Gynecologic Cancer Disparities Lee-may Chen, MD John A. Kerner - - PowerPoint PPT Presentation

gynecologic cancer disparities
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Gynecologic Cancer Disparities Lee-may Chen, MD John A. Kerner - - PowerPoint PPT Presentation

Disclosures UCSF Helen Diller Family Comprehensive Cancer Center I have no financial disclosures Gynecologic Cancer Disparities Lee-may Chen, MD John A. Kerner Distinguished Professor in Gynecologic Oncology Department of Obstetrics,


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UCSF Helen Diller Family Comprehensive Cancer Center

10/19/18

Lee-may Chen, MD John A. Kerner Distinguished Professor in Gynecologic Oncology Department of Obstetrics, Gynecology and Reproductive Sciences

Gynecologic Cancer Disparities

Disclosures

I have no financial disclosures

2 Helen Diller Family Comprehensive Cancer Center Helen Diller Family Comprehensive Cancer Center 3

Learning Objectives

  • To define health disparities, versus health care

disparities

  • To describe examples of disparities in gynecologic

cancer

  • To participate in improving health equity for all patients

Trends in Mortality by Race

Rate per 100,000 population, by Year of Death

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SEER, 2003

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Examples of Cancer Health Disparities

  • Incidence (new cases)
  • Prevalence (all existing cases)
  • Mortality
  • Morbidity
  • Survivorship , QOL after Cancer Treatment
  • Burden of cancer, related health conditions
  • Screening rates
  • Stage at diagnosis

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Cancer Health Disparities

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Disparities of Referrals

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Source: UCSF Cancer Registry

Definitions

Health Disparities: difference in health that is closely linked with social or economic, and/or environmental disadvantage Equal health may require different levels of resources.

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Age-standardized Incidence and Death Rates

Rates per 100,000, 1996-2000

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Cervical Cancer Stage

By Race and Ethnicity, SEER 1996-2000

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By Poverty Rate, SEER 1995-1999

Factors that Influence Social Disparities

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Ward et al, CA Cancer Clin J 2004

Cervical Cancer

  • Difficulty in access
  • Poor follow-up of abnormal screenings
  • Lower literacy rates
  • Medical comorbidities
  • Public insurance
  • Low socioeconomic status
  • Black women are more likely to be treated with primary radiation /

chemotherapy, less likely to undergo full surgery, minimally invasive surgery

  • Older women, low volume hospitals, Medicaid/MediCal less likely

to receive guideline-based care

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Fleming et al, PLoS One, 2014 Uppal et al, Gynecol Oncol 2016

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Delivery of Radiation Therapy

Cervix Radiation therapy completed within 60 days of initiation of radiation among women diagnosed with any stage of cervical cancer [CERRT] 100% (n=12/12) 81% Chemo administered to cervical cancer patients who received raddiation for stages IB2-IV (Group 1) or with + pelvic LN, + surgical margin, &/or + parametrium (Group 2) [CERCT] 100% (n=29/29) 90% Use of brachytherapy in patients treated with primary radiation with curative intent in any stage of cervical cancer [CBRRT] 98% (n=46/47) 69%

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  • Brachytherapy
  • Chemosensitization
  • Timing

Source: UCSF Cancer Registry & ACS CoC UCSF 2015 ACS CoC Benchmark

Disparities in Primary RT/Chemo for Cervical Cancer

National Cancer Database: 51% utilization of brachytherapy

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Korenaga et al, WAGO 2018

Improving prevention & screening

  • Promotion of HPV vaccination
  • 41% completion by females at Kaiser
  • Asians: 1.29 OR, Hispanics: 0.82 OR, Black 0.53 OR

‒ Higher adherence in younger girls, less acculturated Latinas

  • Self sampling of HPV
  • 20% completed self -collected Pap smears, versus 6%
  • 2.7% positive for HPV 16/18

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Freeman et al, Obstet Gynecol 2018 Sultana et al, Int J Cancer, 2016

What’s New isn’t always better

  • LACC Trial: Phase III trial of Open versus Minimally Invasive

Radical Hysterectomy for Stage IA1-IB2 cervical CA

  • Methods: 740 patients for 90% power to declare noninferiority in

DFS at 4.5 years with a margin of 7.2%

  • Study closed at 631 patients, median follow-up of 2.5 years.

‒ MIS: 16% robotic, 83% laparoscopic

  • MIS was associated with worse overall survival (97% versus

86%, HR 6.0, 95% CI 1.48-20.3, p = 0.004) and disease free survival (HR 3.74, 95% CI 1.63-8.58, p = 0.002)

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Ramirez et al, SGO 2018

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Endometrial Cancer

  • Modifiable risk factors
  • Obesity

‒ Impacting minimally invasive surgery, efficacy of chemotherapy & radiation

  • Diabetes
  • Black women were less likely to receive surgery (OR 0.38)

‒ Even after adjusting for age, stage, region, income, comorbidities

  • Black women have higher mortality (OR 1.6-2.9) and more high-risk

disease

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Doll et al, Am J Obstet Gynecol, 2017 Modesitt et al, Obstet Gynecol Surv, 2005

Minimally Invasive Surgery & Adjuvant therapy

Endometrium Endoscopic or Laparoscopic, robotic, or converted to

  • pen surgery performed for all endometrial cancer, for

all stages [ENDLRC]

96% (n=97/101)

75% Chemotherapy and/or radiation administered to patients with Stage IIIC or IV endometrial cancer [ENDCTRT] 90.5% (n=19/21) 85.5%

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Source: UCSF Cancer Registry & ACS CoC

UCSF 2015 ACS CoC Benchmark

Laparoscopy vs. Laparotomy

  • GOG LAP2
  • Randomized trial of laparoscopy vs. laparotomy for

comprehensive surgical staging of uterine cancer

  • N=2616 (920 lap, 1696 L/S), 1996-2005

78% vs 86% complete staging 23% conversion to open, influenced by age, obesity Median OR time: 3.3 vs. 2.2hrs Median LOS: 3 vs. 4 days Laparoscopy with less pneumonia, ileus

3 year recurrence: 11.3 vs. 10.2% 5-year survival: 89.8% in both groups

Walker et al, J Clin Oncol 2009 Walker et al, J Clin Oncol 2012

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Role of Gynecologic Oncologist

  • SEER database, linked to Medicare
  • n=18,338 Endometrial cancer patients, Stage I-IV,

1991-2002

  • Multivariate Analysis for Survival

Chan et al, J Clin Oncol 2011 Hazard Ratio Confidence Interval P-value Age at diagnosis 1.04 (1.04 - 1.05) <0.001 Stage 5.89 (5.16 - 6.72) <0.001 Grade 2.87 (2.52 - 3.28) <0.001 Gynecologic oncologist 0.71 (0.62 - 0.82) 0.001

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Endometrial CA: Role of Gyn Oncologist

Yes GynOnc=79% No GynOnc= 73% P=0.001

Disease specific survival, Stage II-IV disease Survival (percent) Time (years) Chan et al, J Clin Oncol 2011

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Calling a Gynecologic Oncologist

  • Surgical staging not readily available
  • Preoperative high risk histology
  • Cervical or extra-uterine disease
  • (+) washings
  • Unexpected endometrial CA on final path
  • Recurrent disease
  • Non-operative therapy considered

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Treatment Guidelines can also be Diverse

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Ovarian Cancer

  • Access to high quality care, involving complex surgical & medical

management

  • Non-adherence associated with Black race, low socio-economic

status, low volume hospital, low volume surgeon

  • High volume surgeons are associated with urban settings
  • Access to clinical trials
  • Low enrollment associated with non-White race,

Medicaid/MediCal, low English proficiency

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Bristow et al, J Natl Cancer Inst, 2013 Mishkin et al, Gynecol Oncol 2016

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Do the Right Ovarian Cancer Surgery

Ovary Salpingo-oophorectomy with

  • mentectomy, debulking,

cytoreductive surgery, or pelvic exenteration in Stages I-IIIC ovarian cancer [OVSAL] 81% (n=30/37) 69%

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UCSF 2015 ACS CoC Benchmark

Source: UCSF Cancer Registry & ACS CoC

Stick with the Guidelines

  • Retrospective cohort study of Stage IIIC-IV ovarian cancer through

SEER-Medicare database, 1992-2009.

  • Primary outcome of adherence to NCCN treatment guidelines for

surgery, chemotherapy N=10,296. Median follow-up: 57 mo. Median survival: 18 mo. Overall, 30.2% received guideline adherent care. 31% whites, 19% blacks, 32% Asians, 25% Hispanics, p < 0.001 Inverse association with non-adherent care and socioeconomic status Median survival for guideline adherent care: 36 mo. HR 1.69 for non-adherence (95% CI 1.60-1.79)

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Bristow et al, Obstet Gynecol 2015

Asians versus Caucasians

  • SEER database review of epithelial ovarian cancer between 1988-

2009 N = 52,260. 3932 Asian, 48,328 white Median age of diagnosis: 56 vs. 64, p < 0.001 On multivariate analysis, age, race, surgery, stage, tumor grade were all independently predictive of 5 year disease specific survival

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Fuh et al, Gynecol Oncol 2015

Genetic Counseling & Testing

  • 53% of ovarian cancer patients are currently offered genetic

counseling and testing. 36% counseled, 33% tested

  • Mean time from diagnosis to counseling: 4.6mo.
  • Barriers: race, language, insurance, referral process

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Manrriquez et al, Gynecol Oncol 2018

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SGO Health Disparities Taskforce 2010

  • Literature review from 1985-2012
  • MeSH terms: health care disparities, racial and ethnic health

disparities, gynecologic cancers, treatment, outcome, ovarian cancer, endometrial cancer, cancer

  • 94 articles identified
  • Limited number of studies for non-Black women
  • Most studies relied on large clinical databases—incomplete

information about systemic factors, provider, and patients

  • Most literature concentrated on socioeconomic status and

comorbidities

  • Recommendations for adherence to guidelines, increasing access

29

Collins et al, Gynecol Oncol 2014

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Healthy People 2020

  • Economic stability
  • Education
  • Social and community context
  • Health & health care
  • Neighborhood and built environment

Five Core Social Determinants

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Koh et al, Health Educ Behav 2011

Role of the Neighborhood

  • Community socioeconomic status contributes to biologic risk

profiles and functions synergistically in a negative fashion ‒ Access to nutritional foods ‒ Recreational facilities for an active lifestyle

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Role of the Health Care System

  • Unequal access to healthcare
  • Barrier to accessing cancer care
  • Medicaid/MediCal, Private supplemental insurance
  • Subsidized clinics

‒ Electronic medical records ‒ Emergency departments ‒ Ancillary services ‒ Consistent staff

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Role of Individuals

  • Physician characteristics influence the success of the doctor-

patient encounter

  • Medical judgements contributing to racial disparities
  • Pain assessment
  • Current oncology workforce does not reflect the population

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Challenges in measuring disparities

  • Race is a social constructed term
  • Ethnicity relates to cultural factors
  • Language, religion, beliefs, practices, ancestry, nationality,

community

  • Observer collected demographic data has poor sensitivity beyond

Black and White

  • Self-reporting of race and ethnicity is the gold standard.

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Racial Discrepancy Examples

  • American Indian / Alaska Native
  • Asian race as diverse populations
  • Hispanic ethnicity as diverse populations
  • Foreign born versus U.S. born
  • SEER categorized as White, Black, Other until 1980
  • Hysterectomy rates affects cancer incidence

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Populations at risk for disparities

  • Limited English proficiency
  • Hispanic, Asian, immigrants
  • Disparities of access, consent, adherence
  • Translations services benefit from in-person translation
  • Language impacts clinical trial enrollment

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Nguyen et al, JNCI Monogr 2005

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Populations at risk for disparities

  • Trans and gender-nonconforming
  • Meeting routine health care needs
  • Unwelcoming health care settings
  • Higher levels of poverty
  • Lower rates of health insurance

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Jaffee et al, Med Care 2016

Populations at risk for disparities

  • Rural populations
  • Healthcare is concentrated in cities
  • Lower education in farming communities
  • Lower socioeconomic status
  • Lower prevalence of private insurance
  • Farther distance from high volume surgeons and hospitals
  • Higher rates of smoking, obesity, sedentary lifestyle

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Bristow et al, Gynecol Oncol 2014 Moy et al, MMWR Surveil Summ 2017

Improvements in patient navigation

  • American College of Surgeons CoC Standard 3.1
  • A patient navigation process driven by a triennial community

Needs Assessment is established to address health care disparities and barriers to cancer care. Resources to address identified barriers may be provided either on‐site or by referral.

  • Reducing no-show rates in colposcopy from 50% 30%

‒ Blacks. Latina, publicly insured tended to miss more appointments

  • Improving antiestrogen therapy for hormone receptor positive

breast cancer, 1.73 OR

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Luckett et al, J Womens Health 2015 Ko et al, J Clin Oncol 2014

Addressing Cancer Disparities

  • Researching factors that influence cancer risk
  • Clinical trials to test interventions in diverse populations
  • Delivering cancer care into diverse communities
  • Training to increase diversity in cancer and cancer

disparities research workforce

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UCSF School of Medicine Differences Matter

  • Recruitment, Retention, Climate
  • Learning Environment
  • Clinical Health Equity
  • Research Action Group for Equity
  • Pipeline, Outreach, and Pathways

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