Geographic remoteness and risk of advanced colorectal cancer at diagnosis in Queensland: a multilevel study.
ABSTRACT We examine the relationships between geographic remoteness, area disadvantage and risk of advanced colorectal cancer.
Multilevel models were used to assess the area- and individual-level contributions to the risk of advanced disease among people aged 20-79 years diagnosed with colorectal cancer in Queensland, Australia between 1997 and 2007 (n=18,561).
Multilevel analysis showed that colorectal cancer patients living in inner regional (OR=1.09, 1.01-1.19) and outer regional (OR=1.11, 1.01-1.22) areas were significantly more likely to be diagnosed with advanced cancer than those in major cities (P=0.045) after adjusting for individual-level variables. The best-fitting final model did not include area disadvantage. Stratified analysis suggested this remoteness effect was limited to people diagnosed with colon cancer (P=0.048) and not significant for rectal cancer patients (P=0.873).
Given the relationship between stage and survival outcomes, it is imperative that the reasons for these rurality inequities in advanced disease be identified and addressed.
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ABSTRACT: Urban-rural variation in cancer incidence, treatment, and clinical outcomes has been well researched. With the growing numbers and longer lifespan of cancer survivors, quality of life (QOL) is now a critical issue. The present study investigates the QOL of head and neck cancer (HNC) survivors in Ireland, paying special attention to urban and rural variation. From the population-based National Cancer Registry Ireland, we identified 991 survivors of HNC (ICD10 C00-C14, C32), who were at least eight months post-diagnosis, and invited them to complete a postal survey. We used self-reported data and information from the Registry to create a composite variable classifying respondents' current area of residence as "urban" or "rural." Respondents self-reported QOL using the Functional Assessment for Cancer Therapy with Head and Neck module (FACT-HN). We used bootstrap linear regression to control for confounding variables, while estimating the association of urban and rural residence to FACT-HN domain scores. We obtained survey and Registry data from 583 HNC survivors. Controlling for demographic and clinical variables, rural survivors reported higher physical (coefficient 1.27, bias-corrected and accelerated 95% confidence interval 0.54, 2.43), emotional (coef. 0.99, 95% CI 0.21, 2.02), and HNC-specific (coef. 1.55, 95% CI 0.32, 3.54) QOL than their urban counterparts. Social and functional QOL did not differ significantly. These findings add to growing evidence of important differences in life experiences of cancers survivors in urban and rural settings. Results such as these will allow health professionals, policy makers and service providers to better serve these populations.Oral Oncology 04/2014; · 2.70 Impact Factor
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ABSTRACT: While overall survival for most common cancers in Australia is improving, the rural-urban differential has been widening, with significant excess deaths due to lung, colorectal, breast and prostate cancer in regional Australia. Internationally a major focus on understanding variations in cancer outcomes has been later presentation to healthcare and later diagnosis. Approaches to reducing time to diagnosis of symptomatic cancer include public symptom awareness campaigns and interventions in primary care to improve early cancer detection. This paper reports the protocol of a factorial cluster-randomised trial of community and general practice (GP) level interventions to reduce the time to diagnosis of cancer in rural Western Australia (WA).BMJ Open 01/2014; 4(9):e006156. · 1.58 Impact Factor
Geographic remoteness and risk of advanced colorectal cancer
at diagnosis in Queensland: a multilevel study
PD Baade*,1,2,3, P Dasgupta1, J Aitken1,3,4and G Turrell2
1Viertel Centre for Research in Cancer Control, Cancer Council Queensland, Spring Hill, Brisbane, QLD 4004, Australia;2School of Public Health,
Queensland University of Technology, Brisbane, QLD 4059, Australia;3Griffith Health Institute, Griffith University, Gold Coast, QLD 4222, Australia;
4School of Population Health, University of Queensland, Brisbane, QLD 4061, Australia
BACKGROUND: We examine the relationships between geographic remoteness, area disadvantage and risk of advanced colorectal
METHODS: Multilevel models were used to assess the area- and individual-level contributions to the risk of advanced disease among
people aged 20–79 years diagnosed with colorectal cancer in Queensland, Australia between 1997 and 2007 (n¼18561).
RESULTS: Multilevel analysis showed that colorectal cancer patients living in inner regional (OR¼1.09, 1.01–1.19) and outer regional
(OR¼1.11, 1.01–1.22) areas were significantly more likely to be diagnosed with advanced cancer than those in major cities
(P¼0.045) after adjusting for individual-level variables. The best-fitting final model did not include area disadvantage. Stratified analysis
suggested this remoteness effect was limited to people diagnosed with colon cancer (P¼0.048) and not significant for rectal cancer
CONCLUSION: Given the relationship between stage and survival outcomes, it is imperative that the reasons for these rurality inequities
in advanced disease be identified and addressed.
British Journal of Cancer (2011) 105, 1039–1041. doi:10.1038/bjc.2011.356
Published online 6 September 2011
& 2011 Cancer Research UK
Keywords: colorectal cancer; stage; health inequality; rural health; socio-economic status
While colorectal (CRC) survival rates in Australia are among the
highest in the world (Coleman et al, 2011), people living outside
major cities or in disadvantaged areas have poorer prognosis (Yu
et al, 2005; Kelsall et al, 2009). Since stage at diagnosis is a major
predictor of long-term CRC outcomes (Altekruse et al, 2010), its
relationship to factors such as socio-economic status (SES) and
geographic remoteness is of particular relevance for cancer
control. With major medical centres being concentrated in densely
populated urban centres, it has been suggested that rural and
remote locations may be associated with poorer access to
screening and specialised health care (Parikh-Patel et al, 2006;
Heathcote and Armstrong, 2007). However ecological studies have
presented a mixed picture in terms of SES (Parikh-Patel et al, 2006;
Frederiksen et al, 2008; Henry et al, 2009; Booth et al, 2010) and
geographic remoteness (Fazio et al, 2005; McLafferty and Wang,
2009; Sankaranarayanan et al, 2009) in stage at diagnosis.
Most of the evidence is based on ecological studies and these are
not able to separate the area-level or individual-level influences
(Baade et al, 2010), limiting our understanding about area-level
health inequalities. To date, no Australian study has employed
multilevel methods to investigate links between geographic
individual-level factors and
MATERIALS AND METHODS
Ethical approval to conduct this study was obtained from the
University of Queensland and Queensland Health. Data for
individuals aged 20–79 years diagnosed with invasive stage
1–IV CRC (ICD-O3 codes C18 to C20, C21.8) in Queensland
between 1 January 1996 and 31 December 2007 (inclusive)
(n¼18561) with complete address information were extracted
from the Queensland Cancer Registry (QCR).
Information extracted from pathology forms (Krnjacki et al,
2008) was used to determine stage at diagnosis according to TNM
system (Sobin and Wittlekind, 2002) as described previously
(Baade et al, 2011). For multivariate analysis, localised cases
(Stages I–II) were considered as early stage (Parikh-Patel et al,
2006; Henry et al, 2009) while regional and distant cases were
categorised as ‘advanced’ based on their lower survival rates
(Altekruse et al, 2010).
Information was obtained from QCR on individual-level
variables: year and age of diagnosis, cancer site, gender, marital
status, occupation (Turrell et al, 2007) and indigenous status (see
Table 2 for categories).
Statistical Local Areas (SLAs), which are typically based on
local governments and councils and thus likely to be socio-
economically relevant to their residents, were used as the
geographical definition for area-level analysis (Baade et al,
2010). Remoteness of residence was defined using the Accessi-
bility/Remoteness Index of Australia (ARIAþ) classification
measured using theIndex
Received 6 July 2011; revised 18 July 2011; accepted 13 August 2011;
published online 6 September 2011
*Correspondence: Professor PD Baade; E-mail: email@example.com
British Journal of Cancer (2011) 105, 1039–1041
& 2011 Cancer Research UK All rights reserved 0007– 0920/11
Disadvantage (IRSD) (Australian Bureau of Statistics, 2006) which
categorises SLAs into five quintiles of increasing advantage from
Multilevel logistic modelling (MLwiN 2.21) using Markov Chain
Monte Carlo (Browne, 2009) approaches in MLwiN version 2.21
(University of Bristol, UK) was used. Chain convergence was
checked using Raftery-Lewis diagnostics. Models were compared
Spiegelhalter et al, 2002), with smaller values indicating better fit.
Analyses were conducted in three steps: (1) a null model
comprising individuals (Level 1) nested in SLAs (Level 2) with
no fixed effects; (2) extending to include individual-level factors
as fixed effects (Model 2); and (3) geographic remoteness
(Model 3) and neighbourhood disadvantage (Model 4) were
included separately as fixed effects to quantify how much area
variation in stage was due to these factors independent of
compositional effects, and then in combination (Model 5). Fixed
effects results are reported as odds ratios (95% CI) (Merlo et al,
2001; Eikemo et al, 2008). Significance of individual coefficients was
tested using Z test.
Overall, 57.1% of patients were male with 67.2% having colon
cancer. The mean age at diagnosis was 65 years (median¼66
years). About 44.8% were diagnosed with advanced CRC. Just over
half of the patients (57.6%) lived in major cities and around 36.5%
were in the two most affluent SES quintiles.
In the multivariable logistic regression analyses, the null model
(Model 1) indicated significant (P¼0.041) between area variations
across the SLAs (Table 1).
Based on the DIC statistic (Table 1), the model fit improved
substantially by including individual-level characteristics (Model 2)
and then geographic remoteness (Model 3). Adding area
disadvantage (Model 4) to Model 2 did not improve the fit.
Similarly, the full model (Model 5) provided a poor fit to the data
than Model 3, suggesting that Model 3 was the best-fitting model
for these data. There was no evidence for area-level interaction
(results not shown).
In this final model (Model 3), and independent of individual
factors, geographic remoteness was associated with cancer
stage (Table 2). At individual level sex, occupation, indigenous
status and anatomic site were independent predictors (Po0.001)
of advanced CRC (Table 2). Independent of area effects the
likelihood of advanced CRC was significantly higher for females
than for males; blue-collar workers vs professionals; individuals
with known indigenous status compared with unknown and
patients with colon rather than rectal cancer (Table 2).
Analyses stratified by cancer site (Model 3) (results not shown)
showed that area remoteness was significant for colon cancer
(P¼0.048) but not for rectal cancer (P¼0.873).
Table 1Random effects
Model 1 Model 2 Model 3Model 4 Model 5
Area variance and standard error
P-value for area variance
Percentage reduction in area variance from the null model
Abbreviation: DIC¼Deviance Information Criterion. Model 1: no fixed effects. Model 2: adjusted for sex, age, year, marital and indigenous status, occupation and cancer site.
Model 3: adjusted for sex, age, year, marital and indigenous status, occupation, cancer site and remoteness. Model 4: adjusted for sex, age, year, marital and indigenous status,
occupation, cancer site and area disadvantage. Model 5: adjusted for sex, age, year, marital and indigenous status, occupation, cancer site, remoteness and area disadvantage.
advanced stage colorectal cancer, Queensland, 1996–2007
Final fixed effect factors on the probability of experiencing
Fixed effects OR95% CI
Area-remoteness index of Australia
Year of diagnosis
Not in the labour force
Abbreviations: OR¼odds ratio; CI¼confidence interval.
Determinants of colorectal cancer stage
PD Baade et al
British Journal of Cancer (2011) 105(7), 1039–1041
& 2011 Cancer Research UK
This study is one of the first to consider geographical variations in
CRC stage at diagnosis after adjusting for both area- and
individual-level factors. We found significant evidence that a
person’s risk of being diagnosed with advanced CRC depends on
where they live, specifically for those diagnosed with colon cancer,
independently of the individual characteristics of the patient
themselves. The impact of geographical location, however, was
limited to rurality with no evidence that area disadvantage was
associated with stage at diagnosis.
Given the nature of our data, any discussion of the possible
reasons for the remoteness differential can only be speculative; but
these may include a relative shortage of experienced medical staff
in regional areas and greater difficulty of accessing diagnostic
Significantly higher risks of late-stage diagnosis were seen for
patients with colon vs rectal cancer, consistent with international
studies (Frederiksen et al, 2008; Sankaranarayanan et al, 2009). We
also found that the risk of advanced disease was higher in more
regional areas compared with major cities for colon cancers only.
A contributing reason for both these observations may be that
compared with colon cancer rectal cancer often presents with more
visible symptoms (Majumdar et al, 1999), thereby making patients
more likely to seek medical care and be diagnosed earlier.
The strengths of this study include the use of staged CRC cases
from a large, unselected, state-wide population-based registry.
Approximately 84% of records in our initial cohort had sufficient
information to be staged similar to that reported elsewhere (Yu
et al, 2008). We were limited to the individual-level SES variable of
occupation, since the QCR does not collect information about
education (Frederiksen et al, 2008), income (Frederiksen et al,
2008) or private insurance status (Halpern et al, 2009) known to be
associated with advanced CRC. In addition, due to the high
prevalence of advanced CRC the odds ratios may reflect an
overestimation of the relative risk.
Given the relationship between stage at diagnosis and survival
outcomes, it is imperative that the reasons for the geographical
inequities in advanced disease be identified and addressed.
This study was supported by a grant from the (Australian)
National Health and Medical Research Council (NHMRC)
(ID561700). Associate Professor Peter Baade is supported by an
NHMRC Career Development Fellowship (ID1005334); Professor
Gavin Turrell is supported by an NHMRC Senior Research
Fellowship (ID 1003710).
Conflict of interest
The authors declare no conflict of interest.
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British Journal of Cancer (2011) 105(7), 1039–1041
& 2011 Cancer Research UK