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How Changes in Central Cancer Registries are Impacting Cancer Research Presented by: Thomas C. Tucker, PhD, MPH Director, Kentucky Cancer Registry University of Kentucky 29th Advanced Cancer Registrars Workshop Louisville, KY– September 10-11, 2015 Kentucky Cancer Registry Topics to be covered • A very short history of the Kentucky Cancer Registry • The importance of population-based cancer research ▫ Internal Validity ▫ External validity • How population-based cancer registries can improve cancer research ▫ ▫ ▫ ▫ Providing a Population-Based Sample Frame Making Rapid Case Ascertainment Possible Serving as a Virtual Tissue Repository Measuring the last Phase of Translational Research • The Kentucky model for moving evidence-based research into the population • An example of the potential impact of implementing evidencebased research in the population The importance of population-based cancer research Two important concepts • Internal validity • External validity Animal Studies genetically Developed Did not identical mice Disease Develop Disease Exposed A B Animals Unexposed Animals C Relative Risk = (A/A+B)/(C/C+D) D Randomized Clinical Trial Random Allocation Randomized trial (Prospective) Exposure or Intervention Study Outcome Occurred A No Exposure C or Intervention Did not Occur B D Relative Risk = (A/A+B)/(C/C+D) Internal Validity • When differences between the experimental (exposed) group and the control group are completely accounted for, the study is said to have internal validity and causal inferences can be made. • In other words, it is possible to determine whether the exposure causes some outcome (disease, etc.). • Many have argued that “randomization” was the most important scientific advance of the 20th century. • Why is it that the findings from randomized clinical trials with internal validity almost never have the same effect when they are applied to general populations? External Validity • When the findings from a research project or study can be generalized to some defined population, they are said to have external validity. • Epidemiology (population science) provides the tools to explore external validity and many argue that moving from studies with strong internal validity to studies with strong external validity is the next step in advancing our scientific understanding. • The continuum from research with strong internal validity to studies with strong external validity is also part of “Translational Research”. Population-based Central Cancer Registries Can Enhance Cancer Research in Several Important Ways. 1. As a Population-Based Sample Frame Geographic Area Covered by the Population-Based Cancer Registry Cancer cases occurring each year Cancer research with strong “external validity” Information gathered on each cancer case (the ability to generalize the findings to the underlying population) The Population-Based Cancer Registry A scientific sample of data from cancer patients representing the population covered by the registry is provided to the researcher Intimate Partner Violence and Cancer Disparities A novel population-based cohort study • Research Question: Is IPV associated with delayed screening, late stage Dx or poor survival among women diagnosed with breast, colorectal or cervical cancer in Kentucky? • Design: Population-based prospective cohort study • Methods: KCR recruitment • Population-based Sample: n=1,850 • Results: IPV (37% lifetime) Partner Interference (13%) Indirect Pathway IPV & Partner Interference with Cancer Treatment Poverty, Risk behaviors, Access to care, Low education, Co-morbidity Direct Pathway Later Stage at Diagnosis Suboptimal Treatment Poorer Quality of Life Poorer Survival 2. For Rapid Case Ascertainment Geographic Area Covered by the Population-Based Cancer Registry Cancer research with strong “external validity” Pathology Labs (the ability to generalize the findings to the underlying population) Electronic Path (EPath) Reports for Cancer Patients Sent Automatically at the Time of Diagnosis Biospecimens collected The Population-Based Cancer Registry Receives EPath Reports for 95% of All New Cancer Cases Diagnoses each Year A population-based sample of cancer cases provided to the researcher High Arsenic, Chromium and Radon Levels and High Lung Cancer Rates in Appalachian Kentucky (Top) Arsenic content and coal field locations in Kentucky; (Bottom) Incidence of lung cancer in the Appalachian versus Non-Appalachian region of Kentucky. Environmental Exposure and Lung Cancer A population-based lung cancer case-control study By Drs. Arnold, Orren, Mellon, and Huang Lung Cancer Rate per 100,000 Arsenic PPM 0-100 57 – 95 100-250 96 – 102 250-2200 103 – 116 117 – 150 Appalachia Study Area Epi, Blood, Urine, Hair, Toenails, Radon level, Tap water, Soil, GPS Hypothesis: Lung cancer incidence is higher than expected from smoking alone and is associated with exposure to environmental carcinogens Environmental Exposure and Lung Cancer A population-based lung cancer case-control study By Drs. Arnold, Orren, Mellon, and Huang Live lymphocytes 3. As a Population-Based Virtual Tissue Repository Geographic Area Covered by the Population-Based Cancer Registry Cancer research with strong Pathology Labs “external validity” (the ability to generalize the findings to the underlying population) The Population-Based Cancer Registry Formalin fixed paraffin imbedded tissue samples are collected from the labs by the Registry for a populationbased sample of cases A population-based sample of cancer case data and tissue are provided to the researcher 1. A retrospective cohort study using the registry as a virtual tissue repository to explore 5 distinct proteins associated with breast cancer recurrence Purpose of the Study Determine whether female breast cancer patients who were disease-free following surgery but subsequently had a recurrence of their breast cancer within five years had altered levels or activity of one or any combination of five proteins compared to women who were diseasefree and did not have a recurrence. The Five Proteins • Par-4: pro-apoptotic tumor suppressor protein downregulated during breast cancer recurrence • Wnt/b-catenin: signaling pathway induces epithelial-mesenchymal transition (EMT) and promotes metastasis • SNAIL, TWIST: transcription factors, promote EMT promote cancer progression (metastasis) elevated in metastatic and recurrent tumors • c-Abl, Arg: tyrosine kinases, oncoproteins promote survival, proliferation, and metastasis activity levels measured by pCrkL activity A Retrospective Cohort Study 2000-2007 Using the Registry, all female breast cancer patients treated surgically between 2000 and 2007 at UK for their 1st Ca. and determined to be disease free were identified. Tissue blocks from the initial surgery were obtained for all of these patients, TMAs were constructed and stained to determine activity levels for each protein. This cohort was then traced forward in time to determine which patients recurred and which did not. (479 patients met the study criteria). 2012 Comparisons were made between activity levels of each protein among the primary tumors of recurrent patients (62) and the non-recurrent patients (417). For patients that recurred, comparisons were made between the tumor tissue at first surgery (the primary tumor) and the tissue taken at the time of recurrence. Tissue at the time of recurrence was only available for 22 patients. Did Not Recur Identify the study Population Recurred Tissue at the time of recurrence Preliminary Results PROTEIN EXPRESSION IN PRIMARY TUMORS FROM RECURRENT VS. NON-RECURRENT PATIENTS TWIST SNAIL Intensity Allred Score Intensity X Percent HER2+ (n=36) HER2-/ER+/PR+ (n=282) HER2-/ER-/PR+ (n=32) HER2-/ER-/PR- (n=75) HER2+ HER2-/ER+/PR+ HER2-/ER-/PR+ HER2-/ER-/PRHER2+ HER2-/ER+/PR+ HER2-/ER-/PR+ HER2-/ER-/PR- PAR4 b-catenin pCrkL H L H L H L H: Significantly high in the primary tumor of recurrent patients L: Significantly low in the primary tumor of recurrent patients Preliminary Results PROTEIN EXPRESSION IN RECURRENT VS. PRIMARY TUMORS TWIST SNAIL PAR4 b-CATENIN Intensity Allred Score Intensity x Percentage pCrkL H H H H: Significantly high at the time of recurrence in the tissue sample of patient who recurred compared to their primary tumors ● ● ● ● ● ● ● Preliminary Results ● ● ● ● ● 2 ● 2 ● Beta_allred 4 PAR4_allred 4 ●●● ● ●● ● ● ● 0 0 pCrkL EXPRESSION IN RECURRENT VS. Primary Recurrent PRIMARY TUMORS ● ●● ● Primary Paired Wilcoxon S 8 8 Paired t−test P = 0.013 Wilcoxon Signed Rank P = 0.02 ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●●●●● ●●●●●● ● Primary ● ● ●●● Recurrent ● 0 0 PCrkl_Cyt_allred 2 4 6 ● PCrkl_Nuc_allred 2 4 6 ●● ● ● ● ● ● ● ●●● ● ●● ● ● ● ● ●● ● Primary Conclusions • Elevated levels of Twist, and low or not activated c-Abl/Arg (pCrkL) in HER2-/ER+/PR+ breast tumors may potentially serve as a novel biomarker for the recurrence of breast cancer. • c-Abl/Arg was activated and over expressed in the tumors of patients at the time of recurrence. Inhibiting c-Abl/Arg activation may potentially prevent recurrence. • It is difficult to imagine doing this study without using the Cancer Registry as a virtual tissue repository. 2. Pre-Invasive Cervical Cancer HPV Genotyping Study: Research Questions • Are the HPV genotypes different for non-Appalachian white women diagnosed with pre-invasive cervical cancer (CIN-3) compared to Appalachian white women? • Are the HPV genotypes different for non-Appalachian white women diagnosed with pre-invasive cervical cancer (CIN-3) compared to non-Appalachian black women? • Are the HPV genotypes different for white women diagnosed with CIN-3 compared to white women diagnosed with AIS? Study Population • All Kentucky women age 18 or older diagnosed with CIN-3 or AIS between January 1, 2009 and December 31, 2012 were available for this study. • The cases were divided into four strata (non-Appalachian white women, non-Appalachian black women, Appalachian white women and AIS cases). • A total of 4903 pre-invasive cervical cancer cases fell into one of these strata. • 3099 were non-Appalachian white women diagnosed with CIN-3. • 290 were non-Appalachian black women diagnosed with CIN-3. • 1360 were Appalachian white women diagnosed with CIN-3. • 154 were white women diagnosed with AIS. • The recruitment goal was to obtain tissue specimens from a random sample of 150 cases in each strata (for a total of 600 cases). A random sample of 200 cases was drawn from each strata except AIS to allow replacement for cases for which tissue could not be obtained. Study Procedures • The Kentucky Cancer Registry (KCR) served as the “Honest Broker” for this study. • KCR solicited the required tissue blocks from each of 48 the labs where the tissue was stored. • Tissue blocks were sent directly to KCR, the blocks were anonymized and given a unique code. • The coded blocks were cut by the Markey Cancer Center, Biospecimens and Tissue Procurement Research Lab and the tissue specimens sent to CDC for genotyping. • The original blocks were returned to the contributing lab by KCR. • All of the HPV genotyping was done at CDC. • The HPV genotype or types for each specimen and the associated unique code were then returned to KCR and linked with other data in the preinvasive cervical cancer surveillance database to create a research data set. Pre-Invasive Cervical Cancer HPV Genotyping Study: # and % of Cases Currently Available for Analysis Groupings Available for study Frequency + (% of 421) 421 (100%) Appalachian white 121 (28.7%) Non-Appal white 113 (26.8%) Non-Appal black 105 (24.9%) AIS white 82(19.5%) Pre-Invasive Cervical Cancer HPV Genotyping Study: Research Question 1 Are HPV genotypes different for Appalachian white vs non-Appalachian white females? HPV Genotype Any oncogenic HPV except 16 & 18 Region % with genotype p-value Appalachian 22% 0.0588 Non-Appalachian 34% Pre-Invasive Cervical Cancer HPV Genotyping Study: Research Question 2 Are HPV genotypes different for non-Appalachian white vs non-Appalachian black females? HPV Genotype RACE % with genotype p-value 16 (alone or with any other HPV) White 61.1% 0.0208 Black White Black White Black 44.8% 46.9% 29.5% 2.7% 13.3% Any oncogenic HPV White Black White 1.8% 9.5% 33.6% except 16 & 18 Black 46.7% 16 alone 35 (alone or with any other HPV) 35 alone 0.0120 0.0043 0.0158 0.0539 Pre-Invasive Cervical Cancer HPV Genotyping Study: Research Question 3 Are HPV genotypes different for white females with CIN-3 vs white females with AIS? HPV Genotype 18 (alone or with any other HPV) 18 alone 31 (alone or with any other HPV) 31 alone 52 (alone or with any other HPV) 52 alone 33 (alone or with any other HPV) CIN-3 Vs. AIS CIN-3 AIS CIN-3 AIS CIN-3 AIS CIN-3 AIS CIN-3 AIS CIN-3 AIS CIN-3 AIS % with genotype 3.0% 39.0% 1.7% 32.9% 10.3% 0.0% 7.3% 0.0% 6.8% 1.2% 3.4% 0.0% 0.0% 4.3% p-value <0.0001 <0.0001 0.001 0.0084 0.0829 0.1177 0.0689 Preliminary Conclusions • HPV oncogenic types other than 16 and 18 were more common among non-Appalachian white women diagnosed with CIN-3 compared to Appalachian white women • HPV 16 alone or with any other HPV type was more common among white women diagnosed with CIN-3 compared to black women. • HPV 35 alone or with any other HPV type was more common among black women diagnosed with CIN-3 compared to white women. • HPV 18 alone or with any other HPV type was more common among white women diagnosed with AIS compared to white women diagnosed with CIN-3. The final step in translational research is the broad based implementation of cancer research findings in the genral population and measuring the impact of these interventions. From the Laboratory to the Population Genes Cells Animals Basic Science Humans Clinical Science Translational Research Populations Epidemiology EXAMPLE Quercitrin, a natural product from apple peel, is tested in an animal model to determine if it prevents UV exposure induced skin cancer Randomized trials in human populations Broad application of the findings to the general population From the Population to the Laboratory And back again Genes Cells Animals Basic Science Humans Clinical Science Translational Research Populations Epidemiology Example Cell line and animal studies are conducted to determine if exposure to arsenic and chromium contributes to the onset of colon cancer. Epidemiologic studies show that colorectal cancer is excessively high in the Appalachian area of Kentucky and this same population has high exposure to arsenic and chromium. Example Cell line and animal studies are conducted to determine if exposure to arsenic and chromium contributes to the onset of colon cancer. Human trials Epidemiologic studies show that colorectal cancer is excessively high in the Appalachian area of Kentucky and this same population has high exposure to arsenic and chromium. From the Laboratory or the Population Genes Cells Animals Basic Science Humans Clinical Science Translational Research Populations Epidemiology The ultimate goal of translational cancer research is the adoption and wide-spread use of evidencebased research findings that significantly reduce the cancer burden in the population. This includes the wide-spread implementation of evidence-based cancer control interventions. The Kentucky Model for Moving Evidence-based Cancer Research Findings into to the Population Kentucky Cancer Consortium (KCC) Kentucky Cancer Program (KCP) Lung Cancer by Area Development District in KY, 2005-2009 High School Current Age- Age- Education 2006Smokers Adjusted Kentucky Cancer Registry (KCR)Adjusted 2010 2001-2005 Incidence Mortality Area Development District Kentucky River Big Sandy Cumberland Valley Gateway Buffalo Trace Barren River Lake Cumberland Fivco Green River Pennyrile Lincoln Trail Purchase Northern Kentucky Kipda Bluegrass Percent Rank 65.6 69.0 67.8 73.7 73.3 78.6 70.9 78.2 83.0 80.1 82.7 83.0 86.4 86.4 84.7 1 3 2 6 5 8 4 7 11 9 10 12 15 14 13 Overall Rank Percent Rank Rate Rank Rate Rank 35.7 35.5 35.5 32.0 33.0 31.8 31.1 32.5 30.3 31.3 31.1 28.5 29.0 28.6 28.2 1 2 3 6 4 7 10 5 11 8 9 14 12 13 15 124.7 131.7 117.2 102.1 96.9 105.8 101.2 99.9 105.0 97.2 96.3 97.7 96.2 94.9 92.6 2 1 3 6 11 4 7 8 5 10 12 9 13 14 15 99.8 96.2 86.0 79.9 78.3 78.0 77.7 71.0 76.1 70.1 66.4 69.4 71.4 66.6 68.0 1 2 3 4 5 6 7 10 8 11 15 12 9 14 13 5 8 11 22 25 25 28 30 35 38 46 47 49 55 56 Source: Kentucky Cancer Registry (KCR) Source: Kentucky Cancer Registry (KCR) Combining Data from Multiple Sources Demographic Characteristics Contribute to Risk Factors Contribute to Incidence and Late Stage DX Contribute to Cancer Mortality Logic Model What are the common sources of data that can be used for defining the cancer burden? • • • • Demographic data (Census U.S) Risk factor data (BRFSS) Incidence data (KCR) Mortality data (State Vital Records) Lung Cancer by Area Development District in KY, 2006-2010 Area Development District U.S. Kentucky Barren River Big Sandy Bluegrass Buffalo Trace Cumberland Valley Fivco Gateway Green River Kentucky River Kipda Lake Cumberland Lincoln Trail Northern Kentucky Pennyrile Purchase High Poverty School Rate (%) Education 2006(%) 2010 2006-2010 Age-Adjusted Age-Adjusted Smoking Incidence Late Stage Mortality Rate (%) Incidence 2001% Number Rate Number Rate 2005 87.6 81.0 78.6 69.0 84.7 73.3 15.1 17.4 19.1 25.2 16.9 22.4 19.96 30.4 31.8 35.5 28.2 33.0 292,495 23077 1569 1155 3449 321 67.0 100.5 105.8 131.7 92.6 96.9 79.7 80.7 83.1 82.9 81.1 80.5 229,103 16701 1148 835 2510 256 52.5 73.2 78.0 96.2 68.0 78.3 67.8 28.7 35.5 1590 117.2 81.6 1153 86.0 78.2 73.7 83.0 65.6 86.4 19.5 25.2 15.5 29.2 14.3 32.5 32.0 30.3 35.7 28.6 866 442 1284 840 4602 99.9 102.1 105.0 124.7 94.9 79.1 79.5 80.2 84.4 77.9 613 342 933 658 3223 71.0 79.9 76.1 99.8 66.6 70.9 24.3 31.1 1295 101.2 80.2 992 77.7 82.7 14.8 31.1 1291 96.3 79.8 873 66.4 86.4 11.4 29.0 1921 96.2 80.8 1413 71.4 80.1 83.0 18.5 16.3 31.3 28.5 1220 1232 97.2 97.7 83.5 81.2 873 879 70.1 69.4 High School Education (2006-2010) vs Smoking Rate (2001-2005) 40 High School Education vs Smoking Rate in 2001-2005 Linear (High School Education vs Smoking Rate in 2001-… Percent Smoker R² = 0.8204 35 30 25 65 70 75 80 Percent High School Education 85 90 Smoking (2001-2005) vs Lung Cancer Incidence (2006-2010) 140 Smoking (2001-2005) vs Lung Cancer Incidence 130 Lung Cancer Incidence R² = 0.7015 120 110 100 90 27 28 29 30 31 32 33 Percent Smoker (2001-2005) 34 35 36 37 Lung Cancer Incidence vs Mortality (2006-2010) 105 Lung Cancer Incidence versus Mortality Linear (Lung Cancer Incidence versus… 100 R² = 0.8795 Mortality Rate 95 90 85 80 75 70 65 90 100 110 Lung Cancer Incidence 120 130 Lung Cancer by Area Development District in KY, 2006-2010 Area Development District High School Education, 2006-2010 Current Smoker, 2001-2005 AgeAdjusted Incidence AgeAdjusted Mortality Overall Rank Percent Rank Percent Rank Rate Rank Rate Rank Kentucky River 65.6 1 35.7 1 124.7 2 99.8 1 5 Big Sandy Cumberland Valley Gateway 69.0 3 35.5 2 131.7 1 96.2 2 8 67.8 2 35.5 3 117.2 3 86.0 3 11 73.7 6 32.0 6 102.1 6 79.9 4 22 Buffalo Trace 73.3 5 33.0 4 96.9 11 78.3 5 25 Barren River 78.6 8 31.8 7 105.8 4 78.0 6 25 Lake Cumberland 70.9 4 31.1 10 101.2 7 77.7 7 28 Fivco 78.2 7 32.5 5 99.9 8 71.0 10 30 Green River 83.0 11 30.3 11 105.0 5 76.1 8 35 Pennyrile 80.1 9 31.3 8 97.2 10 70.1 11 38 Lincoln Trail 82.7 10 31.1 9 96.3 12 66.4 15 46 Purchase Northern Kentucky Kipda 83.0 12 28.5 14 97.7 9 69.4 12 47 86.4 15 29.0 12 96.2 13 71.4 9 49 86.4 14 28.6 13 94.9 14 66.6 14 55 Bluegrass 84.7 13 28.2 15 92.6 15 68.0 13 56 An Example In 2001, Kentucky had the highest colorectal cancer incidence rate in the U.S. compared to all of the other states In 2001, it was also noted that Kentucky was ranked 49th in colorectal cancer screening compared to all other states with the second to the lowest rate (34.7% of the age eligible population). Using the process previously described, data about the burden of colorectal cancer was assembled and presented to each of the 15 District Cancer Councils. Following these presentations, all 15 of the District Cancer Councils implemented evidence based cancer control intervention programs aimed at increasing colorectal cancer screening for age eligible people living in their District. What happened following the implementation of these colorectal cancer screening programs? Colorectal Cancer Screening in Kentucky 70% 65% 63.70% 63.70% 2008 23rd 2010 65.70% 58.60% 60% 55% 47.20% 50% 43.90% 45% 40% 34.70% 35% 30% 2000 49th 2002 2004 2006 Source: http://cdc.gov/brfss accessed August 2014 2012 Kentucky Colorectal Cancer Incidence (1999-2011) 70 68 66 68.2 68.8 66.7 65.4 65.2 64.2 64 Rate 62 60 58 61.2 59.3 59.5 58.1 57.2 56 54.4 54 52.5 52 50 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 Year P<.05 Source: http://cancer-rates.info/ky, Accessed January 2014 Kentucky Colorectal Cancer Mortality (1999-2011) 25 24.2 23.6 24 23 22.6 22.5 23.0 22 Rate 21 20 19 20.5 20.5 19.6 20.6 19.1 19.0 18 17.5 17.4 17 16 15 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 Year P<.05 Source: http://cancer-rates.info/ky, Accessed January 2014 A 24% reduction in colorectal cancer incidence and a 28% reduction in colorectal cancer mortality is a significant public health success. It is important to note that we would not have seen this problem without data from our population-based Cancer Registry and we could not have measured the impact of our interventions without data from our population-based Cancer Registry Kentucky Cancer Registry Thank You! Questions?