Impact and implications of Cancer Death Status Reporting Delay on Population- Based Relative Survival Analysis with Presumed-Alive Assumption X Dong, Y Ren, R Wilson, and K Zhang NAACCR 6-20-2017
Introduction Population-based survival analysis is a core application of cancer surveillance data to better understand the impact of cancer epidemic Relative survival methodology is becoming the default method for population-based cancer survival analysis Because of the difficulties to ascertain up-to-date dates of last contact for some cancer patients, presumed-alive assumption is adopted to facilitate the analysis of some cancer surveillance data RELIABLE TRUSTED SCIENTIFIC DCPC
Introduction Date of diagnosis, date of last contact and vital status determine cancer survival estimation Reporting issues may contribute biases into cancer survival estimates Incidence case Date of diagnosis Date of last contact Vital status RELIABLE TRUSTED SCIENTIFIC DCPC
Introduction Incidence reporting delay The cases are reported outside designated reporting window and are not known to the current study Our study reported in 2016 NAACCR conference demonstrated the possible incidence reporting delay induced underestimation biases in population-based cancer survival with presumed alive assumption Date of diagnosis Missing and erroneous dates of diagnosis Very slight in NPCR data and the biasing potential low RELIABLE TRUSTED SCIENTIFIC DCPC
RELIABLE TRUSTED SCIENTIFIC DCPC Introduction Date of last contact NPCR states are not funded for active follow-up, which makes dated date of last contact a concern for survival estimation By employing presumed alive assumption, reliable survival estimates can be computed with NPCR data
RELIABLE TRUSTED SCIENTIFIC DCPC Introduction Vital status Vital status provides essential event (death) information to survival analysis Death status reporting delay (DSRD): Death status of a cancer patient is not reported to a cancer surveillance system at the same year death occurred. The damages lay in two areas: Incomplete death counts will cause underestimation of hazard rate (death rate) which will in turn cause overestimation of survival Presumed alive assumption erroneously will regard these DSRD cases as alive and attribute much longer survival time than they should have, resulting in overestimation of survival again
Objectives To study DSRD patterns in NPCR data To quantify biases induced by DSRD to the population-based cancer relative survival analysis with presumed-alive assumption RELIABLE TRUSTED SCIENTIFIC DCPC
Death Status Reporting Delay in NPCR data
Data and Method Data: NPCR data submissions: November 2002-November 2014 (2002-2014) From 16 states that data quality met survival analysis criteria and had consistent patient IDs between Submission 2002-2014 Method: The cases experienced death between 1999-2014 were tracked among submissions The dates of the 1 st appearance of the status Dead in NPCR data were reported RELIABLE TRUSTED SCIENTIFIC DCPC
RELIABLE TRUSTED SCIENTIFIC DCPC Results: DSRD in NPCR Data (16 Sates) Year of Death Yrs of Delay 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total 0 0 0 22187 23280 27501 27016 29707 35152 43735 38913 40565 36820 53488 41880 41030 40639 501913 1 0 58491 49338 55032 45942 57231 72174 74514 69446 79759 74579 107754 90558 83389 62041 980248 2 61749 65797 78706 80271 94795 92740 92720 96461 102161 107524 119111 102136 111350 135291 1340812 3 4557 5786 3273 2409 3000 11724 1635 4869 4870 5304 6172 3072 2495 59166 4 1449 924 1572 869 8408 1011 4353 1158 790 2221 2095 1029 25879 5 593 928 590 6623 347 626 1085 463 1808 1552 793 15408 6 442 356 1759 293 444 907 466 1478 1121 741 8007 7 149 731 3865 365 1114 520 1300 871 614 9529 8 294 3257 288 998 460 1034 824 542 7697 9 1199 290 662 499 917 972 770 5309 10 79 393 493 779 840 262 2846 11 132 360 530 718 217 1957 12 319 583 483 218 1603 13 252 263 168 683 14 131 136 267 15 56 56 Total 71401 138295 163914 172354 183985 194043 205034 215508 224545 236014 243315 250811 257891 260560 103071 40639 2961380 Table 1: DSDR of all cancer patients diagnosed between 1999-2014 and died between 1999-2014
RELIABLE TRUSTED SCIENTIFIC DCPC Results: DSRD in NPCR Data (16 States) Year of Death (Diagnosis year = 2001) Yrs of Delay 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total 0 0 0 2 13438 6809 3877 2949 2451 2785 2133 1732 1433 2203 1770 1121 1626 44329 1 0 0 28887 16680 4444 3085 2865 3056 2318 2629 1980 3651 3093 1363 2394 0 76445 2 0 0 40379 20164 12465 8537 7255 5778 4829 4643 4726 3133 2645 3991 0 0 118545 3 0 0 1608 707 395 1514 111 312 333 343 313 117 101 0 0 0 5854 4 0 0 585 226 1804 120 313 78 38 162 94 41 0 0 0 0 3461 5 0 0 238 2477 102 68 120 25 163 81 48 0 0 0 0 0 3322 6 0 0 444 131 69 109 39 157 63 38 0 0 0 0 0 0 1050 7 0 0 1142 88 176 62 153 47 48 0 0 0 0 0 0 0 1716 8 0 0 81 277 72 180 60 55 0 0 0 0 0 0 0 0 725 9 0 0 238 133 200 123 63 0 0 0 0 0 0 0 0 0 757 10 0 0 126 233 160 37 0 0 0 0 0 0 0 0 0 0 556 11 0 0 144 246 54 0 0 0 0 0 0 0 0 0 0 0 444 12 0 0 227 66 0 0 0 0 0 0 0 0 0 0 0 0 293 13 0 0 46 0 0 0 0 0 0 0 0 0 0 0 0 0 46 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Total 0 0 74147 54866 26750 17712 13928 11959 10577 10029 8893 8375 8042 7124 3515 1626 257543 Table 2: DSDR of cancer patients diagnosed in 2001 and died between 2001-2014
RELIABLE TRUSTED SCIENTIFIC DCPC Results: DSRD in NPCR Data (DXYR=2001) Year of Death (Diagnosis year = 2001) Yrs of Delay 2001 2002 2003 2004 2005 2006 2007 Total 0 2 13438 6809 3877 2949 2451 2785 32311 1 28887 16680 4444 3085 2865 3056 2318 61335 2 40379 20164 12465 8537 7255 5778 4829 99407 3 1608 707 395 1514 111 312 333 4980 4 585 226 1804 120 313 78 38 3164 5 238 2477 102 68 120 25 163 3193 6 444 131 69 109 39 157 63 1012 7 1142 88 176 62 153 47 48 1716 8 81 277 72 180 60 55 0 725 9 238 133 200 123 63 0 0 757 10 126 233 160 37 0 0 0 556 11 144 246 54 0 0 0 0 444 12 227 66 0 0 0 0 0 293 13 46 0 0 0 0 0 0 46 Total 74147 54866 26750 17712 13928 11959 10577 209939 Table 3: Effects of DSDR on survival time assigned Compare effects of DSDR with a conceptual cohort (diagnosed in 2001 and follow-up to 2007) between Submission 2009 and 2014 Cases diagnosed in 2001, in green, reported as Dead in Submission 2009 Cases diagnosed in 2001, in colors, reported as Dead in Submission 2014 Years of survival erroneously assigned: cutoff year (2007) less death year Death 2001: 6-7 years of 781 cases Death 2002: 5-6 years of 955 cases Death 2003: 4-5 years of 662 cases Death 2004: 3-4 years of 511 cases Death 2005: 2-3 years of 435 cases Death 2006: 1-2 years of 362 cases Death 2007: 0-1 years of 645cases 4351 DSDR cases of the cohort are wrongly assigned, by presumed alive assumption, 0-7 more years of survival in Submission 2009 than those if the study were done with Submission 2014 data
Impact of DSRD on Population-Based Cancer Survival with Presumed Alive Assumption
RELIABLE TRUSTED SCIENTIFIC DCPC Data and Method Data (N=2,240,010) NPCR data submissions 2009-2014 Study cohort: Cases diagnosed between 2001-2007 with follow-up to 2007 From 16 states that met the data quality standards of survival analysis and had consistent patient IDs between submission 2002-2014 Method Assume all death of the cohort were reported in 2014 submission Removed all cases with incidence reporting delay since our early study indicated underestimation biases All factors were controlled except for leaving the vital status as the sole varying factor among submissions Simulate estimation of 5-year relative survival in each submission sequentially from 2009 to 2014 for the same cohort Used customized NPCR Relative Survival SAS tool to estimate the relative survival
Results: Impact of DSDR Cancer site Submission 5-year relative survival Standard error DSDR Induced Overestimation Biases All sites Combined 2009 65.1% 0.0% *0.9% All sites Combined 2010 64.7% 0.0% *0.5% All sites Combined 2011 64.5% 0.0% *0.3% All sites Combined 2012 64.4% 0.0% *0.3% All sites Combined 2013 64.2% 0.0% 0.1% All sites Combined 2014 64.2% 0.0% 0.0% Thyroid 2009 96.8% 0.2% 0.2% Thyroid 2010 96.8% 0.2% 0.1% Thyroid 2011 96.7% 0.2% 0.1% Thyroid 2012 96.7% 0.2% 0.0% Thyroid 2013 96.7% 0.2% 0.0% Thyroid 2014 96.6% 0.2% 0.0% Liver & IBD 2009 16.7% 0.3% *1.6% Liver & IBD 2010 16.1% 0.3% *1.0% Liver & IBD 2011 15.9% 0.3% *0.8% Liver & IBD 2012 15.7% 0.3% 0.6% Liver & IBD 2013 15.2% 0.3% 0.1% Liver & IBD 2014 15.1% 0.3% 0.0% All sites combined Maximum bias 0.9% Significant bias exists till the 4 th data submission Thyroid (high survival) Maximum bias 0.2% No significant bias Liver & IBD (low survival) Maximum bias 1.6% Significant bias exists till the 3 rd data submission Table 4: Examples of impact of DSDR on relative survival RELIABLE TRUSTED SCIENTIFIC DCPC
RELIABLE TRUSTED SCIENTIFIC DCPC Results: Impact of DSDR Cancer Site Submission 5-Year Survival Standard Error Biases Submissions with Significant Bias Cervix 2009 68.3% 0.4% 0.8% 0 Hodgkin lymphoma 2009 82.8% 0.4% 0.4% 0 Testis 2009 95.7% 0.2% 0.1% 0 Thyroid 2009 96.8% 0.2% 0.2% 0 Larynx 2009 60.5% 0.5% 1.1% 1 Brain & other nervous system 2009 31.7% 0.3% 1.2% 1 Myeloma 2009 37.5% 0.4% 1.4% 1 Ovary 2009 44.3% 0.3% 1.0% 1 Leukemia 2009 49.3% 0.3% 1.0% 1 Oral cavity & pharyn 2009 58.3% 0.3% 1.0% 1 Non-Hodgkin lymphoma 2009 65.6% 0.2% 0.9% 1 Kidney & renal pelvis 2009 70.3% 0.3% 0.7% 1 Corpus & uterus 2009 80.5% 0.2% 0.6% 1 Melanoma 2009 89.4% 0.2% 0.5% 1 Pancreas 2009 7.7% 0.2% 1.3% 4 Liver & IBD 2009 16.7% 0.3% 1.6% 3 Esophagus 2009 17.7% 0.3% 1.4% 2 Lung & bronchus 2009 18.0% 0.1% 1.3% 4 Stomach 2009 28.5% 0.3% 1.8% 3 Colon & rectum 2009 64.0% 0.1% 1.1% 3 All sites Combined 2009 65.1% 0.0% 0.9% 4 Urinary bladder 2009 76.3% 0.2% 1.1% 2 Breast 2009 88.7% 0.1% 0.6% 2 Prostate 2009 98.1% 0.1% 0.6% 3 Table 5: Summary of DSRD on relative survival in 24 cancer sites
RELIABLE TRUSTED SCIENTIFIC DCPC Conclusion: Impact of DSRD DSRD is substantially presented in NPCR data The level of DSRD s impact on survival time is diagnosis year specific and depends on study cohort cutoff date and actual death date The impact of DSRD on survival is significant, but also cancer specific, especially in Cancers with high case load Cancers with low survival Statistical comparisons on temporal scales of these cancer sites should be reconsidered, if without any precautionary adjustments to study populations
Possible Next Steps: Study the combined effects of reporting delays, incidence reporting delay and death status reporting delay, on survival A long-term study to investigate the factors that might contribute to DSDR (need to involve NPCR states) Annually monitoring reporting delay related biases in NPCR survival outcomes It might be necessary to publish an annual NPCR relative survival study population selection guidelines RELIABLE TRUSTED SCIENTIFIC DCPC
Thank You and Questions! Contact Information Xing Dong xdong@icfi.com Reda Wilson dfo8@cdc.gov