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. Author manuscript; available in PMC: 2020 Aug 1.
Published in final edited form as: Ann Epidemiol. 2019 Jun 21;36:40–47. doi: 10.1016/j.annepidem.2019.06.002

Prevalence and determinants of cervical cancer screening with a combination of cytology and Human Papillomavirus testing

Joël Fokom Domgue 1,2,3, Sonia A Cunningham 1, Robert K Yu 4, Sanjay Shete 1,2,4
PMCID: PMC6732232  NIHMSID: NIHMS1532501  PMID: 31320153

Abstract

Purpose

In the US, recommended options for cervical cancer screening in women aged ≥ 30 years include cytology alone, and a combination of cytology and Human Papillomavirus (HPV) testing (co-testing). While there is a body of evidence suggesting that co-testing may be the preferred screening option in this group of women, little is known about the characteristics of women who screen for cervical cancer with co-testing.

Methods

A multistage area probability design-based survey was administered to a representative sample of Texas residents. Of the 1,348 female respondents, 572 women aged 30 years or above were included in this analysis. Population-weighted survey logistic regression was used to identify determinants of cervical screening with co-testing versus screening with cytology alone.

Results

Women vaccinated against HPV (aOR: 4.48, 95% CI: 1.25 – 15.97) or Hepatitis B virus (HBV) (aOR: 2.48 (1.52 – 4.02)), those with a personal cancer history (aOR: 2.96 (1.29 – 6.77)), and hormonal contraception users (aOR: 2.03 (1.03 – 3.97), were more likely to be screened with co-testing than with cytology alone. Moreover, the likelihood of being screened with co-testing decreased with increasing age and decreasing annual household income.

Conclusions

Benefits and indications of co-testing should be better explained to women and healthcare providers.

Keywords: Cervical cancer screening, cytology, HPV testing, co-testing

Introduction

The widespread implementation of cervical cancer screening programs over the past decades has resulted in as significant reduction of cervical cancer burden in the United States (US). Despite this progress, there still persists geographic, ethnic, and racial disparities in cervical cancer morbidity and mortality.1 Of particular concern are the declining trends in cervical cancer screening uptake in the US,2 and the projected failure to meet the Healthy People 2020 national goal of 93% screening rate. In 2018, it was estimated that 13,240 women in the US would be diagnosed with cervical cancer and 4,170 would die from their disease.3 In Texas, the second most populous State in the US, incidence (9.2 cases per 100,000 women) and mortality (2.8 deaths per 100,000 women) of cervical cancer are roughly 20% higher than national rates.4 Furthermore, the state-wide mortality from cervical cancer is substantially higher among Blacks (4.0 per 100.000) and Hispanics (3.3 per 100.000) than among Whites (2.9 per 100.000).4 Prophylactic vaccination against Human Papillomavirus (HPV) may further reduce the incidence of cervical cancer, but its indications are still restricted to certain age groups, and even among the eligible US population, HPV vaccination coverage is sub-optimal.5 In Texas, only 39.7% of adolescents aged 13 to 17 are up to date with HPV vaccination, leaving this state ranked as 47th nation-wide for HPV vaccination.5 Besides, HPV vaccination does not substitute for screening that will continue to play an important role in the prevention of cervical cancer.6

While cytology (Pap test) has traditionally been used as the main method for cervical cancer screening in the US, the development of molecular assays for HPV detection in cervical cells has been a major breakthrough that can enhance the effectiveness of existing screening programs.6 Since 2012, recommended options for cervical cancer screening in women aged ≥ 30 years include a combination of cytology and HPV testing (co-testing) every 5 years, or the standard cervical cytology alone every 3 years.7–9 Importantly, the consensus guidelines jointly issued by the American Cancer Society (ACS), the American Society of Colposcopy and Cervical Pathology (ASCCP), and the American Society for Clinical Pathology (ASCP), have endorsed co-testing as the preferred approach in this age range.7 This recommendation is further supported by a recent HPV focal trial, which concluded that co-testing produces better results than cytology alone.10 Despite these guidelines, a substantial proportion of women aged 30 years or older are still screened with cytology alone. In a study examining changes in cervical cancer screening practices, only about one third of women up to date on cervical screening in the US reported having undergone co-testing during their most recent cervical screening.2

Given the added value of co-testing, further efforts to understand the determinants of screening with co-testing are warranted to improve the effectiveness of cervical screening programs. Previous studies have examined the predictors of cervical cancer screening in the US.11,12 Since most of these reports have focused on cytology, little is known about the socio-demographic, health-related, and behavioral determinants of cervical cancer screening with co-testing. Using a 2018 population-based state-wide survey, the present study aimed to determine the prevalence and predictors of cervical cancer screening with co-testing among women 30 years or older in Texas.

Methods

Study population and recruitment procedure

The study population was selected from a representative sample of the Texas population.13,14 A non-probability sample of 2050 respondents to the Texas health screening survey were collected using strata set to mirror Texas demographics for sex, ethnicity, race, and income. However, oversampling of non-Hispanic blacks (NHBs) was conducted to ensure more accurate comparisons for this minority group. The non-Hispanic white (NHW) category consisted of those selecting white as the sole race and the NHB category of those selecting black/African American (either alone or in addition to other races). The recruitment target included 60% urban and 40% rural respondents, categorized by matching ZIP code to county designations.15,16 This study focused on the 894 female respondents aged 30 years or older.

Survey design and implementation

The Texas health screening survey is a questionnaire that we developed to evaluate socio-demographic and cancer risk factors, beliefs about cancer, and cancer screening behaviors in the Texas population.13 Most of the questions included in this survey were derived from the National Health Interview Survey (NHIS), the Health Information National Trends Survey (HINTS), and the Behavioral Risk Factor Surveillance System Questionnaire. The instrument was prepared in both English and Mexican Spanish using the services of Masterword Services, Inc. (Houston, Texas), and administered through the Qualtrics online survey platform (Qualtrics International Inc., Provo, Utah and Seattle, Washington). The study population was comprised of a non-probability sample restricted to opt-in panelists living in Texas. Thus, strata were set beforehand for sex, ethnicity, race, income and rurality, and the sample size calculated, overall and per strata. The goal was to meet the sampling targets while ascertaining data from these strata, in order to obtain a representative sample of the Texas adult population that could allow accurate estimation of health outcome measures. As people were invited to participate and screened for eligibility, as they consented to fill out the questionnaire and were surveyed, submitted questionnaires were regularly assessed for completeness and assigned to relevant strata. When the sampling targets were met in a given strata, the subsequent completion of the survey by participants falling into that strata was automatically disabled. In all, 5658 responses (including screeners and over quotas) were attempted including 1600 dropouts. A final total of 2050 complete responses were received. In this survey, we collected a wide range of information including health education and behavior, health information retrieval, healthcare access and coverage, mental and physical health, cancer screening, cancer history and area of residence.17–19 The data collection was conducted between February 5 and March 5, 2018. The study protocol (PA16–0724) was approved by MD Anderson’s Institutional Review Board.

Outcome Measures

The primary outcome for this study was self-reported cervical cancer screening and its measure was derived from the cancer screening section of the NHIS, which includes questions regarding Pap and HPV tests to adult women. Thus, 2 questions were used to define the outcome variable: 1) A Pap test is a test for cancer of the cervix. Have you ever had a Pap test? (Pap_Test) with a binary Yes/No response; and 2) An HPV test is sometimes given with the Pap test for cervical cancer screening. Have you ever had an HPV test? (HPV_Test). The response to the latter could be either “Yes”, “No” or “Don’t know/Not sure”. Our outcome variable (self-reported cervical cancer screening) was classified into three categories: co-testing (when the response to both questions was Yes); Pap testing (cytology) alone (when the response to the first question was Yes and the response to the second question was No); and No screening (when the response to both questions was No). A total of 316 eligible respondents (women aged 30 or older) who responded “Don’t know/Not sure” to the second question (HPV_Test), as well as the 6 eligible respondents who had a positive response to the second question (HPV_Test) and a negative response to the first question (Pap_Test), were excluded from the analyzes.

Predictors

Predictor variables were selected from measures collected in the Texas health screening survey. The main explanatory variables for this analysis were cancer risk perceptions and beliefs. Perceived risk of cancer was measured with the following question: Compared to other people your age, how likely are you to get cancer in your lifetime? Six measures were used to assess cancer beliefs: 1) It seems like everything causes cancer, 2) There’s not much you can do to lower your chances of getting cancer, 3) Cancer is most often caused by a person’s behavior or lifestyle, 4) I’d rather not know my chance of getting cancer, 5) When I think about cancer, I automatically think about death, and 6) There are so many different recommendations about preventing cancer, it’s hard to know which ones to follow. The responses to these questions were classified into two categories: “Agree/Disagree”.

Other predictors were analyzed based on their potential influence on cervical cancer screening, including socio-demographic factors (age, ethnicity/race, nativity, educational attainment, marital status, occupation status, urban versus rural residence, home ownership and household income). Behavioral, mental and health-related variables included smoking status, health coverage, depression, vaccination against Hepatitis B virus (HBV), vaccination against HPV, hormonal contraception use, body mass index (BMI), personal or family history of any cancer, and health literacy.

Statistical Analysis

Data were weighted by ICF International, Inc, Fairfax, Virginia using a three-dimensional raking approach with iterative post-stratification based on sex; age and race/ethnicity.20 We used means and standard deviation (continuous variables), weighted percentages and weighted 95% confidence interval (categorical variables), to describe and compare potential predictors by screening status. Multivariable weighted survey logistic regressions using PROC SURVEYLOGISTIC (SAS for Windows, version 9.4), were employed to examine factors associated with co-testing use (versus screening with cytology alone). For this analysis, the outcome variable as well as the predictor variables were pre-specified. Women who reported having never been screened for cervical cancer were excluded from the logistic regression, and the study outcome was categorized as a binary variable: co-testing vs Pap testing alone (the latter being the reference category). All variables considered to be potential predictors of co-testing were included in the final model.

Considering that the variables “income” and “education” could potentially modify the effect of women’s cancer beliefs on the choice of either screening strategy, we conducted further analysis. We first removed these two variables from the full logistic regression model. Further, we assessed the interaction of income and education with the main explanatory variables. These interactions were tested: i) separately in two different models (addition of income×cancer beliefs variables in one model, and education×cancer beliefs variables in the other model), then: ii) combined in a same model (addition of both income×cancer beliefs variables, and education×cancer beliefs variables in the same model).

Results

Characteristics of the study population

Of the 572 women aged 30 years or older included in this analysis, 273 (weighted percentage: 44.8%, weighted 95% confidence interval: 40.4 – 49.1%) reported having been screened with cotesting, 242 (45.5% (41.1 – 49.9%)) with cytology alone, while 57 (9.7% (7.2 – 12.3%)) reported having never been screened for cervical cancer.

Table 1 describes the sociodemographic, health-related, mental, and behavioral characteristics of the study sample, stratified by screening status. Compared to women screened with cytology alone, those screened with co-testing were: younger (mean age (95% CI): 44.8 years (43.4 – 46.2) versus 53.2 years (51.5 – 54.9)) and; more likely to be Hispanics (weighted percentage (weighted 95% CI): 33.9% (27.9 – 39.8) versus 24.0% (18.5 – 29.6)). They were also more likely to: use hormonal contraception (83.9% (79.3 – 88.5) versus 75.4% (69.7 – 81.1)); be vaccinated against HBV (56.7% (50.3 – 63.1) versus 28.9% (22.9 –- 35.0)); and HPV (13.0% (9.1 – 17.0) versus 1.5% (0.0 – 3.1)); and to have a personal cancer history (12.1% (7.7 – 16.5) versus 7.4% (3.7 – 11.2) compared to women screened with cytology alone. With regard to cancer beliefs, women screened with co-testing were less likely to agree with the statement “There’s not much you can do to lower your chances of getting cancer” (61.5% (55.1 – 67.8) versus 66.4% (60.0 – 72.8)), and less likely to agree with the statement “There are so many different recommendations about preventing cancer, it’s hard to know which ones to follow” (76.1% (70.6 – 81.6) versus 80.3% (74.9 – 85.6)) than women who screened with cytology alone.

Table 1:

Characteristics of the study Population, by cervical screening status

VARIABLES Total Women ever screened Women never screened
Co-testing (Cytology and HPV test) Pap testing (cytology alone)
N %, Weighted (95% CI) N %, Weighted (95% CI) N %, Weighted (95% CI) N %, Weighted (95% CI)
Respondents 572 100.0 273 44.8 (40.4 – 49.1) 242 45.5 (41.1 – 49.9) 57 9.7 (7.2 – 12.3)
1. Socio-demographic Factors
Age (mean)a 48.4 (47.3 – 49.5) 44.8 (43.4 – 46.2) 53.2 (51.5 – 54.9) 42.6 (39.5 – 45.6)
Age groups
 30–44 283 40.7 (36.5 – 44.9) 164 50.8 (44.3 – 57.3) 83 26.9 (21.4 – 32.5) 36 59.2 (45.2 – 73.1)
 45–59 194 40.6 (36.1 – 45.0) 84 39.3 (32.8 – 45.8) 92 43.1 (36.3 – 49.9) 18 34.4 (20.8 – 48.0)
 ≥60 95 18.7 (15.1 – 22.3) 25 9.9 (5.9 – 13.9) 67 30.0 (23.6 – 36.3) 3 6.4 (0.0 – 14.0)
Ethnicity / Race
 Black, non-Hispanic 156 13.0 (10.9 – 15.2) 80 14.3 (11.0 – 17.5) 63 12.1 (8.95 – 15.1) 13 11.9 (5.3 – 18.5)
 Hispanic 167 29.0 (25.1 – 32.9) 89 33.9 (27.9 – 39.8) 60 24.0 (18.5 – 29.6) 18 30.1 (17.9 – 42.3)
 Others 44 7.5 (5.3 – 9.7) 23 8.6 (5.2 – 12.0) 17 6.7 (3.6 – 9.9) 4 5.9 (0.2 – 11.6)
 White, non-Hispanic 205 50.5 (46.1 – 54.9) 81 43.3 (36.7 – 49.9) 102 57.2 (50.7 – 63.7) 22 52.1 (38.4 – 65.8)
Born in USA
 No 51 8.7 (6.3 – 11.1) 25 9.4 (5.7 – 13.0) 19 7.6 (4.1 – 11.1) 7 10.6 (3.0 – 18.1)
 Yes 521 91.3 (88.9 – 93.7) 248 90.6 (87.0 – 94.3) 223 92.4 (88.9 – 95.9) 50 89.4 (81.9 – 97.0)
Education
 No greater than 12 years or completed high school 128 24.0 (20.2 – 27.8) 47 19.5 (14.2 – 24.7) 62 26.0 (20.0 – 31.9) 19 35.6 (22.3 – 49.1)
 Post high school training or some college 208 35.4 (31.2 – 39.7) 108 39.3 (33.0 – 45.6) 83 33.7 (27.3 – 40.1) 17 25.7 (14.2 – 37.1)
 College/Postgraduate 236 40.6 (36.2 – 44.9) 118 41.2 (34.9 – 47.5) 97 40.3 (33.7 – 47.0) 21 38.7 (25.1 – 52.3)
Marital Status
 Single/Widowed 149 21.9 (18.4 – 25.5) 66 18.8 (14.1 – 23.4) 59 21.4 (15.9 – 26.8) 24 39.4 (25.9 – 52.9)
 Living as Married/ Married 123 21.6 (18.0 – 25.3) 59 21.3 (16.0 – 26.6) 58 23.7 (18.0 – 29.5) 6 13.2 (3.1 – 23.2)
 Divorced/Separated 300 56.5 (52.1 – 60.8) 148 59.9 (53.8 – 66.2) 125 54.9 (48.1 – 61.6) 27 47.4 (33.6 – 61.2)
Occupation
 Employed 304 50.8 (46.4 – 55.2) 156 52.3 (45.8 – 58.7) 117 48.6 (41.8 – 55.4) 31 54.5 (40.7 – 68.3)
 Homemaker/Unemployed/Disabled 176 32.2 (28.1 – 36.4) 84 34.4 (28.2 – 40.6) 69 28.2 (22.1 – 34.3) 23 40.9 (27.2 – 54.5)
 Student/Retired/Other 92 17.0 (13.6 – 20.4) 33 13.3 (8.8 – 17.9) 56 23.2 (17.4 – 29.0) 3 4.7 (0.0 – 10.1)
Income
 ≤ $19,999 109 17.6 (14.3 – 21.0) 44 16.0 (11.3 – 20.8) 46 16.0 (11.2 – 20.8) 19 32.4 (19.5 – 45.4)
 $20,000 – $49,999 197 33.8 (29.6 – 38.0) 87 28.9 (23.2 – 34.6) 94 39.7 (33.1 – 46.4) 16 28.6 (15.9 – 41.2)
 $50,000 – $74,999 123 22.6 (18.8 – 26.3) 59 22.9 (17.4 – 28.4) 51 22.3 (16.6 – 27.9) 13 22.8 (11.4 – 34.1)
 ≥ $75,000 143 26.0 (22.1 – 29.9) 83 32.2 (26.1 – 38.2) 51 22.0 (16.3 – 27.6) 9 16.2 (6.0 – 26.5)
Residence
 Rural 236 50.9 (46.4 – 55.3) 103 47.9 (41.4 – 54.3) 112 54.8 (48.1 – 61.4) 21 46.4 (32.5 – 60.4)
 Urban 336 49.1 (44.7 – 53.6) 170 52.1 (45.7 – 58.6) 130 45.2 (38.6 – 51.9) 36 53.6 (39.6 – 67.5)
Home Ownership (N=571)
 Own 309 58.7 (54.4 – 63.0) 133 54.3 (48.0 – 60.7) 150 65.0 (58.6 – 71.4) 26 49.0 (35.1 – 63.1)
 Rent/ Occupied without paying monetary rent 262 41.3 (37.0 – 45.6) 140 45.7 (39.3 – 52.0) 92 35.0 (28.6 – 41.4) 30 51.0 (37.0 – 65.0)
2. Health Behavior, Access and Coverage
Hormonal Contraception
 No 148 24.5 (20.7 – 28.2) 47 16.1 (11.5 – 20.7) 65 24.6 (18.9 – 30.3) 36 62.4 (49.0 – 75.9)
 Yes 424 75.5 (71.8 – 79.3) 226 83.9 (79.3 – 88.5) 177 75.4 (69.7 – 81.1) 21 37.6 (24.1 – 51.0)
Smoking
 Current smokers 108 19.1 (15.6 – 22.6) 58 22.0 (16.7 – 27.4) 41 16.3 (11.3 – 21.3) 9 18.6 (7.5 – 29.7)
 Former smokers 100 20.4 (16.7 – 24.2) 44 20.1 (14.6 – 25.6) 51 23.4 (17.5 – 29.3) 5 8.3 (0.9 – 15.6)
 Never smokers 364 60.5 (56.1 – 64.9) 171 57.9 (51.4 – 64.3) 150 60.3 (53.6 – 67.0) 43 73.1 (60.7 – 85.5)
Health Care Coverage (N=571)
 No 136 22.3 (18.6 – 25.9) 60 21.4 (16.1 – 26.6) 52 18.6 (13.5 – 23.7) 24 43.5 (29.8 – 57.3)
 Yes 435 77.7 (74.1 – 81.4) 212 78.6 (73.4 – 83.9) 190 81.4 (76.3 – 86.5) 33 56.5 (42.7 – 70.2)
Last Routine Checkup
 Never/unknown 23 3.9 (2.3 – 5.6) 10 3.8 (1.4 – 6.2) 7 2.8 (0.6 – 5.1) 6 9.7 (2.0 – 17.8)
 Within the past year 398 70.9 (66.9 – 74.9) 205 76.2 (70.9 – 81.6) 169 71.9 (65.9 – 78.0) 24 42.0 (28.3 – 55.7)
 One year ago or more 151 25.2 (21.4 – 28.9) 58 20.0 (15.0 – 25.0) 66 25.3 (19.4 – 31.1) 27 48.2 (34.3 – 62.0)
Hepatitis B Virus vaccination
 No 334 59.8 (55.4 – 64.1) 117 43.3 (36.9 – 49.7) 170 71.1 (65.0 – 77.1) 47 82.5 (72.1 – 93.0)
 Yes 238 40.2 (35.9 – 44.6) 156 56.7 (50.3 – 63.1) 72 28.9 (22.9 – 35.0) 10 17.5 (7.0 – 27.9)
Human Papillomavirus Vaccination
 No 485 86.5 (83.7 – 89.4) 209 78.8 (73.8 – 83.8) 229 95.2 (92.4 – 97.9) 47 81.9 (71.2 – 92.6)
 Do not know 37 6.2 (4.1 – 8.2) 22 8.2 (4.7 – 11.8) 9 3.3 (1.0 – 5.6) 6 10.1 (2.0 – 18.1)
 Yes 50 7.3 (5.2 – 9.4) 42 13.0 (9.1 – 17.0) 4 1.5 (0.0 – 3.1) 4 8.0 (0.2 – 15.9)
How difficulty to understand information that doctors, nurses, and other professional tell you?
 Easy 521 91.0 (88.5 – 93.5) 252 92.2 (88.8 – 95.6) 222 92.1 (88.6 – 95.7) 47 79.6 (68.0 – 91.2)
 Difficult 51 9.0 (6.5 – 11.5) 21 7.8 (4.4 – 11.2) 20 7.9 (4.4 – 11.4) 10 20.4 (8.8 – 32.0)
3. Mental and Physical Health
Depression
 Never 159 25.6 (21.8 – 29.3) 73 25.0 (19.5 – 30.5) 64 23.9 (18.2 – 29.6) 22 35.8 (22.7 – 48.8)
 A few times a year 195 32.9 (28.8 – 37.1) 98 34.1 (28.0 – 40.1) 83 33.4 (27.0 – 39.7) 14 25.8 (13.5 – 38.0)
 Daily, weekly or monthly 218 41.5 (37.1 – 45.9) 102 41.0 (34.6 – 47.3) 95 42.8 (36.0 – 49.5) 21 38.5 (24.9 – 52.0)
BMI (N=568)
 Underweight to normal (<25) 164 29.9 (25.8 – 34.0) 72 27.2 (21.4 – 33.1) 76 32.1 (25.8 – 38.5) 16 31.9 (18.3 – 45.5)
 Overweight (25 to <30) 149 24.8 (21.0 – 28.6) 79 27.9 (22.1 – 33.6) 54 21.4 (15.8 – 27.0) 16 26.3 (14.5 – 38.1)
 Obesity ( ≥ 30) 255 45.3 (40.9 – 49.7) 121 44.9 (38.5 – 51.3) 112 46.5 (39.7 – 53.2) 22 41.8 (27.7 – 55.9)
Personal history of any cancer
 No 526 90.7 (88.0 – 93.4) 246 87.9 (83.5 – 92.3) 226 92.6 (88.8 – 96.3) 54 94.7 (88.4 – 100.0)
 Yes 46 9.3 (6.6 – 12.0) 27 12.1 (7.7 – 16.5) 16 7.4 (3.7 – 11.2) 3 5.3 (0.0 – 11.6)
Family History of any cancer
 No 150 23.9 (20.2 – 27.6) 68 22.4 (17.1 – 27.6) 54 20.3 (15.0 – 25.7) 28 47.3 (33.6 – 61.1)
 Not sure 41 8.2 (5.7 – 10.7) 19 8.2 (4.6 – 11.9) 16 7.3 (3.7 – 10.9) 6 12.4 (2.8 – 21.9)
 Yes 381 67.9 (63.8 – 72.0) 186 69.4 (63.5 – 75.3) 172 72.4 (66.4 – 78.4) 23 40.3 (26.6 – 54.0)
4. Perceived Risk and Beliefs about Cancer
Compared to other people your age, how likely are you to get cancer in your lifetime?
 Likely 152 27.5 (23.5 – 31.4) 78 29.9 (24.0 – 35.8) 65 27.9 (21.8 – 34.0) 9 14.4 (5.3 – 23.4)
 Neutral 283 50.5 (46.1 – 54.9) 135 51.0 (44.6 – 57.4) 120 50.9 (44.1 – 57.7) 28 46.3 (32.6 – 60.1)
 Unlikely 137 22.0 (18.4 – 25.7) 60 19.1 (14.2 – 24.1) 57 21.2 (15.8 – 26.6) 20 39.3 (25.5 – 53.1)
It seems everything causes cancer
 Agree 161 26.9 (23.0 – 30.8) 75 26.6 (20.9 – 32.3) 64 24.2 (18.5 – 29.9) 22 40.8 (27.1 – 54.4)
 Disagree 411 73.1 (69.2 – 77.0) 198 73.4 (67.7 – 79.1) 178 75.8 (70.1 – 81.5) 35 59.3 (45.6 – 72.9)
There’s not much you can do to lower your chances of getting cancer
 Agree 362 62.6 (58.3 – 66.9) 174 61.5 (55.1 – 67.8) 161 66.4 (60.0 – 72.8) 27 49.9 (36.1 – 63.8)
 Disagree 210 37.4 (33.1 – 41.7) 99 38.5 (32.2 – 44.9) 81 33.6 (27.2 – 40.0) 30 50.1 (36.3 – 63.9)
Cancer is most often caused by a person’s behavior or lifestyle (N=570)
 Agree 356 62.4 (58.1 – 66.7) 165 60.7 (54.5 – 67.0) 156 64.6 (58.1 – 71.2) 35 59.6 (46.0 – 73.2)
 Disagree 214 37.6 (33.3 – 41.9) 107 39.3 (33.0 – 45.5) 85 35.4 (28.9 – 41.9) 22 40.4 (26.8 – 54.0)
I’d rather not know my chance of getting cancer (N=571)
 Agree 310 54.3 (49.9 – 58.7) 160 58.7 (52.3 – 65.0) 129 52.6 (45.9 – 59.4) 21 41.6 (27.6 – 55.6)
 Disagree 261 45.7 (41.3 – 50.1) 113 41.3 (35.0 – 47.7) 113 47.4 (40.6 – 54.2) 35 58.4 (44.4 – 72.4)
When I think about cancer, I automatically think about death
 Agree 219 38.5 (34.2 – 42.8) 102 38.3 (32.0 – 44.6) 93 37.4 (30.8 – 43.9) 24 44.5 (30.7 – 58.3)
 Disagree 353 61.5 (57.2 – 65.8) 171 61.7 (55.4 – 68.0) 149 62.6 (56.1 – 69.2) 33 55.5 (41.7 – 69.3)
There are so many different recommendations about preventing cancer, it’s hard to know which ones to follow (N=570)
 Agree 436 77.1 (73.4 – 80.8) 207 76.1 (70.6 – 81.6) 191 80.3 (74.9 – 85.6) 38 66.5 (53.1 – 79.9)
 Disagree 134 22.9 (19.2 – 26.6) 66 23.9 (18.4 – 29.4) 50 19.7 (14.3 – 25.1) 18 33.5 (20.1 – 46.9)
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a:

mean age instead of weighted percentage, with the 95% confidence interval

Determinants of cervical cancer screening with co-testing

Table 2 shows the adjusted odds ratios (aORs) of cervical cancer screening with co-testing, compared to screening with cytology alone, according to sociodemographic, health-related, mental, and behavioral characteristics as reported by screening-eligible women in Texas. The adjusted odds of using hormonal contraception (aOR: 2.03 (1.03 – 3.97)); being vaccinated against Hepatitis B virus (HBV) (aOR:2.48 (1.52 – 4.02)); being vaccinated against HPV (aOR: 4.48, 95% CI: 1.25 – 15.97); or having a personal history of any cancer (aOR: 2.96 (1.29 – 6.77)) was higher for women who reported having been screened with co-testing compared to women who reported having had cytology alone. In addition, the odds of being screened with co-testing was lower in age groups (in years) 45–59 and 60 or older, compared to the age group 30–44 (aOR: 0.48 (0.27 – 0.85) and aOR: 0.14 (0.06 – 0.32), respectively); and in women with an annual household income between $20,000 and $49,999 compared to those with an income between $50,000 and $74,999 (aOR: 0.49 (0.25 – 0.96). However, place of birth (in the US versus outside), place of residence (urban versus rural), women’s beliefs about cancer, cancer risk perceptions, depression, race, education level, marital status, smoking, BMI, health literacy, were not significantly associated with cervical screening with co-testing in this population.

Table 2:

Factors associated with cervical cancer screening with co-testing, compared to screening with cytology alone in Texas

Characteristics Adjusted ORa (95% CI) P-value
1. Socio-demographic Factors
Age group (years)
 30–44 Ref
 45–59 0.48 (0.27 – 0.85) 0.011
 ≥60 0.14 (0.06 – 0.32) <0.001
Ethnicity/Race
 White, Non-Hispanic Ref
 Black, Non-Hispanic 1.74 (0.78 – 3.85) 0.173
 Hispanic 1.52 (0.73 – 3.15) 0.260
 Other 1.74 (0.65 – 4.65) 0.271
Born in USA
 No Ref
 Yes 1.21 (0.55 – 2.70) 0.633
Education
 No greater than 12 years or completed high school Ref
 Post high school training or some college 1.45 (0.73 – 2.86) 0.284
 College/Postgraduate 1.23 (0.59 – 2.57) 0.587
Marital Status
 Single/widowed Ref
 Divorced/separated 1.00 (0.55 – 1.84) 0.995
 Living as married/married 1.28 (0.64 – 2.58) 0.490
Occupation
 Employed Ref
 Homemaker, unemployed, disabled 1.32 (0.72 – 2.43) 0.362
 Other, retired, student 1.79 (0.82 – 3.91) 0.143
Income
 ≤ $19,999 0.67 (0.28 – 1.60) 0.363
 $20,000 – $49,999 0.49 (0.25 – 0.96) 0.037
 $50,000 – $74,999 Ref
 ≥ $75,000 1.28 (0.64 – 2.58) 0.488
Residence
 Urban Ref
 Rural 1.07 (0.57 – 2.03) 0.829
Home Ownership
 Own Ref
 Rent/occupied without paying monetary rent 1.10 (0.66 – 1.83) 0.724
2. Health Behavior, Access and Coverage
Hormonal Contraception
 No Ref
 Yes 2.03 (1.03 – 3.97) 0.040
Smoking
 Never Ref
 Former 0.95 (0.48 – 1.86) 0.877
 Current 1.10 (0.58 – 2.12) 0.765
Health Care Coverage
 No Ref
 Yes 0.92 (0.51 – 1.69) 0.793
Last routine Checkup
 Unknown/Never Ref
 Within the past year 0.50 (0.14 – 1.79) 0.289
 One year ago or more 0.31 (0.08 – 1.17) 0.083
Hepatitis B virus Vaccination
 No Ref
 Yes 2.48 (1.52 – 4.02) <0.001
Human Papillomavirus Vaccination
 No Ref
 Unknown 2.58 (0.90 – 7.43) 0.079
 Yes 4.48 (1.25 – 15.97) 0.021
How difficulty to understand information that doctors, nurses, and other professional tell you?
 Easy Ref
 Difficult 0.98 (0.45 – 2.13) 0.958
3. Mental and Physical Health
Depression
 Never Ref
 A few times a year 1.05 (0.57 – 1.93) 0.880
 Daily, weekly, or monthly 1.02 (0.57 – 1.85) 0.937
BMI
 Underweight to Normal (<25) Ref
 Overweight (25 to <30) 1.33 (0.68 – 2.60) 0.408
 Obesity ( ≥ 30) 0.84 (0.47 – 1.50) 0.555
Personal History of any Cancer
 No Ref
 Yes 2.96 (1.29 – 6.77) 0.010
Family History of any Cancer
 No Ref
 Not sure 0.76 (0.27 – 2.11) 0.596
 Yes 0.74 (0.41 – 1.32) 0.299
4. Perceived Risk and Beliefs about Cancer
Compared to other people your age, how likely are you to get cancer in your lifetime?
 Unlikely Ref
 Neutral 1.29 (0.50 – 2.05) 0.416
 Likely 1.01 (0.70 – 2.35) 0.974
Cancer is most often caused by a person’s behavior or lifestyle
 Disagree Ref
 Agree 0.99 (0.59 – 1.65) 0.959
When I think about cancer, I automatically think about death
 Disagree Ref
 Agree 1.18 (0.70 – 1.98) 0.531
It seems everything causes cancer
 Disagree Ref
 Agree 1.15 (0.63 – 2.08) 0.654
There’s not much you can do to lower your chances of getting cancer
 Disagree Ref
 Agree 0.67 (0.39 – 1.14) 0.140
I’d rather not know my chance of getting cancer
 Disagree Ref
 Agree 1.00 (0.60 – 1.65) 0.990
There are so many different recommendations about preventing cancer, it’s hard to know which ones to follow
 Disagree Ref
 Agree 0.66 (0.36 – 1.24) 0.196
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a:

women who reported having never been screened where not included

In further analyzes, the removal of the variables “income” and education” from the logistic regression model did not significantly alter our main results. Likewise, including the interaction of income and/or education with cancer beliefs variables into the logistic regression model did not change our results, with no significance detected for the interaction terms.

Discussion

In this representative sample of women aged 30 years or older residing in Texas and surveyed about their cervical cancer screening practices, HPV vaccination, HBV vaccination, hormonal contraception use, and personal cancer history were positively associated whereas older age and lower household income were negatively associated with co-testing. To the best of our knowledge, this is the first study to examine the determinants of using co-testing versus cytology alone for cervical cancer screening in the US. Our findings provide key information on the use of co-testing for cervical cancer screening in Texas, and identifies the subsets of women that should be targeted by public health interventions to increase co-testing uptake, thereby improving the effectiveness of cervical screening programs.

Overall, 90.3 % of women in this study of Texas residents reported having been screened for cervical cancer. In 2015, it was estimated that one third of women screened for cervical cancer in the US, had been screened with co-testing.2 While these results indicate a progression in the use of co-testing for cervical screening, they reveal that a substantial proportion of women eligible for co-testing continue to be screened with cytology alone. In fact, evidence suggests that cervical screening with co-testing is more accurate than cytology. Not only is co-testing less likely to miss cervical lesions (dysplasia or cancer) than cytology,10 but also, it performs better than cytology alone in detecting abnormalities of the endo-cervix (the inner part of the cervix, lined with glandular cells). Indeed, cytology screening refers to the morphologic examination of exfoliated cells obtained from the cervical mucosa through Pap smear. Since the endo-cervix is not easily accessible to clinical examination, cervical cells collected through Pap smear mainly stem from exo-cervix. Thus, cytology may miss a lesion in the endo-cervical canal that does not extend to the exo-cervix.21 HPV test, however, detects the presence of HPV’s genome within cervical cells. It is now established that HPV infection is a multifocal infection, as viruses that enter cervical cells in the transformation zone, generally spread to the entire ano-genital region, including to the vagina, the vulva, and the endo-cervical canal.22,23 This is the reason why a positive HPV test on cervical specimen (or even vaginal specimen) is correlated with the presence of the virus in the endo-cervix canal, and colposcopic examination based on a positive HPV test is more likely to detect endo-cervical lesions. Interestingly, the 5-year cumulative risk of CIN3+ in women screened with co-testing was found to be lower than the 3-year cumulative risk of CIN3+ in women screened with cytology alone, when the screening result is negative or normal.24 As a result, the recommended cervical screening interval with co-testing (5 years) is longer than with cytology alone (3 years),25 a consideration that is not negligible, especially in underserved populations. In addition to reducing the rates of women’s absences from their workplace, longer screening intervals may reduce the number/frequency of visits to healthcare facilities, the cost of transportation to and from healthcare facilities for women, as well as providers’ workload. Therefore, emphasis should be made on promoting co-testing as the preferred option for cervical cancer screening in women age 30 years and older, particularly in hard-to-reach communities. In this regard, it is imperative to improve awareness of providers and patients on the indications and benefits of co-testing over cytology alone. Alternatively, screening guidelines should be simplified to endorse co-testing as the only recommended option for cervical screening in the appropriate age group.

In a previous study assessing cervical screening changes in the US, co-testing and cytology were compared each with no screening. These authors reported that the odds of having undergone co-testing were similar to those for having been screened with cytology, with a few exceptions. Hispanics and non-Hispanic Blacks had higher odds of being screened with co-testing than Whites, as did US-born compared to foreign-born women. In accordance with our results, these findings suggest the existence of socio-demographic disparities in the use of co-testing for cervical screening among eligible women in the US, and stresses the need for decision makers to implement adequate policies aimed at reducing these inequalities.

In the digital era, younger people are more likely than older people to use the internet for health information seeking,26 which may be reflected in lower odds of using co-testing for cervical screening among older women. In addition, older women may be seen by older providers who may not be following the most recent recommendations. Owing to the increased risk of developing second primary cancers among cancer survivors, people with personal cancer history are more likely than people without cancer to receive cervical cancer screening. Our finding of a higher odds of cervical screening with co-testing among cancer survivors, indicates a higher utilization of more effective screening tools in this high-risk group to prevent subsequent development of cancer. Interestingly, cancer risk perceptions and beliefs were not associated with cervical screening with co-testing in Texas. While avoiding information on personal risk of cancer has been linked to lower intent to engage in cancer screening,28,29 and fatalistic beliefs about cancer associated with reduced screening rates,30,31 our findings suggest that these factors do not predict the use of co-testing for cervical screening.

HPV vaccination was one of the strongest predictors of screening with co-testing in this study. This finding may reflect a higher health education of HPV-vaccinated women in general, and in particular their better knowledge of the role of HPV in the genesis of cervical cancer. In an analysis of the predictors of HPV vaccination uptake among female high school students, women empowered about their health care had a higher chance of being vaccinated for HPV.32 After HPV vaccination was approved in the US for cervical cancer prevention, there were fears that women who had received HPV immunization might be unwilling to get screened for cervical cancer.34 Adding to the existing evidence that women vaccinated against HPV are more likely to undergo cervical screening than unvaccinated women,2,35,36 our results further indicate that HPV vaccinated women who screen for cervical cancer are more likely to use co-testing.

Our finding that HBV vaccination is a positive predictor of cervical cancer screening with co-testing was unforeseen, as HBV vaccination is universally (at any age) recommended in the US since 2006, per the Advisory Committee on Immunization Practices’ (ACIP) guidelines.37 However, our study sample consisted of women aged 30 years and older, i.e. who were born when HBV vaccine was either unavailable or recommended only for certain adult populations. As a result, women vaccinated against HBV in our report were more likely to have received HBV vaccine at teenage or adult age, which could reflect a better health-related knowledge compared to non HBV-vaccinated women.

The lower odds of screening with co-testing among lower-income women may be attributable to the higher cost of co-testing, compared to cytology alone. In the US, the rate and quality of insurance coverage increases with income level.38 Specifically, low income women are more likely to be uninsured or underinsured, and even when insured, they are less likely to be enrolled in health insurance plans that cover clinical preventive services.39 As a result, it is possible that lower income women who go for cervical screening get screened with the most affordable strategy recommended by their provider.

In our analysis, hormonal contraception use was found to be a predictor of cervical screening with co-testing. Contraception use and access is recognized as an indicator of women’s empowerment and autonomy.40 This autonomy in decision-making about their health is reflected in the use of co-testing by women who screen for cervical cancer. The association between hormonal contraception and cervical cancer screening with co-testing could also be explained by the fact that women who utilize healthcare to acquire contraception are more likely to have frequent interaction with providers, and thus, to be exposed to more effective screening tools.

In addition to women’s characteristics, institutional factors and interaction with health care providers play a critical role in the choice of the cervical cancer screening option women receive. In healthcare facilities where equipment for HPV testing is not readily available, cytology screening may be the only option proposed to clients. Even when both screening options are available, patients who usually look for the best care possible, may get confused when many screening options are recommended, and often rely on their healthcare providers to make the right decision.41 To improve cancer screening effectiveness, the USPSTF suggests that healthcare professionals use the shared decision-making (SDM) approach when recommending cancer screening to patients.42 The principle of the SDM states that patients and clinicians work together and jointly make an informed healthcare decision.42 The SDM has gained significant attention as a means for incorporating patient-centeredness into a healthcare decision, one of the six dimensions of healthcare performance proposed by the 2001 Institute of Medicine (IOM) report.43 As noted by the USPSTF, the SDM (joint participation) is clearly differentiated from the informed consent (clinician disclosure) in terms of the degree of patient involvement and should satisfy both the “informed” and “joint” elements in the decision.42

Henceforth, our findings highlight the importance to further explore the influence of these key factors on the type of cervical cancer screening women aged ≥ 30 years receive in the US. Further investigations are needed to understand the interactions that occur between healthcare providers and women that ultimately lead to the use of co-testing, particularly among older and lower income women. Also, it is important to identify barriers to co-testing in populations found to be more inclined to receive cytology screening.

Limitations

Our study had some limitations. First, this study used self-reported data. Although most questions related to cervical cancer have been validated with medical records data, women who usually confuse pelvic examination with cervical screening, tend to over report cervical screening.44 Also, since screening intervals differ based on the screening strategy, more appropriate approaches to examine cervical cancer screening practices are needed. An option could be to ask women: i) whether they have ever undergone screening, ii) the date of the last screening, and iii) the screening tool used.45

Second, the wording of the question on HPV testing did not allow us to determine if it was used concurrently with cytology in all women surveyed, although those indicating no Pap testing were excluded from the analysis. In our study population, HPV testing may have been performed as a reflex test in some women with abnormal cytology. However, the proportion of women with abnormal cytology (atypical squamous cells of undetermined significance) that can be followed up with reflex HPV testing both in the US and Texas is very low 46,47, making its potential contribution to the definition of our outcome measure (co-testing) minimal. On the other hand, an HPV assay was approved by the Food and Drug Administration (FDA) in 2014 for primary cervical screening of women aged 25 and older. However, most US guidelines do not recommend primary screening with HPV testing, although several organizations including the ACS, the ASCCP, and the ASCP have released interim guidance for clinicians interested in primary screening with HPV testing.49,50 Since interim guidelines are not definitive and generally uncovered by health insurance, it is probable that the majority of women in our study sample had HPV testing as part of co-testing.

Third, because our data was based on a survey directed towards women, we could not explore the effect of healthcare providers, as well as health system’s characteristics that contribute to the choice of either cervical screening method.

Conclusion

This study assessed the prevalence and correlates of cervical cancer screening with co-testing in Texas. While about half of eligible women in Texas reported having ever been screened with co-testing, certain groups were less likely to have benefited from this preferred method. It is imperative to improve awareness among providers and populations on the benefits and indications of co-testing. To that end, public policies should develop and implement appropriate interventions focusing on older and lower income women.

Acknowledgments

Funding Support:

This study was supported by the National Cancer Institute (CCSG, 5P30CA016672, and 5P30CA016672 Sub-Project ID: 5697 (PI: S Shete), a Cancer Prevention Fellowship supported by the Cancer Prevention and Research Institute of Texas (CPRIT) grant award, RP170259 (PI: S Chang); and The Barnhart Family Distinguished Professorship in Targeted Therapy.

Footnotes

Conflicts of interests

None of the authors have any conflict of interest.

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