0 (-)	6 (-)
Debulking Status, CA125*				0.07
Optimal	255 (66.6)	151 (72.6)	104 (63.8)
Suboptimal	116 (30.3)	57 (27.4)	59 (36.2)
No debulking surgery	12 (3.1)	1 (-)	11 (-)
Missing	209 (-)	89 (-)	120 (-)
p < 0.10; *p < 0.05 when comparing follow-up to no follow-up
¹Charlson index uses the following comorbidities: asthma, arthritis, diabetes, digestive issues, heart trouble, HIV/AIDs, kidney disease, liver disease, & stroke
²includes both invasive and borderline

Sociodemographic and health care access characteristics of the AACES population have potential importance with regards to determinants of health disparities. The highest level of education of approximately half of the participants was high school or less (51%), almost half reported a total family income of less than $24,999 annually (45%), one third of participants were married or living as married (33%), and close to one-third of participants were uninsured or had Medicaid coverage (32%) (Table 2). Among women reporting the lowest annual family income in phase 1 (<$10,000), participants were more likely to have Medicaid or no insurance (63%) and have a high school education or less (77%).

There were no clear differences in SES-related factors and other basic demographic characteristics by women who completed at least one follow-up survey and those who did not. However, participants who were deceased before the follow-up survey were older at diagnosis than those who could not be followed for other reasons, with a mean age of 61 years (SD = 10.8) compared to 55 years (SD = 11.2) (${\chi }^{2}$ p < 0.001), respectively.

Overall, almost a quarter of AACES participants had high Charlson scores (≥ 3 comorbid conditions, 24%), more than half reported being obese (BMI one year prior to diagnosis ≥ 30 kg/m², 59%), more than half reported never smoking (55%), almost two-thirds reported previous talc use (63%), almost two-thirds reported less than 2 hours of physical activity per week (62%), the majority reported never using post-menopausal hormones (83%), and the majority reported ever using oral contraceptives (70%) (Table 2).

Of note, obesity did not differ according to participation in the follow-up survey (Table 2). Those who did not participate in the follow-up survey were more likely to report they were a current smoker and less likely to have never smoked compared to those who participated in at least one follow-up survey (current: 37% vs 32%; never: 51% vs 59%) (Table 2). Participants who were deceased before follow-up were more likely to have higher scores on the Charlson comorbidity index than those who were lost to follow-up for other reasons, with 70% and 61% reporting a non-zero Charlson score, respectively (p = 0.086).

Tumor and Clinical Data. The distribution of the tumor characteristics including stage at diagnosis and histotype is shown in Table 2. Most participants were diagnosed at FIGO stage III/IV (63%), a major determinant of poor survival, and most had high-grade serous tumors (68%). The least common histotypes were low-grade serous (3%) and carcinosarcoma (3%).

Those who completed at least one follow-up survey were less likely to have stage III/IV disease compared to those who did not participate, 61% vs 66%, respectively. When comparing participants who completed at least one follow-up survey to those who did not complete a follow-up survey, participants were slightly more likely to be diagnosed with FIGO stage I disease, 27% vs 24%, respectively, and slightly less likely to be diagnosed with FIGO stage IV disease, 16% vs 21%, respectively. The distribution of histologic subtypes was similar across the baseline and follow-up groups, with most women having high-grade serous ovarian cancer.

Half of the women with high-grade serous ovarian cancer who were lost to follow-up were deceased at the first attempt of follow-up (50%), and this was the highest rate among the five major histotypes. Similarly, approximately half of the women diagnosed at FIGO stage III/IV were lost to follow-up because they were deceased at the first attempt to contact (51%). More than half of participants who had suboptimal debulking were lost to follow-up because they were deceased at the first attempted contact (56%).

The proportion of the five major histotypes among participants in AACES compared to the proportion in SEER data for Black women, respectively, are similar: 75.9% vs 77.8% HGS, 3.3% vs 2.7% LGS, 10.9% vs 7.4% endometrioid, 4.4% vs 4.6% clear cell, and 5.5% vs 7.5% mucinous (p > 0.10). Supplemental Fig. 1 shows Kaplan-Meier survival curves by the five major histotypes in AACES and in SEER. The poorest overall survival is seen for women with high-grade serous ovarian cancer, while women with endometrioid tumors have the best survival. To date in AACES, more than two-thirds of women who were diagnosed with high-grade serous ovarian cancer are deceased (69%), compared with approximately one-fifth of women diagnosed with endometrioid ovarian cancer (19%). When comparing these to the similar Kaplan-Meier estimates from SEER data, we see similar survival for women with high-grade serous, mucinous, and endometrioid cancers.

After medical record abstraction, 12 participants did not receive debulking surgery. Of the remaining 580, information on residual disease/debulking status was available on 340 participants (59%). Among women who were missing this information and whose CA125 level at the end of adjuvant chemotherapy was used as a proxy for debulking status (n = 43), 32 women were classified as having optimal debulking (CA125 < 35 units/mL), and 11 women were classified as having suboptimal debulking (CA125 ≥ 35 units/mL). By incorporating CA125 levels, information on debulking status was available on 383 participants (65%), and the missing data was reduced to 209 participants (35%).

At baseline, approximately one-third of the participants had any residual disease, while one-third had no gross residual disease. However, no information on residual disease was recorded for approximately one-third of the participants. Comparing participants by follow-up survey completion, women who completed at least one follow-up survey were more likely to have no residual disease. Optimal debulking status, which is correlated with residual disease, was also highest among those who participated in at least one follow-up survey. In Supplemental Fig. 3, we also show that the survival curve among those with missing debulking status fell in-between those whose debulking status was either optimal or suboptimal. This suggests that data were missing at random with respect to debulking status, and therefore imputation of the missing data would likely be unbiased.

Participants with optimal, suboptimal, and missing debulking status have a median survival of 7.1, 3.0, and 4.9 years, respectively. In preliminary analysis, we find a similar hazard ratio (HR) for the complete-case group analysis (HR = 0.43; 95% CI = 0.32, 0.60) compared with the estimate computed using multiple imputation (HR = 0.46; 95% CI = 0.36, 0.60).

Based on the baseline survey data, except for having reported a prior breast cancer diagnosis, comorbid conditions were similar irrespective of participation in at least one follow-up survey. The proportion of those with a prior breast cancer diagnosis was greatest among those who completed at least one follow-up survey. There was a trend for a higher distribution of the Charlson Comorbidity Index among those who did not participate in the follow-up survey compared to those who did.

Genetic Variants and Tumor Biomarkers. AACES has contributed significantly and will continue to contribute to the genetic susceptibility and tumor biomarker research of ovarian cancer in Black women. Our GWAS findings were reported by Manichaikul et al. [41] suggesting similarities and differences in genetic association in Black compared to White women. Future plans include assessing genetic variation in AACES phase 2. Initial results from multiplex immunofluorescence staining of immune markers and survival of Black women in AACES are found in Peres et al. [42]

AACES Phase 2 Preliminary Response Rates

Phase 2 is currently ongoing. To date, of 271 eligible potential participants, 138 (51%) were successfully contacted. Of these, 55 (40%) completed an interview, 53 (38%) actively refused, and 30 (22%) are pending. Participants in phase 2 range in age from 27 to 80 years at interview, with a mean of 60 years (SD = 10.6). Fifteen women (29%) reported confirmed or likely exposure to COVID-19, and 11 (22%) reported a positive COVID-19 test result. 19 (40%) have a score of 0 on the Charlson comorbidity index, and 14 (29%) have a score of 3 or more.

Here we describe a multi-level approach to determine associations between epithelial ovarian cancer survival and factors associated with the social and built environment, individual patient characteristics, and the tumor immune microenvironment with the goal to examine the full spectrum of exposure variables and clinical factors to help characterize the “whole person.” Our scientific rationale is based on the premise that multiple factors contribute to the poor survival of ovarian cancer among Black women compared with other racial and ethnic groups and that many of these factors have a synergistic relationship or mediate the relationship with inflammatory and immune processes.

Our biospecimen collection, with an unprecedented number of well-annotated specimens, represents an important resource for the molecular characterization of EOC diagnosed in Black women. The purpose of the study is to generate needed evidence to address the racial disparity in EOC survival. Most large medical claims databases examining racial and ethnic differences in ovarian cancer survival lack information on lifestyle behaviors and beliefs that may be key to the interactions with the health care system. AACES provides a rigorously designed and truly unique resource to achieve our goal of understanding factors that influence mortality to better understand why Black women experience worse survival after a diagnosis of EOC. AACES integrates key data that will address this critical evidence gap and provide a major step forward in understanding multilevel predictors of poor EOC prognosis in Black women. The resulting evidence will inform translational strategies to reduce this racial disparity. To illustrate this point, we recently published a paper based on AACES phase 1 participants that showed perceived everyday discrimination was associated with prolonged symptom duration, whereas more commonly evaluated determinants of access to care and trust in physicians were not [43].

A major strength of AACES is that participants reside in over 11 geographic regions in the US, both in the east and west coast as well as southern and northern regions. With substantial proportions of the cohort having relatively low levels of household income, education, and insurance coverage, AACES will be well-positioned to assess the contribution of social determinants of health to the racial disparity in ovarian cancer survival.

Related to social determinants of health, this cohort is also characterized by a high prevalence of obesity and comorbidities. A large study exploring racial and ethnic disparities found that 36% of Non-Hispanic White women are obese, while 59% of Non-Hispanic Black women are obese [44]. This prevalence of obesity in Black EOC cases is equivalent to the proportion found in our population. In another study using data from the National Health Interview Study (NHIS), the rates of multiple comorbidities are roughly similar to that in the AACES. When age-adjusting their estimates, approximately 66% of Non-Hispanic Black women reported either having 0 or 1 comorbidities, while approximately 74% of Non-Hispanic White women reported having 0 or 1 comorbidities [45]. While this raw count is not strictly comparable to the Charlson comorbidity index (some more severe comorbidities are weighted > 1), 60% of the women in our sample have a Charlson score of 0 or 1. This is naturally a slight undercount of number of comorbidities, so it makes sense for this proportion to fall under that of the general population.

The distribution of the variables related to social determinants of health along with the high prevalence of factors such as obesity and comorbidities that lead to worse prognosis, will enable the AACES to generate needed evidence on the role that these factors, alone and in combination, contribute to Black women having the lowest survival from ovarian cancer. Integrating information such as mentioned above related to perceived discrimination will further enrich the insights that can be gained in this patient population.

Comparisons of the survival of women with EOC in phase 1 of AACES to that in the SEER database suggests that AACES phase 1 participants are representative of those who survive at least 10 months since their diagnosis. Therefore, our study population may underrepresent the sickest patients diagnosed with EOC. When conditioning on having survived at least 10 months, the survival among Black women in AACES is worse compared to White women diagnosed with EOC in the SEER database. Due to these findings, inferences from the AACES results will likely not be as generalizable to women with the most severe disease. The appearance of poorer low-grade serous ovarian cancer survival and better clear cell ovarian cancer survival in the AACES sample may be due to the small number of women with these histotypes in AACES. Some of this could also be due to differences in stage at diagnosis. Due to the underrepresentation of the sickest patients diagnosed with EOC, women diagnosed with clear cell tumors at a later stage and poorer prognosis could be missing from the AACES sample.

We compared baseline data among women in AACES phase 1 who did or did not participate in at least one follow-up survey showing differences with those completing at least one follow-up survey being younger at diagnosis, having fewer comorbid conditions, being less likely to have ever smoked, having less distant stage disease at diagnosis, and having less residual disease after debulking surgery. The higher proportion of women who completed a follow-up survey reporting a previous breast cancer could be underrepresenting women who had more severe breast cancer and did not survive long enough to develop ovarian cancer. Approximately 50% of study subjects completed at least one follow-up survey and these women had a median survival of more than 6 years compared to less than 5 years for AACES 1 phase participants overall. In SEER, the median survival time among Black women with EOC is approximately 5 years. Therefore, women completing the follow-up survey are survivors of a highly fatal disease and overrepresent younger women with less severe disease and lower comorbidity burden. Nevertheless, AACES appears to have a similar survival experience compared to the few studies addressing ovarian cancer survival. A study from Australia reported an average follow-up of 7.3 years with only 45% alive after 5 years from diagnosis [46] and recent cohort study of ovarian cancer patients in China reported a median follow-up time of 3.1 years [47], although these studies do not include Black women with EOC.

We continue to improve our methods for accrual of patients. As funding began in July 2020, we experienced delays due to the COVID 19 pandemic but cannot fully assess the impact on our study since we cannot know about women we were unable to reach. We have highlighted several strategies that we have undertaken to improve recruitment and retention, mainly providing ample scheduling flexibility and many options for questionnaire administration. We will continue adapting our methods to accommodate ongoing pandemic challenges.

Implications for Cancer Survivors

Population-based epidemiologic studies present many challenges. In this paper, we layout the anatomy of a unique multi-center study of a rare cancer in an underserved minority population. Ongoing work will address how neighborhood disadvantage, lifestyle behaviors, and the tumor immune microenvironment interact to affect ovarian cancer prognosis in Black women. Our findings will have the potential to shed light on the causes of the persistent racial disparities in EOC survival and provide strategies towards cancer health equity.

Acknowledgments

We would like to acknowledge the AACES interviewers, Brandy Arredondo, Rachel Boehm, Dannelle Charles, Melody Chavez, Lauren Dempsey, Kierstin Faw, Juliana Fucinari, Mary Kan, Mary Beth Kolbicz, Arianna Mason, Juana Paniagua, and Maelia Pendley. We also acknowledge the individuals responsible for facilitating case ascertainment across the sites including: Kevin Ward and Mackenzie Crawford (Georgia); Tingting Li and Lauren Maniscalco (Louisiana); Dhanya Chanumolu and Myneka Macenat (New Jersey); Paul Terry (Tennessee); Ann Hamilton (California), Mary Beth Kolbicz (Michigan); Cynthia Webb, JoElla Marting, and Heather Tipaldos (North Carolina); and Maxwell Akonde, Stephanie Chiodini, and Deb Hurley (South Carolina).

Funding

The AACES study was funded by the National Cancer Institute (R01CA142081 & R01CA237318). Additional support was provided by Metropolitan Detroit Cancer Surveillance System (MDCSS) with federal funds from the National Cancer Institute, National Institute of Health, Dept. of Health and Human Services, under Contract No. HHSN261201000028C and the Epidemiology Research Core, supported in part by NCI Center Grant (P30CA22453) to the Karmanos Cancer Institute, Wayne State University School of Medicine. This work has been supported in part by the Participant Research, Interventions, and Measurements Core Facility at the H. Lee Moffit Cancer Center & Research Institute, an NCI designated Comprehensive Cancer Center (P30-CA076292).

Competing Interests

The authors have no relevant financial or non-financial interests to disclose.

Author Contributions

The following authors were a part of the writing group: Joellen Schildkraut, Lauren Dempsey, Courtney Johnson, Anthony Alberg, Paul Terry, Elisa Bandera, Bo Qin, Hannah Mandle, Michele Cote, Maxwell Akonde, and Edward Peters. The analysis was completed by: Courtney Johnson.

The following authors provided comments and edits to the manuscript: Lauren Peres, Patricia Moorman, Ann Schwartz, Michael Epstein, and Andrew Lawson.

The following authors helped in development of the surveys: Patricia Moorman, Joellen Schildkraut

The following authors helped in data collection: Joellen Schildkraut, Anthony Alberg, Patricia Moorman, Elisa Bandera, Paul Terry, Maxwell Akonde, Edward Peters, Michele Cote, Jeffrey Marks, Melissa Bondy, Ann Schwartz, and Hannah Mandle.

Data Availability

The datasets generated during and/or analyzed during the current study are available on reasonable request, in accordance with NIH data sharing policy.

Ethics Approval

This study was approved by the Western Institutional Review Board-Copernicus Group (WCG IRB).

Consent to Participate

Informed consent was obtained from all individual participants included in the study.

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No competing interests reported.

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Survival of epithelial ovarian cancer in Black women: a society to cell approach in the African American Cancer Epidemiology Study (AACES)

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Version 1

Abstract

Figures

Introduction

Methods

The AACES Study Design

Baseline and Follow-Up Surveys

Geocoding and Area-Level Variables

Biospecimen Collection

Pathology

Medical Record Abstraction (Acquisition and Review)

Follow-Up and Vital Status Collection

Statistical Analysis

Results

AACES Phase 1 Accrual

AACES Phase 2 Preliminary Response Rates

Conclusions

Implications for Cancer Survivors

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1