At the Heart of the Matter: Predicting Cardiovascular Risk in Childhood Cancer Survivors

Transcription

1 At the Heart of the Matter: Predicting Cardiovascular Risk in Childhood Cancer Survivors Eric Chow, MD, MPH Seattle Children s Cancer Survivor Program University of Washington

2 Disclosures Off label use: Dexrazoxane US Food/Drug Administration approved for breast cancer patients receiving high-dose anthracyclines No other relevant disclosures/conflicts

3 Northernmost major metro area in US, further north than Toronto! A slightly more affordable Vancouver Mt. Rainier = 14k ft Last major eruption ~5k yrs ago, buried much of modern day Puget Sound REI & Amazon HQs Tom Hanks & Meg Ryan s boathouse

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5 Cardiovascular disease after cancer Chapter 1: What is the problem? Chapter 2: Who will develop it? Chapter 3: Can we prevent it? Jacket design, Bryan Coffelt

6 Chapter 1: Discover & Describe UT Austin 1829 map Geocurrents.info Herodotus map

7 Heart disease after cancer therapy Childhood cancers, >80% 5-year survival >400,000 survivors in US Oeffinger, NEJM 2006 Reulen, JAMA 2010

8 Pathogenesis Host Factors Environment Genetics Treatment Factors Radiotherapy Chemotherapy Surgery Obesity Hypertension Dyslipidemia Insulin resistance [Metabolic syndrome] Cardiomyopathy Fibrosis Cardiovascular Disease

9 Radiation & Anthracycline Chemotherapy Is there a low dose safe threshold? May not be known until survivors reach old age. Mulrooney, BMJ 2009 van der Pal, Eur J Ca 2006

10 Role of Genetics? Anthracycline cardiomyopathy UGT1A6 Secondary metabolism glucuronodation Wang, JCO 2016 Aminkeng, Nat Genet 2015 Armenian, Br J Hem 2013 Blanco, JCO 2012 Leger, BBMT 2016 Lipshultz, Cancer 2013 Rajic, Leuk Lymphoma 2009 Rossi, Leukemia 2009 Visscher, JCO 2012 & PBC 2013 Wang, JCO 2014 Wojnowski, Circulation 2005 Armenian, Br J Hem 2013 Lipshultz, Cancer 2013 Rajic, Leuk Lymphoma 2009 Rossi, Leukemia 2009 Visscher, Ped Blood Ca 2013 Wang, JCO 2014 Wojnowski, Circulation 2005

11 Prevalence of CV risk factors among childhood cancer survivors over time A = hypertension, B = dyslipidemia, C = diabetes, D = obesity (Armstrong, JCO 2013)

12 Childhood Survivors are Insulin Resistant Insulin Resistance (M-lbm) Siblings (n=208) All survivors (n=319) Leukemia (n=110) CNS (n=82) Solid tumors (n=127) Mean age = 14.5 yrs (range 9-18) Major treatment risk factors: TBI, cranial XRT + platinum, steroids w/o platinum/crt Steinberger, J Peds 2011; Baker, CEBP 2013

13 Study Outcomes Seattle/Vanderbilt ALL survivors: 1 st remission 10% cranial RT Chemo vs. BMT Chemo n=48 All TBI-exposed Off GVHD meds Median age 15 years (8-21) and 9 yrs (3-19) since diagnosis BMT n=26 Overweight (BMI), % Waist to hip ratio, mean ± SD 0.83 ± ± 0.07 <0.01 BP 120/80 mmhg or 90 th % Insulin resistance, median (range) 1.3 (0.1, 5.5) 2.6 (0.2, 10.8) <0.01 Triglyceride, median (range) 63 (16, 177) 127 (63, 327) <0.01 HDL, median (range) 54 (33, 108) 45 (32, 63) < traits, % <0.01 P Family history & 2 traits: OR ~4 BBMT 2010

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15 Chapter 2: Towards a better understanding Risk Prediction? NASA, Wikipedia Tischkoff S, Science 2009

16 Risk Prediction General population CV risk estimators likely inadequate Need to incorporate unique cancer survivor specific factors Most oncology screening guidelines consensus based Create data-driven individual-level prediction to guide more targeted screening, interventions Need large dataset to develop prediction models External validation?

17 Example 20-year old man, non-smoker, not on medications with total cholesterol 257, HDL cholesterol 41, systolic blood pressure 115 Standard population predictor -> 1% risk of heart attack in 10 yrs; 1-5% risk of any heart disease in 30 yrs But what if this person also had relapsed leukemia, and received 2 transplants, and doxorubicin chemotherapy plus total body irradiation? Are the above risk still accurate? Probably not.

18 Childhood Cancer Survivor Study 31 pediatric North American centers contributed to form a cohort of >24,000 5-year survivors of childhood cancer treated from (plus ~5,000 siblings). US NIH-supported resource study Cohort has been prospectively followed since

19 Risk Prediction Childhood Cancer Survivor Study Cardiomyopathy/CHF, ischemic heart disease, stroke Limit to CTCAE Grade 3+ (self-reported conditions with medication corroboration; death records) Predict individual risk by age 40 to 50 Inputs (readily available) Sex, diagnosis age Chemo: anthracycline, alkylator, platinum, vinca XRT: brain, neck, chest, abdomen Area under the curve (AUC) at 40y Concordance (C) statistic thru 40y Chance = 0.5

20 Heart Radiation Dose, Gy Risk Prediction Model Simple Standard Heart Treatment exposure information Yes/No only Chemo dose, clinical XRT dose Chemo dose, heart XRT dosimetry r = 0.84 Chest Radiation Dose, Gy Courtesy of M. Stovall, MDACC

21 Risk Prediction (CHF) Training Validation No. cases thru age 40 Ascertainment Simple Standard Heart CCSS N=13, centers, Netherlands N=1,362 Single center, Nat l Wilms N=6,760 Clinical trials group, St. Jude N=1,695 Single center, Self-report + medications, death records Medical & death records, some clinical assessment Medical & death records; self-report + medications Medical & death records, some clinical assessment JCO 2014

22 Risk Prediction (CHF) Training Validation No. cases thru age 40 Ascertainment CCSS N=13, centers, Netherlands N=1,362 Single center, Nat l Wilms N=6,760 Clinical trials group, St. Jude N=1,695 Single center, Self-report + medications, death records Simple Standard Heart Medical & death records, some clinical assessment Medical & death records; self-report + medications Medical & death records, some clinical assessment JCO 2014

23 Risk Prediction (CHF) Training Validation No. cases thru age 40 Ascertainment CCSS N=13, centers, Netherlands N=1,362 Single center, Nat l Wilms N=6,760 Clinical trials group, St. Jude N=1,695 Single center, Self-report + medications, death records Medical & death records, some clinical assessment Medical & death records; self-report + medications Medical & death records, some clinical assessment Simple Standard Heart JCO 2014

24 Risk Prediction (CHF) Gender Diagnosis age, yrs Characteristic Male Female < , 15 Anthracycline, mg/m Risk Score year-old girl [1 pt] diagnosed with ALL at age 3 [2 pts], who received 150 mg/m 2 of anthracyclines [3 pts], alkylators, and vinca alkaloids, but no radiotherapy. Total = 6 pts (Standard Model) Chest radiation, Gy <5 5-14, JCO 2014

25 Risk Prediction (CHF) Risk Group Risk Score Cumulative Incidence at 40yrs, % (95% CI) Relative Risk vs. siblings [vs. group above] Low <3 0.5 ( ) 1.8* [ - ] Moderate ( ) 12.1 [6.6 ] High ( ) 41.5 [3.4 ] *p=0.11 p<0.01 JCO 2014

26 JCO 2014

27 Online risk calculator: ccss.stjude.org/chfcalc

28 Risk Prediction: Other Outcomes Heart Failure Ischemic Heart Disease Stroke No. events (Grades 3-5) Model Inputs Cross-validated AUC / C-index 248 Sex Dx age Anthra ChestRT BrainRT Alkylator 0.74 / 0.76 (age 40) External validation JCO 2014 Manuscript in preparation

29 Risk Prediction: Other Outcomes Heart Failure Ischemic Heart Disease Stroke No. events (Grades 3-5) Model Inputs Sex Dx age Anthra ChestRT BrainRT Alkylator Sex Dx age Anthra ChestRT BrainRT Alkylator Sex Dx age Anthra ChestRT BrainRT Alkylator Cross-validated AUC / C-index 0.74 / 0.76 (age 40) 0.70 / 0.70 (age 50) 0.63 / 0.66 (age 50) External validation JCO 2014 St Jude 0.67 / 0.66 St Jude 0.68 / 0.71 Dutch 0.72 / 0.72 Manuscript in preparation

30 Cardiovascular Disease Risk Prediction 20-year old man, non-smoker, not on medications with total cholesterol 257, HDL cholesterol 41, systolic blood pressure 115 Standard population predictor -> 1% risk of heart attack in 10 yrs; 1-5% risk of any heart disease in 30 yrs After factoring cancer treatment exposures (total body irradiation, doxorubicin): Survivor specific predictor: 12% risk of heart attack and/or heart failure based on cancer treatments alone by age 50 (not even factoring in high cholesterol)

31 Risk Prediction: Role of conventional CV conditions? Characteristic CHF Male Female 1 Anthracycline 3 Ischemic Heart Chest XRT 3 3 Neck XRT 1 Stroke 1 1 Brain XRT 3 AUC/C-index

32 Risk Prediction: Role of conventional CV conditions? Characteristic CHF Male Female 1 Anthracycline 3 Ischemic Heart Chest XRT 3 3 Neck XRT 1 Stroke 1 1 Brain XRT 3 AUC/C-index Obesity Diabetes 2 Dyslipidemia Hypertension AUC/C-index These factors are important, and may improve prediction, at least slightly Influence limited by relative rarity among young adults (age 26) & when restricted to those on medications only

33 Risk Prediction: Summary Engage large cohorts to develop validated risk models among childhood cancer survivors Similar efforts among adult cancer survivors Ezaz G, Risk prediction for heart failure after trastuzumab for breast cancer, J Am Heart Assoc 2014 Next steps: Can these tools improve positive and negative predictive values of screening? Better identify high risk survivors who might benefit more from risk factor reduction?

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35 Cardiovascular disease after cancer Chapter 1: What is the problem? Chapter 2: Who will develop it? Chapter 3: Can we prevent it? Jacket design, Bryan Coffelt

36 Interventions: Cardiomyopathy Example Better risk prediction? Efficacy of dexrazoxane? Armenian, Gelehrter, Chow: Cardiol Res Pract 2012

37 Primary Prevention: Dexrazoxane Iron chelator Bisdioxopiperazine intracellular iron chelation decreases oxygen free radicals May have other effects as well weak topoisomerase inhibitor Reduces anthracycline-associated myocyte death in vitro FDA: women w/ metastatic breast cancer, doxorubicin dose 300 mg/m2 ASCO: Consider in adults, 300 mg/m2 (Hensley, 2008) Data very limited in pediatrics & usage remains low

38 Dexrazoxane & heart failure Less frequent troponin elevations among pediatric ALL patients Less pathologic ventricular remodeling at 5-yrs Increased risk of 2 nd cancers? van Dalen, Cochrane Rev 2008 Liphsultz, NEJM 2004 & Lancet Oncol 2010

39 ALTE11C2 Long-term cardiac assessment of COG patients previously treated on dexrazoxane randomized trials One-time assessment of cardiac function: standard echocardiogram blood biomarkers 6 minute walk questionnaires updated health status (late relapse/2 nd cancers)

40 Participating COG Sites Thank you CHEO, McMaster!

41 Preliminary Results COG data plus National Death Index overall mortality (HR 1.03) relapse (HR 0.81) 2 nd cancer deaths (HR 1.25), including AML (HR 1.39) No difference DRZ+ vs. DRZ- Measurements DRZ+ DRZ- N=41 N=33 P Overweight/obese, % Prehypertensive/hypertensive, % Lipid abnormality, % Pre-diabetic/diabetic, % Left ventricular systolic function Shortening fraction, mean±sd 35±5 32± Thickness-dimension ratio, mean±sd 0.18± ± JCO 2015 Preliminary

42 Interventions: Cardiomyopathy Example Better risk prediction? Exercise? Nutrition? Improve CV control? Efficacy of dexrazoxane? ALTE1621 (PREVENT-CHF) Armenian, Gelehrter, Chow: Cardiol Res Pract 2012

43 Lifestyle Interventions CCSS Exercise & Quality Diet After Leukemia (EQUAL) Study Adult-aged overwgt or obese ALL survivors 2yr RCT with web-based individual health coach focused on exercise & wgt loss (Healthways at Hopkins) PI: Emily Tonorezos (MSKCC) COG ALTE1631 School age ALL survivors, 3mo after EOT, who are inactive 6 month RCT with wearable activity monitor & interactive website Goal: improve fitness (6MWT) and assess effects on QoL and biomarkers of CV health PI: Kiri Ness (St Jude)

44 Lifestyle Interventions Teen survivors Exercise RCT Fitbit plus Facebook peer support group (n=30) Attention controls (n=30) (NCT ) PI: J. Mendoza (St. Baldrick s)

45 Young adult childhood cancer survivors have high burden of CV conditions Dexrazoxane study data (n=74) Measurements DRZ+ DRZ- N=41 N=33 P Overweight/obese, % Prehypertensive/hypertensive, % Lipid abnormality, % Pre-diabetic/diabetic, % Childhood Cancer Survivor Study Home Sample (n=175) Undertreated & underdiagnosed CV conditions common

46 Risk of undertreatment? CCSS data self-reported hypertension medication use Ischemic heart disease, RR Heart failure, RR RT- Htn- (ref) RT+ Htn- RT- Htn+ RT+ Htn+ Ant- Htn- (ref) Ant+ Htn- Ant- Htn+ Ant+ Htn+ CV risk factors may act synergistically with treatment exposures Armstrong, JCO 2013

47 Risk of undertreatment? BMT survivors: lab values at 1 year & subsequent CV disease What remains unknown is whether improved control will actually reduce risk? BBMT 2014

48 Cardiovascular disease after cancer Chapter 1: What is the problem? Toxicity of new agents, genetics? Chapter 2: Who will develop it? Incorporate genetics, other biomarkers as part of prediction? Chapter 3: Can we prevent it? DRZ as primary prevention? Alternative anthracyclines? Pharmacologic secondary prevention? Can improved control of CV traits and lifestyle factors make a significant longterm difference? Jacket design, Bryan Coffelt

49 At the Heart of the Matter: Predicting, Preventing, and Treating Cardiovascular Disease in Childhood Cancer Survivors June 13, 2021

50 Acknowledgements (it takes a village) Seattle Scott Baker Irv Bernstein Nancy Blythe Norm Breslow Doug Hawkins Stephanie Lee Beth Mueller John Hansen Kara Haugen Wendy Leisenring Paul Martin Jason Mendoza Jeannine McCune Cate Pihoker Christian Roth Jean Sanders Karen Syrjala Lue Ping Zhao CCSS Les Robison Yutaka Yasui Chuck Sklar Greg Armstrong Yan Chen Lieke Feijen Leontien Kremer Lillian Meacham Paul Nathan Kiri Ness Kevin Oeffinger COG Saro Armenian Barabara Asselin Smita Bhatia Debra Friedman Melissa Hudson Lisa Kopp Steve Lipshultz Cindy Schwartz Lynda Vrooman Funding NCI K07, R03, P30, U24 ASBMT ASCO / Livestrong Hyundai Hope on Wheels Leukemia & Lymphoma Society Rally Foundation Seattle Children s Res. Institute St. Baldrick s Foundation And especially all the patients and families!

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