Secondary Logo

Journal Logo

Contents: Original Research

Disparities in Adherence to National Comprehensive Cancer Network Treatment Guidelines and Survival for Stage IB–IIA Cervical Cancer in California

Pfaendler, Krista S. MD, MPH; Chang, Jenny MPH; Ziogas, Argyrios PhD; Bristow, Robert E. MD, MBA; Penner, Kristine R. MD, MPH

Author Information
doi: 10.1097/AOG.0000000000002591

Although predominantly a disease of women in low- and middle-income countries where cervical cancer screening is not widely available,1 13,240 new cases and 4,170 cervical cancer-related deaths are expected in the United States in 2018.2 Five-year relative survival rates for cervical cancer in the United States have remained stagnant over the past 35 years (69.1% in 1975–1977, 68.8% in 2007–2013), whereas rates for breast cancer (74.8% in 1975–1977, 91.1% in 2007–2013) and ovarian cancer (36.0% in 1975–1977, 46.7% 2007–2013) have improved.3

Women from minority and socioeconomically disadvantaged groups have decreased access to screening, increased incidence, later stage at diagnosis, and higher mortality from cervical cancer; these issues, along with decreased receipt of guideline-adherent care, are thought to explain poorer cervical cancer survival for this population.3–21

Receipt of guideline-adherent treatment is associated with improved survival for locally advanced cervix cancer22 and other cancers, including ovarian cancer.23 However, there are limited data regarding the association of guideline-adherent treatment to survival for patients with early-stage cervical cancer; in fact, a search of PubMed for articles using the key words “cervical cancer,” “early stage,” and “guideline adherence” revealed no articles on this subject in the English language literature in recent years. We hypothesized that 5-year survival for patients with early-stage cervical cancer would be higher for those receiving National Comprehensive Cancer Network guideline–adherent care. Thus, studying women with stage IB–IIA cervical cancer in California, our primary objective was to determine whether National Comprehensive Cancer Network guideline adherence was associated with improved survival. Our secondary objective was to evaluate the association of sociodemographic and hospital characteristics with adherence to National Comprehensive Cancer Network treatment guidelines.


This was a retrospective population-based cohort study of new cervical cancer cases diagnosed and reported to the California Cancer Registry from January 1, 1995, through December 31, 2009. Incident cases from 1995 through 2009 were requested to ensure an adequate sample size within a time of relatively unchanged treatment paradigm and to enable the evaluation of 5-year survival with initial data analysis performed in 2016. Since 1988, standardized data collection and quality control measures have been in place and it has been legally mandated that every cancer diagnosis in California is reported to the California Cancer Registry. Within 18 months of the end of a calendar year, completeness of case reporting exceeds 95% in the California Cancer Registry.24 This statewide population-based cancer surveillance system provided the opportunity for data linkage to the Office of Statewide Health Planning and Development hospital discharge data for our cohort. The Office of Statewide Health Planning and Development database contains International Classification of Disease (ICD) diagnosis information and inpatient discharge data for each admission to a licensed hospital in California. The Surveillance, Epidemiology, and End Results primary site codes for cervical cancer (C530–C539) were used to identify incident cervical cancer cases for inclusion in our study cohort. The study was approved by the institutional review board of the University of California, Irvine (HS#2014-1527) and the State of California Health and Human Services Agency Committee for the Protection of Human Subjects (15-02-1867).

The study included women 18 years of age or older in whom invasive cervical cancer was the first or only cancer diagnosis using the ICD, 9th Revision before 1999 and ICD, 10th Revision for 1999 and later. A total of 22,975 incident cases of cervical cancer were identified with follow-up through May 2015. Among these, a total of 6,063 cases of stage IB–IIA cervical cancer were identified after excluding preinvasive disease, stage IA, stage IIB or greater, unknown stage, incomplete stage information, and diagnosis at autopsy (Fig. 1). Stage IA cases were excluded as a result of the inability of the database to differentiate between stage IA1 and IA2, which have different National Comprehensive Cancer Network guideline treatment recommendations. The database did not differentiate between stage IB1 and IB2; however, overlap in guideline care was deemed sufficient to group these patients together.

Fig. 1.
Fig. 1.:
Flow diagram illustrating inclusions and exclusions to arrive at the final cohort.Pfaendler. Stage IB–IIA Cervical Cancer Disparities. Obstet Gynecol 2018.

Explanatory variables included patient, tumor, and hospital characteristics. Patient variables included age at diagnosis, year of diagnosis, race, ethnicity, insurance payer, socioeconomic status, marital status, and health status (Charlson-Deyo comorbidity score). Age at diagnoses was used both as a continuous variable and as a categorical variable with three groups: 18–39 years of age, 40–64 years of age, and 65 years of age and older. Race and ethnicity of the patient were categorized into five groups: non-Hispanic white, non-Hispanic black, Hispanic, Asian or Pacific Islander, and other. Insurance type was categorized into five groups: Managed care (managed care, health maintenance organization, preferred provider organization, or private insurance), Medicaid, Medicare, other insurance type, and uninsured or unknown. Socioeconomic status was classified into quintiles based on the Yost or Yang score. The Yost score, utilized for patients who were diagnosed before 2006, is a composite index of socioeconomic status contained in the California Cancer Registry that is based on principal component analysis of block group level census variables such as education, income, and occupation.25 The Yang scale, which was used for patients who were diagnosed after 2006, is a similar index based on American Community Survey variables at the block group level.26 Patient comorbidity was measured by the Deyo adaptation of the Charlson Comorbidity Index.27 Comorbidity scores were calculated by using diagnosis codes for comorbidities included in Office of Statewide Health Planning and Development hospital discharge data at the time of the cancer diagnosis. Charlson-Deyo comorbidity score was categorized into three groups: 0, 1 or higher, and unknown; scores of 1 and higher were grouped together because only 5% of our study population had a score of 2 and only 6% had a score of 3 or higher. Tumor variables included clinical stage, histopathologic grade, tumor size, and histology. Hospital characteristics included American College of Surgeons (ACS) Commission on Cancer accreditation and hospital volume. The ACS Commission on Cancer accredits programs that have data-driven performance measures for comprehensive, high-quality, and multidisciplinary patient-centered care. Distribution of hospital volume was examined. Cutoffs for quartiles of hospital annual cases in the data were 4.4, 8.1, and 17.0 cervical cancer cases of all stages per year. Cutoffs for quintiles were 3.9, 6.4, 10.7, and 19.5 cases per year. To minimize the number of the categories of hospital volume and maximize the effect of hospital volume, the optimal cutoff was 20 cervical cancer cases of all stages per year, dividing the cohort such that just more than 80% of patients were treated in low-volume centers and nearly 20% of patients were treated in high-volume centers. Furthermore, previous ovarian cancer literature uses the same cutoff of 20 cases per year.23 Using this cutoff, we categorized eight hospitals as high volume and 358 hospitals as low volume.

The first main outcome variable was adherence to National Comprehensive Cancer Network treatment guidelines, accounting for guideline changes that occurred during the study time period. The National Comprehensive Cancer Network Clinical Practice Guidelines represent consensus statements of evidence regarding currently accepted standard of care approaches to cancer treatment. Guideline change requests can be submitted when practice changing data are published, after which the expert panel discusses the request and associated references and decides when changes to the National Comprehensive Cancer Network guidelines are appropriate. For stages IB–IIA, National Comprehensive Cancer Network adherence included surgical or primary radiation approaches. Guideline-adherent surgery was defined as radical hysterectomy with pelvic lymphadenectomy. If pelvic lymph nodes were negative, either radiation or no radiation was considered adherent care as a result of the absence of information regarding other risk factors that are not included in the California Cancer Registry database. If pelvic lymph nodes were known to be positive, this had to be followed by pelvic radiation with or without brachytherapy. For patients diagnosed after January 1, 2000, with positive pelvic lymph nodes, adherence required concurrent chemotherapy with pelvic radiation; if treatment occurred on or before December 31, 1999, chemotherapy administration was not required for treatment to be considered adherent care. For stages IB–IIA, adherent nonsurgical management required both pelvic radiation and brachytherapy; concordant chemotherapy was included for guideline adherence on or after January 1, 2000.

The second main outcome variable was cervical cancer–specific 5-year survival. Cause of death was recorded according to ICD criteria in effect at the time of death. The last date of follow-up was either the date of death or the date of last contact. Cervical cancer–specific death was defined as death caused by cervical cancer alone. Patients who died from other causes were treated as censored cases at the time of the event. Given the sample sizes of 2,831 patients receiving guideline-adherent care compared with 3,232 patients receiving non–National Comprehensive Cancer Network guideline–adherent care, the study was powered to detect odds ratios of at least 1.15 for a prevalence of exposure of 25%. Similarly, with 674 deaths from cervical cancer, the study was powered to detect hazard ratios as small as 1.25 for a characteristic with 25% prevalence.

Descriptive statistics for demographic, clinical, and hospital characteristics by patients' status of receiving National Comprehensive Cancer Network–adherent care were analyzed with χ2 test for categorical variables. Multivariate logistic regression analysis was performed to estimate the probability of adherence to National Comprehensive Cancer Network guidelines, generating adjusted odds ratios and 95% CIs. Survival analysis was performed using the Kaplan-Meier estimate of survival probability and log-rank test. After verifying the proportionality assumption, a Cox proportional hazards model was fitted to evaluate the independent effect on survival of each predictor. Possible interaction terms of main effects were tested. Adjusted hazard ratios and 95% CIs were generated. All P values are two-sided. All statistical analysis was performed using SAS 9.4.


A total of 6,063 patients were identified for study inclusion. The median follow-up time was 8.7 years with a range of 0–20.2 years. Age at diagnosis ranged from 18 to 98 with most women being reproductive age and only 13.7% were 65 years of age or older (Table 1). The majority presented with stage I disease (88.1%) and 26.2% had a Charlson-Deyo comorbidity score of 1 or higher. The largest racial and ethnic group was non-Hispanic white (41.8%) women followed in frequency by Hispanic women (38.3%) and Asian or Pacific Islander (13.8%) women. Only 5% of the population was identified as non-Hispanic black women. Just more than half (51.5%) of the study population was treated in a hospital with ACS Commission on Cancer accreditation and only 18.8% of patients were treated in high-volume hospitals. Overall, 46.7% of patients received National Comprehensive Cancer Network guideline–adherent care. Details regarding the treatment provided to patients receiving nonadherent care are delineated in Appendix 1, available online at

Table 1.
Table 1.:
Patient, Tumor, and Hospital Characteristics
Table 1.-a
Table 1.-a:
Patient, Tumor, and Hospital Characteristics

The multivariate logistic regression model for adherence to National Comprehensive Cancer Network treatment guidelines revealed statistically significant decreased odds of receiving guideline-adherent care with increasing age, lower socioeconomic status, higher Charlson-Deyo comorbidity score, larger tumor size, higher stage of disease, and treatment in a low-volume center (Table 2). Compared with those in the highest socioeconomic status quintile, women in the lowest socioeconomic status quintile were 32% less likely to receive guideline-adherent care (adjusted odds ratio [OR] 0.69, 95% CI 0.57–0.84, P<.001). Women with a Charlson-Deyo comorbidity score of 1 or higher had a similarly decreased likelihood of receiving guideline-adherent care (adjusted OR 0.78, 95% CI 0.69–0.89, P<.001). In low-volume centers, 45.9% of patients received adherent care compared with 50.9% in high-volume centers (effect size 0.90, 95% CI 0.84–0.96; adjusted OR 0.74, 95% CI 0.64–0.85, P<.001).

Table 2.
Table 2.:
Univariate and Multivariate Logistic Regression on Receipt of National Comprehensive Cancer Network Guideline–Adherent Care

The Cox proportional hazards model demonstrated that the risk of death from cervical cancer was increased in patients who did not receive National Comprehensive Cancer Network guideline–adherent care (adjusted hazard ratio 1.43, 95% CI 1.19–1.73, P<.001) compared with those who did receive National Comprehensive Cancer Network guideline–adherent care (Table 3). Specifically, 13.3% of patients receiving non–National Comprehensive Cancer Network guideline–adherent care died from cervical cancer compared with 8.6% of those patients receiving National Comprehensive Cancer Network guideline–adherent care (effect size 1.55, 95% CI 1.34–1.80). Patients who received care in a low-volume hospital (fewer than 20 cases treated/year) were not found to have a statistically significant increased risk of death from cervical cancer (adjusted hazard ratio 1.29, 95% CI 0.99–1.67, P=.057). Black race, Medicaid payer status, Charlson-Deyo score, larger tumor size, higher tumor grade, and higher stage at diagnosis were each statistically significantly associated with increased probability of dying from cervical cancer. After adjusting for other variables, socioeconomic status was not a significant predictor of cervical cancer–specific survival.

Table 3.
Table 3.:
Predictors of Cervical Cancer–Specific Mortality Analyzed Using Cox Proportional Hazards Model

The cervical cancer–specific 5-year survival of the study population was 90.4% (standard error 0.4%). For patients receiving National Comprehensive Cancer Network guideline–adherent care, the cervical cancer–specific 5-year survival was 93.0% (standard error 0.5%) compared with 88.1% (standard error 0.6%) among those receiving nonadherent care (log-rank test P<.001) (Fig. 2).

Fig. 2.
Fig. 2.:
Kaplan-Meier survival curve for cervical cancer–specific survival according to National Comprehensive Cancer Network guideline adherence.Pfaendler. Stage IB–IIA Cervical Cancer Disparities. Obstet Gynecol 2018.


In this large population-based cohort study of patients with early cervical cancer in California, we found a significant association between adherence to National Comprehensive Cancer Network guidelines and 5-year survival. Patients with increasing age, lower socioeconomic status, higher comorbidities, and receipt of care in a low-volume hospital were more likely to receive non–National Comprehensive Cancer Network guideline–adherent care. The survival difference associated with adherence persisted after multivariate analysis controlling for factors known to affect survival. Black race, Medicaid payer status, higher comorbidities, stage II disease, grade 2 or higher histology, and larger tumor size were also associated with an increased risk of death from cervical cancer. Our study reinforces that improvements in cervical cancer screening, early detection, and treatment have not been evenly distributed among women of all racial, ethnic, and socioeconomic backgrounds.20

Cervical cancer in the United States has persistently and disproportionately burdened the socioeconomically disadvantaged and racial and ethnic minorities, resulting in a higher rate of disease and mortality for these groups.3–21 Previous work has established that differences in cervical cancer–specific survival are intimately tied to advanced stage at diagnosis,13,16,18 race,14,16 insurance status,7 and socioeconomic status.16,18 Recent research demonstrated that hysterectomy-corrected age-standardized cervical cancer mortality rates were higher and more disparate between black and white women than previously thought. After correcting for hysterectomy, the mortality rate was 10.1 per 100,000 for black women compared with 4.7 per 100,000 for white women.28 However, in a study of the United States Military Health Care System, where black and white women had equal access regardless of race, ethnicity, or socioeconomic status, 5- and 10-year survival were comparable, indicating that race was not an independent predictor of survival after controlling for access to equal care.11 Similarly, in a population of women who all had Medicare fee-for-service insurance, race, ethnicity, and socioeconomic status were not associated with variations in survival.10 Persistent racial, ethnic, and socioeconomic disparities in cervical cancer–specific mortality prompted this investigation to determine whether receipt of National Comprehensive Cancer Network guideline–adherent care, rather than other patient characteristics, may be a driving force behind disparate survival outcomes. Our data add to the existing body of literature regarding cervical cancer disparities by demonstrating that receipt of non–National Comprehensive Cancer Network guideline–adherent care is an independent predictor of cervical cancer–specific mortality, specifically in patients with early cervical cancer.

Strengths of this study include the reliability of statewide reporting to the California Cancer Registry and the large sample size, which is particularly essential for evaluating survival in this patient population given 5-year survival of 90% for early cervical cancer. Furthermore, the database included a diverse population including women of all ethnicities and socioeconomic backgrounds. Many prior studies compared black and white women only, whereas more than half of our study population was Hispanic (38.3%) or Asian American (13.8%), providing an excellent representation of other minority populations in the United States. The socioeconomic, racial, and ethnic makeup of California closely represents the projected makeup of the United States in 40 years according to U.S. Census Bureau data.29 Therefore, understanding disparities in care and outcomes in the California population now will help physicians, administrators, and policymakers to address similar issues in patients with early cervical cancer throughout the United States in the future.

The current study also has limitations that must be considered when interpreting the data presented. Tumor size and lymph node status were not consistently reported and additional information such as lymphovascular space invasion, depth of cervical stromal invasion, margin, and parametrial status of surgical specimens were not available to determine which subsets of patients with negative pelvic lymph nodes should have received adjuvant radiation in accordance with National Comprehensive Cancer Network guidelines. Additionally, among the 22,975 incident cervical cancer cases from January 1, 1995, through December 31, 2009, there was a sizeable portion (16.6%) with unknown (n=2,775) or incomplete (n=1,033) staging who were excluded from analysis, potentially creating selection bias.

In conclusion, for women in California with early-stage cervical cancer, disparities exist in access to National Comprehensive Cancer Network guideline–adherent care. Not receiving adherent care was associated with decreased survival, even in a subpopulation with high 5-year survival. By taking a systematic approach to identify the factors contributing to delivery of non–National Comprehensive Cancer Network guideline care, we can begin to implement health policy and health care delivery systems designed to mitigate the driving forces contributing to variation in delivery of adherent care, including not only patient and hospital characteristics, but also health care provider practices and geographic distribution of care. With the goal to diminish disparities in survival, continued focus is merited on the delivery of National Comprehensive Cancer Network guideline–adherent care for women with early-stage cervical cancer.


1. Ferlay J, Soerjomataram I, Ervik M, et al. GLOBOCAN 2012 v1. 0, cancer incidence and mortality worldwide: IARC CancerBase No. 11. Lyon (France): International Agency for Research on Cancer; 2013.
2. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2018. CA Cancer J Clin 2018;68:7–30.
3. Howlader N, Noone AM, Krapcho M, Miller D, Bishop K, Kosary CL, et al. SEER cancer statistics review, 1975–2014. Available at: Retrieved August 7, 2017.
4. Adams SA, Fleming A, Brandt HM, Hurley D, Bolick-Aldrich S, Bond SM, et al. Racial disparities in cervical cancer mortality in an African American and European American cohort in South Carolina. J S C Med Assoc 2009;105:237–44.
5. Ashing-Giwa K, Rosales M. Evaluation of therapeutic care delay among Latina- and European-American cervical cancer survivors. Gynecol Oncol 2013;128:160–5.
6. Bradley CJ, Given CW, Roberts C. Health care disparities and cervical cancer. Am J Public Health 2004;94:2098–103.
7. Brookfield KF, Cheung MC, Lucci J, Fleming LE, Koniaris LG. Disparities in survival among women with invasive cervical cancer: a problem of access to care. Cancer 2009;115:166–78.
8. Chu KC, Miller BA, Springfield SA. Measures of racial/ethnic health disparities in cancer mortality rates and the influence of socioeconomic status. J Natl Med Assoc 2007;99:1092–100, 1102–4.
9. Clegg LX, Reichman ME, Miller BA, Hankey BF, Singh GK, Lin YD, et al. Impact of socioeconomic status on cancer incidence and stage at diagnosis: selected findings from the surveillance, epidemiology, and end results: National Longitudinal Mortality Study. Cancer Causes Control 2009;20:417–35.
10. Coker AL, Du XL, Fang S, Eggleston KS. Socioeconomic status and cervical cancer survival among older women: findings from the SEER-Medicare linked data cohorts. Gynecol Oncol 2006;102:278–84.
11. Farley JH, Hines JF, Taylor RR, Carlson JW, Parker MF, Kost ER, et al. Equal care ensures equal survival for African-American women with cervical carcinoma. Cancer 2001;91:869–73.
12. Harlan LC, Greene AL, Clegg LX, Mooney M, Stevens JL, Brown ML. Insurance status and the use of guideline therapy in the treatment of selected cancers. J Clin Oncol 2005;23:9079–88.
13. Leath CA 3rd, Straughn JM Jr, Kirby TO, Huggins A, Partridge EE, Parham GP. Predictors of outcomes for women with cervical carcinoma. Gynecol Oncol 2005;99:432–6.
14. Lim JW, Ashing-Giwa KT. Examining the effect of minority status and neighborhood characteristics on cervical cancer survival outcomes. Gynecol Oncol 2011;121:87–93.
15. Lin Y, Zhan FB. Geographic variations of racial/ethnic disparities in cervical cancer mortality in Texas. South Med J 2014;107:281–8.
16. McCarthy AM, Dumanovsky T, Visvanathan K, Kahn AR, Schymura MJ. Racial/ethnic and socioeconomic disparities in mortality among women diagnosed with cervical cancer in New York City, 1995-2006. Cancer Causes Control 2010;21:1645–55.
17. Moshkovich O, Lebrun-Harris L, Makaroff L, Chidambaran P, Chung M, Sripipatana A, et al. Challenges and opportunities to improve cervical cancer screening rates in US health centers through patient-centered medical home transformation. Adv Prev Med 2015;2015:182073.
18. Movva S, Noone AM, Banerjee M, Patel DA, Schwartz K, Yee CL, et al. Racial differences in cervical cancer survival in the Detroit metropolitan area. Cancer 2008;112:1264–71.
19. Parikh S, Brennan P, Boffetta P. Meta-analysis of social inequality and the risk of cervical cancer. Int J Cancer 2003;105:687–91.
20. Pierce Campbell CM, Menezes LJ, Paskett ED, Giuliano AR. Prevention of invasive cervical cancer in the United States: past, present, and future. Cancer Epidemiol Biomarkers Prev 2012;21:1402–8.
21. Rauh-Hain JA, Clemmer JT, Bradford LS, Clark RM, Growdon WB, Goodman A, et al. Racial disparities in cervical cancer survival over time. Cancer 2013;119:3644–52.
22. Kang YJ, O'Connell DL, Lotocki R, Kliewer EV, Goldsbury DE, Demers AA, et al. Effect of changes in treatment practice on survival for cervical cancer: results from a population-based study in Manitoba, Canada. BMC Cancer 2015;15:642.
23. Bristow RE, Chang J, Ziogas A, Anton-Culver H. Adherence to treatment guidelines for ovarian cancer as a measure of quality care. Obstet Gynecol 2013;121:1226–34.
24. Parikh-Patel A, Allen M, Wright WE; California Teachers Study Steering Committee. Validation of self-reported cancers in the California Teachers Study. Am J Epidemiol 2003;157:539–45.
25. Yost K, Perkins C, Cohen R, Morris C, Wright W. Socioeconomic status and breast cancer incidence in California for different race/ethnic groups. Cancer Causes Control 2001;12:703–11.
26. Yang J, Schupp C, Harrati A, Clarke C, Keegan T, Gomez S. Developing an area-based socioeconomic measure from American Community Survey data. Fremont (CA): Cancer Prevention Institute of California; 2014.
27. Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol 1992;45:613–9.
28. Beavis AL, Gravitt PE, Rositch AF. Hysterectomy-corrected cervical cancer mortality rates reveal a larger racial disparity in the United States. Cancer 2017;123:1044–50.
29. Colby SL, Ortman JM. Projections of the size and composition of the U.S. population: 2014 to 2060. In: Current population reports. Washington, DC: U.S. Census Bureau; 2014. p. 25–1143.

Supplemental Digital Content

© 2018 by American College of Obstetricians and Gynecologists. Published by Wolters Kluwer Health, Inc. All rights reserved.