Socioeconomic disparities in colorectal cancer survival: contributions of prognostic factors in a large Australian cohort.

PURPOSE: We quantified the contributions of prognostic factors to socioeconomic disparities in colorectal cancer survival in a large Australian cohort. METHODS: The sample comprised 45 and Up Study participants (recruited 2006-2009) who were subsequently diagnosed with colorectal cancer. Both individual (education attained) and neighbourhood socioeconomic measures were used. Questionnaire responses were linked with cancer registrations (to December 2013), records for hospital inpatient stays, emergency department presentations, death information (to December 2015), and Medicare and Pharmaceutical Benefits claims for subsidised procedures and medicines. Proportions of socioeconomic survival differences explained by prognostic factors were quantified using multiple Cox proportional hazards regression. RESULTS: 1720 eligible participants were diagnosed with colorectal cancer after recruitment: 1174 colon and 546 rectal cancers. Significant colon cancer survival differences were only observed for neighbourhood socioeconomic measure (p = 0.033): HR = 1.55; 95% CI 1.09-2.19 for lowest versus highest quartile, and disease-related factors explained 95% of this difference. For rectal cancer, patient- and disease-related factors were the main drivers of neighbourhood survival differences (28-36%), while these factors and treatment-related factors explained 24-41% of individual socioeconomic differences. However, differences remained significant for rectal cancer after adjusting for all these factors. CONCLUSION: In this large contemporary Australian cohort, we identified several drivers of socioeconomic disparities in colorectal cancer survival. Understanding of the role these contributors play remains incomplete, but these findings suggest that improving access to optimal care may significantly reduce these survival disparities.

Status Analysis of Nursing Assessment Terminology of Neurological Conditions and Its Cross-Mapping with the International Classification of Functioning, Disability, and Health (ICF).

Patients with nervous system disorders with an accurate nursing assessment can experience an improved prognosis and promotion of health. The lack of uniform terminology limits the accuracy of nursing in China. ICF constitutes a unified and standard language can help standardize nursing assessment terms. This study show that ICF is suitable for Chinese nursing practice by using ICF Clinical Checklist and ICF-linking-rules to map the nursing assessment terminology of neurological conditions with ICF.

Contributions of prognostic factors to socioeconomic disparities in cancer survival: protocol for analysis of a cohort with linked data.

INTRODUCTION: Socioeconomic disparities in cancer survival have been reported in many developed countries, including Australia. Although some international studies have investigated the determinants of these socioeconomic disparities, most previous Australian studies have been descriptive, as only limited relevant data are generally available. Here, we describe a protocol for a study to use data from a large-scale Australian cohort linked with several other health-related databases to investigate several groups of factors associated with socioeconomic disparities in cancer survival in New South Wales (NSW), Australia, and quantify their contributions to the survival disparities. METHODS AND ANALYSIS: The Sax Institute's 45 and Up Study participants completed a baseline questionnaire during 2006-2009. Those who were subsequently diagnosed with cancer of the colon, rectum, lung or female breast will be included. This study sample will be identified by linkage with NSW Cancer Registry data for 2006-2013, and their vital status will be determined by linking with cause of death records up to 31 December 2015. The study cohort will be divided into four groups based on each of the individual education level and an area-based socioeconomic measure. The treatment received will be obtained through linking with hospital records and Medicare and pharmaceutical claims data. Cox proportional hazards models will be fitted sequentially to estimate the percentage contributions to overall socioeconomic survival disparities of patient factors, tumour and diagnosis factors, and treatment variables. ETHICS AND DISSEMINATION: This research is covered by ethical approval from the NSW Population and Health Services Research Ethics Committee. Results of the study will be disseminated to different interest groups and organisations through scientific conferences, social media and peer-reviewed articles.

Contrasting temporal trends in lung cancer incidence by socioeconomic status among women in New South Wales, Australia, 1985-2009.

OBJECTIVE: We examined long-term trends in lung cancer incidence for women by socioeconomic groups in New South Wales (NSW), Australia. METHODS: Data on lung cancer incidence for women were extracted from the NSW Cancer Registry database. We divided the study cohort into five quintiles according to an area-based index of education and occupation (IEO) and calculated annual age-standardised incidence rates by IEO quintile for the period 1985-2009. The age-standardised incidence ratio (SIR) was estimated for IEO quintiles and 5-year period of diagnosis using the highest IEO quintile as the reference. RESULTS: Overall, lung cancer incidence for women aged 25-69 years increased gradually from 19.8 per 100,000 in 1985 to 25.7 per 100,000 in 2009. The trends by IEO quintile were somewhat comparable from 1985 through to 1995, but from then on rates remained relatively stable for women residing in the highest quintile while increasing for women residing in the remaining four quintiles. Consequently, the SIR for all four of the lower IEO quintiles increased significantly over the 25-year period. For example, the SIR in the lowest IEO quintile increased from 1.16 (95% CI, 0.99-1.37) during 1985-1989 to 1.70 (95% CI, 1.50-1.93) during 2005-2009. The corresponding estimates for women aged 70 years or older showed no clear pattern of socioeconomic gradient. CONCLUSION: The increasing gap in lung cancer incidence between women in the highest socioeconomic group and all others suggests that there is a continued need for the broad implementation of tobacco control interventions, so that smoking prevalence is reduced across all segments of the population and the subsequent benefits are shared more equitably across all demographic groups.

Spatial and temporal patterns of nasopharyngeal carcinoma mortality in China, 1973-2005.

We fitted generalized linear models using data from three national retrospective surveys on cause of death in China to explore the spatial and temporal patterns of nasopharyngeal carcinoma (NPC) mortality over the period 1973 to 2005. The results suggest that there was a significant decrease in NPC mortality in China over time (p < 0.0001), the mortality rate ratio (RR) for the two later time periods were 0.59 (95% CI: 0.55-0.64) for 1990-1992 and 0.42 (95% CI: 0.39-0.45) for 2004-2005 compared to that of 1973-1975. Residents living in the South China areas have an elevated risk of mortality from NPC compared to those living in North China across all three time periods, with the RR being 4.96 (95% CI: 4.31-5.70) in 1973-1975, 12.83 (95% CI: 10.73-15.34) in 1990-1992 and 15.20 (95% CI: 12.34-18.72) in 2004-2005. Although NPC mortality in most areas of China has reduced to very low levels, the widening geographical disparities in NPC mortality are still noteworthy. It may be necessary to target public health policies to address the widening geographical disparities in NPC mortality.

Phase of care prevalence for prostate cancer in New South Wales, Australia: A population-based modelling study.

OBJECTIVE: To develop a method for estimating the future numbers of prostate cancer survivors requiring different levels of care. DESIGN, SETTING AND PARTICIPANTS: Analysis of population-based cancer registry data for prostate cancer cases (aged 18-84 years) diagnosed in 1996-2007, and a linked dataset with hospital admission data for men with prostate cancer diagnosed during 2005-2007 in New South Wales (NSW), Australia. METHODS: Cancer registry data (1996-2007) were used to project complete prostate cancer prevalence in NSW, Australia for 2008-2017, and treatment information from hospital records (2005-2007) was used to estimate the inpatient care needs during the first year after diagnosis. The projected complete prevalence was divided into care needs-based groups. We first divided the cohort into two groups based on patient's age (<75 and 75-84 years). The younger cohort was further divided into initial care and monitoring phases. Cause of death data were used as a proxy for patients requiring last year of life prostate cancer care. Finally, episode data were used to estimate the future number of cases with metastatic progression. RESULTS: Of the estimated total of 60,910 men with a previous diagnosis of prostate cancer in 2017, the largest groups will be older patients (52.0%) and younger men who require monitoring (42.5%). If current treatment patterns continue, in the first year post-diagnosis 41% (1380) of patients (<75 years) will have a radical prostatectomy, and 52.6% (1752) will be likely to have either active surveillance, external beam radiotherapy or androgen deprivation therapy. About 3% will require care for subsequent metastases, and 1288 men with prostate cancer are likely to die from the disease in 2017. CONCLUSIONS: This method extends the application of routinely collected population-based data, and can contribute much to the knowledge of the number of men with prostate cancer and their health care requirements. This could be of significant use in planning future cancer care services and facilities in Australia.

Impact of geographic area level on measuring socioeconomic disparities in cancer survival in New South Wales, Australia: A period analysis.

BACKGROUND: Area-based socioeconomic measures are widely used in health research. In theory, the larger the area used the more individual misclassification is introduced, thus biasing the association between such area level measures and health outcomes. In this study, we examined the socioeconomic disparities in cancer survival using two geographic area-based measures to see if the size of the area matters. METHODS: We used population-based cancer registry data for patients diagnosed with one of 10 major cancers in New South Wales (NSW), Australia during 2004-2008. Patients were assigned index measures of socioeconomic status (SES) based on two area-level units, census Collection District (CD) and Local Government Area (LGA) of their address at diagnosis. Five-year relative survival was estimated using the period approach for patients alive during 2004-2008, for each socioeconomic quintile at each area-level for each cancer. Poisson-regression modelling was used to adjust for socioeconomic quintile, sex, age-group at diagnosis and disease stage at diagnosis. The relative excess risk of death (RER) by socioeconomic quintile derived from this modelling was compared between area-units. RESULTS: We found extensive disagreement in SES classification between CD and LGA levels across all socioeconomic quintiles, particularly for more disadvantaged groups. In general, more disadvantaged patients had significantly lower survival than the least disadvantaged group for both CD and LGA classifications. The socioeconomic survival disparities detected by CD classification were larger than those detected by LGA. Adjusted RER estimates by SES were similar for most cancers when measured at both area levels. CONCLUSIONS: We found that classifying patient SES by the widely used Australian geographic unit LGA results in underestimation of survival disparities for several cancers compared to when SES is classified at the geographically smaller CD level. Despite this, our RER of death estimates derived from these survival estimates were generally similar for both CD and LGA level analyses, suggesting that LGAs remain a valuable spatial unit for use in Australian health and social research, though the potential for misclassification must be considered when interpreting research. While data confidentiality concerns increase with the level of geographical precision, the use of smaller area-level health and census data in the future, with appropriate allowance for confidentiality.

Cancer survival in New South Wales, Australia: socioeconomic disparities remain despite overall improvements.

BACKGROUND: Disparities in cancer survival by socioeconomic status have been reported previously in Australia. We investigated whether those disparities have changed over time. METHODS: We used population-based cancer registry data for 377,493 patients diagnosed with one of 10 major cancers in New South Wales (NSW), Australia. Patients were assigned to an area-based measure of socioeconomic status. Five-year relative survival was estimated for each socioeconomic quintile in each 'at risk' period (1996-2000 and 2004-2008) for the 10 individual cancers. Poisson-regression modelling was used to adjust for several prognostic factors. The relative excess risk of death by socioeconomic quintile derived from this modelling was compared over time. RESULTS: Although survival increased over time for most individual cancers, Poisson-regression models indicated that socioeconomic disparities continued to exist in the recent period. Significant socioeconomic disparities were observed for stomach, colorectal, liver, lung, breast and prostate cancer in 1996-2000 and remained so for 2004-2008, while significant disparities emerged for cervical and uterus cancer in 2004-2008 (although the interaction between period and socioeconomic status was not significant). About 13.4% of deaths attributable to a diagnosis of cancer could have been postponed if this socioeconomic disparity was eliminated. CONCLUSION: While recent health and social policies in NSW have accompanied an increase in cancer survival overall, they have not been associated with a reduction in socioeconomic inequalities.

Lung cancer treatment is influenced by income, education, age and place of residence in a country with universal health coverage.

Selection of lung cancer treatment should be based on tumour characteristics, physiological reserves and preferences of the patient. Our aims were to identify and quantify other factors associated with treatment received. Lung cancer patient data from 2002 to 2011 were obtained from the national population-based Cancer Registry of Norway, Statistics Norway and the Norwegian Patient Register. Multivariable logistic regression examined whether year of diagnosis, age, sex, education, income, health trust, smoking status, extent of disease, histology and comorbidities were associated with choice of treatment; surgery or radical or palliative radiotherapy, within 1 year of diagnosis. Among the 24,324 lung cancer patients identified, the resection rate remained constant while the proportion of radical radiotherapy administered increased from 8.6 to 14.1%. Older patients, those with lower household incomes and certain health trusts were less likely to receive any treatment. Lower education and the male gender were identified as negative predictors for receiving surgery. Smoking history was positively associated with both radical and palliative radiotherapy, while comorbidity and symptoms were independently associated with receiving surgery and palliative radiotherapy. Although Norway is a highly egalitarian country with a free, universal healthcare system, this study indicates that surgery and radical and palliative radiotherapy were under-used among the elderly, those with a lower socioeconomic status and those living in certain health trusts.

Temporal trends show improved breast cancer survival in Australia but widening urban-rural differences.

We examined geographic patterns in breast cancer survival over time using population-based data for breast cancer diagnosed between 1987 and 2007 in New South Wales, Australia. We found that five-year relative survival increased during the entire study period. Multivariable analysis indicated that there was little geographic variation in 1992-1996, but in 1997-2001 and 2002-2007 geographic variation was statistically significant (P < 0.01), with women living in rural areas having higher risk of death from breast cancer. The underlying reasons for this widening survival disparity must be identified so that appropriately targeted interventions can be implemented and the disparity reduced.

A population-based study of breast cancer prevalence in Australia: predicting the future health care needs of women living with breast cancer.

BACKGROUND: Breast cancer places a heavy burden on the Australian healthcare system, but information about the actual number of women living with breast cancer and their current or future health service needs is limited. We used existing population-based data and innovative statistical methods to address this critical research question in a well-defined geographic region. METHODS: Breast cancer data from the New South Wales (NSW) Central Cancer Registry and PIAMOD (Prevalence and Incidence Analysis MODel) software were used to project future breast cancer prevalence in NSW. Parametric models were fitted to incidence and survival data, and the modelled incidence and survival estimates were then used to estimate current and future prevalence. To estimate future healthcare requirements the projected prevalence was then divided into phases of care according to the different stages of the survivorship trajectory. RESULTS: The number of women in NSW living with a breast cancer diagnosis had increased from 19,305 in 1990 to 48,754 in 2007. This number is projected to increase further to 68,620 by 2017. The majority of these breast cancer survivors will require continued monitoring (31,974) or will be long-term survivors (29,785). About 9% will require active treatment (either initial therapy, or treatment for subsequent metastases or second cancer) and 1% will need end of life care due to breast cancer. CONCLUSIONS: Extrapolating these projections to the national Australian population would equate to 209,200 women living with breast cancer in Australia in 2017, many of whom will require active treatment or post-treatment monitoring. Thus, careful planning and development of a healthcare system able to respond to this increased demand is required.

Projections of cancer prevalence by phase of care: a potential tool for planning future health service needs.

PURPOSE: The objective of this study is to describe a method for estimating the number of cancer survivors requiring different types of cancer care in the future. METHODS: Colon cancer data (1972-2007) from the New South Wales (NSW) Central Cancer Registry were used to estimate prevalence in 2008-2017, which was then divided into five phases of care (initial, post-treatment monitoring, treatment for recurrence and second colon cancer, long-term survivors and last year of life). Patterns of care study data were used to calculate the type and number of treatments required by patients in initial care. RESULTS: There were 17,375 patients living in NSW who had a past diagnosis of first primary colon cancer in 2007. Our statistical model suggests that by 2017, this number will have increased to 22,671. At least 2,430 patients are expected to require initial surgery for colon cancer in 2017, and of these, 753 will also require adjuvant chemotherapy. Furthermore, an additional 538 cases will require therapy due to cancer recurrence (307) or a second primary colon cancer (231). CONCLUSION: Our proposed method provides more complete estimates of future cancer care needs. With some modifications, this method can be used to estimate the future prevalence of many major cancer types in many other jurisdictions. IMPLICATIONS FOR CANCER SURVIVORS: Our proposed method can be a useful tool for planning future cancer care with the goal of improving the cancer survivorship experience for survivors, their caregivers and their families.

Socioeconomic disparities in breast cancer survival: relation to stage at diagnosis, treatment and race.

BACKGROUND: Previous studies have documented lower breast cancer survival among women with lower socioeconomic status (SES) in the United States. In this study, I examined the extent to which socioeconomic disparity in breast cancer survival was explained by stage at diagnosis, treatment, race and rural/urban residence using the Surveillance, Epidemiology, and End Results (SEER) data. METHODS: Women diagnosed with breast cancer during 1998-2002 in the 13 SEER cancer registry areas were followed-up to the end of 2005. The association between an area-based measure of SES and cause-specific five-year survival was estimated using Cox regression models. Six models were used to assess the extent to which SES differences in survival were explained by clinical and demographical factors. The base model estimated the hazard ratio (HR) by SES only and then additional adjustments were made sequentially for: 1) age and year of diagnosis; 2) stage at diagnosis; 3) first course treatment; 4) race; and 5) rural/urban residence. RESULTS: An inverse association was found between SES and risk of dying from breast cancer (p < 0.0001). As area-level SES falls, HR rises (1.00 --> 1.05 --> 1.23 --> 1.31) with the two lowest SES groups having statistically higher HRs. This SES differential completely disappeared after full adjustment for clinical and demographical factors (p = 0.20). CONCLUSION: Stage at diagnosis, first course treatment and race explained most of the socioeconomic disparity in breast cancer survival. Targeted interventions to increase breast cancer screening and treatment coverage in patients with lower SES could reduce much of socioeconomic disparity.

Assessing the impact of socio-economic status on cancer survival in New South Wales, Australia 1996-2001.

OBJECTIVE: To assess the impact of socio-economic status (SES) on cancer survival in the state of New South Wales (NSW), Australia. METHODS: Patients diagnosed with one of 13 major cancers during 1992-2000 in NSW were followed-up to the end of 2001. The effect of SES on survival was estimated for each individual cancer and all 13 cancers combined using multivariable modeling. The numbers of lives that could be extended if all people had the same level of excess risk of death due to cancer as patients in the highest SES areas were also estimated. RESULTS: There were highly statistically significant variations in survival across SES groups for four cancers: stomach, liver, lung, and breast and all 13 cancers combined. Variation remained highly significant after adjusting for disease stage. Patients in lower SES areas had 10-20% higher excess risk than those in the highest SES areas. In total, there were 3,346 lives potentially extendable beyond 5 years; the highest number was for lung cancer (756). CONCLUSION: The significantly worse survival in lower SES areas from cancers of the stomach, liver, lung, and breast may be due to poorer access to high-quality cancer care. Estimates of the number of lives potentially extendable by improving cancer survival in lower SES areas suggest that priority should be given to improving lung cancer care in lower SES areas in NSW, Australia.