Increased Risk of Unknown Stage Cancer from Residence in a Rural Area: Health Disparities with Poverty and Minority Status

Transcription

1 Increased Risk of Unknown Stage Cancer from Residence in a Rural Area: Health Disparities with Poverty and Minority Status Eugene J. Lengerich, Gary A. Chase, Jessica Beiler and Megan Darnell From the Department of Health Evaluation Sciences, Pennsylvania State University and the Penn State Cancer Institute Hershey Medical Center, Hershey (PA)

2 ABSTRACT Objectives: Quantify risk for unknown stage cancer associated with rural residence. Methods: Logistic regression using invasive cancer incidence data from three states, with adjustment for individual- and area-level characteristics. Results: Of all cases 59,493 (12.6%) were of unknown stage. Cancers of the prostate and lung/bronchus had highest percentage with unknown stage. Among age-gender groups, males at least 65 years of age had the greatest overall percentage of unstaged cancer. Residents of rural zip codes were at 17% increased risk of unknown stage (adjusted OR=1.17, 95% CI: 1.14 to 1.20). Risk from rural residence was greater for blacks and other races than it was for whites; increased risk from rurality was found for blacks and other races in both high-and low-poverty counties. Rurality interacted with both poverty and race to increase the risk of unstaged cancer. Conclusions: Residents of rural areas with high percentages in poverty were at increased risk for unstaged cancer. The increased risk from rurality was most marked in minorities. Unknown stage is an indicator of a health disparity that may be associated with poor health outcomes. 2

3 BACKGROUND The stage of cancer at initial diagnosis is important information both for an individual patient and a population. For a patient whose cancer could be treated with one of several possible protocols, stage is one of the primary factors used to select a treatment plan. Additionally, stage at diagnosis is a primary consideration for development of an accurate clinical prognosis for an individual cancer patient. After the stage has been determined and recorded for individual cancer patients, aggregate statistics on the stage at initial diagnosis can be used to assess a population s utilization of early detection modalities, to identify specific subpopulations to target for an early-detection public health program, or to evaluate the impact of an early detection program. At the population level, the most common schema used to classify stage at initial diagnosis of cancer is summary staging. Summary staging, also called the General Staging, California Staging, and Surveillance, Epidemiology, and End Results (SEER) Staging, is based upon the theory of cellular growth of cancer and clinical and pathological information 1. Summary staging is composed of four specific stages in situ, local, regional and distant. If there is insufficient clinical and pathological information to assign a specific stage to a cancer, such as in a case without a thorough diagnostic workup or where there is ambiguous or contradictory information, a cancer may be recorded in aggregate statistics as having an unknown stage. Knowledge of the magnitude and distribution of unknown stage cancer at diagnosis in a defined population is important for several reasons. First, cancers with an unknown stage represent a potentially important portion of the cancer burden for that population. Second, if the actual incidence of cancer in a population does not change over time but the percentage of unknown stage cancers in that population decreases over time (i.e. possibly because diagnostic capability increases over time), then the observed incidence of stage-specific cancer will change even though the actual incidence of stage-specific cancer may not have changed. Such a situation may lead to inaccurate observations and conclusions about the health of the population. Finally, an increase in risk of unknown stage cancer for members of a particular subpopulation may be evidence of a health disparity associated with a poor health outcome. The epidemiological literature on the incidence of unknown stage cancer is sparse; in fact, surveillance reports frequently exclude unknown stage cancer from analyses, especially studies that examine stage-specific rates. Without controlling for potential confounders, Liff et al found that among cancer cases from Georgia ( ), rural cases were approximately two times more likely to be unknown stage than were urban cancer cases 2. In a multivariable analysis limited to lung and esophageal cancer, Silverstein et al found that older, poorer, non-white, single, and rural patients were at increased risk for unknown stage 3. In both studies, the authors concluded that increased occurrence of unknown stage cancer among rural patients may have partially resulted from reduced health care access 2, 3. Supporting this conclusion, access to cancer screening services for breast, cervical and colorectal cancer has been found to be reduced in rural areas. 4 3

4 Unknown stage cancer may 1) be an important component of the total burden of cancer in a population, 2) has been reported to be increased in rural areas, and 3) increase risk for a poor health outcome, our goal was to better understand the risk for unknown stage cancer from rural residence. Specifically, the objectives of this populationbased, multiple-site study were to: 1) determine the number and percentage of cancers that were unknown stage at initial diagnosis in rural and non-rural areas; 2) determine if the adjusted risk of being unstaged at the time of diagnosis was increased for cancer cases from patients who resided in rural areas; 3) determine if the adjusted risk from rural residence was similar across various cancer sites. METHODS This study was completed at Penn State University with data from the Appalachia Cancer Network (ACN), a member of the Special Populations Network of the National Cancer Institute 5,6. ACN seeks to reduce cancer disparities among the medically underserved of Appalachia and has reported increased incidence of cancer of the lung, colon, rectum, and cervix in the Appalachian and rural areas of Kentucky (KY), Pennsylvania (PA), and West Virginia (WV) 7,8. In , approximately 17.7 million people resided in the three states with a substantial rural area; 90.2% were white, 8.4% black, and % of other races. Individual-level data on histologically confirmed incident cancer cases diagnosed among KY, PA, and WV residents between January 1, 1994 and December 31, 1998 were reviewed (n=509,591). Data for each case included summary stage, primary cancer site, histology, and date of diagnosis as well as the cancer patient's age, race (mutually exclusive groups of white, black, and other), gender, and the county and zip code of residence at the time of diagnosis. Cases with either a local, regional, or distant stage were grouped together into staged cancer. In situ (non-invasive) cases were excluded from the analysis (n=37,449) because requirements for collection of data of in situ cancer changed during the time period of the study; this change is not expected to have affected the collection of data for invasive cancers. Cases where the zip code at time of diagnosis was missing/invalid (n=98) or was not found in the Rural-Urban Commuting Area Codes (described below) were excluded (n=1,705) 10. Cases with a transsexual or hermaphrodite gender (n=5) were also excluded because of the analysis of gender-specific cancer sites of the cervix, prostate and female breast. Cases were grouped into six specific cancer sites based on the primary site of tumor origin: lung/bronchus (ICD-O-2 C34.0-C34.9), colon (C18.0-C18.9, C26.0), rectum (C19.9, C20.9), female breast (C50.0-C50.9), prostate (C61.9) and cervix uteri (C53.0-C53.9). In addition to data on individual cancer cases, we included area-level variables to account for availability of health care, socioeconomic status, and rural residency. Estimation of the availability of health care used the number of physicians per 10,000 county population in Estimation of socioeconomic status included the percentage of county residents below the federal poverty level in Assignment of rural/non-rural residency used the dichotomous categorization C of the Rural-Urban Commuting Area Codes (RUCA Codes) of the case s zip code at the time of diagnosis that designated rural as being composed of large towns and more isolated areas 9. Non- 4

5 rural was defined as urban core census tracts, census tracts strongly or weakly tied to an urban core, and all other census tracts with 30-50% flowing to an urbanized area 9. To estimate the relative risk for unknown stage cancer from rural residence, we conducted logistic regression and calculated odds ratios (ORs) and 95% confidence intervals (CIs) that compared stage at diagnosis for cancer cases from patients that resided in rural zip codes with the stage at diagnosis for cancers from patients who resided in non-rural zip codes. We first estimated the unadjusted risk with race-stratified, bivariate analyses that examined the stage with individual- (e.g. age < 20 years) and area-level variables (e.g. availability of health care). This analysis was followed by multiple-variable models to assess the risk of unknown stage cancer for residents of rural areas. Variables in the model were age (under 65 vs. 65+ years), gender (for appropriate cancer sites), race, histology (for the specific cancer sites), availability of health care, and socioeconomic status. Multiple logistic regressions were conducted for all cancers, for each of the six specific cancer sites, and for other cancers. Analyses were performed by SAS, Version 8.2 (SAS Institute Inc., Cary, North Carolina) 10. All first-order interactions were examined. Stepwise selection was used to determine significant interactions with a level of significance equal to This study was approved by the Institutional Review Board, Penn State College of Medicine, on July 17, 2001, Protocol No EM. RESULTS From 1994 through 1998, 59,493 (12.6%) of the invasive cancer cases in KY, PA, and WV were unknown stage (Table 1). Cancers of the prostate and lung/bronchus, as well as other cancers, had the highest percentage of cases with an unknown stage (14.2%, 12.6%, 17.0%, respectively). Female breast cancer had the lowest percentage of cases with unknown stage (4.1%). Though the percentage of unstaged cancers was slightly greater for rural cases than for non-rural cases, the relative order of the percentage with unknown stage was the same for rural and non-rural cases. Among all cancers, those cancers from patients residing in rural areas were 1.20 (95% CI: 1.18, 1.22) times more likely to be of unknown stage than were cancers from patients that resided in non-rural areas without adjustment for any confounders (Table 2). Cancer cases from patients between years of age tended to be least affected by rural residence, although this trend did not hold for the race-stratified analysis. Stratifying by race showed that the effect of rural residence was greater for blacks (OR=1; 95% CI: 1.28, 1.55) and other races (OR=1.51; 95% CI: 1.36, 1.67), than it was for whites (OR=1.21; 95% CI: 1.19, 1.24). Among whites and blacks, the effect of rural residence on males and females was similar. The effect of rurality on risk appeared greater for females of other races than for males of other races, though the 95% confidence intervals for the two odds ratios overlapped. For counties with at least 10% of the population below poverty level, residence in a rural zip code conveyed significant risk for unknown stage cancer within each race (whites: OR=1.24; 95% CI: 1.21, 1.27; blacks: OR=4; 95%CI: 1.30, 1.60; other OR=1.34; 95% CI: 1.19, 1.52). In counties with less than 10% of the population below poverty level, the rurality effect was significant only in other races. Among whites, the risk for unstaged cancer from rural 5

6 residence was greatest for counties with a low availability of physicians, while the availability of physicians did not appear to affect the risk from residence in rural zip code for blacks. In other races, the risk from rural residence was greater in counties with a higher concentration of physicians (OR=2.02; 95% CI: ) than in counties with a lower concentration of physicians (OR=1.37; 95% CI: 1.19, 1.57). In multiple logistic regressions, residence in a rural area significantly increased the risk of unknown stage cancer (adjusted OR=1.17; 95% CI: 1.14 to 1.20) (Table 3). The effect of rural residence was significant for cancers of the lung/bronchus (adjusted OR=1.32; 95% CI: 1.25, 1.39), colon (adjusted OR=1.23; 95% CI: 1.11, 1.35), prostate (adjusted OR=1.12; 95% CI: 1.05, 1.18) and female breast (adjusted OR=1.35; 95% CI: 1.22, 8). Though elevated, the risk from rural residence was not statistically significant for cervical cancer (adjusted OR=1.15; 95% CI: 0.88, 9). In rectal cancer, rural residence did not affect the risk for unknown stage (adjusted OR=0.92; 95% CI: 0.81, 1.06). The adjusted odds ratio for the effect of residence in a rural zip code did not change meaningfully when any of the confounder interactions were included in the multiple logistic regression. Several first-order interactions were statistically significant (p<0.05). Interactions of residence in rural zip code with poverty and with race were each significant (p<0.001). For example, blacks and other races in counties with a high percentage of persons below poverty levels of risk (OR=1.56, 95% CI: 1.09, 2.23 and OR=1.62; 95% CI: 1.29, 2.03, respectively) of unknown stage cancer is greater than what would be predicted by simply combining the separate effects of race and socioeconomic status of the area (Table 4). Also significant was the interaction of age with gender; percentage of unknown stage cancer was largest for males who were at least 65 years of age. DISCUSSION In this 5-year data set from a large geographic area 32% of all cancer cases were from patients residing in a rural zip code. We found that 12% (59,493) of all cases and 14% (21,178) of those with a rural zip code were of unknown stage at the time of initial diagnosis. After adjustment for individual- and area-level characteristics, we found that cancers in patients who resided in rural zip codes were 17% more likely to be registered as unstaged. This estimate of increased risk was less than the 28% increase in the rate of unstaged cancer found for the rural Appalachian area of KY, PA, and WV 9. The difference in the estimates from these two studies may be due to the different analytic methods, geographic areas and definitions of residence in a rural area. In addition, the previous study used SEER data for a comparison group. However, both studies found a statistically significant increase in the risk of unstaged cancer for rural residents. We found a statistically significant interaction of residence in a rural zip code with race for the risk of unknown stage cancer. Specifically, the risk from rural residence was greater for blacks and members of other races than it was for whites. We also found a significant interaction of rural residence with county-level poverty on the risk for unknown stage cancer. Cancer patients who resided in a rural zip code and a county with a high level of poverty had an increased risk for unknown stage cancer greater than what would be expected from these two factors acting 6

7 independently. While residence in a rural zip code conferred an overall increased risk of unknown stage, the risk from rural residence varies by poverty and racial group; blacks in poor counties had a 44% increase in risk. We found no statistically significant interaction between the availability of health care providers at the county level and residence in a rural zip code. We also found inconsistent effects of the availability of health care providers on the risk of unknown stage cancer for residents of rural zip codes. This is a departure from the findings in South Carolina where the number of primary care physicians per county population was found to be associated with unknown stage lung/esophageal cancer 3. We found that the estimated increase in risk for unstaged cancer associated with rurality was not the same for each of the examined cancer sites. The increase in risk was greatest for female breast cancer (35%) and lung/bronchus (32%), while the risk increase for unstaged cancer of the rectum and cervix was not statistically significant. It is important to note that the risk of unknown stage for cancer of the cervix was elevated though not statistically significant. Cancer of the cervix was the least commonly diagnosed site (n=416 unknown stage cancers). Reasons for the difference in risk by cancer site are not clear, but could include reduced diagnostic and specialist capabilities for specific cancers, different physician preferences for treatment of cancer by site, and patient treatment preferences by site. Silverstein et al found a 16% increase (p=0.0009) in the percentage of unknown stage lung/esophageal cancer for patients who resided in a rural zip code (42.7% of unknown stage cancers were rural) when compared to those from a patient who did not reside in a rural zip code (36.7% of known stage cancers were rural) 3. The difference in the estimates from these two studies may be due to the use of a different geographic area, adjustment for different factors, and the different grouping of cancers. Cancer cases with an unknown stage may have unfavorable implications for population health. At the population level, we found that 12.6% of all cases would have been excluded from analyses that included only known stage cancers. If actual cancer incidence remained steady over time but diagnostic capabilities improved over time, the observed number of stage-specific cancers would increase. The degree to which the numbers increase would depend upon the relative stage distribution of the known stage cancers, and the relative distribution of the stage of cancers that would have previously been unknown stage. For example, assume that the stage distribution of all invasive cancers is 51.1% local stage, 25.3% regional stage, and 23.6% distant (as was the present study population). If 50% of the unknown stage cases are now staged (n=29,746 in the present study population) and the distribution of those cases is 10% local, 30% regional and 60% distant, the number of local stage, regional stage, and distant stage cases will increase %, 8.6%, and 18.4%, respectively. Despite its frequent use in the literature, health disparity is inconsistently defined. Healthy People 2010 recognizes a health disparity to be present when different groups experience any difference in a health-related area, including behavior, access to care, morbidity and mortality. The NCI states that a cancer health disparity is present when there are differences in cancer incidence, survival or mortality. According to these definitions, our data support the existence of a health disparity for rural residents. 7

8 Alternatively, others propose more restrictive criteria for a health disparity - a disparity exists if there is difference in health. Under such a definition, the findings from our study can only suggest the existence of a health disparity for rural cancer patients because we did not attempt to assess health. However, other data suggest that unknown stage cancer is a risk for poor health. For example, the 5-year relative survival rate of persons with unknown stage cancer is low, and closest to those with distant stage cancer 11. Also, women with unstaged cervical cancer were less likely to receive recommended surgical or radiation treatment and women with improperly staged ovarian cancer received both over and under treatment of their disease 12,13. Consequently, it seems plausible that the increased risk for unknown stage cancer from rural residence contributes to poor outcomes, such as the excess cancer mortality that has been reported for rural Appalachia 14. We did not attempt to assess whether the stage was actually unknown while the patient received care. For example, this measurement error may exist if registry data recorded a case as unknown stage because complete clinical and pathologic information on a cancer patient was not available to the registrar, but was available to the attending physicians. Also, we were unable to assess individual and provider reasons for unknown stage. For example, the stage may appropriately remain unknown if the patient s co-morbidity would compromise his/her clinical stability during a surgical procedure necessary to conclusively establish the stage. This study is limited by its use of non-contiguous, area-level variables that attribute characteristics of the geographic area to individuals, leading to possible ecological bias 15. This method assumes that the process of care for an individual cancer case can be accurately assessed by area-level measurements. With the possible inmigration of educated and affluent persons to rural areas, this ecological technique may result in under-estimation of the effects of poverty and rurality because such in-migrants may bring health care patterns and health behaviors with them that are typical of non-rural residents (e.g. high use of specialty care). However, this categorization was considered appropriate for our study because the overall pattern of cancer care is likely to differ substantially between metropolitan areas (broadly defined) and rural communities. Despite these limitations, our study found a consistent increase in the risk of unstaged cancer for residents of rural areas and for poverty and minority status, even after controlling for other characteristics. Strengths of this study include the large number of cancer cases; the utilization of data from multiple, high-quality registries; general consistency of findings for various cancer sites; and the inclusion of socioeconomic status and availability of health care in the model. Future research should seek to confirm the difference we detected in other rural areas and further estimate the patient, provider and facility factors, as well as the outcomes, associated with unknown stage cancers. 8

9 REFERENCES 1. National Cancer Institute. Surveillance, Epidemiology and End Results Program [homepage on the Internet]. [cited December 23, 2003] Available at URL: 2. Liff JM, Chow WH, Greenberg RS.Rural-urban differences in stage at diagnosis. Possible relationship to cancer screening. Cancer Mar 1; 67(5): Silverstein MD, Nietert PJ, Xiaobu Y, Lackland DT. Access to care and stage at diagnosis for patients with lung cancer and esophageal cancer: analysis of the Savannah River Region Information System cancer registry data. South Med J Aug;95(8): Lengerich EJ, Wyatt SJ, Rubio A, Beaulieu J, Coyne CA, Bottorff D, et al. The Appalachia Cancer Network: opportunity for cancer research with a rural, medically underserved population. J Rural Health. In press National Cancer Institute. Special Populations Network. Abstracts. The Appalachia Cancer Network. [cited Dec 2003] Available at 6. Appalachian Regional Commission. The Appalachian region [homepage on the Internet]. [cited 2003 Feb 23] Available at: 7. Lengerich EJ, Tucker T, Powell RK, Colsher P, Lehman E, Ward AJ, et al. Cancer incidence in Kentucky, Pennsylvania, and West Virginia: Disparities in Appalachia. J Rural Health. In press Health Resources and Services Administration, Bureau of Health Professions, Area Resource File (ARF) System [database on the internet], Fairfax, VA: Quality Resource Systems, Inc., [updated 2003 Feb; cited 2003 Oct) Available from: 9. WWAMI (Washington, Wyoming, Alaska, Montana, & Idaho) Rural Health Research Center. Rural-Urban Commuting Area Codes (RUCA Codes) [homepage on the internet]. [updated June 2002; cited October 2003] Available at: SAS Institute Inc., Version 8.2, SAS Institute Inc.: Cary, North Carolina, Ries LAG, Eisner MP, Kosary CL, Hankey BF, Miller BA, Clegg L, et al. SEER Cancer Statistics Review, , National Cancer Institute. Bethesda, MD, Merrill RM, Merrill AV, Mayer LS. Factors associated with no surgery or radiation therapy for invasive cervical cancer in Black and White women. Ethn Dis Spring-Summer; 10(2): Le T, Adolph A, Krepart GV, Lotocki R, Heywood MS. The benefits of comprehensive surgical staging in the management of early-stage epithelial ovarian carcinoma.gynecol Oncol May; 85(2): Huan B, Wyatt S, Tucker T, Bottorff D, Lengerich E, Hall HI. Cancer death rates Appalachia, MMWR 2002;51(24): Morgenstern H. Ecological Studies. In: Rothman KJ, Greenland S, editors. Modern Epidemiology. 2 nd edition. Philadelphia: Lippincott-Raven Publishers; Chapter 23. 9

10 Table 1: Number and Percentage of Total and Unknown Stage Invasive Cancers, by Rural/non-Rural Zip Code of Residence at Time of Diagnosis and Cancer Site, States of KY, PA, and WV. Cancer Site Number of Cases Total Rural Non- Rural Unknown Stage Cases Total Rural Non-Rural Number Percentage Number Percentage Number Percentage All Lung and Bronchus Colon Rectum Prostate Cervix Female Breast Other Cancers Note: Cases were grouped into six cancer sites based on the primary site of tumor origin: lung/bronchus (ICD-O-2 C34.0-C34.9), colon (C18.0-C18.9, C26.0), rectum (C19.9, C20.9), female breast (C50.0-C50.9), prostate (C61.9) and cervix uteri (C53.0-C53.9). Assignment of rural/non-rural residency, used the dichotomous categorization C of the Rural-Urban Commuting Area Codes (RUCA Codes) of the case s zip code at the time of diagnosis that designated rural as being composed of large towns and more isolated areas 10. Non-rural was defined as urban core census tracts, census tracts strongly or weakly tied to an urban core, and all other census tracts with 30-50% flowing to an urbanized area

11 Table 2: Unadjusted Odds Ratio (OR) and 95% Confidence Interval (CI) for Unknown Stage Invasive Cancer Comparing Risks for Cancer Patient Cases Residing in Rural and Non-Rural Zip Codes at Time of Initial Diagnosis, By Race and Selected Individual- and Area-level Characteristics, States of KY, PA, and WV. Total 1.20 (1.18, 1.22) Age (years) Gender Socioeconomic Status of County Availability of Health Care in County <20 0 (1.09, 1.80) (0.97, 1.10) (1.19, 1.30) (1.19, 1.25) Male 1.21 (1.19, 1.24) Female 1.18 (1.15, 1.21) Poor 1.23 (1.20, 1.26) Non-poor 0.97 (0.93, 1.01) High 1.13 (1.08, 1.18) Low 1.25 (1.22, 1.28) All Races Whites Blacks Other OR 95% CI OR 95% CI OR 95% CI OR 95% CI (1.19, 1.24) (1.09, 1.88) (1.06, 1.21) (1.22, 1.33) (1.19, 1.25) (1.20, 1.26) (1.15, 1.21) (1.21, 1.27) (0.92, 1.00) (1.05, 1.16) (1.22, 1.28) (1.28, 1.55) (0.66, 6.50) (0.63, 1.14) (0.91, 4) (3, 1.81) (1.23, 1.59) (1.23, 1.65) (1.30, 1.60) (0.81, 1.61) (1.22, 1.80) (1.26, 1.71) Note: Cases were grouped into six cancer sites based on the primary site of tumor origin: lung/bronchus (ICD-O-2 C34.0-C34.9), colon (C18.0-C18.9, C26.0), rectum (C19.9, C20.9), female breast (C50.0-C50.9), prostate (C61.9) and cervix uteri (C53.0-C53.9). Assignment of rural/non-rural residency, we used the dichotomous categorization C of the Rural-Urban Commuting Area Codes (RUCA Codes) of the case s zip code at the time of diagnosis that designated rural as being composed of large towns and more isolated areas 10. Non-rural was defined as urban core census tracts, census tracts strongly or weakly tied to an urban core, and all other census tracts with 30-50% flowing to an urbanized area 10. We designated counties with at least 10% of its population below the federal poverty level as poor and counties with less than 10% of its population below the federal poverty level as non-poor. We designated a county s availability of health care as high when its population had at least 20 physicians per 10,000 and as low when its population had less than 20 physicians per 10, (1.36, 1.67) (0.65, 5.09) (0.85, 5) (1.36, 2.06) (1.33, 1.76) (1.21, 1.57) (0, 2.00) (1.19, 1.52) (5, 2.23) (1.60, 2.55) (1.19, 1.57) 11

12 Table 3: Adjusted Odds Ratio and 95% Confidence Interval (CI) for Unknown Stage Invasive Cancer Comparing Risk for Cancer Patient Cases Residing in Rural with Non-Rural Zip Codes at Time of Initial Diagnosis, By Cancer Site, States of KY, PA, and WV. Cancer Odds Ratio 95% CI P Value All 1.17 (1.14, 1.20) <.001 Lung/Bronchus 1.32 (1.25, 1.39) <.001 Colon 1.23 (1.11, 1.35) <.001 Rectum 0.92 (0.81, 1.06) Prostate 1.12 (1.05, 1.18) <.001 Cervix 1.15 (0.88, 9) Breast 1.35 (1.22, 8) <.001 Note: Multiple logistic regression include variables for individual-level (race, sex, and age) and county-level characteristics (availability of health care and socioeconomic status). Analysis of site-specific cancers also controlled for histology. Cases were grouped into six cancer sites based on the primary site of tumor origin: lung/bronchus (ICD-O-2 C34.0- C34.9), colon (C18.0-C18.9, C26.0), rectum (C19.9, C20.9), female breast (C50.0-C50.9), prostate (C61.9) and cervix uteri (C53.0-C53.9). For assignment of rural/non-rural residency, we used the dichotomous categorization C of the Rural-Urban Commuting Area Codes (RUCA Codes) of the case s zip code at the time of diagnosis that designated rural as being composed of large towns and more isolated areas 10. Non-rural was defined as urban core census tracts, census tracts strongly or weakly tied to an urban core, and all other census tracts with 30-50% flowing to an urbanized area 10 12

13 Table 4: Adjusted Odds Ratio and 95% Confidence Interval (CI) for Unknown Stage Invasive Cancer Comparing Risks for Cancer Patient Cases Residing in Rural and Non-Rural Zip Codes at Time of Diagnosis, By Stratification of Race and Area s Socioeconomic Status, States of KY, PA, and WV. Stratification Level Odds Ratio 95% CI P-Value White: Poor (1.120, 1.185) <.001 White: Non-poor (0.969, 1.054) Black: Poor (1.079, 53) Black: Non-poor 1.56 (1.089, 2.234) Other: Poor 11 (1.196, 1.666) <.001 Other: Non-poor (1.289, 2.031) <.001 Note: Multiple logistic regression included variables for individual-level (race, sex, and age) and county-level characteristics (availability of health care and socioeconomic status). Cases were grouped into six cancer sites based on the primary site of tumor origin: lung/bronchus (ICD-O-2 C34.0- C34.9), colon (C18.0-C18.9, C26.0), rectum (C19.9, C20.9), female breast (C50.0-C50.9), prostate (C61.9) and cervix uteri (C53.0-C53.9). Assignment of rural/non-rural residency, we used the dichotomous categorization C of the Rural-Urban Commuting Area Codes (RUCA Codes) of the case s zip code at the time of diagnosis that designated rural as being composed of large towns and more isolated areas 10. Non-rural was defined as urban core census tracts, census tracts strongly or weakly tied to an urban core, and all other census tracts with 30-50% flowing to an urbanized area 10. We designated counties with at least 10% of its population below the federal poverty level as poor and counties with less than 10% of its population below the federal poverty level as non-poor. 13