Against the Grain Bringing PCPs back into Cancer Care through Onco-Primary Care

Transcription

1 Against the Grain Bringing PCPs back into Cancer Care through Onco-Primary Care Kevin C. Oeffinger, MD Director, Duke Center for Onco-Primary Care Professor with Tenure Department of Medicine Secondary: Department of Community & Family Medicine Duke Community & Family Medicine Grand Rounds June 18, 2018

2 Cancer continuum (screening, prevention, cancer care, survivorship) Current care model in U.S. Onco-primary care model Duke Center for Onco-Primary Care (T+13 months) Outline

3 Cancer Continuum Prevention Screening Cancer Therapy Survivorship People in the U.S., M 310 M 151 M 1.6 M 1.1 M 2016 Model Prevention o Lifestyle o (Chemoprevention) o (Genetics) Screening o One-size fits all o Cervical o Breast o Colon o Prostate o Lung Survivorship o One-size fits all 2026 Model Prevention o Lifestyle o Targeted chemoprevention o Population genetics Screening o Risk-stratified o Tumor biomarkers o Expanded cancers Survivorship o Risk-stratified o Efficient utilization of resources o Coordinated care

4 Advances in Cancer Screening

5 Screenable Cancers in the U.S. Cancer Cases/yr % of total % of deaths Breast 246, % 6.8% Colorectal 134, % 8.3% Cervical 12, % 0.7% Prostate 180, % 4.4% Lung 224, % 26.5% Total 47.4% 46.7%

6 Screenable Cancers in the U.S. Cancer Cases/yr % of total % of deaths % localized Breast 246, % 6.8% 61% Colorectal 134, % 8.3% 39% Cervical 12, % 0.7% 46% Prostate 180, % 4.4% 80% Lung 224, % 26.5% 16% Total 47.4% 46.7%

7 Screenable Cancers in the U.S. Cancer Cases/yr % of total % of deaths % localized Breast 246, % 6.8% 61% Colorectal 134, % 8.3% 39% Key points: Cervical Almost 50% 12,990 of cancer cases 0.8% can potentially 0.7% be detected 46% Prostate by current 180,890 screening tests 10.7% 4.4% 80% Lung These cancers 224,390 account 13.3% for about 50% 26.5% of cancer 16% deaths Substantial % of cancers detected at advanced stage Total 47.4% 46.7% Though not all screen-detected cancers can be cured, we can do MUCH better

8 U.S. Cancer Screening Rates Percent Cervical Breast Colon Prostate Lung Smith RA, et al. CA Cancer J Clin, 2017

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10 Siu AL, et al. Ann Intern Med, 2016 How does a woman age make an informed decision on breast cancer screening? Oeffinger KC, et al. JAMA, 2015

11 If we take 1,000 women at the age of 40 and follow them for 5 years with an annual mammogram 6 in in in1000

12 If we take 1,000 women at the age of 40 and follow them for 5 years with an annual mammogram 6 in in in1000 Family History and Breast Density 6 12/1, /1,000 BRCA1 carrier 6 80/1,000 1/12

13 If we take 1,000 women at the age of 40 and follow them for 5 years with an annual mammogram Risk-Stratified Cancer Screening 6 in in in1000 Family History and Breast Density 6 12/1, /1,000 BRCA1 carrier 6 80/1,000 1/12

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15 No significant difference in prostate cancer deaths between two groups. However, 90% of control group had undergone PSA testing.

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17 20% reduction in prostate-specific mortality Rate ratio = 0.80 (95% CI )

18 Moyer VA, et al. Ann Intern Med, 2012

19 USPSTF, JAMA 2018

20 Negoita S, et al. Cancer, 2018

21 Prostate Cancer Screening

22 Duke Primary Care PSA Screening Algorithm

23 Duke Primary Care and Duke Primary Care Consortium County Durham Practice DPC Pickett Road DPC Croadaile DUC Croasdaile DUC Fayetteville Road Durham Medical Center Durham Pediatrics Main Sutton Station Internal Medicine Triangle Family Practice 224 primary care physicians 34 practice sites 7 counties Expanding sites and physicians All on same EHR (Epic) Existing research infrastructure (PBRN) Granville Vance Alamance Chatham Orange Wake DPC Butner-Creedmoor Oxford Family Physicians DPC Henderson DPC Mebane Kernodle Clinic West DPC of Galloway Ridge DPC Hillsborough DUC Hillsborough DPC Meadowmont DPC Timberlyne DPC Apex DPC Blue Ridge DPC Brier Creek DPC Creedmoor Road DPC Midtown DPC Knightdale DPC Morrisville DPC Waverly Place DPC Wellesley DPC Western Wake DPC Wake Forest DPC Wakelon Internal Medicine DUC Brier Creek DUC Knightdale DUC Morrisville North Hills Internal Medicine

24 Duke Primary Care PSA Screening Algorithm

25 Duke Primary Care PSA Screening Algorithm

26 Implementation Resulted in Increased Screening Percent 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Change in PSA Testing Pre-Post February 22, % Pre PSA Present Post 70% Courtesy of Kevin Shah, MD

27 Screening increased in all clinics, but rates of screening by clinic vary widely Courtesy of Kevin Shah, MD

28 Urology Referrals February 22, 2017 February 21, 2018 Age Group Algorithm PSAs Urology Referrals % <40 yrs Do not screen % Resume screening at 50 3, % Screen q 2yrs 1, % Refer % Screen q 2 yrs 11, % Refer 1, % Screen q 2 yrs 2, % Refer % 76+ Do not screen % Totals 21,230 2,183

29 Urology Referrals February 22, 2017 February 21, 2018 Age Group Algorithm PSAs Urology Referrals % <40 yrs Do not screen % Resume screening at 50 3, % Screen q 2yrs 1, % Refer % Screen q 2 yrs 11, % Refer 1, % Screen q 2 yrs 2, % Refer % 76+ Do not screen % Totals 21,230 2,183

30 Urology Referrals February 22, 2017 February 21, 2018 Age Group Algorithm PSAs Urology Referrals % <40 yrs Do not screen % Resume screening at 50 3, % Screen q 2yrs 1, % Refer % Screen q 2 yrs 11, % Refer 1, % Screen q 2 yrs 2, % Refer % 76+ Do not screen % Totals 21,230 2,183

31 Key Lessons Rapid uptake using Epic with algorithm embedded in health maintenance / lab results Substantial variation in practice Under and over referrals Need for efficient and effective informed decision tool

32 Decision Aid Development and pilot testing of a CDCsupported patient decision aid for prostate cancer screening. Led by John Ragsdale, MD and Sharon Hull, MD

33 Potential Approaches to Help PCP level approaches Adding Prostate Health Index (PHI) reflex Role of Digital Rectal Exams Alternative referral pathways Patient-level approaches Pre-visit video vignettes via MyChart Decision aid with visit (upcoming pilot test in 3 sites) Improved lab result messaging within Epic System-level approaches Nurse navigator (DCI-DPC liaison) Better tracking of screening to referral to scheduled appointment Multi-disciplinary quality improvement team Primary care physician participation in GU oncology tumor board

34 Chemoprevention Uptake of SERMs for chemoprevention in clinical practice Smith SG, et al. Ann Oncol, 2016

35 Precision Screening and Chemoprevention Liquid biopsy circulating cell-free DNA (cfdna) circulating tumor cells (CTC) Vockley JG and Niederhuber JE. BMJ, 2015 Meyskens FL, et al. J Natl Cancer Inst, 2016 Albini A, et al. Clin Cancer Res, 2016 Epigenetic-marker based system with detection rate of breast cancer similar to mammography Uehiro N, et al. Breast Ca Res, 2016 Cancer interception Example: ErbB2 inhibition and lapatinib Li D, et al. Oncotarget, 2017

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37 Importance of Non-Cancer Comorbidities Probability of death from breast cancer or other causes among women age 50 and older with ER+ early stage breast cancer SEER: Percent of women with early stage breast cancer and a cardiovascular risk factor SEER-Medicare: Percent Hanrahan EO, et al. J Clin Oncol, 2007 HTN Lipids DM Chen J, et al. J Am Coll Cardiol, 2012 Bradshaw PT, et al. Epidem, 2016

38 Percent of breast cancer survivors adherent to their statin therapy prior to and following early stage breast cancer diagnosis and treatment (Group Health , N=4,221 women) Percent Year - 1 Treatment period Year + 1 Year + 2 Year + 3 Calip GS, et al. Breast Cancer Res Treat, 2013 Presented by: Kevin C. Oeffinger, MD

39 Predictors of nonadherence to medications among breast cancer survivors (Group Health , N=2,308) Calip GS, et al. Breast Cancer Res Treat, 2017 Presented by: Kevin C. Oeffinger, MD

40 Importance of Non-Cancer Comorbidities Most women with breast cancer will not die of breast cancer Continued monitoring and management of common comorbidities may be as important for longevity / QoL as treatment of the breast cancer Lack of standardized approaches to manage hypertension, diabetes, and lipid disorders

41 Management of Comorbidities Hypertension (pre/during/post cancer) is a key risk factor in development of heart failure in cancer survivors treated with cardiotoxic therapy Jawa Z, et al. Medicine, 2016 Chen J, et al. J Am Coll Cardiol, 2012 Salz T, et al. J Clin Oncol, 2017 Studies pre new AHA / ACC guidelines for HTN <120 / <80 To date, no intervention studies aimed at blood pressure management during / after cancer therapy Other comorbidities associated with an increased risk of poor outcomes

42 47-year-old breast cancer survivor Diagnosed at age 42 Invasive ductal carcinoma ER- PR- HER2+ T2N1 Trastuzumab 50 Gy to Right breast /13 6/14 6/15 6/16 6/18

43 47-year-old breast cancer survivor Diagnosed at age 42 Invasive ductal carcinoma ER- PR- HER2+ T2N1 Trastuzumab 50 Gy to Right breast Lipid profile Total = 247 LDL = 188 HDL = 51 TG = year risk = 1.8% Statin therapy?

44 Chronic Cancer Patient Increasing number of patients with advanced cancer are now being treated as chronic cancer patients Management of comorbidities remains essential in this population Cure the cancer, lose the patient

45 Future Study Randomized controlled trial Population: Breast and prostate cancer patients receiving cardiotoxic therapy Primary outcome blood pressure control Intervention: automated text alert to patient and Epic message to PCP when BP is above threshold Control usual care Team: oncology, cardiology, primary care, population health science, biostatistics, onco-primary care Overarching goals: Blood pressure management and prevention of cardiotoxicity Re-engage PCPs in the care of patients on therapy

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47 Cancer Survivors in the United States There are now 14.5 million survivors in the US By 2020, there will be almost 18 million survivors De Moor JS, et al. Cancer Epidemiol Biomarkers Prev, 2013

48 Late Mortality Among 5+ Year Survivors Childhood Cancer Survivor Study (N=20,483) Causes SMR Second cancers 15.2 Cardiac 7.0 Pulmonary 8.8 Mertens AC, et al. J Natl Cancer Inst, 2009

49 Cumulative Cause-Specific Mortality Childhood Cancer Survivor Study Armstrong GT, et al. J Clin Oncol, 2009

50 Late Mortality Among 5+ Year HL Survivors MSKCC Hodgkin Lymphoma Study ( ; N=747) Matasar M, et al. J Natl Cancer Inst, 2015

51 Cumulative Incidence by Causes of Death for Patients With Stage I Testicular Seminoma SEER Registry: N=9193 men; Diagnosed Beard CJ, et al. Cancer 2013

52 Probability of death from breast cancer or other causes among women age 50 and older with ER+ early stage breast cancer SEER: Hanrahan EO, et al. J Clin Oncol, 2007

53 Cumulative incidence of chronic physical health conditions among 10,397 young adult survivors of childhood cancer Childhood Cancer Survivor Study 1 Cumulative Incidence Years since Cancer 73.4% with at least one chronic condition 42.4% with a severe or life-threatening condition or death Oeffinger KC, et al. N Engl J Med, 2006

54 To date, some studies looking at specific outcomes (SMN, cardiac) in specific cancer populations (Hodgkin lymphoma, testicular cancer) No overall estimates of morbidity U-shaped curve by age? o o o Morbidity following Adult Cancer Younger age: developing organs Mid-age: interaction of therapy with comorbid health conditions Older age: senescent organs

55 System Exposures Potential Late Effects Cardiac Pulmonary Renal/Urological Endocrine CNS Radiation therapy Anthracyclines Radiation therapy BCNU/CCNU Bleomycin Radiation therapy Platinums Ifosfamide/Cyclophos Radiation therapy Alkylating agents Radiation therapy Intrathecal chemotherapy Valvular disease Pericarditis Myocardial infarction Congestive heart failure Restrictive lung disease Exercise intolerance Atrophy or hypertrophy Renal insufficiency or failure Growth failure Pituitary, thyroid, adrenal disease Ovarian or testicular failure Delayed 2 o sex characteristics Infertility Learning disabilities Cognitive dysfunction Psychological Cancer Post-traumatic stress Employment & educational problems Insurance discrimination Adaptation/problem solving Second malignancies Radiation therapy Alkylating agents Epipodophyllotoxins Solid tumors Leukemia Lymphoma

56 Factors contributing to late effects Health Behaviors Tobacco Diet Alcohol Exercise Sun Aging Host Factors Age Gender Race Premorbid conditions Late Effect Risk Treatment Events Genetic BRCA, ATM, p53 polymorphisms Treatment Factors Tumor Factors Surgery Chemotherapy Radiation therapy Histology Site Biology Response Hudson MM. Cancer, 2005

57 Second Primary Cancer (SPC) 20% of incident cancers are a second (or subsequent) primary cancer Causal pathways: Lifestyle habits Aging Genetic factors Treatment exposures for the first cancer All of the above (interactions)

58 SPC after Breast or Colorectal Cancer Age at first cancer Risk prediction model 10-year cumulative risk of SPC Cohort of 293,435 from 12 French registries FEMALES Calendar period for first cancer First Breast Cancer 10-yr cumulative risk Difference with general population First Colorectal Cancer 10-yr cumulative risk Difference with general population yrs 6.8% +1.5% 10.0% +3.0% % +1.9% 10.7% +2.2% > % +2.0% 10.6% +1.6% Moitry M, et al. Cancer Epidemiol, 2017

59 SPC after Prostate or Colorectal Cancer Age at first cancer Risk prediction model 10-year cumulative risk of SPC Cohort of 293,435 from 12 French registries MALES Calendar period for first cancer First Prostate Cancer 10-yr cumulative risk Difference with general population First Colorectal Cancer 10-yr cumulative risk Difference with general population yrs 13.1% +5.5% 19.4% +6.3% % +5.0% 21.7% +3.1% > % +2.5% 22.1% +4.4% Moitry M, et al. Cancer Epidemiol, 2017

60 SPC in TP53 carriers NCI Li-Fraumeni Syndrome Cohort (N=286) Risk of SPC by time since first cancer and by age Mai PL, et al. Cancer, 2016

61 SPC in Mismatch Repair (MMR) genes Colon Cancer Family Registry (N=764) Cumulative risk of extracolonic cancer following CRC Win AK, et al. J Natl Cancer Inst, 2012

62 SPC following Hodgkin Lymphoma Dutch HL Cohort (N=3905) Age at HL diagnosis, Schaapveld M, et al. N Engl J Med, 2015 Van Eggermond AM, et al. Blood, 2014

63 Lung cancer after Hodgkin lymphoma Case-Control study from population-based registry Age at Hodgkin lymphoma median 50 years Relative Risk Non / Light Smoker Moderate-Heavy Smoker 0 N/N N/Alk RT/N RT/Alk Treatment Group Travis LB, et al. J Natl Cancer Inst, 2002

64 Vignette Mary presents to your office with a 2 month history of vague, non-exertional chest pain. She was treated at the age of 20 for stage IIA nodular sclerosing Hodgkin lymphoma with 21 Gy involved field radiotherapy, including the neck, mediastinum and the para-aortic nodes, and 6 cycles of ABVD. Mary s only cardiovascular risk factor is dyslipidemia. She has also been fairly sedentary. Her paternal uncle had an MI at the age of 59 yrs.

65 Vignette Mary presents to your office with a 2 month history of vague, non-exertional chest pain. She was treated at the age of 20 for stage IIA nodular sclerosing Hodgkin lymphoma with 21 Gy involved field radiotherapy, including the neck, mediastinum and the para-aortic nodes, and 6 cycles of ABVD. What is her pre-probability risk of a myocardial infarction in the next 10 years? What is the preferred next step, other than proceeding to a cardiac catheterization? Mary s only cardiovascular risk factor is dyslipidemia. She has also been fairly sedentary. Her paternal uncle had an MI at the age of 59 yrs.

66 21 Gy Irradiation to 20 year-old with Hodgkin lymphoma Courtesy of Constine LS.

67 Hodgson DC, et al. Semin Radiat Oncol 2007

68 Courtesy of Hodgson D. Involved Nodal Radiation

69 Mantle / Mediastinal Radiotherapy Men and women treated with mediastinal radiotherapy have a substantially elevated risk of coronary artery disease. 20 yrs post moderate-dose RT (37.2 Gy), actuarial risk of symptomatic CAD = 21.2% Reinders JG, et al. Radiother Oncol, 1999 By 30 yrs, incidence of MI = 12.9% Aleman BM, et al. Blood, 2007 Standardized Mortality Ratio with MI = 3.2 Swerdlow AJ, et al. JNCI, 2007

70 Cumulative incidence of coronary heart disease in HL survivors diagnosed prior to age 51 ( ) 10-yr risk = 12% By age 40, 5.5% with CHD van Nimwegen FA, et al. J Clin Oncol, 2016

71 americanheart.org

72 ClinCalc.com

73 ClinCalc.com 10-year risk = 12%

74 Need for validated CAD risk prediction models for cancer survivors 10-year risk = 10-15% Salz T, et al MSK and Danish Cancer Institute ClinCalc.com

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76 Risk-based health care of cancer survivors Monitor for recurrence of cancer Surveillance for second cancers and late effects Early diagnosis and intervention Prevention Tobacco use, physical activity, calcium intake Counseling and targeted education Oeffinger KC. Institute of Medicine, 2003 Oeffinger KC, Hudson MM. CA Cancer J Clin 54: , 2004

77 Cancer Survivors at Duke In the interval from January 1, 2016 June 30, 2017 (18 months), the following unique patients were seen by Duke oncology providers Cancer INTERVAL FROM CANCER DIAGNOSIS, YRS < Breast GI GU GYN All cancers Courtesy of Steve Power and Phillip Maxwell

78 Cancer Survivors at Duke In the interval from January 1, 2016 June 30, 2017 (18 months), the following unique patients were seen by Duke oncology providers Cancer INTERVAL FROM CANCER DIAGNOSIS, YRS With 2018 Value-Based Care, can we (DCI/DUHS) afford to continue following 7,000 individuals who are 5+ year cancer survivors? < Breast GI GU GYN All cancers Courtesy of Steve Power and Phillip Maxwell

79 Primary Care Physicians and Survivorship Systematic review of 35 articles, 10,941 PCPs 45% involved during cancer treatment 70-80% during survivorship 95% preferred a more active role across phases 50% felt unprepared to manage late effects Rarely and inconsistently received sufficient information from oncologists Lawrence RA, et al. J Gen Intern Med, 2015

80 Risk-stratified survivorship health care High risk Bone marrow transplantation High dose radiation or chemotherapy Intermediate risk Moderate dose radiation Moderate dose chemotherapy Low risk Surgery only, or Surgery with low dose chemotherapy

81 Oeffinger KC, McCabe MS. J Clin Oncol, 2005 McCabe MS, et al. Semin Oncol, 2013

82 Oeffinger KC, McCabe MS. J Clin Oncol, 2005 McCabe MS, et al. Semin Oncol, 2013

83 Moderate / Low Risk Cancer Survivors Independent Advanced Practice Provider (NP/PA) Time of transition Focus of visit Surveillance for recurrence of primary cancer Preparation of Survivorship Care Plan Evaluation for medical and psychosocial late effects Education about survivorship issues and availability of community resources Health promotion counseling Duration of care by APP Shared care with primary care provider Pilot nurse navigator embedded in primary care

84 MD-APP team Populations: High Risk Cancer Survivors Cancer survivors at high risk of a serious late effect or with persistent multi-organ toxicity Chronic cancer patients Focus of visit Surveillance for recurrence of primary cancer Screening and management of late effects Other aspects of risk-based survivorship care Duration of care Shared care with primary care provider

85 ASCO Survivorship Care Plan Template

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87 Duke Center for Onco-Primary Care Aims of Center 1. Deliver evidence-based, patient-centered, personalized health care across the cancer continuum by enhancing the interface between cancer specialists and primary care clinicians; 2. Conduct innovative research with cutting-edge technology that can be translated to the community setting; and 3. Train and educate the next generation of clinicians and researchers to extend this mission.

88 Duke Center for Onco-Primary Care Duke Cancer Institute Duke Regional and Duke Raleigh Duke Cancer Research Network (23 sites across eastern U.S.) WakeMed Washington / Fulkerson / Owens Kastan / Patierno Onco-Primary Care Team Oeffinger Corbett Ragsdale Associate Director 2 physician researchers 2 health service researchers Support staff Duke Primary Care

89 Duke Center for Onco-Primary Care External Advisory Board Patricia Ganz, MD UCLA / Johnsson Cancer Center Los Angeles, CA Ronald Kline, MD Centers for Medicare Services Washington DC Eva Grunfeld, MD, Dphil Dept of Family Medicine University of Toronto Toronto, Canada Richard Wender, MD American Cancer Society Atlanta, GA Jamie von Roen, MD American Society of Clinical Oncology Alexandria, VA Ann Partridge, MD Dana Farber Cancer Institute Boston, MA Larissa Nekhlyudov, MD Brigham & Women s Dana Farber Boston, MA Deborah Mayer, RN, PhD UNC Lineberger Cancer Center Chapel Hill, NC Wendy Demark- Wahnefried, PhD, RD UAB Cancer Center Birmingham, AL Electra Paskett, PhD Ohio State University Cancer Center Columbus, OH

90 Duke Center for Onco-Primary Care Distributed Care Model Duke Primary Care (224 primary care physicians in 34 sites across 7 counties) DCI Onco-trained primary care physician

91 Target Populations Catchment Area Patients throughout Duke University Health System (225 Primary care clinicians in 34 practice sites (rapidly expanding) 7,500 new cancer cases per year Across the Eastern seaboard through the 21-center Duke Cancer Network Via future DUHS partnerships and alliances including the expansion into Wake County and statewide. Encompassed within these clinical and research goals will be a concerted effort to reduce cancer disparities within these populations and, in partnership with other institutions, throughout North Carolina.

92 Summary Currently, there are shortcomings in our care across the cancer continuum Care will become much more complex in the next decade Need for radical practice redesign International examples: Canada (Grunfeld) Australia (Emery / Jeffords)

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94 Questions?