The impact of geographic unit of analysis on socioeconomic inequalities in cancer survival and distant summary stage - a population-based study

Socioeconomic disadvantage and its impact on colorectal cancer in Australia: a scoping review

BACKGROUND

Social disparities in cancer survival have been demonstrated in Australia despite a universal healthcare insurance system. Colorectal cancer is common, and reasons for survival disparities related to socioeconomic status need to be investigated and addressed. The aim is to evaluate the current Australian literature concerning the impact of socioeconomic status on colorectal cancer survival and stage at presentation.

METHODS

A systematic search of PUBMED, EMBASE, SCOPUS and Clarivate Web of Science databases from January 2010 to March 2022 was performed. Studies investigating the impact of socioeconomic status on colorectal stage at presentation or survival in Australia were included. Data were extracted on author, year of publication, state or territory of origin, patient population, other exposure variables, outcomes and findings and adjustments made.

RESULTS

Of the 14 articles included, the patient populations examined varied in size from 207 to 100 000+ cases. Evidence that socioeconomic disadvantage was associated with poorer survival was demonstrated in eight of 12 studies. Evidence of effect on late stage at presentation was demonstrated in two of seven studies. Area-level measures were commonly used to assess socioeconomic status, with varying indices utilized.

CONCLUSION

There is limited evidence that socioeconomic status is associated with late-stage at presentation. More studies provide evidence of an association between socioeconomic disadvantage and poorer survival, especially larger studies utilizing less clinically-detailed cancer registry data. Further investigation is required to analyse why socioeconomic disadvantage may be associated with poorer survival.

A qualitative exploration of the facilitators and barriers to early diagnosis and treatment of head and neck cancer: Perceptions of patients and carers

OBJECTIVE

The objective of this study to explore experiences of patients and carers of the pathway to diagnosis and treatment of head and neck cancer (HNC), focusing on differences based on remoteness of residence.

METHODS

Patients ≥6 months post-treatment completion, and their carers, were recruited. Semi-structured interviews, guided by the Model of Pathways to Treatment as the theoretical framework, were conducted to examine pathways to treatment of HNC and facilitators and barriers to early diagnosis and treatment. Thematic analysis with an iterative and data-driven approach was used to identify themes.

RESULTS

A total of 39 patients and 17 carers participated in the interviews. Facilitators of timely diagnosis and treatment included a sense of urgency from health care professionals (HCPs), advocacy by the HCP or carers, and leveraging social capital. Distance to services, financial costs, and a perceived lack of emotional investment by HCPs arose as barriers to timely diagnosis and treatment. Participants were often able to rationalise that not all delays were negative, depending causes and expected impact on cancer management.

CONCLUSION

The findings highlight the complex nature of factors facilitating and impeding early HNC diagnosis and treatment that may be targeted in interventions to support patients and meet important benchmarks for high-quality cancer care.

Socioeconomic deprivation and cancer survival in a metropolitan area: An analysis of cancer registry data from Hamburg, Germany

Background

Few studies have investigated socioeconomic inequalities within cities. Yet, such analyses are particularly important given the increasing international trend to urbanization. Here we investigated area-based socioeconomic inequalities in cancer survival in Hamburg, a port city in the North of Germany (population: 1.84 million people).

Methods

Patients with a diagnosis of colorectal, lung, female breast, and prostate cancer in 2004–2018 (follow-up until 31.12.2018) and registered in the Hamburg cancer registry were included. Area-based socioeconomic deprivation on urban district level was assigned to the patients and grouped in five quintiles. Relative survival in 2014–2018 was calculated using the period approach. Trend analyses between 2004 and 2018 were conducted. Relative excess risks adjusted for age and stage were computed with model-based period analyses.

Findings

For the 73,106 included patients, age-standardized 5-year relative survival in 2014–2018 decreased with increasing deprivation with significant differences between the most and least deprived group of 14·7 (prostate), 10·8 (colorectal), 8·0 (breast), and 2·5 (lung) percent units. Standardization by cancer stage decreased the difference for prostate cancer to 8·5 percent units and for breast cancer to 3·6 percent units but had only a minor effect for colorectal and lung cancer. Similar socioeconomic inequalities were already present in 2004–08.

Interpretation

Strong socioeconomic inequalities in cancer survival were observed in Hamburg, which could be partly explained by differences in the stage distribution. Further research including information on screening participation as well as information on cancer care are important to further understand and finally overcome these inequalities.

Funding

10.13039/501100005972German Cancer Aid.

Small-area analysis on socioeconomic inequalities in cancer survival for 25 cancer sites in Germany

Socioeconomic inequalities in cancer survival have been reported in various countries but it is uncertain to what extent they persist in countries with relatively comprehensive health insurance coverage such as Germany. We investigated the association between area-based socioeconomic deprivation on municipality level and cancer survival for 25 cancer sites in Germany. We used data from seven population-based cancer registries (covering 32 million inhabitants). Patients diagnosed in 1998 to 2014 with one of 25 most common cancer sites were included. Area-based socioeconomic deprivation was assessed using the categorized German Index of Multiple Deprivation (GIMD) on municipality level. We estimated 3-month, 1-year, 5-year and 5-year conditional on 1-year age-standardized relative survival using period approach for 2012 to 2014. Trend analyses were conducted for periods between 2003-2005 and 2012-2014. Model-based period analysis was used to calculate relative excess risks (RER) adjusted for age and stage. In total, 2 333 547 cases were included. For all cancers combined, 5-year survival rates by GIMD quintile were 61.6% in Q1 (least deprived), 61.2% in Q2, 60.4% in Q3, 59.9% in Q4 and 59.0% in Q5 (most deprived). For most cancer sites, the most deprived quintile had lower 5-year survival compared to the least deprived quintile even after adjusting for stage (all cancer sites combined, RER 1.16, 95% confidence interval 1.14-1.19). For some cancer sites, this association was stronger during short-term follow-up. Trend analyses showed improved survival from earlier to recent periods but persisting deprivation differences. The underlying reasons for these persisting survival inequalities and strategies to overcome them should be further investigated.

Socioeconomic status during youth and risk of car crash during adulthood. Findings from the DRIVE cohort study

BACKGROUND

Young drivers of low socioeconomic status (SES) have a disproportionally high risk of crashing compared with their more affluent counterparts. Little is known if this risk persists into adulthood and if it differs between men and women.

METHODS

We used data from a 2003/2004 Australian survey of young drivers (n=20 806), which included measures of drivers' demographics and established crash risk factors. These data were linked to police-reported crash, hospital and death data up to 2016. We used negative binomial regression models to estimate the association between participants' SES, with car crash.

RESULTS

After adjusting for confounding, drivers of lowest SES had 1.30 (95% CI 1.20 to 1.42), 1.90 (95% CI 1.25 to 2.88), 3.09 (95% CI 2.41 to 3.95) and 2.28 (95% CI 1.85 to 2.82) times higher rate of crash, crash-related hospitalisation, crash in country areas and crash on streets with a speed limit of 80 km/hour or above compared with drivers of highest SES, respectively. For single-vehicle crashes, women in the lowest SES groups had 2.88 (95% CI 1.83 to 4.54) times higher rate of crash compared with those in the highest SES group, but no differences were observed for men from different SES groups.

CONCLUSION

Young drivers who lived in areas of low SES at the time of the survey had a sustained increased risk of crash over the following 13 years compared with drivers from the most affluent areas. Our findings suggest that in addition to traditional measures, road transport injury prevention needs to consider the wider social determinants of health.

Educational inequalities and regional variation in colorectal cancer survival in Finland

BACKGROUND

Previous studies have reported lower colorectal cancer (CRC) survival in patients with low compared to high educational levels. We investigated the impact of education on CRC survival by using both individual and area-based information on education.

METHODS

Patients diagnosed with CRC in Finland in 2007-2016 were followed up for death until the end of 2016. Age-standardized relative survival and relative excess risk of death (RER) were estimated by sex using period approach. RERs were adjusted for age, stage at diagnosis, cancer site, urbanity, hospital district and municipality by using Bayesian piecewise constant excess hazard models. Analyses were conducted including individual (basic, secondary, high) and area-based (quartiles Q1-Q4 based on the proportion of population with basic education) education separately as well as both measures in one model.

RESULTS

We analysed in all 24 462 CRC patients. There was a clear gradient in 5-year relative survival across education groups (men: basic 62 %, secondary 64 %, high 69 %; women: basic 61 %, secondary 67 %, high 71 %). Compared to the basic education group, RER in the high education group was significantly lower. This association was still present after including area-based education in the models (men: RER 0.72, 95 % Confidence interval (CI) 0.64-0.81; women: RER 0.76, 95 % CI 0.59-0.96). Area-based education revealed smaller effect estimates than individual education in CRC survival and no association for men.

CONCLUSION

Individual education information should be preferred over area-based when survival differences are studied by education. Educational differences in CRC survival are still present in Finland.

Social Inequalities in Cancer Survival in Belgium: A Population-Based Cohort Study

BACKGROUND

Socioeconomic status (SES) is an important factor in cancer survival; however, results are heterogeneous and linked to characteristics of the study population and health care system. This population-based cohort study evaluates the association between individual-level socioeconomic and demographic factors and cancer survival for the first time in Belgium.

METHODS

From the Belgian Cancer Registry, we identified 109,591 patients diagnosed between 2006 and 2013 with one of eight common cancer types. Information on treatment, socioeconomic parameters, and vital status were retrieved from multiple data sources and linked using a unique personal identification number. The outcome was 5-year observed survival. Associations between survival and socioeconomic and demographic factors were assessed using multivariable Cox proportional-hazard regression models.

RESULTS

Lower income, unemployment, and living alone were all associated with worse cancer survival. These associations were most pronounced for certain lifestyle-related cancer types (e.g., head and neck cancers) and those with good to moderate prognosis (e.g., colorectal and female breast cancer).

CONCLUSIONS

These results indicate that, despite a comprehensive and nationwide health insurance program in which equity in rights and access to health care are pursued, SES is associated with disparities in cancer survival in Belgium.

IMPACT

This population-based study with individual-level socioeconomic information of more than 100,000 patients with cancer identifies patient groups that may be at highest risk for socioeconomic disparities in cancer survival. Reasons behind the observed disparities are multiple and complex and should be further examined. Health policy interventions should consider the observed deprivation gap to plan targeted actions.

Emerging cancer incidence, mortality, hospitalisation and associated burden among Australian cancer patients, 1982 - 2014: an incidence-based approach in terms of trends, determinants and inequality

OBJECTIVE

Cancer is a leading killer worldwide, including Australia. Cancer diagnosis leads to a substantial burden on the individual, their family and society. The main aim of this study is to understand the trends, determinants and inequalities associated with cancer incidence, hospitalisation, mortality and its burden over the period 1982 to 2014 in Australia.

SETTINGS

The study was conducted in Australia.

STUDY DESIGN

An incidence-based study design was used.

METHODS

Data came from the publicly accessible Australian Institute of Health and Welfare database. This contained 2 784 148 registered cancer cases over the study period for all types of cancer. Erreygers' concentration index was used to examine the magnitude of socioeconomic inequality with regards to cancer outcomes. Furthermore, a generalised linear model was constructed to identify the influential factors on the overall burden of cancer.

RESULTS

The results showed that cancer incidence (annual average percentage change, AAPC=1.33%), hospitalisation (AAPC=1.27%), cancer-related mortality (AAPC=0.76%) and burden of cancer (AAPC=0.84%) all increased significantly over the period. The same-day (AAPC=1.35%) and overnight (AAPC=1.19%) hospitalisation rates also showed an increasing trend. Further, the ratio (least-most advantaged economic resources ratio, LMR of mortality (M) and LMR of incidence (I)) was especially high for cervix (M/I=1.802), prostate (M/I=1.514), melanoma (M/I=1.325), non-Hodgkin's lymphoma (M/I=1.325) and breast (M/I=1.318), suggesting that survival inequality was most pronounced for these cancers. Socioeconomically disadvantaged people were more likely to bear an increasing cancer burden in terms of incidence, mortality and death.

CONCLUSIONS

Significant differences in the burden of cancer persist across socioeconomic strata in Australia. Policymakers should therefore introduce appropriate cancer policies to provide universal cancer care, which could reduce this burden by ensuring curable and preventive cancer care services are made available to all people.

Geographical Variations in Prostate Cancer Outcomes: A Systematic Review of International Evidence

Background: Previous reviews of geographical disparities in the prostate cancer continuum from diagnosis to mortality have identified a consistent pattern of poorer outcomes with increasing residential disadvantage and for rural residents. However, there are no contemporary, systematic reviews summarizing the latest available evidence. Our objective was to systematically review the published international evidence for geographical variations in prostate cancer indicators by residential rurality and disadvantage.

Methods: Systematic searches of peer-reviewed articles in English published from 1/1/1998 to 30/06/2018 using PubMed, EMBASE, CINAHL, and Informit databases. Inclusion criteria were: population was adult prostate cancer patients; outcome measure was PSA testing, prostate cancer incidence, stage at diagnosis, access to and use of services, survival, and prostate cancer mortality with quantitative results by residential rurality and/or disadvantage. Studies were critically appraised using a modified Newcastle-Ottawa Scale.

Results: Overall 169 studies met the inclusion criteria. Around 50% were assessed as high quality and 50% moderate. Men from disadvantaged areas had consistently lower prostate-specific antigen (PSA) testing and prostate cancer incidence, poorer survival, more advanced disease and a trend toward higher mortality. Although less consistent, predominant patterns by rurality were lower PSA testing, prostate cancer incidence and survival, but higher stage disease and mortality among rural men. Both geographical measures were associated with variations in access and use of prostate cancer-related services for low to high risk disease.

Conclusions: This review found substantial evidence that prostate cancer indicators varied by residential location across diverse populations and geographies. While wide variations in study design limited comparisons across studies, our review indicated that internationally, men living in disadvantaged areas, and to a lesser extent more rural areas, face a greater prostate cancer burden. This review highlights the need for a better understanding of the complex social, environmental, and behavioral reasons for these variations, recognizing that, while important, geographical access is not the only issue. Implementing research strategies to help identify these processes and to better understand the central role of disadvantage to variations in health outcome are crucial to inform the development of evidence-based targeted interventions.

Socioeconomic Differences and Lung Cancer Survival-Systematic Review and Meta-Analysis

Background: The impact of socioeconomic differences on cancer survival has been investigated for several cancer types showing lower cancer survival in patients from lower socioeconomic groups. However, little is known about the relation between the strength of association and the level of adjustment and level of aggregation of the socioeconomic status measure. Here, we conduct the first systematic review and meta-analysis on the association of individual and area-based measures of socioeconomic status with lung cancer survival.

Methods: In accordance with PRISMA guidelines, we searched for studies on socioeconomic differences in lung cancer survival in four electronic databases. A study was included if it reported a measure of survival in relation to education, income, occupation, or composite measures (indices). If possible, meta-analyses were conducted for studies reporting on individual and area-based socioeconomic measures.

Results: We included 94 studies in the review, of which 23 measured socioeconomic status on an individual level and 71 on an area-based level. Seventeen studies were eligible to be included in the meta-analyses. The meta-analyses revealed a poorer prognosis for patients with low individual income (pooled hazard ratio: 1.13, 95 % confidence interval: 1.08–1.19, reference: high income), but not for individual education. Group comparisons for hazard ratios of area-based studies indicated a poorer prognosis for lower socioeconomic groups, irrespective of the socioeconomic measure. In most studies, reported 1-, 3-, and 5-year survival rates across socioeconomic status groups showed decreasing rates with decreasing socioeconomic status for both individual and area-based measures. We cannot confirm a consistent relationship between level of aggregation and effect size, however, comparability across studies was hampered by heterogeneous reporting of socioeconomic status and survival measures. Only eight studies considered smoking status in the analysis.

Conclusions: Our findings suggest a weak positive association between individual income and lung cancer survival. Studies reporting on socioeconomic differences in lung cancer survival should consider including smoking status of the patients in their analysis and to stratify by relevant prognostic factors to further explore the reasons for socioeconomic differences. A common definition for socioeconomic status measures is desirable to further enhance comparisons between nations and across different levels of aggregation.

Spatially varying effects of predictors for the survival prediction of nonmetastatic colorectal Cancer

Background

An increasing number of studies have identified spatial differences in colorectal cancer survival. However, little is known about the spatially varying effects of predictors in survival prediction modeling studies of colorectal cancer that have focused on estimating the absolute survival risk for patients from a wide range of populations. This study aimed to demonstrate the spatially varying effects of predictors of survival for nonmetastatic colorectal cancer patients.

Methods

Patients diagnosed with nonmetastatic colorectal cancer from 2004 to 2013 who were followed up through the end of 2013 were extracted from the Surveillance Epidemiology End Results registry (Patients: 128061). The log-rank test and the restricted mean survival time were used to evaluate survival outcome differences among spatial clusters corresponding to a widely used clinical predictor: stage determined by AJCC 7th edition staging system. The heterogeneity test, which is used in meta-analyses, revealed the spatially varying effects of single predictors. Then, considering the above predictors in a standard survival prediction model based on spatially clustered data, the spatially varying coefficients of these models revealed that some covariate effects may not be constant across the geographic regions of the study. Then, two types of survival prediction models (a statistical model and a machine learning model) were built; these models considered the predictors and enabled survival prediction for patients from a wide range of geographic regions.

Results

Based on univariate and multivariate analysis, some prognostic factors, such as “TNM stage”, “tumor size” and “age at diagnosis,” have significant spatially varying effects among different regions. When considering these spatially varying effects, machine learning models have fewer assumption constraints (such as proportional hazard assumptions) and better predictive performance compared with statistical models. Upon comparing the concordance indexes of these two models, the machine learning model was found to be more accurate (0.898[0.895,0.902]) than the statistical model (0.732 [0.726, 0.738]).

Conclusions

Based on this study, it’s recommended that the spatially varying effect of predictors should be considered when building survival prediction models involving large-scale and multicenter research data. Machine learning models that are not limited by the requirement of a statistical hypothesis are promising alternative models.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4985-2) contains supplementary material, which is available to authorized users.