Background:

Through adequate screening and follow-up, cervical cancer can be prevented or detected at early-stage (stage I), which is related to excellent survival. Current guidelines recommend discontinuing screening for women ≥65 years with history of normal Pap and/or HPV tests, potentially leaving this age group vulnerable. This study examined late-stage disease in a population-based cohort.

Methods:

Using California Cancer Registry data, we identified 12,442 patients ages ≥21 years with a first primary cervical cancer diagnosed during 2009–2018. Proportions of late-stage disease (stages II–IV) and early- and late-stage 5-year relative survival are presented by the age group. Among patients ages ≥65 years, multivariable logistic regression estimated associations of sociodemographic and clinical characteristics with late-stage cervical cancer.

Results:

Nearly one fifth of patients (n = 2,171, 17.4%) were ≥65 years. More women ages ≥65 years (71%) presented with late-stage disease than younger women (48% in patients ages <65). Late-stage 5-year relative survival was lower for women ≥65 years (23.2%–36.8%) compared with patients <65 (41.5%–51.5%). Characteristics associated with late-stage cervical cancer in women ≥65 years included older age [odds ratio (OR), 1.02; 95% confidence interval (CI), 1.01–1.04; each year], non-adenocarcinoma histologic subtypes, and comorbidities (OR, 1.59; 95% CI, 1.21–2.08).

Conclusions:

There remains a significant burden of advanced cervical cancer in women ≥65.

Impact:

Efforts should be made to better understand how the current screening paradigm is failing women of 65 years and older. Future work should focus on determining past screening history, lapses in follow-up care, and non-invasive testing approaches.

Although effective screening for cervical cancer exists and can detect pre-malignant lesions and early-stage (stage I) disease (1, 2), many women in the United States (US) present with late-stage disease (stages II–IV; ref. 3). Following the introduction and widespread adoption of the Papanicolaou (Pap) smear test in the 1940s, cervical cancer incidence and mortality have fallen significantly (4, 5). However, incidence rates have plateaued since 2012, and rates of invasive cervical cancer have actually increased in recent decades (5). Furthermore, from 2015 to 2019, nearly half of cervical cancers in the US were diagnosed late-stage (6). Prior research suggests that women ≥65 years had a greater burden of cervical cancer with higher incidence and more late-stage diagnoses (7–10).

The American Cancer Society, the US Preventive Services Task Force, and the American College of Obstetricians and Gynecologists all recommend that cervical cancer screening end for women >65 years with adequate negative prior screening (3 consecutive normal Pap tests, two consecutive negative HPV tests, or two consecutive negative cotests with Pap and HPV within the prior 10 years, with the most recent screening occurring within the previous five years, and no diagnosis of a precancerous lesion in the past 25 years; refs. 1, 11, 12). However, 23.2% of women in the US ≥18 are not up-to-date on recommended cervical cancer screening (13). For example, disadvantaged subgroups in the US, including uninsured women and those of lower socioeconomic status were the least likely to report being up to date with cervical cancer screening compared with women of higher educational attainment (13, 14). In addition, screening adherence may decrease as women approach 65, thereby increasing the likelihood that women have not been adequately screened before the upper age cutoff value (15). As many as 58% of women of 64 to 66-years-old in a national database failed to meet the criteria to exit screening (16).

We therefore sought to examine cervical cancer stage at diagnosis and relative survival in women ≥65 years. Previous studies have focused on differences in incidence, mortality, and therapeutic management for younger women (<65) diagnosed with cervical cancer versus older groups (7, 9, 15). However, they have not considered adjusted sociodemographic and clinical characteristics associated with late-stage cervical cancer in women ≥65 years or associated relative 5-year survival by stage at diagnosis compared with younger age groups within the screening criteria. Therefore, this study used large population-based data from the California Cancer Registry (CCR) to examine cervical cancer relative survival by stage at diagnosis and characteristics associated with late-stage disease among women ≥65 years.

Study population

The CCR is a state-mandated population-based cancer surveillance system that has collected cancer incidence and patient demographic, diagnostic, and treatment information since 1988. Statewide data are collected through a network of regional registries that are affiliated with the National Cancer Institute's Surveillance, Epidemiology and End Results program (SEER). The CCR has consistently met the highest national standards for data quality and completeness. We used CCR to identify all women ≥21 years who were diagnosed with a first primary cervical cancer in California from 2009 to 2018, the 10 most recent years for which complete data were available. Cervical cancer was identified using the SEER site recode International Classification of Diseases for Oncology, 3rd edition (ICD-O-3; ref. 17) code 27010 with the histologic subtypes grouped into adenocarcinoma (8098, 8140–8245, 8250–8500), squamous cell carcinoma (8050–8084), and other histologies (8000–8046, 8130, 8246, 8560, 8570, 8720–9473). Patients diagnosed posthumously (n = 81) were excluded. In total, 13,485 patients were identified, including 2,420 patients ≥65 years. However, for the main analysis, 1,043 (7.7%) patients diagnosed at unknown stage were excluded; 12,442 total patients and 2,171 ≥65 years remained.

Sociodemographic and clinical characteristics

Patient demographic and clinical characteristics included stage at diagnosis, histologic subtype, comorbidity, neighborhood socioeconomic status (nSES), health insurance status, urbanicity, marital status, race/ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic, Asian/Pacific Islander, and other/unknown), age at diagnosis, and year of diagnosis. Stage at diagnosis was determined by using American Joint Committee on Cancer staging rules (18). We defined early-stage as stage I, as the International Federation of Gynecology and Obstetrics classifies stage I as disease confined to the organ of origin, similar to localized stage; late-stage was classified as stages II–IV as they are similar to regional and distant stages (19).

To capture patient comorbidities, we used a modified Charlson comorbidity score, a weighted index of 16 comorbid conditions, not including cancer, diagnosed from 12 months before 6 months following cancer diagnosis (20). Comorbidities were categorized as having none, one, ≥2, or missing comorbidity information. nSES is derived using principal components analysis of aggregated 2015–2019 block group level demographic, economic, social, and housing data collected through the American Community Survey using methods described previously by Yang and colleagues (21). nSES was categorized into tertiles (lowest, medium, and highest). Health insurance was categorized as private/military (health maintenance organization, preferred provider organization, Fee-For-Service, military insurance, and Medicare with supplement), public/Medicaid (Medicaid, county-funded, Indian Health Service or other public health service, Medicare with Medicaid eligibility, Medicare without supplement, Medicaid/Medicare), uninsured, and unknown. Urbanicity was determined using the California Health Manpower Policy Commission Medical Service Study Area urban/rural designation (22).

Statistical analysis

Five-year relative survival by the age group (20–39, 40–59, 60–64, 65–69, 70–74, 75–79, ≥80) and stage at diagnosis were calculated using SEER*Stat software (23). Relative survival was calculated using the US state-county 1992–2016 life tables by SES/geography/ race/ethnicity (non-Hispanic White, non-Hispanic Black, non-Hispanic Asian and Pacific Islander, non-Hispanic American Indian and Alaskan Native, and Hispanic), ages 0 to 99. Relative survival was calculated using the Ederer II method and is a net survival measure that estimates the probability of avoiding death due to cancer in the absence of other causes of death (24). It is defined as the ratio of the observed survival rate among those who have cancer divided by the expected survival rate for people of the same sex, race/ethnicity, and age who do not have cancer, and is expressed as a percentage.

Descriptive statistics (frequencies and percentages) and χ2 tests assessed unadjusted associations between cervical cancer stage (early and late) at diagnosis and the age group. Among women ≥65 years, multivariable logistic regression was used to assess sociodemographic and clinical characteristics associated with late-stage (stages II–IV vs. I). Models were adjusted for health insurance status, race/ethnicity, nSES, comorbidities, marital status, histologic subtype, year of diagnosis, and age in years. SAS version 9.4 was used to conduct analyses. Collinearity was examined using variance inflation factors and eigenvalues. Results are presented as adjusted odds ratios (OR) and 95% confidence intervals (CI). A two-sided P value of <0.05 was considered statistically significant. Sensitivity analyses were conducted, including unknown stage with stages II–IV, because Kaplan–Meier curves indicated that survival for those with unknown stage at diagnosis was similar to those with stage IV diagnosis and we wanted to assess the impact of excluding unknown stage at diagnosis on associations in our main analyses. All analyses were overseen by the Institutional Review Board of the University of California, Davis.

Data availability

The data analyzed in this study are available from the CCR. Access is granted through an application process by the management or data custodians (https://www.ccrcal.org/retrieve-data/).

Among 12,442 women diagnosed from 2009 to 2018 with a first primary cervical cancer, 17.4% (2,171) were ages ≥65 years (Table 1). The proportion of women diagnosed late-stage increased with increasing age through ages 75 to 79 (Fig. 1). Among women ≥65 years, the proportion diagnosed late-stage ranged from 60.2% to 70.6% compared with 33.5% to 58.7% for those ages 21 to 64 years. Among women diagnosed with early-stage disease, 5-year relative survival was lowest for women 80 years and older at 51.6%. For those 20–39, 40–59, 60–64, 65–69, 70–74, and 75–79, 5-year relative survival was 93.6%, 92.9%, 89.3% 81.5%, 86.2%, and 72.0%, respectively. Likewise, among those with late-stage cervical cancer, 5-year relative survival was lowest for women 80 years and older at only 23.2%. For those 20–39, 40–59, 60–64, 65–69, 70–74, and 75–79, 5-year relative survival was 51.5%, 47.5%, 41.5%, 36.8%, 39.1%, and 30.8%, respectively (Fig. 2).

Of 2,171 women ≥65 years, most patients were ages 65–69 (34.6%) followed by 70–74 (24.7%), 80 plus (23.1%), and 75–79 (17.5%). More women with early-stage disease at diagnosis were younger (65.7% 65–74 years and 34.3% ages 75 years and older) compared with women with late-stage disease at diagnosis (56.7% 65–74 years and 43.3% ages75 years and older). The most common histologic subtype for both early-stage and late-stage diagnoses was squamous cell carcinoma (67.0% early-stage; 69.3% late-stage), followed by adenocarcinoma (27.1% early-stage; 19.3% late-stage), and other subtypes (5.9% early-stage; 11.3% late-stage; Table 1). Compared with patients diagnosed at early-stage, those diagnosed at late-stage had ≥2 comorbidities, were unmarried, and had non-adenocarcinoma histologic subtypes.

In multivariable logistic regression models, among patients ≥65 years, factors associated with late-stage included older age at diagnosis (increase with each additional year of age, OR, 1.02; 95% CI, 1.01–1.04), ≥2 comorbidities (vs. no comorbidities: OR, 1.59; 95% CI, 1.21–2.08), squamous cell carcinoma histology (OR, 1.38; 95% CI, 1.10–1.74), or other subtypes (OR, 2.52; 95% CI, 1.68–3.79) versus adenocarcinoma (Table 2). Women of Hispanic ethnicity were less likely to be diagnosed with late-stage disease (OR, 0.76; 95% CI, 0.60–0.97) compared with non-Hispanic White women. Year of diagnosis, marital status, health insurance status, nSES, and urbanicity were not shown to be significantly associated with late-stage cervical cancer.

In sensitivity analyses, including unknown stage at diagnosis with late-stage, unmarried women were more likely to be diagnosed late-stage (OR, 1.27; 95% CI, 1.04–1.56; Supplementary Table S1). Late-stage disease was associated with older age, comorbidity, non-adenocarcinoma histology and less associated with Hispanic ethnicity, consistent with the main analysis that excluded unknown stage.

In our large population-based study in California, nearly 1 in 5 new cervical cancer cases diagnosed from 2009 to 2018 were in women ≥65 years, and these older women had lower 5-year relative survival for both early- and late-stage diagnoses than younger women, with women 80 years and older having the lowest survival of all age groups. We also observed that the proportions of late-stage diagnoses increased up to age 79 years. Among women ≥65 years, those who were older, had non-adenocarcinoma histology, and had comorbidities that were more likely to be diagnosed with late-stage disease.

Our study confirms findings from prior US-based studies that have noted substantial burden of cervical cancer, high rates of late-stage disease, and worse survival in women ≥65 years (7–10, 15). However, to our knowledge, prior studies have not examined cervical cancer 5-year relative survival by age group and stage at diagnosis. Our study found worsening 5-year relative survival with each increasing age grouping category for both early- and late-stage diagnoses.

Although we cannot determine the reason for these age disparities with our data, several factors may contribute. More late-stage diagnoses may be due to inadequate screening in women approaching 65 as noted previously (15). Some reasons cited for forgoing screening include discomfort, pain, embarrassment, and the intrusiveness of speculum-based exams (25, 26). Another reason can be lack of follow-up after an abnormal screen. As many as 50% of women with abnormal results do not receive follow-up care (27, 28). Comorbidities can also contribute to late-stage cancer diagnoses. Comorbidities increase with age and can result in a delayed diagnosis because of distraction from other health issues (29, 30). Worse survival with older age can result from more late-stage diagnoses but can also result from less aggressive treatments in women ≥65 years. Eggemann and colleagues (31) reported that patients ≥61 years were less likely to undergo surgery and radiochemotherapy compared with patients <61 years. Diver and colleagues (7) likewise found that women ≥65 years were less likely to receive surgery.

Another issue that could contribute to late-stage diagnosis is the use of supracervical hysterectomy. This procedure leaves the cervix intact and accounted for approximately 7.1% of laparoscopic hysterectomies in 2016 in the US (32). Unfortunately, some women do not realize the need to continue screening; Mattingly and colleagues (33) found that only 67% of women who had undergone minimally invasive hysterectomy correctly identified whether their cervix had been removed and if they needed screening. McHale and colleagues (34) found that 5.3% of women undergoing a secondary resection of a retained cervix after supracervical hysterectomy had cervical cancer.

Despite adequate prior screening, some women ≥65 years are still diagnosed with cervical cancer (35, 36). Pap testing can be difficult post-menopause when cytology tests may become less sensitive due to retraction of the squamocolumnar junction and vulvovaginal and cervical epithelium atrophy (26, 37). In addition, Pap testing is more effective at detecting squamous cell carcinoma and its precursors than adenocarcinoma that has been increasing in incidence (35, 38, 39). However, our study found that women with non-adenocarcinoma histologies were more likely to be diagnosed late-stage.

HPV testing provides increased sensitivity for cervical cancer precursors compared with Pap smear testing (11, 40, 41), but there is evidence that many women approaching age 65 years have not received HPV testing (42) and acceptance of it has been found to be low (43). Less intrusive options for HPV testing are becoming available, including self-testing through vaginal swabs and urine collection, and have been successfully used in other countries (44–47). Self-testing has been shown to be accurate and a good alternative to speculum-based exams that can be a reason to delay or altogether avoid testing as noted (25, 48).

Year of diagnosis was not associated with stage at diagnosis, indicating that the proportion of late-stage cervical cancer diagnosis has not changed over time among women ≥65 years in California. This differs from a previous US study that found that the proportion of regional and distant cervical cancer has in fact increased from 2001 to 2009 in most states, which might have been driven by the removal of pre-malignant lesions and the resulting increase in the proportion of invasive cervical cancer in unscreened women and those who did not receive adequate follow-up (49). However, our data are more recent and restricted to women ≥65 years, for many of whom advances in screening technologies and changes in guidelines were not applicable. This highlights the importance of ensuring women ≥65 years have met the screening criteria before exiting as well as strategies aimed at enhancing follow-up after abnormal screening tests.

Prior studies of younger women have found increased late-stage cervical cancer diagnoses among women of Hispanic ethnicity, African American/Black race, and lower SES (49–51). Our study did not observe these associations and instead found that older Hispanic women were less likely than non-Hispanic White women to be diagnosed late-stage. Consistent with prior studies (8), our sensitivity analyses suggest that unmarried women ≥65 years were diagnosed more often with late-stage cervical cancer. Increased late-stage diagnosis in unmarried patients could be related in part to differences in exposure to sexually transmitted infections between unmarried women and married women, as HPV is the causative agent in approximately 91% of cervical cancer cases (52). Although the percentage of HPV cases attributable to reactivation remains constant with age (18%–36%), the remaining HPV infections are caused by sexual exposure (53). The risk of acquiring HPV increases for women with new, casual, or concurrent sexual partners (53). In addition, unmarried patients may be diagnosed late-stage more often due to economic disadvantage and less social, emotional, and practical support compared with married patients (54).

Our study had some limitations. We were unable to determine adherence to screening guidelines of our cohort or capture any HPV information, such as new or recurring infection. In addition, we excluded 10.3% of women ≥65 years (n = 249) with unknown stage from our main analysis. However, when we included these women in our sensitivity analysis, our logistic regression results were similar. Despite these limitations, we used high-quality, large, population-based registry data to evaluate the stage at diagnosis and associated relative survival of women ≥65 years diagnosed with cervical cancer.

In California, nearly one fifth of cervical cancers were diagnosed in women ≥65 years and the majority were late-stage. Late-stage cervical cancer diagnoses increased with age and were associated with low 5-year relative survival of 36.8% to 23.2%. Our findings highlight the need to better understand how the current screening paradigm might be failing women ≥65 years. Future work should focus on determining past screening history of older women, determining lapses in follow-up care, and non-invasive testing approaches for women nearing age 65 years or those who might need catch-up screening.

No disclosures were reported.

The ideas and opinions expressed herein are those of the author(s) and do not necessarily reflect the opinions of the State of California, Department of Public Health, the National Cancer Institute, and the Centers for Disease Control and Prevention or their Contractors and Subcontractors.

J.J.P. Cooley: Conceptualization, resources, formal analysis, investigation, visualization, methodology, writing–original draft, writing–review and editing. F.B. Maguire: Conceptualization, resources, writing–review and editing. C.R. Morris: Conceptualization, supervision, writing–review and editing. A. Parikh-Patel: Writing–review and editing. R. Abrahão: Resources, writing–review and editing. H.A. Chen: Resources, writing–review and editing. T.H.M. Keegan: Supervision, writing–review and editing.

Research reported in this publication was supported by the UC Davis Comprehensive Cancer Center and National Cancer Institute of the National Institutes of Health under award number P30CA093373 (to T.H.M. Keegan). The collection of cancer incidence data used in this study was supported by the California Department of Public Health pursuant to California Health and Safety Code Section 103885; Centers for Disease Control and Prevention's (CDC) National Program of Cancer Registries, under cooperative agreement 5NU58DP006344; the National Cancer Institute's Surveillance, Epidemiology and End Results Program under contract HHSN261201800032I awarded to the University of California, San Francisco, contract HHSN261201800015I awarded to the University of Southern California, and contract HHSN261201800009I awarded to the Public Health Institute.

The publication costs of this article were defrayed in part by the payment of publication fees. Therefore, and solely to indicate this fact, this article is hereby marked “advertisement” in accordance with 18 USC section 1734.

Note: Supplementary data for this article are available at Cancer Epidemiology, Biomarkers & Prevention Online (http://cebp.aacrjournals.org/).

1.
Curry
SJ
,
Krist
AH
,
Owens
DK
,
Barry
MJ
,
Caughey
AB
,
Davidson
KW
, et al
.
Screening for cervical cancer: US preventive services task force recommendation statement
.
JAMA
2018
;
320
:
674
86
.
2.
Yang
DX
,
Soulos
PR
,
Davis
B
,
Gross
CP
,
Yu
JB
.
Impact of widespread cervical cancer screening: number of cancers prevented and changes in race-specific incidence
.
Am J Clin Oncol
2018
;
41
:
289
94
.
3.
Siegel
RL
,
Miller
KD
,
Jemal
A
.
Cancer statistics, 2020
.
CA Cancer J Clin
2020
;
70
:
7
30
.
4.
Vaccarella
S
,
Lortet-Tieulent
J
,
Plummer
M
,
Franceschi
S
,
Bray
F
.
Worldwide trends in cervical cancer incidence: impact of screening against changes in disease risk factors
.
Eur J Cancer
2013
;
49
:
3262
73
.
5.
Howlader
N
,
Noone
AM
,
Krapcho
M
,
Miller
D
,
Brest
A
,
Yu
M
, et al
.
SEER Cancer Statistics Review, 1975–2017
,
National Cancer Institute
.
Available from
: https://seer.cancer.gov/csr/1975_2017/.
6.
U.S. Cancer Statistics Working Group
.
2022 U.S. Cancer Statistics Data Visualizations Tool, based on 2021 submission data (1999–2019)
.
U.S. Department of Health and Human Services, Centers for Disease control and Prevention and national Cancer Institute.
Available from: www.cdc.gov/cancer/dataviz.
Accessed 2022 September 4
.
7.
Diver
EJ
,
Hinchcliff
EM
,
Gockley
AA
,
Melamed
A
,
Contrino
L
,
Feldman
S
, et al
.
Assessment of treatment factors and clinical outcomes in cervical cancer in older women compared to women under 65 years old
.
J Geriatr Oncol
2018
;
9
:
516
9
.
8.
Saghari
S
,
Ghamsary
M
,
Marie-Mitchell
A
,
Oda
K
,
Morgan
JW
.
Sociodemographic predictors of delayed- versus early-stage cervical cancer in California
.
Ann Epidemiol
2015
;
25
:
250
5
.
9.
Feldman
S
,
Cook
E
,
Davis
M
,
Gershman
ST
,
Hanchate
A
,
Haas
JS
, et al
.
Cervical cancer incidence among elderly women in massachusetts compared with younger women
.
J Low Genit Tract Dis
2018
;
22
:
314
7
.
10.
Quick
AM
,
Krok-Schoen
JL
,
Stephens
JA
,
Fisher
JL
.
Cervical cancer among older women: analyses of surveillance, epidemiology and end results program data
.
Cancer Control
2020
;
27
:
1073274820979590
.
11.
Fontham
ETH
,
Wolf
AMD
,
Church
TR
,
Etzioni
R
,
Flowers
CR
,
Herzig
A
, et al
.
Cervical cancer screening for individuals at average risk: 2020 guideline update from the American Cancer Society
.
CA Cancer J Clin
2020
;
70
:
321
46
.
12.
Updated Cervical Cancer Screening Guidelines
.
2021 Practice Advisory. American College of Obstetricians and Gynecologists
.
Available from:
https://www.acog.org/clinical/clinical-guidance/practice-advisory/articles/2021/04/updated-cervical-cancer-screening-guidelines.
Accessed 2022 August 30
.
13.
Sabatino
SA
,
Thompson
TD
,
White
MC
,
Shapiro
JA
,
Clarke
TC
,
Croswell
JM
, et al
.
Cancer screening test use-U.S., 2019
.
Am J Prev Med
2022
;
63
:
431
9
.
14.
Moss
JL
,
Roy
S
,
Shen
C
,
Cooper
JD
,
Lennon
RP
,
Lengerich
EJ
, et al
.
Geographic variation in overscreening for colorectal, cervical, and breast cancer among older adults
.
JAMA Netw Open
2020
;
3
:
e2011645
.
15.
White
MC
,
Shoemaker
ML
,
Benard
VB
.
Cervical cancer screening and incidence by age: unmet needs near and after the stopping age for screening
.
Am J Prev Med
2017
;
53
:
392
5
.
16.
Mills
JM
,
Morgan
JR
,
Dhaliwal
A
,
Perkins
RB
.
Eligibility for cervical cancer screening exit: comparison of a national and safety net cohort
.
Gynecol Oncol
2021
;
162
:
308
14
.
17.
NCI Surveillance Epidemiology and End Results Program
.
2008 Site Recode ICD-O-3/WHO 2008 Definition
.
Available from:
https://seer.cancer.gov/siterecode/icdo3_dwhoheme/.
Accessed 2022 August 31
.
18.
Amin
MB
,
Edge
S
,
Greene
F
,
Byrd
DR
,
Brookland
RK
,
Washington
MK
et al
AJCC Cancer Staging Manual (8th edition)
.
Springer International Publishing
:
American Joint Commission on Cancer
;
2017
.
19.
Bhatla
N
,
Berek
JS
,
Cuello Fredes
M
,
Denny
LA
,
Grenman
S
,
Karunaratne
K
, et al
.
Revised FIGO staging for carcinoma of the cervix uteri
.
Int J Gynaecol Obstet
2019
;
145
:
129
35
.
20.
Lichtensztajn
DY
,
Giddings
BM
,
Morris
CR
,
Parikh-Patel
A
,
Kizer
KW
.
Comorbidity index in central cancer registries: the value of hospital discharge data
.
Clinical epidemiology
2017
;
9
:
601
9
.
21.
Yang
JSC
,
Harrati
A
,
Clarke
C
,
Keegan
THM
,
Gomez
SL
.
Developing an area-based socioeconomic measure from American Community Survey data
.
Cancer Prevention Institute of California
.
Available from
: https://cancerregistry.ucsf.edu/sites/g/files/tkssra1781/f/wysiwyg/Yang%20et%20al.%202014_CPIC_ACS_SES_Index_Documentation_3-10-2014.pdf.
22.
California Health and Human Services Agency
.
2022 Medical Service Study Area (MSSA) Detail. California Health and Human Services Open Data Portal.
Available from: https://data.chhs.ca.gov/dataset?q=MSSA.
Accessed 2022 March 12
.
23.
Surveillance Research Program
.
National Cancer Institute SEER*Stat software
.
Available from:
https://seer.cancer.gov/seerstat/.
Accessed 2022 February 3
.
24.
Lambert
PC
,
Dickman
PW
,
Rutherford
MJ
.
Comparison of different approaches to estimating age standardized net survival
.
BMC Med Res Methodol
2015
;
15
:
64
.
25.
O'Laughlin
DJ
,
Strelow
B
,
Fellows
N
,
Kelsey
E
,
Peters
S
,
Stevens
J
, et al
.
Addressing anxiety and fear during the female pelvic examination
.
J Prim Care Community Health
2021
;
12
:
2150132721992195
.
26.
Freeman
M
,
Waller
J
,
Sasieni
P
,
Lim
AW
,
Marlow
LA
.
Acceptability of non-speculum clinician sampling for cervical screening in older women: a qualitative study
.
J Med Screen
2018
;
25
:
205
10
.
27.
Harper
DM
.
Cervical cancer elimination is dependent on women's self-tests for primary human papillomavirus testing triaged by methylation status
.
J Clin Oncol
2022
;
40
:
3003
5
.
28.
Perkins
RB
,
Adcock
R
,
Benard
V
,
Cuzick
J
,
Waxman
A
,
Howe
J
, et al
.
Clinical follow-up practices after cervical cancer screening by co-testing: a population-based study of adherence to U.S. guideline recommendations
.
Prev Med
2021
;
153
:
106770
.
29.
Terret
C
,
Castel-Kremer
E
,
Albrand
G
,
Droz
JP
.
Effects of comorbidity on screening and early diagnosis of cancer in elderly people
.
Lancet Oncol
2009
;
10
:
80
7
.
30.
Sarfati
D
,
Koczwara
B
,
Jackson
C
.
The impact of comorbidity on cancer and its treatment
.
CA Cancer J Clin
2016
;
66
:
337
50
.
31.
Eggemann
H
,
Ignatov
T
,
Geyken
CH
,
Seitz
S
,
Ignatov
A
.
Management of elderly women with cervical cancer
.
J Cancer Res Clin Oncol
2018
;
144
:
961
7
.
32.
Desai
VB
,
Wright
JD
,
Lin
H
,
Gross
CP
,
Sallah
YH
,
Schwartz
PE
, et al
.
Laparoscopic hysterectomy route, resource use, and outcomes: change after power morcellation warning
.
Obstet Gynecol
2019
;
134
:
227
38
.
33.
Mattingly
M
,
Juran
R
,
Su
I
,
Ebinger
J
,
Daggy
J
., Tucker Edmonds B.
Patient knowledge of hysterectomy and pap screening after minimally invasive hysterectomy
.
Patient Educ Couns
2017
;
100
:
121
5
.
34.
McHale
MP
,
Smith
AJB
,
Fader
AN
,
Wethington
SL
.
Outcomes of women undergoing excision of the retained cervix after supracervical hysterectomy
.
Obstet Gynecol
2021
;
137
:
831
6
.
35.
Yost
S
,
Hoekstra
A
.
Cervical cancer in women over 65: an analysis of screening
.
Gynecol Oncol Rep
2018
;
25
:
48
51
.
36.
Gnade
CM
,
Hill
EK
,
Botkin
HE
,
Hefel
AR
,
Hansen
HE
,
Sheets
KA
, et al
.
Is the age of cervical cancer diagnosis changing over time?
J Gynecol Obstet Hum Reprod
2021
;
50
:
102040
.
37.
Gustafson
LW
,
Petersen
LK
,
Bor
P
,
Andersen
B
,
Hammer
A
.
Cervical cancer prevention among older women—challenges in screening, diagnostic workup and treatment
.
Acta Obstet Gynecol Scand
2021
;
100
:
1364
8
.
38.
Pak
SC
,
Martens
M
,
Bekkers
R
,
Crandon
AJ
,
Land
R
,
Nicklin
JL
, et al
.
Pap smear screening history of women with squamous cell carcinoma and adenocarcinoma of the cervix. The Australian and New Zealand journal of obstetrics & gynaecology
2007
;
47
:
504
7
.
39.
Islami
F
,
Fedewa
SA
,
Jemal
A
.
Trends in cervical cancer incidence rates by age, race/ethnicity, histological subtype, and stage at diagnosis in the United States
.
Prev Med
2019
;
123
:
316
23
.
40.
Melnikow
J
,
Henderson
JT
,
Burda
BU
,
Senger
CA
,
Durbin
S
,
Weyrich
MS
.
Screening for cervical cancer with high-risk human papillomavirus testing: updated evidence report and systematic review for the US preventive services task force
.
JAMA
2018
;
320
:
687
705
.
41.
Ogilvie
GS
,
van Niekerk
D
,
Krajden
M
,
Smith
LW
,
Cook
D
,
Gondara
L
, et al
.
Effect of screening with primary cervical HPV testing vs. cytology testing on high-grade cervical intraepithelial neoplasia at 48 months: the HPV FOCAL randomized clinical trial
.
JAMA
2018
;
320
:
43
52
.
42.
MacLaughlin
KL
,
Jacobson
RM
,
Radecki Breitkopf
C
,
Wilson
PM
,
Jacobson
DJ
,
Fan
C
, et al
.
Trends over time in pap and pap-HPV cotesting for cervical cancer screening
.
J Womens Health
2019
;
28
:
244
9
.
43.
Saraiya
M
,
Kwan
A
,
Cooper
CP
.
Primary HPV testing: U.S. women's awareness and acceptance of an emerging screening modality
.
Prev Med
2018
;
108
:
111
4
.
44.
Hwang
SH
,
Shin
HY
,
Lee
DO
,
Sung
NY
,
Lee
B
,
Lee
DH
, et al
.
A prospective pilot evaluation of vaginal and urine self-sampling for the Roche cobas 4800 HPV test for cervical cancer screening
.
Sci Rep
2018
;
8
:
9015
.
45.
Maver
PJ
,
Poljak
M
.
Primary HPV-based cervical cancer screening in Europe: implementation status, challenges, and future plans
.
Clin Microbiol Infect
2020
;
26
:
579
83
.
46.
Polman
NJ
,
Snijders
PJF
,
Kenter
GG
,
Berkhof
J
,
Meijer
C
.
HPV-based cervical screening: rationale, expectations and future perspectives of the new Dutch screening programme
.
Prev Med
2019
;
119
:
108
17
.
47.
Serrano
B
,
Ibáñez
R
,
Robles
C
,
Peremiquel-Trillas
P
,
de Sanjosé
S
,
Bruni
L
.
Worldwide use of HPV self-sampling for cervical cancer screening
.
Prev Med
2022
;
154
:
106900
.
48.
Inturrisi
F
,
Aitken
CA
,
Melchers
WJG
,
van den Brule
AJC
,
Molijn
A
,
Hinrichs
JWJ
, et al
.
Clinical performance of high-risk HPV testing on self-samples versus clinician samples in routine primary HPV screening in the Netherlands: an observational study
.
Lancet Reg Health Eur
2021
;
11
:
100235
.
49.
Benard
VB
,
Watson
M
,
Saraiya
M
,
Harewood
R
,
Townsend
JS
,
Stroup
AM
, et al
.
Cervical cancer survival in the United States by race and stage (2001–2009): findings from the CONCORD-2 study
.
Cancer
2017
;
123
:
5119
37
.
50.
Eggleston
KS
,
Coker
AL
,
Williams
M
,
Tortolero-Luna
G
,
Martin
JB
,
Tortolero
SR
.
Cervical cancer survival by socioeconomic status, race/ethnicity, and place of residence in Texas, 1995–2001
.
J Womens Health
2006
;
15
:
941
51
.
51.
Coker
AL
,
Desimone
CP
,
Eggleston
KS
,
White
AL
,
Williams
M
.
Ethnic disparities in cervical cancer survival among Texas women
.
J Womens Health
2009
;
18
:
1577
83
.
52.
Saraiya
M
,
Unger
ER
,
Thompson
TD
,
Lynch
CF
,
Hernandez
BY
,
Lyu
CW
, et al
.
US assessment of HPV types in cancers: implications for current and 9-valent HPV vaccines
.
J Natl Cancer Inst
2015
;
107
:
djv086
.
53.
Gravitt
PE
,
Winer
RL
.
Natural history of HPV infection across the lifespan: role of viral latency
.
Viruses
2017
;
9
:
267
.
54.
Buja
A
,
Lago
L
,
Lago
S
,
Vinelli
A
,
Zanardo
C
,
Baldo
V
.
Marital status and stage of cancer at diagnosis: a systematic review
.
Eur J Cancer Care
2018
;
27
:
e12755
.