Skip to main content
Top
Published in: Cancer Causes & Control 3/2013

01-03-2013 | Original Paper

The modifying effect of patient location on stage-specific survival following colorectal cancer using geosurvival models

Authors: Lung-Chang Chien, Mario Schootman, Sandi L. Pruitt

Published in: Cancer Causes & Control | Issue 3/2013

Login to get access

Abstract

Colorectal cancer (CRC) is the third leading cause of cancer death in the US, and stage at diagnosis is the primary prognostic factor. To date, the interplay between geographic place and individual characteristics such as cancer stage with CRC survival is unexplored. We used a Bayesian geosurvival statistical model to evaluate whether the spatial patterns of CRC survival at the census tract level varies by stage at diagnosis (in situ/local, regional, distant), controlling for patient characteristics, surveillance test use, and treatment using linked 1991–2005 SEER-Medicare data of patients ≥ 66 years old in two US metropolitan areas. The spatial pattern of survival varied by stage at diagnosis for both cancer sites and registries. Significant spatial effects were identified in all census tracts for colon cancer and the majority of census tracts for rectal cancer. Geographic disparities appeared to be highest for distant-stage rectal cancer. Compared to those with in situ/local stage in the same census tracts, patients with distant-stage cancer were at most 7.73 times and 4.69 times more likely to die of colon and rectal cancer, respectively. Moreover, frailty areas for CRC at in situ/local stage more likely have a higher relative risk at regional stage, but not at distant stage. We identified geographic areas with excessive risk of CRC death and demonstrated that spatial patterns varied by both cancer type and cancer stage. More research is needed to understand the moderating pathways between geographic and individual-level factors on CRC survival.
Literature
1.
2.
go back to reference Taplin SH, Haggstrom D, Jacobs T, Determan A, Granger J, Montalvo W et al (2008) Implementing colorectal cancer screening in community health centers: addressing cancer health disparities through a regional cancer collaborative. Med Care 46:S74–S83PubMedCrossRef Taplin SH, Haggstrom D, Jacobs T, Determan A, Granger J, Montalvo W et al (2008) Implementing colorectal cancer screening in community health centers: addressing cancer health disparities through a regional cancer collaborative. Med Care 46:S74–S83PubMedCrossRef
3.
go back to reference Alexander DD, Waterbor J, Hughes T, Funkhouser E, Grizzle W, Manne U (2007) African-American and Caucasian disparities in colorectal cancer mortality and survival by data source: an epidemiologic review. Cancer Biomar 3:301–313 Alexander DD, Waterbor J, Hughes T, Funkhouser E, Grizzle W, Manne U (2007) African-American and Caucasian disparities in colorectal cancer mortality and survival by data source: an epidemiologic review. Cancer Biomar 3:301–313
4.
go back to reference Brenner H, Hoffmeister M, Arndt V, Haug U (2007) Gender differences in colorectal cancer: implications for age at initiation of screening. Br J Cancer 96:828–831PubMedCrossRef Brenner H, Hoffmeister M, Arndt V, Haug U (2007) Gender differences in colorectal cancer: implications for age at initiation of screening. Br J Cancer 96:828–831PubMedCrossRef
5.
go back to reference Ward E, Jemal A, Cokkinides V, Singh GK, Cardinez C, Ghafoor A et al (2004) Cancer disparities by race/ethnicity and socioeconomic status. CA-Cancer J Clin 54:78–93PubMedCrossRef Ward E, Jemal A, Cokkinides V, Singh GK, Cardinez C, Ghafoor A et al (2004) Cancer disparities by race/ethnicity and socioeconomic status. CA-Cancer J Clin 54:78–93PubMedCrossRef
6.
go back to reference Hsu CE, Mas FS, Hickey JM, Miller JA, Lai D (2006) Surveillance of the colorectal cancer disparities among demographic subgroups: a spatial analysis. South Med J 99:949–956PubMedCrossRef Hsu CE, Mas FS, Hickey JM, Miller JA, Lai D (2006) Surveillance of the colorectal cancer disparities among demographic subgroups: a spatial analysis. South Med J 99:949–956PubMedCrossRef
7.
go back to reference Hernandez MN, Roy Chowdhury R, Fleming LE, Griffith DA (2011) Colorectal cancer and socioeconomic status in Miami-Dade County: neighborhood-level associations before and after the Welfare Reform Act. Appl Geogr 31:1019–1025CrossRef Hernandez MN, Roy Chowdhury R, Fleming LE, Griffith DA (2011) Colorectal cancer and socioeconomic status in Miami-Dade County: neighborhood-level associations before and after the Welfare Reform Act. Appl Geogr 31:1019–1025CrossRef
8.
go back to reference Naishadham D, Lansdorp-Vogelaar I, Siegel R, Cokkinides V, Jemal A (2011) State disparities in colorectal cancer mortality patterns in the United States. Cancer Epidem Biomar 20:1296–1302CrossRef Naishadham D, Lansdorp-Vogelaar I, Siegel R, Cokkinides V, Jemal A (2011) State disparities in colorectal cancer mortality patterns in the United States. Cancer Epidem Biomar 20:1296–1302CrossRef
9.
go back to reference Semrad TJ, Tancredi DJ, Baldwin L-M, Green P, Fenton JJ (2011) Geographic variation of racial/ethnic disparities in colorectal cancer testing among medicare enrollees. Cancer 117:1755–1763PubMedCrossRef Semrad TJ, Tancredi DJ, Baldwin L-M, Green P, Fenton JJ (2011) Geographic variation of racial/ethnic disparities in colorectal cancer testing among medicare enrollees. Cancer 117:1755–1763PubMedCrossRef
10.
go back to reference López-Carr D, Davis J, Jankowska MM, Grant L, López-Carr AC, Clark M (2012) Space versus place in complex human–natural systems: spatial and multi-level models of tropical land use and cover change (LUCC) in Guatemala. Ecol Model 229:64–75CrossRef López-Carr D, Davis J, Jankowska MM, Grant L, López-Carr AC, Clark M (2012) Space versus place in complex human–natural systems: spatial and multi-level models of tropical land use and cover change (LUCC) in Guatemala. Ecol Model 229:64–75CrossRef
11.
go back to reference Diez-Roux AV (1998) Bringing context back into epidemiology: variables and fallacies in multilevel analysis. Am J Public Health 88:216–222PubMedCrossRef Diez-Roux AV (1998) Bringing context back into epidemiology: variables and fallacies in multilevel analysis. Am J Public Health 88:216–222PubMedCrossRef
12.
go back to reference Oakes JM (2004) The (mis)estimation of neighborhood effects: causal inference for a practicable social epidemiology. Soc Sci Med 58:1929–1952PubMedCrossRef Oakes JM (2004) The (mis)estimation of neighborhood effects: causal inference for a practicable social epidemiology. Soc Sci Med 58:1929–1952PubMedCrossRef
13.
go back to reference Chaix B, Merlo J, Chauvin P (2005) Comparison of a spatial approach with the multilevel approach for investigating place effects on health: the example of healthcare utilisation in France. J Epidemiol Commun Health 59:517–526CrossRef Chaix B, Merlo J, Chauvin P (2005) Comparison of a spatial approach with the multilevel approach for investigating place effects on health: the example of healthcare utilisation in France. J Epidemiol Commun Health 59:517–526CrossRef
14.
go back to reference Huang L, Kulldorff M, Gregorio D (2007) A spatial scan statistic for survival data. Biometrics 63:109–118PubMedCrossRef Huang L, Kulldorff M, Gregorio D (2007) A spatial scan statistic for survival data. Biometrics 63:109–118PubMedCrossRef
15.
go back to reference Osnes K, Aalen OO (1999) Spatial smoothing of cancer survival: a Bayesian approach. Stat Med 18:2087–2099PubMedCrossRef Osnes K, Aalen OO (1999) Spatial smoothing of cancer survival: a Bayesian approach. Stat Med 18:2087–2099PubMedCrossRef
16.
go back to reference Banerjee S, Wall MM, Carlin BP (2003) Frailty modeling for spatially correlated survival data, with application to infant mortality in Minnesota. Biostatistics 4:123–142PubMedCrossRef Banerjee S, Wall MM, Carlin BP (2003) Frailty modeling for spatially correlated survival data, with application to infant mortality in Minnesota. Biostatistics 4:123–142PubMedCrossRef
17.
go back to reference Adebayo SB, Fahrmeir L (2005) Analysing child mortality in Nigeria with geoadditive discrete-time survival models. Stat Med 24:709–728PubMedCrossRef Adebayo SB, Fahrmeir L (2005) Analysing child mortality in Nigeria with geoadditive discrete-time survival models. Stat Med 24:709–728PubMedCrossRef
18.
go back to reference Crook AM, Knorr-Held L, Hemingway H (2003) Measuring spatial effects in time to event data: a case study using months from angiography to coronary artery bypass graft (CABG). Stat Med 22:2943–2961PubMedCrossRef Crook AM, Knorr-Held L, Hemingway H (2003) Measuring spatial effects in time to event data: a case study using months from angiography to coronary artery bypass graft (CABG). Stat Med 22:2943–2961PubMedCrossRef
19.
go back to reference Lian M, Schootman M, Doubeni CA, Park Y, Major JM, Torres Stone RA et al (2011) Geographic variation in colorectal cancer survival and the role of small-area socioeconomic deprivation: a multilevel survival analysis of the NIH-AARP diet and health study cohort. Am J Epidemiol 174:828–838PubMedCrossRef Lian M, Schootman M, Doubeni CA, Park Y, Major JM, Torres Stone RA et al (2011) Geographic variation in colorectal cancer survival and the role of small-area socioeconomic deprivation: a multilevel survival analysis of the NIH-AARP diet and health study cohort. Am J Epidemiol 174:828–838PubMedCrossRef
20.
go back to reference Hennerfeind A, Brezger A, Fahrmeir L (2006) Geoadditive survival models. J Am Stat Assoc 101:1065–1075CrossRef Hennerfeind A, Brezger A, Fahrmeir L (2006) Geoadditive survival models. J Am Stat Assoc 101:1065–1075CrossRef
21.
go back to reference Hofner B, Kneib T, Hartl W, Küchenhoff H (2011) Building Cox-type structured hazard regression models with time-varying effects. Stat Model 11:3–24CrossRef Hofner B, Kneib T, Hartl W, Küchenhoff H (2011) Building Cox-type structured hazard regression models with time-varying effects. Stat Model 11:3–24CrossRef
22.
go back to reference Hennerfeind A, Held L, Sauleau EA (2008) A Bayesian analysis of relative cancer survival with geoadditive models. Stat Model 8:117–139CrossRef Hennerfeind A, Held L, Sauleau EA (2008) A Bayesian analysis of relative cancer survival with geoadditive models. Stat Model 8:117–139CrossRef
23.
go back to reference Kandala N-B, Ghilagaber G (2006) A geo-additive bayesian discrete-time survival model and its application to spatial analysis of childhood mortality in Malawi. Qual Quant 40:935–957CrossRef Kandala N-B, Ghilagaber G (2006) A geo-additive bayesian discrete-time survival model and its application to spatial analysis of childhood mortality in Malawi. Qual Quant 40:935–957CrossRef
24.
go back to reference Doubeni CA, Schootman M, Major JM, Torres Stone RA, Laiyemo AO, Park Y et al (2011) Health status, neighborhood socioeconomic context, and premature mortality in the United States: the National Institutes of Health-AARP Diet and Health Study. Am J Public Health 102(4):680–688PubMedCrossRef Doubeni CA, Schootman M, Major JM, Torres Stone RA, Laiyemo AO, Park Y et al (2011) Health status, neighborhood socioeconomic context, and premature mortality in the United States: the National Institutes of Health-AARP Diet and Health Study. Am J Public Health 102(4):680–688PubMedCrossRef
25.
go back to reference Ivory VC, Collings SC, Blakely T, Dew K (2011) When does neighbourhood matter? Multilevel relationships between neighbourhood social fragmentation and mental health. Soc Sci Med 72:1993–2002PubMedCrossRef Ivory VC, Collings SC, Blakely T, Dew K (2011) When does neighbourhood matter? Multilevel relationships between neighbourhood social fragmentation and mental health. Soc Sci Med 72:1993–2002PubMedCrossRef
26.
go back to reference Matheson FI, White HL, Moineddin R, Dunn JR, Glazier RH (2012) Drinking in context: the influence of gender and neighbourhood deprivation on alcohol consumption. J Epidemiol Commun Health 66(6):e4CrossRef Matheson FI, White HL, Moineddin R, Dunn JR, Glazier RH (2012) Drinking in context: the influence of gender and neighbourhood deprivation on alcohol consumption. J Epidemiol Commun Health 66(6):e4CrossRef
27.
go back to reference Schootman M, Andresen EM, Wolinsky FD, Miller JP, Yan Y, Miller DK (2010) Neighborhood conditions, diabetes, and risk of lower-body functional limitations among middle-aged African Americans: a cohort study. BMC Public Health 10:283PubMedCrossRef Schootman M, Andresen EM, Wolinsky FD, Miller JP, Yan Y, Miller DK (2010) Neighborhood conditions, diabetes, and risk of lower-body functional limitations among middle-aged African Americans: a cohort study. BMC Public Health 10:283PubMedCrossRef
28.
go back to reference Winkleby M, Cubbin C, Ahn D (2006) Effect of cross-level interaction between individual and neighborhood socioeconomic status on adult mortality rates. Am J Public Health 96:2145–2153PubMedCrossRef Winkleby M, Cubbin C, Ahn D (2006) Effect of cross-level interaction between individual and neighborhood socioeconomic status on adult mortality rates. Am J Public Health 96:2145–2153PubMedCrossRef
29.
go back to reference Marcella S, Miller JE (2001) Racial differences in colorectal cancer mortality: the importance of stage and socioeconomic status. J Clin Epidemiol 54:359–366PubMedCrossRef Marcella S, Miller JE (2001) Racial differences in colorectal cancer mortality: the importance of stage and socioeconomic status. J Clin Epidemiol 54:359–366PubMedCrossRef
30.
go back to reference Schwartz KL, Crossley-May H, Vigneau FD, Brown K, Banerjee M (2003) Race, socioeconomic status and stage at diagnosis for five common malignancies. Cancer Causes Control 14:761–766PubMedCrossRef Schwartz KL, Crossley-May H, Vigneau FD, Brown K, Banerjee M (2003) Race, socioeconomic status and stage at diagnosis for five common malignancies. Cancer Causes Control 14:761–766PubMedCrossRef
32.
go back to reference DeChello LM, Sheehan TJ (2007) Spatial analysis of colorectal cancer incidence and proportion of late-stage in Massachusetts residents: 1995–1998. Int J Health Geogr 6:20PubMedCrossRef DeChello LM, Sheehan TJ (2007) Spatial analysis of colorectal cancer incidence and proportion of late-stage in Massachusetts residents: 1995–1998. Int J Health Geogr 6:20PubMedCrossRef
33.
go back to reference Elferink MA, Pukkala E, Klaase JM, Siesling S (2011) Spatial variation in stage distribution in colorectal cancer in the Netherlands. Eur J Cancer 48(8):1119–1125PubMedCrossRef Elferink MA, Pukkala E, Klaase JM, Siesling S (2011) Spatial variation in stage distribution in colorectal cancer in the Netherlands. Eur J Cancer 48(8):1119–1125PubMedCrossRef
34.
go back to reference Rushton G, Peleg I, Banerjee A, Smith G, West M (2004) Analyzing geographic patterns of disease incidence: rates of late-stage colorectal cancer in Iowa. J Med Syst 28:223–236PubMedCrossRef Rushton G, Peleg I, Banerjee A, Smith G, West M (2004) Analyzing geographic patterns of disease incidence: rates of late-stage colorectal cancer in Iowa. J Med Syst 28:223–236PubMedCrossRef
35.
go back to reference Henry KA, Niu X, Boscoe FP (2009) Geographic disparities in colorectal cancer survival. Int J Health Geogr 8:48PubMedCrossRef Henry KA, Niu X, Boscoe FP (2009) Geographic disparities in colorectal cancer survival. Int J Health Geogr 8:48PubMedCrossRef
36.
go back to reference Schootman M, Lian M, Deshpande A, McQueen A, Pruitt S, Jeffe D (2011) Temporal trends in geographic disparities in small-area-level colorectal cancer incidence and mortality in the United States. Cancer Causes Control 22:1173–1181PubMedCrossRef Schootman M, Lian M, Deshpande A, McQueen A, Pruitt S, Jeffe D (2011) Temporal trends in geographic disparities in small-area-level colorectal cancer incidence and mortality in the United States. Cancer Causes Control 22:1173–1181PubMedCrossRef
37.
go back to reference Leung EY, Crozier JE, Talwar D, O’Reilly DS, McKee RF, Horgan PG et al (2008) Vitamin antioxidants, lipid peroxidation, tumour stage, the systemic inflammatory response and survival in patients with colorectal cancer. Int J Cancer 123:2460–2464PubMedCrossRef Leung EY, Crozier JE, Talwar D, O’Reilly DS, McKee RF, Horgan PG et al (2008) Vitamin antioxidants, lipid peroxidation, tumour stage, the systemic inflammatory response and survival in patients with colorectal cancer. Int J Cancer 123:2460–2464PubMedCrossRef
38.
go back to reference Skrzydlewska E, Sulkowski S, Koda M, Zalewski B, Kanczuga-Koda L, Sulkowska M (2005) Lipid peroxidation and antioxidant status in colorectal cancer. World J Gastroenterol 11:403–406PubMed Skrzydlewska E, Sulkowski S, Koda M, Zalewski B, Kanczuga-Koda L, Sulkowska M (2005) Lipid peroxidation and antioxidant status in colorectal cancer. World J Gastroenterol 11:403–406PubMed
39.
go back to reference Vrieling A, Kampman E (2010) The role of body mass index, physical activity, and diet in colorectal cancer recurrence and survival: a review of the literature. Am J Clin Nutr 92:471–490PubMed Vrieling A, Kampman E (2010) The role of body mass index, physical activity, and diet in colorectal cancer recurrence and survival: a review of the literature. Am J Clin Nutr 92:471–490PubMed
40.
go back to reference Warren JL, Klabunde CN, Schrag D, Bach PB, Riley GF (2002) Overview of the SEER-Medicare data: content, research applications, and generalizability to the United States elderly population. Med Care 40(8 Suppl): IV-3–18 Warren JL, Klabunde CN, Schrag D, Bach PB, Riley GF (2002) Overview of the SEER-Medicare data: content, research applications, and generalizability to the United States elderly population. Med Care 40(8 Suppl): IV-3–18
43.
go back to reference Fritz AG (2000) International classification of diseases for oncology: ICD-O, 3rd edn. World Health Organization, Geneva Fritz AG (2000) International classification of diseases for oncology: ICD-O, 3rd edn. World Health Organization, Geneva
44.
go back to reference Hodgson DC, Fuchs CS, Ayanian JZ (2001) Impact of patient and provider characteristics on the treatment and outcomes of colorectal cancer. J Natl Cancer Inst 93:501–515PubMedCrossRef Hodgson DC, Fuchs CS, Ayanian JZ (2001) Impact of patient and provider characteristics on the treatment and outcomes of colorectal cancer. J Natl Cancer Inst 93:501–515PubMedCrossRef
45.
go back to reference Polite BN, Dignam JJ, Olopade OI (2006) Colorectal cancer model of health disparities: understanding mortality differences in minority populations. J Clin Oncol 24:2179–2187PubMedCrossRef Polite BN, Dignam JJ, Olopade OI (2006) Colorectal cancer model of health disparities: understanding mortality differences in minority populations. J Clin Oncol 24:2179–2187PubMedCrossRef
46.
go back to reference Charlson ME, Pompei P, Ales KL, MacKenzie CR (1987) A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 40:373–383PubMedCrossRef Charlson ME, Pompei P, Ales KL, MacKenzie CR (1987) A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 40:373–383PubMedCrossRef
47.
go back to reference Gomez SL, O’Malley CD, Stroup A, Shema SJ, Satariano WA (2007) Longitudinal, population-based study of racial/ethnic differences in colorectal cancer survival: impact of neighborhood socioeconomic status, treatment and comorbidity. BMC Cancer 7:193PubMedCrossRef Gomez SL, O’Malley CD, Stroup A, Shema SJ, Satariano WA (2007) Longitudinal, population-based study of racial/ethnic differences in colorectal cancer survival: impact of neighborhood socioeconomic status, treatment and comorbidity. BMC Cancer 7:193PubMedCrossRef
48.
go back to reference Salz T, Weinberger M, Ayanian JZ, Brewer NT, Earle CC, Elston Lafata J et al (2010) Variation in use of surveillance colonoscopy among colorectal cancer survivors in the United States. BMC Health Serv Res 10:256PubMedCrossRef Salz T, Weinberger M, Ayanian JZ, Brewer NT, Earle CC, Elston Lafata J et al (2010) Variation in use of surveillance colonoscopy among colorectal cancer survivors in the United States. BMC Health Serv Res 10:256PubMedCrossRef
49.
go back to reference Cox D, Oakes D (1984) Analysis of survival data. Chapman and Hall, London Cox D, Oakes D (1984) Analysis of survival data. Chapman and Hall, London
50.
go back to reference Kindermann R, Snell JL (1980) Markov random fields and their applications. American Mathematical Society, ProvidenceCrossRef Kindermann R, Snell JL (1980) Markov random fields and their applications. American Mathematical Society, ProvidenceCrossRef
51.
go back to reference Gamerman D (1997) Sampling from the posterior distribution in generalized linear mixed models. Stat Comput 7:57–68CrossRef Gamerman D (1997) Sampling from the posterior distribution in generalized linear mixed models. Stat Comput 7:57–68CrossRef
52.
go back to reference Knorr-Held L (1999) Conditional prior proposals in dynamic models. Scand J Stat 26:129–144CrossRef Knorr-Held L (1999) Conditional prior proposals in dynamic models. Scand J Stat 26:129–144CrossRef
53.
go back to reference Musio M, Sauleau EA, Buemi A (2010) Bayesian semi-parametric ZIP models with space-time interactions: an application to cancer registry data. Math Med Biol 27:181–194PubMedCrossRef Musio M, Sauleau EA, Buemi A (2010) Bayesian semi-parametric ZIP models with space-time interactions: an application to cancer registry data. Math Med Biol 27:181–194PubMedCrossRef
54.
go back to reference Pankratz VS, Andrade MD, Therneau TM (2005) Random-effects Cox propotional hazards model: general variance components methods for time-to-event data. Genetic Epidemiol 28:97–109CrossRef Pankratz VS, Andrade MD, Therneau TM (2005) Random-effects Cox propotional hazards model: general variance components methods for time-to-event data. Genetic Epidemiol 28:97–109CrossRef
55.
go back to reference Cressie N (1993) Statistics for spatial data. Wiley, New York Cressie N (1993) Statistics for spatial data. Wiley, New York
56.
go back to reference Spiegelhalter DJ, Best NG, Carlin BP, Van Der Linde A (2002) Bayesian measures of model complexity and fit. J Roy Stat Soc B 64:583–639CrossRef Spiegelhalter DJ, Best NG, Carlin BP, Van Der Linde A (2002) Bayesian measures of model complexity and fit. J Roy Stat Soc B 64:583–639CrossRef
58.
go back to reference R Development Core Team (2011) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna R Development Core Team (2011) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna
59.
go back to reference Gorey KM, Luginaah IN, Bartfay E, Fung KY, Holowaty EJ, Wright FC et al (2011) Effects of socioeconomic status on colon cancer treatment accessibility and survival in Toronto, Ontario, and San Francisco, California, 1996–2006. Am J Public Health 101:112–119PubMedCrossRef Gorey KM, Luginaah IN, Bartfay E, Fung KY, Holowaty EJ, Wright FC et al (2011) Effects of socioeconomic status on colon cancer treatment accessibility and survival in Toronto, Ontario, and San Francisco, California, 1996–2006. Am J Public Health 101:112–119PubMedCrossRef
60.
go back to reference McMillan DC, Canna K, McArdle CS (2003) Systemic inflammatory response predicts survival following curative resection of colorectal cancer. Br J Surg 90:215–219PubMedCrossRef McMillan DC, Canna K, McArdle CS (2003) Systemic inflammatory response predicts survival following curative resection of colorectal cancer. Br J Surg 90:215–219PubMedCrossRef
61.
go back to reference Roxburgh CS, McMillan DC (2010) Role of systemic inflammatory response in predicting survival in patients with primary operable cancer. Future Oncol 6:149–163PubMedCrossRef Roxburgh CS, McMillan DC (2010) Role of systemic inflammatory response in predicting survival in patients with primary operable cancer. Future Oncol 6:149–163PubMedCrossRef
62.
go back to reference Schulz AJ, Mentz G, Lachance L, Johnson J, Gaines C, Israel BA (2012) Associations between socioeconomic status and allostatic load: effects of neighborhood poverty and tests of mediating pathways. Am J Public Health e1–e6 Schulz AJ, Mentz G, Lachance L, Johnson J, Gaines C, Israel BA (2012) Associations between socioeconomic status and allostatic load: effects of neighborhood poverty and tests of mediating pathways. Am J Public Health e1–e6
63.
go back to reference Lovasi GS, Hutson MA, Guerra M, Neckerman KM (2009) Built environments and obesity in disadvantaged populations. Epidemiol Rev 31:7–20PubMedCrossRef Lovasi GS, Hutson MA, Guerra M, Neckerman KM (2009) Built environments and obesity in disadvantaged populations. Epidemiol Rev 31:7–20PubMedCrossRef
64.
go back to reference Juster RP, McEwen BS, Lupien SJ (2010) Allostatic load biomarkers of chronic stress and impact on health and cognition. Neurosci Biobehav Rev 35:2–16PubMedCrossRef Juster RP, McEwen BS, Lupien SJ (2010) Allostatic load biomarkers of chronic stress and impact on health and cognition. Neurosci Biobehav Rev 35:2–16PubMedCrossRef
65.
go back to reference Steptoe A, Hamer M, Chida Y (2007) The effects of acute psychological stress on circulating inflammatory factors in humans: a review and meta-analysis. Brain Behav Immun 21:901–912PubMedCrossRef Steptoe A, Hamer M, Chida Y (2007) The effects of acute psychological stress on circulating inflammatory factors in humans: a review and meta-analysis. Brain Behav Immun 21:901–912PubMedCrossRef
66.
go back to reference Taylor L, Loerbroks A, Herr RM, Lane RD, Fischer JE, Thayer JF (2011) Depression and smoking: mediating role of vagal tone and inflammation. Ann Behav Med 42:334–340PubMedCrossRef Taylor L, Loerbroks A, Herr RM, Lane RD, Fischer JE, Thayer JF (2011) Depression and smoking: mediating role of vagal tone and inflammation. Ann Behav Med 42:334–340PubMedCrossRef
67.
go back to reference Chan AT, Ogino S, Fuchs CS (2009) Aspirin use and survival after diagnosis of colorectal cancer. JAMA 302:649–658PubMedCrossRef Chan AT, Ogino S, Fuchs CS (2009) Aspirin use and survival after diagnosis of colorectal cancer. JAMA 302:649–658PubMedCrossRef
68.
go back to reference Sauleau EA, Hennerfeind A, Buemi A, Held L (2007) Age, period and cohort effects in Bayesian smoothing of spatial cancer survival with geoadditive models. Stat Med 26:212–229PubMedCrossRef Sauleau EA, Hennerfeind A, Buemi A, Held L (2007) Age, period and cohort effects in Bayesian smoothing of spatial cancer survival with geoadditive models. Stat Med 26:212–229PubMedCrossRef
69.
go back to reference Strasak AM, Lang S, Kneib T, Brant LJ, Klenk J, Hilbe W et al (2009) Use of penalized splines in extended Cox-type additive hazard regression to flexibly estimate the effect of time-varying serum uric acid on risk of cancer incidence: a prospective, population-based study in 78,850 men. Ann Epidemiol 19:15–24PubMedCrossRef Strasak AM, Lang S, Kneib T, Brant LJ, Klenk J, Hilbe W et al (2009) Use of penalized splines in extended Cox-type additive hazard regression to flexibly estimate the effect of time-varying serum uric acid on risk of cancer incidence: a prospective, population-based study in 78,850 men. Ann Epidemiol 19:15–24PubMedCrossRef
70.
go back to reference Dunson DB (2001) Commentary: practical advantages of bayesian analysis of epidemiologic data. Am J Epidemiol 153:1222–1226PubMedCrossRef Dunson DB (2001) Commentary: practical advantages of bayesian analysis of epidemiologic data. Am J Epidemiol 153:1222–1226PubMedCrossRef
Metadata
Title
The modifying effect of patient location on stage-specific survival following colorectal cancer using geosurvival models
Authors
Lung-Chang Chien
Mario Schootman
Sandi L. Pruitt
Publication date
01-03-2013
Publisher
Springer Netherlands
Published in
Cancer Causes & Control / Issue 3/2013
Print ISSN: 0957-5243
Electronic ISSN: 1573-7225
DOI
https://doi.org/10.1007/s10552-012-0134-4

Other articles of this Issue 3/2013

Cancer Causes & Control 3/2013 Go to the issue
Webinar | 19-02-2024 | 17:30 (CET)

Keynote webinar | Spotlight on antibody–drug conjugates in cancer

Antibody–drug conjugates (ADCs) are novel agents that have shown promise across multiple tumor types. Explore the current landscape of ADCs in breast and lung cancer with our experts, and gain insights into the mechanism of action, key clinical trials data, existing challenges, and future directions.

Dr. Véronique Diéras
Prof. Fabrice Barlesi
Developed by: Springer Medicine