The Impact of Rural Residency on Time to Lung Cancer Treatment in West Virginia and Patient Survival

The Impact of Rural Residency on Time to Lung Cancer Treatment in West Virginia and Patient Survival | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Impact of Rural Residency on Time to Lung Cancer Treatment in West Virginia and Patient Survival Sabina Nduaguba, Anna Lumudae, Nicole Stout This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4492769/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose : To examine the association of rurality with timely receipt of lung cancer treatment and survival in West Virginia (WV). Methods : A retrospective study was conducted using 1993-2021 WV Cancer Registry data to identify persons diagnosed with NSCLC who received treatment. Participants were classified by rurality (rural vs non-rural), and time to treatment from diagnosis was dichotomized as early treatment (<35 days) or delayed treatment (≥35 days). Descriptive statistics and survival analysis (with univariate and multivariate Cox regression were used to address study objectives. Results : Of 10,463 participants, 678 (6.5%) were rural residents. The majority were male (58.1%), married or partnered (59.9%), and non-Hispanic white (97.5%). 61% received early treatment. 45%, 38%, and 16% received systemic therapy, surgery, and radiation, respectively. There were significantly more non-Hispanic white (99.6% vs 97.3%) patients residing in rural areas compared to non-rural areas, and fewer rural residents were diagnosed at stages 1 (29.4% vs 34.3%) or 2 (10.0% vs 11.6%). Rurality was not associated with time to treatment but was associated with 9% increase in hazard of death (HR=1.09, 95% CI=1.00-1.18). Significant covariates associated with increasing hazard of treatment included being male (HR=1.08, 95% CI=1.04-1.13) and cancer stage (HR range=1.19-2.38, while being Black and receiving surgery (0.43, 0.30-0.62), radiation (0.48, 0.33-0.68), or systemic therapy (0.33,0.23-0.47) (compared to other treatment) were each associated with reduced hazard of treatment. Conclusion : In WV, rurality affects lung cancer outcomes but not time to treatment increasing risk of death for NSCLC patients by 9%. Rural disparities Lung cancer Health care access Cancer epidemiology INTRODUCTION Lung cancer is the second most common cancer diagnosis in the US and the leading cause of cancer death with a five-year survival rate of 28%.[ 1 – 3 ] When diagnosed at an early stage when the cancer is localized and confined to a primary site, the five-year survival rate increases to 65% compared to 9% for metastasized cancer.[ 4 ] Treatment is dependent on cancer stage, involving surgery or definitive radiation therapy at stages IA to IIB, surgery or definitive chemoradiation for stages IIB to IIIB, and systemic therapy for metastatic lung cancer.[ 5 ] The timeliness of lung cancer treatment is associated with survival outcomes, particularly for early stage lung cancer.[ 6 – 11 ] However, 21% of patients with lung cancer receive no treatment resulting in missed opportunities to improve cancer outcomes.[ 1 ] Patients with cancer who reside in rural areas are at significant risk of poor outcomes as a result of reduced access to care. Poor access to care typically manifests as late cancer diagnosis and delayed time to treatment. West Virginia (WV) is located entirely inside the Appalachian region with about 38% of its population considered rural.[ 12 ] The state ranks among the top five states with the highest mortality rates for lung cancer, with a survival rate of 20%, which is considerably lower than the national rate.[ 1 , 13 ] Twelve percent of patients with lung cancer in WV do not receive treatment.[ 1 ] However, the proportion of treated patients for whom treatment is delayed and the impact of delay is not clear. The impact of rurality on timeliness of lung cancer treatment and survival outcomes in WV has also not been elucidated. The aim of this study was to determine the timeliness of treatment among patients with lung cancer as well as the association of rurality with timely receipt of lung cancer treatment and survival in West Virginia (WV). METHODS Study Design and Population This was a retrospective cohort study utilizing data from West Virginia Cancer Registry. The WV cancer registry is an all-site registry established by the WV Department of Health and Human Resources which collects data on all cancers diagnosed in WV except basal and squamous cell carcinoma of the skin and in situ cervical cancer. The data collected by WV Cancer Registry includes information on cancer diagnosis and characteristics, patient demographics, facility providing care, and vital status at follow-up. Persons 18 years or older diagnosed with histologically confirmed primary non-small cell lung cancer between 1993 and 2021 who had non-missing data on cancer stage were included in the study. The protocol for the study was reviewed and approved by West Virginia University Office of Human Research Protections and considered to be minimal risk. Outcome Variable The outcomes of interest were time to treatment for non-small cell lung cancer and overall survival. Time to treatment was defined as the difference in days between date of cancer diagnosis and date of treatment initiation. Overall survival was defined as the difference in months between date of cancer diagnosis and either date of death or date of last contact, whichever occurs last. Main Independent Variable The main independent variable was rurality. This was based on the last recorded rural-urban continuum code – 1993, 2003, or 2013.[ 14 ] Counties in metro areas and areas with population size of 2,500 or more were classified as urban while areas with population size less than 2,500 were classified as rural. Covariates The covariates included age in years, sex at birth, race/ethnicity, marital status, Charlson comorbidity index, cancer stage, and treatment type. Race/ethnicity was classified as non-Hispanic White, Non-Hispanic Black, Hispanic, and others. Marital status was classified as married or partnered vs not coupled (single, separated, divorced, widowed). Charlson comorbidity index was based on ICD-10 codes for secondary diagnosis and comorbidity identified at cancer diagnosis and adapted from the method proposed by Glasheen et al.[ 15 ] Cancer stage was based on the American Joint Committee on Cancer 7th edition clinical and pathological classification and staging system for lung cancer, with preference giving to the clinical staging system.[ 16 ] Treatment type was classified into systemic therapy, surgery, radiation, and other treatment. Analysis For our analysis, we classified patients based on the timeliness of treatment – early treatment (treatment within 35 days), late treatment (treatment received later than 35 days), and no treatment.[ 10 , 17 ] Only persons who received treatment for lung cancer were included in the final analysis, i.e. those classified as receiving early or late treatment, with those who received no treatment excluded. The complete case analytical approach was used by excluding cases with missing values on any of the variables via listwise deletion. Descriptive analysis was conducted using means and standard deviations for continuous variables and frequencies and percentages for categorical variables. Comparisons were made on the descriptive variables between rural and non-rural residents using t-tests for continuous variables, Wilcoxon two-sample test for discrete variables, and chi-square tests for categorical variables. Finally, Cox regression was used to determine the association between rurality and time to treatment and survival in both univariate and multivariate analysis controlling for the covariates. Statistical significance was set at p < 0.05. Analysis was conducted using SAS 9.4. RESULTS A total of 56,117 persons were diagnosed with lung cancer between 1993 and 2021. 56,109 were 18 years or older. Of these, 26,253 were diagnosed with histologically confirmed primary NSCLC. Twenty-eight percent (N = 7,285) of the 26,253 diagnosed persons did not receive treatment and were excluded. After further excluding those with missing values on relevant data points, 10,463 were retained for analysis. Table 1 shows the characteristics of persons included in the study by rurality status. The average age was 66 years (± 10). Most were male (58.1%), married or partnered (59.9%), and non-Hispanic white (97.5%). Sixty-nine percent had a CCI of 0 with the majority diagnosed at stages 1 (34.0%) or stage 4 (32.7%). The median time to treatment was 27 days with 61% treated within 35 days (early treatment). Forty-five percent received systemic treatment while 38% and 16% received surgery and radiotherapy, respectively. By rurality status, 2.3% of non-rural residents were non-Hispanic Black compared to 0.3% of rural residents (p < 0.01). The majority of non-rural residents (34.3%) were diagnosed at stage 1 compared to 29.4% of rural residents (p < 0.05). There were no significant differences in age, sex, marital status, CCI, time to treatment, timeliness of treatment, and treatment type by rurality status. Table 2 shows the results of the association between rurality and time to treatment among persons with lung cancer who received treatment, controlling for age, sex, race/ethnicity, marital status, CCI, cancer stage, and treatment type. Table 3 also shows the association of rurality and overall survival among persons with lung cancer who received treatment, controlling for the same covariates as well as timeliness of treatment. In both univariate and multivariable analyses, rurality was not associated with time to treatment but was associated with overall survival. After controlling for covariates, rural residency was associated with 9% higher risk of death compared to urban residency (Hazard ratio (HR) = 1.09, 95% confidence interval (95% CI) = 1.00-1.18). Covariates associated with time to treatment included age, race/ethnicity, cancer stage, and treatment type. Being male was associated with 8% higher probability of treatment (HR = 1.08, 95% CI = 1.04–1.13). Being Black was associated was 12% lower probability of treatment compared to being White (HR = 0.88, 95% CI = 0.77-1.00). The probability of treatment also increased with cancer stage (HR of 1.19–2.38 for stages 2 through 4 compared to stage 1). Covariates associated with overall survival included age, sex, marital status, CCI, cancer stage, treatment type, and timeliness of treatment. Each year increase in age was associated with 1% increase in risk of death (HR = 1.01, 95% CI = 1.01–1.02). Being male was associated with 21% increase in risk of death (HR = 1.21, 95% CI = 1.16–1.26), Being married was associated with 8% lower risk of death (HR = 0.92, 95% CI = 0.88–0.96), Each unit increase in CCI was associated with 7% increase in risk of death (HR = 1.07, 95% CI = 1.05–1.09). The risk of death increased with cancer stage (HR of 1.58–4.79 for stages 2 through 4 compared to stage 1). Delayed treatment was associated with 18% lower risk of death (HR = 0.82, 95% CI = 0.78–0.85) DISCUSSION This study aimed to evaluation the association of rurality with time to treatment and survival among patients with NSCLC who received treatment in WV. The median time from diagnosis to treatment was 27 days with 61% of study participants treated within 35 days. In other words, treatment was delayed for 39% of those who were treated. The observed time to treatment is within the range of 14 to 39 days observed in other studies.[ 9 , 10 , 18 – 23 ] Rurality was not associated with time to treatment but was associated with 9% higher risk of death. Contrary to expectation, delayed treatment was associated with 18% lower risk of death suggesting that there may confounding factors that explain outcomes among those whose treatment was delayed. One potential explanation for the unexpected finding of improved survival with delayed treatment is the clinical status of those whose treatment was timely vs those for whom treatment was delayed. Our study population included a significantly higher proportion (p < 0.0001) of those diagnosed at stage 4 (70.1%) who received treatment within 35 days, compared to those diagnosed at stages 1 (55.9%), 2 (54.2%) (results not shown), and 3 (57.9%) Hence, those who received timely treatment comprised of a large number of advanced cases (37.7%) who typically have poor prognosis.[ 6 , 24 ] This potentially explains the counterintuitive finding of increased risk of death with early treatment. Several studies similarly report that treatment for patients with early-stage lung cancer is often delayed relative to those who with late-stage diagnosis.[ 25 – 31 ] As expected, rurality was associated with a higher risk of death, reflecting challenges such as long distance to tertiary care clinics, lower socioeconomic status, and lack of or limited health insurance.[ 32 – 35 ] These challenges contribute to health care access disparities that affect the timeliness of receiving care and continued surveillance and monitoring. However, we did not observe any association between rurality and time to treatment in this study. Our observation of poor survival with rural residency may, therefore, be as a result of other factors that result from poor access to care for rural residents such as delayed cancer diagnosis.[ 36 ] In our study, a significantly higher proportion of rural residents were diagnosed at stages 3 or 4 compared to non-rural residents (61% vs 54%). Cancer stage was also an important predictor of overall survival, implying that late diagnosis due to rural residency impacted prognosis. A particular strength of our study is the use of state-wide cancer registry data. Thirty-eight percent of the WV population is considered rural, making the state registry data ideal for a study of the impact of rurality on the timeliness of treatment and lung cancer outcomes.[ 12 ] One limitation of the study is that data collection began at cancer diagnosis. Delays to receiving treatment begin much earlier than the point of diagnosis such as initial screening and/or suspicion of cancer, referral to specialist, and diagnostics for confirmatory diagnosis. While most of our study participants were treated with 35 days of lung cancer diagnosis, it has been shown that the time interval from symptom onset to first abnormal test and from first abnormal test to treatment can each be as long as two months.[ 19 , 37 ] Further investigation into the delay points along the lung cancer continuum according to rurality status is needed to better understand how the process of care may impact rural patients with lung cancer. Further, this was a retrospective study involving the use of data collected for surveillance purposes. Data on potentially confounding geographic variables such as distance to clinic and neighborhood hospital density that impact timeliness of receiving medical care were not collected or controlled for. Finally, the association of rurality with survival does not mean causation. We believe that there are mediating factors such as poor access to care[ 38 ] and other socio-economic factors[ 39 ] that more directly explain poor survival outcomes observed among rural residents. To conclude, rurality was not associated with time to treatment. The observed association of delayed treatment with survival was likely due to confounding by the stronger association between cancer stage and survival since most patients with delayed treatment were early stage. Despite these null and counterintuitive findings, rurality remained associated with poor survival, reflecting issues with poor access to health care that manifested as delayed diagnosis. Interventions that focus on screening and early diagnosis of lung cancer would likely be more effective at improving prognosis and survival outcomes for persons who reside in rural areas. Declarations Consent to Participate Declaration A waiver of HIPAA authorization was granted for the study by West Virginia University Office of Human Research Protections as the study was considered to be minimal risk. Funding Declaration No funding was provided for this study Data Availability Declaration The data that support the findings of this study are not available from the authors because restrictions apply to the availability of these data, which were provided by West Virginia Cancer Registry, and so are not publicly available. Competing Interest Declaration The authors have no conflicts of interest to declare Author Contribution SN conceptualized and designed the study, procured and analyzed data, and led the writing of the initial draft. AL supported in the writing of the initial draft and reviewed the final version of the manuscript. NS reviewed the manuscript and provided expert input in rural health disparities. 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Cancer Control 28:10732748211011956. https://doi.org/:10.1177/10732748211011956 Tables Table 1 Characteristics of Patients with Lung Cancer in West Virginia, 1993–2021 (N = 10,463) Characteristics Rural Non-Rural Total p-value (Prob) Age 65.81 (10.02) 65.72 (10.09) 65.72 (10.09) 0.82 Sex 0.41 Male 384 (56.64) 5,699 (58.24) 6,083 (58.14) Female 294 (43.36) 4,086 (41.76) 4,380 (41.86) Marital Status 0.29 Married or Partnered 419 (61.80) 5,847 (59.75) 6,266 (59.89) Not coupled 259 (38.20) 3,938 (40.25) 4,197(40.11) Race/Ethnicity 0.0041 Non-Hispanic White 675 (99.56) 9,524 (97.33) 10,199 (97.48) Non-Hispanic Black 2 (0.29) 225 (2.30) 227 (2.17) Hispanic 0 (0.00) 15 (0.15) 15 (0.14) Other 1 (0.15) 21 (0.21) 22 (0.21) Charlson Comorbidity Index 0.96 0 470 (69.32) 6,793 (69.42) 7,263 (69.42) ≥ 1 208 (30.68) 2,992 (30.58) 3,200 (30.58) Stage 0.012 1 199 (29.35) 3,360 (34.34) 3,559 (34.02) 2 68 (10.03) 1,132 (11.57) 1,200 (11.47) 3 168 (24.78) 2,116 (21.62) 2,284 (21.83) 4 243 (35.84) 3,177 (32.47) 3,420 (32.69) Time to Treatment Yes 26 (8–49) 27 (7–52) 27 (7–52) 0.74 Timely Treatment 0.63 Early 418 (61.65) 5,942 (60.73) 6,360 (60.79) Delayed 260 (38.35) 3,843 (39.27) 4,103 (39.21) Treatment Type 0.065 Systemic 326 (48.08) 4,379 (44.75) 4,705 (44.97) Surgery 234 (34.51) 3,791 (38.74) 4,025 (38.47) Radiation 118 (17.40) 1,584 (16.19) 1,702 (16.27) Other 0 (0.00) 31 (0.32) 31 (0.30) Table 2 Cox Regression of Time to Treatment on Rurality among Patients with Lung Cancer who Received Treatment Time to Treatment Characteristic Univariate Hazard Ratio (95% CI) Multivariate Hazard Ratio (95% CI) Rurality (Ref = Non-rural) Rural 1.05 (0.97–1.14) 1.03 (0.95–1.11) Age 1.00 (1.00–1.00) 1.00 (1.00–1.00) Sex (Ref = Female) Male 1.10 (1.06–1.14) d 1.08 (1.04–1.13) d Race/Ethnicity (Ref = Non-Hispanic White) Non-Hispanic Black 0.84 (0.74–0.96) a 0.88 (0.77-1.00) a Hispanic 1.14 (0.68–1.88) 1.12 (0.68–1.86) Others 1.43 (0.94–2.18) 1.32 (0.87–2.01) Marital Status (Ref = Not married) Married/Partnered 1.05 (1.01–1.09) a 1.03 (0.99–1.08) Charlson Comorbidity Index 0.99 (0.97-1.00) 1.00 (0.98–1.02) Cancer Stage (Ref = 1) 2 1.09 (1.02–1.16) a 1.19 (1.11–1.28) d 3 1.28 (1.22–1.35) d 1.51 (1.42–1.60) d 4 2.05 (1.95–2.15) d 2.38 (2.24–2.53) d Treatment Type (Ref = Other Treatment) Systemic treatment 0.36 (0.25–0.51) d 0.33 (0.23–0.47) d Surgery 0.31 (0.22–0.44) d 0.43 (0.30–0.62) d Radiation 0.46 (0.32–0.65) d 0.48 (0.33–0.68) d a p<0.05; b p<0.01; c p<0.001; d p<0.0001 Table 3 Cox Regression of Overall Survival on Rurality among Patients with Lung Cancer who Received Treatment Survival Characteristic Univariate Hazard Ratio (95% CI) Multivariate Hazard Ratio (95% CI) Rurality (Ref = Non-rural) Rural 1.13 (1.04–1.23) b 1.09 (1.00-1.18) a Age 1.01 (1.01–1.01) d 1.01 (1.01–1.02) d Sex (Ref = Female) Male 1.21 (1.16–1.26) d 1.21 (1.16–1.26) d Race/Ethnicity (Ref = Non-Hispanic White) Non-Hispanic Black 0.96 (0.83–1.11) 0.94 (0.82–1.09) Hispanic 1.47 (0.87–2.49) 1.70 (1.01–2.88) Others 1.17 (0.75–1.83) 1.03 (0.66–1.61) Marital Status (Ref = Not married) Married/Partnered 0.94 (0.90–0.98) b 0.92 (0.88–0.96) c Charlson Comorbidity Index 1.05 (1.03–1.07) d 1.07 (1.05–1.09) d Cancer Stage (Ref = 1) 2 1.53 (1.43–1.65) d 1.58 (1.46–1.70) d 3 2.36 (2.22–2.50) d 2.36 (2.20–2.52) d 4 4.97 (4.70–5.25) d 4.79 (4.47–5.12) d Treatment Type (Ref = Other Treatment) Systemic treatment 0.19 (0.13–0.27) d 0.17 (0.12–0.24) d Surgery 0.09 (0.06–0.13) d 0.16 (1.11–0.22) d Radiation 0.33 (0.23–0.48) d 0.34 (0.24–0.49) d Timely Treatment (Ref = Early) Delayed 0.86 (0.82–0.89) d 0.82 (0.78–0.85) d a p<0.05; b p<0.01; c p<0.001; d p<0.0001 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4492769","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":318390020,"identity":"87ac1da4-65b1-4ae0-96b7-fe61cc4fe4a2","order_by":0,"name":"Sabina Nduaguba","email":"data:image/png;base64,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","orcid":"","institution":"West Virginia University","correspondingAuthor":true,"prefix":"","firstName":"Sabina","middleName":"","lastName":"Nduaguba","suffix":""},{"id":318390025,"identity":"c5ef95f5-f282-44d2-92a0-affb2f298fd0","order_by":1,"name":"Anna Lumudae","email":"","orcid":"","institution":"West Virginia University","correspondingAuthor":false,"prefix":"","firstName":"Anna","middleName":"","lastName":"Lumudae","suffix":""},{"id":318390029,"identity":"09a5b9f2-5568-45d5-966a-76e25c9031f8","order_by":2,"name":"Nicole Stout","email":"","orcid":"","institution":"West Virginia University","correspondingAuthor":false,"prefix":"","firstName":"Nicole","middleName":"","lastName":"Stout","suffix":""}],"badges":[],"createdAt":"2024-05-28 18:55:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4492769/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4492769/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":59800420,"identity":"e23db15a-b28f-4465-a514-8a483bad0983","added_by":"auto","created_at":"2024-07-07 12:40:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":863391,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4492769/v1/84888445-bf03-4e1b-b43e-8f28cee1d632.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Impact of Rural Residency on Time to Lung Cancer Treatment in West Virginia and Patient Survival","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eLung cancer is the second most common cancer diagnosis in the US and the leading cause of cancer death with a five-year survival rate of 28%.[\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] When diagnosed at an early stage when the cancer is localized and confined to a primary site, the five-year survival rate increases to 65% compared to 9% for metastasized cancer.[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] Treatment is dependent on cancer stage, involving surgery or definitive radiation therapy at stages IA to IIB, surgery or definitive chemoradiation for stages IIB to IIIB, and systemic therapy for metastatic lung cancer.[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] The timeliness of lung cancer treatment is associated with survival outcomes, particularly for early stage lung cancer.[\u003cspan additionalcitationids=\"CR7 CR8 CR9 CR10\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] However, 21% of patients with lung cancer receive no treatment resulting in missed opportunities to improve cancer outcomes.[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/p\u003e \u003cp\u003ePatients with cancer who reside in rural areas are at significant risk of poor outcomes as a result of reduced access to care. Poor access to care typically manifests as late cancer diagnosis and delayed time to treatment. West Virginia (WV) is located entirely inside the Appalachian region with about 38% of its population considered rural.[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] The state ranks among the top five states with the highest mortality rates for lung cancer, with a survival rate of 20%, which is considerably lower than the national rate.[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] Twelve percent of patients with lung cancer in WV do not receive treatment.[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] However, the proportion of treated patients for whom treatment is delayed and the impact of delay is not clear. The impact of rurality on timeliness of lung cancer treatment and survival outcomes in WV has also not been elucidated. The aim of this study was to determine the timeliness of treatment among patients with lung cancer as well as the association of rurality with timely receipt of lung cancer treatment and survival in West Virginia (WV).\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Population\u003c/h2\u003e \u003cp\u003eThis was a retrospective cohort study utilizing data from West Virginia Cancer Registry. The WV cancer registry is an all-site registry established by the WV Department of Health and Human Resources which collects data on all cancers diagnosed in WV except basal and squamous cell carcinoma of the skin and in situ cervical cancer. The data collected by WV Cancer Registry includes information on cancer diagnosis and characteristics, patient demographics, facility providing care, and vital status at follow-up. Persons 18 years or older diagnosed with histologically confirmed primary non-small cell lung cancer between 1993 and 2021 who had non-missing data on cancer stage were included in the study. The protocol for the study was reviewed and approved by West Virginia University Office of Human Research Protections and considered to be minimal risk.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eOutcome Variable\u003c/h2\u003e \u003cp\u003eThe outcomes of interest were time to treatment for non-small cell lung cancer and overall survival. Time to treatment was defined as the difference in days between date of cancer diagnosis and date of treatment initiation. Overall survival was defined as the difference in months between date of cancer diagnosis and either date of death or date of last contact, whichever occurs last.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003eMain Independent Variable\u003c/h2\u003e \u003cp\u003eThe main independent variable was rurality. This was based on the last recorded rural-urban continuum code \u0026ndash; 1993, 2003, or 2013.[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] Counties in metro areas and areas with population size of 2,500 or more were classified as urban while areas with population size less than 2,500 were classified as rural.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eCovariates\u003c/h2\u003e \u003cp\u003eThe covariates included age in years, sex at birth, race/ethnicity, marital status, Charlson comorbidity index, cancer stage, and treatment type. Race/ethnicity was classified as non-Hispanic White, Non-Hispanic Black, Hispanic, and others. Marital status was classified as married or partnered vs not coupled (single, separated, divorced, widowed). Charlson comorbidity index was based on ICD-10 codes for secondary diagnosis and comorbidity identified at cancer diagnosis and adapted from the method proposed by Glasheen et al.[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] Cancer stage was based on the American Joint Committee on Cancer 7th edition clinical and pathological classification and staging system for lung cancer, with preference giving to the clinical staging system.[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] Treatment type was classified into systemic therapy, surgery, radiation, and other treatment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis\u003c/h2\u003e \u003cp\u003eFor our analysis, we classified patients based on the timeliness of treatment \u0026ndash; early treatment (treatment within 35 days), late treatment (treatment received later than 35 days), and no treatment.[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] Only persons who received treatment for lung cancer were included in the final analysis, i.e. those classified as receiving early or late treatment, with those who received no treatment excluded. The complete case analytical approach was used by excluding cases with missing values on any of the variables via listwise deletion. Descriptive analysis was conducted using means and standard deviations for continuous variables and frequencies and percentages for categorical variables. Comparisons were made on the descriptive variables between rural and non-rural residents using t-tests for continuous variables, Wilcoxon two-sample test for discrete variables, and chi-square tests for categorical variables. Finally, Cox regression was used to determine the association between rurality and time to treatment and survival in both univariate and multivariate analysis controlling for the covariates. Statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Analysis was conducted using SAS 9.4.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eA total of 56,117 persons were diagnosed with lung cancer between 1993 and 2021. 56,109 were 18 years or older. Of these, 26,253 were diagnosed with histologically confirmed primary NSCLC. Twenty-eight percent (N\u0026thinsp;=\u0026thinsp;7,285) of the 26,253 diagnosed persons did not receive treatment and were excluded. After further excluding those with missing values on relevant data points, 10,463 were retained for analysis. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the characteristics of persons included in the study by rurality status. The average age was 66 years (\u0026plusmn;\u0026thinsp;10). Most were male (58.1%), married or partnered (59.9%), and non-Hispanic white (97.5%). Sixty-nine percent had a CCI of 0 with the majority diagnosed at stages 1 (34.0%) or stage 4 (32.7%). The median time to treatment was 27 days with 61% treated within 35 days (early treatment). Forty-five percent received systemic treatment while 38% and 16% received surgery and radiotherapy, respectively. By rurality status, 2.3% of non-rural residents were non-Hispanic Black compared to 0.3% of rural residents (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). The majority of non-rural residents (34.3%) were diagnosed at stage 1 compared to 29.4% of rural residents (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). There were no significant differences in age, sex, marital status, CCI, time to treatment, timeliness of treatment, and treatment type by rurality status.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the results of the association between rurality and time to treatment among persons with lung cancer who received treatment, controlling for age, sex, race/ethnicity, marital status, CCI, cancer stage, and treatment type. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e also shows the association of rurality and overall survival among persons with lung cancer who received treatment, controlling for the same covariates as well as timeliness of treatment. In both univariate and multivariable analyses, rurality was not associated with time to treatment but was associated with overall survival. After controlling for covariates, rural residency was associated with 9% higher risk of death compared to urban residency (Hazard ratio (HR)\u0026thinsp;=\u0026thinsp;1.09, 95% confidence interval (95% CI)\u0026thinsp;=\u0026thinsp;1.00-1.18). Covariates associated with time to treatment included age, race/ethnicity, cancer stage, and treatment type. Being male was associated with 8% higher probability of treatment (HR\u0026thinsp;=\u0026thinsp;1.08, 95% CI\u0026thinsp;=\u0026thinsp;1.04\u0026ndash;1.13). Being Black was associated was 12% lower probability of treatment compared to being White (HR\u0026thinsp;=\u0026thinsp;0.88, 95% CI\u0026thinsp;=\u0026thinsp;0.77-1.00). The probability of treatment also increased with cancer stage (HR of 1.19\u0026ndash;2.38 for stages 2 through 4 compared to stage 1).\u003c/p\u003e \u003cp\u003eCovariates associated with overall survival included age, sex, marital status, CCI, cancer stage, treatment type, and timeliness of treatment. Each year increase in age was associated with 1% increase in risk of death (HR\u0026thinsp;=\u0026thinsp;1.01, 95% CI\u0026thinsp;=\u0026thinsp;1.01\u0026ndash;1.02). Being male was associated with 21% increase in risk of death (HR\u0026thinsp;=\u0026thinsp;1.21, 95% CI\u0026thinsp;=\u0026thinsp;1.16\u0026ndash;1.26), Being married was associated with 8% lower risk of death (HR\u0026thinsp;=\u0026thinsp;0.92, 95% CI\u0026thinsp;=\u0026thinsp;0.88\u0026ndash;0.96), Each unit increase in CCI was associated with 7% increase in risk of death (HR\u0026thinsp;=\u0026thinsp;1.07, 95% CI\u0026thinsp;=\u0026thinsp;1.05\u0026ndash;1.09). The risk of death increased with cancer stage (HR of 1.58\u0026ndash;4.79 for stages 2 through 4 compared to stage 1). Delayed treatment was associated with 18% lower risk of death (HR\u0026thinsp;=\u0026thinsp;0.82, 95% CI\u0026thinsp;=\u0026thinsp;0.78\u0026ndash;0.85)\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study aimed to evaluation the association of rurality with time to treatment and survival among patients with NSCLC who received treatment in WV. The median time from diagnosis to treatment was 27 days with 61% of study participants treated within 35 days. In other words, treatment was delayed for 39% of those who were treated. The observed time to treatment is within the range of 14 to 39 days observed in other studies.[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan additionalcitationids=\"CR19 CR20 CR21 CR22\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] Rurality was not associated with time to treatment but was associated with 9% higher risk of death. Contrary to expectation, delayed treatment was associated with 18% lower risk of death suggesting that there may confounding factors that explain outcomes among those whose treatment was delayed.\u003c/p\u003e \u003cp\u003eOne potential explanation for the unexpected finding of improved survival with delayed treatment is the clinical status of those whose treatment was timely vs those for whom treatment was delayed. Our study population included a significantly higher proportion (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) of those diagnosed at stage 4 (70.1%) who received treatment within 35 days, compared to those diagnosed at stages 1 (55.9%), 2 (54.2%) (results not shown), and 3 (57.9%) Hence, those who received timely treatment comprised of a large number of advanced cases (37.7%) who typically have poor prognosis.[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] This potentially explains the counterintuitive finding of increased risk of death with early treatment. Several studies similarly report that treatment for patients with early-stage lung cancer is often delayed relative to those who with late-stage diagnosis.[\u003cspan additionalcitationids=\"CR26 CR27 CR28 CR29 CR30\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eAs expected, rurality was associated with a higher risk of death, reflecting challenges such as long distance to tertiary care clinics, lower socioeconomic status, and lack of or limited health insurance.[\u003cspan additionalcitationids=\"CR33 CR34\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] These challenges contribute to health care access disparities that affect the timeliness of receiving care and continued surveillance and monitoring. However, we did not observe any association between rurality and time to treatment in this study. Our observation of poor survival with rural residency may, therefore, be as a result of other factors that result from poor access to care for rural residents such as delayed cancer diagnosis.[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] In our study, a significantly higher proportion of rural residents were diagnosed at stages 3 or 4 compared to non-rural residents (61% vs 54%). Cancer stage was also an important predictor of overall survival, implying that late diagnosis due to rural residency impacted prognosis.\u003c/p\u003e \u003cp\u003eA particular strength of our study is the use of state-wide cancer registry data. Thirty-eight percent of the WV population is considered rural, making the state registry data ideal for a study of the impact of rurality on the timeliness of treatment and lung cancer outcomes.[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] One limitation of the study is that data collection began at cancer diagnosis. Delays to receiving treatment begin much earlier than the point of diagnosis such as initial screening and/or suspicion of cancer, referral to specialist, and diagnostics for confirmatory diagnosis. While most of our study participants were treated with 35 days of lung cancer diagnosis, it has been shown that the time interval from symptom onset to first abnormal test and from first abnormal test to treatment can each be as long as two months.[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] Further investigation into the delay points along the lung cancer continuum according to rurality status is needed to better understand how the process of care may impact rural patients with lung cancer. Further, this was a retrospective study involving the use of data collected for surveillance purposes. Data on potentially confounding geographic variables such as distance to clinic and neighborhood hospital density that impact timeliness of receiving medical care were not collected or controlled for. Finally, the association of rurality with survival does not mean causation. We believe that there are mediating factors such as poor access to care[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] and other socio-economic factors[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] that more directly explain poor survival outcomes observed among rural residents.\u003c/p\u003e \u003cp\u003eTo conclude, rurality was not associated with time to treatment. The observed association of delayed treatment with survival was likely due to confounding by the stronger association between cancer stage and survival since most patients with delayed treatment were early stage. Despite these null and counterintuitive findings, rurality remained associated with poor survival, reflecting issues with poor access to health care that manifested as delayed diagnosis. Interventions that focus on screening and early diagnosis of lung cancer would likely be more effective at improving prognosis and survival outcomes for persons who reside in rural areas.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConsent to Participate Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA waiver of HIPAA authorization was granted for the study by West Virginia University Office of Human Research Protections as the study was considered to be minimal risk.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was provided for this study\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are not available from the authors because restrictions apply to the availability of these data, which were provided by West Virginia Cancer Registry, and so are not publicly available.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflicts of interest to declare\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eSN conceptualized and designed the study, procured and analyzed data, and led the writing of the initial draft. AL supported in the writing of the initial draft and reviewed the final version of the manuscript. NS reviewed the manuscript and provided expert input in rural health disparities.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAmerican Lung Association (2024) State of Lung Cancer, 2023;[cited 2024 February 20]. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.lung.org/research/state-of-lung-cancer\u003c/span\u003e\u003cspan address=\"https://www.lung.org/research/state-of-lung-cancer\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGBD (2019) Cancer Collaborators Cancer Incidence, Mortality, Years of Life Lost, Years Lived with Disability, and Disability-Adjusted Life Years for 29 Cancer Groups from 2010 to 2019: A Systematic Analysis of Cancer Burden Globally, Nationally, and by Socio-Demographic Index for the Global Burden of Disease Study 2019. 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Am J Clin Oncol 35(4):373\u0026ndash;377. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/:10.1097/COC.0b013e3182143cce\u003c/span\u003e\u003cspan address=\":10.1097/COC.0b013e3182143cce\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMuluk S, Sabik L, Chen Q, Jacobs B, Sun Z, Drake C (2022) Disparities in geographic access to medical oncologists. Health Serv Res 57(5):1035\u0026ndash;1044. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/:10.1111/1475-6773.13991\u003c/span\u003e\u003cspan address=\":10.1111/1475-6773.13991\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAfshar N, English DR, Milne RL (2021) Factors Explaining Socio-Economic Inequalities in Cancer Survival: A Systematic Review. Cancer Control 28:10732748211011956. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/:10.1177/10732748211011956\u003c/span\u003e\u003cspan address=\":10.1177/10732748211011956\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCharacteristics of Patients with Lung Cancer in West Virginia, 1993\u0026ndash;2021 (N\u0026thinsp;=\u0026thinsp;10,463)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNon-Rural\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value (Prob)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65.81 (10.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65.72 (10.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65.72 (10.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e384 (56.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,699 (58.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,083 (58.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e294 (43.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,086 (41.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,380 (41.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarried or Partnered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e419 (61.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,847 (59.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,266 (59.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot coupled\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e259 (38.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,938 (40.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,197(40.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace/Ethnicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0041\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-Hispanic White\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e675 (99.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9,524 (97.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10,199 (97.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-Hispanic Black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (0.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e225 (2.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e227 (2.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (0.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (0.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (0.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (0.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22 (0.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharlson Comorbidity Index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e470 (69.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,793 (69.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,263 (69.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e208 (30.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,992 (30.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,200 (30.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eStage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e199 (29.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,360 (34.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,559 (34.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68 (10.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,132 (11.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,200 (11.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e168 (24.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,116 (21.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,284 (21.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e243 (35.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,177 (32.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,420 (32.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime to Treatment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26 (8\u0026ndash;49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27 (7\u0026ndash;52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27 (7\u0026ndash;52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTimely Treatment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEarly\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e418 (61.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,942 (60.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,360 (60.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDelayed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e260 (38.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,843 (39.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,103 (39.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment Type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSystemic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e326 (48.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,379 (44.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,705 (44.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSurgery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e234 (34.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,791 (38.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,025 (38.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRadiation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e118 (17.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,584 (16.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,702 (16.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31 (0.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31 (0.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCox Regression of Time to Treatment on Rurality among Patients with Lung Cancer who Received Treatment\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eTime to Treatment\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUnivariate\u003c/p\u003e\n \u003cp\u003eHazard Ratio (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMultivariate\u003c/p\u003e\n \u003cp\u003eHazard Ratio (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRurality (Ref\u0026thinsp;=\u0026thinsp;Non-rural)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.05 (0.97\u0026ndash;1.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.03 (0.95\u0026ndash;1.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00 (1.00\u0026ndash;1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00 (1.00\u0026ndash;1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex (Ref\u0026thinsp;=\u0026thinsp;Female)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.10 (1.06\u0026ndash;1.14)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.08 (1.04\u0026ndash;1.13)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace/Ethnicity\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(Ref\u0026thinsp;=\u0026thinsp;Non-Hispanic White)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-Hispanic Black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.84 (0.74\u0026ndash;0.96)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ea\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.88 (0.77-1.00)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ea\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.14 (0.68\u0026ndash;1.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.12 (0.68\u0026ndash;1.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.43 (0.94\u0026ndash;2.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.32 (0.87\u0026ndash;2.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital Status (Ref\u0026thinsp;=\u0026thinsp;Not married)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarried/Partnered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.05 (1.01\u0026ndash;1.09)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ea\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.03 (0.99\u0026ndash;1.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharlson Comorbidity Index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.99 (0.97-1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00 (0.98\u0026ndash;1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCancer Stage (Ref\u0026thinsp;=\u0026thinsp;1)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.09 (1.02\u0026ndash;1.16)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ea\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.19 (1.11\u0026ndash;1.28)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.28 (1.22\u0026ndash;1.35)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.51 (1.42\u0026ndash;1.60)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.05 (1.95\u0026ndash;2.15)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.38 (2.24\u0026ndash;2.53)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment Type (Ref\u0026thinsp;=\u0026thinsp;Other Treatment)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSystemic treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.36 (0.25\u0026ndash;0.51)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.33 (0.23\u0026ndash;0.47)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSurgery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.31 (0.22\u0026ndash;0.44)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.43 (0.30\u0026ndash;0.62)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRadiation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.46 (0.32\u0026ndash;0.65)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.48 (0.33\u0026ndash;0.68)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003e\u003csup\u003ea\u003c/sup\u003ep\u0026lt;0.05; \u003csup\u003eb\u003c/sup\u003ep\u0026lt;0.01; \u003csup\u003ec\u003c/sup\u003ep\u0026lt;0.001; \u003csup\u003ed\u003c/sup\u003ep\u0026lt;0.0001\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCox Regression of Overall Survival on Rurality among Patients with Lung Cancer who Received Treatment\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eSurvival\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUnivariate\u003c/p\u003e\n \u003cp\u003eHazard Ratio (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMultivariate\u003c/p\u003e\n \u003cp\u003eHazard Ratio (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRurality (Ref\u0026thinsp;=\u0026thinsp;Non-rural)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.13 (1.04\u0026ndash;1.23)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003eb\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.09 (1.00-1.18)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ea\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.01 (1.01\u0026ndash;1.01)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.01 (1.01\u0026ndash;1.02)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex (Ref\u0026thinsp;=\u0026thinsp;Female)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.21 (1.16\u0026ndash;1.26)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.21 (1.16\u0026ndash;1.26)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace/Ethnicity\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(Ref\u0026thinsp;=\u0026thinsp;Non-Hispanic White)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-Hispanic Black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.96 (0.83\u0026ndash;1.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.94 (0.82\u0026ndash;1.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.47 (0.87\u0026ndash;2.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.70 (1.01\u0026ndash;2.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.17 (0.75\u0026ndash;1.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.03 (0.66\u0026ndash;1.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital Status (Ref\u0026thinsp;=\u0026thinsp;Not married)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarried/Partnered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.94 (0.90\u0026ndash;0.98)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003eb\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.92 (0.88\u0026ndash;0.96)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ec\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharlson Comorbidity Index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.05 (1.03\u0026ndash;1.07)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.07 (1.05\u0026ndash;1.09)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCancer Stage (Ref\u0026thinsp;=\u0026thinsp;1)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.53 (1.43\u0026ndash;1.65)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.58 (1.46\u0026ndash;1.70)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.36 (2.22\u0026ndash;2.50)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.36 (2.20\u0026ndash;2.52)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.97 (4.70\u0026ndash;5.25)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.79 (4.47\u0026ndash;5.12)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment Type (Ref\u0026thinsp;=\u0026thinsp;Other Treatment)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSystemic treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.19 (0.13\u0026ndash;0.27)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.17 (0.12\u0026ndash;0.24)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSurgery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.09 (0.06\u0026ndash;0.13)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.16 (1.11\u0026ndash;0.22)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRadiation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.33 (0.23\u0026ndash;0.48)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.34 (0.24\u0026ndash;0.49)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTimely Treatment (Ref\u0026thinsp;=\u0026thinsp;Early)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDelayed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.86 (0.82\u0026ndash;0.89)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.82 (0.78\u0026ndash;0.85)\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003e\u003csup\u003ea\u003c/sup\u003ep\u0026lt;0.05; \u003csup\u003eb\u003c/sup\u003ep\u0026lt;0.01; \u003csup\u003ec\u003c/sup\u003ep\u0026lt;0.001; \u003csup\u003ed\u003c/sup\u003ep\u0026lt;0.0001\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Rural disparities, Lung cancer, Health care access, Cancer epidemiology","lastPublishedDoi":"10.21203/rs.3.rs-4492769/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4492769/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose\u003c/strong\u003e: To examine the association of rurality with timely receipt of lung cancer treatment and survival in West Virginia (WV).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e:\u003cstrong\u003e \u003c/strong\u003eA retrospective study was conducted using 1993-2021 WV Cancer Registry data to identify persons diagnosed with NSCLC who received treatment. Participants were classified by rurality (rural vs non-rural), and time to treatment from diagnosis was dichotomized as early treatment (\u0026lt;35 days) or delayed treatment (≥35 days). Descriptive statistics and survival analysis (with univariate and multivariate Cox regression were used to address study objectives.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e:\u003cstrong\u003e \u003c/strong\u003eOf 10,463 participants, 678 (6.5%) were rural residents. The majority were male (58.1%), married or partnered (59.9%), and non-Hispanic white (97.5%). 61% received early treatment. 45%, 38%, and 16% received systemic therapy, surgery, and radiation, respectively. There were significantly more non-Hispanic white (99.6% vs 97.3%) patients residing in rural areas compared to non-rural areas, and fewer rural residents were diagnosed at stages 1 (29.4% vs 34.3%) or 2 (10.0% vs 11.6%).\u003c/p\u003e\n\u003cp\u003eRurality was not associated with time to treatment but was associated with 9% increase in hazard of death (HR=1.09, 95% CI=1.00-1.18). Significant covariates associated with increasing hazard of treatment included being male (HR=1.08, 95% CI=1.04-1.13) and cancer stage (HR range=1.19-2.38, while being Black and receiving surgery (0.43, 0.30-0.62), radiation (0.48, 0.33-0.68), or systemic therapy (0.33,0.23-0.47) (compared to other treatment) were each associated with reduced hazard of treatment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: In WV, rurality affects lung cancer outcomes but not time to treatment increasing risk of death for NSCLC patients by 9%.\u003c/p\u003e","manuscriptTitle":"The Impact of Rural Residency on Time to Lung Cancer Treatment in West Virginia and Patient Survival","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-26 09:56:17","doi":"10.21203/rs.3.rs-4492769/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2778f241-2255-4fd0-9439-2f3f13b789e0","owner":[],"postedDate":"June 26th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-07-07T12:32:01+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-26 09:56:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4492769","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4492769","identity":"rs-4492769","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}