The contribution of melanocortin-1 receptor (MC1R) gene variants to the development of early-onset melanoma is unknown. Using an Australian population-based, case-control-family study, we sequenced MC1R for 565 cases with invasive cutaneous melanoma diagnosed between ages 18–39 years, 409 unrelated controls and 518 sibling controls. Variants were classified a priori into `R' variants (D84E, R142H, R151C, I155T, R160W, D294H) and `r' variants (all other nonsynonymous variants). We estimated odds ratios (OR) for melanoma using unconditional (unrelated controls) and conditional (sibling controls) logistic regression. The prevalence of having at least one R or r variant was 86% for cases, 73% for unrelated controls and 81% for sibling controls. R151C conferred the highest risk (per allele OR 2.57, 95% confidence interval 1.86–3.56 for the case-unrelated-control analysis and 1.70 (1.12–2.60) for the case-sibling-control analysis). When mutually adjusted, the ORs per R allele were 2.23 (1.77–2.80) and 2.06 (1.47–2.88), respectively from the two types of analysis, and the ORs per r allele were 1.69 (1.33–2.13) and 1.25 (0.88–1.79), respectively. The associations were stronger for men and those with none or few nevi or with high childhood sun exposure. Adjustment for phenotype, nevi and sun exposure attenuated the overall log OR for R variants by approximately 18%, but had lesser influence on r variant risk estimates. MC1R variants explained about 21% of the familial aggregation of melanoma. Some MC1R variants are important determinants of early-onset melanoma. The strength of association with melanoma differs according to the type and number of variants.
MC1R; melanoma; early-onset; phenotype; nevi; sun exposure
The ability of medical practitioners to communicate risk estimates effectively to patients diagnosed with melanoma relies on accurate information about prognostic factors and their impact on survival. This study reports the development of one of the few melanoma prognostic models, called the Melanoma Severity Index (MSI), based on population-based cancer registry data.
Data from the Queensland Cancer Registry for people (20–89 years) diagnosed with a single invasive melanoma between 1995 and 2008 (n = 28,654; 1,700 melanoma deaths). Additional clinical information about metastasis, ulceration and positive lymph nodes was manually extracted from pathology forms. Flexible parametric survival models were combined with multivariable fractional polynomial for selecting variables and transformations of continuous variables. Multiple imputation was used for missing covariate values.
The MSI contained the variables thickness (transformed, explained 40.6% of variation in survival), body site (additional 1.9% in variation), metastasis (1.8%), positive nodes (0.7%), ulceration (1.3%), age (1.1%). Royston and Sauerbrei’s D statistic (measure of discrimination) was 1.50 (95% CI = 1.44, 1.56) and the corresponding RD2 (measure of explained variation) was 0.47 (0.45, 0.49), demonstrating strong explanatory performance. The Harrell-C statistic was 0.88 (0.88, 0.89). Lacking an external validation dataset, we applied internal-external cross validation to demonstrate the consistency of the prognostic information across geographically-defined subsets of the cohort.
The MSI provides good ability to predict survival for melanoma patients. Beyond the immediate clinical use, the MSI may have important public health and research applications for evaluations of public health interventions aimed at reducing deaths from melanoma.
Melanoma; Survival; Prognostic model; Thickness; Population-based; Risk
Multilevel and spatial models are being increasingly used to obtain substantive information on area-level inequalities in cancer survival. Multilevel models assume independent geographical areas, whereas spatial models explicitly incorporate geographical correlation, often via a conditional autoregressive prior. However the relative merits of these methods for large population-based studies have not been explored. Using a case-study approach, we report on the implications of using multilevel and spatial survival models to study geographical inequalities in all-cause survival.
Multilevel discrete-time and Bayesian spatial survival models were used to study geographical inequalities in all-cause survival for a population-based colorectal cancer cohort of 22,727 cases aged 20–84 years diagnosed during 1997–2007 from Queensland, Australia.
Both approaches were viable on this large dataset, and produced similar estimates of the fixed effects. After adding area-level covariates, the between-area variability in survival using multilevel discrete-time models was no longer significant. Spatial inequalities in survival were also markedly reduced after adjusting for aggregated area-level covariates. Only the multilevel approach however, provided an estimation of the contribution of geographical variation to the total variation in survival between individual patients.
With little difference observed between the two approaches in the estimation of fixed effects, multilevel models should be favored if there is a clear hierarchical data structure and measuring the independent impact of individual- and area-level effects on survival differences is of primary interest. Bayesian spatial analyses may be preferred if spatial correlation between areas is important and if the priority is to assess small-area variations in survival and map spatial patterns. Both approaches can be readily fitted to geographically enabled survival data from international settings.
Electronic supplementary material
The online version of this article (doi:10.1186/1476-072X-13-36) contains supplementary material, which is available to authorized users.
Bayesian; Multilevel; Colorectal cancer; Epidemiology; All-cause survival; Spatial
To explore the impact of geographical remoteness and area-level socioeconomic disadvantage on colorectal cancer (CRC) survival.
Multilevel logistic regression and Markov chain Monte Carlo simulations were used to analyze geographical variations in five-year all-cause and CRC-specific survival across 478 regions in Queensland Australia for 22,727 CRC cases aged 20–84 years diagnosed from 1997–2007.
Area-level disadvantage and geographic remoteness were independently associated with CRC survival. After full multivariate adjustment (both levels), patients from remote (odds Ratio [OR]: 1.24, 95%CrI: 1.07-1.42) and more disadvantaged quintiles (OR = 1.12, 1.15, 1.20, 1.23 for Quintiles 4, 3, 2 and 1 respectively) had lower CRC-specific survival than major cities and least disadvantaged areas. Similar associations were found for all-cause survival. Area disadvantage accounted for a substantial amount of the all-cause variation between areas.
We have demonstrated that the area-level inequalities in survival of colorectal cancer patients cannot be explained by the measured individual-level characteristics of the patients or their cancer and remain after adjusting for cancer stage. Further research is urgently needed to clarify the factors that underlie the survival differences, including the importance of geographical differences in clinical management of CRC.
Colorectal cancer; Epidemiology; Survival; Inequalities; Multilevel
Melanocortin-1 receptor (MC1R) gene variants are very common and are associated with melanoma risk, but their contribution to melanoma risk prediction compared with traditional risk factors is unknown. We aimed to 1) evaluate the separate and incremental contribution of MC1R genotype to prediction of early-onset melanoma, and compare this with the contributions of physician-measured and self-reported traditional risk factors, and 2) develop risk prediction models that include MC1R, and externally validate these models using an independent dataset from a genetically similar melanoma population.
Using data from an Australian population-based, case-control-family study, we included 413 case and 263 control participants with sequenced MC1R genotype, clinical skin examination and detailed questionnaire. We used unconditional logistic regression to estimate predicted probabilities of melanoma. Results were externally validated using data from a similar study in England.
When added to a base multivariate model containing only demographic factors, MC1R genotype improved the area under the receiver operating characteristic curve (AUC) by 6% (from 0.67 to 0.73; P < 0.001) and improved the quartile classification by a net 26% of participants. In a more extensive multivariate model, the factors that contributed significantly to the AUC were MC1R genotype, number of nevi and previous non-melanoma skin cancer; the AUC was 0.78 (95% CI 0.75-0.82) for the model with self-reported nevi and 0.83 (95% CI 0.80-0.86) for the model with physician-counted nevi. Factors that did not further contribute were sun and sunbed exposure and pigmentation characteristics. Adding MC1R to a model containing pigmentation characteristics and other self-reported risk factors increased the AUC by 2.1% (P = 0.01) and improved the quartile classification by a net 10% (95% CI 1-18%, P = 0.03).
Although MC1R genotype is strongly associated with skin and hair phenotype, it was a better predictor of early-onset melanoma than was pigmentation characteristics. Physician-measured nevi and previous non-melanoma skin cancer were also strong predictors. There might be modest benefit to measuring MC1R genotype for risk prediction even if information about traditional self-reported or clinically measured pigmentation characteristics and nevi is already available.
MC1R; Risk prediction; Accuracy; Melanoma; Sun exposure; Early-onset; Pigmentation; Nevi
Cutaneous malignant melanoma (CMM) is a major health issue in Queensland, Australia which has the world’s highest incidence. Recent molecular and epidemiologic studies suggest that CMM arises through multiple etiological pathways involving gene-environment interactions. Understanding the potential mechanisms leading to CMM requires larger studies than those previously conducted. This article describes the design and baseline characteristics of Q-MEGA, the Queensland study of Melanoma: Environmental and Genetic Associations, which followed-up four population-based samples of CMM patients in Queensland, including children, adolescents, men aged over 50, and a large sample of adult cases and their families, including twins. Q-MEGA aims to investigate the roles of genetic and environmental factors, and their interaction, in the etiology of melanoma. 3,471 participants took part in the follow-up study and were administered a computer-assisted telephone interview in 2002–2005. Updated data on environmental and phenotypic risk factors, and 2,777 blood samples were collected from interviewed participants as well as a subset of relatives. This study provides a large and well-described population-based sample of CMM cases with follow-up data. Characteristics of the cases and repeatability of sun exposure and phenotype measures between the baseline and the follow-up surveys, from six to 17 years later, are also described.
This pilot study aimed to test the acceptability and short-term effectiveness of a telephone-delivered multiple health behaviour change intervention for relatives of colorectal cancer survivors.
A community-based sample of 22 first-degree relatives of colorectal cancer survivors were recruited via a media release. Data were collected at baseline and at six weeks (post-intervention). Outcome measures included health behaviours (physical activity, television viewing, diet, alcohol, body mass index, waist circumference and smoking), health-related quality of life (Short Form-36) and perceived colorectal cancer risk. Intervention satisfaction levels were also measured. The intervention included six telephone health coaching sessions, a participant handbook and a pedometer. It focused on behavioural risk factors for colorectal cancer [physical activity, diet (red and processed meat consumption, fruit and vegetable intake), alcohol, weight management and smoking], and colorectal cancer risk.
From baseline to six weeks, improvements were observed for minutes moderate-vigorous physical activity (150.7 minutes), processed meat intake (−1.2 serves/week), vegetable intake (1 serve/day), alcohol intake (−0.4 standard drinks/day), body mass index (−1.4 kg/m2), and waist circumference (−5.1 cm). Improvements were also observed for physical (3.3) and mental (4.4) health-related quality of life. Further, compared with baseline, participants were more likely to meet Australian recommendations post-intervention for: moderate-vigorous physical activity (27.3 vs 59.1%); fruit intake (68.2 vs 81.8%); vegetable intake (4.6 vs 18.2%); alcohol consumption (59.1 vs 72.7%); body mass index (31.8 vs 45.5%) and waist circumference (18.2 vs 27.3%). At six weeks participants were more likely to believe a diagnosis of CRC was related to family history, and there was a decrease in their perceived risk of developing CRC in their lifetime following participation in CanPrevent. The intervention retention rate was 100%, participants reported that it was highly acceptable and they would recommend it to others at risk of colorectal cancer.
Positive behaviour change achieved through this intervention approach has the potential to impact on the progression of CRC and other cancers or chronic diseases. A large scale randomised controlled trial is required to confirm the positive results of this acceptability and short-term effectiveness study.
Colorectal cancer; Multiple health behaviour change intervention; Lifestyle; Physical activity; Telephone; Prevention; Family history
The Kallikrein-related peptidase, KLK4, has been shown to be significantly overexpressed in prostate tumours in numerous studies and is suggested to be a potential biomarker for prostate cancer. KLK4 may also play a role in prostate cancer progression through its involvement in epithelial-mesenchymal transition, a more aggressive phenotype, and metastases to bone. It is well known that genetic variation has the potential to affect gene expression and/or various protein characteristics and hence we sought to investigate the possible role of single nucleotide polymorphisms (SNPs) in the KLK4 gene in prostate cancer. Assessment of 61 SNPs in the KLK4 locus (±10 kb) in approximately 1300 prostate cancer cases and 1300 male controls for associations with prostate cancer risk and/or prostate tumour aggressiveness (Gleason score <7 versus ≥7) revealed 7 SNPs to be associated with a decreased risk of prostate cancer at the Ptrend<0.05 significance level. Three of these SNPs, rs268923, rs56112930 and the HapMap tagSNP rs7248321, are located several kb upstream of KLK4; rs1654551 encodes a non-synonymous serine to alanine substitution at position 22 of the long isoform of the KLK4 protein, and the remaining 3 risk-associated SNPs, rs1701927, rs1090649 and rs806019, are located downstream of KLK4 and are in high linkage disequilibrium with each other (r2≥0.98). Our findings provide suggestive evidence of a role for genetic variation in the KLK4 locus in prostate cancer predisposition.
Sunbed use is associated with increased risk of melanoma. Younger people might be more susceptible to the carcinogenic effects of ultraviolet radiation. We investigated the association between sunbed use and risk of early-onset cutaneous malignant melanoma. From the Australian Melanoma Family Study, a multi-centre, population-based, case-control-family study, we analysed data for 604 cases diagnosed between ages 18 and 39 years and 479 controls. Data were collected by interview. Associations were estimated as odds ratios (ORs) using unconditional logistic regression, adjusting for age, sex, city, education, family history, skin colour, usual skin response to sunlight, and sun exposure. Compared with having never used a sunbed, the OR for melanoma associated with ever-use was 1.41 (95% confidence interval (CI) 1.01-1.96), and 2.01 (95% CI 1.22-3.31) for more than 10 lifetime sessions (Ptrend 0.01 with cumulative use). The association was stronger for earlier age at first use (Ptrend 0.02). The association was also stronger for melanoma diagnosed when aged 18-29 years (OR for more than 10 lifetime sessions = 6.57, 95% CI 1.41-30.49) than for melanoma diagnosed when 30-39 years (OR 1.60, 95% CI 0.92-2.77; Pinteraction 0.01). Among those who had ever used a sunbed and were diagnosed between 18-29 years of age, three quarters (76%) of melanomas were attributable to sunbed use. Sunbed use is associated with increased risk of early-onset melanoma, with risk increasing with greater use, an earlier age at first use and for earlier onset disease.
sunbed; artificial tanning; melanoma; risk factor; early-onset
We report a genome-wide association study of melanoma, conducted by GenoMEL, of 2,981 cases, of European ancestry, and 1,982 study-specific controls, plus a further 6,426 French and UK population controls, all genotyped for 317,000 or 610,000 SNPs. The analysis confirmed previously known melanoma susceptibility loci. The 7 novel regions with at least one SNP with p<10−5 and further local imputed or genotyped support were selected for replication using two other genome-wide studies (from Australia and Houston, Texas). Additional replication came from UK and Dutch case-control series. Three of the 7 regions replicated at p<10−3: an ATM missense polymorphism (rs1801516, overall p=3.4×10−9); a polymorphism within MX2 (rs45430, p=2.9×10−9) and a SNP adjacent to CASP8 (rs13016963, p=8.6×10−10). A fourth region near CCND1 remains of potential interest, showing suggestive but inconclusive evidence of replication. Unlike the previously known regions, the novel loci showed no association with nevus or pigmentation phenotypes in a large UK case-control series.
So far, two familial melanoma genes have been identified, accounting for a minority of genetic risk in families. Mutations in CDKN2A account for approximately 40% of familial cases1, and predisposing mutations in CDK4 have been reported in a very small number of melanoma kindreds2. To identify other familial melanoma genes, here we conducted whole-genome sequencing of probands from several melanoma families, identifying one individual carrying a novel germline variant (coding DNA sequence c.G1075A; protein sequence p.E318K; rs149617956) in the melanoma-lineage-specific oncogene microphthalmia-associated transcription factor (MITF). Although the variant co-segregated with melanoma in some but not all cases in the family, linkage analysis of 31 families subsequently identified to carry the variant generated a log odds ratio (lod) score of 2.7 under a dominant model, indicating E318K as a possible intermediate risk variant. Consistent with this, the E318K variant was significantly associated with melanoma in a large Australian case–control sample. Likewise, it was similarly associated in an independent case–control sample from the United Kingdom. In the Australian sample, the variant allele was significantly over-represented in cases with a family history of melanoma, multiple primary melanomas, or both. The variant allele was also associated with increased naevus count and non-blue eye colour. Functional analysis of E318K showed that MITF encoded by the variant allele had impaired sumoylation and differentially regulated several MITF targets. These data indicate that MITF is a melanoma-predisposition gene and highlight the utility of whole-genome sequencing to identify novel rare variants associated with disease susceptibility.
In Australia, breast cancer is the most common cancer affecting Australian women. Inequalities in clinical and psychosocial outcomes have existed for some time, affecting particularly women from rural areas and from areas of disadvantage. We have a limited understanding of how individual and area-level factors are related to each other, and their associations with survival and other clinical and psychosocial outcomes.
This study will examine associations between breast cancer recurrence, survival and psychosocial outcomes (e.g. distress, unmet supportive care needs, quality of life). The study will use an innovative multilevel approach using area-level factors simultaneously with detailed individual-level factors to assess the relative importance of remoteness, socioeconomic and demographic factors, diagnostic and treatment pathways and processes, and supportive care utilization to clinical and psychosocial outcomes. The study will use telephone and self-administered questionnaires to collect individual-level data from approximately 3, 300 women ascertained from the Queensland Cancer Registry diagnosed with invasive breast cancer residing in 478 Statistical Local Areas Queensland in 2011 and 2012. Area-level data will be sourced from the Australian Bureau of Statistics census data. Geo-coding and spatial technology will be used to calculate road travel distances from patients' residence to diagnostic and treatment centres. Data analysis will include a combination of standard empirical procedures and multilevel modelling.
The study will address the critical question of: what are the individual- or area-level factors associated with inequalities in outcomes from breast cancer? The findings will provide health care providers and policy makers with targeted information to improve the management of women with breast cancer, and inform the development of strategies to improve psychosocial care for women with breast cancer.
While risk factors for primary cutaneous melanoma are well defined, relatively little is known about predictors for second primary melanoma. Given the rising incidence of this cancer, coupled with improvements in survival, there is a prevalent and growing pool of patients at risk of second primary melanomas. To identify the predictors of second primary melanoma, we followed a cohort of 1083 Queensland patients diagnosed with incident melanoma between 1982-90 and who completed a baseline questionnaire. During a median follow-up of 16.5 years, 221 patients were diagnosed with at least one additional primary melanoma. In multivariate analyses, second primary melanomas were associated with high nevus count (HR 2,91, 95%CI 1,94 - 4.35), high familial melanoma risk (2.12, 1.34-3.36), fair skin (1.51, 1.06-2.16, inability to tan (1.66, 1.13-2.43), an in situ first primary melanoma (1.36, 0.99-1.87) and masculine sex (1.49, 1.12-2.00) Patients whose first primary was lentigo maligna melanoma (1.80, 1.05-3.07) or nodular melanoma (2.13 , 1.21-3.74) had higher risks of subsequent primaries than patients whose first primary tumor was superficial spreading melanoma. These characteristics could be assessed in patients presenting with first primary melanoma to assess their risk of developing a second primary.
Discovering and understanding genetic risk factors for melanoma and their interactions with phenotype, sun exposure, and other risk factors could lead to new strategies for melanoma control. This paper describes the Australian Melanoma Family Study, which uses a multicenter, population-based, case-control-family design. From 2001 to 2005, the authors recruited 1,164 probands including 629 cases with histopathologically confirmed, first-primary cutaneous melanoma diagnosed before age 40 years, 240 population-based controls frequency matched for age, and 295 spouse/friend controls. Information on lifetime sun exposure, phenotype, and residence history was collected for probands and nearly 4,000 living relatives. More than 3,000 subjects donated a blood sample. Proxy-reported information was collected for childhood sun exposure and deceased relatives. Important features of this study include the population-based, family-based design; a focus on early onset disease; probands from 3 major cities differing substantially in solar ultraviolet exposure and melanoma incidence; a population at high risk because of high ultraviolet exposure and susceptible pigmentation phenotypes; population-based, spouse/friend, and sibling controls; systematic recruitment of relatives of case and control probands; self and parent reports of childhood sun exposure; and objective clinical skin examinations. The authors discuss methodological and analytical issues related to the study design and conduct, as well as the potentially novel insights the study can deliver.
case-control studies; environmental exposure; family; genetic predisposition to disease; melanoma; risk factors
Patterns of diagnosis and management for men diagnosed with prostate cancer in Queensland, Australia, have not yet been systematically documented and so assumptions of equity are untested. This longitudinal study investigates the association between prostate cancer diagnostic and treatment outcomes and key area-level characteristics and individual-level demographic, clinical and psychosocial factors.
A total of 1064 men diagnosed with prostate cancer between February 2005 and July 2007 were recruited through hospital-based urology outpatient clinics and private practices in the centres of Brisbane, Townsville and Mackay (82% of those referred). Additional clinical and diagnostic information for all 6609 men diagnosed with prostate cancer in Queensland during the study period was obtained via the population-based Queensland Cancer Registry.
Respondent data are collected using telephone and self-administered questionnaires at pre-treatment and at 2 months, 6 months, 12 months, 24 months, 36 months, 48 months and 60 months post-treatment. Assessments include demographics, medical history, patterns of care, disease and treatment characteristics together with outcomes associated with prostate cancer, as well as information about quality of life and psychological adjustment. Complementary detailed treatment information is abstracted from participants' medical records held in hospitals and private treatment facilities and collated with health service utilisation data obtained from Medicare Australia. Information about the characteristics of geographical areas is being obtained from data custodians such as the Australian Bureau of Statistics. Geo-coding and spatial technology will be used to calculate road travel distances from patients' residences to treatment centres. Analyses will be conducted using standard statistical methods along with multilevel regression models including individual and area-level components.
Information about the diagnostic and treatment patterns of men diagnosed with prostate cancer is crucial for rational planning and development of health delivery and supportive care services to ensure equitable access to health services, regardless of geographical location and individual characteristics.
This study is a secondary outcome of the randomised controlled trial registered with the Australian New Zealand Clinical Trials Registry (ACTRN12607000233426)
We report a genome-wide association study of melanoma conducted by the GenoMEL consortium based on 317k tagging SNPs for 1650 genetically-enriched cases (from Europe and Australia) and 4336 controls and subsequent replication in 1149 genetically-enriched cases and 964 controls and a population-based case-control study of 1163 cases and 903 controls. The genome-wide screen identified five regions with genotyped or imputed SNPs reaching p < 5×10−7; three regions were replicated: 16q24 encompassing MC1R (overall p=2.54×10−27 for rs258322), 11q14-q21 encompassing TYR (p=2.41×10−14 for rs1393350) and 9p21 adjacent to MTAP and flanking CDKN2A (p=4.03×10−7 for rs7023329). MC1R and TYR are associated with pigmentation, freckling and cutaneous sun sensitivity, well-recognised melanoma risk factors, while the 9p21 locus is novel for common variants associated with melanoma. Despite wide variation in allele frequency, these genetic variants show notable homogeneity of effect across populations of European ancestry living at different latitudes and contribute independently to melanoma risk.
In Australia, associations between geographic remoteness, socioeconomic disadvantage, and colorectal cancer (CRC) survival show that survival rates are lowest among residents of geographically remote regions and those living in disadvantaged areas. At present we know very little about the reasons for these inequalities, hence our capacity to intervene to reduce the inequalities is limited.
This study, the first of its type in Australia, examines the association between CRC survival and key area- and individual-level factors. Specifically, we will use a multilevel framework to investigate the possible determinants of area- and individual-level inequalities in CRC survival and quantify the relative contribution of geographic remoteness, socioeconomic and demographic factors, disease stage, and access to diagnostic and treatment services, to these inequalities. The multilevel analysis will be based on survival data relating to people diagnosed with CRC in Queensland between 1996 and 2005 (n = 22,723) from the Queensland Cancer Registry (QCR), area-level data from other data custodians such as the Australian Bureau of Statistics, and individual-level data from the QCR (including extracting stage from pathology records) and Queensland Hospitals. For a subset of this period (2003 and 2004) we will utilise more detailed, individual-level data (n = 1,966) covering a greater range of risk factors from a concurrent research study. Geo-coding and spatial technology will be used to calculate road travel distances from patients' residence to treatment centres. The analyses will be conducted using a multilevel Cox proportional hazards model with Level 1 comprising individual-level factors (e.g. occupation) and level 2 area-level indicators of remoteness and area socioeconomic disadvantage.
This study focuses on the health inequalities for rural and disadvantaged populations that have often been documented but poorly understood, hence limiting our capacity to intervene. This study utilises and develops emerging statistical and spatial technologies that can then be applied to other cancers and health outcomes. The findings of this study will have direct implications for the targeting and resourcing of cancer control programs designed to reduce the burden of colorectal cancer, and for the provision of diagnostic and treatment services.
We conducted a genome-wide association pooling study for cutaneous melanoma and performed validation in samples totalling 2019 cases and 2105 controls. Using pooling we identified a novel melanoma risk locus on chromosome 20 (rs910873, rs1885120), with replication in two further samples (combined P <1 × 10-15). The odds ratio is 1.75 (1.53, 2.01), with evidence for stronger association in early onset cases.
Colorectal cancer survivors may suffer from a range of ongoing psychosocial and physical problems that negatively impact on quality of life. This paper presents the study protocol for a novel telephone-delivered intervention to improve lifestyle factors and health outcomes for colorectal cancer survivors.
Approximately 350 recently diagnosed colorectal cancer survivors will be recruited through the Queensland Cancer Registry and randomised to the intervention or control condition. The intervention focuses on symptom management, lifestyle and psychosocial support to assist participants to make improvements in lifestyle factors (physical activity, healthy diet, weight management, and smoking cessation) and health outcomes. Participants will receive up to 11 telephone-delivered sessions over a 6 month period from a qualified health professional or 'health coach'. Data collection will occur at baseline (Time 1), post-intervention or six months follow-up (Time 2), and at 12 months follow-up for longer term effects (Time 3). Primary outcome measures will include physical activity, cancer-related fatigue and quality of life. A cost-effective analysis of the costs and outcomes for survivors in the intervention and control conditions will be conducted from the perspective of health care costs to the government.
The study will provide valuable information about an innovative intervention to improve lifestyle factors and health outcomes for colorectal cancer survivors.
Cutaneous melanoma is a relatively common cancer in adolescents and young adults in Australia, but detailed information about occurrence patterns and prognosis is limited. We evaluated incidence trends from 1982 to 2010 and recent survival rates in those aged 15–24 years in the state of Queensland. In situ and invasive melanoma cases were identified from the Queensland Cancer Registry. Incidence rates were age-standardised to the 2000 World population and trends calculated using joinpoint regression. Five-year relative survival was estimated by the period method and Poisson models were used to produce adjusted mortality hazard ratios. Average annual incidence rates for the 5-year period 2006–2010 were 6.3 per 100,000 [95% confidence interval (CI) 5.4, 7.2] for in situ and 10.1 per 100,000 (95% CI 9.0, 11.3) for invasive melanoma. Since the mid-1990s, incidence rates for in situ melanomas have been stabilizing while invasive melanoma has decreased in both sexes, mainly owing to declining rates of thin tumours (≤1 mm) (−5.4% per year, 95% CI −8.3%, −2.4%). Incidence rates of melanomas >1 mm in thickness have remained relatively unchanged since 1991 however. In the period 2006–2010, relative 5-year survival of 15–24 year olds with invasive melanoma was 95.7% (95% CI 92.9%, 97.5%). The subgroup with tumours >1 mm was nearly six times more likely to die within 5 years than those with thin tumours (adjusted hazard ratio = 5.53, 95% CI 1.72, 17.80). Incidence of thin melanoma in young people in Queensland is declining, suggesting benefits of primary prevention efforts are being realised.
Although some of the highest known incidence rates ofcutaneous melanoma are found in Queensland, Australia, few studies have examined incidence specifically among 15- to 24-year-olds in the state. This evaluation shows that the incidence of invasive melanoma is relatively high for the 15- to 24-year-old age group. However, incidence rates were found to have declined generally among Queensland's adolescents and young adults since the mid- to late 1990s. The decline may be a reflection of successful primary prevention efforts in young people in recent decades.
melanoma; incidence trends; survival rates; adolescents; young adults